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Using Hierarchical Cluster Analysis as a Tool to Fit Aggregate Production Functions

Author

Listed:
  • Rafael Solis

    (Department of ISDS Craig School of Business, California State University, Fresno)

  • K.C. Tseng

    (Department of ISDS Craig School of Business, California State University, Fresno)

Abstract

In this study, we discuss the use of clustering algorithms to group countries based on a set of macroeconomic variables and their effect on the estimation of the parameters of a Cobb-Douglas type production function. The findings suggest that the utilization of clustering methodologies could play an important role when grouping of countries may be needed without adversely affecting the meaning of the parameters of the fitted production functions.

Suggested Citation

  • Rafael Solis & K.C. Tseng, 2018. "Using Hierarchical Cluster Analysis as a Tool to Fit Aggregate Production Functions," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 17(2), pages 95-112, September.
    • Handle: RePEc:ijb:journl:v:17:y:2018:i:2:p:95-112
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    References listed on IDEAS

    as
    1. Slottje, Daniel J, 1991. "Measuring the Quality of Life across Countries," The Review of Economics and Statistics, MIT Press, vol. 73(4), pages 684-693, November.
    2. Beckmann, Martin J & Sato, Ryuzo, 1969. "Aggregate Production Functions and Types of Technical Progress: A Statistical Analysis," American Economic Review, American Economic Association, vol. 59(1), pages 88-101, March.
    3. Basu, Susanto & Fernald, John G, 1997. "Returns to Scale in U.S. Production: Estimates and Implications," Journal of Political Economy, University of Chicago Press, vol. 105(2), pages 249-283, April.
    4. Hirschberg, Joseph G. & Maasoumi, Esfandiar & Slottje, Daniel J., 1991. "Cluster analysis for measuring welfare and quality of life across countries," Journal of Econometrics, Elsevier, vol. 50(1-2), pages 131-150, October.
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    Cited by:

    1. Sharif N. Ahkam & Khairul Alom, 2019. "Liquidity, Level of Working Capital Investment, and Performance in an Emerging Economy," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 18(3), pages 307-328, December.

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    More about this item

    Keywords

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    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access

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