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"Identification and Estimation of Production Function with Unobserved Heterogeneity" by Dr. Hiroyuki Kasahara
Publishing Date: 17/04/2018 (Last Update: 17/04/2018)
The University of British Columbia
|Date||Monday, 30 April 2018|
|Time||4:30pm - 6pm|
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 unobserved heterogeneity in production technology, we shows that 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 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). 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 industry.