Papers Containing Tag(s): 'Alfred P Sloan Foundation'
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Viewing papers 31 through 40 of 105
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Working PaperEarnings 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.View Full Paper PDF
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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 PaperRe-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.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 PaperWhy the Economics Profession Must Actively Participate in the Privacy Protection Debate
March 2019
Working Paper Number:
CES-19-09
When Google or the U.S. Census Bureau publish detailed statistics on browsing habits or neighborhood characteristics, some privacy is lost for everybody while supplying public information. To date, economists have not focused on the privacy loss inherent in data publication. In their stead, these issues have been advanced almost exclusively by computer scientists who are primarily interested in technical problems associated with protecting privacy. Economists should join the discussion, first, to determine where to balance privacy protection against data quality; a social choice problem. Furthermore, economists must ensure new privacy models preserve the validity of public data for economic research.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 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 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
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Working PaperAn Economic Analysis of Privacy Protection and Statistical Accuracy as Social Choices
August 2018
Working Paper Number:
CES-18-35
Statistical agencies face a dual mandate to publish accurate statistics while protecting respondent privacy. Increasing privacy protection requires decreased accuracy. Recognizing this as a resource allocation problem, we propose an economic solution: operate where the marginal cost of increasing privacy equals the marginal benefit. Our model of production, from computer science, assumes data are published using an efficient differentially private algorithm. Optimal choice weighs the demand for accurate statistics against the demand for privacy. Examples from U.S. statistical programs show how our framework can guide decision-making. Further progress requires a better understanding of willingness-to-pay for privacy and statistical accuracy.View Full Paper PDF
