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Twisting the Demand Curve: Digitalization and the Older Workforce
November 2020
Working Paper Number:
CES-20-37
This paper uses U.S. Census Bureau panel data that link firm software investment to worker earnings. We regress the log of earnings of workers by age group on the software investment by their employing firm. To unpack the potential causal factors for differential software effects by age group we extend the AKM framework by including job-spell fixed effects that allow for a correlation between the worker-firm match and age and by including time-varying firm effects that allow for a correlation between wage-enhancing productivity shocks and software investments. Within job-spell, software capital raises earnings at a rate that declines post age 50 to about zero after age 65. By contrast, the effects of non-IT equipment investment on earnings increase for workers post age 50. The difference between the software and non-IT equipment effects suggests that our results are attributable to the technology rather than to age-related bargaining power. Our data further show that software capital increases the earnings of high-wage workers relative to low-wage workers and the earnings in high-wage firms relative to low-wage firms, and may thus widen earnings inequality within and across firms.
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Total Error and Variability Measures for the Quarterly Workforce Indicators and LEHD Origin Destination Employment Statistics in OnTheMap
September 2020
Working Paper Number:
CES-20-30
We report results from the first comprehensive total quality evaluation of five major indicators in the U.S. Census Bureau's Longitudinal Employer-Household Dynamics (LEHD) Program Quarterly Workforce Indicators (QWI): total flow-employment, beginning-of-quarter employment, full quarter employment, average monthly earnings of full-quarter employees, and total quarterly payroll. Beginning-of-quarter employment is also the main tabulation variable in the LEHD Origin-Destination Employment Statistics (LODES) workplace reports as displayed in On-TheMap (OTM), including OnTheMap for Emergency Management. We account for errors due to coverage; record-level non response; edit and imputation of item missing data; and statistical disclosure limitation. The analysis reveals that the five publication variables under study are estimated very accurately for tabulations involving at least 10 jobs. Tabulations involving three to nine jobs are a transition zone, where cells may be fit for use with caution. Tabulations involving one or two jobs, which are generally suppressed on fitness-for-use criteria in the QWI and synthesized in LODES, have substantial total variability but can still be used to estimate statistics for untabulated aggregates as long as the job count in the aggregate is more than 10.
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United States Earnings Dynamics: Inequality, Mobility, and Volatility
September 2020
Working Paper Number:
CES-20-29
Using data from the Census Bureau's Longitudinal Employer-Household Dynamics (LEHD) infrastructure files, we study changes over time and across sub-national populations in the distribution of real labor earnings. We consider four large MSAs (Detroit, Los Angeles, New York, and San Francisco) for the period 1998 to 2017, with particular attention paid to the subperiods before, during, and after the Great Recession. For the four large MSAs we analyze, there are clear national trends represented in each of the local areas, the most prominent of which is the increase in the share of earnings accruing to workers at the top of the earnings distribution in 2017 compared with 1998. However, the magnitude of these trends varies across MSAs, with New York and San Francisco showing relatively large increases and Los Angeles somewhere in the middle relative to Detroit whose total real earnings distribution is relatively stable over the period. Our results contribute to the emerging literature on differences between national and regional economic outcomes, exemplifying what will be possible with a new data exploration tool'the Earnings and Mobility Statistics (EAMS) web application'currently under development at the U.S. Census Bureau.
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Family-Leave Mandates and Female Labor at U.S. Firms: Evidence from a Trade Shock
September 2020
Working Paper Number:
CES-20-25
We study the role of family-leave mandates in shaping the gender composition at U.S. firms that experience a negative demand shock. In a regression discontinuity framework, we compare firms mandated to provide job-protected leave under the Family and Medical Leave Act (FMLA) and firms that are exempt from the law (non-FMLA) following the post-2001 surge in Chinese imports. Using confidential microdata on matched employers and employees in the U.S. non-farm private sector, we find that between 2000 and 2003, an increase in import competition decreases the share of female workers at FMLA compared to non-FMLA firms. The negative differential effect is driven by female workers in prime childbearing years, with less than college education, and is strongest at firms with all male managers. We find similar patterns in changes in the female share of earnings and promotions. These results suggest that, when traditional gender norms prevail, adverse shocks may exacerbate gender inequalities in the presence of job-protected leave mandates.
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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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Earnings Growth, Job Flows and Churn
April 2020
Working Paper Number:
CES-20-15
How much do workers making job-to-job transitions benefit from moving away from a shrinking and towards a growing firm? We show that earnings growth in the transition increases with net employment growth at the destination firm and, to a lesser extent, decreases if the origin firm is shrinking. So, we sum the effect of leaving a shrinking and entering a growing firm and remove the excess turnover-related hires because gross hiring has a much smaller association with earnings growth than net employment growth. We find that job-to-job transitions with the cross-firm job flow have 23% more earnings growth than average.
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Human Capital, Parent Size and the Destination Industry of Spinouts
October 2019
Working Paper Number:
CES-19-30
We study how spinout founders' human capital and parent size relate to founders' propensity to stay in the same industry as their parents or to go outside the industry. Individuals with high human capital face a higher performance penalty if they form spinouts outside the parent industry, but they also face greater deterrence from large parents if they stay in that industry. Using matched employer employee data on spinout founders and their coworkers, we find that individuals with higher human capital are less likely to form spinouts in distant industries than in the parent's industry. Further, we find that as parent size increases, such individuals are less likely to form spinouts in the parent's industry and more likely to form spinouts in distant industries.
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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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Re-engineering Key National Economic Indicators
July 2019
Working Paper Number:
CES-19-22
Traditional methods of collecting data from businesses and households face increasing challenges. These include declining response rates to surveys, increasing costs to traditional modes of data collection, and the difficulty of keeping pace with rapid changes in the economy. The digitization of virtually all market transactions offers the potential for re-engineering key national economic indicators. The challenge for the statistical system is how to operate in this data-rich environment. This paper focuses on the opportunities for collecting item-level data at the source and constructing key indicators using measurement methods consistent with such a data infrastructure. Ubiquitous digitization of transactions allows price and quantity be collected or aggregated simultaneously at the source. This new architecture for economic statistics creates challenges arising from the rapid change in items sold. The paper explores some recently proposed techniques for estimating price and quantity indices in large scale item-level data. Although those methods display tremendous promise, substantially more research is necessary before they will be ready to serve as the basis for the official economic statistics. Finally, the paper addresses implications for building national statistics from transactions for data collection and for the capabilities and organization of the statistical agencies in the 21st century.
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Fraudulent Financial Reporting and the Consequences for Employees
March 2019
Working Paper Number:
CES-19-12
We examine employment effects, such as wages and employee turnover, before, during, and after periods of fraudulent financial reporting. To analyze these effects, we combine U.S. Census data with SEC enforcement actions against firms with serious misreporting ('fraud'). We find compared to a matched sample that fraud firms' employee wages decline by 9% and the separation rate is higher by 12% during and after fraud periods while employment growth at fraud firms is positive during fraud periods and negative afterward. We discuss several reasons that plausibly drive these findings. (i) Frauds cause informational opacity, misleading employees to still join or continue to work at the firm. (ii) During fraud, managers overinvest in labor changing employee mix, and after fraud the overemployment is unwound causing effects from displacement. (iii) Fraud is misconduct; association with misconduct can affect workers in the labor market. We explore the heterogeneous effects of fraudulent financial reporting, including thin and thick labor markets, bankruptcy and non-bankruptcy firms, worker movements, pre-fraud wage levels, and period of hire. Negative wage effects are prevalent across these sample cuts, indicating that fraudulent financial reporting appears to create meaningful and negative consequences for employees possibly through channels such as labor market disruptions, punishment, and stigma.
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