SHERP

A Parametric Test for the Distinction between Unemployed and Out of the Labor Force Statuses

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Authors
Ahn, SeungChan; Low, Stuart
Issue Date
2007
Publisher
Seoul Journal of Economics
Citation
Seoul Journal of Economics 20 (No. 1 2007): 59-92
Keywords
Bivariate probitMisclassificationUnemploymentOut of labor force
Abstract
Whether or not to empirically consider two (employed versus
not employed) or three (employed, unemployed, and out-of-laborforce)
classifications in labor supply studies is a controversial
issue. We develop a generalized censored probit likelihood
function that nests both possibilities. A novelty of this likelihood
function is that it allows researchers to test which representation
of the labor market is appropriate as well as to estimate the
degree to which classification errors may cloud inferences. Our
empirical results demonstrate that classifying the three groups is
useful to identify individuals’ labor force and employment
decisions separately. However, failure to incorporate classification
ambiguities may result in unemployed rates that are understated
and out-of-labor-force rates that are overstated.
ISSN
1225-0279
Language
English
URI
http://hdl.handle.net/10371/1375
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College of Social Sciences (사회과학대학)Institute of Economics Research (경제연구소)Seoul Journal of EconomicsSeoul Journal of Economics vol.20(1) (Spring 2007)
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