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Noritaka Kudoh and Hiroaki Miyamoto
 
''Time aggregation and unemployment volatility''
( 2023, Vol. 43 No.2 )
 
 
This paper explores the importance of time aggregation for labor market fluctuations. Instead of correcting time aggregation bias in the data, we develop a simple search-matching model in which some individuals lose and find a job within a period to artificially generate the bias. The magnitude of time aggregation bias is highly procyclical. An increase in the degree of time aggregation bias is associated with a significantly lower unemployment volatility.
 
 
Keywords: worker flows, time aggregation bias, unemployment volatility.
JEL: J6 - Mobility, Unemployment, and Vacancies: General
E3 - Prices, Business Fluctuations, and Cycles: General (includes Measurement and Data)
 
Manuscript Received : Feb 27 2023 Manuscript Accepted : Jun 30 2023

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