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A spatial latent class model

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  • Lee, Jiyon

Abstract

This paper applies the latent class approach to underlying spatial dynamic models. Spatial weights are assumed to be time-varying, although the class membership of each unit is fixed over time. The class-specific parameters and class memberships are estimated with EM algorithm. The performance of the proposed model with a finite sample is examined using Monte Carlo simulation.

Suggested Citation

  • Lee, Jiyon, 2018. "A spatial latent class model," Economics Letters, Elsevier, vol. 162(C), pages 62-68.
    • Handle: RePEc:eee:ecolet:v:162:y:2018:i:c:p:62-68
    DOI: 10.1016/j.econlet.2017.10.004
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    1. Andrew Clark & Fabrice Etilé & Fabien Postel-Vinay & Claudia Senik & Karine Van der Straeten, 2005. "Heterogeneity in Reported Well-Being: Evidence from Twelve European Countries," Economic Journal, Royal Economic Society, vol. 115(502), pages 118-132, March.
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    3. Kelejian, Harry H. & Piras, Gianfranco, 2014. "Estimation of spatial models with endogenous weighting matrices, and an application to a demand model for cigarettes," Regional Science and Urban Economics, Elsevier, vol. 46(C), pages 140-149.
    4. Case, Anne C, 1991. "Spatial Patterns in Household Demand," Econometrica, Econometric Society, vol. 59(4), pages 953-965, July.
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    6. Xi Qu & Xiaoliang Wang & Lung‐fei Lee, 2016. "Instrumental variable estimation of a spatial dynamic panel model with endogenous spatial weights when T is small," Econometrics Journal, Royal Economic Society, vol. 19(3), pages 261-290, October.
    7. Lung-Fei Lee, 2004. "Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Autoregressive Models," Econometrica, Econometric Society, vol. 72(6), pages 1899-1925, November.
    8. Bryan S. Graham, 2017. "An Econometric Model of Network Formation With Degree Heterogeneity," Econometrica, Econometric Society, vol. 85, pages 1033-1063, July.
    9. Lung-fei Lee & Jihai Yu, 2012. "QML Estimation of Spatial Dynamic Panel Data Models with Time Varying Spatial Weights Matrices," Spatial Economic Analysis, Taylor & Francis Journals, vol. 7(1), pages 31-74, March.
    10. Qu, Xi & Lee, Lung-fei & Yu, Jihai, 2017. "QML estimation of spatial dynamic panel data models with endogenous time varying spatial weights matrices," Journal of Econometrics, Elsevier, vol. 197(2), pages 173-201.
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    Cited by:

    1. Alberto Gude & Inmaculada Álvarez & Luis Orea, 2018. "Heterogeneous spillovers among Spanish provinces: a generalized spatial stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 50(3), pages 155-173, December.
    2. Manuel A. Zambrano-Monserrate & Maria Alejandra Ruano & Carlos A. Silva & Ronald Campoverde & Christian Rosero & Daniel A. Sanchez-Loor, 2023. "Dynamism of the housing rental market in Guayaquil, Ecuador: an empirical analysis," Empirical Economics, Springer, vol. 64(2), pages 747-764, February.
    3. Luc Anselin & Pedro Amaral, 2024. "Endogenous spatial regimes," Journal of Geographical Systems, Springer, vol. 26(2), pages 209-234, April.

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    More about this item

    Keywords

    Spatial dynamic model; Latent class model; Time-varying spatial weights; EM algorithm;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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