This paper contributes by developing new models for assessing dynamic inefficiency that incorporate machine learning techniques. In particular, the new approaches apply decision trees models for the estimation of dynamic production technologies that account for investment adjustment costs. Methodologically, the new models build on the recently developed techniques of Efficiency Analysis Trees (EAT) and Convexified Efficiency Analysis Trees (CEAT) and extend them even further to a dynamic framework comprising dynamic EAT and CEAT models. The study compares dynamic inefficiency scores estimated assuming the new models against the traditional dynamic free disposal hull (FDH) and dynamic data envelopment analysis (DEA). Our empirical application focuses on dairy manufacturing firms in the main dairy processing countries in the European Union for the years 2014 and 2018. The results show that inefficiency related to the dynamic CEAT or EAT is higher than their corresponding values calculated through the dynamic DEA or FDH. The discriminating power of dynamic DEA (dynamic FDH) drastically improves when switching to dynamic CEAT (dynamic EAT). Finally, the differences between countries are observed regarding the development of dynamic inefficiency in the period associated with milk quota abolition.

This paper attempts to study the effectiveness of the ‘lockdown’ on the positive case prevalence and fatality due to COVID-19 during 13 weeks’ period starting from 11th of March 2020, which marks the declaration of the pandemic by WHO. Based on a sample of 60 countries, a cross-country panel regression with country fixed effects and Generalized Method of Moments are utilized to study the same. The paper identifies that the lockdown by its own results in a decline in the number of cases by 0.2%, whereas it causes an increase in the fatality rate by 0.005 points, however these results are statistically insignificant. On further analysis, it can be seen that when the lockdown is implemented with clinical measures such as mass testing, the impact of such interacting effect of ‘lockdown and testing’ is statistically significant, making the lockdown beneficial. We identify that given the presence of a lockdown, increasing testing capacity by one unit brings down the case prevalence by 2 percent and the fatality rate by 1.12 points. This study contributes to the literature of studying the effect of lockdown at a cross country level and understanding the impact of both, non-clinical and clinical measures.

This paper introduces a novel regression model that combines two important areas of the methodological development in panel data analysis, namely the varying coefficient specification and spatial error dependence. While the former is shown to allow flexible nonlinear interactions, the latter enables spatial correlations of the disturbance that differs significantly from other random effect models in the literature. To estimate the model, a new estimation procedure is established that can be viewed as a generalization of the quasi-maximum likelihood method for a spatial panel data model to the conditional local likelihood procedure. The main theoretical results of this paper are the uniform consistency of the quasi maximum likelihood estimators involved, which are established based on a set of primitive conditions often used in the semi- and nonparametric literature. Various novel inference methods, particularly variable selection and hypothesis testing of parameter constancy, are accordingly introduced and shown to be effective under complex spatial error dependence. To illustrate their empirical validity and relevance, extensive simulation exercises are performed, while these procedures are also applied to analyze municipal disparities in mental health service spending by the local councils in England.

Conditional cash transfers (CCT) prominently designed to eradicate poverty through human capital enhancement. Yet, there is still limited evidence on the sustainability of program’s impact that leads to human capital accumulation. Using Difference-in-Differences (DID), we aim to examine the impact of CCT on beneficiaries’ expenditure and aspiration based on the program graduation status. We use the large-scale experimental data of CCT in Indonesia, which is called Program Keluarga Harapan (PKH), in 2007 and 2013. We find that household total expenditure per capita and food expenditure per capita are significantly higher for the beneficiaries who stopped receiving PKH. However, those beneficiaries have lower expenditure for health and education per capita. This evidence reflects that beneficiaries are no longer allocate more of their budget for health and education after they stop receiving PKH. Related to aspiration, we find that there is no significant difference of parents’ aspiration on their children further education after they stop receiving PKH. These findings suggest that the poor tend to have high aspiration on their children’s education, but they could not allocate more of their budget for education and health after the cessation of the program. Therefore, continuous assistance for the poor’s education and health is required.

The US government was front-runner in the employment of in-house bidding in public procurement tenders, known as A-76 competitions. In 2009, this type of competitions was prohibited due to a number of concerns, including uncertainty with regard to cost savings. We study a tender where an in-house unit competes with external private bidders. In equilibrium, the in-house bidder bids its true competitive cost, generating cost savings for the government (/buyer). Under a scenario of information revelation regarding the competing bids to the in-house bidder, the equilibrium strategy of the in-house bidder remains unchanged, and so this information does not translate into an advantage for the in-house bidder, or the buyer. Under a collusion scenario, the in-house bid serves as an upper bound to the collusive bid, lowering its value (reaching a bounded collusion effect).

Metafrontier analysis is widely used to account for technological heterogeneity among producers. The approach involves combining a number of group-specific production possibilities sets to form a production possibilities metaset. Even though the union of the group sets normally results in a nonconvex metaset, most authors proceed as if the metaset is convex. Kerstens, O’Donnell and Van de Woestyne (2019) obtain new results on the union operator on sets under various assumptions. They then use a production context to empirically illustrate that the popular convexification strategy is highly questionable. In this paper we transpose their results on the union operator from a production context to a cost context: this is new. We then explore the extent to which a convexification strategy is tenable when estimating a cost metafrontier. We use a secondary data set to illustrate the main issues. We establish that the convexification strategy leads to potentially-biased estimates of the cost metafrontier and associated measures of efficiency.

Considering that Brexit is a challenge for labour market, the aim of this paper is to assess the impact of this event on unemployment rate. The synthetic control method is applied for the period 1995-2022 under three types of donor pools: a sample that includes all the Old EU Member States, a similar sample that excludes Spain and Greece and a pool based only on the EU neighbours of the UK. The sample based only on the EU neighbours provides the most accurate results and indicates a lower, but non-significant unemployment in the absence of Brexit compared to the real situation. On the other hand, there is a long-run relationship from inflation and economic growth to unemployment in the period February: 2020-December: 2022, while inflation acts like a factor that reduces unemployment.

The finding of small price changes in many retail price datasets is usually interpreted as inconsistent with the simple menu cost model. We demonstrate that small price changes can be consistent with menu costs if we account for sales volume. Analyzing a large retail scanner price dataset that contains information on both prices and sales volume, we find that small price changes are more frequent when products’ sales volume is higher. This finding holds across product categories, within product categories, and for individual products. It is also robust to various sensitivity analyses such as measurement errors, the definition of small price changes, the inclusion of measures of price synchronization, the size of producers, the time horizon used to compute the average sales volume, etc. To explain the finding, we employ a simple menu cost model to show that there is an inverse relationship between sales volume and the width of the (S, s) band. That is, if sales volume is high, then small price changes will be more frequent.

Much of empirical macroeconomics is concerned with first constructing series of ‘shocks’ to estimate causal effects. In settings with confounding factors, these shocks are typically constructed by orthogonalising causal variables of interest, before being used in a second stage. For a general set of estimators, we show that this two-step ‘shock-first’ approach can be problematic relative to a simple one-step procedure, which includes confounding factors as control variables directly. When one- and two-step estimators share a common population estimand, there are practical drawbacks to the two-step approach: standard errors will typically be mis-estimated, resulting in unnecessarily more conservative inference. When the estimators differ in population, there is omitted-variable bias in the two-step approach. In linear regression, this bias can arise when additional controls are included in the second stage. For other estimators, such as quantile regression, estimating the shocks first can be especially problematic since uncorrelatedness with omitted variables is insufficient for removing bias. We demonstrate these findings in an application to monetary policy, controlling for central-bank information. One-step estimates indicate that the dis-inflationary consequences of tighter US monetary policy are more robust than previously realised and not subject to a ‘price puzzle’ at the mean.

Does political preference affect household inflation beliefs? We try to answer this question using new online survey data from South Korea. The survey was run between the presidential election in March 2022 and the presidential inauguration in May 2022, during which participants experienced a regime change. We find that (1) political bias affects both perceived inflation in the past year and inflation expectations but (2) self-reported financial literacy mitigates the bias.

What accounts for contrasting economic paths between core and periphery countries in the euro area? Unlike many studies focusing on fiscal problems, we highlight the interplay of bank mortgage lending standards and imbalances created by the common monetary policy framework. To illustrate the mechanism, we derive a country-specific monetary policy stance gap and estimate the panel VAR model of core and periphery countries, respectively. While the widening monetary policy stance gap-the accommodative stance of the ECB given individual economic conditions-induces a similar increase in the demand for mortgage credit in both regions, it is followed by sharply different responses of the supply side of mortgage credit: bank mortgage lending standards are relaxed (tightened) in periphery (core) countries, which can rationalize vastly different paths in mortgage credit, residential investment, and housing prices between the two Europes. In searching for the source of different bank lending behaviors, we find that banks in core countries, where macroprudential policies on mortgage credit are tightened and bank lending margin decreases, increase their cross-border lending to periphery countries, which could fuel excessive risk-taking in periphery countries.

Persistent international current account imbalances and real exchange rate movements have become a permanent feature of the world economy. This paper, therefore, sets out to investigate the relationship between the real exchange rate and current account dynamics of eleven African countries, using data from 1980 to 2013, based on a stochastic Mundell-Fleming model in which shocks to real exchange rates and current account have been identified as permanent and temporary. Using a bi-variate structural VAR approach, the results are in consonant with the theoretical model, with permanent shocks having permanent and positive effects on both the current account and the real exchange rates. On the other hand, while temporary shocks have insignificant effects on the real exchange rates, they have very different effects on the current accounts of different countries.

We study the distributional consequences of uncertainty shocks in the U.S. economy at a business cycle frequency. We document that the effects of uncertainty shocks are highly heterogeneous across income and wealth distribution and also vary depending on the sources of uncertainty. First, uncertainty shocks tend to have a more adverse effect on income at the top and bottom of the distribution spectrum resulting in narrower income inequality between the rich and the middle class but wider inequality between the middle class and the poor. Second, once the redistribution policy is considered, uncertainty shocks do reduce income inequality. Third, the distributional consequences for wealth differ from those for income, as uncertainty shocks are relatively beneficial to both the middle class and the poor. Fourth, the COVID-19 pandemic has brought different implications on wealth inequality between Wall Street and Main Street uncertainty; whereas the former reduces wealth inequality through its particularly adverse effect on risky asset prices, the latter uncertainty increases it by damaging the labor market.

We study the impact of local geopolitical risk on U.S. cross-border portfolio investment between April 1994 and November 2021, and find an important heterogeneity between advanced and emerging markets: local geopolitical risk reduces U.S. purchases of bonds and equities only in emerging markets but not in advanced markets. Poor institutional quality is identified as the main reason for the stronger sensitivity of portfolio investment to geopolitical risk in emerging markets, indicating a potential financial stability implication. We also observe that U.S. investment in emerging market bonds declines substantially in response to the geopolitical risk of other emerging markets in their geographical proximity, exhibiting a strong contagion effect. In contrast, we do not find a contagion effect on cross-border equity investment. Interestingly, such contagions exist only among emerging markets, shedding light on how investors adjust their portfolios in response to heightened geopolitical risk.

We investigate the effect of rising Chinese demand for agriculture goods between 1997 and 2012 on U.S. local agricultural sectors, exploiting cross-county variation in exposure to Chinese demand due to differences in crop/product specialization. We find that, farmland value rises in counties that are more exposed to the rise in Chinese demand. Meanwhile, rising exports causes an increase in farmland concentration. The benefits are unequally distributed across farmers: the income of wealthy farm owners rises, but the income of poorer farm owners and typical farm labour stagnates.

The present study seeks to understand the ex-ante (general equilibrium) and ex-post (gravity analysis) economy wide impacts of the RCEP agreement including assessment of trade diversion and trade creation for India and also the impact of reduction of tariff and non-tariff barriers, including deeper integration policies like increased physical and human capital flows on carbon emissions using GTAP-E on all members of the RCEP nations and India. We use structural gravity model to explain volume of trade among 15 RCEP nations and India and importantly predict India’s trade with the east Asian region after the formation and signing of the RCEP trade deal in 2019. The present paper further uses the general equilibrium model the GTAP – E (Environment and Energy) to analyse the gains and losses of India and the RCEP nations, among others, under two experimental simulation scenarios: the first in which India bilaterally liberalizes on one to one basis with the 15-RCEP nations and the second in which India becomes part of the comprehensive RCEP treaty. We further attempt analysing carbon emissions in the two experimental scenarios along with welfare and GDP gains/losses, among others. The results reveal that if we adopt comprehensive policies such as trade and capital liberalization, make concerted efforts to improve productivity of skilled labour, impose carbon taxation to address climate change and also adopt industrial policies to improve the productivity of the transport and communication sector, there would be relatively higher gains in terms of welfare (equivalent variation) and value of GDP growth for India in the first scenario as compared to the second simulations when India possibly becomes a part of RCEP in future. The second simulation results project gains for India in terms of reduction in carbon emissions and positive trade balance with the rest of the world.

As the largest soybean importing country, this study examines the overweight effects of the soybean import shock (Soybean Overweight Shock: SOS) on Chinese. Exploiting prefecture-level variations in the extensive soybean import liberalization in 1996, we found large and reasonable SOS effects: a one-standard-deviation reduction in prefecture-level import tariffs on soybeans is associated with a 2.6% increase in the probability of becoming overweight, with tariff reductions on soybeans accounting for an 8% increase in the overall prevalence of overweight across China after trade liberalization. In this way, exposure to a soybean import shock significantly reduces the market price for soybean oil, which consequently leads to an increase in people’s total caloric and fat intake. We also discovered that people who eat out are often exposed to greater SOS effects than those who primarily eat in at home, while those individuals who prefer the cooking methods adopted when preparing stir-fried and deep-fried foods were meanwhile also found to feature higher SOS effects.

This paper provides a novel look at capital flow determinants by assessing the role of expectations, uncertainty and media sentiments. Analyzing eight emerging economies, we assess the effects of macroeconomic expectations and disagreement among professionals and various media-based sentiment indicators based on high frequency news coverage. Our results show that survey and sentiment indicators which are available in real time contain useful information about capital flow dynamics which go beyond the effects of conventional push and pull factors for all countries we analyze. In line with theoretical considerations, good news about the domestic economy tends to increase capital flows.

Can ETFs improve stock market efficiency? While earlier studies confirm the impact of ETFs on their constituent stocks in terms of liquidity, volatility, and returns, the effect on the price discovery of component stocks remains a subject of debate. This paper takes an innovative approach and presents evidence that ETFs have a negative impact on market efficiency through noise trading. To achieve this, we integrate high-dimensional inference and financial network literature and construct a financial network using a high-dimensional vector autoregressive (VAR) model. Our methodology involves a two-step process that highlights significant spillover effects of ETFs on the idiosyncratic risk component of S&P 500 constituent stocks’ returns, after accounting for systematic risk factors. Our findings reveal that, with regards to non-fundamental shocks, all comprehensive cross-industry ETFs serve as net influencers. Furthermore, within each non-financial industry, industry-specific ETFs exert a greater influence than the average S&P 500 component stocks in their respective industries. Additionally, our results suggest that fluctuations in treasury yield can affect the degree of connectedness between ETFs and stocks. In particular, bond and total market ETFs become considerably more influential during periods of declining treasury yield. These observations provide valuable insights for policymakers and market participants alike.

We compare the networks of five well-known methods constructed from publicly available daily market data to networks of reported exposures along many dimensions of the balance sheet. We use granular confidential bank-level data to construct benchmark balance sheet networks of direct and common exposures in loans, bonds, equity, and fund shares. Our findings suggest that while the global network structure remains stable, individual exposures are more dynamic. Direct comparisons of the networks estimated with many methods suggest that all of the market-based networks are most closely related to indirect exposure networks. Further, bond exposures, both direct and indirect, are more reflected in the market-based measures than their corresponding loan exposures. Regression analysis shows that different market-based estimates capture different types of exposures. Networks constructed based on credit risk variables seem to reflect all types of interconnections, both direct and indirect. Networks based on simple returns capture mostly common factors.

The goal of this paper is to analyses the impacts of Geopolitical Risk (GPR) on Sectoral Credit Default Swap (SCDS) index of Europe and North America after the period of Russian-Ukraine conflict. For this purpose, we use symmetric and asymmetric the fractional frequency flexible Fourier form Toda-Yamamoto causality tests and use daily data between February 24, 2022 and April 17, 2023. Although there is no evidence of causal relation between variables by using the symmetric version of test, we obtain significant results by using its asymmetric version. Most important of these is that regardless of region, there are causality running from positive and negative geopolitical risk shocks to positive and negative shocks of all sectoral CDSs within the two days scale. Taking into account of this and other results of the study, we can recommend individual, institutional investors along with regulators and policy makers that they have to consider the asymmetric effects of geopolitical risk on their investment decisions and policy making process.

Aim of this paper is the study of the financial stress – macroeconomic fundamentals interrelations and the usefulness of financial stress as a leading indicator of macro-fundamentals. We construct a set of financial stress indices for 25 countries, both developed and developing. After assessing these indices ability to capture periods of macrofinancial instability, a forecasting exercise is conducted, where major macroeconomic variables are forecasted using the aforementioned early warning indicators. The out-of-sample forecasting evidence verifies the ability of these financial stress indices to act as valuable modern tools for assessing the vulnerability of a range of economies. We suggest that such aggregate financial risk capturing tools can be of great interest for policy makers, as well as individual investors.

We propose to implement the TVP-VAR-SV model and the spillover index approach to investigate the dynamics of mutual influences between market volatility and risk aversion sentiment (represented by variance risk premium), from aspects of realized variance (RV) and implied variance (IV). We innovatively study the evolution of volatility information transmission mechanisms by analyzing time-varying impulse response and dynamic connectedness in the Chinese market. Upon inspecting shock effects from investor sentiment to RV and IV, we discover that investor sentiment can cause sudden shocks on realized volatility but produce expansive shocks on expected volatility. As we compare spillover effects in call and put options, we find that (i) sentiments in put option contain more volatility information and can affect market volatility, while sentiments in call option primarily perceive volatility spillovers from market volatility, and (ii) investor sentiments in call (put) option become to present more volatility information in a bullish (bearish) market. Our study provides valuable insights on behavioral finance theory and portfolio risk management.

This study examines the impact of M&A deals initiated by companies from the TMT sector (completed over the period 2003-2018) on the post-M&A companies’ performance measured by the change models (Yook, 2004; Martynova et al., 2007; Grigorieva & Petrunina, 2015). Firstly, we analyze changes in the post-M&A operating performance. Secondly, we assess changes in the post-M&A companies’ value measured by the economic profit indicator. In the last step, we apply standard regression analysis to examine the determinants of the post-M&A operating results. Our results indicate that M&A deals initiated by companies from the TMT sector have a positive impact on the post-M&A operating performance of the combined company (+2.20%) and its value (+$16.3 million) in the long run. Stock-financed M&As have a better impact on post-M&A performance which supports the theory of investment opportunities. Domestic M&As have a better impact because of the differences in culture which lead to the complexity of post-M&A management due to high information asymmetry. We prove a positive statistically significant influence of the industry relatedness because of the effectiveness of M&As with participants which have similar business models. Our results show a negative impact of the acquirer’s R&D intensity on the post-M&A performance which confirms the argument that high R&D expenditures are associated with a higher degree of uncertainty and substitution effect leads to the results in which the acquirer’s R&D costs have a negative influence on the overall efficiency. A positive influence of the acquirer’s CAPEX intensity on the post-M&A performance is consistent with the previous research the authors of which called CAPEX an indirect indicator of technological development.

The US stock market has displayed considerable excess volatility during the different waves of the COVID-19 pandemic. Notably, while most US indexes fell abruptly and lost about 20%-30% during the first wave and in times of lockdown, unlike the global financial crisis of 2008-2009, the correction was rapid, and most stock indexes subsequently exceeded their pre-COVID levels. Accordingly, it is important to assess whether this dynamic is driven more by a switch in fundamentals or whether it is simply due to a conversion of investors’ emotions. This chapter aims to analyze the dynamics of the US (S&P500) stock index both before and during the ongoing coronavirus pandemic. Our findings point to three interesting results. First, US stock returns are driven by both macro-financial and behavioral factors. Second, a two-regime multifactorial model reproduces the dynamics of the US market in which financial factors play a key role whatever the regime, while the impact of behavioral factors appears more significant only in the second regime when investors’ anxiety exceeds a given threshold. Third, our in-sample forecasts point to the superiority of our nonlinear multifactorial model to forecast the dynamics of the US stock market.

The concept of imitation introduces new rules in shaping the behavior of organizations. Little has been written about the mimetic behavior of banking organizations and its role in business performance. In the banking sector, mimicry can manifest in various ways, such as the adoption of similar investment strategies, loan markets, risk management techniques, or business models. This paper offers new insights into understanding how the production process, business performance, and risk perception of banking institutions are amplified or dampened through imitative behavior. We propose a novel two-step framework that classifies banks into reference clusters upon business activities and targets. To test these arguments, we surveyed the European banking network for the period spanning from 2011 to 2021. The results show evidence that mimetic behavior is proximity-driven to peers, leading banks to converge or deviate from the network consensus. We conclude that mimetic behavior within the banking network can boost risk-taking and deteriorate business performance, contributing to the propagation of risky and non-sustainable practices, systemic failures, and financial instability.

The empirical investment literature studying the determinants of investment relies almost exclusively on truncated samples of publicly listed firms due to the lack of data on private firms. This truncation, however, is not random because listing is a choice for many firms, whereas others cannot list due to their characteristics. The ensuing endogenous truncation entails biased estimates. We develop a methodology that corrects for the bias. The bias-corrected results lend strong support for the q-theory: the investment-cash flow sensitivity disappears and the relation between investment and q nearly quadruples. Our econometric framework is also applicable in other economic contexts.

Postal service has become an important channel for drug trafficking worldwide. This paper examines the impact of the real-name mailing regulation on drug use in a Chinese province. Based on the universe of drug arrest, the difference-in-differences analysis shows that after the implementation of this regulation, on average, a town with 10 percent more courier services penetration exhibits a 0.78 percent reduction in drug arrest. This effect persists for at least a year. We exploit the early development of the courier service industry and use the early mulberry tree planting status as the Instrumental Variable for the courier service penetration today. We find no evidence that police activities change or drug users substitute alternative substances. Further analysis shows that the number of new drug users diminishes, while the number of addicted users remains. We suggest that this regulation on courier service companies is likely to be a cost-effective method to decrease the supply of drugs.

The Child and Dependent Care Credit (CDCC) subsidizes caregiving expenses for working households with a disabled spouse or adult dependent, but few childless households claim it. We examine the value of the CDCC for households caring for adults. We find that, as of 2016, over 10 percent of 50- to 65-year-olds had a coresident spouse or parent likely to be a qualifying individual. We document how state and federal benefits decrease post-tax costs of caregiving services across states and household types over time. Making the CDCC refundable would nearly double the number of eligible spousal caregivers aged 50 to 65.

The purpose of our analysis is to assess the drivers of unemployment rates for the European Union states. Closely referring to the specialized literature in this field, this reserach uses various regression analysis techniques upon a panel structured dataset for the 2015-2021 time interval, considering the sample of 27 European Union states. Our results estimate the positive impact of shadow economy as a financial and economic cirme proxy upon European unemployment rates. There’s also a direct impact of income inequality and life expectancy upon unemployment and an indirect impact of sustainable development proxies like the Human Development Index and economic prosperity, measured as per capita gross domestic product, on the evolution of unemployment throughout Europe. Our findings are robust for the subsample of old European member states. Policy measures need to be implemented on behalf of reducing European inequalities and the development of its shadow economy, and boosting human and economic development, in order to contract European unemployment levels.

When patients are fit for discharge but continue to stay in hospitals and await transfer to an appropriate destination like a facility-based long-term care bed, a home with care services, or a palliative care bed, hospitals designate them as alternate level of care (ALC) patients and provide reduced services within an acute care setting. However, ALC is not well equipped to meet the needs of those patients; it also causes crowding in the emergency room and the postponement of day surgeries. In Canada, provincial governments provide block funding to hospitals to provide acute care. However, hospitals must divert the fund partially to provide ALC, which is clinically not necessary. Among those discharged in 2019-20, ALC accounted for 17.2% of total bed-days. Yet, the cost of ALC is unknown. Previous estimates related to the costs associated with ALC focused on small sample sizes and/or had other methodological limitations. The objective of this study is to estimate the cost of ALC, using administrative data capturing all hospital discharges in Canada. Estimating the cost of ALC is challenging, as cost data for ALC days is lacking. However, the hospitalization cost (acute care plus ALC costs) and the number of acute and ALC days are available. Applying log-log regression to CIHI’s Discharge Abstract Database, supplemented with hospitalization cost data, the cost elasticity of ALC length-of-stay was estimated. The cost of ALC was then estimated using the estimated cost elasticity, average hospitalization cost, average ALC length-of-stay, and total ALC bed-days. Among those discharged in 2018-19 and 2019-20, the estimated ALC costs were $2.3 and $2.5 billion, respectively. Without ALC, hospitals could have handled at least 400,000 more hospitalizations, resulting in shorter wait times, and waiting lists, more efficient use of healthcare resources, and better value for money.

Technical and Vocational Education Training (TVET), especially at the post-secondary level, has the potential to play a critical role in poverty reduction, job creation, and national development. In contrast, blended and online learning has the potential to provide education to both well-served and underserved populations in academic and TVET settings, provide credentials for knowledge observed in informal and formal sets, and possibly be more cost-effective than traditional classroom-based education. However, the evidence on comparison of learning outcomes in different learning modes in TVET is scant…

This paper is an attempt to unravel some specific inter-related dimensions of inequality in participation in higher education by economic status of the households. The importance of examining the linkages between economic status and participation in higher education also lies with the fact that a substantial proportion of the increase in economic inequality is linked with the increase in the returns to education and low level of inter-generational mobility. More clearly, a vicious circle is clear: the barriers to access to higher education among low-income students widen the income inequality, which in turn widens the inequality in access to higher education. Given this, it is important to examine how far students from poor households are able to access higher education in India. The inequality in access to higher education-measured in terms of the gross enrolment ratio, gross attendance ratio, and rate of higher education attainment that is percentage of higher educated people in the total population-by economic status of the households in India is analysed in detail in the paper. Taking economic status as cross-cutting reference for all dimensions, gender and rural-urban differences are also analysed. Then we analyse inequality in household expenditure on higher education by these categories. Finally probability of attending higher education by various groups of population is estimated using logit regressions. The concluding section provides a summary of the major findings of the study along with some important policy implications.

Numerous studies show that access to clean water reduces child mortality and morbidity, but little work has been done on the consequences for school enrollment and child labor. The effects are theoretically ambiguous because healthier children could go to school or go to work. I examine the short-term effect of municipal installation of water filtration plants on school enrollment and child labor in American cities from 1880-1920. Using a difference-in-differences approach, I find that municipal water filtration has a positive effect on school enrollment. Also, I find a negative effect on child labor, but it is not significant at conventional levels.

Korea has long debated whether the reputation of high schools unfairly affects college admission. Therefore, there is a demand for a blind admission policy that addresses this unfairness. Using the 2010-2017 Graduates Occupational Mobility Survey in Korea, this study finds that the halo effect of elite high schools affects college admission and is stronger in families where the father’s education or family income is low. We conduct a simulation using a machine-learning methodology to evaluate a blind admission policy, and construct a synthetic dataset that mitigates the halo effect. The results show that the halo effect disappears regardless of family background, implying that the blind admission policy prevents it from distorting admission outcomes, thereby, preventing underprivileged families from making unnecessary sacrifices to benefit from it. Therefore, maintaining the main framework for early admission while enhancing the blind admission policy is the best strategy to mitigate the ‘halo effect.’

This study examines the factors that influence on Saber 11 test scores, emphasizing on reading for entertainment. Based on micro-level data from Colombia, students’ scores in Saber 11 increase as they show a greater collection of books at home and read for >2 hours every day. Public school students score lower than students from private schools, regardless of the number of books possessed, although they score higher than their private counterparts when they read for >2 hours every day. Unfortunately, more books and hours of daily reading do not eliminate the score gap between urban and rural students.

Learning losses during the COVID-19 pandemic have been well documented, and in this paper we attempt to learn more about determinants of the magnitude of the adverse effects of the emergency shift to remote learning in Polish upper-secondary schools. The analysis focuses on local internet speed and the structure of remote classes and uses a value-added framework to identify the variable impacts. The results show that local internet speed and the structure of remote classes are strongly related to the achievement of vocational school students. Those in communities with internet speed in the lowest decile fare particularly poorly in mathematics.

Child undernutrition is considered as a wicked problem due to the dynamic and causal nature of the deep-rooted contributors and factors. The existing frameworks reveal that the enabling determinants define the fundamental structure of the issue. This study explores the role and components of the enabling determinants that have fundamentally contributed to the chronic issue of child undernutrition. The components identified are classified under the major theme of knowledge and evidence, politics and governance and capacity and resources. Further, it investigates the interlinkages in the enabling environment of child undernutrition using a systems thinking approach. The framework developed based on the existing evidence of interlinkages in the enabling environment of child nutrition appeals for a more political-based approach over technical solutions to tackle the persisting issue of child undernutrition.

Poverty is still one of today’s most pressing global concerns. The Sustainable Development Goals (SDGs) acknowledge this issue by making poverty eradication their number one, frontline goal. Development Aid (ODA), which employs various tools, is being used to reduce poverty levels. However, ODA programs can sometimes exacerbate poverty. In contrast, some researchers regard Complementary Currencies (CCs) as a highly effective, underutilized tool for poverty reduction. Thus, this paper aims to assess whether CCs can help the poor overcome poverty. The expectation is that if CCs are utilized, the poor will fare better. Four assessment indicators are applied: employment, income, and financial inclusion (better access to a means of payment, credit), while relevant literature and empirical data analyses is conducted. The latter is executed exploratory in a case study approach with 11 semi-structured expert interviews on 16 different CCs from developed and developing countries. The results in theory suggest that CCs benefit the poor because they prioritize local development, which promotes local employment, local income, and better access to a means of payment and credit, even for the extremely poor. In practice, only 5 CCs could perform with the highest impact on these indicators. After analysing the outcomes, most CCs designed with mutual credit and/or by community banks had the highest impact on poverty reduction. In contrast to what some claim, this holds true whether they are placed in a developed or developing country. In general, the specific design, the location, and economic imbalances, like lack of liquidity (Fiat) might affect the outcome. These findings are significant for better understanding the function of CCs in local development and the fight against poverty. This study thus adds to the conversation on how to achieve SDG 1 with ODA by emphasizing the importance of CCs in development aid as a common tool for reducing poverty.

Rising gender inequality is a major pressing policy concern around the world. The global non-attainment of the Sustainable Development Goal (SDG) 5 indicates this issue. This issue becomes more critical, when the educated women refrain from joining the labor force. The institutional and political dynamics of an economy might play a significant role in shaping the female labor force participation. A conducive and gender-inclusive policy environment created by these factors should drive the educated women in joining the labor force. This policy dynamics might be moderated by the female representation in the politics. However, the absence of a global benchmark policy framework is restraining this objective from its realization. The present study has attempted to develop this policy framework by analyzing the aforesaid dynamics across 125 countries over 1990-2020. The two-step System GMM and marginal impact analysis through elasticity modeling are applied in the empirical pursuit. The study outcomes show that the institutional and political dynamics might require a policy level realignment to ensure the labor force participation of educated women. The women political participation is found to exert a catalytic effect in realizing this policy objective. The study outcomes are utilized to develop a policy framework for attaining the objectives of SDG 5.

We propose a theoretically founded and ex ante estimable measure of employment elasticities within and between sectors based on observed transition rates. We use this to study the heterogeneity of structural changes across occupations in Germany during the past decades. First, employment growth per unit of wage growth is twice as large for occupations ex ante classified as relatively elastic compared to inelastic occupations. This is true in linear projections and when isolating occupational demand shocks via instrumental variables based on initial routine task content. Second, cross-elasticities, capturing the effect on employment growth of wage changes in close substitute occupations, matter as much as own-elasticities. We validate the estimated employment elasticities with external correlates, including occupational licencing and task distance. The model explains substantially more of the structural changes during 1985-2010 than an approach with homogeneous labor supplies.

The paper benchmarks the magnitude of sex work throughout 29 European countries (EU-28 and Norway), including prohibitionist, regulationist, abolitionist and neo-abolitionist regimes. First, literature review over the two past decades distinguishes between theoretical and empirical contribution, and voluntary versus coerced sex work. Second, scant data from representative household surveys on male sexual behaviour document the demand side. Third, data sources on the supply-side help designing three series of Estimates as of year 2010: one from HIV prevalence amongst female sex workers, one from international NGOs and one from victims of sexual exploitation trafficking. Fourth, Estimates are checked against National Accounts adjustment for illegal production on the supply side and for consumption expenditure on the demand side; last, Estimates are assessed as for their share in the female labour force and informal employment.

We study changes in educational homogamy in the US and four European countries over the decade covering the Great Recession. The marital preferences identified point to the widening of the social gap between different educational groups since these preferences have increased the inclination of the individuals to match with others of similar educational traits in all five countries. We obtain this finding with an aggregate measure characterizing revealed preferences of individuals in relationship. We apply a novel approach for validating our finding: we compare our aggregate measure with dating data informative about the reservation points not only of those people who will be in a couple, but also those who will remain single. Finally, we challenge a commonly held view: we argue that marital preferences should not be blamed for the documented increase of the social gap since preferences are not exogenous, but are shaped by changes in the employment prospects of the potential partners.

In this paper we test the persistence of involuntary part-time employment, making use of large historical series for the US and UK. Following a standard and comprehensive macro-econometric approach, a battery of panel and time series unit root/stationarity tests were performed, also allowing for flexible specifications as fractional integration and structural breaks in the series. As a result, our contribution provides evidence of the existence of a long memory process in the involuntary part-time series for both the analyzed countries and suggests a structural break in the mean of the series in the Great Recession surroundings, overall confirming the hysteresis phenomenon in involuntary part-time employment. At the national level, the two phenomena, identified by a sudden deterministic break in the levels of the models employed and by a unit root process of order one or higher, coexist an interact together.

This article examines the influence of labor markets flexibility and the generous social contract on the female youth unemployment rate in the resource-rich, Gulf Cooperation Council (GCC) countries. The research question is motivated by the observation that the female youth unemployment rate is more than double the male youth rate. We hypothesize that labor market flexibility reduces the female youth unemployment rate, while the generous social contract increases it. We adopt panel data model and fixed effects and an instrumental variables/ generalized method of moments estimation methodologies. Empirical evidence surprisingly shows that both labor market flexibility and the social contract improve female youth unemployment rate. Unemployment concerns about adopting flexible labor market on youth unemployment are therefore unfounded.

For years, universities have been putting great efforts into introducing improvements in innovations in teaching. To this end, the use of different tools is being incorporated, supporting the methodologies. This article analyzes the application of the use of Metaverses in a training session for a group of 40 university professors, from a business school. The results obtained are analyzed statistically, appearing certain differences in the disposition for their employment, which is higher among the youngest of the study, because they are considered more “digital natives, among men and among Doctors. The conclusions invite us to think that teachers consider that the Metaverses can be an excellent tool to multiply remote teaching options, both completely online and hybrid, considering them as a complement, rather than as a substitute. But, it can be seen that, in general, there is a long way to go for them to implement it as a teaching activity, because there is a lack of technical knowledge and experience. The conclusions invite us to think that teachers consider that metaverses can be an excellent tool to multiply remote teaching options, both completely online and hybrid, and considering it as a complement, rather than as a substitute, in the case of traditional teaching. It appreciates that, in general, they consider that there is a long way to go for them to implement it as a teaching activity, because there is a lack of technical knowledge and experience of use, both in teachers and students.

Derivatives are increasingly used by managers not only to hedge risks but also to pursue non-hedging activities for fulfilling opportunistic incentives. The Statement of Financial Accounting Standards No. 161 (hereafter, SFAS 161) requires firms to disclose their objectives and strategies of using derivatives. Using the adoption of this standard, we examine whether and how derivative disclosures influence managerial opportunistic behavior. We employ insider trades and stock price crash risk to capture managerial opportunism. Applying a difference-in-differences research design with hand-collected data on derivative designations, we find that, after the implementation of SFAS 161, derivative users that comply with SFAS 161 experience a significantly greater decrease in both insider trades and stock price crash risk, compared with a matched control sample of non-derivative-users. We further provide evidence to suggest that SFAS 161 curbs managerial opportunism via reducing information asymmetry between corporate insiders and outside investors and enhancing the effectiveness of derivative hedging. We find no evidence that, compared to the non-derivative-users, derivative users not compliant with SFAS 161 have a greater reduction in either insider trades or stock price crash risk in the post-SFAS-161 period, implying the importance of enhancing the enforcement of the regulation.

Online shopping is an ascendant phenomenon. Simultaneously, the concern with consumption of unhealthy food is also rising. Although nudges are known to affect choices, it is unclear how they impact healthy food purchase intentions online. We use a randomized experimental design to examine the impact of nudges in an online-grocery setting on urban consumers in a developing country context. Although the role of nudges on consumption has been studied in physical settings, it has received limited attention in virtual environments. We find economically significant impacts of an endowment-related and convenience-based nudges, and draw conclusions for policy and marketing.

In countries with multiple cultural and ethno-linguistic cleavages, it is often difficult to reach agreements about historical relations. In the Spanish case, a scientific examination of the geographical direction of public investment may shed light on government intentions, for certain historical periods. During the Franco dictatorship, our empirical results point to an early discrimination, during the autarkic period, against the productive interests in Catalonia and the Basque Country. This situation could have been corrected later, for reasons linked both to economic liberalization and to the search for political survival, in the face of a revolutionary threat. In this sense, the significance of the ideological determinants of public investment, at the provincial level, confirms the existence of non-economic incentives behind the territorial allocation of infrastructure.

In this paper we analyse sex work in post-revolutionary Paris. Sex work has been frequently associated with poverty and considered a survival strategy for women in economic need. We develop a theoretical model showing that an increase in the cost of living was associated with an increase in the number of sex workers. The French system of sex work regulation allows us access to statistics on the monthly number of registered sex workers in Paris in the first half of the nineteenth century (1812-1854). We run an autoregressive distributed lag model to test for the positive relationship between grain prices (as a proxy of the cost of living) and the number of registered sex workers. We confirm the existence of a positive long-running relationship between two variables.

This paper studied how the COVID-19 pandemic has impacted the performance of micro, small, and medium-sized enterprises (MSMEs) in creating and preserving jobs. We assessed the pandemic impacts on firms’ effectiveness in protecting/preserving existing jobs and creating new jobs between 2019 and 2021. We used a mixed-effects Poisson model for longitudinal data to understand factors explaining MSMEs’ jobs performance. The model is estimated using a newly conducted firm-level database with about 500 MSMEs in Kenya and Rwanda (Africa). Most surveyed MSMEs were women-owned, women-led, or employing at least 50% of women. We show that the pandemic impacts on MSMEs job outcomes vary widely with the type of industry and country. We found that the pandemic caused significant jobs lost with a gradual decline in firms’ capability to maintain existing jobs and create new ones. We also found that MSMEs employing only women are the most intensive in green jobs, but they operate informally and are less efficient in creating and preserving existing jobs compared to the others. Most MSMEs were on a growth trajectory before the pandemic. We concluded that improving Women-MSMEs access to working capital, long-term capital, capacity building, skills upgrading, and providing incentives to formalize and engage in sustainable activities are critical to ensure an inclusive and sustainable recovery.

While there is an almost unanimous view of the benefits of trade – fueling economic growth, supporting a greater number of and better paying employment, raising living standards and enhancing the consumer surplus with affordable goods and services, contemporary research has primarily looked at external trade i.e. trade across national borders. This has led to an under-appreciation of the quantum and the effects of internal trade i.e. trade within national borders. This is of particular significance for larger economies such as India. One reason is the relative paucity of data for tracking internal trade. This study proposes to make use of domestic taxation (VAT/GST/Sales Tax) data to get a sense of the volume and directions of internal trade with a special emphasis on India. Along with trade, the internal movement of people (for economic reasons) is also tracked. The study quantifies interstate trade flows in India to amount to about 69% of the GDP, when domestic movement of import goods are included and about 35% of the GDP, when only domestically produced goods are taken into account. Further, internal trade appears to be growing at more than twice the pace of growth of the GDP. Amongst other reasons, this enhanced economic integration is attributable to the transportation efficiency gains that have accrued after the introduction of the Goods & Services Tax (GST). To discern trends in internal migration, data from the Public Distribution System (PDS) is used. It is seen that movement of people also displays gravity effects and that the flows of internal migration may have changed over the last decade. The study has significant implications in public policy decisions especially those related to provision of physical infrastructure and for development of human resources. It also has implications for businesses to base decisions regarding predicting sources of likely future demand.

Concessions to private companies were a common form of economic and administrative organization during the colonial era in Africa. In 1891, Portugal granted the central and northern regions of Mozambique as concessions to private companies. The Mozambique and Niassa Companies ruled their concession territories through an extensive forced labour regime that transformed the people in their areas into subservient proletarians. I examine the long-term effects of concession companies on human development in Mozambique using a spatial regression discontinuity (RD) design. My estimates show that the Mozambique and Niassa Companies had mixed effects on present-day wealth, health, and education outcomes. Individuals residing in villages located just inside the former concession borders of the Mozambique Company have significantly higher levels of education compared to those living outside them. In contrast, individuals residing in villages inside the former concession borders of the Niassa Company have significantly lower levels of health and education compared to those living outside them. My results shed light on the effects of the concession system on contemporary development outcomes and aim to advance the understanding of the colonial origins of the lack of integration in Mozambique.

How do institutional structures affect the productivity in innovative sectors? Using German re-unification as a natural experiment, we analyze the effect of institutional change in the East German academic system on the scientific productivity of East German scientists in the research fields of science, technology, engineering, mathematics, and medicine (STEMM). We find a strong correlation between restructuring of the East German academic system and the productivity of East German scientists. To identify the causal effects that yield this correlation, we investigate to what extent the observed productivity is brought about by efficiency gains and to what extent by reallocation. We analyze difference-in-differences in productivity, collaboration, field switching behavior, and attrition of the treatment and non-treatment groups of East German scientists. We find reallocation between fields or attrition to be the dominant feature that underlies East German scientists’ productivity differences when institutional effects are isolated. Our findings have implications for the effects of increased competition in today’s academic environment.

What are the benefits that a man generates to his household just for the sake of being a man? Using regression discontinuity design, we estimate the impact of adult male presence in female headed households on six socioeconomic outcomes in rural Burundi. We use the age of the oldest male in the household to compare female headed households with a young adult male (> 18 years-old)—who enjoys the privileges of a man—with female headed households with a teenage male around the 18 years-old mark—who has not yet achieved malehood. We show that adult male presence increases household income, asset value and children’s years of education. But it does not change land use, nutrition and health outcomes. The mechanisms that drive these results appear to be better access to off-farm labour markets, increased agriculture production, increased ownership of smaller productive assets, and better social integration. Our work provides empirical evidence of how gender norms constraint microeconomic development in an agricultural economy with a high degree of gender inequality.

In this paper, we utilize the remote sensing data to estimate the employment of Bangladesh. Since the labor force survey in Bangladesh had been done occasionally, total employment was measured statistically based on scarce survey data. To exploit the real-time availability and regionally subdivided characteristic of remote sensing data, we construct the annual employment by job quality by 64 districts using interpolation. With interpolated employment data by job quality which shows how many employments are in good quality such as employer or regular-paid job, we construct the forecasting model for annual employment data with mixed frequency control variables in quarterly frequency, as well as remote sensing data. Then we extend the model for estimating quarterly employment status using monthly series which includes the remote sensing data such as nighttime light and enhanced vegetation index. Since there is no true observation in our target variable, there is no way to verify the accuracy of the forecasting model. Instead, we extend our approach to do out-of-sample forecast since we have the real-time data up to the first half of 2022. In result, remote sensing data may not capture the overall trend of employment because control variables such as industrial production dominates. However, remote sensing data shows idiosyncratic movement by districts. Therefore, our result is helpful for policymaker to implement labor policy for specific districts by seeing the trend of remote sensing data in real-time.

This study examines how the social media (e.g. Facebook, Twitter, Instagram, and Linkedin) influences the vote share of populist parties, left-wing and right-wing populist vote shares, in Europe. We use the Generalized Method of Moments (GMM)-system estimations and analyze the European Union 27 (EU-27) member states over the period 2014-2020. We distinguish between clearly oriented political communication and general communication of political parties through social media. The main results show that populist political oriented communication through Facebook, Twitter, Instagram, and Linkedin boosts the populist votes for both left and right-wing parties, while the general use of social media by political parties presents a contrary effect.

We use panel data to analyse Spanish firms and their collaborations for innovation with EU partners (outside Spain) in 2004-2016. The evolution of intra EU cooperation throughout good and harsh economic times is examined. The article also enquires as to whether different types of companies (domestic business groups, unaffiliated domestic firms, foreign subsidiaries and state-owned-enterprises) display similar cooperative behaviour. The period is divided into three sub-periods (boom, downturn, and recovery) and three logit models with panel data of a representative sample of Spanish firms are proposed. Firstly, we analyse cooperation for innovation with all types of partners (suppliers, clients, consultants, universities, etc). Then, we single out for analysis cooperation with EU universities. We find that drivers of intra-EU cooperation for innovation with all types of partners vary throughout the business cycle. Firms that have persisted in their cooperative activities with EU partners are more prone to cooperate even during the crisis; those that export to the rest of the EU and those that have received EU funding are also more prone to stay cooperative. Moreover, innovative firms and firms that can absorb spillovers coming from technological sources and from competitors are more likely to resort to cooperation with EU partners during hard economic times. Cooperation for innovation with universities displays certain specific drivers. A large size or the capacity to launch new products into the market are less important predictors in this case. Ownership and the probability that a firm cooperates for innovation with EU partners are associated. The type of firm most likely to cooperate for innovation with EU partners are SOEs and the less likely are unaffiliated domestic firms. Domestic business groups and foreign subsidiaries display similar behaviour. The results contain policy implications.

This paper proposes an empirical test to depict possible endogenous cycles within Heterogeneous Agent Models (HAMs). We consider a 2-type HAM into a standard small-scale dynamic asset pricing framework. Fundamentalists base their expectations on the fundamental value, while chartists, subject to self-fulfilling moods, consider the level of past prices. Because these strategies, by their nature, cannot be directly observed but can cause the response of the observed data, we construct a state-space model where agents’ beliefs are considered the unobserved state components and from which the heterogeneity of fundamentalist-chartist trader cycles can be mathematically derived and empirically tested. The model is estimated using the S&P500 index for the period 1990-2020 at different time scales, specifically, quarterly, monthly, and daily. We find empirical evidence of endogenous damped fluctuations with a higher percentage of speculators in the shortterm horizon. In addition, results indicate time-varying behavioral heterogeneity within-group. Moreover, the model exhibits better long-run out-of-sample forecasting accuracy compared to the benchmark random walk model.

This paper quantifies the local economic impact of Special Economic Zones (SEZs) that were established in India between 2005-2013. Based on a novel data set that combines census data on the universe of Indian firms with georeferenced data on SEZs, we find that SEZs increased manufacturing and service employment with positive spillover effects up to 10km. This employment gain was paralleled by a decline in local agricultural employment, in particular of women, suggesting that the policy contributed to structural change. We find no evidence for heterogeneous effects between privately and publicly run SEZs or zones with different industry denominations.

We study the willingness to pay (WTP) for a large set of improvements in water service related to water quality, continuity, and securing access for people with no house piped water during the COVID-19 pandemic. Using data from urban Peru, and the contingent valuation method, we estimate a mean WTP of around PEN 4.3 (USD 1.05), 3.7 and 1.8, respectively, for the aforementioned sets of improvements, with the combined WTP representing a 23% increase in the households’ water service monthly bill. We find that the WTP for all sets of improvements is influenced by the expenditure in bottled water (which acts as a substitute for tap water) and a proxy variable for household assets. The influence of the individual characteristics typically scrutinized by the literature (e.g. sex, age, and education) varies with the type of improvement examined. We find a significant heterogeneity in WTP across providers and calculate the users’ contribution to a water fund that could crowd-in the public investment in water infrastructure.

Understanding complex systems like climate and human interactions and response is a fundamental global challenge in the present century. Climate change has severe consequences not at just local, regional but also at a global scale. Since such shifts in the climate, the substantial agriculture sector of India has been suffering widely from its drastic change. The present study is carried out in Indian state of Telangana, to explore the adaptation strategies of farm households to climate change. This study expounds the perception of farmers, their farming adaptations to climate change and determinants of adaptation strategies in the study area. Primary data is collected from 304 farmers of Karimnagar and Mahabubnagar districts in Telangana. Binary logistic regression was employed to find out the aspects that shape smallholder farmer’s adaptation strategies. The analysis revealed that more than 90 percent of the study region farmers reported that climate is changing over the last 30 years or more. Similarly, farmers’ awareness and perceptions about changes in rainfall and temperature parameters indicated that a significant portion of farmers perceived that rainfall is decreasing and temperatures are increasing, including the number of hot days. Further, the study area farmers reported that the most commonly practiced adaptation strategies are: early maturing varieties, adjusting sowing/planting dates, enhancing irrigation facilities, using a different variety of crop seeds, mixed crops or intercropping, engaging in non-farm activities, water management practices, migration and crop insurance. Furthermore, the empirical outcomes of the logit regression evidenced that level of education, gender, yearly income, landholding size and perceptions on climatic variables have a significant favorable impact on farmer’s adaptation strategies. This study suggests that government policies need to focus on improving the aforesaid important determinants to boost farmers’ adaptation and thereby minimize vulnerability.

Over the last few decades, the atmospheric dioxide emission has been amplified to a great extent in India. Sustainability concerns are also increasing globally. Other side, in India these concerns are increased hugely, it’s happened mainly due to lack of education, depletion of natural resources and growth of economy can lead to severe threats to the environment. To study this issue, the present study examines the phenomena that in which way natural resources, human capital, and economic growth affect two important indicators i.e. ecological footprint and carbon emission in India. The data has taken from 1985 to 2019 by using the dynamic autoregressive distribution lag (DARDL) approach. The results show that in the long run human capital and natural resources has a negative relationship with carbon emission, but economic growth had a positive relationship with carbon emission. In case of short run, human capital and economic growth has a positive relationship with carbon emission whereas natural resources had a negative relationship with ecological footprint. Moreover, by creating awareness among the citizens together with governmental regulatory pressures might help in solving the problems related to the environment resulting in preserving the sustainability of future generations in India.

We build a model with labor market frictions to explain income disparities between provinces, sectors (formal/informal), and skill groups (skilled/unskilled) in the Democratic Republic of the Congo. Quantitative analyses show the role of technologies, human capital, infrastructure, and labor market frictions in explaining spatial and within-province inequalities. We highlight ”O-ring” inequality patterns, implying that successful development policies involve a combination of coordinated policy actions. Technological disparities contribute the most to spatial inequalities, a development policy that disregards the informal sector has anti-redistributive effects. Taken in isolation, policies targeting education, infrastructure, and labor market frictions can increase poverty, at least along the intensive margin.

Theoretical concerns exist that a psychological wellness risk experienced in one period influences endogenous preferences in later periods. We test the association between childhood psychological wellness risk and adulthood altruistic attitudes. We find that a 1 standard deviation increase in the likelihood of experiencing childhood psychological wellness risk predicts a 0.24-2.34 percent of standard deviation decrease in desire for dynasty-building and generosity during adulthood. We also find evidence for the altruism-habit formation hypothesis. We suggest that the ever-experienced psychological wellness risk leads to self-interest-oriented choices rather than to altruism-oriented preferences in later periods. Our results are robust for several robustness checks.

We scrutinize the effect of global, Russian and the USA’s geopolitical risks on Russian uranium export-driven USA’s nuclear energy consumption from January 1996 to December 2019. Using the cross-quantilogram (CQ) procedure, we find that global geopolitical risks negatively affect Russian uranium export-driven USA’s nuclear energy consumption in the lower quantiles and positively from medium to upper quantiles in the long memory. Besides, Russian own geopolitical risks have no significant influence, while USA’s geopolitical risks positively impact it from the medium to upper quantiles in the extended memory. Finally, we make our findings robust using the wavelet coherency analysis procedure.

While extensive literature is available on the impact of the early childhood nutritional food program, little we know about the nutritious food provision at a later stage. Our paper examines the causal effect of one such program. In late 2010, the central government of India introduced the Rajiv Gandhi Scheme for Empowerment of Adolescent Girls (SABLA) for adolescent girls aged 11-18. The implementation of the program provides us with ample variation in the treatment. Using multiple nationally representative datasets, we employ the difference in differences technique to estimate the causal impact of the program on the educational and learning outcomes of treated adolescent girls. Our results reveal that the program significantly improves enrollment status. However, improvement in the learning outcomes (reading ability and math skills) is at the basic level. We identify the significant improvement in the programs’ recipient health status (BMI and weight) and the increase in the child-specific educational expenditure as the possible mediating channels causing these effects. Our findings also suggest that the impact is vital for those who get early access to the program. This implies that government should focus on providing nutritious food in early childhood, rather than later, for the overall development of children. Our findings are consistent across different datasets, tested against potential confounding factors, and are robust to alternative specifications.

Economic decisions depend upon macroeconomic expectations. Using monthly survey data between 2000 and 2009, we construct macro- and household-level optimism indices based on households’ expectations on various economic issues for the next year. We show that individuals with higher socioeconomic status (SES) have more optimistic views both on macroeconomic and household-level expectations. For macroeconomic optimism, a higher level of education, while for household-level optimism, a higher income level causes a more pessimistic outlook during recessions. We also find that income rank remains significant only for household-level optimism once we control for the households’ evaluation of their previous year. We also confirm that a higher optimism level increases the propensity to purchase durable goods, a car, or a home.

This study examines the effects of community-level electrification on women’s social autonomy in India using panel household survey data, administrative data and satellite data spanning over two decades. Using flexible difference-in-difference estimators, we find higher community-level electricity hours reduce incidence of sexual violence against women, and improve women’s mobility, fertility choices and access to health care. Results are robust when using night-time luminosity as an alternative indicator of community electrification, most recent data on reliability of electricity and alternative longitudinal estimation techniques. Heterogeneity analysis shows that the effects are stronger in rural areas compared to urban areas. We identify four main channels through which electricity impacts women’s autonomy: paid employment, education, exposure to mass media and safety.

This work scrutinizes time-varying return interlinkages among major cryptocurrencies, NFT tokens, and DeFi assets between 1 July 2018 and 19 February 2023. Moreover, we perform a portfolio backtesting analysis and determine optimal portfolio allocations and hedging effectiveness under different portfolio construction techniques. Our findings reveal that (i) the overall connectedness index prominently captures well-known financial/geopolitical distress incidents and peaks on 5 May 2022, (ii) the leading cryptocurrencies (ETH, BTC, and BNB) are the largest transmitter of return shocks, (iii) cryptocurrencies, NFTs, and DeFi form distinct cluster groups in terms of return connectedness, (iv) the connectedness network estimated around the FTX’s filling for the bankruptcy is characterized by the strongest interlinkages among the returns, (v) transitory connectedness dominates the study episode and persistent diversification options are higher, (vi) optimal portfolio strategies computed by different portfolio construction techniques display similar motifs and have sustained growth paths except for some short-lived drop backs.

Digital ability can increase job-searching efficiency of labor. However, the impact of digital ability on employment adequacy in rural households in China has not received sufficient attention. Using survey data from 1,953 rural households in China, this study analyses labor participation and working time as indicators of employment adequacy. Item Response Theory was used to construct digital ability indicators, while Conditional Mixed Process, IV-Probit, and IV-Tobit models were used for empirical estimation. After controlling for endogeneity, the results show that: 1) digital ability has a positive impact on labor participation rate and total working time; 2) digital ability has a positive effect on non-agricultural participation and working time, but negative effect on agricultural participation and production time; 3) the promotion effect of digital ability on working time is more obvious in households with high dependency ratio and low income; 4) both overtime work and underemployment co-exist among rural households. These results provide evidence that digital ability promotes employment adequacy and off-farm transfer of rural labor. Policymakers should consider improving the digital ability of rural households, especially those with high dependency burdens and low incomes. These are crucial to promote the labor input of rural households and achieve common prosperity.

We study how stock-by-stock fluctuations of illiquidity are related to covid news. Facing many proxies for (il)liquidity, we build a Y-index for a bilateral regression with residuals orthogonal on the xs. We evaluate four normalisations (constraining (i) the Y-index’ variance, (ii) the sum of the weights, (iii) the sum of the squared weights, and (iv) the sum of the absolute values of the weights) for such a best-fit (‘Efficient’) Y-index and compare them, performance wise, with the simple average and the ys’ principal component. In our application, the simple mean outperforms only in an uneventful period where noise dominates signals. In two turbulent periods with a better information-versus-noise ratio, the constraint on the sum of the weight works best and the one on the sum of the squared weights worst, but all indices do better than the individual measures even taking into account uncertainty coming from their weighting schemes.

In a voting problem with a finite set of alternatives to choose from, we study the manipulation of tops-only rules. Since all non-dictatorial (onto) voting rules are ma- nipulable when there are more than two alternatives and all preferences are allowed, we look for rules in which manipulations are not obvious. First, we show that a rule does not have obvious manipulations if and only if when an agent vetoes an alterna- tive it can do so with any preference that does not have such alternative in the top. Second, we focus on two classes of tops-only rules: (i) (generalized) median voter schemes, and (ii) voting by committees. For each class, we identify which rules do not have obvious manipulations on the universal domain of preferences

Microcredit emerged as a product innovation from traditional credit design, and allowed lenders to capture a new segment of the market. However, its key building blocks have been criticized as not fit for purpose: Rigid repayment schedules are incompatible with fluctuating business income and lead to underinvestment. Group lending has been shown to induce excessive peer pressure. Recent evidence suggests that more flexible microloan repayment benefits borrowers, but lenders fear diminished repayment morale. We study repayment choices in rigid and flexible loan contracts with discretion in repayment timing. Using a lab-in-the-field experiment with 645 microcredit borrowers in the Philippines, we identify moral hazard and quantify social pressure. Payoff maximization predicts low repayment in our rigid benchmark contract, and increased repayment with flexibility. Results suggest the opposite: Repayment in the rigid contract is high, and drops substantially under flexible repayment. Social pressure decreases. Our results are consistent with a strong social norm for repayment, which is weakened by introducing flexibility. Norms, which may be inculcated by the lender, may help explain several recent puzzles in microfinance research, including high and equal repayment rates across individual- and joint-liability contracts, and excessive peer pressure. Importantly, norm-driven behavior may erode with the introduction of flexibility.

In this paper we study the relationship between air pollution and crime. We construct a city-level, hourly data set with 2.4 million crimes and link each crime to data on pollution and controls, e.g. weather variables. We study the effects of four pollutants (nitrogen dioxide, sulphur dioxide, carbon monoxide, and ozone), as these have different neurotoxic effects. Our identification strategy relies on using high dimensional fixed effects and exploiting hourly variations. We find that higher levels of carbon monoxide increase violent crimes, but that higher levels of ozone reduce property crimes. We find evidence of an inverted U-shaped relationship between violent crime and carbon monoxide. Further, we find heterogeneity in the effect of ozone on property crimes across cities but not for the effect of carbon monoxide.

Labour is often regarded as a homogeneous input in the literature on knowledge production and innovation. However, the diversity of employees may also have an impact on knowledge creation. For instance, immigrants may contribute to innovation through their unique ideas stemming from their diverse cultural backgrounds. Conversely, they may hinder innovation due to conflicting behaviour. Organizational behaviour (OB) theories have also identified decision-making and social categorization as two underlying processes that may influence the impact of diversity on innovation. Nevertheless, jury is still out on the impact of immigrant employees on innovation. In this study, we investigate the impact of employee diversity on product and process innovations using data from the Canadian Workplace and Employee Surveys (WES) between 1999 and 2005. Our mixed logit model estimation results support the positive influence of immigrants on innovation even after controlling for various employee and employer characteristics. The results hold up when we address potential endogeneities. Additionally, the results indicate that immigrants are more effective in promoting innovation in firms with more organizational capital and training programs. Among industries, manufacturing and service sectors appear to have benefited the most from immigrants’ contributions to innovation.

How does technology transfer of government inventions affect follow-on innovation? Being aware of the importance of technology development and commercialization, the United States enacted a group of policies in the 1980s that aimed at promoting the commercializing of government-funded research by licensing. It, however, remains questionable whether patenting and licensing are appropriate tools to spur welfare-improving follow-on innovation. To analyze this question, we exploit the NASA Technology Transfer Program that fosters the licensing of NASA technologies by third parties. Combining this technology-related information with United States patent data, we find that NASA technologies that are just part of the licensing portfolio show no different follow-on innovation pattern than those that are not. Leveraging the information about the licensing status, we find that an exclusive licensing agreement facilitates subsequent technological developments. Consequently, our results imply that commercialization by licensing government inventions is an important policy tool to increase the benefits for society.

The present study aims to predict overnight stays in Italy at tourist accommodation facilities through a nonlinear, single factor, stochastic model called CIR#. To this end, we look at Eurostat monthly data before and during the COVID-19 pandemic breaking regular patterns. Based on this data, we test the performance of the suggested model against others ranging from simple exponentially weighted moving average (EWMA) to Holt-Winters; from autoregressive integrated moving average (ARIMA) combined with exponential generalized autoregressive conditional heteroskedasticity (EGARCH) models, to seasonal integrated autoregressive moving average (SARIMA) and denoised neural network autoregressive models (DNNAR). This study confirms that the suggested approach outperforms the baseline models mentioned above, is based on a single factor (thus reducing the model’s risk) and requires only the time series under consideration. The contribution to the literature is twofold: in terms of forecast accuracy and in terms of parsimony (both from the perspective of the data and the complexity of the modeling) when a regular pattern in the time series is disrupted.

I estimate CES aggregate production functions for the US, the UK, Japan, Germany, and Spain using data from the EU KLEMS database. I distinguish between three types of capital: information and communication technologies (ICT), intellectual property (IP) capital, and traditional capital. I assume that the aggregate output is produced using labor and these three types of capital and allow for differences in the elasticities of substitution between labor, an aggregate of ICT and IP capital, and traditional capital. The estimated elasticities of substitution between ICT and IP capital are strictly below one for all sample countries implying gross complementarity. ICT and IP capital together are gross substitutes for labor while traditional capital is a gross complement. The results for the US imply that the fast pace of technological progress in ICT and IP capital accumulation together are responsible for about 80 percent of the fall in labor income share.

In order to assess how well-suited the Nigerian environment is for implementing the just concluded currency re-design and cashless policy, this study evaluates the financial infrastructure and level of financial inclusion in the country. The report emphasizes Nigeria’s issues and constraints by contrasting it with other economies that have embarked on similar policy of demonetization. The results show that the atmosphere in Nigeria is not yet favorable for the policy’s successful implementation. Significant impediments included things like a weak legal system, poor financial awareness, and insufficient financial infrastructure. The study underscores how crucial it is to create a supportive climate before enacting such policies. The study suggests that decision-makers study the practices of other nations, like the US, the UK, and India, who have successfully implemented similar policies. Nigeria can create the essential conditions for the successful implementation of currency reform and cashless policies by studying their tactics and best practices. In conclusion, this study emphasizes how crucial favorable conditions, a reliable financial system, and adequate legislative frameworks are for the effective implementation of currency reform and cashless policy in Nigeria.

We provide new evidence about US monetary policy using a model that: (i) estimates time-varying monetary policy weights without relying on stylized theoretical assumptions; (ii) allows for endogenous breakdowns in the relationship between interest rates, inflation and output; and (iii) generates a unique measure of monetary policy activism that accounts for economic instability. By estimating monetary policy weights whilst accounting for periods where there is a breakdown in the relationship between the three key variables, we show that there is little support for the argument that inflation was inadequately targeted prior to the Great Recession. Moreover, the relaxation of key restrictions prevalent in existing research negates evidence that the over-targeting of the output gap during the 1970s contributed to the inflation experienced during that period. We also create a novel measure of time-varying monetary policy activism and show that evidence of a weaker trade-off between inflation and output over the past three decades is substantially a reflection of identification issues associated with increased monetary policy activism. After accounting for the latter, the slope of the US Phillips Curve with respect to the output gap rises from 0.2 to 0.5.

Using survey data collected in Germany and China, this paper ex amines the impact of patriotism on individuals’ fairness perception and preferences regarding inequality and on their attitudes toward economic policy involving inequality. Across surveys and countries, a positive and significant effect of blind patriotism on economic indi vidualism is found. For China, we also find a significant relationship between blind patriotism and the agreement to unequal economic pol icy. In contrast to blind patriotism, we do not find an association of constructive patriotism to economic individualism and to attitudes toward economic policy involving inequality. Political and economic implications based on the results are discussed.

External imbalances played a pivotal role in the run-up to the global financial crisis, being an important underlying cause of the ensuing turmoil. While current account (flow) imbalances have narrowed in the aftermath of the crisis, net international investment position (stock) imbalances still persist. In this paper, we explore the implications of countries’ net foreign positions on systemic risk. Using a sample composed of 450 banks located in 46 advanced, developing and emerging countries over the period 2000-2020, we document that banks can reduce their systemic risk exposure when the countries where they are incorporated maintain creditor positions vis-à-vis the rest of the world. However, only the equity components of the net international investment positions are responsible for this outcome, whereas debt flows do not contribute significantly. In addition, we find that the heterogeneity across countries is substantial and that only banks located in advanced markets that maintain their creditor positions have the potential to improve their resilience to system-wide shocks. Our findings are relevant for policy makers who seek to improve banks’ resilience to adverse shocks and to maintain financial stability.

In this paper, we provide theoretical and empirical evidence on how the bilateral trade balance affects the bilateral tourism flows. We investigate over 1600 bilateral tourism and trade relationships between developed and developing countries. We find that tourism flows from the developed country to the developing country increase as the bilateral trade deficit of the developing country increases. We observe that this relationship is stronger for the pairs of countries that are geographically closer. More importantly, we show that financial development of the developing country is an important contributing factor in this relationship. In this paper, we reveal the implicit government policies to promote the bilateral tourism, thus tourism sectors can benefit from these findings in order to forecast the trends. In absence of mature financial markets in the developing country, the developed country implicitly encourages tourism flows to the developing country, which prevents worsening in balance of payments between the countries. As a novelty to the literature, we provide evidence of the usage of implicit tourism policies by the developed countries under balance of payment hypothesis.

This paper investigates how deep integration affects productivity levels within the EU by utilizing theCompNet database. For this purpose, the paper constructs a measure for deep integration in the case of the EU by capturing various components of the EU agreement. The paper utilizes the EU wave instrument based on geographical proximity to tackle the endogeneity problem. The results from Instrumental Variable (IV) strategy reveal that there is a causal effect of deep integration on total factor productivity, labor productivity, and capital productivity across various sectors. Moreover, the paper investigates how this deep integration affects productivity decomposition based on Olley and Pakes (1996) across sectors. The findings show that deep integration enhances aggregate productivity and within-firm productivity across the EU. For robustness, the paper utilizes two additional EU wave instruments based on cultural and trade proximities to support the main results.

The great financial crisis has brought increased attention to the consequences of international reserves holdings. In an era of high financial integration, we investigate the relationship between the real exchange rate and international reserves using nonlinear regressions and panel threshold regressions over 110 countries from 2001 to 2020. We capture the buffer effect of international reserves is more pronounced in Europe and Central Asia above a threshold of 17%. Unlike previous literature, our study contributes the level of financial institution development plays an essential role in explaining the buffer effect of international reserves. Countries with a low development of their financial institutions may use the international reserves as a shield to deal with the negative consequences of terms-of-trade shocks on the real exchange rate. We also found that the buffer effect is stronger in countries with intermediate levels of financial openness.

In this paper, we analyze whether foreign investor-targeted firms improve their management quality and practices after acquisition by focusing on Foreign Direct Investments (FDI) occurring in Italy between 2010 and 2020. To proxy management quality, we resort to granular administrative data on ISO certificates held by Italian firms and find that firms acquired by foreign investors experience an increase in management standards, regardless of the country from which the FDI originates. This is not the case for firms involved in domestic M&As. Our empirical strategy controls for ex-ante selection, and findings are robust to a broad set of additional tests. They show that the positive effects of FDI documented in the literature can be partly attributed to improved managerial practices implemented in target firms.

This study investigates the response of China’s overall and sectoral stock returns towards COVID-19 vaccines, utilizing quantile-on-quantile regression and causality in quantile approaches. The empirical outcomes affirm that the higher quantiles of COVID-19 vaccine augment the higher quantiles of the Shanghai stock returns. Concurrently, the higher quantiles of vaccines negatively influence the lower quantiles of the Shanghai stock returns. On the sectoral level, basic materials, consumer discretionary, telecommunication, utilities, and industrial sector mirror the outcomes of the Shanghai stock market vis-à-vis the COVID-19 vaccine. Based on the underlying asymmetry, the study underscores that the COVID-19 vaccine bolsters the overall and sectoral stock returns when the market is performing well, and the effect of the former becomes hostile when the market exhibits bearish condition. The study findings apprise policymakers and investors about the disproportionate or asymmetric impact of COVID-19 vaccine on China’s overall and sectoral stock market returns.

Improving information disclosures and monitoring corporate commercial activities are the core content of commercial reform, which is conducive to providing commercial support for enterprises, creating a good commercial environment, and promoting high-quality economic development. In the decade from the global financial crisis to the COVID-19 pandemic, China implemented a series of digital technologies to accelerate the process of commercial reform. To explore the economic effectiveness of digitalization-based commercial reform, we manually collect the data of digitalization-based commercial reform in which the Market Supervision Administration in each city introduces a digital commercial registration system for improving information transparency and monitoring the commercial activities of firms. Using a large sample of Chinese listed firms and the staggered difference-in-differences research design, we find that digitalization-based commercial reform reduces firms’ stock price crash risk, and that it does so via improving information quality and enhancing monitoring for the firms. We also find that the commercial reform has a more pronounced inhibitory effect on stock price crash risk for firms with higher levels of digitalization and innovation and for those with worse governance structures. Overall, our findings highlight a potential benefit of the application of digital technologies in the regulatory reform for governments, encouraging them to use digital technologies to improve information disclosure and monitoring for firms, thereby promoting a more stable and efficient capital market.

This study employs the Structural Break Threshold Vector Autoregression (SBTVAR) models to examine the asymmetric effects of policy shocks on the return volatility of various asset classes. The results indicate that pandemic-induced economic policy uncertainty and national lockdowns triggered a structural break in the relationship between policy uncertainty and return volatility of stocks, commodities, oil, gold, and cryptocurrencies. Variance impulse response functions using GARCH structural errors reveal a regime shift in volatility linkages with varying responses across assets. Bitcoin was the most reactive to the policy shock, followed by oil, commodities, stock, and gold. Oil and commodities exhibited the largest differences in their responses before and after the structural break. The SBTVAR with a constant threshold and break outperforms the conventional VAR, Threshold VAR and Structural Break VAR by capturing the asymmetric dynamics of economic and financial risk factors.

This paper finds that Chinese stocks rise in February instead of January. Further analysis shows that the February premium is attributed to the Chinese New Year. We propose an explanation for this premium based on liquidity preference, i.e., investors prefer holding liquid assets before the holiday and illiquid assets after the holiday. This hypothesis is supported by the empirical evidence of a substantial decrease (increase) in the monetary base and a significant increase (decrease) in market activity after (before) the Chinese New Year. The empirical fact that the Chinese New Year effect is particularly strong for stocks with low institutional ownership, small-cap stocks, and illiquid stocks also supports this hypothesis. The explanation for the Chinese New Year effect in this paper may offer valuable insights into the turn of the year effect found in many countries.

This study proposes a stricter criterion for resolving the low-beta anomaly (LBA), arguing that subsuming the observed betting-against-beta (BAM) alpha, a typical signal as resolving LBA, does not guarantee sufficient resolution. Any return drivers negatively biasing the betareturn relationship can induce LBA, but the observed BAM alpha cannot capture them all. Those uncaptured may induce a BAM alpha orthogonal to an explanation fitting the observed BAM alpha. Thus, a sufficient explanation should capture most potential LBA drivers. We design a test accordingly and find that prevailing explanations claiming to resolve LBA do not meet this stricter criterion. A new stronger BAM alpha emerges, indicating that much about LBA remains unknown despite what we know. We derive the necessary conditions for adopting the stricter criterion and test, justifying the empirical results. The findings also explain why negative beta-alpha relationships should be pervasive for other factors/anomalies.

This paper adopts direct measures of firm spending on bank relationship and loan contracting from a recent survey on small and median enterprises (SMEs) in China to systematically examine their inter-connections. Our findings are twofold. First, bank relationship spending significantly alleviates SMEs’ financial constraints and such effect is heterogeneous across regions with varying degrees of economic growth but not across industries. Second, while bank relationship spending allows SMEs to access more bank credit and longer maturity loans, it also leads to higher interest rates, guarantee requirement and overall dissatisfaction of loan services. Our findings shed new light on the role of ‘Guanxi’ in China’s micro-credit market and its consequences.

The present study estimated the burden of diseases of shrimp cultivators in Jagatsinghpur district of Odisha. Data were collected by using simple random sampling. The sample size is 356. Disability-adjusted life years (DALY) was used to measure the health status of shrimp cultivators. DALY is the summation of the burden of disease from mortality and morbidity. Sensitive and uncertainty analysis is used by changing the value of the parameter and method, respectively. The total loss of healthy life years in 2020 ranges from 101.03 years based on equal age weightage, without discount rate, and potential life expectancy (DALY0, 0, PLE) to 84.02 years based on unequal age weightage, discount rate, and standardized life expectancy (DALY1, 0.03, SLE). The higher burden of diseases from non-communicable diseases is followed by injury and communicable diseases for both methods. The disease burden from mortality is more than two-thirds of the total disease burden, and the rest from morbidity. The top five subcategories of disease burden are mental disorders, cardiovascular diseases, diabetes, musculoskeletal diseases, and digestive diseases among shrimp cultivators. DALY is sensitive to parameter changes because it changes between 92.10 and 63.03 with the change in the parameter. Uncertainty in DALY is due to method variation, which ranges between 120.03 and 74.06. The government should strengthen health care provision in shrimp-cultivated areas and create awareness among shrimp cultivators to maintain a sustainable lifestyle to reduce the burden of diseases among them. The limitation of the present study is not adjusted for the prevailing comorbidity.

Vaccine manufacturing in India has historically been centered around producing a wide-variety of conventional vaccines that made the country self-sufficient as well as a net exporter of basic vaccines. However, overtime, other safe and efficacious vaccines that follow technologically more advanced manufacturing processes became available in the market against some high burdened diseases, their increased uptake made the country import dependent in both UIP and non-UIP categories. In the second half of 2000s when manufacturing capacity of public sector was being dismantled, India became a big market for imported vaccines since then and export affected adversely. Despite such repercussions, India continued to enjoy comparative advantage (RCA>1) due to high acceptability of Indian vaccines in developing countries market. High R&D intensity and active State support are critical for making the country self-reliant and self-sufficient in vaccine development and manufacturing, and addressing future health challenges like the Coronavirus.

This work aims to analyze poverty in Morocco through a multidimensional approach in times of crisis. This paper aims to contribute to the clarification of the concept of poverty and review the body of work, both theoretical and empirical, that has dealt with poverty, specifically its approaches, profile, evolution, and dynamics. The originality of this subject is justified on the one hand by the accelerated changes that the globe has experienced, especially after the Covid 19 pandemic and their consequences on the accentuation of poverty levels in several countries. On the other hand, in the case of Morocco, we have assisted in generalising social protection to all citizens, including those with low incomes. In the same sense, the review of the efficiency of social aid policies has been the subject of debate, the result of which is the setting up of a unique social register on the Moroccan territory. On a methodological level, we will adopt a descriptive study. The aim is to present a conceptual and theoretical framework for a multidimensional analysis of poverty. Then, an overview of poverty in Morocco will be presented, and finally, observations will be made based on this conceptual, theoretical, and descriptive analysis.

Background: Performance of the F-test critically depends on the distributional assumptions and the choice of robustness measures. The robustness of F-test to non-normality has been studied and validated in literature however, the assumption of homogeneity has not been given due attention in literature. Regarding robustness measures, F-test is not evaluated against both the liberal and conservative criterion simultaneously. This study provides a systematic examination of F-test robustness to violations of normality and homogeneity in terms of Type I error, considering a wide variety of distributions commonly found in psychology, social and medical sciences. Method: This study conducted Monte Carlo simulations to compute the Type-I error rates of F-test under non-normality and heterogeneity assumption. To assess the Type-I error rates, 100,000 samples were generated with 1900 scenarios to ensure reliable results. The manipulated parameters include shape and scale parameters of distributions, number of groups, equal and unequal sample sizes, total and average sample size, inequality in the sample size and variance ratio. Results: The findings of this study show that the robustness of the F-test in terms of Type-I error rates depend on the choice of robustness measure, variance ratio, sample size, and equality of samples. The F-test is robust under a threshold value of variance ratio when evaluated against liberal criteria and non-robust against conservative criterion.

A large literature has established that mental health is negatively correlated with smoking behavior. We contribute to this literature by providing causal estimates of mental health using an instrumental-variables model that controls for individual-level fixed effects. Such a model is identified via the death of a close friend as a source of exogenous variation in mental health. This estimation approach, combined with 16 years of longitudinal data from Australia, tackles the problems of reverse causality, unobserved confounders, and measurement error. The results show that mental health has a significant negative impact on the likelihood of being a current smoker. This general conclusion is robust to alternative methods of addressing the endogeneity of mental health, including the use of both internal and external instruments, two-stage residual inclusion estimation, and dynamic panel methods. As such it could be useful in raising awareness about the power of people’s mental health in shaping their smoking behavior.

The response to the COVID pandemic has varied widely across countries and over time. In this paper, we analyze the determinants of COVID restrictions both theoretically and empirically. Consistent with our model’s predictions, we find that the COVID protocol increases with the burden on the healthcare system especially in countries with lower levels of trust and productivity. We also find that the country-level introduction of vaccines helped governments achieve a better trade-off between healthcare and economic costs. Overall, the results provide novel insights on how cross-country cultural and institutional heterogeneity affect policy making.

Many developed countries have seen employment shifting away from middle-paying occupations towards both higher and lower paid ones. This polarization phenomenon is often explained by Routine Bias Technical Change. This paper offers a complementary explanation that emphasises the increase in skill supply and the endogenous adoption of technology. I exploit the large policy-driven expansion of higher education in the UK and show three stylized facts that support my model. My counterfactual analysis suggests that the shift in skills supply alone can account for between a third and two thirds of the actual decline in routine manual occupations.

This paper studies the impact of international economic sanctions on income mobility at the Macro level. A series of economic sanctions were imposed on Iran during 2007-15 and lifted to some extent in 2015. Using some pseudo-panel datasets, constructed based on 18 household surveys during 2001-2018, we investigate the impact of sanctions on four income mobility measures: directional income movement, positional movement, time dependence, and mobility as an equalizer of longer-term incomes. The results show that in the sense of directional income mobility, the sanctions are followed by welfare losses for all income groups, with richer groups experiencing larger losses than poorer ones. The rich face income declines that are larger compared to those experienced by the poor, and this causes: first, richer (poorer) groups to face a higher probability of moving downward (upward) in relative terms, thus we see an increase in positional income mobility (and also time dependence) with the sanctions; and second, an increase in mobility in the sense of equalizer of longer-term incomes. We get the opposite results with the removal of sanctions.

Human capital constitutes a significant ingredient of economic growth. As more and more countries are moving on the path of growth and development, one needs to explore the contribution of human capital in economic growth. Considering health and education as two components of human capital, the paper attempts to achieve three-fold objectives. First to examine the status of health and education in both countries for the period 1970-2019, secondly to comprehend the role of public expenditure on health in economic growth and finally, to examine the role played by human capital comprising of both health and education components in the economic growth of both the nations. To achieve the first objective, the paper attempts to construct the Index of health and education in India and China, also comparing it with the South Asian region. Public health expenditure by the government (PHE), out-of-pocket expenditure (OPE), Life Expectancy (LE), and Access to health care (HC access) are selected as indicators of health, while educational attainment at least completed upper secondary, population 25+ (EDU) indicating the access to education, Literacy rate (LR) and number of patent applications by residents (PA) are considered as indicators of education. Both health and education indices are constructed using the Principal Component Analysis (PCA) method. The study uses the Vector autoregression (VAR) model to examine the causality between the countries’ public health expenditure and economic growth by deploying the Engel-Granger Causality test. Finally, an endogenous growth model is run, selecting the appropriate variables, and considering health and education indices as inputs. The study observes uni-directional causality between public health expenditure and economic growth, GDP granger causes PHE in India and China. Both health and education indexes have a positive impact on growth in India and South Asia however, the results of regression depict that health and education negatively affect the growth rate in China. The paper holds great relevance in terms of policy implications highlighting the need for developing nations to invest in human capital, both health and education. It is crucial to comprehend the significance of accessibility of health and education by removing the political economy and making these facilities more inclusive.

Academic standards, even within a single college, can vary a lot-from one instructor to another. Empirical and theoretical research suggests that the various grading practices in different contexts can be motivating, neutral, or demotivating to the students. To understand the dynamics of student motivation under the various grading treatments, Galiullina (2022) builds a two-period theoretical model of extrinsic motivation. The model allows to channel the effects of the initial grades on further effort through the lenses of the student grade targets, self-beliefs, and explanatory styles. I design a lab experiment to test the model predictions. I impose an absolute grading standard, and offer monetary rewards to students who achieve a certain GPA level. To introduce an exogenous shock to the grading standard, I randomly and blindly assign the subjects’ initial grades to be rounded either upwards or downwards. Despite a modest sample size, the results mostly support the model: the students do adjust their study behavior based on their initial grades, the predicted negative marginal grading effect shows up, and the beneficial effect of the growth mindset is confirmed. My data, however, overwhelmingly refute the conjecture that is widely applied in the literature: that the grading incentives completely crowd out intrinsic motivation. Contrastingly, the students tend to invest too much into costly training for it to be justified solely by extrinsic motivation. I conclude that even under the strong extrinsic incentives, intrinsic motivation can maintain an important role in learning.

Exposure to crime and violence associated with drug trafficking has been shown to have negative consequences on students’ health, peer relationships, academic achievement, and educational attainment. However, little attention has been devoted to analyzing the consequences of drug trafficking on truancy behavior, a critical outcome with a high cost at an individual and societal level. This study investigates the connection between exposure to drug trafficking (an increasingly common form of chronic crime and subsequent violence in Latin America) and school truancy in Costa Rica. To do so, we use a unique and comprehensive microdata set that merges detailed information on cocaine confiscations and socioeconomic characteristics of Costa Rican districts with student and school data from the Programme for International Student Assessment (PISA). In total, we obtain a sample of 4,584 students in secondary education attending 200 schools in 147 districts. Using logistic regression with school and district fixed effects to deal with unobserved heterogeneity, we find that students in districts with higher exposure to drug trafficking (measured by cocaine confiscation rate) are more prone to school truancy. This finding suggests that strategies to tackle school truancy should take into account a neighborhood context perspective.

In India, adolescent girls are among society’s most vulnerable groups as they are exposed to risks that challenge their healthy development into young women. India’s Rajiv Gandhi Scheme for the Empowerment of Adolescent Girls (SABLA) program was designed to address such challenges by building health awareness and encouraging decision-making autonomy as the first steps towards real change in women’s development in the country. Using data from the nationally representative India Demographic and Health Survey (IDHS), with plausibly exogenous variations in the program’s rollout across districts and birth cohorts, we provide evidence that exposure to SABLA increases the likelihood of young female participants having knowledge of family planning and diarrhoea treatment, using contraception, and having autonomy in their personal financial decision-making. The effects are more pronounced for women who reside in urban areas, have completed secondary education or higher, and primarily for Muslim women.

Contraceptive usage is a crucial tool that empowers women to control their bodily autonomy and reproductive outcomes. At the same time, violence against women remains a pressing pubIic health issue worldwide depleting women’s autonomy. In this paper, we establish a causal link between the decision to use contraceptives and the occurrence of intimate partner violence. We use a nationally representative survey data from the fifth wave of the National Family Health Surveys of India for 2019-21 to estimate our causal effects. To address potential endogeneity in the decision to use contraceptives, we utilize an instrumental variable approach. Using exogenous variation in the cluster average of women’s exposure to family planning messages via radio as an instrument, we show that if the decision to use contraceptives is solely taken by the woman, she is at a significantly higher risk of IPV. The results point to greater likelihood of physical, sexual as well as emotional domestic violence. Our findings underscore the importance of increasing focus on sexual and reproductive health concerns in the existing initiatives that aim to reduce the prevalence of domestic violence. The heterogeneous results by employment status of men and women also call for an expansion of government programs aimed at improving men’s understanding of the use of contraceptives and family planning

I examine how the provision of a job amenity at the firm level can affect the process of attraction and retention of workers, generate compensating differentials in wages, and influence wage trajectories and promotions over time. I analyse the impacts of a program that allowed Brazilian firms to extend the length of maternity leave offered to their workers from 4 to 6 months. Using a linked employer-employee dataset that covers the universe of formal employment in Brazil, I estimate the effects of the introduction of this amenity by analyzing roughly 50,000 firms that adopted the program at different points in time. I find evidence of compensating differentials, with an average reduction of female wages of around 3%. I also document that the effects of the policy do not manifest immediately and are mainly driven by new hires, indicating some degree of wage rigidity in the market. While adopting the program leads to a small increase in the share of female workers at the firm level, the proportion of women in high-skill positions shows a significant and persistent decline of almost 10%. This group of workers is 43% more likely to use extended maternity leave in comparison to low-skill workers. Finally, I estimate that a worker using extended leave is 12% more likely to be dismissed within two years after birth when compared to workers using the baseline level of maternity leave.

When individuals are not engaged in occupations according to their ability or ‘talent’, we observe talent misallocation in an economy. This paper shows that talent allocation improved in India over 1983-2012. To explain this, I compute similarity indices and examine the patterns in educational attainment and wages for marginalised (relative to privileged) gender and caste groups. I then use the reduced form approach to relate these indices with talent allocation. The paper’s findings suggest that the improvement in talent allocation is correlated with the decline in labor market discrimination and barriers to educational attainment towards marginalised groups. Furthermore, using the decomposition technique, I find that convergence in educational attainment among these two barriers accounts for most of the improvement in talent allocation.

We provide the first empirical evidence that prostitution is a substitute for marriage. Exploiting the adoption of the Nordic model of penalizing sex buyers, we find that restraining commercial sex leads to a significant increase in marriage rates and a significant decrease in divorce rates. These results are mainly driven by marriages among young people and marriages among previously single people (compared to those who were previously in legal unions). We further show that the substitution effect of prostitution on marriage is stronger when female’s socioeconomic status is weaker and when people prefer marriage over cohabitation.

This paper takes advantage of a natural experiment, in which Soviet Jewish immigrants were quasi-randomly allocated to the U.S. and Israel. I find that young women who immigrated as children follow similar fertility profiles in the two host countries. In Israel, they are also similar to native-born women by exercising almost no selection into motherhood and postnatal labor force participation. By contrast, and away from native-born American women, immigrants to the U.S. either combine family and career or become low-educated non-working mothers. This non-trivial segregation arises from a combination of the American Dream with origin-determined fertility norms.

Education choice produces uncertain income. We investigate how education choices in terms of an individual’s highest qualification and the field of study contribute to future earnings. Traditional analysis of returns to education tends to focus on average or median earnings rather than analysing the whole distribution of earnings. However, there is variability of earnings and it is important to take into account this risk component into modelling returns to education. Therefore, we analyze the full distributional impacts in terms of risk and returns of education on earnings. We use GAMLSS regressions to estimate different shapes of earnings distributions for our 45 education categories by modelling the first four moments of the earnings distribution (mean, variance, skewness and kurtosis) as functions of our education categories and a rich set of socio-demographic and ability controls. We find substantial differences in the shape of earnings distributions across our education categories. There is no single ranking of education categories like on the mean with OLS, hence risk preferences matter in choosing field of study. Thus, it is important to consider the full distributional impact and include the risk component when modelling returns to education. Our findings have practical implications for individuals, as higher education is a major financial decision, and a thorough understanding of the relationship between education and future earnings helps students to make informed decisions about their education. There are also applications in public policy from a fiscal policy perspective, such as public investment in education and student loan programs.

Legal aid to indigent defendants is omnipresent in developed countries. While it is commonly justified on social justice grounds, understanding its impact on its recipients is a task of primary importance which has so far been ignored. This paper makes the first moves in filling this gap, leveraging two empirical strategies—fuzzy regression discontinuity design and double machine learning—to quantify the effect of being refused legal aid on court outcomes, in the context of serious crimes. In my sample, the counterfactual to receiving aid is hiring a private lawyer, rather than self-representation. Both locally and globally, I find evidence that public defence provides services similar to those provided by (counterfactual) private firms. Hence the main difference between these two modes of legal services provision is then on whom the burden of legal costs falls—the government or indigent defendants.

Eradicating poverty worldwide is the first primary target of the United Nations 2030 Agenda for Sustainable Development. China, the largest developing country, has an enormous population living in poverty, so combating poverty is of vital importance to China for achieving its development goals. In this context, the Chinese government held the National Conference on Development-driven Poverty Alleviation in December 2015 and thereafter issued policies to call for corporate participation in reducing poverty. Yet, engaging in poverty alleviation requires considerable resources, plausibly increasing a firm’s financing needs. Against this backdrop, we investigate whether Chinese firms’ involvements in poverty alleviation affect their costs of financing. We find causal evidence that firms’ contributions to poverty alleviation result in lower cost of equity and lower cost of debt, suggesting that poverty alleviation is appreciated by both equity investors and debt investors. This result is more pronounced for non-state-owned firms, financially healthy firms, firms receiving more subsidies from local governments, and firms with larger spending in advertisements. Our mediating analyses further reveal that enhanced reputation and trust among stakeholders are the mechanisms through which corporate alleviation of poverty reduces the costs of financing. Overall, our findings highlight to firms a potential benefit of their involvement in poverty alleviation, thereby encouraging them to make greater contributions to poverty eradication for their countries.

The global financial crisis has affected all countries during the period 2007-2014. Tourist companies, especially in Italy, play a significant role in the economy of a country. The performance of tourism companies, and in particular hotels and travel agencies and tour operators, will be analysed in this paper, relative to the period of the crisis. The aim of this paper is to analyze profitability dynamics of the aforementioned tourist companies, to check whether they have suffered the effects of the global crisis. To this end, data from AIDA database relating to Italian companies in the sector were used. The profitability of these companies has been analyzed using the main profitability ratios, ROI and ROS ratios. An analysis of the trends and ANOVA of these ratios was carried out for the period 2007-2015. In this way, it has been verified whether the global crisis has affected profitability dynamics of hotels and travel agencies and tour operators in Italy. There is a parallelism in the trends of the main operators’ indices in the three Italian macro-regions. The best performance is in the South, in a less developed economic context. The crisis has reduced the income indices in the first three years, even if the figure remains positive. Since 2012 there is a clear recovery, especially for hotels; intermediaries, on the other hand, suffer from competition from websites. However, the indices confirm the close relationship between travel agencies, tour operators and hotels. ROI mainly rewards first, while ROS intermediaries.

Flawed research can be harmful both within and outside of academia. Even when published research has been retracted and refuted by the scientific community, it may continue to be a source of misinformation. The media can play an important role in drawing broader attention to research, but may also ensure that research, once retracted, ceases to feature in popular discourse. Yet, there is little evidence on whether media reporting influences the retraction process and authors’ careers. Using a conditional difference-in-differences strategy, this paper shows that articles that gained popularity in the media at publication and were later retracted face heavy citation losses, while subsequent citations become more accurate. Further, authors of such papers see a permanent decline in research output. Lastly, the paper provides evidence that media can influence both the likelihood of retraction and its timing, highlighting that the media can play an important role in contributing to the integrity of the research process.

The theft of copper cable in Medellín generates costs for the most representative telecommunications company in the city and for society. This study finds that for each criminal event of this sort in a year the risk of loss of assets is between 83% and 98%. Combining robustness analysis, survival analysis and spatial econometrics, by event (location of theft) and by neighborhood, this research concludes that the increase in expected loot and the presence of the ConectarTV network both raise the risk of loss and encourage the crime to happen earlier in the year. On the contrary, greater cost (or effort) to carry out the theft decreases it risks and postpones it. These results are consistent with the economic theory of crime.

An abundant body of literature has developed on the effect of gender on the adoption of agricultural technologies, but the works on this theme have been carried out across several regions and with very different estimation methodologies. Despite the abundance of work on the issue, no synthesis of this subject exists to date. Few systematic reviews have recently been produced on the adoption of agricultural technologies. However, these works do not specifically address the gender aspect and may produce limited information regarding the importance of gender in technological adoption. Moreover, these systematic reviews are limited to only one type of technology (improved varieties) or good agricultural practices and are often focused on a particular geographical context. To fill this gap, this study involves a quantitative synthesis of the literature on gender and agricultural technology adoption at a global scale. It is based on a selection of 124 empirical studies that yield a total of 274 observations. The results show that the heterogeneity of the effect of being a woman on the adoption of agricultural technologies depends on several factors and that, on average, being a woman decreases the probability of adopting an agricultural technology but this varies according to the type of agricultural technology. This effect is negative and significant for improved seed varieties and not significant for technologies such as good agricultural practices and fertilizers.

There are indirect network effects between electric vehicles (EVs) and charging piles, including pile-to-vehicle and vehicle-to-pile, which have an important impact on EV adoption. When one of the parties is affected by local EV subsidy termination and the epidemic, what will the indirect network effect change? This paper aims to reveal the change law of indirect network effects between vehicles and piles under the influence of such external factors. Based on the provincial monthly panel data from July 2018 to January 2021 in China, by constructing 2SLS models and designing new instrumental variables, this paper finds that the two indirect network effects both declined after the subsidy termination (70.42%, 53.33%, respectively), and rebounded after the outbreak of the epidemic (20.47%, 128.57%, respectively), showing the dynamics. The dynamics can exacerbate the impacts of policy interventions, reflecting the enhanced effect. The pile-to-vehicle indirect network effect is larger, indicating the asymmetric. In addition, ignoring the dynamics will lead to the measurement bias of the indirect network effects at different stages. These findings enrich the theoretical study of indirect network effects, and also provide references for governments to better formulate promotion strategies for electric vehicles and charging piles after the local EV subsidy termination and the epidemic.

What are the economic effects of administrative delays? I analyze this question in the context of the United States Patent and Trademark Office, where delays can lead to a lengthening of the patent term. The consequences of this unique setting, where private benefits may result from public inefficiencies, however, remain questionable. To identify the effects of this constellation, I exploit the quasi-random assignment of patent applications to examiners as source of variation in the patent term length. I find that a delay-induced prolongation of the patent term positively affects innovation value, but has a negative effect on follow-on innovations. This implies that the social impact of delays in the patent office is negative, while the patent holder benefits from a prolonging adjustment in the patent term.

Achieving universal access to clean energy requires a transition from high-carbon-intensive fuels to less carbon-intensive options. However, several factors can prevent countries and households from reaching this goal. One such barrier is the impact of civil conflict on households’ clean energy choices. This study looks at how Nepal’s decade-long civil conflict between 1996 and 2006 affected household access to clean lighting and cooking fuels. Our findings show that higher levels of conflict intensity decrease the likelihood of households having access to clean energy sources. Further, we propose household income loss, market and infrastructure destruction, and resource shifts towards defence as possible mechanisms through which conflict affects household clean fuel choices. This result reveals the important, but often overlooked, negative effect of civil conflict on the clean energy transition in developing countries.

The study attempts to examine the relationship between economic growth, energy consumption, trade openness, carbon dioxide emissions, urbanization, and the human development index in five Southeast Asian countries between 1991 and 2020 using the fixed effect and random effect models. Results of the feasible generalized least squares model demonstrated that economic growth and urbanization may accelerate the human development in five selected Southeast Asian countries. Surprisingly, it has been empirically found that renewable energy consumption, trade openness, and CO2 emissions do not have relationships with the human development in the region. Finally, policies are recommended to improve the human development index and achieve sustainable development for the region.

There has long been interest in understanding how learning is manifested in financial markets and in macroeconomic policy. If learning is relevant in financial markets and macroeconomic policy, we hypothesize that countries that have experienced a financial crisis or more would have fared better economically and in their financial systems in the wake of the COVID-19 pandemic. Employing dataset that covers many regions of the word, the study provides the following results: first, crisis experience increases the efficiency of the financial system; second, the pandemic crisis reduces the level of credit supply but increases the level of stock traded. Finally, crisis experience positively compliments the negative impact of the COVID-19 pandemic on credit supply. The results are robust to an array sensitivity check including control of alternative methodology, variable specifications and the institutional quality.

The aim of this study is to analyse the effect of inequalities on water and electricity supply on homicide. This study uses panel data on intentional homicide rates and inequality for a sample of 21 sub-Saharan African countries over the period 2000-2015, based on information from the United Nations World Crime Survey, World Bank data and the World Development Indicator, to analyse the effect of inequality on intentional homicide. A climate model incorporating inequality is estimated using the Pooled OLS method and the DCM method. These estimators take into account unobserved country-specific effects, the joint endogeneity of some of the explanatory variables and the existence of certain types of measurement errors affecting the homicide data. The results show that inequalities on water and electricity supply increase the rate of intentional homicide. Furthermore, by performing a long-run dynamic fixed effects analysis, the results showed that inequalities in access to water and inequalities in access to electricity will increase the more significant and robust coefficients of the intentional homicide rate if governments do not implement better strategies.

The use of financial instruments is attracting attention in the quest for sustainable development. There is an ongoing debate as to whether the development of financial markets will lead to a reduction in pollution emissions or their expansion. Using an R&D-based growth model with money, this study analyses the impact of monetary policy under environmental taxes and emission quotas on growth and welfare, and identifies the relationship between pollution emissions and financial development. The analysis shows that increasing the environmental tax rate and reducing the nominal interest rate as well as the CIA constraint in innovation sector leads to pollution reduction and economic growth, as well as an expansion of money volume and credit due to deflation. On the other hand, reducing emission allowances leads to sustainable development. Besides, through the credit expansion effect of deflation and the credit contraction effect of money holdings, a U-shaped relationship is created between emission allowances and credit. As emission allowances cap output, the Fisher effect and welfare effect of monetary policy disappear. Finally, the policy mix of environmental and monetary policy determines trade-offs or win-win relationships between pollution emissions and financial development. These results suggest that the impact of financial development on emissions may depend on monetary and environmental policies.

This paper studies the effect of gasoline price shocks on food prices. We use data on the prices of aggregate and disaggregate food products to estimate a partially identified structural vector autoregressive model using Bayesian methods. We found that a positive gasoline price shock leads to a significant increase in the aggregate food price along with the prices of disaggregated retail food items. Furthermore, we found that higher gasoline prices trigger a significant increase in the price of fertilizers and animal feed leading to an increase in the cost of producing food products. Our results, however, suggest that higher gasoline prices do not significantly increase the food marketing cost. Finally, we conduct a historical counterfactual analysis and find that higher gasoline prices contributed to the increase in the aggregate food price as well as the prices of cereals and dairy products during the 2005-2007 period and following the onset of the Russia-Ukraine conflict.

In modern developed economies, one of the primary objectives is to manage the transition from polluting to cleaner technologies as efficiently as possible. By now, in the current empirical literature, one can identify technological spillovers from environmental innovations as a major driver of this process. Specific energy policy aspects connected with industry behaviour have yet to be explored. The aim of this paper is to investigate energy efficiency via environmental innovation and the resulting degree of resilience and adaptation of both developed and developing countries. The work applies the non-parametric DEA (Data Envelopment Analysis) framework and Tobit analysis. For this scope, it is built a panel dataset made of some 5000 observations based on energy policy and sustainable development variables for 136 OECD and non-OECD countries. The results show that knowledge spillovers from environmental innovations reduce inefficiency and therefore strengthen the resilience of economies that decide and manage to invest adequately in the transition to more sustainable technologies. Besides, OECD countries improve their energy efficiency scores over time, whilst non-OECD countries do not. This implies that sustainable technologies transition is made more efficient by environmental innovation but the process is fostered by disposing of a resilient economic system – hence, vulnerability can affect the transition. These hypotheses lead to important economic, social and environmental implications for energy policy modelling.

Agricultural land markets are relatively illiquid. Although complete samples are available for many areas, the number of farmland price observations is relatively small, especially when it comes to spatially disaggregated data. Due to the regionally heterogenous characteristics of land, available data at the small-scaled spatial level is essential for agricultural land market research and practice. Therefore, the aim of this study is to improve farmland price data by ap-plying the small area estimation. We do this exemplarily for the German federal state Branden-burg. Within this, two challenges are focused: (i) given direct estimates for communities (in-sample communities) with one or more transactions are re-estimated, and (ii) out-of-sample communities are added. Previous findings from hedonic farmland price models are used to se-lect auxiliary variables. As a result, robust and plausible farmland price estimates are generated for 416 communities in Brandenburg.

Energy prices fluctuation remains a key global issue given the spillover effects to other macroeconomic factors. Additionally, it has been argued that global uncertainty is a significant cause of these fluctuations. Through that aim, the current study examines the impact of global uncertainty on energy price exuberance using monthly data from January 1990 to October 2022. The supremum augmented Dickey-Fuller (SADF) and Generalized-SADF (GSADF) tests were initially utilized to identify energy price exuberance during the study period. In line with this, the study observed seven episodes of price exuberance, six of which were related with bubbles and one with bursts. Furthermore, the study carried out a logit model analysis to determine the impact of uncertainty on the identified periods of price exuberance. The study found GPR acts, and Ukraine GPR have a significant and positive effect on price exuberance, however Russia’s GPR has a negative effect on bubble formation. To this end, the study recommends the establishment of a buffer system and safe passage for the flow of energy supply in the event of geopolitical conflict or a major global event that could have a spillover effect on energy prices.

This article presents an economic examination of paddy cultivation in Malaysia, specifically analyzing the Malaysian Agriculture Development Authority (MADA) and the Integrated Agriculture Development Authority (IADA) BLS schemes. The study evaluates the feasibility of these schemes through benefit-cost ratio analysis and machinery performance evaluation, while 80 face-to-face survey interviews provide qualitative data. The study emphasizes the need to mechanize certain paddy cultivation activities, particularly fertilization (spraying), to minimize health hazards. The results indicate that IADA BLS yields nearly 50% more paddy than the national average, while MADA’s production expenses are lower due to a higher proportion of self-owned farms. The research highlights the importance of government subsidies and incentives to maintain paddy farming and suggests prioritizing the mechanization of paddy cultivation in future agricultural plans to improve the industry in Malaysia. The paper further recommends that the government consider raising the minimum guaranteed price of paddy grain to ensure economic viability for future generations and introducing a rental incentive to support landless farmers.

Conditional quantile regression has been considered in the spatial econometric literature as a robust alternative to the standard linear regression when data are characterized by non-normality. They are also complementary to the conditional mean model in that they provide a complete representation of the conditional distribution of Y given the predictors and not only their conditional mean. So far the literature concentrated on conditional quantile spatial lag specifications which incorporate spatial correlation in the form of a spatially lagged variable included in the list of predictors. This paper aims at exploring the other side of the moon by specifying conditional spatial quantile models in the form of a spatial error correlation and by suggesting feasible estimators of the parameters involved. We propose a procedure analogous to the feasible GLS suggested for the standard linear models, we illustrate its use on real data and we examine its small sample properties through a set of Monte Carlo experiment. The estimator is demonstrated on empirical example on housing prices in Germany.

The continued deviations of house prices from their fundamental value due to macroeconomic policy changes have continued to catch the attention of academics and policymakers across the globe. A boom in residential property prices witnessed between 1996 and 2006 resulted in the 2008 global financial crisis after the bust of house prices in 2007. The substantial increase in residential property prices is further witnessed during the Covid 19 lockdown from 2020 to 2022. The study explored the causes of the boom-bust of residential property prices. The study estimated the long-run effects of interest rates, mortgage finance, inflation, economic growth, and money supply on housing prices using the Johansen cointegration and monthly data from January 2001 to July 2021. The study found a significant long-term association between money supply, inflation rate, economic growth, and interest rates on house prices. The data also revealed no discernible relationship between mortgage loans and home prices. The variance decomposition illustrated that economic growth accounts for 25%, inflation level accounted for 15%, mortgage finance 0.1%, money supply 4%, and interest rates 13% of the changes in home prices. The study concludes that policy changes significantly influence house prices and recommends that macro and micro-prudential supervision and maintaining inflation within the inflationary targeting framework should remain a priority.

In this paper we propose a new methodology for the estimation of fundamental property asset-level investment time series performance and operating data based on real estate investment trusts (REITs). The methodology is particularly useful to develop publicly accessible operating statistics for investment real estate, such as income or expenses per square foot. Commercial property operating statistics are relatively under-studied from an investment perspective. We show how the methodology can be used to estimate the time series of property values, net operating income, cap rates, operating expenses and capital expenditures, per square foot of building area, by property type (sector) at the quarterly frequency for multiple specific geographic markets from 2004 through 2018. We show illustrative empirical results for Los Angeles offices and Atlanta apartments. The methodology allows estimation of actual quantity levels, not just dimensionless index numbers (longitudinal relative). It allows for an ”additive” model structure that is more parsimonious, thereby addressing the need for granular market segmentation. We also introduce a Bayesian framework that allows the estimation of reliable time series even in small markets.

A spatially dispersed market for a tradable good is deemed integrated if there are no barriers to trade between its spatial segments (except for geographical barriers, namely distances between the segments). The law of one price usually serves as a criterion of integration. However, perfectly integrated markets are not a common case; as a rule, a market deviates from this ideal state. Therefore, estimating a degree of integration is more helpful then an answer of the type ‘all or nothing’ (whether the market is integrated or not integrated). In an integrated market, price for a good is determined in the national market as a whole, not depending on demand in its spatial segments. Hence, a dependence of local price on local demand (controlling for transportation costs) indicates a deviation from the law of one price, and its ‘strength’ can measure the degree of market integration. Based on this idea, we estimate the annual integration degrees of the US market for an aggregated good (grocery basket) over 15 years, 2001-2015. The spatial segments are represented by cities; our spatial sample covers 68 cities from 39 states of the US. The results suggest that the US market is not perfectly integrated; however, the integration degree of the US market is fairly stable over time. We also compare results for the US with results of a similar study for Russia. With a reservation that the empirical material is not fully comparable, we can conclude that the US market is integrated more strongly than the Russian market and that the integration degree in Russia is more volatile.

Barsky and Sims (2012, AER) demonstrated, via indirect inference, that confidence innovations can be viewed as noisy signals about medium-term economic growth. They highlighted that the connection between confidence and subsequent activity, such as consumption and output, is primarily driven by news shocks about the future. We expand upon their research in two significant ways. First, we incorporate the Great Recession and ZLB episodes, and second, we employ unique state-level data to offer insights into how to interpret the relationship between consumer confidence and economic activity. Our results confirm the main finding of Barsky and Sims (2012) that this relationship is predominantly driven by news about the future.

This article explores the evolution of spatial disparities and spatial dynamics of economic activities in Morocco, focusing on issues related to the convergence of living standards among regions and the economic catch-up of lagging regions. The study uses Classical Sigma and Beta Convergence Analysis, as well as the Shift-Share method, to understand regional economic development and the various contributions made by different regions in Morocco towards this development. The article also discusses the key factors that influence the convergence of living standards and the need for implementing public policies and tailored funding mechanisms to mitigate spatial disparities and promote well-balanced development across regions. The findings suggest that despite attempts to decrease regional disparities in Morocco, the efforts were not successful in significantly reducing the gaps. The analysis of Structural Variation, value added at the basic price, allocation effect, and competitive advantage demonstrates significant disparities in production and economic development among different regions of Morocco, highlighting the need to direct public policy and investments towards more dynamic sectors and regions. The article concludes by emphasizing the importance of implementing effective public policies aimed at reducing regional inequalities and improving the well-being of populations in the most disadvantaged regions.

This study investigates whether an increase in women’s political empowerment is associated with better air quality outcomes. Women display stronger environmental concerns and are more likely to engage in pro-environmental behaviors than men, which may translate into better air quality outcomes as more women progressively break the glass ceiling in politics. To test this hypothesis, we employ a novel data set on air pollutant emissions and women’s political empowerment for a sample of 230 European regions of 27 EU countries. We apply instrumental variables and partial identi cation methods to ensure that our results are not in uenced by confounding variables. Our empirical analysis reveals that female political empowerment leads to better air quality. Moreover, we nd that the observed positive relationship between women’s empowerment and air quality is robust to a variety of changes in the empirical setup. Taken together, our results suggest that the observed positive link between women empowerment and air quality in Europe is likely to be causal.

In this paper we will study the rise in interest rates from two perspectives: Inflation and GDP growth and in two territorial areas: the United States and the European Union. For this study, we will begin by analyzing the current and expected evolution of the two reference variables (inflation and growth) based on the reports of the ECB and the FED as well as various independent institutions. To analyze the above data and reports, we will analyze inflation and growth from the perspective of the Taylor Rule and study possible future inflation and growth scenarios and the possibilities for stagflation. We also carry out a comparative analysis with the results of the monetary policies carried out in the oil crises and the parallels between the macroeconomic picture existing at that time and in the current one. In conclusion, based on everything analyzed and exposed, we present our opinion on the possible benefits and risks to inflation and growth associated with interest rate rises.

In 2008, Pacific Century Regional Development and China Netcom Corporation, two major shareholders of Pacific Century CyberWorks (PCCW, 00008.hk), proposed taking the firm private and de-listed from Hong Kong Stock Exchange. Minority shareholders opposed fiercely. The proposal, although endorsed in special shareholders meeting in February 2009, was challenged in Court and overturned in legal battles, due to allegations of vote-rigging in the shareholders meeting. One interesting aspect of this episode is that, while the offer by major shareholders was very attractive comparing to the current share price, it is hard to understand why relatively large percentage of shareholders voted against the offer. The percentage deviates from what often found in ultimatum game experiments, as the offer proposed by the major shareholders was comparable to the median offers in a lot of ultimatum game experiments. This could be understood through loss aversion, which predict a bias towards status quo. Prospect theory (Kahnnman and Tversky, 1979) predicts risk aversion facing a perceived gain prospect while risk loving facing a perceived lost prospect. In equity market, the recent fluctuation of the share price of a firm, of which privatization bid was offered, forms the backdrop of whether the offer is a perceived gain prospect or lost prospect. The voting result of the privatization bid offers a natural experiment to test these predictions.

Using data on the transition of young people to the labor markets of French-speaking Sub-Saharan Africa conducted by the Centre d’Etudes et de Recherche et Economie et Gestion (CREG) and the International Development Research Centre (IDRC) in 2021 on 4710 young people, this paper analyzes the inequality of wage expectations between girls and boys still in the education system in Cameroon and Chad. The methods used are Ordinary Least Squares (OLS) on the whole population and on girls and boys separately, the Oaxaca-Blinder type decomposition technique and conditional and unconditional quantile decompositions. First, the OLS estimates show that gender is significantly and negatively correlated with wage expectations for girls and boys in SSA and is higher in Chad than in Cameroon. Second, a Blinder-Oaxaca decomposition shows that about 30 percent of these differences are attributable to explained characteristics versus 70 percent attributable to unexplained characteristics in SSA. On the other hand, the conditional and unconditional quantiles without taking into account the covariates show that this gap is variable at each considered decile and quartile of the wage expectation distribution. Finally, the conditional decompositions with covariates taken into account show that gender differences in field of study and educational attainment are important in explaining the gender gap in youth wage claims.

This paper proposes a new method to test for regime-dependent Granger causality in a cross-sectionally dependent panel data setting using vector autoregressive (VAR) models and seemingly unrelated regressions (SUR). Estimation of regime-dependent model parameters is based on bootstrapped Wald test statistics. Extensive Monte Carlo simulations demonstrate that the proposed tool has the desirable small sample properties and outperforms conventional approaches in most evaluated scenarios. We also apply our testing framework to revisit the relationship between GDP growth and sovereign debt. Our results fail to find support for the debt threshold hypothesis (Reinhart and Rogoff, 2010) when imposing an exogenously introduced threshold of 90 per cent of the debt-to-GDP ratio. However, our analysis provides evidence for debt threshold effects when allowing for endogenous regime detection, which is spread over a wide range (40 per cent to 100 per cent of the debt-to-GDP ratio).

Multi-country surveys often aim at cross-country comparisons. A common quality standard is conducting such surveys within a common fieldwork period, across all participating countries. However, the rate the target sample is achieved within that fieldwork period in each country varies substantially. Thus, the distribution of the interview month often varies substantially in the final sample. We demonstrate the implications of such asynchronous fieldwork in cross-country surveys, using the European Social Survey Round 7. Our analytical sample focuses on six countries with data collected between September 2014 and January 2015. We present results for modelling physical activity using regression analysis and provide a set of different postestimation predictions that can be obtained. We found that physical activity varies across interview month, with the highest activity reported in September, decreasing thereafter, reaching the lowest level in January. Thus, countries with more observations during autumn were upward-biased, compared to countries with more observations during winter. Our results demonstrate how comparisons between countries are affected when interview month is omitted. This is prevalent using both unweighted and weighted regression techniques. Thus, our study suggests how accounting for interview month in analysis is an easy way to mitigate this problem.

The international economic order has undergone profound changes since the end of the twentieth century. The acceleration of the globalization process and the integration of emerging economies into the dynamics of international trade have led to the emergence of new centers of economic power, whose greatest exponent has been China. This paper analyzes the evolution of bilateral trade between China, the emerging economy that has most developed in recent decades, and several European countries.

Globally, the evolution of digitalization has transformed the way business activities are carried out. In this path, e-commerce marketplaces with dynamic technology, value creation, and capacity strengthening through technical collaboration have enabled positive spillover in terms of connecting several businesses, consumers, and the economy. These also advance greater trade openness and transaction cost reduction for better inclusive growth. Not only this, but the range of new opportunities for firms, mainly micro, small, and medium-sized enterprises (MSMEs), have facilitated integration into the GVC. However, the sudden boom in the e-commerce sector has been questioned in several economies in the world, particularly so in India. The country’s traders’ associations have complained that the e-commerce sector has been growing at the expense of the offline retail sector, primarily MSMEs. In this context, the paper considers the Indian economy and conducts one of the first attempts to analytically examine the significance of the growing e-commerce on India’s manufacturing and retail sector, especially the MSME sector (which comprises the country’s largest employment and revenue-generating cohort) for two time periods, viz. 1988-2020 and 2014-2020. We conduct two different sets of assessments. First, we assess the impact of the online sector on the overall sales of the total retail and manufacturing sectors of India, while extracting the effect on their MSME counterparts. This highlights the potential of the Indian economy to engage in and benefit from the expansion of e-commerce and MSMEs. The results indicated while e-commerce has assumed a significant role in positively impacting the sales of the overall retail and manufacturing sectors of the country (on average) during the assessment periods, however, the same does not hold true for MSMEs, specifically retail MSMEs, indicating the untapped potential of the sector to take advantage of the growing e-commerce sector. The second assessment builds on the impact of e-commerce in facilitating the GVC performance of Indian firms. We look at the GVC intensity of the selected enterprises and found that, once again, it is the MSME sector, especially the retail MSMEs, which has not been able to significantly take advantage of this new channel of export and import in improving their GVC performance, though the impact turned out to be positive. Finally, the study also discusses the importance of the pre-requisite of having the tool of digitalization to access the channel e-commerce. The findings advocate setting up a comprehensive e-commerce regulatory framework in India to ensure sustained and inclusive growth for both the e-commerce and MSME sectors. Currently, however, the country is still in the process to implement the e-commerce policy (which also includes deciding the mode of foreign investment and hence, the ‘business model’ for foreign e-commerce entities).

Does digitalization promote the export of Indian manufacturing Micro, Small, and Medium Enterprises? We empirically address this under-researched area by using the Centre for Monitoring Indian Economy’s Prowess database consisting of around 800 manufacturing MSMEs for the period 1990-2019. The summary of the findings based on the robust econometric techniques such as the System Generalized Method of Moments and Dynamic Probit Regression Model, and employing three alternative definitions of digitalization, reveals that a higher level of digitalization of an Indian manufacturing MSME increases its exports intensity. Also, a digitalized manufacturing MSME firm is more likely to enter the export market, vis-à-vis a non-digitalized one. In fact, the likelihood further increases if digitalization is complemented with technical knowledge. The findings advocate an urgent need for manufacturing MSMEs to go for digitalization to sustain and strengthen their contribution to the Indian economy, specifically in the post-covid era.

Suppose a rational agent can invest in domestic bonds (Euro (EUR) corporates) and foreign bonds (Dollar (USD) corporates) hedged into EUR using cross-currency swaps. Let xccyt represent the cross-currency basis spread of the FX hedging, where xccyt measures deviations from covered interest parity (CIP), a gauge of potential arbitrage profits in FX derivatives markets, see Du et al. (2018). Under the assumption that the bonds pay some spreads over their domestic benchmark rates, I propose a model that relates xccyt to three drivers. First, I show that xccyt is determined by 1) credit spreads differential, 2) output differential, and 3) expected inflation differential. Second, I analyze the theoretical predictions of the model, i.e., the effects of the three drivers on xccyt . Third, I perform an empirical analysis to verify the theoretical predictions. Finally, I discuss the results in the light of CIP deviations, FX-based arbitrage opportunities and policy.

Preferential Trade Agreements (PTAs) have emerged as the dominant form of international trade governance. Provisions included in PTAs are increasingly numerous, broad in the number of policy areas they cover, deep in their scope, and varied between agreements. We study the economic, political, and geographic determinants of PTA design differences. For each of the hundreds of classified PTA provisions, we consider hundreds of country-pair characteristics as potential determinants, covering many individual mechanisms the literature has studied. To deal with this high-dimensionality and complexity, we employ random forests, a supervised machine learning technique. We use modern variable importance measures to identify the most important determinants of the inclusion of each PTA provision.

Women’s economic autonomy can protect against intimate partner violence (IPV), but the process of increasing economic autonomy may generate adverse effects. We provide experimental evidence on the impacts of an important pathway to economic autonomy for women: self-employment. We randomize women in Uganda to a control group or two versions of an entrepreneurship program. Both follow the same curriculum but differ in how they deliver mentoring. In Intensive Mentoring, mentors seek out women at their home or business. Women in Opt-In Mentoring can visit mentors at the training venue. Women in Intensive Mentoring experience large reductions in IPV relative to control and Opt-In Mentoring. However, women have a strong revealed preference for Opt-In Mentoring. Intensive Mentoring appears to increase spousal knowledge of women’s businesses, allowing women to negotiate for better household outcomes but limiting household decision-making power and control over their business. Our results underline the trade-offs women make when building economic autonomy.

Objective: This study seeks to verify the validity of the Fisher hypothesis pre and post the Covid-19 outbreaks in the United States and in Canada. And, thus to determine if the hedging properties are robust towards the outbreak effect and to some considered model specifications. Methodology: This paper proposes 4 ARDL-GARCH models. ARDL specifications for the mean and GARCH specifications for the volatility. In the basic ARDL mean equation, stock market returns is explained by energy inflation, while the second ARDL one concerns in addition the role of the exchange rate, the third takes into account of the Covid-19 effect, and the fourth combines exchange rate effect and Covid effect. All considered mean equations and volatility GARCH equation are estimated by Maximum likelihood method. The Covid effect detection is based on the growth of the percentage of infected population (COVIDG variable for long-run effect) or on some binary variables for outliers (temporal effect) detected by quantile method. Results: This study reveals that both Canadian and American stock returns have robust partial hedge property against the global inflation rate (energy) pre and post the Covid-19 pandemic whatever ARDL-GARCH specification used from the 4 considered models. The effect of Covid-19 is found temporarily significant with positive or negative effects for some particular dates. Long run Covid effect is insignificant. Originality: The originality of this work lies in the use of the energy inflation rate in place of local inflation measure (based on CPI) to determine whether or not American and Canadian stock returns protect themselves against global inflation in the period of the Covid-19 pandemic. Compared to previous research whish look for short run or long run Covid effect, this paper looks in addition for temporal effects via some binary variables.

In this paper we examine systemic risk in the core international banking system using the network-based spectral eigen-pair method which is introduced for the first time by Markose et al. (2021) and treats network failure as a dynamical system stability problem. In this study, the quarterly balance sheet data of cross border banking system are used to construct the so-called stability network of Core Global Banking System (CGBS) for 19 reporting BIS countries in the span of 2005 to 2020. Our findings then show the early-warning signal in terms of the tipping point which is analogous to the R number for the Global Financial Crisis (GFC) in 2007-2008 using the spectral Systemic Risk Index (SRI). Furthermore, we identify systemically important and vulnerable banking systems using network centrality metrics. We also show the threatening role of the US, UK, and Spain banking system, and the possible consequences of failure of these banking systems in international banking system.

Our paper explores the political determinants of bank cash holdings. We show that banks in more corrupt countries hoard more cash. Notwithstanding, a higher level of the rule of law alleviates this effect. Furthermore, we also offer that this effect only holds for Non-Common Law countries. Additionally, we highlight the impact of election years on the decision of banks to increase reserves. Our results are robust to several specifications, including a propensity score matching approach.

Background: Biju Swasthya Kalyan Yojana (BSKY) is a flagship public-funded health insurance scheme of the Government of Odisha launched on 15 August 2018 for achieving universal health coverage in the state. Objectives: The present study assessed the awareness about BSKY, identified its determinants, and examined the utilization of the scheme among households in Khordha district of Odisha. Methods: Primary data were collected from randomly chosen 150 households using a pretested structured questionnaire from Balipatana block of Khordha district, Odisha. Descriptive statistics and binomial logistic regression were used to substantiate the objectives. Findings: The study found that 79.30 percent of the sample households were enrolled in the scheme. However, only 56.70 percent had heard about BSKY, and procedure-specific awareness was consistently low. State government-organized BSKY health insurance camp was a major source of information. The regression model with an R2 of 0.41 was found to be a good fit. Socioeconomic characteristics (i.e., caste, gender, and economic category), ownership of health insurance, and insurance awareness were significant determinants of BSKY awareness. Only 12.60 percent of the cardholders had utilized the card and only 10.67 percent had received benefits. The mean out-of-pocket expenditure (OOPE) paid by the beneficiaries was Rs 15743.59. The beneficiaries financed the OOPE mainly from their savings and borrowings. Conclusions: Awareness of the nature, features, and operational procedures of the scheme was low. The trend of low benefit received and higher OOPE among the scheme beneficiaries may hamper the economic health of the poor. Finally, the study highlighted the need to increase the magnitude of scheme coverage and administrative efficiency.

What role do health insurance policies play in improving access to quality health care? Are sociodemographic factors such as wealth and employment relevant for access to medical treatment? To study these questions, this paper uses data on Nigeria -sourced from the Demographic and Health Survey (DHS) and the World Health Organization (WHO) to 1) Evaluate the role of National Health Insurance Schemes (NHIS) in providing access to quality health care and to 2) Examine the relationship between sociodemographic characteristics and the availability of medical services, by applying an empirical design that is based on a binary logistic regression model. Based on the evidence, wealthier families are more likely to have access to medical care, and employed people are also more likely to have health insurance and visit health facilities. Furthermore, having health insurance increases the likelihood of receiving medical treatment, and changes in NHIS strongly affect access to healthcare.

The possible transactions between buyers and sellers are analyzed with intermediaries, called traders, using a network structure in this study. We investigate asymmetric network structures pertaining to one seller-two buyers and two sellers-one buyer structures. Goods are assumed to be traded in their respective markets through the trade networks under asymmetric information on the valuation of goods in a two-stage game. An interesting finding suggests that when the trader is linked to two sellers and one buyer, that trader can sometimes offer the same price to all three parties to receive the maximum profit.

Incidents of intense violence can cause a variety of reactions in direct victims as well as in the general public, most notably post-traumatic stress disorder (PTSD). PTSD may influence an individual’s social behavior, economic preferences, and decision-making. This article examines the way in which post-traumatic events are associated with economic decision-making, time preference, and attitudes toward risk. Specifically, we investigate the effects of rocket attacks on the population of Israel during the Israeli army’s operation “Guardian of the Walls” during May 2021. Our research involved a questionnaire distributed to Israeli civilians affected by the Gaza rocket attacks in various areas of Israel, and its aim was to assess the effects of post-traumatic stress disorder on economic decision-making. It was found that individuals suffering from post-traumatic symptoms are more likely to prefer current consumption over future consumption than healthy individuals, and they tend to take fewer economic risks than healthy individuals. In light of the above, it is important that individuals who suffer from post-traumatic disorders, their relatives, and therapists be aware of this tendency and take it into consideration.

In this article, we study the impact of both subjective and objective land tenure security on farming house holds’ propensity to invest in land as well as the pro ductivity of the soil. For that purpose, we resort to the World Bank LSMS-ISA data collected in 2014 at the national level of 10,800 households in Burkina Faso. The empirical application favors a simultaneous equa tions system made up of a multivariate Probit with ran dom effects on the one hand, and a Cobb-Douglas-type production function on the other hand. From the appli cation of the limited information maximum likelihood estimation and cmp methods using Stata 17.1, the re sults show that a secured individual field management and the membership in a socio-economic organization, considered together, have a positive and significant ef fect on yield per ha at 13.1% on average. But for the approved or objective land tenure security and a sub jective one in terms of the location of crop fields, the total impact of both on the soil productivity is negative and significant at 18.6%. Accordingly, it would be ad visable to stress, strengthen and increasingly promote the protection of individual exploitations specifically.

This paper uses synthetic data and four different endogeneity treatments to demonstrated that as the sample increases this problem fades. It is proposed a hypothetical equation system with an embedded endogeneity problem and the four endogeneity treatments are applied to it. Additionally, there are behavioral and statistical assumptions in each treatment which are underlined as they are used through this research. The data inputs for these endogeneity treatments are synthetic data, which are based on random numbers. This research results demonstrated that a treatment for endogeneity can be developed when the sample size increases.

Firms can now use algorithms to regulate workers’ time and activities more stringently than ever before. Using rich transaction data from a ride-hailing company in Asia, we document algorithmic wage-setting and study its impact on worker behavior. The algorithm profiles drivers based on their working schedules. Our data show that drivers favored by the algorithm earn 8% more hourly than non-favored drivers. To quantify the welfare effects of such preferential algorithms, we construct and estimate a two-sided market model with time-varying demand and dynamic labor supply decisions. Results show that removing the preferential algorithm would, in the short term, reduce platform revenues by 12% and total surplus by 7%. In the long run, raising rider fares re-balances demand and supply, resulting in minimal welfare loss. Without the preferential algorithm, an additional 10% of drivers would switch to flexible schedules. Lastly, young, male, local drivers benefit more from the non-preferential algorithm.

Utilizing data from the Jiangsu Province manufacturing sector from 2008 to 2020, this study applies the entropy value method to build a manufacturing upgrading level indicator system from three dimensions: scale, efficiency, and quality. From there, it investigates the variables affecting the Jiangsu Province manufacturing sector’s upgrading level. The ridge regression analysis’s findings demonstrate that Jiangsu Province’s manufacturing upgrading has shown a significant and positive relationship with GDP and capital investment. On the other side, FDI and R&D investments have little impact on Jiangsu Province’s manufacturing upgrading.

This paper analyzes the issue of demand estimation and market definition in industries where products differ according to their quality levels. An econometric methodology based on substitution elasticities is explained, and then applied to the Argentine beer industry, using data from the period 2011-2017. The results are compared to equivalent ones obtained using an alternative methodology, concluding that in Argentina we can identify two relevant markets inside the beer industry (corresponding to high/medium quality beers, and low quality beers).

In the most recent decade, economists have welcomed the circular economy theory, which aims to minimize resource input, waste production, and energy leakage. Various scholars claim to draw inspiration from this new outlook. However, our critical examination reveals that there are very few studies on the relationship between the circular economy and the Sraffian ecological economics theory. This paper uses the Sraffa theory in an entropic universe to calculate the relative prices and the profit rates of the resources on municipal solid waste (MSW) management in Paris. Our results suggest that the negative profit rates justify a system of subsidies for recycling and recovery on MSW. The results are supported by the analytic determination of dimensions. To the best of our knowledge, this is the first paper that analyses factors involved to criticize the foundation of circular economy and their justification as a solution in waste management by using Sraffian theory.

The Environmental Kuznets Curve (EKC) hypothesis assumes that there is an inverted U-shaped relationship between environmental degradation and income per capita. It holds that environmental quality declines in the early periods of per capita GDP growth before increasing while the Pollution Haven Hypothesis (PHH) argues that firms try to avoid the expense of strict environmental laws (and high energy prices) by locating their factories in countries with less stringent environmental standards. Research on this issue of EKC and PHH has developed rapidly in recent years and is of interest in this contribution. Our objective is to examine the empirical validity of the relationship between three different known pollutants (Carbon Dioxide , Methane and Nitrous Oxide ) and per capita income under the EKC and pollution Haven hypotheses, through spatial econometric regression modeling of a panel of 40 African countries over the period 1971 to 2019. The results show that the validation of the environmental Kuznets curve and the pollution Haven hypothesis depends, among other things, on the inclusion in the modeling employed, the variables used, the spatial dependence, as well as the length of the period studied.

This paper provides fresh evidence of temperature effects on GDP per capita growth and economic policy uncertainty (epu). We apply the quantile via moments methodology (Machado and Santos Silva, 2019) in a sample of 35 countries for the period 1980-2021, the most current time frame of the work we reviewed. To the best of our knowledge, temperature effects on epu, in a panel quantile setting, have not been examined before. Our empirical results provide evidence in favor of asymmetric temperature impacts on both growth rates and epu. Specifically, we find that: First, the impact of temperature and of its interaction with economic policy uncertainty on the growth rate is negative, quadratic, and more intense for poorer countries. Second, the combined temperature and policy uncertainty effect on growth rates is of greater magnitude compared to the simple temperature effect. Third, hotter countries are more vulnerable to economic policy uncertainty, with the effect being more pronounced as uncertainty increases.

This paper demonstrates the past and current experience of the Federal Reserve Bank (Fed) related to its policy of Quantitative Tightening (QT). The research is an addition to the already existing Word Bank estimates about unconventional monetary policy. We intend to show that the long-end yields were unanchored till the starting of QT. For the set of countries, we selected Emerging Market (EM) samples to examine the impact of the Fed’s QT on 10-year government bond yields, between the period of 2012-2022. The result proves that the highest correlation between the long-end yields of the United States and the selected EM has materialized exactly during the first QT operation by the Fed, between 2017 and 2019. We expect exactly the same behaviour of long-end yields during the second QT policy for the selected EM countries. It was also examined through the data, that the U.S. stasfied the three preliminary conditions for QT implementation, related to level of GDP, unemployment rate and the level of policy interest rate, but not all the EM countries. Since, some EM coutries has inappropriate level of GDP or unemplyment rate for QT process implementation. The QT has limitation, it should not have any material effect through signalling channels of monetary transmission mechanism.

For China, which is in a critical period of economic transformation, human capital is increasingly becoming the most dynamic factor driving economic development. Human capital is crucial to the economic and social development of cities and directly determines the competitiveness of cities. To improve the competitiveness of human capital, it is necessary to formulate scientific and reasonable strategic human capital planning based on the current status of human capital. This paper compares the differences in human capital between Sichuan Province and Chongqing City by reading relevant literature, thus analyzing the economic growth of the two cities, and Draw relevant conclusions.

The study investigates the relationship between household consumption demand and household incomes by considering consumption expenditure and income of different decile households, which is not empirically studied in the Indian literature. Using linear and nonlinear panel fixed effect regression models on the estimated MPCE, the study uncovers the fact that even the lower strata households have greater capacity to consume, just as their income is lower, they are constrained to increase their aggregate consumption to their potential levels at the economy-wide context as well as in both rural and urban India. The problem is glaring more in rural areas comparing urban India. The study calls for drastic and urgent policy interventions by the government in undertaking appropriate redistributive policy measures to uplift the income of poor and thereby not only address widespread income disparity but also address the sagging investment demand in the present context to which the economy is deadlocked over a longer period.

This paper examines the influence of selected macroeconomic variables in terms of crude oil price, consumer price index, exchange rates, foreign direct investment, and interest rate on the growth of Indian economy. Changes in the rates of oil prices, CPI, foreign direct investment, exchange rates, and interest rates are directly affected the GDP growth in India…

We study how environmental policy affects corporate default risk using a large sample of 537,141 firm-year observations and 55,298 unique firms from 31 countries over 1990-2020. We show that environmental policy reduces corporate default risk, in line with Porter’s hypothesis. This effect is stronger for firms in common law countries and for those financially unconstrained. The results remain robust to difference-in-differences estimation, alternative series, and an extensive set of control variables. Further analysis identifies four potential mechanisms that explain how environmental policy stringency influences default risk: competitive advantage, investment in innovation, cash holding, and cost of external financing. Our study reveals important economic outcomes of environmental policy stringency that previous research has not explored.

This work studies the firm-level concentration of Chinese exports in individual markets. Chinese exports are less concentrated in larger markets and more concentrated in wealthier markets. Top Chinese exporters are more predominant in larger markets, but these markets attract significantly more Chinese exporters, leading to lower overall concentration levels of Chinese exports there. As the income level of an export market increases, lower trade barriers open the market to more Chinese exporters. However, at the same time, a greater share of Chinese exports to the market are conducted via bulky processing trade. On balance, the concentration of Chinese exports increases with the income level of the export market.

This research investigated the impact of political factors on defense expenditure in Sub-Saharan Africa (SSA). The study used data covering for the period 2000 to 2019. Variables used include previous defense expenditure, military in politics, ethnic conflict and external conflict. Descriptive statistics, unit root test were the carried out. The Generalized method of moment by Arrelano and Bond (1991) were used for estimation. Findings revealed that only previous defense expenditure was statistically significant. From the study, it is recommended that policy makers in SSA countries should always consider past defense expenditure before undertaking current defense spending on defense and also political factors should not crowd out other factors when defense spending is involved.

This paper explores the effect of a new Brazilian law on insurance pricing. The law regulates and disciplines the activity of dismantling land vehicles. For the state where the new law went into effect, we find a significant reduction in the number of claims reported and the indemnities paid by insurance companies for vehicle theft. The considerable reduction in vehicle thefts can serve as an argumentative basis to encourage other places to invest more in the application of similar laws as a way to improve public security and social welfare. We find a significant decrease in insurance premia for passenger cars produced domestically and motorbikes. In addition, on average, female drivers in São Paulo paid smaller insurance premia after the Chop Shop Law. The full interaction term of the region, policy, and gender produces a negative estimate of R$139,51 per year, indicating heterogeneity in the effects of the Chop Shop Law.

This paper adds to the literature by examining fiscal competition and deficit financing by local governments in a developing country, China. We examine a unique revenue source in China, land-use premiums (a type of property tax), in a panel dataset consolidated at the prefectural level from 2006 to 2016. Our results indicate that fiscal competition in land-use premiums exists and is stronger among wealthier than poorer local governments, a result that supports the view of Cai and Treisman (2005) that competition among asymmetrically endowed regions can lead to less discipline. Moreover, we find higher local deficits are associated with lower land-use premiums, a result that suggests that the local government does not fill any fiscal gap with own revenues.

We identify the causal impact of housing demolition on employment and occupational mobility of working-age individuals in China. We exploit housing demolition events as a quasi-natural experiment and apply a two-way fixed effects approach to overcome the potential endogeneity problem. Using data from the CHFS, we find that on the extensive margin, housing demolition creates skill waste by making individuals less likely to work; while on the intensive margin, housing demolition leads to occupational upward mobility, especially among low-skilled workers. We do not find any empirical evidence that housing demolition influences internal migration flow or migrant workers’ occupational mobility

We use the negotiations for large-scale open-access agreements between German research institutions and leading academic publishers to study how changes in the attractiveness of various journals affect the publication behavior of researchers in economics and adjacent fields. First, as German universities canceled their subscriptions to Elsevier, we study how this affected German economists’ incentives to publish in its journals. Second, Springer and Wiley entered into open-access agreements so that researchers in Germany are eligible to publish articles open-access without additional charges for them. Using 243,757 articles published between 2015 and 2022, we find a shift toward included journals, which is most pronounced among women. For Elsevier, the effect is negative and women have a higher tendency to opt out than men. In mixed teams, the dominant gender drives behavior. We conclude that men tend to seek reputation, women visibility. Thereby, female researchers contribute more to the public good of open science. Our findings provide a new explanatory channel of the academic gender gap.

We estimate the effects of unobserved skills on labor market outcomes by investigating a change in the distribution of unobserved skills. Among people with the same levels of observed skills such as education and work experience, there are still disparities in labor market outcomes. To explain the disparities and find the effect of unobserved skills, we exploit a discontinuity generated by the 2012 education policy in Iran. This policy restricting female students in specific college majors changes the size and skill distribution of high school graduates. We find three main findings. First, the education quota lowers women’s college attendance. Second, young high-school graduate women are more likely to participate in the labor market and have a job. Third, the gender wage gap decreases among high-school workers due to both within and between occupation changes: treated women are paid more and they take up higher-paying middle-skilled positions that used to be non-traditional occupations for them.

The paper studies the convergence of regional house prices in China. We find that the commercial property market is more homogeneous, while there is substantial heterogeneity in residential property prices. The formation of convergence clubs varies over time and across types of properties. The market for newly-constructed housing becomes more integrated over time, with a smaller number of regional clusters identified in the latter period, while the second-hand housing market becomes more fragmented. Using regression analysis, we find that rent, land supply, air quality, and economic development of cities play an important role in explaining house price convergence across cities.

The study investigates whether access to digital ways of conducting a business can enhance the productivity of the unorganized sector MSMEs in India, and hence, foster their participation in international trade. The analysis is conducted using the National Sample Survey’s (NSS) 73rd round on unincorporated non-agricultural Indian enterprises for the year 2015-16, covering approximately 2,90,000 firms, and performing separate analysis for both manufacturing and services firms. The key findings are: First, access to ICT infrastructure has a positive impact on firm-level productivity while controlling for firm-level characteristics. Second, the quantile regression analysis confirms the robust impact of digital assets across different levels of productivity. Third, the Probit Regression Model highlights the combined positive and significant impact of digital infrastructure and productivity on the international trade participation of an unorganized sector MSME. These findings can serve as a motivation for accelerating ‘bottom-up approach’ in the policy efforts towards better productivity and digital transformation of these firms, particularly for manufacturing MSMEs.

We study the informativeness of corporate textual disclosures in an environment of extreme uncertainty by using the COVID-19 pandemic as the setting. An increasing number of firms disclose or being encouraged to disclose more information about their operations and their business conditions in written form. Even so, there is a debate about whether the writing in a company’s Management Discussion and Analysis (MD& A) is relevant or clear enough to users. The Covid-19 pandemic had such severe and unexpected effects on business operations that any disclosure by management during the crisis would be of great interest to investors and other stakeholders. This interest would be even greater for real estate companies, since the industry was widely expected to be immediately and significantly affected directly and indirectly. Using data from CRSP, Compustat, SEC EDGAR and other sources, we analyze textual disclosures by Real Estate Investment Trusts (REITs) in the United States between 2017 and 2022. Our empirical results reveal changes in the linguistic style of disclosures during the pandemic in a comprehensive perspective. We find that, after March 2020, (i) the length of disclosures increases; (ii) their tone becomes more negative; (iii) the uncertainty expressed in the disclosures increases; (iv) they become less readable; and (v) the level of boiler plating falls. We find that these effects are also economically significant. We also find that these effects are correlated contemporaneously, even after controlling for common independent variables, and that there are significant differences across different types of REITs. Even so, we suggest that the changes have less economic significance than might be expected during a crisis. Our results contribute to debates on the impact of the pandemic, as well as the significance and informativeness of MD& A disclosures. Understanding REITs’ disclosure behavior in an environment of extreme uncertainty has important implications for investors and policy makers.

In this paper, we examine the outcome of different market structures using a three-sector model of an economy consisting of competitive final good, a competitive intermediate good and an oligopolistic intermediate good sector. We examine if a competitive market is preferable to an imperfectly competitive market in the long run with respect to real income and income distribution. Our analyses show that tougher competition will not necessarily lead to an increase of real income in the long run. Tougher competition affects the allocation of input factors and redistributes income from the young to the old generation. Enhanced welfare in terms of real income will be generated only, if the benefits resulting from an improved allocation of resources exceed the welfare losses resulting from a lower capital stock. Furthermore, the existence of monopoly rents supports an unfair distribution of income and wealth. We show that reduction in inequalities and improvement in the welfare of workers are achievable in a progressive income tax system.

This research aims to analyze the model of entrepreneurial inclusive civic culture created and developed in the Agro ecological Park of Zapopan (PAZ). Based on the need to rescue vacant urban land use with the participation of residents residing in the surrounding colonies, social movements, civil society and local government, they have designed and implemented actions to create PAZ (PEACE) as an area of green innovation. In addition to the cultivation of vegetables, vegetables, medicinal plants and decoration under relations of cooperation, trust and community support, the formation of social capital that sustains a culture of peace based on environmental sustainability activities. The results of the implementation of this project, born from bottom of the social and power structures, constitute a significant experience in the regeneration of public spaces and green areas that provides greater economic efficiency in terms of family income, a greater relevance of equity, inclusion and social justice and improvement of environmental sustainability.

Natural disasters can cause direct economic and substantial damage worldwide. It has been happening more frequently over time, and tropical economies suffer significantly due to its adverse impact. The effects of extreme occurrences of natural disasters on agriculture might be favourable or detrimental. However, there is still uncertainty in the existing literature regarding their impact on agricultural production, especially in tropical regions. Hence, the study aims to analyse the relationship between natural disaster intensity and agricultural production in tropical economies for the last two decades (2000 to 2020). Using a panel dataset of 95 tropical economies, this study employs regression analysis and the Generalized Method of Moments technique to identify the variables that influence the value of agricultural productivity and total agricultural productivity in tropical regions. Second, we also employ the instrumental variable model to study how natural disasters have impacted agricultural production over the years and Powell Quantile Regression Model to study the effects of disaster and several factors upon the agriculture productivity in these economies at different quantiles. The findings reveal that the total economic damage caused by natural disasters has an adverse effect on total agricultural production. Our empirical results further demonstrate that arable land, rural population, and consumer price index favorably and significantly affect total agricultural production. Overall, we notice that in the midst of disaster-agricultural yield dynamics, inflation, and temperature change also play enhancing roles. This study has provided critical insight and adds to the existing literature on the dynamics of natural disasters, agricultural production in the paradigms of sustainable development, and socio-economic development in developing countries by providing detailed empirical evidence. However, it has not considered a few tropical economies due to the unavailability of data on these regions.

The analysis of homebuyers’ willingness to pay for quality living environment has drawn considerable interests among scholars. A vigorous exploration of homebuyer preference is lacking nevertheless. The current study endeavors to fill this gap. The method suggested – extracting homebuyer preference from comment texts – is more comprehensive, reliable, and cost-effective than the popular survey approach. Latent Dirichlet Allocation (LDA) topic model analysis of comment texts confirm that homebuyers would pay attention not only to the hard infrastructure surrounding a housing estate as suggested in earlier literature, but also to the soft infrastructure which was rarely considered by previous scholars. On the basis of an enriched understanding of homebuyer preference, we first adopt hedonic price model to analyze the marginal willingness to pay for different dimensions of living environment from a global perspective. After which, geographically weighted regression model was employed to analyze the spatial distribution of such willingness. The results show that the preference for soft infrastructure has a significant explanatory power over housing price premium, and some premia exhibit significant spatial differences within a single city. Our results inform property developers and city planners of the huge potential of internet comment texts in aiding future property development and public facilities planning.

In this paper we assess the effect of benefits and income on the number of photovoltaic (PV) installations and their average capacity size in the two biggest regions of Belgium, Flanders and Wallonia. Due to the variation in benefit schemes across the regions and within regions across different years, we are able to statistically estimate the effect of changes in future benefits on adoption patterns in the residential sector. We find a high sensitivity of benefits on the number of installations and also on average capacity size. While lower income groups in our sample are shown to be less prone to invest in PV systems, we find an adverse effect of benefits on these groups. We also find that higher benefits are able to decrease the gap in adoption numbers between high income municipalities and the rest. Our results suggest that benefits highly matter for energy-related investments in the residential sector. This highlights the necessity of governmental benefit schemes for these investments, especially when they are prohibitively high otherwise. Our results also suggest that targeting lower income groups in particular may be beneficial if large scale adoption of these technologies is the goal.

Since 2018, the Digital Village Construction project has been given much higher priority in Chinese rural revitalization. Besides building digital facilities, governments also provide training courses on information and telecommunication technology(ICT) use to farmers. This paper studies the effects of (ICT) and information acquisition(IA) on the profitability of organic fertilizer use(POFU). Using data from a field survey on 1585 vegetable growers in six main vegetable-producing provinces of China, we build Tobit model and endogenous switching regression model (ESR) to study. The results show that ICT and IA affects POFU significantly, with a percentage point of IA and the competence of ICT use increase, the POFU will increase by 8.4% and 2.340%, respectively for all vegetable growers, and the moderating effect of IA is significant at 10% level. The treatment effect shows that when farmers improve their competence of ICT use, their POFU will increase by 1.237 yuan RMB per unit.

This paper examines the relationship among ecological footprint (EF), electricity consumption, and GDP in China using annual data ranging from 1960 to 2019. Howev-er, factors like trade openness, urbanization, and life expectancy might increase EF as ecological distortions are mainly human-induced. This study explores the effect of these variables on the environment, which is captured by EF. Quantile Regression (QR) estimates indicate that electricity consumption and real GDP increase environ-mental degradation, while trade and urbanization reduce EF, allowing for a higher en-vironmental quality. On the other hand, the spectral Granger-causality tests reveal that only urbanization and life expectancy affect environmental degradation over the whole frequency domain. In the current geopolitical scenario, relevant policy implications may be derived.

The COVID-19 pandemic has injected reluctance among policymakers in choosing between imposing, lifting, and reinstating lockdowns. This paper provides empirical evidence on the effects of COVID-19 induced firm closures on job losses in Jordan and Morocco. It aims at highlighting the unequal costs borne by the labor force of different industries and emphasizing the permanence of lay-offs for different labor contract types (part-time and full-time). The investigation of whether firms who closed during the pandemic are impacted more heavily compared to firms that did not close is pursued by adopting a propensity-score matching approach in an attempt to minimize the differences between the closing firms and non-closing firms. A follow-up survey is used to provide a clearer and more accurate representation of the persistence and recovery of job losses in different sectors and for different labor contract types. We find a significant increase in job losses in the firms of the manufacturing sector that closed compared to firms in the same sector that did not close after the COVID-19 outbreak. The job loss in the manufacturing sector significantly affects both full-timers and part-timers, however, lay-off effects are short-lived. In the retail industry, while full-time workers do not seem to be affected differently between firms that closed and those that did not close, the effect of firm closure on job losses of part-time workers appears to materialize in the second round, after reporting insignificant effects in the first round. The findings provide policymakers with crucial information about the most affected sectors and worker contract types by the closure that is mostly attributable to lockdown measures.

Despite the numerous policies targeting women, little improvement has been realised in the value of women’s labour and time in Ghana. With access to electricity on the rise, its possible capacity to improve women’s labour and time value has not been appreciatively considered in the Ghanaian literature. Thus, this paper sought to analyse the effect of electricity access on Ghanaian women’s labour and time value as well as the time-saving transmission channels. The 2015 labour force survey data was used and the standard two-stage least-squares instrumental variable and special regressor estimators were employed. We find that electricity access has an insignificant effect on the labour value of farm women while the effect on their non-farm value is significant at the national and rural levels. We further find that electricity access reduces the number of unpaid hours expended by women and generates surplus hours. The transmission channel results also indicate that electrified women are more likely to own time-saving electric technologies relative to those without electricity. From a policy perspective, expansion of electricity access, creation of more rural non-farm enterprises, and government subsidies on electric technologies are recommended to improve Ghanaian women’s labour and time value.

Persons with disabilities (PWD) face multiple challenges when attempting to integrate into the labour market, especially in developing countries. Despite government and non-governmental organizations (NGO) efforts to improve their opportunities, PWD continue to experience social segregation, limited access to support services, and/or economic exclusion. This paper explores the difficulties PWD face in accessing the labour market in two cities: Vijayawada, India, and Béni-Mellal, Morocco. This study was motivated by the need to understand the barriers faced by PWD in different sociocultural contexts. Using a qualitative approach, the study surveyed a total of 69 disabled participants (34 from Morocco and 35 from India), and used multiple linear regression model to evaluate the impact of different independent variables on different aspects of disability difficulties. The findings reveal that PWD in both cities encounter similar challenges in terms of access to employment, transport, services and general attitudes towards disability. However, the nature and magnitude of these challenges vary from country to country due to differences in socio-cultural norms and government policies. Furthermore, the results reveal that (i) PWD in Morocco are more likely to be educated in a specialized institution than Indian disabled; (ii) PWD in India are more likely to receive a scholarship or financial assistance than Moroccan disabled, and (iii) there are significant differences namely in relation to attitude, job searching and work outside their city. This study concluded that social justice is the master key to development, guaranteeing the rights for all regardless of their idiosyncrasies / particularities.