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Robust Statistical Inference In Panel Data Including A Practical Application In The Migration Analysis

Author

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  • Tatiana Medková

    (University of Economics, Prague)

Abstract

The need for robust statistical inference is well-documented even in the elementary case of a regression with a randomly sampled cross section. The usual ordinary least square standard errors are generally biased under the presence of heteroskedasticity; a phenomenon that seems to be a rule rather than an exception in applied anaylsis. The article describes several methods to deal with the biased standard errors grouping them in two categories: sandwich variance estimators and multi-way clustering. Moreover, the empirical application is included. An analysis of migration in European countries using the theory of gravity model is done applying several standard errors correction methods.

Suggested Citation

  • Tatiana Medková, 2019. "Robust Statistical Inference In Panel Data Including A Practical Application In The Migration Analysis," Proceedings of International Academic Conferences 9912282, International Institute of Social and Economic Sciences.
    • Handle: RePEc:sek:iacpro:9912282
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    File URL: https://iises.net/proceedings/international-academic-conference-barcelona/table-of-content/detail?cid=99&iid=039&rid=12282
    File Function: First version, 2019
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    More about this item

    Keywords

    migration; robust; standard errors; heteroskedasticity; panel data;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • F22 - International Economics - - International Factor Movements and International Business - - - International Migration

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