In the first chapter of this dissertation, I exploit the Covid-19 pandemic and associated government restrictions as a natural experiment in order to study the resilience of businesses in the United States. I use a border-county identification strategy with data on government restrictions, employment and open small businesses, in order to assess the resilience of small businesses in the United States. In my main results, I find negative impacts of stay-at-home orders on the number of open small merchants. In particular, shutdowns of businesses accelerated 8 weeks after imposition of a stay-at-home order, suggesting that many businesses were only resilient enough to handle adverse conditions for 8 weeks. On average, a county with a stay-at-home order experienced an additional 1.51 percentage points loss in the number of open small businesses, relative to January 2020, 8 weeks later compared to a neighboring county that did not have a stay-at-home order. Firms were quicker to resort to layoffs. On average a county with an active stay at home order in a month experienced an additional 1.19 percentage point loss in employment, relative to January 2020, the following month compared to a neighbor that did not have a stay-at-home order the previous month. My results suggest that in future scenarios where governments consider enacting similar restrictions further aid is needed for businesses in order to help them stay afloat. In particular, more assistance should be delivered to businesses within two months from the enacting of the order. In the second chapter of this dissertation, I study economic spillovers in the context of theCovid-19 associated government restrictions. I use a detailed geolocation dataset to construct data on the number of visitors per-capita between neighboring counties in the early stages of the pandemic, which I use as a proxy for economic spillovers. I employ a similar border-county identification strategy as in the first chapter to identify the causal effect of stay-at-home orders on inter-county movement. Additionally, I provide evidence for an assumption used in chapter one by examining if there are reduced spillovers in county-pairs that lie in the different commute zones. I find that stay-at-home orders caused reductions in inter-county visits in both directions in a county-pair. That is, I find a decrease in travel from the county without a stay-at-home order to the county with one, as well as a decrease in the opposite direction. On average, a county that does not have stay-at-home order will receive 408 fewer weekly visitors from their neighboring county that has a stay-at-home order. I also examine the effect of stay-at-home orders on the ratio of travel between the two directions in order to find evidence of a net spillover effect between the two counties and fail to find evidence of a net spillover effect. I also find that spillover effects are indeed reduced in neighbor county-pairs where the two counties are in different commute zones. The results of this paper imply that residents in counties with stay-at-home orders decreased travel to their neighboring counties even when those counties did not issue their own orders. In future situations where policy makers need to consider similar restrictions, they should focus on acting more quickly and not be concerned if neighboring counties are not cooperative. In the third chapter of this dissertation, I test the predictions of career concerns models by studying Major League Baseball umpires. Major League Baseball games can be dramatically shaped by minor lapses in judgement from the umpires officiating the game. Due to the indefinite length a game may have, this can include having the game shaped in a way that ends it faster. I study whether evidence for the career concerns model can be found in baseball umpires. A career concerns model would suggest that older umpires, whose careers and reputations are much more established than younger ones, would be more inclined to improperly make judgements that favor the end of the game in extra innings. I use data on MLB umpires and extra-innings games from the 2010-2018 seasons to conduct my empirical analysis and use a linear probability model to isolate the impact of the umpires’ tenure on the probability they make a “bad call.” I find evidence supporting the career concerns hypothesis and that the probability that an umpire makes a bad call that shortens the length of the game and allows them to go home increases with their tenure. I show that these results are likely driven by career concerns, rather than carelessness, by showing their error rate does not increase with tenure in situations where it would not reduce their workload.

本研究以資料包絡分析法來衡量職業球員的績效表現，球員在簽訂複數年合約前後與績效表現之關聯性，來探討球員是否有合約週期的現象，進而再探究球員處於合約年的比率多寡，是否會對球隊的勝率造成影響。 　　本研究以2002年球季結束後至2008年球季開始前，這段期間曾與球團簽訂複數年合約的美國大聯盟球員為研究對象。實證結果顯示投手在簽訂複數年合約前一年，純粹技術效率有明顯增加，野手部分則顯示在簽約前兩年整體技術效率呈現顯著增加。研究結果顯示支持合約週期理論，即球員在合約年之前會刻意增加表現，以便爭取較佳之合約。另外，以2009年各球隊的勝場數為研究對象，實證結果顯示，當球隊中有較多投手處於複數年合約的第一年，則球隊的勝場數顯著較少。 / This research applies Data envelopment analysis to examine the performance of Major League Baseball (MLB) players before and after signing multi-year contracts. The research also aims to explore the claim of contract cycle theory by investigating whether contract status has an influence on wining ratio of a team. The sample includes players who signed multi-year contracts between end of season 2002 and prior season 2008. The result illustrates that pitchers’pure technical efficiency increase significantly before signing the contract and fielders’total technical efficiency increase significantly 2 years before the contract signing. The results support the contract cycle theory that players show a tendency to improve their performance prior to signing a contract in order to earn a better contract. In addition, the teams with more players who are in their first year of multi-year contract have a significantly less number of wining ratio.

The purpose of this thesis is to determine what effects draft order, monetary earnings, and Tommy John Surgery (TJS) have on the perceived value of a pitcher in Major League Baseball (MLB). For the context of this thesis, value will be defined as a player's ability to contribute to their team's wins in a positive manner. TJS has become synonymous with MLB and baseball as a sport, and many are either skeptical of its effects or over-assuming of its benefits. The three aforementioned areas of concerns were used to structure the thesis, as each dependent outcome is analyzed in a chapter of its own. Multiple articles and studies pertaining to the effects draft order, financial earnings, and TJS may have on pitcher value were compiled and analyzed. Looking at studies between pitchers who underwent TJS prior to being drafted, their order by which they are picked by a team is not as affected as assumed, but the pitcher is more likely to return to the disabled/injured list during their career in MLB. A lens of economic value saw that pitchers who were paid more added to their teams' respective wins. However, the financial loss caused by a pitcher missing time to recover from TJS could outweigh the cost of wins. From a purely Tommy-John standpoint, there are significant changes both beneficial and detrimental to a pitcher's overall statistics. Further research and personal knowledge should be explored prior to receiving TJS as a pitcher. Overall, the factor of TJS seems to have a slightly negative influence on the other two factors and an overall stronger influence than draft order or monetary earnings.