A Bayesian Time-Varying Coefficient Model for Cobb–Douglas Production Function

Jongwoo Choi, Seongil Jo () and Jaeoh Kim ()
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Jongwoo Choi: University of Connecticut
Seongil Jo: Inha University
Jaeoh Kim: Inha University

Computational Economics, 2025, vol. 65, issue 3, No 11, 1429-1455

Abstract: Abstract This paper proposes a Bayesian varying coefficient model to estimate parameters exhibiting time-dependence in the Cobb–Douglas (CD) production function. We expand upon the classical CD production function by incorporating time-varying properties to enable more sophisticated modeling. We utilize a flexible and efficient Bayesian approach-based computational algorithm for statistical inference in the constrained parameter space, where the sum of model elasticities must be less than 1. The proposed model is applied to four real datasets from macroeconomics, as well as various social science issues broadly covered by the CD production function. The real data applications demonstrate the effectiveness of the proposed model in estimating underlying time-varying effects for parameters in the CD production function.

Keywords: Bayesian inference; Cobb Douglas production function; Constraint regression model; Hamiltonian Monte Carlo; Time-varying coefficient model (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10614-024-10598-1

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