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Estimation of Random Components and Prediction in One and Two-Way Error Component Regression Models

Author

Listed:
  • Subhash C. Sharma

    (Southern Illinois University Carbondale)

  • Anil K. Bera

    (University of Illinois at Urbana-Champaign)

Abstract

Since one of the main objectives of panel data analysis is to uncover individual and/or time effects, the estimation of these random components is very important. Estimation of individual and time components will also help in predicting the future values of the dependent variable, which has received some attention in the literature. Following the stochastic frontier literature, our contention is that estimation of these random components is akin to the estimation of “firm-specific” efficiency. Thus, considering the conditional distributions of the random components and using the conditional mean and variance, we provide both point and interval estimates of the individual and time effects in the one and two-way error component models. Using these standard errors one can also test the significance of random components. Equations for predictions are also provided for these models. Finally, all our theoretical results are illustrated with an empirical application.

Suggested Citation

  • Subhash C. Sharma & Anil K. Bera, 2021. "Estimation of Random Components and Prediction in One and Two-Way Error Component Regression Models," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 419-441, December.
    • Handle: RePEc:spr:jqecon:v:19:y:2021:i:1:d:10.1007_s40953-021-00278-4
    DOI: 10.1007/s40953-021-00278-4
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    References listed on IDEAS

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    1. Anil Bera & Subhash Sharma, 1999. "Estimating Production Uncertainty in Stochastic Frontier Production Function Models," Journal of Productivity Analysis, Springer, vol. 12(3), pages 187-210, November.
    2. Badi H. Baltagi & Bernard Fingleton & Alain Pirotte, 2014. "Estimating and Forecasting with a Dynamic Spatial Panel Data Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(1), pages 112-138, February.
    3. Bera, Anil K. & Doğan, Osman & Taşpınar, Süleyman & Leiluo, Yufan, 2019. "Robust LM tests for spatial dynamic panel data models," Regional Science and Urban Economics, Elsevier, vol. 76(C), pages 47-66.
    4. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    5. Jushan Bai, 2013. "Fixed‐Effects Dynamic Panel Models, a Factor Analytical Method," Econometrica, Econometric Society, vol. 81(1), pages 285-314, January.
    6. Swamy, P A V B & Arora, S S, 1972. "The Exact Finite Sample Properties of the Estimators of Coefficients in the Error Components Regression Models," Econometrica, Econometric Society, vol. 40(2), pages 261-275, March.
    7. Baltagi, Badi H. & Griffin, James M., 1983. "Gasoline demand in the OECD : An application of pooling and testing procedures," European Economic Review, Elsevier, vol. 22(2), pages 117-137, July.
    8. Amemiya, Takeshi, 1971. "The Estimation of the Variances in a Variance-Components Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 12(1), pages 1-13, February.
    9. Wallace, T D & Hussain, Ashiq, 1969. "The Use of Error Components Models in Combining Cross Section with Time Series Data," Econometrica, Econometric Society, vol. 37(1), pages 55-72, January.
    10. Fuller, Wayne A. & Battese, George E., 1974. "Estimation of linear models with crossed-error structure," Journal of Econometrics, Elsevier, vol. 2(1), pages 67-78, May.
    11. Taub, Allan J., 1979. "Prediction in the context of the variance-components model," Journal of Econometrics, Elsevier, vol. 10(1), pages 103-107, April.
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    Cited by:

    1. Yong Bao & Aman Ullah, 2021. "The Special Issue in Honor of Anirudh Lal Nagar: An Introduction," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 1-8, December.

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    More about this item

    Keywords

    Panel data models; One-way random components model; Two-way random components model; Estimation; Prediction;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • 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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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