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What Do Establishments Do When Wages Increase?
Evidence from Minimum Wages in the United States
November 2019
Working Paper Number:
CES-19-31
I investigate how establishments adjust their production plans on various margins when wage rates increase. Exploiting state-by-year variation in minimum wage, I analyze U.S. manufacturing plants' responses over a 23-year period. Using instrumental variable method and Census Microdata, I find that when the hourly wage of production workers increases by one percent, manufacturing plants reduce the total hours worked by production workers by 0.7 percent and increase capital expenditures on machinery and equipment by 2.7 percent. The reduction in total hours worked by production workers is driven by intensive-margin changes. The estimated elasticity of substitution between capital and labor is 0.85. Following the wage increases, no statistically significant changes emerge in revenue, materials or total factor productivity. Additionally, I nd that when wage rates increase, establishments are more likely to exit the market. Finally, I provide evidence that when the minimum wage increases the wages of some of the establishments in a firm, the firm also increases the wages for its other establishments.
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Pay, Employment, and Dynamics of Young Firms
July 2019
Working Paper Number:
CES-19-23
Why do young firms pay less? Using confidential microdata from the US Census Bureau, we find lower earnings among workers at young firms. However, we argue that such measurement is likely subject to worker and firm selection. Exploiting the two-sided panel nature of the data to control for relevant dimensions of worker and firm heterogeneity, we uncover a positive and significant young-firm pay premium. Furthermore, we show that worker selection at firm birth is related to future firm dynamics, including survival and growth. We tie our empirical findings to a simple model of pay, employment, and dynamics of young firms.
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Downward Nominal Wage Rigidity in the United States:
New Evidence from Worker-Firm Linked Data
February 2019
Working Paper Number:
CES-19-07
This paper examines the extent and consequences of Downward Nominal Wage Rigidity (DNWR) using administrative worker-firm linked data from the Longitudinal Employer Household Dynamics (LEHD) program for a large representative U.S. state. Prior to the Great Recession, only 7-8% of job stayers are paid the same nominal hourly wage rate as one year earlier - substantially less than previously found in survey-based data - and about 20% of job stayers experience a wage cut. During the Great Recession, the incidence of wage cuts increases to 30%, followed by a large rise in the proportion of wage freezes to 16% as the economy recovers. Total earnings of job stayers exhibit even fewer zero changes and a larger incidence of reductions than hourly wage rates, due to systematic variations in hours worked. The results are consistent with concurrent findings in the literature that reductions in base pay are exceedingly rare but that firms use different forms of non-base pay and variations in hours worked to flexibilize labor cost. We then exploit the worker-firm link of the LEHD and find that during the Great Recession, firms with indicators of DNWR reduced employment by about 1.2% more per year. This negative effect is driven by significantly lower hiring rates and persists into the recovery. Our results suggest that despite the relatively large incidence of wage cuts in the aggregate, DNWR has sizable allocative consequences.
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Why are employer-sponsored health insurance premiums higher in the public sector than in the private sector?
February 2019
Working Paper Number:
CES-19-03
In this article, we examine the factors explaining differences in public and private sector health insurance premiums for enrollees with single coverage. We use data from the 2000 and 2014 Medical Expenditure Panel Survey-Insurance Component, along with decomposition methods, to explore the relative explanatory importance of plan features and benefit generosity, such as deductibles and other forms of cost sharing, basic employee characteristics (e.g., age, gender, and education), and unionization. While there was little difference in public and private sector premiums in 2000, by 2014, public premiums had exceeded private premiums by 14 to 19 percent. We find that differences in plan characteristics played a substantial role in explaining premium differences in 2014, but they were not the only, or even the most important, factor. Differences in worker age, gender, marital status, and educational attainment were also important factors, as was workforce unionization.
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Predictive Analytics and Organizational Architecture:
Plant-Level Evidence from Census Data
January 2019
Working Paper Number:
CES-19-02
We examine trends in the use of predictive analytics for a sample of more than 25,000 manufacturing plants using proprietary data from the US Census Bureau. Comparing 2010 and 2015, we find that use of predictive analytics has increased markedly, with the greatest use in younger plants, professionally-managed firms, more educated workforces, and stable industries. Decisions on data to be gathered originate from headquarters and are associated with less delegation of decision-making and more widespread awareness of quantitative targets among plant employees. Performance targets become more accurate, long-term oriented, and linked to company-wide performance, and management incentives strengthen, both in terms of monetary bonuses and career outcomes. Plants increasing predictive analytics become more efficient, with lower inventory, increased volume of shipments, narrower product mix, reduced management payroll and increased use of flexible and temporary employees. Results are robust to a specification based on increased government demand for data.
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LEHD Infrastructure S2014 files in the FSRDC
September 2018
Working Paper Number:
CES-18-27R
The Longitudinal Employer-Household Dynamics (LEHD) Program at the U.S. Census Bureau, with the support of several national research agencies, maintains a set of infrastructure files using administrative data provided by state agencies, enhanced with information from other administrative data sources, demographic and economic (business) surveys and censuses. The LEHD Infrastructure Files provide a detailed and comprehensive picture of workers, employers, and their interaction in the U.S. economy. This document describes the structure and content of the 2014 Snapshot of the LEHD Infrastructure files as they are made available in the Census Bureau's secure and restricted-access Research Data Center network. The document attempts to provide a comprehensive description of all researcher-accessible files, of their creation, and of any modifications made to the files to facilitate researcher access.
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Labor Market Concentration, Earnings Inequality, and Earnings Mobility
September 2018
Working Paper Number:
carra-2018-10
Using data from the Longitudinal Business Database and Form W-2, I document trends in local industrial concentration from 1976 through 2015 and estimate the effects of that concentration on earnings outcomes within and across demographic groups. Local industrial concentration has generally been declining throughout its distribution over that period, unlike national industrial concentration, which declined sharply in the early 1980s before increasing steadily to nearly its original level beginning around 1990. Estimates indicate that increased local concentration reduces earnings and increases inequality, but observed changes in concentration have been in the opposite direction, and the magnitude of these effects has been modest relative to broader trends; back-of-the-envelope calculations suggest that the 90/10 earnings ratio was about six percent lower and earnings were about one percent higher in 2015 than they would have been if local concentration were at its 1976 level. Within demographic subgroups, most experience mean earnings reductions and all experience increases in inequality. Estimates of the effects of concentration on earnings mobility are sensitive to specification.
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Occupational Classifications: A Machine Learning Approach
August 2018
Working Paper Number:
CES-18-37
Characterizing the work that people do on their jobs is a longstanding and core issue in labor economics. Traditionally, classification has been done manually. If it were possible to combine new computational tools and administrative wage records to generate an automated crosswalk between job titles and occupations, millions of dollars could be saved in labor costs, data processing could be sped up, data could become more consistent, and it might be possible to generate, without a lag, current information about the changing occupational composition of the labor market. This paper examines the potential to assign occupations to job titles contained in administrative data using automated, machine-learning approaches. We use a new extraordinarily rich and detailed set of data on transactional HR records of large firms (universities) in a relatively narrowly defined industry (public institutions of higher education) to identify the potential for machine-learning approaches to classify occupations.
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Firm Leverage, Labor Market Size, and Employee Pay
August 2018
Working Paper Number:
CES-18-36
We provide new estimates of the wage costs of firms' debt using an empirical approach that exploits within-firm geographical variation in workers' expected unemployment costs due to variation in local labor market in a large sample of public firms. We find that, following an increase in firm leverage, workers with higher unemployment costs experience higher wage growth relative to workers at the same firm with lower unemployment costs. Overall, our estimates suggest wage costs are an important component in the overall cost of debt, but are not as large as implied by estimates based on ex post employee wage losses due to bankruptcy; we estimate that a 10 percentage point increase in firm leverage increases wage compensation for the median worker by 1.9% and total firm wage costs by 17 basis points of firm value.
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Strong Employers and Weak Employees:
How Does Employer Concentration Affect Wages?
April 2018
Working Paper Number:
CES-18-15
We analyze the effect of local-level labor market concentration on wages. Using plant-level U.S. Census data over the period 1977'2009, we find that: (1) local-level employer concentration exhibits substantial cross-sectional and time-series variation and increases over time; (2) consistent with labor market monopsony power, there is a negative relation between local-level employer concentration and wages that is more pronounced at high levels of concentration and increases over time; (3) the negative relation between labor market concentration and wages is stronger when unionization rates are low; (4) the link between productivity growth and wage growth is stronger when labor markets are less concentrated; and (5) exposure to greater import competition from China (the 'China Shock') is associated with more concentrated labor markets. These five results emphasize the role of local-level labor market monopsonies in influencing firm wage-setting.
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