We present an exercise where we identify optimal income tax rules according to various social welfare criteria. Empirical applications of optimal taxation theory have typically adopted analytical expressions for the optimal taxes and then imputed numerical values to their parameters by using calibration procedures or previous econometric estimates. Besides the restrictiveness of the assumptions needed to obtain analytical solutions to the optimal taxation problem, a shortcoming of that procedure is the possible inconsistency between the theoretical assumptions and the assumptions implicit in the estimates used for calibrating the theoretical model. In this paper we follow a different procedure, based on a computational approach to the optimal taxation problem. To this end, we estimate a microeconometric model with 78 parameters that capture heterogeneity in consumption-leisure preferences for singles and couples as well as in job opportunities across individuals based on detailed Norwegian household data for 1994. The estimated model is used to simulate the labour supply choices made by single individuals and couples under different tax rules. We then identify optimal taxes – within a class of 10-parameter piecewise-linear rules – by iteratively running the model until a given social welfare function attains its maximum under the constraint of keeping constant the total net tax revenue. We explore a variety of social welfare functions with differing degree of inequality aversion. All the social welfare functions imply monotonically increasing marginal tax rates and a negative marginal tax rate on very low incomes. When compared with the current (1994) tax systems, the optimal rules imply a lower average tax rate. Moreover, all the optimal rules imply – with respect to the current rule – lower marginal rates on low and/or average income levels and higher marginal rates on very high income levels.

Using a Microeconometric Model of Household Labour Supply to Design Optimal Income Taxes

COLOMBINO, Ugo
2013

Abstract

We present an exercise where we identify optimal income tax rules according to various social welfare criteria. Empirical applications of optimal taxation theory have typically adopted analytical expressions for the optimal taxes and then imputed numerical values to their parameters by using calibration procedures or previous econometric estimates. Besides the restrictiveness of the assumptions needed to obtain analytical solutions to the optimal taxation problem, a shortcoming of that procedure is the possible inconsistency between the theoretical assumptions and the assumptions implicit in the estimates used for calibrating the theoretical model. In this paper we follow a different procedure, based on a computational approach to the optimal taxation problem. To this end, we estimate a microeconometric model with 78 parameters that capture heterogeneity in consumption-leisure preferences for singles and couples as well as in job opportunities across individuals based on detailed Norwegian household data for 1994. The estimated model is used to simulate the labour supply choices made by single individuals and couples under different tax rules. We then identify optimal taxes – within a class of 10-parameter piecewise-linear rules – by iteratively running the model until a given social welfare function attains its maximum under the constraint of keeping constant the total net tax revenue. We explore a variety of social welfare functions with differing degree of inequality aversion. All the social welfare functions imply monotonically increasing marginal tax rates and a negative marginal tax rate on very low incomes. When compared with the current (1994) tax systems, the optimal rules imply a lower average tax rate. Moreover, all the optimal rules imply – with respect to the current rule – lower marginal rates on low and/or average income levels and higher marginal rates on very high income levels.
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449
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Optimal taxation; Microsimulation; Random Utility Model; Labour supply.
Aaberge R.; Colombino U.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2318/92560
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