A comparison of different data-driven procedures to determine the bunching window Vincent Dekker and Karsten Schweikert
By: Dekker, Vincent
.
Contributor(s): Schweikert, Karsten.
Material type: 
ArticlePublisher: 2021Subject(s): IMPUESTOS | RENTA | MODELOS DE SIMULACIÓN
In:
Public Finance Review v. 49, n. 2, March 2021, p. 262-293Summary: In this article, we compare three data-driven procedures to determine the bunching window in a Monte Carlo simulation of taxable income. Following the standard approach in the empirical bunching literature, we fit a flexible polynomial model to a simulated income distribution, excluding data in a range around a prespecified kink. First, we propose to implement methods for the estimation of structural breaks to determine a bunching regime around the kink. A second procedure is based on Cook’s distances aiming to identify outlier observations. Finally, we apply the iterative counterfactual procedure proposed by Bosch, Dekker, and Strohmaier which evaluates polynomial counterfactual models for all possible bunching windows.
| Item type | Current location | Home library | Call number | Status | Date due | Barcode |
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In this article, we compare three data-driven procedures to determine the bunching window in a Monte Carlo simulation of taxable income. Following the standard approach in the empirical bunching literature, we fit a flexible polynomial model to a simulated income distribution, excluding data in a range around a prespecified kink. First, we propose to implement methods for the estimation of structural breaks to determine a bunching regime around the kink. A second procedure is based on Cook’s distances aiming to identify outlier observations. Finally, we apply the iterative counterfactual procedure proposed by Bosch, Dekker, and Strohmaier which evaluates polynomial counterfactual models for all possible bunching windows.
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