Dynamic Bunching Estimation with Panel Data Benjamin M. Marx* August 2018 Abstract An increasingly common technique for studying behavioral elasticities uses bunching estimation of the excess mass in a distribution around a price or policy threshold. This paper shows how serial dependence of the choice variable and extensive-margin responses may bias these estimates. It then proposes new bunching designs that take greater advantage of panel data to avoid these biases and estimate new parameters. Standard methods over-reject in simulations using household income data and over-estimate bunching in an application with charities. Designs exploiting panel data provide unbiased bunching estimates, improved heterogeneity analysis, and the ability to estimate extensive-margin responses and long-run effects. JEL: H00, B40, C23, D04. * Department of Economics, University of Illinois at Urbana-Champaign, 214 David Kinley Hall, 1407 W. Gregory, Urbana, IL 61801. Correspondence should be sent to
[email protected]. I am especially grateful to Bruce Kogut, Wojciech Kopczuk, Robert McMillan, Brendan O’Flaherty, Bernard Salanié, and Miguel Urquiola for invaluable advice and discussions. I also thank Raj Chetty, Julie Berry Cullen, Jonathan Dingel, Francois Gerard, Jessie Handbury, Todd Kumler, Ilyana Kuziemko, Corinne Low, David Munroe, Giovanni Paci, Abigail Payne, Petra Persson, Jonah Rockoff, Maya Rossin-Slater, Ugo Troiano, Lesley Turner, Eric Verhoogen, Reed Walker, Caroline Weber, and seminar participants at meetings of the International Institute for Public Finance, the Office of the U.S. Department of the Treasury Office of Tax Analysis, the National Tax Association Annual Conference, the Association for Public Economic Theory, the Midwestern Economics Association, and the University of Illinois and other universities.