Tuition: the cost that has the ability to severely limit student’s learning capabilities while also providing students with ample learning opportunities. Recently, there has been an ongoing trend of prioritizing higher education, but with the increased emphasis comes more selectivity and differences in attainability regarding one’s financial stability. Because of the contradicting effects of tuition, it is logical for there to be a direct relationship between tuition and college enrollment. In fact, studies show that for every $100 increase in tuition, a 0.7% participation drop of 18 to 24 year old participation in college should be expected (Heller, 1997). Tuition continues to be a deterrent for higher education and thus social mobility as a whole, which directly contributes to the inequity present within education and opportunities to join the workforce. The effect of tuition on college enrollment rates can be predicted by tuition elasticity in relation to financially fulfilling majors, financial aid satisfaction, and higher enrollment status.
A student’s enrollment status is a vital factor in determining one’s tuition elasticity and tuition. As hypothesized, “newly enrolled students respond differently to tuition changes than currently enrolled students” (Shin & Milton, 2007). For example, a first-time student might weigh their options by comparing tuition of colleges in which they aren’t enrolled, whereas a returning student might simply accept the tuition level at their college to stick with their college. This means that arriving students are more vulnerable to competing school rates and tuition variations while returning students are more elastic to tuition increases within their college. Speaking of competing colleges, research indicates that “the tuition levels at competing colleges might affect a college’s enrollment (cross-price effects) as much or more than the absolute tuition level at the college itself” (Shin & Milton, 2007). This evidence shows that first-year students are bound to stay at the college they are enrolled in, even if the college increases its tuition, if the tuition is still lower than that of competing colleges. In conclusion, the more seniority a student has within a college, the more the student is willing to pay tuition, despite variations, and maintain enrollment.
While enrollment status is influential to a student’s flexibility and retention in higher education, a student’s academic major also plays a crucial role. Overall, studies conclude that “disciplines expected to result in high rates of return might be less sensitive to tuition level or tuition increase” (Shin & Milton, 2007). This is because students involved in these successful majors expect sufficient monetary returns for their investment in college and are therefore likely to pay more in college. Researchers report that “Engineering graduates received the highest hourly wage, followed by Business, Science, Liberal Arts, and Education” (Shin & Milton, 2007). A study was conducted on a public college between 2002 and 2004 where the tuition was increase $934 each year, and a census was gathered on the enrollments of each major. The Engineering major had the highest amount of enrollments, taking up around 17.9% of all students enrolled in the year 2004, despite the tuition increases (Shin & Milton, 2007). This evidence portrays that even though the tuition of this college was significantly increased per year, the students in majors with substantial financial returns are less likely to be affected by tuition modifications and are more likely to remain enrolled, displayed by their tremendous enrollment rate.
Contrasting to enrollment status and academic major, financial aid has the opposite effect on tuition elasticity and tuition, as it significantly reduces students’ educational finances. Financial aid decreases tuition which then increases enrollment rates–the inverse of the relationship analyzed so far. Students from lower-income families depend on financial aid to have the ability to attend college, which subsequently increases enrollment. In fact, “20% to 40% of the enrollment of lower-income students was due to the existence of grants, and 13% of middle-income student enrollments were due to grants” (Heller, 1997). This statistic portrays how financial aid assists students to attend college by relieving them of their financial responsibilities, therefore increasing enrollment. However, it is also important to note that schools with a typically higher tuition fee have a different application pool. For example, students who have the financial capacity to pay higher tuition are more likely to Early Decision to a school, rather than a student who isn’t as financially stable. Early Decision applicants typically have a higher acceptance rate, thus, financial aid doesn’t always have substantial effects on a student’s decision to apply to an expensive school earlier in the application process.
All in all, the effect of tuition on college retention rates can be predicted by a student’s tuition flexibility which is determined by increasing enrollment status, financially promising majors, and financial aid fulfillment. As a solution to these inequalities, colleges should determine the appropriate tuition by creating a pricing model based on a student’s tuition elasticity which could be “useful in predicting the retention rate of current students at increasing tuition rates” (Bryan & Whipple, 1995). Additionally, universities should utilize Tuition Elasticity and Net Earnings Projections models to evaluate the effects of various tuition rates on enrollment and predict profits from hypothetical scenarios (Bryan & Whipple, 1995). Financial inequity currently has a substantial effect on a student’s decision to apply and/or commit to a college institution or even consider higher education as a whole. This effect should be further mitigated to offer students more mobility regarding their future socioeconomic statuses, and allow their past to not have as much of a lasting effect. By including a cost policy that encompasses enrollment status, academic major, and financial aid while adjusting tuition accordingly, colleges can create a profitable system that not only bolsters enrollment rates, but also creates an accessible learning environment for all.

References
Bryan, G. A., & Whipple, T. W. (1995, September 1). Tuition elasticity of the demand for higher education among current students: a pricing model. Journal of Higher Education (Vol. 66, Issue 5). Retrieved September 26, 2019, from https://go.gale.com/ps/retrieve.do?
tabID=T002&resultListType=RESULT_LIST&searchResultsType=SingleTab&searchType=BasicSearchForm¤tPosition=3&docId=GALE|A17611207&docType=Article&sort=Relevance&contentSegment=ZEDU-MOD1&prodId=PROF&contentSet=GALE|A17611207&searchId=R1&userGroupName=west63149&inPS=true
Heller, D. E. (1997). Student price response in higher education. Journal of Higher Education, 68(6), 624+. Retrieved from https://link.gale.com/apps/doc/A20424145
/PROF?u=west63149&sid=PROF&xid=0bf4c319
Shin, J. C., & Milton, S. (2008). Student response to tuition increase by academic majors: empirical grounds for a cost-related tuition policy. Higher Education, 55(6), 719+. Retrieved from https://link.gale.com/apps/doc/A384440967/PROF?u=west63149&
sid=PROF&xid=5496baf8

Coastal regions are immensely valuable to society; they supply a multitude of ecological resources that are capable of supporting many populations of a diverse array of species. However, due to expeditiously rising sea levels caused by climate change and “the addition of melt water from grounded ice sheets and glaciers,” these regions and their industries face the arduous challenge of maintaining economic resiliency (Williams, 2013). Economic resilience is defined as “the ability of social-ecological systems (SES) to endure biophysical and economic disturbances” and is vital to the country’s economic stability and growth (Caffey, Kazmierczak, and Savolainen, 2015). The statuses of these industries are a valid concern as studies show that between the year 1992 and 2015, coastal region land volume has decreased by approximately 31% due to rising sea levels (Phillips, Jones, & Thomas, 2018). If this shoreline recession continues, the country may bear existential monetary losses like $131 million just within the Gulf of Mexico region (Caffey, Kazmierczak, and Savolainen, 2015). Rising sea levels affect the various industries of coastal regions by negatively impacting the tourism, agriculture, and fishing industries through requiring more economic resiliency.
Rising sea levels resulting from climate change create a tenacious obstacle between the agriculture industry and economic resilience. For example, in Taiwan, there were “losses of 164 billion [New Taiwan Dollars] in agricultural productions and infrastructure in 2009” due to a typhoon caused by rising sea levels and climate change (Lin & Chou, 2019). In Taiwan itself, an experiment was conducted by Hsingchun Lin and Lichen Chou, two economics professors from Chinese universities, in which the economic status of agricultural losses of Taiwan, a coastal region, and Mainland China, a non-coastal region, were compared to see if location significantly impacted the amount of agricultural losses endured (Lin & Chou, 2019). The experiment displayed that Taiwan underwent a loss of approximately 170,204 farming products compared to Mainland China which underwent a loss of approximately 141,312 farming products from 2005 to 2010, resulting in a statistically significant difference of 28,892 between the two regions (Lin & Chou, 2019). This data displays how even though both regions experienced equal exposure to both sea level rise and natural disasters, the coastal region’s agriculture industry was more heavily impacted due to its location. Some may say that since specifically coastal region agricultural industries are more heavily impacted, it should not have a strong effect on the whole nation’s economy since a majority of the nation’s farms are mainland. However, as proven through this experiment, climate change still had a detrimental effect on Mainland China, regardless of its comparison to Taiwan. Therefore the comparatively smaller effects of climate change on mainland regions will accumulate to become severely dangerous for the economy. Moreover, the losses in agricultural products caused by climate change will most likely result in losses in other industries through industrial linkage.
When looking at other instances of industrial linkage, both the agricultural and fishing industries face the effects of rising sea levels. According to a survey that specifically targets the economic status of the fishing industry around the Gulf of Mexico conducted by Louisiana State University professors Caffey, Kazmierczak, and Savolainen, 75% of respondents indicated that their firms experienced financial damage due to circumstances caused by climate change between 2004 and 2008 (2015). This time period was chosen because these years were when the effect of rising sea levels was at its peak as thirteen hurricanes had struck this area. The fishing industry specifically is affected through the following factors: the annual number of trips the business makes, the duration of these trips, the storm surge (feet), the latitude of home port, and the longitude of home port (Caffey, Kazmierczak, and Savolainen, 2015). Some may say that since each fishing business’s damage is dependent on its own unique factors, not all coastal region fishing industries will be impacted by climate change. Despite this fact, the economic resiliency of all businesses within the industry are still declining due to rising sea levels, regardless of the rate at which degradation is occurring.
Lastly, the tourism industry is another major industry to be impacted by rising sea levels and climate change. Investing in a property within a coastal region is extremely popular due to the appealing tropical climate. However, according to Phillips, Jones, and Thomas, UK professionals from the Coastal and Marine Research Group, the Institute for Tourism Travel and Culture, and the Construction Department of Wales, respectively, “global warming and sea level rise are coastal hazards difficult to quantify, but indirect costs will include falling property values and loss or transfer of tourism revenues” (2018). Therefore, it is shown how less people are willing to invest in coastal properties due to the increased risk of damage and cost of repair, leading to a drastic drop in the tourism and real estate industry. Continually, if current policies of “managed retreat,” where sections of the coastline are abandoned, and “no active intervention,” where there is no planned investment to defend at the coastline, are followed, each coast might endure a monetary loss of around 66 million dollars (Phillips, Jones, & Thomas, 2018). This striking statistic calls for a more efficient and long term method of policy and management, to ensure that all industries among coastal regions maintain economic resiliency.
The Integrated Coastal Zone Management (ICZM) has been seen as a probable solution to resolve this lack of proper policy and management. Overall, this policy “promotes a broad overall perspective that considers the interdependence and disparity of natural systems and human activities with an impact on coastal areas” (Carrero, Naas, Malvárez, & Cáceres, 2013). This way, an environmentally healthy yet socio-economically considerate policy is being established and implemented. Additionally, through this method researchers could be able to discover how a coastal environment has changed over a certain period of time and then continue to make predictions about what the land will evolve into (Carrero, Naas, Malvárez, & Cáceres, 2013). This solution is desperately needed from an economic and environmental standpoint. According to Hill and Martinez-Diaz, for every degree Celsius increase of warming, the US economy will lose about 1.2 percent of GDP per year, effectively halving the country’s annual growth (2020). So regardless of whether or not one may be physically living in a coastal region, each country’s fiscal situation is deteriorating due to this rising issue. Action must be taken immediately to ensure that the nation does not fall into a dangerous economic cycle of aid and debt, ultimately leading to a depletion of the global economy.

References
Brecher, J. (2015). Protecting the Future: A Strategic Proposal to Stop Climate Change. New Labor Forum, 24(2), 18-24. Retrieved January 27, 2020, from www.jstor.org/stable/24718592
Craft, C., Clough, J., Ehman, J., Joye, S., Park, R., Pennings, S., . . . Machmuller, M. (2009). Forecasting the Effects of Accelerated Sea-Level Rise on Tidal Marsh Ecosystem Services. Frontiers in Ecology and the Environment, 7(2), 73-78. Retrieved January 26, 2020, from www.jstor.org/stable/25595059
Crowley, T. (2000). Causes of Climate Change over the past 1000 Years. Science, 289(5477), 270-277. Retrieved January 27, 2020, from www.jstor.org/stable/3077577
Funk, C., & Kennedy, B. (2019, April 19). How Americans see climate change in 5 charts. Retrieved from https://www.pewresearch.org/fact-tank/2019/04/19/how-
americans-see-climate-change-in-5-charts/
Jeffress Williams, S. (2013). Sea-Level Rise Implications for Coastal Regions. Journal of Coastal Research, 184–196. https://doi.org/10.2112/SI63-015.1
Lippsett, L. (2017). More floods and faster-rising sea levels: geological records help forecast escalating coastal hazards. Oceanus, 52(2), 8. Retrieved from https://link.gale.com/apps
/doc/A503309991/GRNR?u=west63149&sid=GRNR&xid=93d1b5b5
Marcantonio, R. A., Field, S., & Regan, P. M. (2019). Toxic trajectories under future climate conditions. PLoS ONE, 14(12), e0226958. Retrieved from https://link.gale.com/apps/doc/A609588051/GPS?u=west63
149&sid=GPS&xid=c1a0ce5a
Ramasamy, R., Surendran, S.N. (2011). Possible impact of rising sea levels on vector-borne infectious diseases. BMC Infect Dis 11, 18 https://doi.org/10.1186/1471-2334-11-18
The European Carbon Tax. (1992). Energy Exploration & Exploitation, 10(1), 23-28. Retrieved January 27, 2020, from www.jstor.org/stable/43753824
Thompson, J., & Curran, M. (2015). TROUBLING TIDES: Will Sea Turtles Survive the Rising Seas? Science Scope, 39(3), 19-26. Retrieved January 27, 2020, from www.jstor.org/stable/43691477
Thorne, K. M., Buffington, K. J., Elliott-Fisk, D. L., & Takekawa, J. Y. (2015). Tidal marsh susceptibility to sea-level rise: Importance of local-scale models. Journal of Fish and Wildlife Management, 6(2), 290+. Retrieved from https://link.gale.com/apps/doc/
A464054432/GPS?u=west63149&sid=GPS&xid=244247fe