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

Rafael Solis and K.C. Tseng
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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

International Journal of Business and Economics, 2018, vol. 17, issue 2, 95-112

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.

Keywords: hierarchical clustering; Cobb-Douglas production function; macroeconomics (search for similar items in EconPapers)
JEL-codes: C31 C38 C51 C82 D24 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)

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