2023•European Journal of Law and EconomicsOpen access

Controlling for fixed effects in studies of income underreporting

Odd Erik Nygård, Thor Olav Thoresen

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Abstract

Abstract The expenditure method of Pissarides and Weber (J Public Econ 39(1):17–32, 1989) shows how one backs out measure of income underreporting by the self-employed by using food consumption as trace of true income. In this paper we make a case for using panel data and fixed effects estimation in such analysis, instead of OLS estimation. The main argument is that fixed effects estimation addresses the problem of omitted variable bias in the identification. We demonstrate the use of panel data and fixed effects estimation by using large-scale administrative register data on charitable donations, exploiting that the data can be turned into a panel dataset. The results suggest that the estimation technique matters—fixed effects estimates are smaller than OLS estimates.

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Abstract The expenditure method of Pissarides and Weber (J Public Econ 39(1):17–32, 1989) shows how one backs out measure of income underreporting by the self-employed by using food consumption as trace of true income. In this paper we make a case for using panel data and fixed effects estimation in such analysis, instead of OLS estimation. The main argument is that fixed effects estimation addresses the problem of omitted variable bias in the identification. We demonstrate the use of panel data and fixed effects estimation by using large-scale administrative register data on charitable donations, exploiting that the data can be turned into a panel dataset. The results suggest that the estimation technique matters—fixed effects estimates are smaller than OLS estimates.

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Available abstract

Abstract The expenditure method of Pissarides and Weber (J Public Econ 39(1):17–32, 1989) shows how one backs out measure of income underreporting by the self-employed by using food consumption as trace of true income. In this paper we make a case for using panel data and fixed effects estimation in such analysis, instead of OLS estimation. The main argument is that fixed effects estimation addresses the problem of omitted variable bias in the identification. We demonstrate the use of panel data and fixed effects estimation by using large-scale administrative register data on charitable donations, exploiting that the data can be turned into a panel dataset. The results suggest that the estimation technique matters—fixed effects estimates are smaller than OLS estimates.

Key concepts: Panel data, Fixed effects model, Estimation, Econometrics, Economics, Instrumental variable, Public finance, Random effects model

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