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引用次数: 0
摘要
本文提出了一种贝叶斯变化系数模型,用于估计柯布-道格拉斯(CD)生产函数中表现出时间依赖性的参数。我们在经典的 CD 生产函数的基础上,加入了时变特性,以实现更复杂的建模。我们利用基于贝叶斯方法的灵活高效的计算算法,在受限参数空间内进行统计推断,其中模型弹性之和必须小于 1。 我们将提出的模型应用于宏观经济学的四个真实数据集,以及 CD 生产函数广泛涵盖的各种社会科学问题。真实数据的应用证明了所提出的模型在估计 CD 生产函数参数的潜在时变效应方面的有效性。
A Bayesian Time-Varying Coefficient Model for Cobb–Douglas Production Function
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.
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.