ESRI Discussion Paper Series No.368 Identification and Estimation of Production Function with Unobserved Heterogeneity

Hiroyuki Kasahara
University of British Columbia
Paul Schrimpf
University of British Columbia
Michio Suzuki
Tohoku University


This paper examines the non-parametric identifiability of production function when production functions are heterogeneous across firms beyond Hicks-neutral technology terms. Using a finite mixture specification to capture unobserved heterogeneity in production technology, we show that the production function for each unobserved type is non-parametrically identified under regularity conditions. We estimate a random coefficients production function using the panel data of Japanese manufacturing plants and compare it with the estimate of the production function with fixed coefficients estimated by the method of Gandhi, Navarro, and Rivers (2020). Our estimates for random coefficients production function suggest that there exists substantial heterogeneity in production function coefficients beyond Hicks neutral term across firms within narrowly defined industries.

Structure of the whole text(PDF-Format 1 File)

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    • 1 Introduction
    • 2 Evidence for unobserved heterogeneity
    • 3 The Model
    • 4 Nonparametric identication
    • 5 Estimation of production function with random co-effcients
    • 6 Empirical Application