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RANDOMIZED SAFETY INSPECTIONS AND RISK EXPOSURE ON THE JOB: QUASI-EXPERIMENTAL ESTIMATES OF THE VALUE OF A STATISTICAL LIFE

January 2014

Working Paper Number:

CES-14-05

Abstract

Compensating wages for workplace fatality and accident risks are used to infer the value of a statistical life (VSL), which in turn is used to assess the benefits of human health and safety regulations. The estimation of these wage differentials, however, has been plagued by measurement error and omitted variables. This paper employs the first quasi-experimental design within a labor market setting to overcome such limitations in the ex-tant literature. Specifically, randomly assigned, exogenous federal safety inspections are used to instrument for plant-level risks and combined with confidential U.S. Census data on manufacturing employment to estimate the VSL using a difference-in-differences framework. The VSL is estimated to be between $2 and $4 million ($2011), suggesting prior studies may substantially overstate the value workers place on safety, and therefore, the benefits of health and safety regulations.

Document Tags and Keywords

Keywords Keywords are automatically generated using KeyBERT, a powerful and innovative keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant keywords.

By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the text, highlighting the most significant topics and trends. This approach not only enhances searchability but provides connections that go beyond potentially domain-specific author-defined keywords.
:
economist, econometric, endogeneity, payroll, estimator, regulation, workforce, occupation, labor statistics, layoff, risk, compensation, mortality

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:
Annual Survey of Manufactures, Bureau of Labor Statistics, Service Annual Survey, Ordinary Least Squares, Permanent Plant Number, University of Maryland, Supreme Court, Environmental Protection Agency, Chicago Census Research Data Center, Survey of Income and Program Participation, Cornell University, Special Sworn Status

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