Document Type

Working Paper

Publication Date

2021

College/Unit

Chambers College of Business and Economics

Document Number

21-01

Department/Program/Center

Economics

Abstract

We propose a varying coefficient regression model for panel data that controls for both latent heterogeneities in cross-sectional units and unobserved common shocks over time. The model allows different smoothing variables to enter through either a stand-alone function or a coefficient function. Without requiring a normalization of the fixed effects, we propose a two-step estimator. First, we estimate the varying coefficients with the pilot series-based estimators, eliminating fixed effects though differencing. Second, we perform a one-step kernel backfitting to improve the estimation efficiency. We demonstrate through Monte-Carlo simulations that our estimators are computationally efficient and perform well relative to a profile-based kernel estimator.

Included in

Economics Commons

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