Econometric Estimation of Production Function with Applications

Awoingo Adonijah Maxwell, I. D. Essi
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引用次数: 2

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.
生产函数的计量估计及其应用
研究了蒙特卡罗方法在生产函数参数估计中的应用。采用普通最小二乘法对未知参数进行估计。数据生成过程采用蒙特卡罗模拟方法。对生成的数据进行了带有乘法误差项的Cobb-Douglas生产模型拟合。从表1.1到1.3中,对于样本量为20、40和80的情况,结果的均方误差(MSE)分别为0.007678、0.001972和0.001253。我们的发现表明,均方误差(MSE)值随输入变量幂的和而变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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