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Bayesian Hierarchical Estimation and Impact Analysis of Generalized Production Functions

Received: 19 March 2021     Accepted: 30 March 2021     Published: 12 April 2021
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Abstract

Bayesian model is constructed to estimate the missing data of capital stock, and the impact of three industrial structures on the tertiary industry is discussed. The results show that: the maximum MC error with missing data on capital stock estimated by Bayesian is 0.4963, the maximum MC error of production function estimated by Bayesian stratation is 0.3276, the standard deviation is 0.0890 and the accuracy is high; from 1993 to 2018, the sum of capital output elasticity and labor output elasticity in the tertiary industry in Yunnan Province was greater than 1, and the scale compensation was increasing; the level of technological progress, the growth rate of all factors, the elasticity of capital output and the elasticity of labor output were all close to stable, and the ranges of changes were 0.2714-0.3252, -0.0680-0.0390, 0.5615-0.5858 and 0.4522-0.4784, respectively; the elasticity of capital output was greater than that of labor force output, and the tertiary industry in Yunnan Province was more dependent on the elasticity of capital output.

Published in American Journal of Theoretical and Applied Statistics (Volume 10, Issue 2)
DOI 10.11648/j.ajtas.20211002.14
Page(s) 122-128
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Generalized Production Function, Capital Stock, Non-random Missing, Gibbs Sampling, Impact Analysis

References
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[3] Feng liying, Feng ruiqin, Li haixia. The production efficiency measurement of Inner Mongolia service industry Based on Cobb-Douglas production function [J]. Journal of Inner Mongolia University of Finance and Economics, 2015, 2 (13): 9-14.
[4] Wang jun, Liu lang-juan. Estimation of Elasticity of Substitution in CES function of major Industries in Shanghai [J]. Shanghai Journal of Economics, 2012, (5): 106-112.
[5] Zeng zhao-fa, Mi xian-hua. The Estimation and empirical of extended C-D production function based on Bayesian panel model [J], Statistic & Iformation Forum, 2014, 7 (29): 29-34.
[6] Shi lei, Xiang qi-feng, Cheng fei. Multilevel model and its application in Economics [M]. China science press, 2013.
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[11] Lunn D, Jackson Christopher, Best Nicky, et al. A practical introduction to bayesian Analysis [M]. Chapman & Hall/CRC Press, 2013.
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Cite This Article
  • APA Style

    Xinping Yang, Wei Zheng, Yunyuan Yang, Yanmei Li. (2021). Bayesian Hierarchical Estimation and Impact Analysis of Generalized Production Functions. American Journal of Theoretical and Applied Statistics, 10(2), 122-128. https://doi.org/10.11648/j.ajtas.20211002.14

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    ACS Style

    Xinping Yang; Wei Zheng; Yunyuan Yang; Yanmei Li. Bayesian Hierarchical Estimation and Impact Analysis of Generalized Production Functions. Am. J. Theor. Appl. Stat. 2021, 10(2), 122-128. doi: 10.11648/j.ajtas.20211002.14

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    AMA Style

    Xinping Yang, Wei Zheng, Yunyuan Yang, Yanmei Li. Bayesian Hierarchical Estimation and Impact Analysis of Generalized Production Functions. Am J Theor Appl Stat. 2021;10(2):122-128. doi: 10.11648/j.ajtas.20211002.14

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  • @article{10.11648/j.ajtas.20211002.14,
      author = {Xinping Yang and Wei Zheng and Yunyuan Yang and Yanmei Li},
      title = {Bayesian Hierarchical Estimation and Impact Analysis of Generalized Production Functions},
      journal = {American Journal of Theoretical and Applied Statistics},
      volume = {10},
      number = {2},
      pages = {122-128},
      doi = {10.11648/j.ajtas.20211002.14},
      url = {https://doi.org/10.11648/j.ajtas.20211002.14},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20211002.14},
      abstract = {Bayesian model is constructed to estimate the missing data of capital stock, and the impact of three industrial structures on the tertiary industry is discussed. The results show that: the maximum MC error with missing data on capital stock estimated by Bayesian is 0.4963, the maximum MC error of production function estimated by Bayesian stratation is 0.3276, the standard deviation is 0.0890 and the accuracy is high; from 1993 to 2018, the sum of capital output elasticity and labor output elasticity in the tertiary industry in Yunnan Province was greater than 1, and the scale compensation was increasing; the level of technological progress, the growth rate of all factors, the elasticity of capital output and the elasticity of labor output were all close to stable, and the ranges of changes were 0.2714-0.3252, -0.0680-0.0390, 0.5615-0.5858 and 0.4522-0.4784, respectively; the elasticity of capital output was greater than that of labor force output, and the tertiary industry in Yunnan Province was more dependent on the elasticity of capital output.},
     year = {2021}
    }
    

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  • TY  - JOUR
    T1  - Bayesian Hierarchical Estimation and Impact Analysis of Generalized Production Functions
    AU  - Xinping Yang
    AU  - Wei Zheng
    AU  - Yunyuan Yang
    AU  - Yanmei Li
    Y1  - 2021/04/12
    PY  - 2021
    N1  - https://doi.org/10.11648/j.ajtas.20211002.14
    DO  - 10.11648/j.ajtas.20211002.14
    T2  - American Journal of Theoretical and Applied Statistics
    JF  - American Journal of Theoretical and Applied Statistics
    JO  - American Journal of Theoretical and Applied Statistics
    SP  - 122
    EP  - 128
    PB  - Science Publishing Group
    SN  - 2326-9006
    UR  - https://doi.org/10.11648/j.ajtas.20211002.14
    AB  - Bayesian model is constructed to estimate the missing data of capital stock, and the impact of three industrial structures on the tertiary industry is discussed. The results show that: the maximum MC error with missing data on capital stock estimated by Bayesian is 0.4963, the maximum MC error of production function estimated by Bayesian stratation is 0.3276, the standard deviation is 0.0890 and the accuracy is high; from 1993 to 2018, the sum of capital output elasticity and labor output elasticity in the tertiary industry in Yunnan Province was greater than 1, and the scale compensation was increasing; the level of technological progress, the growth rate of all factors, the elasticity of capital output and the elasticity of labor output were all close to stable, and the ranges of changes were 0.2714-0.3252, -0.0680-0.0390, 0.5615-0.5858 and 0.4522-0.4784, respectively; the elasticity of capital output was greater than that of labor force output, and the tertiary industry in Yunnan Province was more dependent on the elasticity of capital output.
    VL  - 10
    IS  - 2
    ER  - 

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Author Information
  • School of Mathematics and Statistics, Chuxiong Normal University, Chuxiong, China

  • School of Mathematics and Statistics, Chuxiong Normal University, Chuxiong, China

  • School of Geography and Tourist Management, Chuxiong Normal University, Chuxiong, China

  • School of Mathematics and Statistics, Chuxiong Normal University, Chuxiong, China

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