We propose a cross-market volatility forecasting framework by applying attention-based spatial-temporal graph convolutional network model (ASTGCN) to forecast future volatility of stock indices in 18 financial markets. In our work, we construct cross-market volatility networks to integrate interrelations among finan- cial markets and corresponding features of each market. ASTGCN combines the spatial-temporal attention mechanisms with the spatial-temporal convolutions to simultaneously capture the dynamic spatial-temporal characteristics of global volatility data. Compared with competitive models, ASTGCN exhibits superiority in predictive accuracies under multiple forecasting horizons, and it possesses the capability of producing predictive outcomes for multivariate markets. We also inspect the training process of ASTGCN by extracting spatial attention matrices and find that interrelations among global financial markets perform differently in tranquil and turmoil periods. Our study levitates empirical findings in financial networks to practical application with a novel forecasting method in the deep learning community.

This paper introduces a new econometric test for the efficiency of the online soccer betting market. We derived a benchmark for efficiency ($\beta_0=1$) and tested four major European soccer leagues (Bundesliga, La Liga, Premier League, and Serie A) using data covering 14 seasons, from 2005 to 2019, with a total of 20,244 matches. Our results show that the online betting markets have only small, but significant, deviations from efficiency, with an estimated $\beta_0$ around 0.85-0.92. In addition, the four leagues differ slightly in efficiency, with the Bundesliga being the least efficient betting market. These results are robust regardless of the approach, static or dynamic. In fact, we used two different procedures: a static one based on bootstrap sampling and a dynamic one based on a rolling window. The results are of interest to econometricians and policymakers because of the implications for the functioning of the betting market.

Traditionally, the gross domestic product of a country is released well after the quarter in question has passed. A similar schedule is seen with other major economic indicators, especially in developing nations. Nowcasting has thus been the subject of numerous studies, with its importance highlighted especially during times of crisis such as the recent coronavirus 19 pandemic. Knowing the extent of the impact on the economy real-time is of vital importance to policymakers as crises progress. High-frequency data such as social media posts offer near-real-time insight into the sentiments of the population; nonetheless, they have not been heavily utilized for modeling and prediction due to their unstructured and noisy nature. Cleverly-crafted search strategies and developments in text mining techniques, however, allow for social-media-based text to be converted into usable data for macroeconomic nowcasting, yielding information on the state of the economy ahead of official statistics and surveys. The study proposes economy and uncertainty indicators derived from Twitter, now X, within the context of developing countries – with the Philippines as case study – and evaluates their usefulness as a dynamic and cost-effective alternative to the news-based Economic Policy Uncertainty Index. To construct the mentioned indices, tweets in English from 2010 to 2022 containing either both a country and an economy term or both a country and an uncertainty term are mined. Whereas previous indices from Twitter are fixated on tweet counts, the research incorporates weighting schemes, sentiment analyses, and signal separation to produce advanced metrics. The resulting Twitter-based measures of economy and uncertainty enable a data-driven approach to identifying and monitoring significant events across various sectors. Further text mining also allows for the estimation of the relative magnitude and polarity of the impact of an event. Combined with feature engineering, another advantage of the novel set of indicators is configurability. Themes – economic, financial, political, and environmental, for example – may be introduced during construction to highlight domains of interest. In establishing predictive power, traditional economic variables are set as benchmark input. A mixed-data sampling framework is adopted for the nowcasting models, with the quarterly gross domestic product growth and other main indicators as targets. Significantly lower errors are observed in models trained on the tweet-based indicators, both with machine learning and factor modeling. To close, the new tweet-based metrics are tools that policymakers may wield to identify and monitor events concerning a country and assess their impact on the various aspects of the economy. The measures are grounded on a balance of interpretability and accuracy, following a data-driven approach from indicator construction to predictive modeling.

In a world where combating climate change is crucial, it is useful to understand the European Union’s policies to mitigate the climate change and promote green and sustainable development. Some of these policies are directed to businesses, posing great challenges to overcome in terms of reducing emissions and using clean energy. Adapting production technology to new requirements can often be difficult, causing a decrease in the competitiveness of companies. For this reason, some companies carry out lobbying activity to obtain less stringent environmental constraints. The objective of this paper is to understand the pressures exerted by lobbyists on EU climate policies, highlighting whether these pressures are exerted in support or against climate policies. A qualitative analysis was carried out with the MAXQDA program. Multi-Level Perspective (MLP) and discourse theory allowed us to identify the lobbying pressures exerted by actors on EU policies in the dominant and niche scenario and the interactions between them. This study is useful for understanding the possible evolutions of EU climate policy in environmental matters.

This paper investigates the influence of loss aversion framing on students’ test performance. Employing three different approaches — giving points, granting students a perfect score with deductions for incorrect answers, and alternating between giving and subtracting points — the study explores how individuals react to gains and losses in a classroom setting. The findings suggest that studying with a loss frame improves performance more than just earning points. There is no evidence of differential gender effects, and the results do not support the idea that loss aversion has a diminishing effect with time.

This paper studied the impact of alcohol spending on income of formal workers in private sector in the Vietnamese Mekong delta. The data includes 377 observations collected in 2023. Unlike previous studies, this study uses alcohol spending as a measure and takes into account the purpose of drinking to investigate its impact. The results show a positive association between alcohol spending and income of the workers. Especially, once taking into account the purpose of drinking (work-related) the positive impact is robust across all the income levels. Some recommendations are provided.

This paper studies whether the advent of financial globalisation has contributed to increasing wealth inequality in the United States, France, and the United Kingdom. I find that (i) positive changes in the benchmark measure of financial globalisation are associated with a positive change in the top 1% and 10% wealth shares and a negative change in the wealth share of the bottom 50% of the distribution. This is equivalent to an average gain of $1 trillion for the top 10% and $1.6 trillion for the top 1%, over the period of interest. (ii) Portfolio equities and financial derivatives appear to be the driving components behind the increase in wealth share. (iii) The implied change in wealth shares is driven by the accumulation of new financial wealth (flow) rather than the valuation of existing one. (iv) The dynamic is strengthened when a banking crisis hits the economy, possibly because people at the top of the distribution can recover their lost wealth faster than people at the bottom. The main finding is robust with an expanded country sample, albeit reducing the historical context beyond the scope of this paper.

This paper documents that international trade may cause uneven distribution of opportunities and costs to countries in face of uncoordinated environmental policies. Specifically, we use exogenous introductions of national carbon taxes to study how local firms react to such shocks, especially when they make outsourcing decisions on carbon inputs. Results show that regulatory carbon taxes lead domestic firms to import more carbon products, such as cement, iron and steel, from foreign producers. Firm-level data additionally show that firms will increase their trade shares to foreign suppliers headquartered in pollution haven. Exploiting buyer-supplier relation information, we further find that domestic regulatory carbon taxes do benefit foreign carbon suppliers, helping them to, for example, expanded production scales and improved financial performance. These findings highlight the critical role that international trade play in fulfilling growth, welfare and emission reduction goals of environmental policies.

There is no consensus on the impact from changes in the exchange rate on the trade balance – not in theoretical nor in empirical works. The impact from changes in (foreign and domestic) income on exports and imports is relatively understudied. We use data from foreign trade amongst a group of fifteen advanced economies to determine the demand elasticities for exports and imports, by analyzing changes in domestic and foreign income and exchange rates. We construct a trade-weighted Real Effective Exchange Rate to estimate elasticities of exports and imports on goods and services. We also investigate how changes in real income (domestic and foreign) may affect international trade patterns for the economies in the sample. Foreign real income is calculated with the time-varying trade weights…

We investigate the role of Artificial Intelligence (AI) on firms’ resilience to the COVID-19 crisis. We show that firms that adopted any AI technologies (machine learning, intelligent robots, computer vision, natural language processing, and virtual assistants) before the crisis exhibit higher stock returns than non-AI-adopters during the peak of the crisis. This cross-sectional finding also holds in a difference-in-differences setting. Our main finding is more pronounced when AI- adopters (i) own AI patents, and (ii) use AI in combination with EMTs (e.g., big data analytics, cloud computing, IoT). We further find that AI adopters, compared to non-AI adopters, have higher operating performance and firm valuation during the peak of the crisis as well as following the peak. Lastly, we show that heterogeneity in AI adoption matters as the following AI technologies drive our results: machine learning, natural language processing, and virtual assistants. Our results hold across a battery of robustness tests.

COVID-19 forced market regulators to introduce a short-selling ban in some European countries in spring 2020. This paper examines the effect of the ban on volatility and tail risk in equity markets. Such a ban is assumed to be helpful in preventing severe market crashes: removal of short sellers is believed to reduce falls in equity prices. I find that the imposition of the restriction increases market risk metrics such as value-at-risk and the expected shortfall of stock returns. Banks are subject to capital requirements, in relation to market risk they are based upon previously mentioned risk metrics. A sharp change in either makes banks more vulnerable to equity price fluctuations and more susceptible to selling assets to cope with breached capital requirements. Additional sales, caused by the latter effect, leads to a further decrease in equity prices. Asset sales during crises are unlikely to be profitable, hence it decreases capital further. Consequently, a short sale ban that is intended to cool down market panic leads to a further fall in equity prices in bank-based systems. Based on evidence from European markets in 2020, I find that a short-sale ban leads to significant increase in value-at-risk (from 15% to 18%, depending on the methodology), while expected shortfall jumps by 30%.

This paper examines the development of decentralized crypto exchanges in recent years, focusing on Uniswap as a case study. We first establish a theoretical model to analyze the determination of the returns of liquidity providers, and then compile a comprehensive dataset by extracting detailed trading data from the Ethereum Blockchain. We conduct an in-depth examination of all transactions that have occurred at the largest Uniswap liquidity pools since 2021, and explore the relationships between liquidity providers’ return, impermanent loss, pool size, trading volume and fee revenues through a panel regression analysis.

We examine whether institutional portfolio rebalancing triggered by firms’ climate change exposures, affects S\&P 500 firms’ cost of equity via the incurred climate change price pressure (CCPP) during 2005-2021. We estimate stock-level CCPP separately for physical and transition exposures, in a demand-based asset pricing setting. We proxy firms’ cost of equity by real-time, forward-looking option-based measures. The pooled average CCPP is sizable up to -8\%. The predominantly negative cross-sectional CCPP trends downwards (upwards) pre (post)-2016, driven by investors underweighting more (less). A one-standard-deviation decrease in CCPP increases firms’ cost of equity by up to 6\% of its average value. Banks and insurance companies contribute primarily to CCPP by on average underweighting stocks with high climate change exposures. Despite the higher cost of equity from more negative CCPP, firms do not reduce future climate change exposures and carbon emissions, except over periods of heightened media climate change concerns.

This paper assesses the negative consequences and systemic impacts of geopolitical risk on the global banking network. An innovative and adaptable graph-theoretic framework is used for network construction and connectedness measurement. Geopolitical risk profoundly alters the network structure, connectedness level, risk profile, and evolutionary path of the global banking network. Regression analysis further provides some direct and insightful evidence. Higher geopolitical risk is significantly associated with enhancement of bank connectedness (at firm and system levels) and systemic risk. Banks with low profitability and high non-performing loans are more vulnerable to geopolitical risk. The cross-sectional analysis reveals that aggressive business decisions, non-neutral country positions, and geographic proximity are important channels for exacerbating geopolitical risk.

This paper attempts to empirically develop a benchmark to identify safe haven currencies from a view of currency risk premium (CRP) for investors’ reference. We first quantify a general CRP and then select seven currencies including the US Dollar, Pound Sterling, Japanese Yen, Canadian Dollar, Australian Dollar, Chinese Yuan and Russian Ruble to examine the relationship between exchange rate changes and exogenous uncertainties through CRP. We find that overall, increases in exogenous uncertainties lead to the rise of CRP, but situations can be different when examining currencies separately. Whether exchange rate appreciates under a risky environment should be the measuring standard of a safe haven currency.

This paper explores the link between financial literacy and peers’ socio-economic status. We exploit data from 76,789 15-year-old adolescents in 21 high- and middle-income countries participating in the Program for International Student Assessment (PISA) financial questionnaire. We find that peers’ socio-economic status is a robust and significant predictor of financial literacy test scores, being the most important factor in explaining differences in financial literacy among adolescents. Our results hold in both the aggregate sample and by country, with the correlations being more pronounced in wealthier countries. Our findings suggest that policies aiming to increase financial literacy among young people have to consider not only individual socio-economic backgrounds but also peers’ socioeconomic status. In this sense, discouraging the concentration of students from low socio-economic backgrounds in schools is crucial.

In this paper, we assess government interventions in the banking sector during a financial crisis. Our objective is to analyse the ex-post effect of those interventions using a balance sheet approach and evaluate their impact on the sectoral balance sheets of the public and the banking sector. We find that equity-side interventions seem to be the most influential, while liability-side interventions appear to be the most neutral. Further, using econometric techniques, we evaluate the relationships between government interventions and key banking sector indicators. In this respect, we investigate how governments choose to intervene depending on specific driving factors and provide a comprehensive set of different intervention combinations and outcomes. Generally, we observe that governments tend to undertake additional interventions if they have implemented already relevant measures in the past.

In recent years, the emergence of mini flash crashes has become a distinctive concern within contemporary electronic trading markets, garnering attention from scholars, market participants, and regulators alike. These rapid, unforeseen market disruptions have been attributed to the breakneck pace of trading activity. This study employs data from the NYSE Trade and Quote database (TAQ) to examine the efficacy of implementing a “speed bump’ mechanism in mitigating the risks associated with mini flash crashes. Utilizing machine learning techniques to estimate the likelihood of mini flash crashes occurring within the NYSE American market, this analysis offers empirical insights. The findings of this research demonstrate that the introduction of a speed bump mechanism can indeed reduce the probability of mini flash crashes. However, it is noteworthy that this mitigation strategy also leads to an influx of noise traders and an increase in short-term market volatility.

Purpose- This study examines institutional quality’s absorptive capacity in African countries’ remittances-finance nexus. Design/methodology/approach- A balanced panel data set of thirty African countries between 2000 and 2022 is used for the study. The study adopts an augmented mean group (AMG), method of moment quantile regression (MMQR), and two-step system generalised method of moment (2SGMM) as the estimation techniques due to the nature of the data set. Findings- The findings of the direct effect reveal that remittances do not constitute the growth of financial development, while institutional quality promotes the growth of financial development in the long. The moderating effect of institutional quality in the linkages shows that the interactive term of institutional quality and remittances has a significant positive effect on financial development in the region. Hence, institutional quality moderates the impact of remittances. These results are robust to different proxies of financial growth and estimates obtained from MMQR and 2SGMM. Practical implication- This study, therefore, suggests that institutional quality is essential in the linkages between remittances and financial development. Hence, remittances should be seen as one of the instruments that can be used to develop the financial sector rather than survival mechanisms for households. Originality/value- This study contributes to the literature by unearthing the absorptive capacity of institutional quality in the nexus between remittances and financial development in African countries, which extant studies have neglected

This study investigates political trust differences between urban and rural areas in Latin America, focusing on compositional effects and idiosyncratic features. Using an Oaxaca-Blinder decomposition, we analyze LAPOP data for 2019. Trust in the president, Parliament, political parties, and the Supreme Court of Justice are considered. Notably, political trust is higher in rural areas. For trust in Parliament, political parties, and the Supreme Court, the unexplained gap is slightly smaller than the explained part (45% vs. 55%). Trust in the president is solely influenced by the explained effect. Education and income gaps play the most important role in these differences.

In this paper, we examine the nonlinear relationship between the number of fiscal rules in place and compliance with the European Union (EU) numerical fiscal targets included in the Stability and Growth Pact. Using a sample composed of 27 EU Member States for a period spanning 2000 to 2021, we document that countries’ compliance with fiscal rules is positively associated with the number of numerical fiscal targets. However, this association only holds up to a specific threshold. Once this threshold is achieved, the relationship becomes negative, implying that a higher number of numerical fiscal rules may undermine compliance, thereby reducing their effectiveness. In addition, we find that general elections and frequent changes in government reduce compliance, whereas economic adjustment programmes contribute positively to countries’ compliance with fiscal targets. Findings bear critical policy implications against the backdrop of the current review of the European fiscal framework.

The aim of this work is to stress to connectivity between good public governance and financial crime, in order to attain improved sustainable development levels of countries. The rationale behind these relationships is that best institutional quality and law reduce the opportunities to avoid environmental rules, thus the ecological footprint improves. The present paper deals with the moderating role of governance on the impact of crime components (corruption, shadow economy, money laundering and cybercrime) on the sustainable development proxied by Human Development Index, Environment Performance Index, carbon dioxide emissions and green house gas emissions. Our panel dataset covers 185 worldwide countries and the time period is 2015-2022. The methodology ranges from the Pooled OLS method for panel data up to the panel threshold regression modelling. Our results provide strong evidence on the mediating role of good governance in altering the negative impact of financial crime on sustainable development, up to halving it.

We evaluate the causal impact of average neighbourhood attitudes justifying intimate partner violence (IPV) on one’s own attitudes using nationally representative data from the fifth wave of the National Family Health Survey of India. To address potential endogeneity concerns in estimating peer influences, we utilize exogenous variation in average exposure of neighbourhood women to their parental IPV in a leave-one-out instrumental variable strategy to obtain our results. We find robust evidence that a 1 sd increase in a woman’s average neighbourhood attitudes justifying IPV will lead to a 0.36 sd increase in her own attitudes justifying the same. Our results establish the importance of peer influences in defining a woman’s acceptability of IPV as justifiable, especially among less educated and unemployed women having no asset ownership, no access to media and bearing more daughters than sons, thus making them more impressionable. Our findings underscore the need for enhanced implementation of policies targeted towards women’s empowerment to arrest the perpetration of such gender-biased social norms.

The EU boasts the largest single labor market globally; EU citizens enjoy the freedom to take up work anywhere within the common market. Despite considerably diverse labor market regimes across the EU, little is known about how local labor market settings influence spatial labor mobility within the bloc. By integrating cross-country harmonized labor mobility data from the EU Labor Force Survey with the Kaitz index, a standardized measure of local minimum wage (MW) impact, I investigate the relevance of MWs for low-skilled labor mobility in Europe. Utilizing both a fixed effects model and the Arellano-Bond dynamic panel instrumental variable estimator on a sample of 103 NUTS-2 regions across six EU countries from 2003 to 2019, my analysis reveals that more substantial MWs correspond to elevated local labor inflows: On average, a one percent increase in the Kaitz index associates with a 0.03 percentage point higher worker inflow rate to the given region, indicating a Kaitz index elasticity of low-skilled labor inflow of about 0.18. This results holds for several alternative model specifications and robustness tests. Moreover, I observe substantial cross-country heterogeneity, and find particularly pronounced mobility responses for urban areas and among younger people.

Individuals vary considerably in how much they earn during their lifetimes. This study examines the role of the tax-and-transfer system in mitigating such inequalities, which could otherwise lead to disparities in living standards. Utilizing a life-cycle model, we determine that taxes and transfers ofset 45% of lifetime earnings inequality attributed to differences in productive abilities and education. Additionally, the system insures against 48% of lifetime earnings risk. Implementing a lifetime tax reform linking annual taxes to previous employment could improve the system’s insurance capabilities, albeit at the cost of a lower employment rate.

Early childhood in developing countries -where risk factors are more prevalent and resources more limited- demand effective and scalable models. We design and experimentally evaluate a telephonic assistance and messaging program for highly vulnerable families with children aged 0 to 3. The intervention focuses on supporting positive parenting practices at home, fostering language development and offer one-to-one assistance for taking up the government benefits that families are entitled to. The program was implemented in Uruguay with 1,026 families that qualified to receive support from the government agency Uruguay Crece Contigo. Treated families receive weekly calls and messages three times a week for 8 months. We find that the program increases the weekly frequency of parental involvement and reduces parental stress. Another result is that treated families achieve greater access to social benefits and programs including cash transfers, food baskets and labor market programs.

This study deals with skilled human capital formation under the mobility of students and workers. Specifically, it attempts to clarify whether study migrants are motivated to build skilled human capital in the dynamic context as host countries increase the acceptance of unskilled labour migrants. The analysis assumes an overlapping generations economy, solving maximisation problems to derive solutions analytically. Countries pursue to increase domestic skilled human capital by attracting skilled labour migrants and promoting the retention of study migrants as skilled workers after their education. Simultaneously, some countries admit unskilled labour migrants to address unskilled labour shortages. When an unskilled job is a viable option for study migrants after graduation, they might diminish their incentive to build skilled human capital. This study reveals that, in the short run, study migrants are inclined to accumulate more skilled human capital, even when host countries embrace more unskilled labour migrants. It also uncovers that these policies can coexist harmoniously in steady state. Specifically, the skilled human capital of study migrants is likely to increase in steady state with the simultaneous increases in unskilled labour migrants. The findings suggest that seemingly inconsistent policies are compatible and can achieve their respective objectives temporarily and permanently.

Success in life increasingly depends on key skills that allow people to thrive in education, the labor market, and their interactions with others. In this paper, we emphasize creativity as a key skill that is essential to open-ended problem solving and resistant to automation. We use rich longitudinal data to study the relationship between people’s creativity measured in childhood and their individual attributes and life outcomes. We find that childhood creativity predicts labor market and educational success: more creative individuals earn more during the course of their careers, work in higher occupational categories, and reach higher levels of educational attainment. Our analysis of attributes further suggests that creative individuals have a package of practical skills that allows them to thrive in work environments where learning from experience is important.

We study how workers change their work hours in response to a transitory changes in hourly wage. Using data from the New York City Yellow Taxi Cab drivers and a novel instrument variable identification strategy, our preliminary findings indicate that drivers increase their working hours when their hourly wages are higher. This outcome aligns with the conventional, neoclassical model of labor supply. Our results contribute to understanding worker behavior concerning fluctuations in hourly wages and provide valuable insights into labor dynamics.

PURPOSE: The purpose of this study is to investigate the nature and practice of strategic management process in Kosovan enterprises including the presence of formalized strategic plans. Consequently, it examines these aspects to enhance further comprehension of strategic management practices in transitional economies and offer policymakers as well as practitioners some insights regarding the strategic priorities and challenges faced by the enterprises in the Republic of Kosova. METHODOLOGY: A total of 314 enterprises participated in surveys conducted through a random sampling technique that was drawn from the final database of the Kosova Tax Administration. Construct measures that examine strategic management process, strategic plan, as well as utilization of strategic tools, were adapoted/formulated. For example, statistical analyses such as Cronbach’s alpha coefficient and nonparametric tests for association were performed on the collected data. FINDINGS: The results indicate that a large majority of surveyed enterprises do not consider the strategic management process as essential for their organizational strategy; with only 10.2% considering it as important. In the same way, formalized strategic plans, particularly those extending over five years or more are not common among surveyed enterprises; with only 31.21% having such plans. In addition to this, the findings indicate a significant correlation between the strategic management process and the use of strategic tools, while no significant correlation between the strategic plan and the use of strategic tools was found. IMPLICATIONS: The implications of this study, in terms of theory and practice, are several. Initially, the research has shown the need for more focus on strategic management practices in Kosovan enterprises including SMEs. The findings can be helpful to policymakers, business leaders, and researchers when designing strategies that will help improve strategic management practices and increase the sustainable growth and competitiveness of Kosova’s enterprises. Secondly, the research adds to existing literature by providing empirical evidence on strategic management practices in transitional economies. ORIGINALITY AND VALUE: This paper seeks to determine the extent to which organizations in transitional economies have formalized strategic plans, use strategic tools and thereby providing additional insight into the process of strategic management itself. Policymakers, business leaders, as well as researchers who want to improve their businesses’ strategy management and promote sustainable growth and competitive advantage, can benefit from these findings.

In the digital era, governments around the world have embraced advanced technologies to improve their tax administrations. This is particularly important for developing countries, where corporate tax misconducts are severer issues. This study focuses on the Golden Tax Project IV (GTP IV) in China, which initially emphasizes the adoption of digital technologies to tax administration, and investigates its impact on corporate tax avoidance. Using the difference-in-differences regression analysis, we find that GTP IV curbs corporate tax avoidance, with a more pronounced effect on non-state-owned firms, higher-risk firms as well as those with smaller size, greater financial constraints or higher financial opacity. Overall, our findings highlight the effectiveness of digitalization-applied tax administration reform in fostering a more equitable and efficient tax system. Therefore, it would motivate tax authorities worldwide to further pursue or enhance digitalization in tax administrations.

The paper aims to estimate the size of the home field advantage in international women’s football and its temporal variability, using 4,477 matches from 1969 through 2022. We document overall home advantage, home advantage over time, and home advantage across geography. Over the entire sample period, average home advantage is 53%. However, home advantage started out very high, declined to less than 60% by the 1980s, experienced further declines throughout the decades and might have reached a minimum by 2010. We show that home advantage differs across geography. Our analysis concludes that the home advantage in international women’s football has statistically converged to that in international men’s football. We postulate that this convergence was aided by knowledge, tactics, nutrition, and physical training accumulated in over a century of international men’s football.

Acknowledging the critical imperative to narrow the digital divide in the aftermath of the global pandemic and recognizing the significance of digital skills in the context of ‘servitisation’ across diverse economic sectors, this paper investigates the impact of digitalization and city development on the economic growth of developing countries. To achieve this, the study empirically tests the effects of Official Development Assistance (ODA) allocated for digital infrastructure and both urban and rural development, using the Organization for Economic Co-operation and Development (OECD) Creditor Reporting System (CRS) database. The results indicate that doubling the per-capita ODA received for digital infrastructure and city development collectively is associated with an approximate 0.3 percentage point increase in annual economic growth of the recipient country. This effect holds true even when controlling for factors such as the youth population ratio, urbanization ratio, and the initial level of digitalization. The paper also addresses potential endogeneity issues in aid literature and finds the result remains robust. Furthermore, our findings reveal that ODA for city development, when coupled with investments in digital infrastructure, is nearly twice as effective as ODA solely directed towards city development. The inclusion of city development in the study is justified by the intertwining of digitalization and city development in multiple ways, with digital infrastructure being an essential component of city development. The study provides strategic guidance for inclusive international development in the post-pandemic era, emphasizing the crucial roles of digitalization and city development.

This paper aims to examine the correlation between finance and sustainable development in the sub-Saharan EMCCA zone, with a primary focus on understanding the impact of finance on sustainable development. Due to the limited availability of data to concurrently evaluate all three dimensions of sustainable development (economic, social, and environmental), our empirical analysis specifically concentrated on the environmental dimension. To this end, we have used indicators such as CO2 emissions to measure sustainable development and bank credit, official development assistance (ODA) and financial development for finance. Employing a fixed-effect (FE) model and GMM estimation, we aimed to scrutinize this region’s Environmental Kuznets Curve (EKC) hypothesis. The findings reveal that finance, in its current state, tends to have adverse effects on sustainable development and we cannot confirm EKC hypothesis within the EMCCA zone.

With the changes in China’s industrial agglomeration, the past literature on the determinants of industrial agglomeration may not be suitable for the present. Thus, the goal of this study is to investigate the determinants of industrial agglomeration in China from a spatial perspective. Using data on China’s 31 provinces from 2003 to 2020 and spatial panel Durbin model, our results show that industrial agglomeration in adjacent areas has a positive spillover effect on the area under study. Additionally, population density shows a positive effect on industrial agglomeration. Transportation infrastructure and local protectionism are proven to affect industrial agglomeration negatively. Besides, there is a U-shape relationship between economies of scale and industrial agglomeration.

Financial policies are attracting attention as ESG investments are being introduced to combat global warming. However, this financial policy may increase the financing of polluting firms while encouraging the development of decarbonisation technologies. Hence, the development of financial markets and financial agglomeration may not necessarily lead to pollution reduction and decarbonisation. Besides, the location of firms through finance leads to pollution haven. By using an R&D-based location model, this study analyses the impact of financial and environmental policies on firm location and foreign direct investment, as well as on economic growth and pollution emissions. According to the Fisher equation, emission quota reductions decrease global pollution but do not affect location or growth. Interest rate cuts develop financial markets in terms of borrowing and grow the economy. Financial de-agglomeration in the North and financial agglomeration in the South then leads to pollution haven from the North to the South. In other words, it leads to decreased pollution in the North and increased pollution in the South. Under a monetary economy, trade liberalisation leads to the pollution haven hypothesis. Emission quota reductions can mitigate pollution increases due to monetary easing policies. A policy mix of monetary and environmental policies is beneficial for sustainable development.

This paper combines high-resolution satellite-observed inundation maps with geocoded firm-level data to identify the flood exposure at the firm level, and studies the dynamic and spatial spillover effects of inundation on corporate performance for the Chinese economy during 2000–2009. We found negative and permanent effects of floods on firm-level performance measures, and negative but short-run spillover effects on non-inundated firms in nearby neighborhoods. In contrast, non-inundated firms located 8–12 kilometers away from the inundated area expanded their production in the long run. We further identify moderating factors of inundation impacts, and characterize the aggregate effects.

This paper examines the effect of flood exposure on environmental behaviour. I rely on detailed records of flood incidents in England between 2009 and 2022, complemented with precise flood risk modelling. Using both longitudinal observed data and survey on green activities, I show that individuals living in flood-affected postcodes are more likely to donate to environmental charities and support the Green Party. There is also suggestive evidence that these individuals become more pro-environment in their daily lives. The increased engagement in green activities may be attributed to a sense of guilt, as direct flood exposure leads individuals to reconsider their actions as environmentally insufficient. However, this heightened effect does not extend to floods affecting their close neighbours.

In this paper, we make use of the rapid expansion of short-term rentals in Portugal, based on a policy change in 2014, to estimate the effects on house prices. Using a novel dataset consisting of property transaction data, from 2010 to 2017, for the metropolitan areas of Lisbon and Porto, we causally identify the impact of these reforms through a two-way fixed effects model, at the quarterly level, where we control for property-specific characteristics and location and time fixed effects. Our results suggest that a one-unit increment in the number of local lodging establishments results in a 0.142%-0.272% increase in the value of transactions, depending on the fixed effects employed, which is ensured by a set of robustness exercises. Stronger effects are found for properties with four bedrooms, in the municipality of Porto and at the upper quantiles. We also document a decrease in the number of transactions of new buildings and a positive effect on the value of stores.

We study how the COVID-19 pandemic changed the valuation of amenities in the prices of Airbnb listings in Mexico, a country with few tourism and mobility restrictions during the pandemic. Using the universe of Airbnb listings in Mexico from 2018 to 2022, we estimate hedonic price models and analyze how hedonic coefficients changed for amenities associated with lower COVID-19 infection risk and reduced face-to-face contact. Our results show that the valuation of remote-work amenities –such as workspaces–, open-space amenities –such as beach fronts–, and reduced-contact amenities –such as private spaces– significantly increased during the pandemic. Some of these valuation changes, such as those for workspaces and elevators, persist in the post-pandemic period.

This paper addresses a research gap in the study of inequality by revisiting the Kuznets curve, a prominent theoretical model that explains the rise and decline of inequality as economies develop. Our objective is to analyze the dynamics of regional inequality through a spatial lens and to incorporate spatial effects into the Kuznets curve framework.To measure sectoral GDP in China, we utilize satellite day-time and night-time imagery as traditional sectoral information is limited in Chinese cities. Using a spatial econometrics methodology, we examine a dataset comprising satellite nighttime light data, daytime land cover and net primary productivity, and sectoral GDP in 332 cities in China. Our findings reveal that night-time and day-time satellite data are valuable predictors for monitoring sectoral output in Chinese cities. We initially observe the expected inverted U-shaped relationship between regional inequality and economic development. However, this relationship becomes statistically non-significant when the structural change term is incorporated. Importantly, when considering the spatial spillover effects of inequality and structural change, the inverted U-shaped relationship is restored.This research paper contributes to the field in two key ways. First, we construct a new dataset that captures the agriculture and non-agriculture output in Chinese cities, providing valuable insights into the sectoral composition of regional economies. Second, we are the first to examine the spatial Kuznets curve at the city level in China, shedding light on the interplay between regional inequality, economic development, and spatial dynamics.

This study aims to understand circular entrepreneurship trends in different global regions by analyzing the 2014-2018 Global Entrepreneurship Monitor dataset. The content analysis of business descriptors of 79,663 unique entrepreneurs was used to position each startup within the 9R’s framework. The results reveal that startups are generally associated with “repurpose” and “recover”, which are the least desirable options for circularity within the 9R’s framework. Circular entrepreneurs are defined as those with the top 10% highest probability score in circular strategies according to the type of business they run. The BERTopic approach is applied to identify narrow topics of business ventures for these circular entrepreneurs. Some similarities (between North America and Latin America & Caribbean) but also differences (Europe) in the most popular topics across regions are discovered.

In this paper, price discrimination with respect to the organic attribute in the ready-to-eat cereal industry is quantified. I estimate a random coefficient discrete choice demand model to obtain the price-elasticity of each product. Then, with the estimated elasticities and a supply model, I recover the marginal costs, which allows to disentangle whether the amount of price difference between organic and non-organic products is due to price discrimination or due to different production costs. I find that around 6% of the price difference is due to price discrimination with respect to this attribute. Counterfactual exercises show that: i) a tax on non- organic products is welfare detrimental and does not substantially reduce price discrimination; ii) price discrimination happens due to the existence of high in- come households.

For decades, the literature on the estimation of production functions has focused on the elimination of endogeneity biases through different estimation procedures to obtain the correct factor elasticities and other relevant parameters. Theoretical discussions of the problem correctly assume that production functions are relationships among physical inputs and output. However, in practice, they are most often estimated using deflated monetary values for output (value added or gross output) and capital. This introduces two additional problems—an errors-in variables problem, and a tendency to recover the factor shares in value added instead of their elasticities. The latter problem derives from the fact that the series used are linked through the accounting identity that links value added to the sum of the wage bill and profits. Using simulated data from a cross-sectional Cobb-Douglas production function in physical terms from which we generate the corresponding series in monetary values, we show that the coefficients of labor and capital derived from the monetary series will be (a) biased relative to the elasticities by simultaneity and by the error that results from proxying physical output and capital with their monetary values; and (b) biased relative to the factor shares in value added as a result of a peculiar form of omitted variables bias. We show what these biases are and conclude that estimates of production functions obtained using monetary values are likely to be closer to the factor shares than to the factor elasticities. An alternative simulation that does not assume the existence of a physical production function confirms that estimates from the value data series will converge to the factor shares when cross-sectional variation in the factor prices is small. This is, again, the result of the fact that the estimated relationship is an approximation to the distributional accounting identity.

In this paper, we empirically examine the relationship between the novel macroeconomic attention indices (MAI) and commodity market volatility. In-sample analysis indicates that MAI contribute significantly to the volatility fluctuations in commodity markets. In addition, we employ dimension reduction techniques, shrinkage methods, and combination models in an out-of-sample exercise to assess the predictive ability of MAI, alongside a variety of economic predictors including uncertainty measures, and global as well as US economic indicators. Our empirical results demonstrate the superior predictive ability of the elastic net and LASSO models incorporating MAI together with macroeconomic and uncertainty indicators. This empirical finding is reinforced through a series of robustness checks. However, dimension reduction methods exhibit superior performance in longer forecast horizons. Finally, MAI are more informative for commodity volatility forecasting during economic expansions and non-crisis periods. Our study offers new insights on commodity volatility forecasting.

This paper studies the heterogeneous impacts on the export participation and labor training decisions of domestic manufacturers resulting from reduced trade barriers induced by a regional trade agreement. We develop a general equilibrium model with heterogeneous firm-level productivity and two export destinations to explain firm performance following regional trade liberalization. Then, we test the theoretical predictions by generalized difference-in-differences estimations. A single-destination framework shows that the decrease in India’s tariffs leads to increased export entry and training intensity by Chinese manufacturers. However, the effects of regional trade integration on firms’ skill upgrading are heterogeneous in our multi-destination setting.

Earlier research finds correlation between sentiment and future economic growth, but disagrees on the channel that explains this result. We shed new light on this issue by exploiting cross-country variation in sentiment and market efficiency. We find that sentiment shocks in G7 countries increase economic activity, but only temporarily and without affecting productivity. By contrast, sentiment shocks in non-G7 countries predict prolonged economic growth and a corresponding increase in productivity. The results suggest that sentiment can indeed create economic booms, but only in countries with less efficient financial markets where noisy asset prices make sentiment and fundamentals harder to disentangle.

Over the past few decades, there has been a notable rise in global and regional integration. In Africa, the growth of intra-African trade has had a positive impact on national economies, promoting trade diversification and sustainable development. Although this has sparked interest in seeking to deepen their understanding of economic integration in Africa, current measures of economic integration do not fully capture the intricate interactions between trading partners. However, its potential in the African context remains largely unexplored. This study aims to fill this gap by applying complex network analysis and dynamic panel regression techniques to identify the factors driving economic integration in Africa, using data spanning from 2002 to 2019. Our econometric results show that a country’s centrality of position in the African trade network is positively related to a country’s economic development, institutional quality, regional trade agreements, human capital, FDI, and infrastructure quality while trade costs, global financial crisis, and overlapping membership were negatively associated with network-based economic integration. Our findings suggest that a country could enhance its connectivity in the African trade network by identifying key economic and institutional factors of trade partners and thereby strengthening the economies of African countries.

In this paper, we allow there to be multiple traders and analyze how buyer and seller prices are influenced by competition among traders in a model of uncertainty. We start by considering a network with one seller, two traders and one buyer. The seller and buyer have strong positions and they both will try to benefit from the competition between the two traders. The traders compete in the sense of a Bertrand duopoly to choose the price where each trader aims to maximize his profit. We also examine different network structures involving two sellers and one buyer with two traders. We note that the sellers who are not subject to competition between two traders suffer from the consequences of the monopoly competition. We compute the equilibrium bid and ask prices offered by the traders for these cases. There will not be one fixed price that the traders offer the second seller and the buyer both of whom benefit from the equilibrium competition in the second network structures. Finally, we look for the maximum expected payoff for each trader by investigating the best responses to the given bid and ask price schedules. We find that one trader’s best responses depend on the conditions on the valuations for the traded good.

The Pakistani economy finds itself amidst profound economic and financial crises, leading to its consistent reliance on the International Monetary Fund (IMF). We argue that foreign exchange intervention and the maintenance of an overvalued exchange rate are among the vital causes of this crisis. Against this backdrop, this paper aims to achieve two main objectives. Firstly, it constructs an Exchange Market Pressure Index (EMPI) utilizing a Structural Vector Autoregression (SVAR) model, covering the period from January 1991 to April 2019 in Pakistan . Secondly, it evaluates the efficacy of monetary policy in managing foreign exchange market pressures. The findings reveal active involvement by the Central Bank of Pakistan in the foreign exchange market to maintain an overvalued exchange rate parity. Instances are identified where the central bank resisted exchange rate adjustments despite significant market pressures, resulting in a cumulative expenditure of USD 112 billion to sustain the prescribed parity level. Furthermore, it is demonstrated that if policymakers had not intervened to manage the exchange rate, the current parity level would be approximately Rs. 177.43 per dollar, a mere Rs. 35.92 higher than the present rate of Rs. 141.51 per dollar. Additionally, while the study highlights the effectiveness of monetary policy in managing short-term exchange market pressures in Pakistan, it underscores its ineffectiveness in the medium and long term. As a result, it is recommended that the central bank refrain from excessive direct and indirect interventions in the exchange market to uphold exchange rate parity.

This study describes how digital imports have enhanced the growth of Nigerian Micro, Small, and Medium-sized Enterprises (MSMEs). In particular, it provides strong evidence that such MSMEs have benefited from the World Trade Organization’s (WTO) e-commerce moratorium. Our findings are based on a detailed analysis of time-series data at the sectoral level of Nigeria’s MSMEs using data sources such as the MSME Survey Report of Small and Medium Enterprises Development Agency of Nigeria (SMEDAN) and National Bureau of Statistics, coupled with the data on imports of digital products from OECD Input-Output tables. This data-driven approach enabled us to pinpoint the precise contribution of digital imports. Following data collection, our analysis employed econometric panel regression techniques to assess the impact of imported digital transmissions on the productivity, employment, and output dynamics of Nigeria’s SMEs over time. Our econometric regressions suggest that for every 1% increase in digital imported inputs by Nigerian SMEs: SME GDP increases by 0.79%, SME Male Employment increases by 0.46%, SME Female Employment increases by 0.69%, Total Number of SMEs increases by 0.42%, SME E-commerce increases by 0.17%, SMEs with Exportable products increases by 0.90%, Male Labour productivity as defined by SME GDP per male employee increases by 0.61%, Female Labour productivity as defined by SME GDP per female employee increases by 0.89%, GDP per enterprise (size based on GDP) increases by 0.85%, Male Employees per SME (size based on male employment) increase by 0.59%, Female Employees per SME (size based on female employment) increase by 0.92%. The growing use of digital imports by Nigerian MSMEs has boosted labour productivity and economic growth, increased employment opportunities, and expanded the number of businesses. These findings have significant implications for policymaking to enhance business productivity and job creation. Summarily, the increase in digital imports has the potential to not only stimulate the GDP, employment rates, and the number of businesses among small enterprises, but also to elevate labour productivity and scalability.

Cryptocurrency is a remarkable financial innovation that exerts essential impact on the financial system, and its increasingly complex interactions with conventional financial market pose challenge on precisely forecasting its volatility. To this end, we propose a novel framework based on Evolving Multiscale Graph Neural Network (EMGNN). Specifically, we embed a graph, which depicts the interactions between the cryptocurrency and conventional financial market, into the predictive process. Further, we employ the hierarchical evolving graph structure learners to model the dynamic and scale-specific interactions. Meanwhile, we evaluate the robustness of our framework, and we discuss its interpretability by extracting the learned graph structure. The empirical results show that (i) the cryptocurrency volatility is not isolated from the conventional market, and the embedded graph can provide effective information for prediction; (ii) the EMGNN-based forecasting framework generally yields the outstanding and robust performance in terms of multiple cryptocurrency samples, forecasting horizons and evaluation criteria; and (iii) the graph structure in predictive process varies over time and scales and is well captured by our framework. Overall, our work brings new insights into risk management for market participants and into policy formulation for authorities.

Traditional weddings in Israel have a unique tradition of monetary gifting, where guests are expected to provide cash or check gifts, instead of household items. This practice has given rise to a new phenomenon of digital gifting, where guests can now send monetary gifts electronically through a payment link. This digital cash gifting provides a unique opportunity for behavioral economics research, as it allows for the collection of valuable data to analyze gift-giving behavior. The study of behavioral economics mechanisms can provide insights into the amount, timing, and personalization decisions of the gift givers. Our research aims to explore the impact of anchoring: the tendency to rely on a suggested value as a reference point for the gift-giving decision. We manipulate the suggested gift amount to test how different amounts influence gift-giving decisions. Specifically, we argue that high anchors may have a double-edged effect on the gift amounts, causing some individuals to increase the amounts, while others to decrease them. We draw the intuition for our hypothesis from the anchor’s chain — if you pull too hard, you might break it and achieve the opposite of the intended effect. further, our study tests for a tipping point in anchoring efficacy, beyond which the anchor is so high that guests neglect the urge to be nudged upward. Unlike previous literature based on laboratory experiments, we devise a field experiment that inspects the actual gift-giving decisions made by the guests in a naturalistic environment, providing valuable insights into real-life decision-making.

In this paper, we study how and to what extent US electricity and gas utility service firms’ dividend policy changes after the deregulations. We incorporate the Lintner’s speed of adjustment methodology and show that utility service firms sacrificed from dividend smoothing after the deregulations unlike other energy related firms or the rest US based firms from different sectors. Adopting the variance decomposition methodology, we report a sizeable co-movement between net income and payout (implying less payout smoothing) for the utility service firms. While most public firms are able to smooth their payouts, as a result of the restructuring and investment in the plants and alternative energy after the deregulation policies, utility service firms smooth their income shocks mostly by increasing their debt and end up sacrificing smoothed payouts after the deregulations in energy markets. The increased competition among these firms brought large investment costs which led to an increasing role of debt and sacrificing the stable payout policies to smooth income shocks.

The aim of this article is to investigate the time-varying effects of the global oil price cyclic shock, global geopolitical risk, and economic policy uncertainty on the financial stress of G-7 countries. We have employed the time-varying parameter structural vector autoregressive approach based on stochastic volatility (TVP-SVAR-SV) on a monthly dataset from December 2005 to May 2023. Results show that increased oil cyclic shock, geopolitical risk, and economic policy uncertainty intensify the financial stress of G-7 countries at different time frequencies (lag structures) and during major events, especially the COVID-19 and Russia-Ukraine conflict. The financial sector of France is found to be least affected among the G-7. Geopolitical risk impacts most severely the financial stress of Italy, while economic policy uncertainty mostly affects Japan. The cyclical shock of the oil price severely amplifies the financial stress of the USA, UK, Italy, and Germany. Our findings provide important policy implications for stakeholders in the G-7 and international investors.

This paper investigates the effects of macroprudential policies on the net interest margins (NIM) in the 28 European countries over the period of 1996-2019 using the unique narrative database on macroprudential policy actions collected by the experts at the ECB and national central banks (MaPPED). Employing data covering over 22000 observations on over 3000 commercial and cooperative banks, we find a general negative effect of macroprudential policy on the NIM. A tightening of macroprudential policy results in an immediate decrease of net interest margin denoting a 1.3% change from the mean level of NIM, with even stronger effects observed in subsequent annual and bi-annual changes. We also find that the effect of macroprudential policy depends on the instrument types, with lending standards restrictions exerting the most significant immediate impact on NIM levels. Other instrument types have a delayed effect on NIM, with liquidity requirements and limits on currency mismatches resulting in the strongest declines in NIM. Furthermore, we identify that the impact of these policy instruments varies based on the credit risk and, in certain cases, the cost of credit risk for individual banks.

The idiosyncrasies of family managers dominate corporate decisions, despite the fact that family management control is associated with high reputational capital, long-term orientation, and lower strategic default. This study investigates the influence of family management control on the utilization of trade credit in India using a sample of 32,946 firm-year observations from 2005 to 2022. We find that family management control negatively influences the utilization of trade credit, and the negative influence is amplified in the presence of higher family ownership. Our results imply that the effect of family management control on trade credit can be attributed to two plausible causes: financial constraints and control considerations. We note that family firms face lower financial constraints in accessing the formal sources of short-term finance, thereby utilizing lower trade credit. Our findings also validate the monitoring role of trade credit as we report that family firms with an effective governance mechanism, in terms of the presence of institutional investors, utilize a greater amount of trade credit. We then contend that the presence of institutional investors in family firms restrains the self-serving behavior of owner-mangers in their short-term financing decisions.

By employing data from 2010 to 2022, we examine whether environmental, social, and governance (ESG) performance affects TFP and the underlying mechanism through which it affects TFP. Our findings suggest that when firms are committed to fulfilling ESG responsibilities, TFP often significantly increases. In addition, heterogeneity analysis demonstrates that the impact of ESG performance on TFP tends to be greater for state-owned firms with high pollution levels, in regions with a slow marketization process, and in regions with little market attention. The mechanism analysis reveals that this impact can be achieved by alleviating financing constraints, improving technological innovation and green technology innovation, and reducing inefficient investment behavior. Our extension research finds that environmental regulation positively moderates the effect of ESG performance on TFP, whereas public environmental concern does the opposite.

This study examines the impact of traditional news and social media platforms on the crude oil market. By using a unique dataset on sentiment scores from both channels, we discover that news media convey fundamental information that leads to a permanent price impact. In contrast, the predictive power of social media exhibits significant reversals yet retains a positive long-term impact, indicating its influence stems from a mix of fundamental information and noise with fundamentals playing a dominant role. We also demonstrate that the information from news and social media does not entirely overlap, with social media offering a unique informational component not present in news content. Furthermore, we show that news and social media can forecast announcements related to changes in oil inventories and reveal that WTI futures market speculators adjust positions based on news media information, but not on social media posts. Our study provides important implications for regulators to enhance their monitoring of misinformation on social media and for market participants to understand the informational elements of news and social media platforms.

Although numerous studies have examined the crowding-out effect of housing on portfolio choice via the house price risk channel and the liquidity constraint channel, separate analysis distinguishing risky asset choices and drawing a distinction between committed and non-committed mortgage payment under homeownership types has received less attention. We investigate the heterogeneous impact of homeownership type on the risky asset choice using the 2021-2022 Survey of Economics and Household Decision-making. First, we show that homeowners with mortgage debt are less likely to participate in the cryptocurrency market compared to the stock market indicating that the higher risk associated with “speculative assets” likely induced homeowners with mortgage debt to adopt a more cautious approach to selecting their risky portfolio. The debt component separating homeowners becomes even more compelling when the risk level between risky variation is significantly larger, and the agents’ incomes are lower than a certain threshold. However, changes in housing market conditions significantly change the temperance exhibit by homeowners towards risky asset selection. We further decomposed the effects across age groups, risk profiles, net worth group. In addition, we examined the crowding out effect of house price and liquidity constraints associated with homeownership as compared to renting. The empirical evidence shows that homeowners are less likely to participate in both the stock market and the cryptocurrency market compared to renters due to house price risk and liquidity constraints associated with homeownership.

Relative poverty has, in general, become a popular source of interest for research and the public. However, only a few studies have focused on the determinants of relative poverty among the elderly in a comparative setting over time. To fill in this gap, this study decomposed relative poverty among the elderly in 21 European countries, namely Austria, Belgium, Czech Republic, Denmark, France, Finland, Germany, Greece, Hungary, Ireland, Italy, Luxembourg, the Netherlands, Norway, Poland, Romania, Solvakia, Spain, Sweden, Switzerland, and the United Kingdom, based on micro data from the Luxembourg Income Study from around 1995 to around 2022. Various counterfactuals were constructed and simulated. The results showed that relative poverty among the elderly has decreased and is mainly associated with changes in the distribution of pubic pensions, followed by changes in the distribution of private pensions. Labor market factors, especially earnings, have become more poverty-decreasing over time in most of the countries under study. Finally, the demographic structure played a positive role in driving relative poverty among the elderly.

The increasing levels of obesity and overweightness worldwide are an issue of great importance for the healthcare system, policymakers, and the public. A relatively underexplored aspect of weight is the role that one’s location can play on determining their weight. Our study seeks to address this gap by undertaking econometric analysis on weight and place in Australia. This study utilises a dynamic event study framework focusing on those who move location. We use this to look at how weight changes with a change in location and by extension how much of the overall variation in weight can be explained by place-based versus individual factors. As a secondary part of this initial analysis, we also model the effects of place on common behavioural correlates of weight. To complement our initial event study findings, we then undertake a decomposition analysis on both movers and non-movers to determine the role of place in determining differences in weight between groups of areas. Our results indicate a statistically significant and robust place effect on weight in Australia. Our initial event study indicates that place is responsible for 16.08% of the variation of weight in Australia at a 1% significance level. Our decomposition results also indicate that place can explain a portion of the variation in weight which exists between groups of areas.

This paper studies the relationship between preference for long-term orientation and graduation rate from Bachelor’s degree programs for immigrant students living in the U.S. We find that students from countries with higher preference for cultural factors such as long-term orientation and lower preference for indulgence (vs restraint) have higher graduation rate from Bachelor’s degree programs than students from the other countries. We find that the results are robust to the inclusion of factors such as the educational background of the family, income and wealth indicators and the student’s place of birth. The results hold true for graduation rate from Associate’s degree as well as Master’s degree programs. Education attainment of students from 84 countries living in the U.S are analyzed in this study. We also check for possible self-selection of immigrants by comparing with the national level graduation rates of the students’ ancestor countries using OECD and UNESCO data.

This paper quantifies the importance of political connections to congressional committee members for firms’ market power in the United States. For identification, we exploit a congressional procedure (committee exile) that leads to quasi-exogenous variations in a committee member’s political influence, and thus in a firm’s political connections. We find that, on average, 10% more successful political connections to important committee members increases firm-level markups by 0.58 percentage point for US public firms. The effects can be explained more substantially by a reduction of firms’ variable input costs, than by an increase in revenues through government procurement contracts. To estimate the effects of a firm’s political influence on its competitors, we develop a general equilibrium model with both competition for political influence that helps firms ease bureaucratic and regulatory burden following Grossman and Helpman (1994), and competition for market share following Atkeson and Burstein (2008). The model highlights how political connections influence firm market power and economic aggregates.

The academic publishing market is highly lucrative and controlled by a few dominant players. This paper evaluates to which extent a journal’s reputation poses a barrier to entry for new and competing journals and publishers. I leverage a quasi-experimental variation created by Elsevier to measure citation differentials – a core indicator for market success. Relying on the editorial process of their `parent journals,’ the publisher Elsevier launched ‘X journals,’ fully open-access derivatives of their established `parents.’ In parallel, Elsevier continued to offer an open-access option for publications in the latter outlets. Exploiting this threefold variation, a significant and adverse effect on citations exists for the novel journals. This ‘X factor’ represents a non-negligible entry barrier for potential competitors. One possible way to mitigate this could be strict open-access requirements for publications supported by research grants. My findings highlight the challenges to more open access and stronger competition in the academic publishing market.

I investigate how incumbents in the U.S. airline industry respond to threatened and actual route entry by Southwest Airlines. I use a two-way fixed effects and event study approach, and the latest available data from 1999-2022, to identify a firm’s price and quantity response. I find evidence that incumbents cut fares preemptively (post-entry) by 6-8% (16-18%) although the significance, pattern, and timing of the preemptive cuts are quite different to Goolsbee and Syverson’s (2008) earlier results. Incumbents increase capacity preemptively by 10-40%, up to six quarters before the entry threat is established, and by 27-46% post-entry. My results suggest a clear shift in firms’ strategic response from price to quantity. I also investigate the impact of an incumbent’s network structure on its preemptive and post-entry behaviour. While the results on price are unclear, a firm’s post-entry capacity reaction depends strongly on its global network structure as well as the local importance (centrality) of the route.

This study first provides evidence compatible with the idea of employment polarization in the Greek labour market since the early 1990s. Then, using an instrumental variables approach, it uncovers the potential role of routine biased technological change in explaining these developments in the employment structure. The empirical results consistently suggest that employment has polarized more into regions with a higher initial routine share. Overall, the impact of technology on the employment rate is negligible, implying that the expansion of non-routine manual employment fully compensates for the destruction of jobs in middling, routine occupations.

This study examines the effect of labor demand in traditional farming on contemporary gender equality in China. We hypothesize that regions exposed to agro-climatic conditions con ducive to labor-intensive crop cultivation would have historically fostered a greater involvement of female family members in agricultural work. The increased participation of women in farming not only contributed to household income but also elevated their social status. To examine this hypothesis, we analyze county-level data on the labor input required for major crop cultivation in China. Our findings indicate that regions with higher agricultural manpower demand exhibit more balanced sex ratios at birth and demonstrate other indicators of gender equity. These results provide support for the notion that the roots of contemporary gender equality can be traced to the historical involvement of women in farming activities.

Young Innovative Companies (YICs) have a restricted access to the capital market. An interesting question is whether subsidies can help to ease this access. To answer this question, I use a large sample of French public subsidies to YICs granted by the Public Investment Bank (BPI). After verifying the existence of an impact on the access to the capital market, I seek to understand how it is obtained. I distinguish between a prototyping e↵ect and a certification e↵ect. A prototyping e↵ect occurs when receiving a grant enables additional R&D, especially demonstration and prototype works, to be funded. This reduces the project’s technical risk, making it easier for the market to finance the undertaking. The certification e↵ect happens when the selection in the program sends a signal about the quality of the project. It therefore plays a part in reducing the asymmetry of information weighing on start-ups. I also di↵erentiate between the intensive and extensive margins of the program. The companies in our sample are particularly young, less than three years old before treatment. A large proportion have therefore not yet raised any debt. Isolating the extensive margin enables me to better understand the di↵erence in e↵ect for a company accessing credit for the first time, from a company increasing its debt. It also avoids the amplified results inherent to the introduction of transformed zeros in a log-linear model or using the inverse hyperbolic sine function. I find that public financial support has an impact on companies’ access to the capital market, both in terms of equity and debt. The immediate impact observed, for start-ups at a seed stage, suggests that it is mainly generated by a certification e↵ect. This result could also be explained by the limited size of the subsidies in the program studied. A prototype e↵ect also seems to explain the e↵ect obtained for access to debt but not to equity. These results are consistent with the risk profile of each financing vehicle.

Land expropriation is widely used by governments in developing countries to boost economic growth, but it also comes at the cost of creating discontent among the population if they perceive inadequate compensation. Using staggered changes in county-level land compensation mandated by provincial governments in China, I test how increased compensation affects land conflicts using the difference-in-differences method. Perhaps counter-intuitively, I find that an increase in compensation results in a 10% increase in land conflicts. Subsequent investigation uncovers that theincrease in land conflicts is primarily driven by the unequal increase in compensation across regions, although the overall rise in compensation partially alleviates grievances. The results do not seem to be explained by the economic incentives of governments, individuals, and companies to minimize costs when seeking to obtain land. The results highlight the need for carefully designed and progressively changing compensation policies to reduce conflict around land-transfer programs, and provide broad implications for the formulation and implementation of public policies aimed at preventing and reducing civil unrest.

The use of electoral fraud as a tool for securing victory in elections is well-documented. However, its use for purposes that go beyond winning an election remains relatively understudied. Why do autocratic leaders resort to fraud when victory is virtually guaranteed? And what factors guide their decisions regarding the allocation of fraud? Using data from Russian legislative elections (2007-2021), I confirm the presence of electoral manipulations using the excess integer values method and show the non-uniform distribution of fraud across districts. Then, on the example of country-wide protests in 2011, I demonstrate that protesting is associated with a decrease in the odds of having integer-based turnout fraud in subsequent elections by approximately 20 percent. After gathering suggestive evidence of the use of fraud to influence turnout, I hypothesize that improving autocrat’s perceived legitimacy can serve as one of the reasons for manipulating turnout upwards. By conducting a survey with a representative sample of Russian voters, I aim to examine the following mechanism: if reported electoral outcomes influence the population’s perception of the autocrat’s legitimacy, then he might want to employ fraud to achieve the desired result.

In experiments, economics students tend to act more selfishly than students of other disciplines, suggesting that economists perhaps have different personality traits. Two main explanations that the existing literature offers for the differences in behavior between economists and non-economists are: (i) the self-selection effect, and (ii) the indoctrination effect. We offer a different explanation: we argue that these differences can also be explained by differences in the interpretation of the context. We test this hypothesis by conducting two social dilemma experiments in the US and Israel with participants from both economics and non-economics majors. In the experiments, participants face a tradeoff between profit maximization (market norm) and workers’ welfare (social norm). We use priming to manipulate the cues that the participants receive before they make their decision. We find that when participants receive cues signaling that the decision has an economic context, both economics and non-economics students tend to maximize profits. When the participants receive cues emphasizing social norms, on the other hand, both economics and non-economics students are less likely to maximize profits. We conclude that some of the differences found between the decisions of economics and non-economics majors can be explained by contextual cues.

This paper assesses the transition of UK regions towards the policy ambitions of “building back greener” and “levelling-up” the UK economy. We use data envelopment analysis (DEA) methods to calculate regional economic and environmental efficiency for 41 UK ITL2 regions over the period 2005-2020, and then assess their “unconditional” and “spatial” transition probabilities of achieving one of the two or both. We find a trade-off between the two for more than half of the regions and that the costs of transition are unequally distributed. We also find that regions are more likely to become efficient in both directions if they are already environmentally efficient; less economically efficient regions are more likely to become economically efficient than environmentally efficient. Economic efficiency improvements are easier to achieve than environmental efficiency improvements, requiring stronger policy support for the latter. The high inertia of regions when it comes to both types of transition calls for the need of central and local authorities interventions to reduce regional inequalities and improve both types of efficiencies. Whilst we do not find spatial spillovers for environmental transitions, space (negatively) matters for regional economic efficiency. Without a combination of place-based and national policies efficiency there is no natural regional convergence nor levelling up, whilst the transition to net zero will remain too slow.

This study delves into the intricate dynamics surrounding environmental sustainability by examining the nexus between economic growth, energy mix, services, trade openness, and environmental quality across N11 countries. Through a comprehensive methodological framework encompassing panel data analysis and advanced econometric techniques, significant insights have been unveiled. The regression models showcased varying impacts of economic, energy-related, and trade variables on the load capacity factor (LCF), shedding light on their contributions to environmental sustainability. Notably, Granger causality findings underscored bidirectional relationships between LCF and economic growth, substantiated feedback mechanisms between renewable energy consumption and LCF, and highlighted significant causal links from non-renewable energy consumption and trade openness to LCF. Additionally, quantile regression analysis elucidated differential impacts of these variables across load capacity levels, offering nuanced perspectives on sustainability challenges. These empirical findings contribute substantially to understanding sustainability dynamics, emphasizing the multifaceted interplay between economic activities, energy usage patterns, trade policies, and environmental outcomes. The evidence presented underscores the importance of targeted policy interventions and strategic decision-making to foster sustainable development pathways, particularly in the context of N11 countries. By leveraging robust analytical tools and rigorous empirical assessments, this research paves the way for informed policy discussions and actionable strategies aimed at promoting environmental quality while fostering economic growth and societal well-being.

Abstract: Agricultural production is inherently risky due to the uncertainty in output realized from a choice of inputs. Climate change is expected to exacerbate this production uncertainty leading to global food security challenges, especially for developing countries like India. Characterizing the shape of crop yield distributions provides an empirical measure of production risk conditional on input application – fundamental to the understanding of farm-level risk management. Most existing evidence on crop yield densities – particularly at high spatial granularity – focuses on relatively developed, resource-rich regions. We estimate input-conditional crop yield densities using farm-level, observational data for major crops grown on smallholder (i.e., ~2-5 acres) farms in the semi-arid regions of India. Our work adds to the existing literature in two important dimensions. First, we use farm-level observational (in contrast with agronomic experimental data) which can provide insights into a farmer’s decision-making process – particularly the use of inputs for managing production risks. Second, we focus on smallholder farms in semi-arid regions where an understanding of the role of inputs in farm risk management is especially important given the limited availability of formal risk-mitigation strategies. Our empirical strategy utilizes Beta regressions in conjunction with non-linear instrumental variable (IV) regressions to account for the endogeneity between observed input choices and crop yields, termed as the BetaIV framework by Arora and Agarwal (2020). Beta regression models are appropriate because yields are typically non-normal and crop input decisions may impact riskiness of production besides their impact on average yields. Non-linearity in the IV regressions accounts for corner solutions in input application choices. Our estimates provide a first piece of evidence on the yield risk-properties of crop inputs and present a realistic stepping stone for agricultural policy pertaining to production risk management in semi-arid regions. JEL Codes: Q12, O13, C14, C36 Keywords: yield density estimation, risk influencing inputs, beta regression, instrumental variables

Prompt Engineering can be a useful tool to prepare students to develop critical and higher order thinking for future jobs. The focus of businesses is shifting to transform the technology landscape of their processes to include Artificial Intelligence based models, cloud computing and data analytics – to name a few. Undergraduate students in business forecasting course at Penn State University were required to work with a specific generative AI tool to develop prompt engineering skills for completing assignments. One of the challenges students faced was lack of experience for using AI tools efficiently. The paper provides examples of student artefacts and self-reflection pieces to demonstrate how students can develop prompt engineering skills for collaborating with AI based tools for gaining efficiency and higher productivity at work.

The academic grading has a potential to become a convenient motivational tool if its multifaceted influence on student effort is puzzled out. One of the numerous questions that the grading poses is: How sensitive are the students to the grading strictness? To approach this problem empirically, one needs a fluctuating academic standard, and a working identification strategy. I suggest a straightforward way of assessing marginal grading effects on student effort: using the available observational data (school transcripts), and exploiting a rounding shock to grading as a source of exogenous variation. I introduce an anonymous university data set, and use a rounding shock to the Masters students’ first-study-period grade point average (GPA) to identify the grading effects on their subsequent course choices, grades, and dropout decisions. The results show that the students are generally not sensitive to the tiny grading shock, except for high-achieving international males whose further learning outcomes seem to be remarkably affected.

This study examines the impact of happiness on income and income inequality in China, based on data from China Family Panel Studies (CFPS) during 2010 and 2018. The results indicate that both per capita income and happiness have increase in China but there are large differences across provinces and regions. Especially, the top 20% percent people own much higher income than the rest. Moreover, we find that happiness is positively and significantly associated income. Further, we apply a decomposition method which shows that the difference in happiness among different groups of people have also contributed to income inequality. The mechanism analysis suggests that physical and mental health as well as learning during spare time are the pathways through which happiness may affect income and income inequality.

This research investigates the relationship between human and social capital and multiple performance variables and business characteristics of self-employed workers and microenterprises in Mexico by using a data set that comprises over twenty thousand entrepreneurs, combining Ordinary Least Squares and Probit models. The research includes human capital investments (HCI) in addition to task-related human capital (TRHC), industry-specific human capital (ISHC), and social capital constructs. It also includes understudied dependent variables such as Returns-on-assets (ROA), revenues, assets, profits, and employee growth. The results suggest that human capital investment and social capital relate to financial performance and venture characteristics differentially. Social capital relates to these businesses, potentially by enabling access to resources. Task-related and industry-specific human capital has a greater relationship with entrepreneurship than general human capital, highlighting its superior importance in entrepreneurship. Business association affiliation is related to business size and growth, emphasizing its impact on accessing resources. Experience as a salaried worker does not translate into improved business performance but impacts assets and potentially social capital, while previous business ownership influences assets and networks. Human capital is generally linked to positive performance, but it may be influenced by unobserved implicit social capital.

We examine the impact of superstition on earnings management, and do so by focusing on the zodiac-year belief pervasive in China. In Chinese culture, it is believed that zodiac year will bring bad luck to a person, and thus people tend to be more risk-averse during their zodiac years. On this basis, we expect that CEOs are less likely to manipulate earnings in their zodiac years for fear that the manipulation is more likely to detect and that the adverse consequences of the unveiled manipulation are likely to be more material. Such an expectation is on condition that the heightened ex ante risks perceived by CEOs for managing earnings would make their expected costs of doing so surpass the expected benefits. Using difference-in-differences research design and a sample of Chinese listed firms, we find robust evidence that firms exhibit a lower magnitude of earnings management in the CEOs’ zodiac years compared to the years before and after the zodiac years. We also find that the zodiac-year effect on earnings management is more pronounced for firms with high business risk, firms headquartered in regions with a high degree of superstition, firms whose CEOs were born in highly superstitious regions, and non-state-owned firms. Overall, our findings complement the literature on behavioral economics of accounting.

How much foreign experts can contribute to productivity and growth in developing countries is an ongoing debate in development economics. We contribute to this debate by investigating the effects of foreign experts’ influx on scientific capacity of a developing country. We make use of the emigration of German and Austrian professors to Turkey from 1933 to 1940 and Turkish University Reform of 1933 as a natural experiment to establish causal relations between engagement of foreign professors in PhD education and observed scientific productivity differences of two generations of PhD students over a 30 year window. Foreign professors shaped the scientific landscape in Turkey via their collaborations with Turkish scientists and via their contributions to the training of PhD students. Our results reveal that scientists who were trained by foreign professors produce more research and also more impactful research (more cited) over the course of their academic life cycle compared to their Turkish peers. The strength of their impact is primarily driven by their collaboration structures with foreign experts. Moreover, our findings reveal that foreign professors supported women PhD students and hence contributed to gender equalization in Turkish academia.

The most corrupt countries are developing or transition countries, have low income levels, and are closed economies. More interesting, corruption is significantly positively correlated with left-wing governments in a simple cross section of countries – conditional on GDP per capita, income inequality, dominant religion, a recent history of war, and a history of communist rule. Correlation is not causality, however. In this paper, we analyze the direct relevance of government ideology for the extent of corruption, which is a question that has received little attention in the literature so far. Exploiting close electoral races in Brazilian municipalities in a regression discontinuity design, we compare the levels of corruption in municipalities where a left-wing mayoral candidate barely wins to municipalities when she barely loses, and find that left-wing governments have a significant and positive effect on corruption in the use of public funds.

Violent conflicts are typically associated with a long-lasting drag on economic output, while establishing causality based on macro-data remains as a challenge. This study attempts to build causality in the conflict-growth nexus by exploiting within-country variation across industries’ technological intensity. It identifies a channel through which conflicts can impact growth, i.e., by hindering R&D activities. The analysis is based on industry-level data from two-digit manufacturing industries for a large sample of countries over the last four decades. The results show that conflicts lead to a decline labor productivity growth, particularly in industries with higher technological intensity. The estimated magnitude of the differential effect of conflicts on labor productivity growth in high-tech industries is large. Moreover, the additional labor productivity loss in those industries in the years of conflicts does not seem to be offset in the post-conflict period neither. The findings provide an explanation for the observed patterns of durable declines in income in the aftermath of conflicts, considering the role of technological progress and innovation in long-term economic growth.

The standard model of competitive markets asserts that excess demand causes price(s) to adjust to an equilibrium with little delay. In an illiquid market, such as for real estate, reaching an equilibrium may take more time. If so then real-time evidence on market activity would be meaningful, could improve the accuracy of price predictions and could help to distinguish market conditions, such as between a “balanced market” and a “sellers’ market”. This paper has two parts. The first part uses several different types of models to focus on the conceptual distinction between an exogenous variable, an endogenous variable and a variable which is endogenous to a market but which individual participants take as given. We offer six hypotheses. The second part uses vector auto-regression to study persistence, with a particular focus on the average price and a measure of excess demand (the ratio of sales to new listings, S/NL). We show that evidence of excess demand has the expected effect on price contemporaneously and that changes in measured excess demand persist for a period of time. We also find that changes in prices have a statistically significant effect on excess demand in some cities, where the feedback affect price trends. We use monthly data representing residential real estate activities in 26 cities in Canada for up to 23 years. We also discuss whether the effect of market forces differs in different cities.

In the face of fresh water resources scarcity around the world, households are encouraged to use water-saving technologies. This study explores Chinese consumers’ preferences towards under-cabinet style water purifiers, with a focus on water efficiency label. Respondents are randomly assigned to two groups: a comparison group without label and a group with water efficiency label. In order to better understand the heterogeneity of consumer preferences, we used a random parametric model, which showed that water efficiency label was positively associated with water purifier adoption. Under the influence of water efficiency label, respondents’ preference and willingness to pay for the best level of water efficiency is significantly increased. This suggests that the label can promote consumers’ choice of more water-efficient products, providing support for policymakers to continue to implement water efficiency label and improve label standards . In addition, respondents’ health attitudes, environmental identity, perceived benefits of label and subjective norms positively influenced the adoption of water purifiers. We also used a binary response model to estimate adoption intentions for water purifiers, and the results obtained are similar to DCE.

The increasing usage of digital devices in the workplace leads to a constant data stream on employees’ actions and productivity. One way to use this data is by providing it to employees as feedback. However, it is unclear if real-time data availability should imply the provision of real-time feedback since it could be distracting to employees. We use a novel field-in-the-lab experiment in a learning factory to address this question. Participants had to manually assemble two different variants of a component. To switch from producing one variant to producing the other, they needed to retool an assembly machine, which costed time. Feedback was either provided at predetermined moments during the assembly phase (Push) or participants had to actively request it (Pull). In the Baseline, we provided no feedback. Feedback consisted of information on the number and variant of input parts and produced output. We found that participants in the Push treatment retooled more often than in the other two treatments. However, this was not robust to controlling for demographics. Further, participants who retooled less (more) often produced more (less) in the Pull treatment, suggesting that individual timing can improve the value of feedback. This difference in produced output is robust to controlling for demographics, ability, and information attitudes but vanishes when controlling for participants’ feelings of personal control and task satisfaction.

Leakage in the SSNPs in Bangladesh is a significant problem ranging from 10 to 40 per cent of the total budget. The eligible non-beneficiaries are often left out of the safety net coverage, whereas half of the beneficiaries get the allowance without fulfilling the criteria (Haider & Mahamud, 2017). This study aims to identify the gaps/ leakage and to estimate the additional resources needed to bring the eligible non-beneficiaries under the SSNPs. The study identified three key programmes (old age allowance (OAA), widow and husband deserted destitute women allowance (WA), and primary education stipend (PESP)) that represent the life cycle approach. A total of 486 respondents from three programmes were surveyed in 29 upazilla of 15 districts under eight divisions. Besides, 25 FGDs and 29 KIIs were conducted to collate the supply and demand side information. It is identified that 30 per cent of old age and 33 per cent widow beneficiaries are not eligible for any allowance. Besides, yearly around Tk 1500 crore is being spent on the non-eligible beneficiaries, which could be utilised to cover an additional 40 per cent eligible non-beneficiaries. It is suggested to redefine the eligibility criteria, development of a single ID household database, community-based beneficiary selection process, scale up the programmes in the urban areas and increase the allowance amount, etc.

In this paper we focus on the effect of skilled versus unskilled immigrants on the host country exports and particularly focus on how this effect varies with the level of corruption in the immigrants’ home country. Our sample includes 26 OECD immigrant receiving countries and the immigrant stock based on skill level from 96 origin countries. We use the Gravity econometric model framework and examine the effect of skilled versus unskilled immigrants on the host country exports and how this varies with the level of corruption in the immigrants’ home country. Keywords: Immigration, Immigrant Networks, Imports, Skilled versus unskilled, Corruption JEL Codes: F14, F22, D73, D8

This paper studies the relationship between windfall spending propensities and inflation expectations. I show that the windfall spending response to elevated expected inflation is positive but economically negligible, notwithstanding consumer cognisance of better current buying conditions. The findings are consistent with a supply-side inflation interpretation, whereby consumers treat higher inflation as a precautionary signal. Significant demographic differences are, however, present, with older and lower income consumers exhibiting relatively stronger windfall spending propensities. The findings provide little support for education-driven heterogeneity. The results are based on a novel data set of beliefs about windfall spending propensities spanning 90-thousand Australian consumers.

This paper investigates liquidity dynamics in financial and monetary markets, particularly within a network economy, emphasizing the importance of understanding liquidity for financial stability and economic health. The research utilizes the Structural Vector Autoregression (SVAR) model and employs both Cholesky decomposition and B-model identification to analyze causal relationships and capture complex dynamics in the US economy. The study highlights the significance of disruptions in debt payments by firms and the role of the money market in financing current liabilities. The findings also reveal the crucial role of the quick ratio and network effect in the economy’s business cycle, compared to other variables. Robustness checks using different identification methods and network measures validate the reliability of findings. Policymakers, regulators, and market participants can utilize these insights to manage liquidity risks effectively and establish resilient frameworks, promoting market stability and overall economic well-being.

The study explores the impact of export quality on carbon emissions and fossil fuel energy use. We estimated an OLS with fixed effects and conducted a 2SLS analysis using data for 163 countries from 1980–2014. We have found a positive association between export product quality upgrading and fossil fuel consumption for non-OECD member countries and a negative association for OECD member countries. A 1% increase in export quality increases fossil fuel consumption by 0.094% in non-OECD countries and reduces fossil fuel consumption by 1.44% in OECD countries. Similarly, we also found a positive association between export product quality upgrading and carbon emissions for non-OECD member countries and a negative association for OECD countries. A 1% increase in export quality increases carbon emissions by 0.139% in non-OECD countries and reduces carbon emissions by 1.327% in OECD countries. Our results also indicate that the Environmental Kuznets Curve (EKC) hypothesis is valid.

There is much evidence that the era of de-globalization started a decade ago. Globalization was at its peak between 2007 and 2010, and there were many restrictions on trade during this period. De-globalization is defined as reducing financial and trade exchange between international locations. This era of De- globalization can affect a country’s social, economic, political, and technological environment. The world has already suffered a ‘slowdown’ due to the financial crisis during 2008–09. Before we could even recover, the Corona pandemic hit the world. These circumstances have raised concerns about globalization in the future. And these circumstances have pushed countries towards de-globalization. The COVID-19 pandemic created new difficulties and challenges for the globe. Countries’ becoming increasingly dependent on global supply chains highlights the dangers. Due to this dependence, countries have struggled a lot for survival during the Corona pandemic. The present study is an attempt to investigate the linkages between total factor productivity and the Deglobalization Index. The study used the KOF globalization index to measure the Deglobalization index. The study incorporated an ARDL-bound testing model to see the impact of Deglobalization on total factor productivity. Effects for Both the short run and long run were captured. Two ARDL models were estimated; one captured the impact of the Deglobalization index on total factor productivity growth using exogenous variables of globalization FDI Net Inflow and Trade openness and the second was estimated to capture the impact of Deglobalization indicators on TFP growth of India. Selected Deglobalization indicators were Trade Deglobalization, Social Deglobalization, and Cultural Deglobalization. It has been observed that the adjustment coefficient (ECM) found negative and less than -1 in both the models shows convergence towards the long run between the selected variables. Model empirics show that there is a cointegration between the Deglobalization trend and TFP growth in India. Empirics of structural break have also evidently suggested that India should become self-reliant and should focus on competitiveness to fight situations of the pandemic, geo-economics, geo-political disturbances, and financial crisis. By opting for balanced policies towards globalization and Deglobalization India can achieve its goal of Viksit Bharat@2047.

This study investigates how the trade elasticity to trade barriers varies with the bulkiness of goods, measured as the value-to-weight ratio (V/W ratio). The empirical analysis presented herein offers compelling evidence that lighter goods, characterized by higher V/W ratios, demonstrate reduced trade elasticity to distance, contiguity, and colonial relationships but heightened trade sensitivity to language. These findings emphasize the importance of accounting for the variations in V/W ratios when applying gravity models and reveal noteworthy heterogeneity in trade elasticity at the country and trade-pair levels.

Research has long acknowledged the pivotal role of mothers in children’s human capital development, indicating the inappropriateness of the uniform preference assumption in traditional household maximization theory. To bridge this gap, this study integrates household bargaining theory into an intergenerational model of health, emphasizing the role of mothers and the influence of bargaining power in families’ decision-making processes. This framework offers a realistic approach to modeling household behavior, recognizing the substantial impact of parental choices on children’s prospects, and acknowledging the diversity of preferences within households. Utilizing data from the National Health Interview Survey, I find that a mother’s bargaining power is associated with better child health as well as the mother’s own health.

The effects of health insurance on mortality, and on health outcomes while alive, have been often-studied, with mixed results. We report here evidence, from difference-in-differences (DiD) analysis of individual healthcare records, both before and after Medicaid expansion, that health insurance leads to a sharp, immediate, and sustained rise in health care utilization. Increased utilization, in turn, can potentially lead to better health and lower mortality. We study Wisconsin, which in 2014 expanded Medicaid to cover childless adults with incomes up to 100% of the federal poverty limit (FPL). We follow these persons over 2011-2022 using visit-level electronic health records (EHR) records for a major, Milwaukee-based health system. We compare healthcare use for newly enrolled childless adults aged 36-64 (treatment group) with a propensity-score-balanced control group of previously enrolled persons (principally parents of minor children). Outpatient visit rates for new enrollees roughly double after Medicaid enrollment and level off at a level similar to the control group. ED visit rates and hospitalization rates jump initially from below to well above those the control group, but by 2016 fall back to control-group levels. For patients with diabetes, Medicaid eligibility predicts an immediate, sustained increase in new diabetes diagnoses. We observe heterogeneous effects, with treatment effects larger for women than men, and only non-Hispanic Whites showing a post-expansion jump in ED visits.

A vast and growing empirical literature aims at identifying plausible links between health and income. While the most compelling evidence upholding any such relationship has typically been borne by cross-country data, the relevant literature is extensive and controversial leaving policymakers confounded. We revisit the popular hypothesis, that the diseases of the poor are diseases of poverty, using granular data from census tracts on African American and Caucasian populations of urban counties in the US. In doing so, we quantify a causal link between urban life expectancy and household income by employing a machine learning approach harnessing optimum explanatory power conditional on data. We observe that every percentage point increment in household income raises life expectancy by at least 0.10 percentage points: the point elasticity of life expectancy with respect to household income varies between 0.10 and 0.142 among the African American population and between 0.145 and 0.198 among the Caucasian population of urban counties of the US.

Social issues, such as drug abuse, self-injury, and juvenile delinquency, occur at alarmingly high rates nowadays, reflecting a significant social risk among the youth. Hence, educating them on risks or risk literacy is crucial. Risk literacy is the ability to perceive risks to make rational decisions for a healthier well-being. This study aims to determine risk literacy factors influencing youth well-being . A total of 423 youth from the low-income group (B40) in Peninsular Malaysia participated in the survey. A two-stage sampling technique was employed, and data were analyzed using partial least squares structural equation modelling (PLS-SEM). The study indicates that decision-making and risk communication are the main predictors of youth well-being. The most significant impact of being risk-literate is that they can improve their well-being, which may uplift their status from B40 to middle-class society.

The objective of this study is applying a utility based analysis to a comparatively efficient design experiment which can capture people’s perception towards the various components of a commodity. Here we studied the multi-dimensional poverty index and the relative importance of its components and their two-factor interaction effects. We also discussed how to model a choice based conjoint data for determining the utility of the components and their interactions. Empirical results from survey data shows the nature of coefficients, in terms of utility derived by the individuals, their statistical significance and validity in the present framework. There has been some discrepancies in the results between the bootstrap model and the original model, which can be understood by surveying more people, and ensuring comparative homogeneity in the data.

In developing countries like Africa, changing climatic conditions aggravate gender-based violence (GBV) and contribute to a rise in child marriages and females’ genital mutilation (FGM) as it has a deep adverse impact on livelihood and exacerbates poverty. This in turn incentivise families to marry young daughter to reduce the numbers of mouth feed in exchange for a bride price. Given this backdrop, our study tries to understand the decision of female genital mutilation or excision from an economic point of view. In this study, we explored to what extend the climate change adversity affect the household decision making of FGM, and how climate adversity affects the prevalence of FGM and education of women and girls in West Africa. We have proposed a theoretical model of household decision making, which leads to two important propositions that ‘climate adversity aggravates FGM and inversely affect girls’ education’ and ‘promotion of girls’ schooling decrease FGM’. Using the DHS database of selected west African countries, we have tested the above two hypotheses. Our estimations support these two propositions. Our results indicate that extreme weather conditions like, high temperatures, heavy rainfall of high humidity increase the probability of FGM. The significance of the disaster dummy indicates that if the country faced any kind of natural disaster within past two years, it increases the probability of FGM. We further, find that the climatic conditions affect men’s and women’s opinions differently. Women feel that high temperature reduces the probability of FGM being stopped over continuing the practice, whereas men think the opposite. But in case of heavy rainfall or high humidity or any natural disaster, men and women both at the household level prefer to continue the FGM practice rather than stop it. Finally, we indicate some policy dimensions of the study.

The causal relation between innovation and growth is established in the theoretical literature, which has resulted in pro-patent policies. However, the empirical findings do not provide evidence for the positive impact of patenting on innovation and firm growth. To address this puzzle, I focus on the blocking aspect of patents for subsequent innovators, who build their innovation on a set of overlapping patents or a patent thicket. I examine the impact of patent thickets on firm growth for U.S. public manufacturing firms from 1980 to 2003. My findings show a negative impact from patent thickets and their instrumented impact on firm growth. A systematic time effect from patent thickets on firms’ growth due to the US pro-patent shifts is present. The growth of large firms is not penalized by denser thickets after the pro-patent shifts, probably because of such firms’ large patent portfolio and bargaining power. However, small firms’ growth is lowered due to their thickets. My findings also indicate that the patent thicket effect on firm growth is conditional on patent intensity, patent thicket spillovers, and the age of firms.

This study for the first time evaluates the impact of fossil fuel subsidies, CO2 per capita, and oil rent per GDP on energy consumption per GDP of the Middle Eastern main oil exporters countries (Bahrain, Iran, Iraq, Kuwait, Oman, Qatar, Saudi Arabia, and the UAE). For this study, Spatial models of SDM, SAR, SEM, and SAC have been used from 2010 to 2021. The Finding revealed that SDM and SAC models are recognized as the best models to evaluate spatial effects, and the fixed effects have a superior over random effects in this study. Moreover, the results indicate that fossil fuel subsidies have a pronounced impact on the energy consumption of oil-exporter countries. A 1% of the surging in fossil fuel subsidies contributes to 0.05 % of total energy consumption in this region. Likewise, although, oil rent and CO2 emission have a positive and significant impact on energy consumption, the influence of their effects is less than fossil fuel subsidies. Furthermore, the findings of the SDM model demonstrate that the strategy of a country in the region to increase (decrease) the fossil fuel subsidies would have a positive (negative) impact on a neighboring country’s energy consumption. The result implies the importance of establishing a collaborative approach among countries in the region to address the issues of energy consumption and CO2 emissions.

This paper investigates the impact of climate change on women’s agency in Bangladesh. Utilizing a novel dataset linking meteorological data with information on women’s agency from the Bangladesh Demographic and Health Survey, and controlling for a variety of weather indicators in flexible specifications, we find that dry shocks increase tolerance for intimate partner violence among poorest women in agriculture-dependent communities, thus amplifying existing socio-environmental vulnerabilities. Climate resilience projects funded by the Bangladesh Climate Change Trust (BCCT) moderate the negative impacts of dry shocks on intimate partner violence, indicating an important role for initiatives that appear to have positive externalities in terms of ameliorating the harmful consequences of climate change on women. Our findings offer insights into the complex environmental and social dynamics that shape gendered climate change effects, and highlight the role of policy interventions in fostering resilience and women’s wellbeing.

In the midst of Bangladesh’s power and energy crisis, our study introduces a pioneering approach by integrating the psychological Perceived Stress Scale-10 (PSS-10), customized for six distinct scenarios within the crisis, to measure household stress levels. Through a comprehensive national survey, we explore stress triggers and household perceptions towards the energy sector, focusing on the supply and pricing of electricity, gas, and fuel oil. This research focuses on socio-economic factors, political beliefs, and environmental attitudes as principal stress indicators while establishing the PSS-10’s statistical reliability. By utilizing Multivariate OLS, Random Forest, and Ordered Probit models, we identify key variables – such as education, income, urban residency, geographical discrepancies, age of the household head, and several political and environmental beliefs – that significantly correlate with stress levels. In contrast, factors like household size and the sex of the household head show minimal impact. However, our analysis suggests that stress variation might also be significantly influenced by households’ energy and power consumption behaviour, an aspect beyond the scope of this study. Our findings mark a significant advancement in policy analysis, offering a nuanced understanding of public sentiment and paving the way for prioritized, effective policy interventions in Bangladesh’s energy crisis landscape.

The existing evidence about how the industry responds to tighter environmental regulation trends is inconclusive. Several studies have identified a positive correlation between environmental regulations and innovation, but the relationship may not be causal. In this study, we investigate this relationship using a multiplicative interaction panel model. We distinguish two complementary measures of environmental regulation, the OECD Environmental Policy Stringency (EPS) indicator and energy prices and interact them with pollution and energy intensity as industry characteristics respectively. Using data from OECD manufacturing sectors during 2000–2019, we find that increases in energy prices have a negative and statistically significant impact on innovation, especially for energy-intensive industries. In contrast, increases in EPS have a positive effect on innovation. We demonstrate that these results are unlikely to be influenced by reverse causality using the two-step system generalized method of moments (GMM) estimation methods and are robust to a range of checks.

In a trade-connected world, an adverse impact on economic growth on account of temperature shock in one economy may have a spillover effect on other economies. The current study quantitatively evaluates the impact of temperature shock on economic growth, during 1971–2019 for 168 economies, through direct and spillover channels. Our findings indicate that, while a temperature shock engenders an overall adverse effect on economic growth of all economies, only tropical economies experience a direct adverse effect, which is then transmitted to their non-tropical trade partners. The spillover effect is significant and more substantial for non-tropical economies than their direct effect. Among the sectors, the non-agriculture sector is sensitive to the spillover effect. Finally, the overall adverse effects on poor and rich economies hinge upon the direct and spillover effects, respectively. In our analysis, except for rich tropical economies, all experience an overall adverse effect.

The analysis uses a difference-in-differences approach to examine the effect of the Regional Greenhouse Gas Initiative (RGGI) on electricity prices. Results suggest that following the announcement of the RGGI in 2005, wholesale electricity prices did not increase over time. However, coinciding with the electricity market restructuring, re- tail electricity prices increased by 9%. The retail price differences between RGGI and non-RGGI states ten years after the RGGI announcement are similar to those before 2005. However, during those ten years, states under RGGI experienced a significant reduction in CO2 emissions that co-occurred with a transition to cleaner electricity- generating technologies. The analysis also suggests that the industry’s response to the environmental regulation does not initially affect electricity prices. Howbeit, with time, as the reduction to the aggregate emission cap became more significant, electric- ity prices increased: In 2014, RGGI adjusted its aggregate emission cap to about 50% of its level in 2008, and electricity prices increased by 0.66 to 1 cent/kWh.

Abstract Purpose – The purpose of the study is to examine the energy-growth nexus in Ghana, accounting for regime change, fluctuations, and business cycles characteristics of the variables from 1971-2020. This is important because the direction of causality between the variables could be hidden by the presence of structural breaks, regime change, reforms, or crises in general. Therefore, fitting a linear model may not capture the entire characteristics of the data. Design/methodology/approach – The study employed the Markov-switching Vector Autoregressive (MS-VAR) model and regime-dependent impulse response functions. This model accounts for the non-linearity in the data, and the coefficients depend on the state of the economy. Results – The results from the MSIAH(2)-VAR(1) model indicate that economic growth Granger causes electricity consumption only in regime 1 during 1978-1984, 1998-2007 and 2016-2020. This regime shows the period of the energy crises and recession episodes in Ghana over the years. In regime 2, however, no Granger causality was found between the variables, which is line with the neutrality hypothesis. The regime-dependent impulse response functions showed that a shock to electricity consumption reduces economic growth in regime 1 but increases it in regime 2. On the other hand, a shock to economic growth increases electricity consumption in both regimes. That Policy recommendations are provided based on the findings of the study. Originality – In previous studies on Ghana, lack of consistency on the direction of causality between electricity consumption and economic growth is a result of regime shifts, nonlinear dynamics, and time-varying relationships among these two variables. This study accounted for these limitations.

The lack of reliable access to energy poses a significant impediment to achieve sustainable development goals in developing nations like Pakistan. Pakistan is ranked 115th among 137 economies in terms of reliable supply of electricity to households. Consequently, households are compelled to explore alternative and affordable energy backup solutions such as uninterrupted power supply, compact generators, and solar panels. This study endeavours to access household preferences for improved electricity backup alternatives and estimate the willingness to pay for the attributes of enhances electricity backups. Employing the latest Discrete Choice Experiment approach, the study incorporates four attributes: uncertainty, environmental safety, loan availability and upfront cost of superior electricity backup alternatives. A three-stage sampling technique was utilized to randomly select 501 households in the twin highly populated cities of Pakistan. Panel mixed logit regression was used to investigate heterogeneity in consumer preferences and discern trade-offs among different attributes of electricity backups. The results reveal that consumers are less willing to pay for alternatives with environmental safety and loan availability, while demonstrating a greater inclination to pay for alternatives with low uncertainty to mitigate the impacts of blackouts. Furthermore, the study observes that consumers, who own houses, are more likely to invest in solar panel systems compared to those residing in rented houses. The study concludes that households prefer to invest in a costly yet less uncertain electrical backup system to avoid the disruptions caused by blackouts.

Maintaining soil quality in the face of increasing human pressure on lands is a major challenge. Policy efforts to improve soil fertility tend to inform farm-level decisions – but adoption of policy mandates depends upon farmer perceptions about soil quality which drive their subjective cost benefit calculations. Perceptions are likely inconsistent with data-based evidence because expectations about unobserved soil quality are typically formed on the basis of observable (but) imperfect proxies like crop yields. We characterize soil quality perceptions of Indian rice-growers addressing how, if at all, subjective soil quality perceptions (from primary surveys) deviate from corresponding data-based evidence (recorded in soil maps). Further, we evaluate potential drivers of farmers’ soil quality misperceptions, including growers’ economic status, demographic information, and farming history. Finally, we explore spatial patterns in soil quality misperceptions and their linkages with farm-level decisions. We found that a majority of farmers in our sample consistently perceived soil texture but inconsistently perceived soil fertility on their farms relative to the respective data-based measurements. Higher crop yields and greater ease of farming (measured by wealth and irrigation availability) were associated with better soil quality perceptions. Educated, landowning farmers and those belonging to forward castes were more likely to perceive higher soil quality when compared with the respective counterparts. Both consistent and biased perceptions of soil quality were found to spatially clustered and exhibited significant spatial heterogeneity. Lastly, a Chi-squared test of independence revealed that over-perceptions of soil quality were associated with lower nutrient supplementation and lower incidence of crop residue burning. On the other hand, under-perceptions of soil quality were less likely to affect (and be affected by) farm-level decisions. Our findings suggest that land management policy can be improved by incorporating farmers’ subjective perceptions about their soil quality.

Do emotions affect economic behavior? We identify two transmission channels of negative emotions to consumption, one predicted by economists and one predicted by psychologists. We use self-reported financial stress and mental distress to identify negative emotions and use current and expected spending to capture consumption behavior. We find that the psychology transmission channel dominates when budget constraints are not binding. As a coping mechanism, consumers increase consumption to regulate the negative emotions caused by stress. Our results are in line with appraisal models of emotions where the perceived cause of the emotion rather than its pleasantness drives behavior.

I build an equilibrium lifecycle model of wages that combines human capital accumulation with on-the-job search in a frictional labor market. In the model, heterogeneous workers endogenously invest in human capital accumulation and search effort while firms post jobs. I discipline the model using microdata from the SIPP. Using the calibrated model, I show that on-the-job search is the driving force behind lifecycle wage growth while heterogeneous human capital accumulation is the driving force behind lifecycle wage dispersion. Then, I use the model as a laboratory to study the effects of tax and transfer progressivity. An increase in progressivity decreases wages, primarily due to reduced on-the-job search effort. Furthermore, interactions between human capital, search, and job posting amplify the decrease in wages. Surprisingly, increasing progressivity has little effect on wage dispersion because the effects from the human capital and search channels offset each other.

This paper studies the impact of government expenditure on inflation through the lens of an augmented Phillips curve implied from a structural New Keynesian model. Our estimation results, based on external instruments, show that the augmented Phillips curve has a flatter slope than the canonical specification, and government expenditure has a negative coefficient. Changes in government expenditure account for a substantial portion of inflation variations and provide new insights into the ‘missing disinflation’ puzzle. We also observe a negative response of both inflation and inflation expectations to government expenditure shocks, which can be rationalized by the supply-side channel emphasized in our theory.

The research explores the heterogeneous and persistent effects of net worth shocks, utilizing a novel dataset called CountyPlus that spans over 3,058 US counties from 2003 to 2019. By applying the local projection (LP) methods, it’s revealed that the effects of these changes are heterogeneous; they differ greatly from one region to another, depending on local financial conditions and nominal wage frictions, specifically collateral constraints and downward nominal wage rigidity (DNWR). The study highlights that these effects exhibit asymmetries and non- linear patterns that go beyond what standard linear models can explain. A simplified two-agent general equilibrium model is introduced to illustrate the underlying mechanisms, showing that they can lead to slow recoveries and persistent slumps following adverse shocks, as seen in the Great Recession. Our findings underscore the importance of accounting for heterogeneous and non-linear effects when designing policies to foster economic resilience.

It is inferred that the COVID-19 pandemic may have resulted in a spike in intimate partner violence (IPV). Recent empirical studies in this area provide mixed results from across the world, while analyses on the global south are scarce. In this study we investigate the effects of COVID-19 pandemic on possible physical, emotional, and sexual violence on women by their intimate partners in India. We analyze the household level data using the fifth wave of the National Family and Health Survey conducted from 2019 to 2021 in districts in which the survey was conducted both in the pre- and post-pandemic periods. For identification, we utilize the exposure of households to the pandemic depending on the date of survey and then focus on replies to the relevant IPV questions. Unlike some existing studies in other countries that use different measures of IPV, we find that women are less likely to report incidences of emotional or sexual (but not often physical) violence by their partners after the pandemic-induced lockdown. This fall in IPV is not a mere time trend because we do not observe any evidence of a negative trend in IPV in the period before the outbreak. We even employ a difference-in-difference model using the previous round of survey (NFHS-4) and IPV incidence among women from districts, where the survey was conducted post the first wave in comparison to those where the survey was conducted before the outbreak. We find a significant reduction in domestic violence, underscoring the robustness of our findings. Additionally, we observe that the fall in IPV is mainly pronounced in the rural areas and in the states with low gender equality. We conclude by discussing the possible channels for this result such as male backlash, where males increase violence towards wife when they do paid work.

We assess price dispersion in retail markets and its sources over time. Using a product-detailed price database, we document a consistent divergence of prices over time in retail markets in Uruguay: price dispersion increased by 3.1% in fifteen years. Next, we analyze microeconomic and macroeconomic factors that correlate with price dispersion. We differentiate the effect in the short-run—i.e., static differences between markets—and long-run effects—if these effects increase or decrease over time. Macroeconomic factors fluctuate over time in their impact on price dispersion. Microeconomic factors, mainly competition between stores and differences in category assortments between stores, have a substantial shortrun correlation and an increased effect over time. When we add interactions to the trend, our measure of price dispersion, we found that price dispersion is twice higher: 6.3%.

We study the effect of the upsurge of natural resources income from the commodity price boom of the 2000s on the functional distribution of income. To do so, we build a general equilibrium model of Dutch disease that characterizes how natural resource windfalls affect equilibrium factor shares. The theory shows that the response of factor shares to exogenous changes in commodity prices depends on the relative intensity of factors within the tradable and natural resource sectors. We construct estimates of income shares accruing to human capital, raw labor, physical capital, and natural resources, and quantify the effect of the resource boom on their distribution. For identification, we use a differential exposure design to instrument commodity prices. We find that a price-induced natural resource boom negatively impacts the total labor, human capital, and physical capital shares, while the raw labor share remains unchanged. Our estimates suggest that the natural resource boom explains nearly 22 percent of the global decline of the total labor share during the 2000s. We also find a redistribution effect within labor income that indicates an unevenly distributed fall of the labor share against human capital. Besides, we document an attenuation effect on the increasing trend of the physical capital share. These results imply that the commodity price boom of the 2000s slowed the pace of growth of inequality.

Economic policy uncertainty, both globally and domestically, influences the cost structure of firms, subsequently impacting various indicators of firm performance, notably Total Factor Productivity (TFP). This study explores how different aspects of the business environment act as facilitators or barriers to firm productivity in India, where the concept of ‘ease’ is viewed through the lens of reducing the ‘cost’ of conducting business. Drawing on novel data from the Ministry of Corporate Affairs covering the period from 2012 to 2020, the key empirical findings indicate that investments in land, logistics, postal and telecommunications, financing, and compliance contribute positively to the TFP of Indian firms. Conversely, spending on utilities, legal fees, and salaries is expected to impede TFP. Furthermore, the interplay between firms’ cost of doing business and the overall national business environment including the quality of institutions, degree of financial independence, and the state of infrastructure, reaffirms these findings. However, when it comes to delivering necessities, the inefficiencies in the public services delivery system are observed to be one of the critical factors in impeding TFP. The robustness of the results, verified through analyses at both state and industry levels, underscores the diversity in how the cost of conducting business impacts TFP across firms.

The contribution of this paper is twofold. First, it analyzes Italian personal income distribution changes between 1991 and 2020 using the ‘relative distribution’ method. This nonparametric tool uses all distribution information, unlike summary statistics. The analysis documents how distributional changes over time hollowed out the middle of the income distribution and increased household concentration around the highest and lowest deciles, causing polarization to rise. Second, and most importantly, the paper develops a novel methodology to quantify the drivers of distributional changes by directly relating the impact of changes in the expected values of the covariates on the relative polarization indices, which code the direction and magnitude of distributional changes. Results show that the household head’s age, education, and employment status increase the income distribution’s polarization over time. When the household’s head is female, foreign-born, or from the Centre/South/Islands, a counter-polarization effect occurs.

Does market access to high-income countries increase product innovation? This study investigates this by exploiting firm-level variations in export activities and the removal of externally imposed export quotas following China’s accession to the World Trade Organization in 2001. The findings reveal that improved access to high-income countries accounts for 26.35\% of the observed increase in product innovation by Chinese firms between 2000 and 2007. The results also demonstrate that these gains are driven to a large extent by increased revenue and knowledge regarding the variety of new products obtained by trading with high-income countries.

This paper aims at assessing asymmetric dynamics among migration preferences and various security and economic factors, focusing on the movements from Syria to Türkiye and then to the EU via the Greek sea borders (2000M1-2022M12). We perform an economic analysis by developing a utility model, according to which migration preferences depend on security and employment and empirically test asymmetric responses of migration to corresponding shocks. We contribute to the literature by finding that migration is downwards sticky. Despite that theories of international relations (IR) may not be monolithic, the magnitude of security impact on migration implies that the state remains the primary actor responsible for managing this phenomenon, which brings us closer to neo-realism theory. Our findings reveal the factors that lead to the downwards stickiness of migration thus contributing to a better understating of the incentives for migration and to the formulation of more efficient policies.

This paper investigates whether asymmetric consumption responses to either contractionary or expansionary monetary policy shocks depend on the share of adjustable-rate mortgages (ARMs). European data, consistent with the existing literature, indicates that consumption decreases more as the share of ARMs increases in response to contractionary shocks. However, consumption does not increase more to expansionary shocks in a country with a higher share of ARMs, yielding a novel finding in the literature. Both household-level micro evidence and our quantitative model emphasize mortgage refinancing costs, rather than the share of ARMs, as the primary channel for transmitting expansionary monetary policy to consumption. Even under fixed-rate mortgages, households can still lock in their mortgage rates at a lower level after an expansionary monetary policy shock, thereby reducing payment burdens over the long term and increasing consumption.

This paper studies the behaviors of uncertainty through the lens of several popular models of expectation formation. Full-information-rational-expectation (FIRE) predicts the ex-ante uncertainty and the variance of ex-post forecast errors are both equal to the conditional volatility of shocks to the fundamentals. Incomplete-information models such as Sticky Expectation (SE) and Noisy Information (NI) and non-rational models such as Diagnostic Expectations (DE) predict distinctive rankings of these moments. It is also shown that uncertainty provides additional parametric restrictions to favor SE over NI as a model of information rigidity, although both predict similar aggregate patterns of forecast errors and disagreement.

We provide evidence of international spillover of US monetary policy considering three trans- mission channels. In a new framework, we first use a comprehensive dynamic time and fre- quency domain analysis and identify the main transmission channel (spillover) of US monetary policy to be through interest rates followed by asset prices, and the exchange rate channels respectively. We find that the most significant spillover was at the onset of the COVID-19 pandemic, with other peak transmissions being during the European sovereign debt crisis (ESDC) and the global financial crisis (GFC). As a novel contribution, we show that these spillovers can be used as external instruments to remove the prize puzzle for Australia. We further show that US monetary policy could undermine the domestic monetary policy of Aus- tralia. Our findings suggest international interest rate-channel as a dominant transmission channel for cross-country monetary policy spillovers.

Our study analyzes the impact of debt moratorium policies, possibly the oldest approach to addressing repayment problems. Using Colombian administrative data, we compare two groups of firms: those narrowly meeting moratorium criteria and those missing it. Our findings show that stressed firms accessing moratoria enjoy favorable loan conditions on subsequent borrowing: higher loan amounts and lower interest rates, which in turn drive increased investment and employment. We propose a quantitative general equilibrium model to assess short- and long-term implications, and find reduced liquidity concerns alongside heightened default risk. Importantly, our research underscores welfare benefits of interest forgiveness during debt suspension.

Climate change impacts international trade. The literature suggests that this relationship is driven by the damage to infrastructure and reduced productivity caused by this global phenomenon. Furthermore, recent research indicates that the impact on energy consumption could explain the real effects of disasters in the United States. Using a sample of 67 countries during the period 1986–2016, we analyze whether the secular increase in global temperatures and the occurrence of drastic climate events (wildfires, floods, extreme temperatures, epidemics, insect infestations, storms, droughts, and landslides) affect countries’ energy consumption and labor productivity, which can subsequently impact international trade. By estimating a theory-based gravity model, our results suggest that energy intensity is the channel through which rising temperatures affect international trade. Furthermore, the impact of events on international trade does not seem to be channeled through either energy efficiency or labor productivity. A deeper analysis suggests the key role played by China in this regard. The Chinese government’s enormous investment in infrastructure since 1998 to manage these types of disasters seems to be the most reasonable explanation.

This paper evaluates the effect of Brexit uncertainty that arises due to the Brexit referendum on the productivity of the European Union (EU). For this purpose, the supply shock to the domestic firms of the European countries is focused. Using the two‐digit industry‐level data, the results show that Brexit uncertainty adversely affected the total factor productivity, labor productivity, and capital productivity of the domestic firms as the imports from the UK decreased after the referendum. The paper also finds that Brexit uncertainty tends to harm new firms. Moreover, medium‐aged firms are not adversely affected by the Brexit uncertainty. Furthermore, firms with foreign ownership are likely to adjust to tackle the supply shock from Brexit. Using the Difference‐in‐differences (DID) specification, the results show that there is an adverse causal effect of Brexit uncertainty on the productivity of the European countries. As a robustness check, Synthetic Difference‐in‐differences (SDID) further confirms the adverse causal effect of Brexit uncertainty on productivity.

Parents’ education and the time they spend with their children are crucial for child development and human capital formation. We examine the returns of parental education on children’s cognitive development and academic performance, and how these effects vary by ethnicity. Using longitudinal data and random effects models, we identify test score gaps by ethnicity and by parental education. The gaps remain after controlling for socio- demographic and school characteristics, time use and ability. Generally, parental education facilitates intergenerational transmission of human capital across ethnic groups in similar ways. However, in some cases, we observe diminished returns to parental education for ethnic minorities, especially among Indigenous children, boys, and children at the lower end of the test score distribution. In a few cases, there are increased returns to parental education for ethnic minorities, specifically among children of Asian origin. Cultural inheritance and exposure to racism explain some of these ethnic differences. We highlight that test scores, particularly in numeracy, are significant predictors of young adults’ university aspirations and the Australian Tertiary Admission Rank, which are required for university admission and translate into better labour market outcomes. Our results have policy implications with respect to structural barriers and equity in the education system.

This paper examines racial discrepancies in teachers’ evaluations of student achievement, conditional on standardized test achievement. After correcting for measurement error in standardized test scores, results indicate teachers evaluate Black students as higher achieving than White students with the same standardized test achievement. This finding stands in contrast to prior findings on Black-White teacher assessment gaps. Further analysis indicates these findings are consistent with two potential explanations: first, standardized tests may exhibit bias against Black students, and second, teachers may inflate assessments of Black students relative to White students due to social desirability bias.

Like most other countries, China has designed a bulk of social policies to combat income poverty. This paper investigates relative poverty in China and analyzes the effectiveness of government and private transfers in alleviating poverty, relying on data from China Family Panel Studies (CFPS) during 2012-2020. The data allows us to decompose the trajectory of the market income poverty to disposable income poverty into five specific government and private transfers. The results indicate that until 2020, there are above 24% population living in relative poverty in China. Both relative market income and disposable income poverty have decreased between 2012 and 2020 but the overall redistribution has decreased as well. As far as specific transfer programs are concerned, old-age pensions have the largest antipoverty effect (58%), followed by government subsidies (21.15%) and private transfers (16.85%). Instead, the antipoverty effects of compensation for land expropriation and housing demolishment and charity donations are limited (3.37% and 0.63% respectively). Old-age pensions have generated a relatively larger redistributive effect in the urban area than in the rural area, while in the rural area government subsidies, private transfers and charity donations are more efficient in reducing relative poverty than they do in the urban area. Finally, the redistributive effects of the transfers are highly determined by their budget size rather than their targeting.

Based on the UTAUT2 model, this study investigates which factors influence Chinese consumers’ intention and usage behaviour towards mobile health (mHealth) applications and introduces the factor of personal innovativeness in order to gain a comprehensive and in-depth understanding of consumer behaviours. A total of 872 people were surveyed using an online questionnaire, and the data was then analysed using PLS-SEM. The results indicate that, in addition to effort expectancy, performance expectancy, social influence, facilitating conditions, hedonic motivation, habit and personal innovativeness have a positive and significant effect on Chinese consumers’ intention to use mHealth apps, with habit being the key factor influencing people’s behaviour intention and use behaviour. And gender has been found to have a moderating effect. This provides for the promotion and design refinement of mHealth applications.

The development of vaccines has long been viewed as a critical public health tool to raise immunity against the COVID-19 virus and to reopen economic activities globally. Against this background, this study examines the impact of COVID-19 vaccinations on economic outcomes and mental health services in the U.S. We employed the Household Pulse Survey covering 549, 950 and 57, 892 vaccinated and unvaccinated individuals, respectively. For the causal analysis, we control the differences between the vaccinated and unvaccinated groups using propensity score matching (PSM) and weighing methods. Economic outcomes include whether individuals work on-site, telework or work from home, in-store shopping, job loss, or food sufficient. We also consider whether individuals experience mental health distress and receive mental health services as a potential outcome. The empirical results show that the probability of working on-site, in-store shopping, food sufficiency, and using mental health services are significantly higher among the recipients of the COVID-19 vaccines than non-recipients. We also find that the likelihood of teleworking and job loss decreased significantly among the recipients of the COVID-19 vaccine compared to non-recipients. The magnitude of the estimated impact across race and ethnic groups is mixed, which shows that vaccination effects are heterogeneous across the races/ethnic groups in the sample.

How does patent enforcement affect subsequent innovation? I exploit patent infringement litigation in the United States to analyze the effect of patent enforcement on cumulative innovation. The results imply that subsequent innovation increase after a case is filed in a court. While there is a strong increase during the litigation period, the relative effect size decreases in the years following the closure of the case. Further results imply that signals about the value of the patent and reductions in asymmetric information are particular driver of the increase in follow-on innovation. Although there is a general positive effect, subsequent innovation show a low degree of novelty and are close to the litigated patents in terms of technological proximity and general similarity.

The impacts of digital financial inclusion on the economic growth was of great attention recently. Since the lack of comparative study on multiple countries, we makes empirical analysis on global digital financial inclusion data which includes more than 90 countries as a supplement to this field. Based on the Global Findex Database 2021, we verify the promoting function of digital financial inclusion on economic growth among worldwide countries. Besides, through inequality decomposition, we proved that digital financial inclusion performs better in developed countries with higher economic development level and more mature financial system. We also verify the effectiveness of traditional channels in worldwide scale through which digital financial inclusion promotes the economic growth, i.e. encouraging consumption, innovation and entrepreneurship.

Innovativity—an economy’s ability to produce the innovations that drive TFP growth—requires ideas and the ability to process those ideas into new products. We model innovativity as a function of endogenous idea processing capacity subject to an exogenous idea supply constraint and derive a method to identify innovativity that is independent of the TFP data itself. Using exogenous shocks and theoretical restrictions, we establish that: i) innovativity predicts the evolution of average TFP growth; ii) idea processing capacity is the binding constraint on innovativity; and iii) TFP growth fell after 1970 due to a fall in idea processing capacity, not idea supply.

While nonprofit organizations hold only about two percent of granted patents in the United States, their patents represent important contributions to innovation. Text analysis reveals that nonprofits make disproportionate contributions to canonically under-provided areas of innovation, including use-inspired basic research, green, and medical patents. Moreover, nonprofit patenting is concentrated in technological classes that contain public goods. Furthermore, nonprofit patents stand out for their higher citations and importance scores, reflecting a unique blend of impact and novelty in their contributions. The endogenous growth theory assumption, that patents support economic growth by aligning technological progress with profit, fails to capture the unique contributions of nonprofits in the patent landscape. These contributions not only enhance technological and societal impact, but also align closely with the nonprofits’ prosocial missions.

Forest plantations are increasingly valued in developing countries for providing extra income. This is especially true in the Democratic Republic of Congo (DRC), known for its vast tropical forests. We study the the impact of these plantations in the Kaziba chieftancy, a crucial ecological zone in the DRC. Using a combination of survey data, dendrometry, and satellite analysis, we uncover significant income potential from these plantations, which currently boost household income by approximately 27% compared to non-plantation households. This income could be further increased if the plantations were harvested at the optimal rotation age, rather than prematurely as is currently practiced. However, these economic benefits come with environmental considerations, as the plantations lead to substantial changes in the landscape and a reduction in native forests. Additionally, their capacity for carbon sequestration is limited, averaging 237 tonnes per hectare. Our insights could guide policies for sustainable forest plantations in regions like the DRC.

This paper analyzes the intertemporal variation of trust on economic growth. Constructing a unique global country panel dataset and applying a system-generalized method of moments (SYSGMM) estimation approach to a sample of 75 market economies over a 40-year time span (1980-2019), this paper finds evidence of a curvilinear (inverted U-shape) relationship between trust and growth. This relationship corroborates earlier panel data results but challenges findings that posit a general positive relationship between trust and growth. Only a minority of global economies can attain a position close to or above the optimum threshold for trust and growth. Most economies, in fact, fall well below that threshold, and for them, it is incumbent upon their policymakers to consider trust-building measures in order to achieve higher growth. In countries that are close to the optimum threshold, however, such policies can likely be neglected. In fact, in countries where trust levels exceed the optimum, an increase in trust might even hamper growth.

We assess the impacts from physical hazards (or severe weather events) on economic activity in a panel of 98 countries using local projection methods. Proxying the strength of an event by the monetary damages it caused, we find severe weather events to reduce the level of GDP. For most events in the EM-DAT data set the effects are small. The largest events in our sample (above the 90th percentile of damages) bring down the level of GDP by 0.5 percent for several years without recovery to trend. Smaller events (below the 90th percentile) see a less immediate decrease in initial years (0.1 percent) that progressively widens to become similar to the effect of larger disasters after 10 years. Climatological hazards (droughts and forest fires) appear to have the largest effects. These findings are robust across country groupings by development and alternative measures of the strength of the physical hazard.

This article contributes to the scant literature exploring the determinants of methane emissions. A lot is explored considering CO2 emissions, but fewer studies concentrate on the other most dangerous greenhouse gas, methane which contributes largely to the climate change problem. For the empirical analysis, a large dataset is used considering 192 countries with data ranging from 1960 up to 2022 and considering a wide set of determinants (total central government debt, domestic credit to the private sector, exports of goods and services, GDP per capita, total unemployment, renewable energy consumption, urban population, Gini Index, and Voice and Accountability). Panel Quantile Regression (QR) estimates show a non-negligible statistical effect of all the selected variables (except for the Gini Index) over the distribution’s quantiles. Moreover, the Simple Regression Tree (SRT) model allows us to identify losing and winning countries, providing important guidelines for policymakers while implementing environmental policies.

Pollution is a major challenge for the Central and Eastern European (CEE) countries that joined the EU. In this context, the main aim of this paper is to check if renewable energy consumption reduced the CO2 emissions in the region due to EU directives. According to method of moments quantile regression (MMG) and mean group (MG) estimators, the renewable energy consumption reduced the CO2 emissions in 11 CEE countries from the EU in the period 2007-2022. Moreover, the synthetic control method based on a donor pool composed by Russian Federation and Montenegro suggests that Renewable Energy Directive launched in 2009 reduced pollution in the 11 CEE states, but the reduction is larger compared to CEE countries outside the EU since 2019 given the new targets proposed in the Revised Renewable Energy Directive in 2018. In the complex EU policy framework, gender pay gap should be considered and it seems it reduces CO2 emissions in the CEE countries from the EU. An U-pattern is observed in the economic growth-pollution nexus in most of the cases. These findings support the policy recommendations in the EU countries from Central-Eastern region of Europe.

This paper investigates the gender-asymmetric impacts of dams on schooling in Sub-Saharan Africa. Validating and utilizing the fact that dams reduce groundwa- ter storage in the nearby downstream area in an arid environment, we employ a generalized DID strategy to compare the changes in schooling of individuals resid- ing close to and those relatively distant from dams after the construction of dams, for downstream and upstream separately. We find that exposure to dams before age 15 reduced female schooling by 1.2 years in the close-to-dam area, compared to those in the distant area. The decreased schooling is associated with more early marriage and fertility. The effect is particularly pronounced for societies with en- trenched patriarchal traditions. No similar effects were found for males or in the upstream. We show that a major mechanism is school disruptions due to increased time in water-fetching — a burden primarily borne by school-aged girls.

Over the last 15 years, financial literacy has become an important issue for both academic and policy research. As of May 2022, more than 70 countries and economies worldwide were designing or implementing national strategies for financial literacy. The impact of financial literacy on household financial behavior was acknowledged in the countries with different level of economic and financial intermediary market development. However, the question if financial literacy, other things being equal, has a positive effect on financial behavior of people in general, and their ability to manage and pay off debts in particular, is still under discussion due to the problem of potential endogeneity. The research is aimed at contributing to the literature by approaching the endogeneity problem in revealing the impact of financial literacy on the over-indebtedness of households using the panel data of the Survey of Consumer Finances collected in Russia in 2018-2022. The case of Russia is an interesting example of a relatively young, but fast-developing market of consumer finance. Fixed effects panel models show that there is a statistically significant negative association between financial literacy and over-indebtedness considering several diverse controls. However, with the help of strong instrumental variables for endogenous variables, it is found out that financial literacy does not affect the probability of a household of being over-indebted.

Greenhouse gas (GHG) emissions are determined as the most significant factors causing climate change. Carbon dioxide is one of the most important greenhouse gases. Numerous studies have been conducted to determine the impact of various factors affecting environmental degradation. In this study a wide range of driving factors affecting carbon dioxide emissions are investigated by employing machine learning techniques. The empirical analysis carried out for OECD countries over the period of 2000-2020. K-nearest neighbors, CART, Random Forests and XGBoost algorithms are implemented. XGBoost algorithm has provided more accurate predictions for the selected data and the time span.

This paper aims to understand how to explain carbon taxes and how to design redistribution policies to win support for carbon taxes using a representative survey on 3,460 Chinese citizens. Each participant is randomly assigned to two sets of information: (i) what the carbon tax is and how it works; and (ii) personalized information on gains and losses under a specific carbon tax redistribution policy. We find that Chinese citizens are most convinced by the “polluters pay” element of carbon taxes. Moreover, providing detailed information on gains and losses usually does not increase the acceptance, except that receiving information on gains would increase the acceptance under the uniform redistribution scheme.

Recent research underscores a positive correlation between a greater concentration of immigrants in a particular locality and heightened support for anti-immigrant political parties, attributed to resource competition. However, existing studies lack an examination of nuances in interpersonal contact, particularly in distinguishing mere exposure from extended or prolonged interaction. This study aims to investigate the impact of asylum seekers’ influx on public opinion, specifically examining whether there is a discernible shift in support for right-wing ideologies during the 2006 and 2018 national elections. Using a difference-in-differences approach, our findings reveal that in the Centre and South of Italy the existence of a Reception and Integration System (SAI), which are centres that aim at the integration of migrants into society of a migration, diminishes support for Lega, serving as a proxy for anti-immigration sentiment. On the other hand, Extraordinary Reception System (CAS), which are places in which migrants reside temporary, increases the support for Lega, even if the impact is weakly statistically significant. No effects are observed in the North, where Lega’s political discourse has historically been linked, thus reducing the influence of third-party factors on citizens’ voting choices. Spatial analysis is deployed to assess the impact of varying degrees of exposure to immigration inflows. The outcomes align with the principles of contact theory: in municipalities hosting a centre in which people follow integration programmes the anti-immigration sentiment is weaker than in neighbouring.

The aim of the paper is to analyze the effect of environmental innovations on productivity and pos-sible spatial spillover effects related to policy-induced clean innovations in Russia. We provide em-pirical analysis of Russian regions for the period 2010–2015 taking into account relative geograph-ical location of regions. First, we investigate whether Russian regions experience spatial correlation in productivity and clean innovation. Second, we provide empirical panel data analysis, taking into account spatial correlation in productivity as well as common unobserved characteristics of regions located close to each other. The result of spatial panel data analysis show that clean innovations induce a positive effect on productivity not only in a particular region, but also in neighboring ones. We also expect that in the long-run the induction of a clean innovation policy will generate a chain of connected spatial spillover effects on regional productivity.

We examine how superstition shapes corporate tax avoidance and do so by taking a risk perspective and focusing on the zodiac-year belief prevalent in China. Tax avoidance entails reputational risk and legal risk but will benefit the firm by reducing the risk of financial constraints or distress. In Chinese society, it is believed that zodiac year will bring bad luck to a person for her/his conduct, and thus people tend to be more risk-averse during their zodiac years. The zodiac-year belief thus offers a nice setting to understand how CEOs trade off risks associated with corporate tax avoidance. Using a difference-in-differences research design, we find causal evidence that firms exhibit a greater magnitude of tax avoidance in the CEOs’ zodiac years. We also find that the zodiac-year effect on corporate tax avoidance is more pronounced for firms with tight financial constraints, firms with high business risk, firms headquartered in regions with a high degree of superstition, and non-state-owned firms. Overall, our results suggest that, when CEOs are more risk-averse, they attach more importance to financial risk than the risk of reputational losses and litigation associated with corporate tax avoidance.

This study explores the primary factors influencing consumer decisions in the purchase of electric vehicles (EVs), a promising solution for reducing the significant emissions produced by the transportation sector. The research employs a hybrid model, combining the random coefficients discrete choice model (Berry, Levinsohn, and Pakes, 1995) with the total cost of ownership (TCO) model. The analysis of vehicle registration data from New York State, spanning from January 2021 to September 2023, reveals the critical role of TCO in shaping consumers’ demand for electric vehicles. The findings have significant implications for government policies aimed at promoting sustainable transportation and underscore the need for comprehensive models in predicting consumer purchasing behavior in the EV market.