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Identification and Estimation of Production Function with Unobserved Heterogeneity

Paul Schrimpf, Michio Suzuki () and Hiroyuki Kasahara ()
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Paul Schrimpf: The University of British Columbia

No 924, 2015 Meeting Papers from Society for Economic Dynamics

Abstract: This paper examines non-parametric identifiability of production function when production functions are heterogenous across firms beyond Hicks-neutral technology terms. Using a finite mixture specification to capture permanent unobserved heterogeneity in production technology, we show that production function for each unobserved type is non-parametrically identified under regularity conditions. We also propose an estimation procedure for production function with random coefficients based on EM algorithm. We estimate a random coefficients production function using the panel data of Japanese publicly-traded manufacturing firms and compare it with the estimate of production function with fixed coefficients estimated by the method of Gandhi, Navarro, and Rivers (2013).

New Economics Papers: this item is included in nep-ecm and nep-eff
Date: 2015
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