How unobservable productivity biases the value of a statistical life

How unobservable productivity biases the valu ...
Thomas J. Kniesner, Thomas J. ...
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Last edited by MARC Bot
January 21, 2025 | History

How unobservable productivity biases the value of a statistical life

"A prominent theoretical controversy in the compensating differentials literature concerns unobservable individual productivity. Competing models yield opposite predictions depending on whether the unobservable productivity is safety-related skill or productivity generally. Using five panel waves and several new measures of worker fatality risks, first-difference estimates imply that omitting individual heterogeneity leads to overestimates of the value of statistical life, consistent with the latent safety-related skill interpretation. Risk measures with less measurement error raise the value of statistical life, the net effect being that estimates from the static model range from $5.3 million to $6.7 million, with dynamic model estimates somewhat higher"--National Bureau of Economic Research web site.

Publish Date
Publisher
Harvard Law School
Language
English
Pages
23

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Edition Availability
Cover of: How unobservable productivity biases the value of a statistical life
How unobservable productivity biases the value of a statistical life
2005, National Bureau of Economic Research
Electronic resource in English
Cover of: How unobservable productivity biases the value of a statistical life

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Book Details


Edition Notes

"09/2005."

Includes bibliographical references (p. 22-23).

Discussion papers published since September 1997 are available for downloading free of charge from the Olin Center web site.

Published in
Cambridge, MA
Series
Discussion paper -- no. 524, Discussion paper (John M. Olin Center for Law, Economics, and Business) -- no. 524

Classifications

Library of Congress
KF209 .D57 no. 524

The Physical Object

Pagination
23 p.
Number of pages
23

Edition Identifiers

Open Library
OL57496469M
OCLC/WorldCat
70898943

Work Identifiers

Work ID
OL23987835W

Source records

Harvard University record

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January 21, 2025 Created by MARC Bot Imported from Harvard University record