Matching Items (9)
136504-Thumbnail Image.png
Description
A recession at the time of high school graduation could place multiple and competing pressures on a student deciding between entering the labor force and going to college. A recession may lower opportunity costs, increasing college enrollment and depressing the college wage premium; a downturn may also restrict enrollment to

A recession at the time of high school graduation could place multiple and competing pressures on a student deciding between entering the labor force and going to college. A recession may lower opportunity costs, increasing college enrollment and depressing the college wage premium; a downturn may also restrict enrollment to only those with sufficient family resources to pay for it. In the event that either of these illustrations holds true, recessions would seem to result in an adverse, exogenous welfare impact. This paper examines the extent to which recessions at the time of high school graduation affect students' likelihood of enrolling in college and then looks at the long-term earnings effects these early-life recessions carry. I first describe the choice between entering a volatile labor market and enrolling in higher education that faces 18-year-old high school graduates during a recession. For my analysis, I use data from the Panel Study of Income Dynamics to study the effects recessions have on high school graduates' decision-making. I then develop a model using these same data to compare the college wage premiums for individuals treated and untreated by a recession at the time of high school graduation. I find that recessions result in an economically significant uptick in college enrollment. However, the college wage premium for those who enroll in a recession is not statistically different from that witnessed by enrollees in better economic climates. Nonetheless, those young people who enter college during a recession may witness an economically appreciable earnings premium over and above the typical college premium. I conclude by exploring the significance of these findings and reflect on their seemingly contradictory implications.
ContributorsFischer, Brett (Author) / Dillon, Eleanor (Thesis director) / Wiswall, Matthew (Committee member) / Veramendi, Gregory (Committee member) / Barrett, The Honors College (Contributor)
Created2015-05
135638-Thumbnail Image.png
Description
A growing number of jobs in the US require a college degree or technical education, and the wage difference between jobs requiring a high school diploma and a college education has increased to over $17,000 per year. Enrollment levels in postsecondary education have been rising for at least the past

A growing number of jobs in the US require a college degree or technical education, and the wage difference between jobs requiring a high school diploma and a college education has increased to over $17,000 per year. Enrollment levels in postsecondary education have been rising for at least the past decade, and this paper attempts to tease out how much of the increasing enrollment is due to changes in the demand by companies for workers. A Bartik Instrument, which is a measure of local area labor demand, for each county in the US was constructed from 2007 to 2014, and using multivariate linear regression the effect of changing labor demand on local postsecondary education enrollment rates was examined. A small positive effect was found, but the effect size in relation to the total change in enrollment levels was diminutive. From the start to the end of the recession (2007 to 2010), Bartik Instrument calculated unemployment increased from 5.3% nationally to 8.2%. This level of labor demand contraction would lead to a 0.42% increase in enrollment between 2008 and 2011. The true enrollment increase over this period was 7.6%, so the model calculated 5.5% of the enrollment increase was based on the changes in labor demand.
ContributorsHerder, Daniel Steven (Author) / Dillon, Eleanor (Thesis director) / Schoellman, Todd (Committee member) / Economics Program in CLAS (Contributor) / Department of Psychology (Contributor) / Sandra Day O'Connor College of Law (Contributor) / School of Politics and Global Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
137771-Thumbnail Image.png
Description
The US steel industry experienced a great decline between 1950-1985. Influenced by several government policies, the industry was first cartelized during the great depression and then subjected to an extremely powerful organized labor force. Due to high demand between and during WWII and the Korean War, the industry expanded capacity

The US steel industry experienced a great decline between 1950-1985. Influenced by several government policies, the industry was first cartelized during the great depression and then subjected to an extremely powerful organized labor force. Due to high demand between and during WWII and the Korean War, the industry expanded capacity using existing technologies. Simultaneously, organized labor was able to secure increased wages and large severance costs for firms that decided to shutdown existing steel mills. In the post war years this prevented firms from innovating through investing in newer, more efficient, technologies. Eventually US steel firms had no advantage against foreign producers who could produce steel cheaper and more efficiently.
ContributorsCole, Andrew Arthur (Author) / Lagakos, David (Thesis director) / DeSerpa, Allan (Committee member) / Dillon, Eleanor (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor)
Created2013-05
136760-Thumbnail Image.png
Description
Through collection of survey data on the characteristics of college debaters, disparities in participation and success for women and racial and ethnic minorities are measured. This study then uses econometric tools to assess whether there is an in-group judging bias in college debate that systematically disadvantages female and minority participants.

Through collection of survey data on the characteristics of college debaters, disparities in participation and success for women and racial and ethnic minorities are measured. This study then uses econometric tools to assess whether there is an in-group judging bias in college debate that systematically disadvantages female and minority participants. Debate is used as a testing ground for competing economic theories of taste-based and statistical discrimination, applied to a higher education context. The study finds persistent disparities in participation and success for female participants. Judges are more likely to vote for debaters who share their gender. There is also a significant disparity in the participation of racial and ethnic minority debaters and judges, as well as female judges.
ContributorsVered, Michelle Nicole (Author) / Silverman, Daniel (Thesis director) / Symonds, Adam (Committee member) / Dillon, Eleanor (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Politics and Global Studies (Contributor)
Created2014-12
136306-Thumbnail Image.png
Description
With the National Labor Relations Board's decision to allow Northwestern University football players to unionize, the landscape of college athletics is changing very quickly. Due to their recognition as employees of the University, football players at Northwestern will receive many benefits that they would not have received before. They will

With the National Labor Relations Board's decision to allow Northwestern University football players to unionize, the landscape of college athletics is changing very quickly. Due to their recognition as employees of the University, football players at Northwestern will receive many benefits that they would not have received before. They will be able to bargain for the things they want including: scholarships that cover the cost of attendance, increased medical coverage, measures to increase graduation rates, a safer game, and due process with the NCAA. However, this will come at a cost to the general welfare. Subsidies to athletic departments will continue to rise on college campuses due to the increasing costs of athletics and that cost will be incurred regressively on students. With an outcry from students, universities may be forced to stop the increase in subsidies, which may force some athletic departments to cut certain sports according to some parameters set by government legislation and the NCAA.
ContributorsGewecke, Alexander Leland (Author) / Marburger, Daniel (Thesis director) / Dillon, Eleanor (Committee member) / Barrett, The Honors College (Contributor) / Department of Economics (Contributor) / W. P. Carey School of Business (Contributor)
Created2015-05
134477-Thumbnail Image.png
Description
Today, statistical analysis can be used for a variety of different reasons. In sports, more particularly baseball, there is an increasing necessity to have better up to date analysis of players and their performance as they attempt to make it to the Major League. Athletes are constantly moving around within

Today, statistical analysis can be used for a variety of different reasons. In sports, more particularly baseball, there is an increasing necessity to have better up to date analysis of players and their performance as they attempt to make it to the Major League. Athletes are constantly moving around within one or more organizations. Since they are moving around so often, clubs spend an ample amount of time determining whether or not it is for their benefit and betterment of the organization as a whole. The objective of this thesis is to utilize previous baseball statistics in StataSE to determine performance levels of players who played at the major league level. From these, regression-based performance models will be used to predict whether or not Major League Baseball organizations effectively and efficiently move players around from their farm systems to the big leagues. From this, teams will be able to see whether or not they in fact make the right decisions during the season. Several tasks were accomplished to achieve this outcome: 1. First, data was obtained from the Baseball-Reference statistics database and sorted in google sheets in order for me to perform analysis anywhere. 2. Next, all 1,354 players that entered the major leagues in the year 2016, were assessed as to whether or not they started in a given league and stayed, got promoted from the minor leagues to the majors, or demoted from the majors to the minor leagues. 3. Based off of prior baseball knowledge and offensive performance quantifications only, players' abilities were evaluated and only those who were called up or sent down were included in the overall analysis. 4. The statistical analysis software application, StataSE, was used to create a further analyze if any of the four major regression assumptions were violated. It was determined that logistic regression models would produce better results than that of a standard, linear OLS model. After testing multiple models, and slightly refining my hypothesis, the adjustments made developed a more accurate analysis of whether organizations were making an efficient move sending a player down to promote another player up. After producing the model, I decided to investigate at what level a player was deemed to be no longer able to perform at a Major League Baseball level.
ContributorsHayes, Andrew Joseph (Author) / Goegan, Brian (Thesis director) / Marburger, Daniel (Committee member) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
134682-Thumbnail Image.png
Description
The NBA operates under a unique system with both forms of the salary cap. The league has a team salary cap that sets a limit that teams can spend on their entire roster. The NBA has a soft cap and a luxury tax system, meaning if teams spend over a

The NBA operates under a unique system with both forms of the salary cap. The league has a team salary cap that sets a limit that teams can spend on their entire roster. The NBA has a soft cap and a luxury tax system, meaning if teams spend over a determined amount, they are taxed for the salaries in excess. The league also has a player salary cap. The 1999 NBA collective bargaining agreement first introduced the individual player salary cap in the league. This cap sets a limit on what the best players can earn, otherwise known as the maximum contract. In an economic system with a soft team cap, the introduction of the player salary cap has important implications. The stated outcome of such a salary cap is to improve competitive balance and better distribute star players throughout the league. This study evaluated the 1990-2015 regular seasons to measure the impact of the player salary cap on competitive balance, the distribution of team payrolls, and the dispersion of star players. In accordance with the Rottenberg's invariance hypothesis, the player salary cap has hurt the players and benefited the owners by redistributing income from one party to the other, without impacting the distribution of talent in the league. The rule change has not affected competitive balance, while team payrolls have converged and star players have become more dispersed throughout the league. These changes hurt the league overall, preventing the maximization of revenues. Despite this inefficiency, the chance of the league moving to eliminate the player salary cap is low.
ContributorsWelu, Brian Andrew (Author) / Marburger, Daniel (Thesis director) / Goegan, Brian (Committee member) / Sandra Day O'Connor College of Law (Contributor) / Department of Economics (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
135465-Thumbnail Image.png
Description
Upon hiring a new college graduate, employers are left with limited information about the true productivity of the individual, mainly based on the information provided via resume and other related documents. Based on the information, which may include (and is not limited to) education years, grade point average(s), the institution

Upon hiring a new college graduate, employers are left with limited information about the true productivity of the individual, mainly based on the information provided via resume and other related documents. Based on the information, which may include (and is not limited to) education years, grade point average(s), the institution one attended, majors, etc., employers attempt to differentiate between the candidates. Existing employer learning literature, such as Altonji and Pierret (2001) and Peter Arcidiacono, Patrick Bayer, and Aurel Hizmo (2010), have found that employers statistically discriminate upon hiring and estimate wages based on expected productivity conditional to observable characteristics--specifically education. As one's work experience accumulates, the wages are adjusted to the newly learned characteristics correlated with productivity. Thus, college graduates are more appealing as job candidates than high school graduates, with little learning done with experience in the labor market as employers have a more accurate depiction on productivity with more education years. With rising demands for high-skilled labor, there is a growing interest on what employers learn about from the name of the college listed on one's resume, as varying ability students sort into varying quality colleges. I include a one-dimensional index of college quality, as similarly constructed by Eleanor Dillon and Jeffrey Smith (2015), to measure the effects of attending a highly-selective institution in predicting individual ability. This paper provides additional support for the employer learning model on college graduates, with an emphasis on the direct role that college quality has at the start of one's career. Although college quality appears to be influential in providing employers additional information on one's productivity, unlike education, the weight placed on it by employers does not change with experience in the labor market. I further investigate within the college market and provide possible explanations behind learning on the basis of college quality, including: the possibility of information explained by quality unrelated to one's ability and the effects of attending a highly selective college.
ContributorsNam, Jimin (Author) / Veramendi, Gregory (Thesis director) / Dillon, Eleanor (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
135248-Thumbnail Image.png
Description
The NBA Draft has become one of the most exciting and unique events in sports. Draft decisions are so monumental; so crucial to be right, so disastrous to be wrong. The purpose of this project is to build a model that would help teams to predict which types of players

The NBA Draft has become one of the most exciting and unique events in sports. Draft decisions are so monumental; so crucial to be right, so disastrous to be wrong. The purpose of this project is to build a model that would help teams to predict which types of players perform at a high level upon entering the league. By using regression analysis to predict the rookie year PER (performance efficiency rating) as a dependent variable, teams would have some idea of whether their rookies were underperforming, excelling, or performing at a level they could expect. The independent variables and their statistical significance could help answer a host of questions that front offices have about players: If a player came from a worse conference, can we expect them to have a harder time adjusting? Will their shorter wingspan have a negative effect on their play in the NBA? Do guards or forwards tend to have higher PERs upon entering the league? To answer these questions, I've gathered data on every first round NBA draft pick from 2001-2014 who played at least one season of Division 1 NCAA basketball. The data consist of anthropometric measurements (height, wingspan, standing reach, etc.), NBA draft combine results (agility drills, sprint times, etc.) and their college statistics per 40 minutes in their final season of college basketball (points, rebounds, assist-to-turnover ratio, etc.). I then separated the data into seven different sets: aggregate, backcourt, frontcourt, guard, wing, forward, and big. For each of these data sets, I built a predictive model for rookie PER. In doing so, I aimed to gain both a broad understanding of what factors lead to translation of college basketball play to professional play, and also a precise understanding of how those factors change for each distinct position.
ContributorsMurphy, Benjamin Joseph (Author) / Goegan, Brian (Thesis director) / Marburger, Daniel (Committee member) / Economics Program in CLAS (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05