A Model of Asymmetric Employer Learning With Testable Implications

This paper develops and tests a unique model of asymmetric employer learning. The model relaxes the informational assumptions used in most of the previous literature and assumes firms compete for workers through bidding wars. As a result, outside firms can profitably compete for an employed worker who is equally productive in any firm, despite the current employer’s informational advantage. The model in this paper is the first in the literature to predict either wage growth without changes in publicly observed information (e.g., promotions) or mobility between firms without firm- or match-specific productivity. The bidding through which firms compete for a worker produces a sequence of wages that converges to the current employer’s conditional expectation of the worker’s productivity. This convergence of wages allows the model to be tested using an extension of previous work on employer learning. Wage regressions estimated on a sample of men from the NLSY produce evidence consistent with the model’s predictions.Asymmetric Employer Learning; Wage and Performance Relationship; Applications of Auction Theory

Time Spent Exercising and Obesity: An Application of Lewbel’s Instrumental Variables Method

This paper examines the role physical activity plays in determining body mass using data from the American Time Use Survey. Our work is the first to address the measurement error that arises when time use during a single day—rather than average daily time use over an extended period—is used as an explanatory variable. We show that failing to account for day-to-day variation in activities results in the effects of time use on a typical day being understated. Furthermore, we account for the possibility that physical activity and body mass are jointly determined by implementing Lewbel’s instrumental variables estimator that exploits first-stage heteroskedasticity rather than traditional exclusion restrictions. Our results suggest that, on average, physical activity reduces body mass by less than would be predicted by simple calorie expenditure-to-weight formulas, implying compensatory behavior such as increased caloric intake

Did Social-Distancing Measures in Kentucky Help to Flatten the COVID-19 Curve?

In the absence of a vaccine or more effective treatment options, containing the spread of novel coronavirus disease 2019 (COVID-19) must rely on non-pharmaceutical interventions. All U.S. states adopted social-distancing measures in March and April of 2020, though they varied in both timing and scope. Kentucky began by closing public schools and restaurant dining rooms on March 16th before progressing to closing other non-essential businesses and eventually issuing a “Healthy at Home” order with restrictions similar to the shelter-in-place (SIPO) orders adopted by other states. We aim to quantify the impact of these measures on COVID-19 case growth in the state. An event-study model allows us to link adoption of social distancing measures across the Midwest and South to the growth rate of cases, allowing for effects to emerge gradually to account for the lag between infection and positive test result. We then use the results to predict how the number of cases would have evolved in Kentucky in the absence of these policy measures – in other words, if the state had relied on voluntary social distancing alone. We estimate that, by April 25, Kentucky would have had 44,482 confirmed COVID-19 cases without social distancing restrictions, as opposed to the 3,857 actually observed

A Test of Screening Discrimination with Employer Learning

This paper tests for the presence of screening discrimination, a type of statistical discrimination that occurs when employers are less able to evaluate the ability of workers from one group than from another. Using data from the 2000 release of the NLSY79, the author examines wage equations in a framework of employer learning to test the hypothesis that the market receives less reliable productivity signals at labor market entry from black men than from white men. The estimation results support this hypothesis. Variables that are difficult for employers to observe, such as the AFQT score, had less influence on the wages of black men (and easily observed variables had more influence) than on the wages of white men. The influence of hard-to-observe variables on wages, however, increased faster with experience for black men

Housing Vouchers and Economic Self-Sufficiency: Evidence from a Randomized Experiment

Housing policies for low-income families may affect the concentration of poverty in America, which could in turn affect the ability of families receiving housing services to become economically self-sufficient. In this paper we examine the effects of a randomized housing- voucher experiment on welfare receipt and labor market outcomes, both of which are measured using state administrative data. We find that providing families in high-poverty public housing areas with housing vouchers that can only be redeemed in low-poverty neighborhoods reduces rates of welfare use by around 6 percentage points. Most of this reduction in welfare receipt appears to be explained by differences in welfare-to-work transitions. We also find that providing families with unrestricted housing vouchers has little effect on economic outcomes beyond the first year

Chance Elections, Social Distancing Restrictions, and KENTUCKY\u27s Early COVID-19 Experience

Early in the pandemic, slowing the spread of novel coronavirus disease 2019 (COVID-19) relied on non-pharmaceutical interventions. All U.S. states adopted social-distancing restrictions in March and April of 2020, though policies varied both in timing and scope. Compared to states with Democratic governors, those with Republican governors often adopted measures for shorter durations and with greater resistance from their residents. In Kentucky, an extremely close gubernatorial election immediately prior to the discovery of SARS-CoV-2 replaced a Republican incumbent with a Democrat, despite Republicans easily winning all other statewide races. This chance election result offers a unique opportunity to examine the impact of early social distancing policies in a relatively conservative, rural, white-working-class state. Our study begins by estimating an event-study model to link adoption of several common social distancing measures–public school closures, bans on large gatherings, closures of entertainment-related businesses such as restaurants, and shelter-in-place orders (SIPOs)–to the growth rate of cases across counties in the Midwest and South in the early stages of the pandemic. These policies combined to slow the daily growth rate of COVID-19 cases by 9 percentage points after 16 days, with SIPOs and entertainment establishment closures accounting for the entire effect. In order to obtain results with more direct applicability to Kentucky, we then estimate a model that interacts the policy variables with a “white working class” index characterized by political conservatism, rurality, and high percentages of white, evangelical Christian residents without college degrees. We find that the effectiveness of early social distancing measures decreased with higher values of this index. The results imply that the restrictions combined to slow the spread of COVID-19 by 12 percentage points per day in Kentucky’s two largest urban counties but had no statistically detectable effect across the rest of the state