Essays in applied microeconomics

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Abstract/Contents

Abstract
This dissertation consists of three distinct essays in applied microeconomics. "The Effect of Uncertainty on Investment, Hiring, and R& D: Causal Evidence from Equity Options" (with Elizabeth C. Stone, Analysis Group), conducts an econometric analysis of the impact of economic uncertainty on firm behavior. There is wide debate over this impact, due to the difficulty both of measuring uncertainty and of identifying causality. This chapter takes three steps that attempt to address these challenges. First, we develop an instrumental variables strategy that exploits firms' differential exposure to energy and currency prices and volatility. For example, airlines are negatively affected by high oil prices while oil refiners benefit from them, but both are sensitive to oil price volatility; retailers, in comparison, are not particularly sensitive to either the level or volatility of oil prices. Second, we use the expected volatility of stock prices as implied by equity options to obtain forward-looking measures of uncertainty over firms' business conditions. Finally, we examine how uncertainty affects a range of outcomes: capital investment, hiring, research and development, and advertising. We find that uncertainty depresses capital investment, hiring, and advertising, but encourages R& D spending. This perhaps-surprising result for R& D is consistent with a theoretical literature emphasizing that long investment lags create valuable real put options which offset the effects of call options lost when projects are started. Aggregating across our panel of Compustat firms, we find that rising uncertainty accounts for roughly a third of the fall in capital investment and hiring that occurred in 2008-10. "The Visible Hand: Race and Online Market Outcomes" (with Jennifer L. Doleac, University of Virginia), considers questions regarding how and under what circumstances buyers respond to a seller's race in the marketplace. Do prospective customers behave differently based on sellers' race or signals about sellers' socioeconomic class? Does this depend on whether a customer lives somewhere racially segregated or plagued by property crime? We investigate these questions in a year-long experiment in which we sold iPods through local online classified advertisements throughout the U.S., each featuring a photograph of the product held by a hand that is dark-skinned ("black"), light-skinned ("white"), or with a wrist tattoo (associated with lower social class). We find that black sellers do worse than white sellers on a variety of metrics: they receive 13% fewer responses, 18% fewer offers, and offers that are 11-12% lower. These effects are similar in magnitude to those associated with a white seller's display of a tattoo. Buyers corresponding with a black seller also behave in ways suggesting they trust the seller less: they are less likely to include their names, and less likely to agree to a proposed delivery by mail (rather than cutting off communication or expressing concern about long-distance payments). Black sellers suffer particularly poor outcomes in thin markets; it appears that discrimination may not "survive" in the presence of significant competition among buyers. Furthermore, black sellers do worst in markets that are racially segregated and have high property crime rates, suggesting that at least part of the explanation is statistical discrimination--that is, buyers' concerns about the time and potential danger involved in the transaction, or that the iPod is stolen goods. "Race, Skin Color, and Economic Outcomes in Early Twentieth-Century America" (with Roy Mill, Stanford University and Ancestry.com), considers the effect of race on economic outcomes using unique data from the first half of the twentieth century, a period in which skin color was explicitly coded in population censuses as "White, " "Black, " or "Mulatto." We construct a panel of siblings by digitizing and matching records across the 1910 and 1940 censuses and identifying all 12,000 African-American families in which enumerators classified some children as light-skinned ("Mulatto") and others as dark-skinned ("Black"). Siblings coded "Mulatto" when they were children (in 1910) earned similar wages as adults (in 1940) relative to their Black siblings. This within-family earnings difference is substantially lower than the Black-Mulatto earnings difference in the general population, suggesting that skin color in itself played only a small role in the racial earnings gap. To explore the role of the more social aspect that might be associated with being Black, we then focus on individuals who "passed for White, " an important social phenomenon at the time. To do so, we identify individuals coded "Mulatto" as children but "White" as adults. Passing for White meant that individuals changed their racial affiliation by changing their social ties, while skin color remained unchanged. We compare passers to their siblings who did not pass. Passing was associated with substantially higher earnings, suggesting that race in its social form could have significant consequences for economic outcomes. We discuss how our findings shed light on the roles of discrimination and identity in driving economic outcomes.

Description

Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2013
Issuance monographic
Language English

Creators/Contributors

Associated with Stein, Luke Comins Donohoe
Associated with Stanford University, Department of Economics.
Primary advisor Bloom, Nick, 1973-
Thesis advisor Bloom, Nick, 1973-
Thesis advisor Abramitzky, Ran
Thesis advisor Hoxby, Caroline Minter
Advisor Abramitzky, Ran
Advisor Hoxby, Caroline Minter

Subjects

Genre Theses

Bibliographic information

Statement of responsibility Luke C. D. Stein.
Note Submitted to the Department of Economics.
Thesis Thesis (Ph.D.)--Stanford University, 2013.
Location electronic resource

Access conditions

Copyright
© 2013 by Luke Comins Donohoe Stein
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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