A New Panel Data Treatment for Heterogeneity in Time Trends

Our paper introduces a new estimation method for arbitrary temporal heterogeneityin panel data models. The paper provides a semiparametric method for estimatinggeneral patterns of cross-sectional specific time trends. The methods proposed in thepaper are related to principal component analysis and estimate the time-varying trendeffects using a small number of common functions calculated from the data. An importantapplication for the new estimator is in the estimation of time-varying technicalefficiency considered in the stochastic frontier literature. Finite sample performance ofthe estimators is examined via Monte Carlo simulations. We apply our methods to theanalysis of productivity trends in the U.S. banking industry.