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Estimation Of Censored Panel‐Data Models With Slope Heterogeneity

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  • Jason Abrevaya
  • Shu Shen

Abstract

SUMMARY This paper considers estimation of censored panel‐data models with individual‐specific slope heterogeneity. The slope heterogeneity may be random (random slopes model) or related to covariates (correlated random slopes model). Maximum likelihood and censored least‐absolute deviations estimators are proposed for both models. The estimators are simple to implement and, in the case of maximum likelihood, lead to straightforward estimation of partial effects. The rescaled bootstrap suggested by Andrews (Econometrica 2000; 68 : 399–405) is used to deal with the possibility of variance parameters being equal to zero. The methodology is applied to an empirical study of Dutch household portfolio choice, where the outcome variable (portfolio share in safe assets) has corner solutions at zero and one. As predicted by economic theory, there is strong evidence of correlated random slopes for the age profiles, indicating a heterogeneous age profile of portfolio adjustment that varies significantly with other household characteristics. Copyright © 2013 John Wiley & Sons, Ltd.

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  • Jason Abrevaya & Shu Shen, 2014. "Estimation Of Censored Panel‐Data Models With Slope Heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(4), pages 523-548, June.
    • Handle: RePEc:wly:japmet:v:29:y:2014:i:4:p:523-548
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    1. Ayala, Diana & Nedeljkovic, Milan & Saborowski, Christian, 2017. "What slice of the pie? The corporate bond market boom in emerging economies," Journal of Financial Stability, Elsevier, vol. 30(C), pages 16-35.
    2. Yang, Chao & Lee, Lung-fei & Qu, Xi, 2018. "Tobit models with social interactions: Complete vs incomplete information," Regional Science and Urban Economics, Elsevier, vol. 73(C), pages 30-50.
    3. Daniel Buncic, 2019. "Identification and Estimation Issues in Exponential Smooth Transition Autoregressive Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(3), pages 667-685, June.
    4. repec:zbw:bofitp:2016_008 is not listed on IDEAS
    5. Ketz, Philipp, 2018. "Subvector inference when the true parameter vector may be near or at the boundary," Journal of Econometrics, Elsevier, vol. 207(2), pages 285-306.
    6. Wang, Wuyi & Su, Liangjun, 2021. "Identifying latent group structures in nonlinear panels," Journal of Econometrics, Elsevier, vol. 220(2), pages 272-295.
    7. Ayala, Diana & Nedeljkovic, Milan & Saborowski, Christian, 2016. "What slice of the pie? The corporate bond market boom in emerging economies," BOFIT Discussion Papers 8/2016, Bank of Finland Institute for Emerging Economies (BOFIT).
    8. Muhammad Basir Paly, 2019. "Calving Interval of Productive PC to Increase Cattle Population Growth: A Case Study At South Sulawesi, Indonesia," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 67(5), pages 1325-1333.
    9. Welsch, David M. & Zimmer, David M., 2016. "The dynamic relationship between school size and academic performance: An investigation of elementary schools in Wisconsin," Research in Economics, Elsevier, vol. 70(1), pages 158-169.
    10. Jiahang He & Toshiyuki Yamamoto & Tomio Miwa & Takayuki Morikawa, 2020. "Hazard Duration Model with Panel Data for Daily Car Travel Distance: A Toyota City Case Study," Sustainability, MDPI, vol. 12(16), pages 1-13, August.

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