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Mixed-Effects Methods For Search and Matching Research
September 2023
Working Paper Number:
CES-23-43
We study mixed-effects methods for estimating equations containing person and firm effects. In economics such models are usually estimated using fixed-effects methods. Recent enhancements to those fixed-effects methods include corrections to the bias in estimating the covariance matrix of the person and firm effects, which we also consider.
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Quality Adjustment at Scale: Hedonic vs. Exact Demand-Based Price Indices
June 2023
Working Paper Number:
CES-23-26
This paper explores alternative methods for adjusting price indices for quality change at scale. These methods can be applied to large-scale item-level transactions data that in cludes information on prices, quantities, and item attributes. The hedonic methods can take into account the changing valuations of both observable and unobservable charac teristics in the presence of product turnover. The paper also considers demand-based approaches that take into account changing product quality from product turnover and changing appeal of continuing products. The paper provides evidence of substantial quality-adjustment in prices for a wide range of goods, including both high-tech consumer products and food products.
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Market Power And Wage Inequality
September 2022
Working Paper Number:
CES-22-37
We propose a theory of how market power affects wage inequality. We ask how goods and labor market power jointly affect the level of wages, the Skill Premium, and wage inequality. We then use detailed microdata from the US Census between 1997 and 2016 to estimate the parameters of labor supply, technology and the market structure. We find that a less competitive market structure lowers the wage level, contributes 7% to the rise in the Skill Premium and accounts for half of the increase in between-establishment wage variance.
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The Radius of Economic Opportunity: Evidence from Migration and Local Labor Markets
July 2022
Working Paper Number:
CES-22-27
We examine the geographic incidence of local labor market growth across locations of childhood residence. We ask: when wages grow in a given US labor market, do the benefits flow to individuals growing up in nearby or distant locations? We begin by constructing new statistics on migration rates across labor markets between childhood and young adulthood. This migration matrix shows 80% of young adults migrate less than 100 miles from where they grew up. 90% migrate less than 500 miles. Migration distances are shorter for Black and Hispanic individuals and for those from low income families. These migration patterns provide information on the first order geographic incidence of local wage growth. Next, we explore the responsiveness of location choices to economic shocks. Using geographic variation induced by the recovery from the Great Recession, we estimate the elasticity of migration with respect to increases in local labor market wage growth. We develop and implement a novel test for validating whether our identifying wage variation is driven by changes in labor market opportunities rather than changes in worker composition due to sorting. We find that higher wages lead to increased in-migration, decreased out-migration and a partial capitalization of wage increases into local prices. Our results imply that for a 2 rank point increase in annual wages (approximately $1600) in a given commuting zone (CZ), approximately 99% of wage gains flow to those who would have resided in the CZ in the absence of the wage change. The geographically concentrated nature of most migration and the small magnitude of these migration elasticities suggest that the incidence of labor market conditions across childhood residences is highly local. For many individuals, the 'radius of economic opportunity' is quite narrow.
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Does Goliath Help David? Anchor Firms and Startup Clusters
May 2020
Working Paper Number:
CES-20-17
This paper investigates the effects of a large firm's geographical expansion (anchor firm) on local worker transitions into young firms through wage effects in industries economically proximate to the anchor firm. Using hand-collected data matched to administrative Census microdata, I exploit anchor firms' site selection processes to employ a difference-in-differences approach to compare workers in winning counties to those in counterfactual counties. The arrival of an anchor firm induces worker reallocation towards young firms in industries linked through input-output channels by a magnitude of 120 new businesses that account for approximately 2,300 jobs. Consistent with the literature in personnel and organizational economics, incumbent firms experiencing the fastest wage growth due to these shocks shed mid-layer employees who select into young firms within the county and in their own industry of experience. These effects are strongest in the most specialized and knowledge-intensive industries. Attracting an anchor firm to a county appears to have limited spillover effects in overall employment that are mainly driven by reorganization of incumbent firms in the anchor's input-output industries that face rising labor costs.
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Statistics on the Small Business Administration's Scale-Up America Program
April 2019
Working Paper Number:
CES-19-11
This paper attempts to quantify the difference in performance, of 'treated' (program participant) and 'non-treated' (non-participant) firms in SBA's Scale-Up initiative. I combine data from the SBA with administrative data housed at Census using a combination of numeric and name and address matching techniques. My results show that after controlling for available observable characteristics, a positive correlation exists between participation in the Scale-Up initiative and firm growth. However, publicly available survey results have shown that entrepreneurs have a variety of goals in-mind when they start their businesses. Two prominent, and potentially contradictory ones are work-life balance and greater income. That means that not all firms may want to grow and I am unable to completely control for owner motivations. Finally, I do not find a statistically significant relationship between participation in Scale-Up and firm survival once other business characteristics are accounted for.
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The Potential for Using Combined Survey and Administrative Data Sources to Study Internal Labor Migration
January 2017
Working Paper Number:
CES-17-55
This paper introduces a novel data set combining survey data from the American Community Survey (ACS) with administrative data on employment from the Longitudinal Employer-Household Dynamics program, in order to study geographic labor mobility. With its rich set of information about individuals at the time of the migration decision, large sample size, and near-comprehensive ability to detect labor mobility, the new combined ACS-LEHD data offers several advantages over the existing data sets that are typically used in the study of migration, such as the Decennial Census, Current Population Survey, and Internal Revenue Service data. An overview of how these different data sets can be employed, and examples demonstrating the usefulness of the newly proposed data set, are provided.
Aggregate statistics and stylized facts are generated from the ACS-LEHD data which reveal many of the same features as the existing data sets, including the decline of aggregate mobility throughout the past decade, as well as many of the known demographic differences in migration propensity.
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Are firm-level idiosyncratic shocks important for U.S. aggregate volatility?
January 2017
Working Paper Number:
CES-17-23
This paper quantitatively assesses whether firm-specific shocks can drive the U.S. business cycle. Firm-specific shocks to the largest firms can directly contribute to aggregate fluctuations whenever the firm size distribution is fat-tailed giving rise to the granular hypothesis. I use a novel, comprehensive data set compiled from administrative sources that contains the universe of firms and trade transactions, and find that the granular hypothesis accounts at most for 16 percent of the variation in aggregate sales growth. This is about half of that found by previous studies that imposed Gibrat's law where all firms are equally volatile regardless of their size. Using the full distribution of growth rates among U.S. firms, I find robust evidence of a negative relationship between firm-level volatility and size, i.e. the size-variance relationship. The largest firms (whose shocks drive granularity) are the least volatile under the size-variance relationship, thus their influence on aggregates is mitigated. I show that by taking this relationship into account the effect of firm-specific shocks on observed macroeconomic volatility is substantially reduced. I then investigate several plausible mechanisms that could explain the negative sizevariance relationship. After empirically ruling out some of them, I suggest a 'market power' channel in which large firms face smaller price elasticities and therefore respond less to a givensized productivity shock than small firms do. I provide direct evidence for this mechanism by estimating demand elasticities among U.S. manufactures. Lastly, I construct an analytically tractable framework that is consistent with several empirical regularities related to firm size.
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Slow to Hire, Quick to Fire: Employment Dynamics with Asymmetric Responses to News
January 2017
Working Paper Number:
CES-17-15
Concave hiring rules imply that firms respond more to bad shocks than to good shocks. They provide a united explanation for several seemingly unrelated facts about employment growth in macro and micro data. In particular, they generate countercyclical movement in both aggregate conditional 'macro' volatility and cross-sectional 'micro' volatility as well as negative skewness in the cross section and in the time series at different level of aggregation. Concave establishment level responses of employment growth to TFP shocks estimated from Census data induce significant skewness, movements in volatility and amplification of bad aggregate shocks.
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Labor Reallocation, Employment, and Earnings: Vector Autoregression Evidence
January 2017
Working Paper Number:
CES-17-11R
Analysis of the labor market has given increasing attention to the reallocation of jobs across employers and workers across jobs. However, whether and how job reallocation and labor market 'churn' affects the health of the labor market remains an open question. In this paper, we present time series evidence for the U.S. 1993-2013 and consider the relationship between labor reallocation, employment, and earnings using a vector autoregression (VAR) framework. We find that an increase in labor market churn by 1 percentage point predicts that, in the next quarter, employment will increase by 100 to 560 thousand jobs, lowering the unemployment rate by 0.05 to 0.25 percentage points. Job destruction does not predict future changes in employment but a 1 percentage point increase in job destruction leads to an increase in future unemployment 0.14 to 0.42 percentage points. We find mixed results on the relationship between labor reallocation rates and earnings: we nd that, especially for earnings derived from administrative records data, a 1 percentage point increase to either job destruction or churn leads to increased earnings of less than 2 percent. Results vary substantially depending on the earnings measure we use, and so the evidence inconsistent on whether productivity-enhancing aspects of churn and job destruction provide earnings gains for workers in aggregate. Our findings on churn leading to increased employment and a lower unemployment rate are consistent with models of replacement hiring and vacancy chains.
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