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Labor Market Dynamics: A Hidden Markov Approach
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.
Are Labor Market Indicators Telling the Truth? Role of Measurement Error in the U.S. Current Population Survey
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.
Political Economy of Reform in China
This book contains four research papers that clarify the issues behind China's rapid economic growth, using empirical studies. The book makes two distinctive points. First, it elucidates the unique economic development of China from a different perspective than the "state capitalism" theory, based on empirical research on the Chinese economy and politics with the cooperation of leading scholars. Second, the book paints a total picture of China through an interdisciplinary analysis of economics, politics, and history. Each chapter focuses on the political–economic context of China's rapid economic growth on the following basis. First, the authors analyze whether there is a clear difference ...
The Archaeology of Japan
The first book-length introduction to the Yayoi and Kofun periods of Japan (c.600 BC-AD 700).
Recent Trends in Analysis of Images, Social Networks and Texts
This book constitutes revised selected papers of the 9th International Conference on Analysis of Images, Social Networks and Texts, AIST 2020, held in Moscow, Russia, in october 2020. Due to the COVID-19 pandemic the conference was held online. The 14 full papers, 9 short papers and 4 poster papers were carefully reviewed and selected from 108 qualified submissions. The papers are organized in topical sections on natural language processing; computer vision; social network analysis; data analysis and machine learning; theoretical machine learning and optimization; process mining; posters.
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