Econometric Estimation of Production Function with Applications

Awoingo Adonijah Maxwell* and Isaac Didi Essi
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Awoingo Adonijah Maxwell*: Department of Mathematics, Faculty of Science, Rivers State University, P. M. B. 5080 Port Harcourt, Nigeria
Isaac Didi Essi: Department of Mathematics, Faculty of Science, Rivers State University, P. M. B. 5080 Port Harcourt, Nigeria

Academic Journal of Applied Mathematical Sciences, 2019, vol. 5, issue 6, 57-61

Abstract: This study focuses on Monte Carlo Methods in parameter estimation of production function. The ordinary least square (OLS) method is used to estimate the unknown parameters. The Monte Carlo simulation methods are used for the data generating process. The Cobb-Douglas production model with multiplicative error term is fitted to the data generated. From tables 1.1 to 1.3, the mean square error (MSE) of ?1 are 0.007678, 0.001972 and 0.001253 respectively for sample sizes 20, 40 and 80. Our finding showed that the mean square error (MSE) value varies with the sum of the powers of the input variables.

Keywords: Cobb-douglas model; Production; Modeling; Parameter estimation; Capital (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:arp:ajoams:2019:p:57-61

DOI: 10.32861/ajams.56.57.61

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