A Comparison of Different Data-driven Procedures to Determine the Bunching Window. (March 2021)

• Record Type: Journal Article
• Authors: Dekker, Vincent; Schweikert, Karsten
• Is Part Of: Public finance review. Volume 49:Number 2(2021)
• Page Start: 262
• Page End: 293
• Publication Date: 2021-03
• Subjects: bunching window -- Cook's distances -- Monte Carlo simulation -- structural breaks -- taxable income; Finance, Public -- Periodicals; 336.005
• DOI: 10.1177/1091142121993055
• Languages: English
• ISSNs: 1091-1421

Abstract

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. While our simulation results show that all three procedures are fairly accurate, the iterative counterfactual procedure is the preferred method to detect the bunching window when no prior information about the true size of the bunching window is available.