Papers Containing Tag(s): 'Longitudinal Employer Household Dynamics'
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Viewing papers 91 through 100 of 246
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Working PaperHuman 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.View Full Paper PDF
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Working PaperPay, 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.View Full Paper PDF
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Working PaperReleasing Earnings Distributions using Differential Privacy: Disclosure Avoidance System For Post Secondary Employment Outcomes (PSEO)
April 2019
Working Paper Number:
CES-19-13
The U.S. Census Bureau recently released data on earnings percentiles of graduates from post secondary institutions. This paper describes and evaluates the disclosure avoidance system developed for these statistics. We propose a differentially private algorithm for releasing these data based on standard differentially private building blocks, by constructing a histogram of earnings and the application of the Laplace mechanism to recover a differentially-private CDF of earnings. We demonstrate that our algorithm can release earnings distributions with low error, and our algorithm out-performs prior work based on the concept of smooth sensitivity from Nissim, Raskhodnikova and Smith (2007).View Full Paper PDF
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Working PaperFraudulent 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.View Full Paper PDF
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Working PaperOptimal Probabilistic Record Linkage: Best Practice for Linking Employers in Survey and Administrative Data
March 2019
Working Paper Number:
CES-19-08
This paper illustrates an application of record linkage between a household-level survey and an establishment-level frame in the absence of unique identifiers. Linkage between frames in this setting is challenging because the distribution of employment across firms is highly asymmetric. To address these difficulties, this paper uses a supervised machine learning model to probabilistically link survey respondents in the Health and Retirement Study (HRS) with employers and establishments in the Census Business Register (BR) to create a new data source which we call the CenHRS. Multiple imputation is used to propagate uncertainty from the linkage step into subsequent analyses of the linked data. The linked data reveal new evidence that survey respondents' misreporting and selective nonresponse about employer characteristics are systematically correlated with wages.View Full Paper PDF
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Working PaperDownward 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.View Full Paper PDF
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Working PaperHiring through Startup Acquisitions: Preference Mismatch and Employee Departures
September 2018
Working Paper Number:
CES-18-41
This paper investigates the effectiveness of startup acquisitions as a hiring strategy. Unlike conventional hires who choose to join a new firm on their own volition, most acquired employees do not have a voice in the decision to be acquired, much less by whom to be acquired. The lack of worker agency may result in a preference mismatch between the acquired employees and the acquiring firm, leading to elevated rates of turnover. Using comprehensive employee-employer matched data from the US Census, I document that acquired workers are significantly more likely to leave compared to regular hires. By constructing a novel peer-based proxy for worker preferences, I show that acquired employees who prefer to work for startups ' rather than established firms ' are the most likely to leave after the acquisition, lending support to the preference mismatch theory. Moreover, these departures suggest a deeper strategic cost of competitive spawning: upon leaving, acquired workers are more likely to found their own companies, many of which appear to be competitive threats that impair the acquirer's long-run performance.View Full Paper PDF
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Working PaperLEHD 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.View Full Paper PDF
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Working PaperOccupational 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.View Full Paper PDF
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Working PaperFirm 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.View Full Paper PDF
