02181cas a2200241 a 4500 AALejournalIMF016037 230101c9999 xx r poo 0 0eng d 5.00 USD 9781513519265 1018-5941 BD-DhAAL BD-DhAAL Shibata, Ippei. Labor Market Dynamics : A Hidden Markov Approach / Ippei Shibata. Washington, D.C. : International Monetary Fund, 2019. 1 online resource (71 pages) IMF Working Papers <strong>Off-Campus Access:</strong> No User ID or Password Required <strong>On-Campus Access:</strong> No User ID or Password Required Electronic access restricted to authorized BRAC University faculty, staff and students This paper proposes a hidden state Markov model (HMM) that incorporates workers' unobserved labor market attachment into the analysis of labor market dynamics. Unlike previous literature, which typically assumes that a worker's observed labor force status follows a first-order Markov process, the proposed HMM allows workers with the same labor force status to have different history-dependent transition probabilities. I show that the estimated HMM generates labor market transition probabilities that match those observed in the data, while the first-order Markov model (FOM) and its many-state extensions cannot. Even compared with the extended FOM, the HMM improves the fit of the empirical transition probabilities by a factor of 30. I apply the HMM to (1) calculate the long-run consequences of separation from stable employment, (2) study evolutions of employment stability across different demographic groups over the past several decades, (3) compare the dynamics of labor market flows during the Great Recession to those during the 1981 recession, and (4) highlight the importance of looking beyond distributions of current labor force status. Mode of access: Internet IMF Working Papers; Working Paper ; No. 2019/282 Full text available on IMF http://elibrary.imf.org/view/journals/001/2019/282/001.2019.issue-282-en.xml IMF e-Library