This research deals with the specific dynamic pricing strategy of fashion products sold online. The pricing method works under the condition of a pre-determined quantity of inventory with stochastic demand functions on a limited time horizon, which is formulated as an optimization problem. To achieve the maximized profit, it is essential to balance between the extra marginal revenue earned by setting a high selling price and the cost lost from unsold items. In order to find the solution, we first develop and estimate a pricing model that captures the important characteristics of the fashion apparel market. Afterwards, we use data from a leading Taiwanese fashion retailer to examine the accuracy of our model. The final purpose of this research is to provide an insightful conclusion of the dynamic pricing policies that would generate the highest retailer revenues.

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.

South Korea’s rapid industrialization and democratization led to policy reforms that allowed women to invest more heavily in their education, career, and leisure beyond the domestic sphere. Consequently, these women became active participants and consumers of the goods and services within their society, as exemplified by their consumption of media. Given that Korean women in their twenties and thirties have embraced strategies to improve their status as citizens who operate in society in ways that transcend traditional normative, restrictive spheres of action, we would expect them to explain their consumption habits in terms of how the cultural objects resonate with their own experiences. Instead, they reveal ambivalence with regards to the value of these dramas as accurate representations of Korean society. Why? I argue that the widespread consumption of Korean dramas replete with mixed messages that call into question these women’s self-fashioning aspirations can be explained as a function of their ability to detect and stand apart from the submissive qualities reflected in female characters whose behavior represents a capitulation to traditional gendered norms. Through open-ended interview questions about professional women’s viewing habits and career objectives, I demonstrate how the critical distance attendant upon drama consumption is an agentive coping mechanism beyond a passive act of acquiescence to gendered discrimination, and is premised on self-perceptions of critical acumen nurtured by their academic and vocational background. Such knowledge resulting from women’s intense focus on education derives from their perception of education as a conduit for the actualization of career aspirations, which equipped them to interrogate gendered power relations that pose challenges to their success. Critical acumen is viewed as the source of their capacity to recognize and distance themselves from popular media’s representation of gendered socio-economic inequality and the broader patriarchal discourse in Korea that perpetuates norms of women’s submissive position.

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.

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.

This research focuses on the mathematics of gerrymandering. Gerrymandering refers to how political parties draw district boundaries to give them better odds at receiving a majority during congressional elections. Every 10 years district boundaries in the United States are redrawn for congressional elections by the current majority party. With such change in political cartography, redrawing district boundaries not only affects who wins but also the people who live within them. Given the loosely defined criteria for redistricting, we seek to quantify the process of redrawing district lines to determine when this partisan process becomes an act of manipulation and exclusion. We will be use The Metropolis Hastings (M.H.) Algorithm to produce a random walk that has a stationary distribution that will be the probability distribution of all possible districting plans for a given U.S state. By collecting congressional maps and election results, we implemented the M.H. algorithm in python to produce sample spaces for Washington State and Iowa. We will simulate local and federal redistricting requirements using self-defined parameters which measure: compactness of districts, population division, division of counties, and minority voter populations. We simulated election results with respect to our sample districts and compared the simulated outcomes with actual district maps and their election results. This study helps to determine if current redrawn maps legitimately reflect the people they purport to represent or if they are manipulations and subversions of our democratic process.

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.

In Washington State, the goal of the Washington Fish and Wildlife Department’s gray wolf (Canis lupus) conservation and management plan is to not only help wolves naturally re-establish a sustainable population across the state, but also to reduce the conflicts with humans, livestock and other wildlife. A successful implementation of this requires us to understand how the public values wolf management and what factors could shape this kind of value. The purpose of this study is to examine Washington State residences’ willingness to pay for wolf-livestock coexistence projects from a statewide survey including an attribute-based choice-experiment. Willingness to pay shows the maximum amount of money an individual wants to sacrifice to procure a good or service, it can be influenced by personal interests, preferences, incomes and demographic background. In this study, I explore the survey data using random utility maximization (RUM) models to identify both heterogeneity and homogeneity factors that may affect Washington residents’ willingness to pay for wolf-livestock coexistence. I also apply Machine Learning to select covariates that help to generate highly accurate prediction models. An individual’s willingness to pay for wolf-livestock coexistence projects is expected to increase as their income, knowledge about wolf conservation status, and attitudes to wolf conservation increase. The aims of this study are to have a comprehensive understanding of people’s willingness to pay for projects designed to promote human-wolf coexistence and to provide implications for conservation groups and organizations to find alternative funding sources in the future.

Epilepsy is a wide classification of neurological disorders that vary in symptoms, severity, age of onset, and demographics. Developmental and epileptic encephalopathies (DEE) are severe forms of epilepsy that involve both early-onset seizures and cognitive and behavioral impairments. One major cause of DEE is genetic variation. However, only 24-40% of DEE cases receive a molecular diagnosis. Our goal is to identify novel genetic variants that cause DEE via sequencing. In DEE, many of the variants associated are de novo, meaning they are novel mutations not inherited from either parent. Because of this, we are able to utilize segregation testing to identify the inheritance of a variant and determine if a variant is potentially pathogenic. From whole exome sequencing data on 200 patient and parent trios, we identified de novo variants in genes not previously associated with DEE. We then narrowed down our list of potential DEE genes to 53 candidate genes via Sanger sequencing. Using a sequencing technique called single molecule Molecular Inversion Probes (smMIPs), we simultaneously and accurately sequenced these 53 potential DEE genes in our cohort of 898 DEE patients, looking for additional de novo variants. These variants include missense mutations, frameshift insertions and deletions, and premature stop codons. Once potentially pathogenic variants are identified in the patient genome, we screened the parents using specific smMIPs selected for the patient-determined target regions to determine inheritance. If the gene validated as de novo, we can investigate the potential role of the affected protein in the phenotype. Our hope is that by identifying additional de novo variants in some of these 53 candidate genes, we can identify novel genes associated with DEE and provide answers to families about the cause of their child's condition. In the future, we hope the genetic understanding of DEE could lead to better, genotype-driven treatments.

 Recently, there seems to be news about blizzards striking East Coast cities nearly every year. However, most reports simply claim that the frequency and intensity of large snowstorms on the East Coast are increasing without providing convincing evidence. Are they telling the truth? We decided to statistically test if the frequency and intensity of large snowstorms in coastal North America have increased in recent years. In our research, we encountered many difficulties during the data collection and cleaning processes. For example, most cities only have records since around 1950 and the Canadian snow data are hard to clean. We first plot frequency of large snowstorms for each city and detected that there is actually a downward trend of snowstorm frequency in coastal North America. To further verify our finding, we also permuted the time-series data and performed permutation tests on the slopes of the linear regression of extreme snowstorm frequencies versus year. In our current progress, the permutation tests suggest that, for all East Coast cities studied, the hypothesized increases in annual frequencies of extreme snowfall are not statistically significant at any reasonable level of significance for looking at exceeding both the 75% and 90% quantiles of annual snowfall. Thus, our current results imply that the frequency of large snowstorms in many East Coast cities has not been increasing in recent years, which is different from the media claims.

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.

In this study, I revisit Morgan and Sørensen’s (M&S) (1999a) analysis of intergenerational social closure within Catholic and Public schools, using the National Education Longitudinal Study from 1988. In an article appearing in the American Sociological Review, M&S examined Coleman’s (1990) social capital theory of the schooling process. They find a negative association between social closure and mathematics achievement in public schools; and a positive association between social closure and mathematics achievement in Catholic schools (partially supporting Coleman’s Catholic school effect). The present study examines outcomes in deviance and mental-health by applying M&S’s models of norm-enforcing and horizon-expanding schools to explain differing outcomes. Although research on educational achievement is important, further examination into outcomes in deviance and mental-health—based on school social organization—have been somewhat absent in research of education. I hypothesize that students attending schools with higher levels of social capital have lower levels of deviance; students in schools with lower levels of social capital have higher levels of self-esteem. Additionally, I examine whether M&S’s models characterize norm-enforcing schools as having students with low levels of deviance and whether horizon-expanding schools are portrayed by students with high self-esteem.