Trevon D. Logan

Personal Characteristics, Sexual Behaviors, and Male Sex Work A Quantitative Approach

Male sex workers serve multiple groups (i.e., gay-identified men, heterosexually-identified men, and their own sexual partners), making them a unique source to test theories of gender, masculinity, and sexuality. To date, most scholarship on this topic has been qualitative. I assembled a dataset from the largest online male sex worker website to conduct the first quantitative analysis of male escorts in the United States. I find the geographic distribution of male sex workers is more strongly correlated with the general population than with the gay male population. In addition, I estimate the value of sexual behaviors and personal characteristics in this market to test sociological theories of gender and masculinity. Consistent with hegemonic masculinity, I find that male escorts who advertise masculine behavior charge higher prices for their services, whereas escorts who advertise less masculine behavior charge significantly less, a differential on the order of 17 percent. Results show that race and sexual behavior interactions exert a strong influence on prices charged by male sex workers, confirming aspects of intersectionality theory.

The Transformation of Hunger: The Demand for Calories Past and Present

the long struggle with subsistence and chronic malnutrition throughout human history, the quantification of hunger seems a likely candidate to tell us about how living standards have changed over time. Using this insight, I adopt a novel approach to measuring living standards - exploring how the demand for calories in the past compares to the situation in todays developing countries. Using calorie demand to analyze living standards in the past is important in two ways. First, the methodology allows us to look at living standards today and in the past in the same manner and with the same interpretation. Second, this methodology allows us to ask and answer the question of how living standards have changed over time in a tractable way that is closely related to a basic dimension of human welfare. I compare the calorie demand for industrial workers in the United States and Great Britain in the late nineteenth century to those from developing countries today. While calorie demand estimation is

Nutrition and Well-Being in the Late Nineteenth Century

Using the 1888 Cost of Living Survey, I estimate the demand for calories of American and British industrial workers. I find that the income and expenditure elasticities of calories for American households are significantly lower than the corresponding elasticities for British households, suggesting that American industrial workers were nutritionally better off than their British counterparts. I further find that the calorie elasticity differential between the two countries was driven by the higher wages enjoyed in the United States. Additional analysis reveals that the relative price of calories was approximately 20 percent greater in Great Britain than in the United States.

ECONOMIES OF SCALE IN THE HOUSEHOLD: PUZZLES AND PATTERNS FROM THE AMERICAN PAST

Household economies of scale arise when households with multiple members share public goods, making larger households better off at lower per capita expenditures. While estimates of household economies of scale are critical for measuring income and living standards, we do not know how these scale economies change over time. I use American household expenditure surveys to produce the first comparable historical estimates of household scale economies. I find that scale economies changed significantly from 1888 to 1935 for all expenditure categories considered (food, clothing, entertainment, and housing), but not all trends in scale economies are consistent with theoretical predictions. I use these historical estimates of household scale economies to resolve several theoretical and empirical puzzles in the literature. I find that existing explanations for puzzles in the household economies of scale literature do not hold in the past. As such, our notions about household economies of scale must be reassessed in light of this historical evidence.

IS THERE DOWRY INFLATION IN SOUTH ASIA

Abstract. This article is the first systematic attempt to measure the existence and degree of dowry inflation in South Asia. The popular press and scholarly literature have assumed dowry inflation in South Asia for some time, and there are now a number of theoretical papers that have attempted to explain the rise of dowries in South Asia. Despite these advances, there has been no systematic study of dowry inflation. Using large-sample retrospective survey data from India, Bangladesh, Pakistan, and Nepal, researchers assess the empirical evidence for dowry inflation. They find no evidence that real dowry amounts have systematically increased over time in South Asia.

Face Value: Information and Signaling in an Illegal Market

Economists argue that rich information environments and formal enforcement of contracts are necessary to prevent market failures when information asymmetries exist. We test for the necessity of formal enforcement to overcome the problems of asymmetric information by estimating the value of information in an illegal market with a particularly rich information structure: the online market for male sex work. We assemble a rich data set from the largest and most comprehensive online male sex worker Web site to estimate the effect of information on pricing. We show how clients of male sex workers informally police the market in a way that makes signaling credible. Using institutional knowledge, we identify the specific signal male sex workers use to communicate quality to clients: face pictures. We find that there is a substantial return to the signal in this market. The findings provide novel evidence on the ability of rich information environments to overcome problems of asymmetric information without formal enforcement mechanisms.

The National Rise in Residential Segregation

This paper introduces a new measure of residential segregation based on individual-level data. We exploit complete census manuscript files to derive a measure of segregation based upon the racial similarity of next-door neighbors. Our measure allows us to analyze segregation consistently and comprehensively for all areas in the United States and allows for a richer view of the variation in segregation across time and space. We show that the fineness of our measure reveals aspects of racial sorting that cannot be captured by traditional segregation indices. Our measure can distinguish between the effects of increasing racial homogeneity of a location and the tendency to segregate within a location given a particular racial composition. Analysis of neighbor-based segregation over time establishes several new facts about segregation. First, segregation doubled nationally from 1880 to 1940. Second, contrary to previous estimates, we find that urban areas in the South were the most segregated in the country and remained so over time. Third, the dramatic increase in segregation in the twentieth century was not driven by urbanization, black migratory patterns, or white flight to suburban areas, but rather resulted from a national increase in racial sorting at the household level. The likelihood that an African American household had a non-African American neighbor declined by more than 15 percentage points (more than a 25% decrease) through the mid-twentieth century. In all areas of the United States -- North and South, urban and rural -- racial segregation increased dramatically.

Are Sports Betting Markets Prediction Markets?: Evidence From a New Test

Researchers commonly use sports betting lines as predictions of the outcome of sporting events. Betting houses set betting lines conditional on bettors ex ante beliefs about game outcomes, which implies that the predictive power of the sports betting market could be an unintended consequence of betting house profit maximization. Using this insight, the authors propose a new test of the predictive power of the sports betting market, which incorporates a seldom-used piece of complementary betting information: the over/under—the predicted sum of scores for a game. Since the over/under has the same market properties as the betting line, it should be similarly predictive about the actual outcome, while if bettors have different beliefs about this game feature it need not be predictive. Using the universe of betting lines and over/unders on National Football League (NFL), National Basketball Association (NBA), National Collegiate Athletic Association (NCAA) college football, and NCAA college basketball games from 2004 to 2010, the authors test the predictive power of the sports betting market in a seemingly unrelated regression (SUR) structure that allows us to characterize both features of the betting market simultaneously. The joint test reveals that while the betting line is an accurate predictor of the margin of victory, the over/under is a poor predictor of the sum of scores. The authors consistently reject the hypothesis that the sports betting market overall functions well as a prediction market.

Are Engel Curve Estimates of CPI Bias Biased

Recent literature has advanced the use of Engel curves to estimate overall consumer price index (CPI) bias. The author shows that this methodology is sensitive to the modeling of household demography. Existing estimates of CPI bias do not account for the changing effect of household size on the budget shares, which can lead to omitted variable bias. Because the effect of household size on demand changes over time, this effect partially explains the drift in Engel curves attributed to CPI bias. The authors estimates of the changing effect for household size alters the annual rate of CPI bias every year from 1888 to 1935 by at least 25 percent and usually more than 50 percent. These findings caution against the use of Engel curves to correct CPI bias in the past.

Econometric tests of American college football's conventional wisdom

College football fans, coaches and observers have adopted a set of beliefs about how college football poll voters behave. I document three pieces of conventional wisdom in college football regarding the timing of wins and losses, the value of playing strong opponents and the value of winning by wide margins. Using a unique data set with 25 years of Associated Press (AP) poll results, I use a hedonic regression to test college footballs conventional wisdom. In particular, I test (1) whether it is better to lose early or late in the season, (2) whether teams benefit from playing stronger opponents and (3) whether teams are rewarded for winning by large margins. Contrary to conventional wisdom, I find that (1) it is better to lose later in the season than earlier, (2) AP voters do not pay attention to the strength of a defeated opponent and (3) the benefit of winning by a large margin is negligible. I conclude by noting how these results inform debates about a potential playoff in college football.