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|c 5.00 USD
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|z 9781498300452
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|a 1018-5941
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040 |
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|a BD-DhAAL
|c BD-DhAAL
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|a Shibata, Ippei.
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|a Are Labor Market Indicators Telling the Truth? :
|b Role of Measurement Error in the U.S. Current Population Survey /
|c Ippei Shibata.
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|a Washington, D.C. :
|b International Monetary Fund,
|c 2019.
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|a 1 online resource (40 pages)
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|a IMF Working Papers
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|a <strong>Off-Campus Access:</strong> No User ID or Password Required
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|a <strong>On-Campus Access:</strong> No User ID or Password Required
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|a Electronic access restricted to authorized BRAC University faculty, staff and students
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|a Labor market indicators are critical for policymakers, but measurement error in labor force survey data is known to be substantial. In this paper, I quantify the implications of classification errors in the U.S. Current Population Survey (CPS), in which respondents misreport their true labor force status. Once I correct for measurement error using a latent variable approach, the unemployment rate is on average 0.8 percentage points (ppts) higher than the official unemployment rate, with a maximum of 2.0 ppts higher between 1996 and 2018. This paper further quantifies the contributions to business-cycle fluctuations in the unemployment rate from job separation, job finding, and participation. Correcting for misclassification changes previous studies' results about the contributions of these transition probabilities: job separation accounts for more of the unemployment fluctuations, while participation accounts for fewer. The methodology I propose can be applied to any other labor force survey in which labor force status is observed for three periods.
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|a Mode of access: Internet
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|a IMF Working Papers; Working Paper ;
|v No. 2019/040
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|z Full text available on IMF
|u http://elibrary.imf.org/view/journals/001/2019/040/001.2019.issue-040-en.xml
|z IMF e-Library
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