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A Unified Method for Dynamic and Cross‐Sectional Heterogeneity: Introducing Hidden Markov Panel Models

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  • Jong Hee Park

Abstract

Conventional statistical methods for panel data are based on the assumption that unobserved heterogeneity is time constant. Despite the central importance of this assumption for panel data methods, few studies have developed statistical methods for testing this assumption and modeling time‐varying unobserved heterogeneity. In this article, I introduce a formal test to check the assumption of time‐constant unobserved heterogeneity using Bayesian model comparison. Then, I present two panel data methods that account for time‐varying unobserved heterogeneity in the context of the random‐effects model and the fixed‐effects model, respectively. I illustrate the utility of the introduced methods using both simulated data and examples drawn from two important debates in the political economy literature: (1) the identification of shifting relationships between income inequality and economic development in capitalist countries and (2) the effects of the GATT/WTO on bilateral trade volumes.

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  • Jong Hee Park, 2012. "A Unified Method for Dynamic and Cross‐Sectional Heterogeneity: Introducing Hidden Markov Panel Models," American Journal of Political Science, John Wiley & Sons, vol. 56(4), pages 1040-1054, October.
    • Handle: RePEc:wly:amposc:v:56:y:2012:i:4:p:1040-1054
    DOI: 10.1111/j.1540-5907.2012.00590.x
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    Cited by:

    1. Linus Holtermann & Christian Hundt, 2018. "Hierarchically structured determinants and phase related patterns of economic resilience. An empirical case study for European regions," Working Papers on Innovation and Space 2018-02, Philipps University Marburg, Department of Geography.
    2. Xiong, Yingge & Tobias, Justin L. & Mannering, Fred L., 2014. "The analysis of vehicle crash injury-severity data: A Markov switching approach with road-segment heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 109-128.
    3. Li Donni, Paolo & Marino, Maria & Welzel, Christian, 2021. "How important is culture to understand political protest?," World Development, Elsevier, vol. 148(C).
    4. Therese Anders, 2020. "Territorial control in civil wars: Theory and measurement using machine learning," Journal of Peace Research, Peace Research Institute Oslo, vol. 57(6), pages 701-714, November.

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