Estimation of Technical Change and Price Elasticities: A Categorical Time-varying Coefficient Approach

Guohua Feng (), Jiti Gao and Xiaohui Zhang ()

No 2/16, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: In this paper we outline new procedure for estimating technical change and price elasticities. Specifically, we propose a categorical time-varying coefficient translog cost function, where each coefficient is expressed as a nonparametric function of a categorical time variable, thereby allowing each time period to have its own set of coefficients. Our application to U.S. electricity firms reveals that compared with the traditional time trend representation of technical change that has remained a cornerstone of the productivity literature, this model offers two advantages: (1) it is capable of producing estimates of productivity growth that closely track those obtained using the Tornqvist approximation to the Divisia index; and (2) it can solve a well-known problem commonly referred to as "the problem of trending elasticities", i.e. estimated price elasticities show little temporal variation even when in fact they do.

Keywords: semiparametric method; categorical time-varying coefficient model; technical change and productivity (search for similar items in EconPapers)
JEL-codes: C33 D24 (search for similar items in EconPapers)
Pages: 38
Date: 2016
New Economics Papers: this item is included in nep-eff
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Journal Article: Estimation of technical change and price elasticities: a categorical time–varying coefficient approach (2018)
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