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Linear dynamic panel-data estimation using maximum likelihood and structural equation modeling

Author

Listed:
  • Richard Williams

    (University of Notre Dame)

  • Paul D. Allison

    (University of Pennsylvania)

  • Enrique Moral-Benito

    (Banco de España)

Abstract

Panel data make it possible both to control for unobserved confounders and to include lagged, endogenous regressors. However, trying to do both simulta- neously leads to serious estimation difficulties. In the econometric literature, these problems have been addressed by using lagged instrumental variables together with the generalized method of moments, while in sociology the same problems have been dealt with using maximum likelihood estimation and structural equa- tion modeling. While both approaches have merit, we show that the maximum likelihood–structural equation models method is substantially more efficient than the generalized method of moments method when the normality assumption is met and that the former also suffers less from finite sample biases. We introduce the command xtdpdml, which has syntax similar to other Stata commands for linear dynamic panel-data estimation. xtdpdml greatly simplifies the structural equation model specification process; makes it possible to test and relax many of the constraints that are typically embodied in dynamic panel models; allows one to include time-invariant variables in the model, unlike most related methods; and takes advantage of Stata’s ability to use full-information maximum likelihood for dealing with missing data. The strengths and advantages of xtdpdml are illustrated via examples from both economics and sociology. Copyright 2018 by StataCorp LP.

Suggested Citation

  • Richard Williams & Paul D. Allison & Enrique Moral-Benito, 2018. "Linear dynamic panel-data estimation using maximum likelihood and structural equation modeling," Stata Journal, StataCorp LP, vol. 18(2), pages 293-326, June.
    • Handle: RePEc:tsj:stataj:v:18:y:2018:i:2:p:293-326
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    Cited by:

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    2. Sebastian Kripfganz, 2016. "Quasi–maximum likelihood estimation of linear dynamic short-T panel-data models," Stata Journal, StataCorp LP, vol. 16(4), pages 1013-1038, December.
    3. Joo Hun Han & DuckJung Shin & William G. Castellano, & Alison M. Konrad & Douglas L. Kruse & Joseph R. Blasi, 2020. "Creating Mutual Gains to Leverage a Racially Diverse Workforce: The Effects of Firm-Level Racial Diversity on Financial and Workforce Outcomes Under the Use of Broad-Based Stock Options," Organization Science, INFORMS, vol. 31(6), pages 1515-1537, November.
    4. Matthew Thomas Clement & Nathan W. Pino & Jarrett Blaustein, 2019. "Homicide Rates and the Multiple Dimensions of Urbanization: A Longitudinal, Cross-National Analysis," Sustainability, MDPI, vol. 11(20), pages 1-16, October.
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    6. Shepherd, Debra L., 2022. "Food insecurity, depressive symptoms, and the salience of gendered family roles during the COVID-19 pandemic in South Africa," Social Science & Medicine, Elsevier, vol. 301(C).
    7. Doddy Setiawan & Rayenda Khresna Brahmana & Andi Asrihapsari & Siti Maisaroh, 2021. "Does a Foreign Board Improve Corporate Social Responsibility?," Sustainability, MDPI, vol. 13(20), pages 1-17, October.
    8. Guilherme Correa Petry & Ely José Mattos, 2023. "The Effects of Public Expenditure on Municipal Development: A Dynamic Panel Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 165(2), pages 695-714, January.
    9. Abdullah Al Mamun & Abu Reza Md. Towfiqul Islam & Edris Alam & Subodh Chandra Pal & G. M. Monirul Alam, 2022. "Assessing Riverbank Erosion and Livelihood Resilience Using Traditional Approaches in Northern Bangladesh," Sustainability, MDPI, vol. 14(4), pages 1-16, February.
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    11. Kim, Hoolda & Mitra, Sophie, 2022. "Dynamics of health and labor income in Korea," The Journal of the Economics of Ageing, Elsevier, vol. 21(C).
    12. Stephanie Reitzinger & Astrid Pennerstorfer, 2021. "The size–growth relationship in the social services sector in Austria," Service Business, Springer;Pan-Pacific Business Association, vol. 15(3), pages 445-466, September.
    13. Suale Karimu, 2019. "Structural transformation, openness, and productivity growth in sub-Saharan Africa," WIDER Working Paper Series wp-2019-109, World Institute for Development Economic Research (UNU-WIDER).
    14. Dao, Nguyen Dinh, 2020. "Does the microcredit intervention change the life of the low- and middle-income households in rural Vietnam? Evidence from panel data," World Development Perspectives, Elsevier, vol. 20(C).
    15. Lars Leszczensky & Tobias Wolbring, 2022. "How to Deal With Reverse Causality Using Panel Data? Recommendations for Researchers Based on a Simulation Study," Sociological Methods & Research, , vol. 51(2), pages 837-865, May.
    16. Wu, Hania Fei, 2021. "Social determination, health selection or indirect selection? Examining the causal directions between socioeconomic status and obesity in the Chinese adult population," Social Science & Medicine, Elsevier, vol. 269(C).
    17. Connolly, Eric J. & Schwartz, Joseph A. & Block, Kristina, 2022. "The role of poor sleep on the development of self-control and antisocial behavior from adolescence to adulthood," Journal of Criminal Justice, Elsevier, vol. 82(C).
    18. Fedotenkov, Igor & Idrisov, Georgy, 2021. "A supply-demand model of public sector size," Economic Systems, Elsevier, vol. 45(2).
    19. Mulenga, Brian P. & Ngoma, Hambulo & Nkonde, Chewe, 2021. "Produce to eat or sell: Panel data structural equation modeling of market participation and food dietary diversity in Zambia," Food Policy, Elsevier, vol. 102(C).
    20. Maria Elena Bontempi & Jan Ditzen, 2023. "GMM-lev estimation and individual heterogeneity: Monte Carlo evidence and empirical applications," Papers 2312.00399, arXiv.org, revised Dec 2023.
    21. Krzysztof Beck, 2021. "Capital mobility and the synchronization of business cycles: Evidence from the European Union," Review of International Economics, Wiley Blackwell, vol. 29(4), pages 1065-1079, September.
    22. Hoolda Kim & Sophie Mitra, 2023. "Dynamics of Health and Labor Incomes in Korea," Fordham Economics Discussion Paper Series dp2023-01er:dp2023-01, Fordham University, Department of Economics.

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