State-Owned Enterprises (SOE) are legal entities either partially or fully owned by the government that undertake commercial activities on behalf of the state. Their legal status, purpose of establishment and missions vary across countries with some becoming tools for countries to better position themselves in the competitive global economy and some to provide public services and ensure distribution of social welfare. In Malaysia, these SOEs are called Government-Linked Companies (GLCs) where the government owns 20% or more of issued or paid-up capital. GLCs not only account for 54% of market capitalization of the Kuala Lumpur Composite Index but also remain as main service providers to the nation in key strategic utilities and services. In 2004, the government of Malaysia introduced the Government-Linked Transformation Program (GLCTP) in response to observing the poor performance of GLCs relative to the broader market on all key financial indicators. It is a 10-year program consisting of 10 Initiatives, most of which aim to elicit better and effective governance through imposition of guidelines and standards supervised and enforced by the Putrajaya Committee on Government-Linked Companies, PCG. With GLCs presence being so abundant and influential, we question the effectiveness of the program which concerns the future of GLCs and non-GLCs in Malaysia. Thus, this paper aims to measure the impact of GLCTP on the financial performance of GLCs (and non-GLCs) by panel data estimation technique. In particular, this project examines the difference in the financial performances of GLCs relative to non-GLCs pre- and post the program after controlling for other confounding variables. Improvements in performances of GLCs compared to that of non-GLCs is expected. If results show statistically significant, the next interesting discussion would then be corporatization over privatization or divestment.

The rising cost of attending four-year colleges and universities concerns students and parents across the nation, calling for an explanation and possible educational alternatives. One such alternative may be trade schools, which offer a shorter path from secondary education to the workforce. In deciding which post-graduation path to pursue, students (and their parents) may be interested in the rate of return to each of these options. Many estimates have arisen calculating the rate of return to a four-year degree, but comparatively little has been done for trade schools and short-term professional programs. This study is a preliminary attempt to fill this gap. I focus on beauty schools as a specified form of trade school, and compare tuition and early-career salaries from twenty-three beauty schools in the state of Washington to pre-calculated Washington averages for four-year universities. If the labor economy is operating at maximum efficiency, the rate of return for trade schools should be equal to that of four-year universities, i.e. the same benefit to cost ratio. An efficient labor market that includes beauty schools at a higher rate of return than four-year universities could indicate an occurence of social stigma, encouraging unprepared high school students into a longer program than would be economically efficient. The expected result would be an increase in students capitalizing on the program with the higher rate of return. While preliminary results suggest a higher rate of return for four-year programs, I plan to continue the study with expanded data sets.

For many rising metropolitan cities across the United States, the implementation of a major mass-transit system is a potential means of combating unemployment by connecting citizens to jobs that might be otherwise inaccessible. However, relatively little is known about how the effects of mass-transit systems scale with population density, which may deter many cities that stand to gain from investing in such a project. This study examines the effect of population density on the impact of Commuter Rail, Light Rail, and Street-Car transit systems on unemployment rate across every metropolitan city in the United States, in order to enable more informed policy and investment decisions. In applying a difference-in-difference regression model to panel data that spans 192 cities from 1990 to 2016, it is revealed that the introduction of a mass-transit system results in a 19% average decrease in unemployment rate. In addition, it is shown that the existence of a mass-transit system reduces the effect of each percent increase of population density in driving up unemployment by 64%. This study’s findings underscore the viability and effectiveness of mass-transit infrastructure as a means of combating rising unemployment rates by providing citizens with a cheap and consistent method of connecting with a wider selection of job opportunities.

In this economics thesis, I addressed one of the effects that the Affordable Care Act has had on US Health Care since its full implementation in 2014: supply side effects. Specifically, I answered the following question: what is the effect of the implementation of the Affordable Care Act on patient wait times in primary care offices? In order to narrow the field of research, I focused on the tier of the ACA that called for increased Medicaid expansion. Since Medicaid has not been expanded evenly in all states, it has created a robust control group for causal studies such as this. I used a difference-in-difference model and a multivariable regression to establish causality between Medicaid expansion and increased patient wait times. I used data gathered from the Current Population Surveys from 2004, 2009, 2014, and 2016, in 15 different cities around the US (some faced increased Medicaid expansion, and others did not). The dependent variable data (new patient wait times) were extracted from a 2017 Merritt Hawkins Survey which found the wait times for new patient appointments in different medical services across the 15 different cities for the four different years. The different services are as follows: cardiology, dermatology, obstetrics-gynecology, and orthodpedic surgery, and family medicine (where wait times were only measured in 2009, 2014, 2017). This thesis has been fully developed over a yearlong process of data collection and analysis. My findings highlight areas of the ACA that can be improved to accommodate the proven increased demand for health care, especially given that the supply of health care services responds slower than demand for health care, leading to longer patient wait times.

Icelandic wetlands have ecological, climatological, and historical significance. The Millennium Ecosystem Assessment defines ecosystem services as the benefits humans receive from nature. Many of these benefits are not included in the economic market which leaves them out of cost-benefit analysis in decision making. Although the Kyoto Protocol approved wetland restoration as an official climate mitigation activity, wetland restoration activities in Iceland have yet to catch up. Valuing the ecosystem service of carbon sequestration can help clarify for Icelandic policy-makers that the benefits outweigh the costs of restoration. This study conducts an economic valuation of the carbon sequestration service in Úlfarsárdalur to provide the city of Reykjavik with new information to include in a cost-benefit analysis of restoration. Three methods are used to quantify the monetary benefit provided by potential carbon sequestration in Úlfarsárdalur – direct market pricing, damage avoidance cost, and replacement cost. The results relied on physical data provided by the Verkís report of restoration potential in Úlfarsárdalur as well as data collected by Hlynur Óskarsson, a wetland ecology expert. In accordance with claims from the Millennium Ecosystem Assessment, all three methods reflected that the economic benefits of carbon sequestration exceed the costs of restoration by a significant amount. The direct market pricing and replacement cost methods yielded similar values, while the damage avoidance cost came out much lower. These findings suggest that wetland restoration to promote carbon sequestration could serve as a cost-effective climate mitigation measure. Researchers must continue to investigate the accuracy of such valuation techniques as well as their transferability and scalability to larger ecosystems.

Automation instills fear due to implications that eventually it will steal everyone’s jobs and result in mass unemployment. However, this is a contested idea because automation, especially in manufacturing, may also increase employment due to increasing output as well as being a complement to skilled labor. This project’s purpose is to reveal the impact of increasing automation on the number of employees employed, as well as the average cost per employee and sales of a firm in the short run. I have acquired anonymous firm level panel data for the years 2014 and 2016 on manufacturing firms in Myanmar, which has been a target for growth by firms providing automation technology, from the World Bank Enterprise Surveys. With this data I have run fixed effect regressions, which take into account firm specific situations to control for them, in order to model the response of my variables of interest to the amount of capital purchased in the previous year, total capital, proportion of educated workers and whether a process innovation has been done in the past three years. I did this to see if newly purchased capital is significantly different from other capital they possess as well as how this interacts with the proportion of their educated workforce. My results revealed approximately a .01% increase in the number of employed workers in response to a 1% increase in newly purchased capital, while it does not significantly impact average labor cost per worker or sales. This implies that at least in the short run, the impacts on employment are small and output or wages should remain mostly unaffected. However, Myanmar possesses attributes such as poor infrastructure, low technological level and electricity concerns, which limit the applicability of my conclusions elsewhere. Furthermore, my model’s small sample size makes my results weaker overall.