Nonlinear Budget Set Regressions for the Random Utility Model
Sören Blomquist,
Anil Kumar,
Che-Yuan Liang and
Whitney Newey
No 31194, NBER Working Papers from National Bureau of Economic Research, Inc
Abstract:
This paper is about the nonparametric regression of a choice variable on a nonlinear budget set under utility maximization with general heterogeneity, i.e. in the random utility model (RUM). We show that utility maximization and convex budget sets make this regression three dimensional with a more parsimonious specification than previously derived. We show that nonconvexities in the budget set will have little effect on these results in important cases. We characterize all the restrictions of utility maximization on the budget set regression and show how to check these restrictions in applications. We formulate budget set effects that can be identified by this regression and give automatic debiased machine learners of these effects. We consider use of control functions to allow for endogeneity. Throughout we take as the main example the effect of taxes on taxable income including accounting for productivity growth. In an application to Swedish data we find the taxable income elasticity of a change in the slope of each segment to be .52, that the regression satisfies the restrictions of utility maximization at the values chosen for over 95% of observations, and that a productivity growth rate we estimate is close to other estimates.
JEL-codes: C14 C24 H31 J22 (search for similar items in EconPapers)
Date: 2023-04
New Economics Papers: this item is included in nep-des, nep-lma, nep-pbe and nep-upt
Note: LS PE
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Working Paper: Nonlinear Budget Set Regressions for the Random Utility Model (2022) 
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