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Robust tests for heteroskedasticity in the one-way error components model

Author

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  • Gabriel Montes-Rojas

    (Department of Economics - UCL - University College of London [London])

  • Walter Sosa-Escudero

    (Department of Economics - UMSA - Universidad Mayor de San Andrés)

Abstract

This paper constructs tests for heteroskedasticity in one-way error components models, in line with Baltagi, Bresson and Pirotte (Journal of Econometrics, 134, 2006). Our tests have two additional robustness properties. First, standard tests for heteroskedasticity in the individual component are shown to be negatively affected by heteroskedasticity in the remainder component. We derive modified tests that are insensitive to heteroskedasticity in the component not being checked, and hence help identify the source of heteroskedasticity. Second, Gaussian based LM tests are shown to reject too often in the presence of heavy-tailed (e.g. t-Student) distributions. By using a conditional moments framework, we derive distribution-free tests that are robust to non-normalities. Our tests are computationally convenient since they are based on simple artificial regressions after pooled OLS estimation.

Suggested Citation

  • Gabriel Montes-Rojas & Walter Sosa-Escudero, 2010. "Robust tests for heteroskedasticity in the one-way error components model," Post-Print hal-00768191, HAL.
    • Handle: RePEc:hal:journl:hal-00768191
    DOI: 10.1016/j.jeconom.2010.09.010
    Note: View the original document on HAL open archive server: https://hal.science/hal-00768191
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    References listed on IDEAS

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    Cited by:

    1. Richard Kouamé Moussa, 2019. "Heteroskedasticity in One-Way Error Component Probit Models," Econometrics, MDPI, vol. 7(3), pages 1-22, August.
    2. Javier Alejo & Antonio Galvao & Gabriel Montes-Rojas & Walter Sosa-Escudero, 2015. "Tests for normality in linear panel-data models," Stata Journal, StataCorp LP, vol. 15(3), pages 822-832, September.
    3. Packalen, Mikko & Wirjanto, Tony S., 2012. "Inference about clustering and parametric assumptions in covariance matrix estimation," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 1-14, January.
    4. Lili Yue & Jianhong Shi & Jingxuan Luo & Jinguan Lin, 2023. "A Parametric Bootstrap Approach for a One-Way Error Component Regression Model with Measurement Errors," Mathematics, MDPI, vol. 11(19), pages 1-13, October.
    5. Wu, Jianhong & Li, Guodong, 2014. "Moment-based tests for individual and time effects in panel data models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 569-581.
    6. Juhl, Ted & Sosa-Escudero, Walter, 2014. "Testing for heteroskedasticity in fixed effects models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 484-494.
    7. Galvao, Antonio F. & Montes-Rojas, Gabriel & Sosa-Escudero, Walter & Wang, Liang, 2013. "Tests for skewness and kurtosis in the one-way error component model," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 35-52.
    8. Andreas Rathgeber & David Rudolph & Stefan Stöckl, 2015. "Pricing anomaly at the first sight: same borrower in different currencies faces different credit spreads—an explanation by means of a quanto option," Review of Derivatives Research, Springer, vol. 18(2), pages 107-143, July.
    9. Alejo, Javier & Montes-Rojas, Gabriel & Sosa-Escudero, Walter, 2018. "Testing for serial correlation in hierarchical linear models," Journal of Multivariate Analysis, Elsevier, vol. 165(C), pages 101-116.

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    More about this item

    Keywords

    C12; C23; Error components; Heteroskedasticity; Testing;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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