Labor productivity convergence in the Kansas farm sector: a three-stage procedure using data envelopment analysis and semiparametric regression analysis

This paper employs a three stage procedure to investigate labor productivity growth and convergence in the Kansas farm sector for a balanced panel of 564 farms for the period 1993-2007. In the first stage, Data Envelopment Analysis is used to compute technical efficiency indices. In the second stage...

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Bibliographic Details
Published in:	Journal of productivity analysis 2012-08, Vol.38 (1), p.63-79
Main Authors:	Mugera, Amin W., Langemeier, Michael R., Featherstone, Allen M.
Format:	Article
Language:	eng
Subjects:	Accounting/Auditing Agricultural production Agriculture Crop economics Crops Data envelopment analysis Decomposition Econometrics Economic growth Economics Economics and Finance Employee efficiency Farms Labor productivity Linear programming Microeconomics Operations Research/Decision Theory Parametric models Productive efficiency Productivity Productivity growth Productivity measurement Regression analysis Studies Technological change
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Summary:	This paper employs a three stage procedure to investigate labor productivity growth and convergence in the Kansas farm sector for a balanced panel of 564 farms for the period 1993-2007. In the first stage, Data Envelopment Analysis is used to compute technical efficiency indices. In the second stage, labor productivity growth is decomposed into components attributable to efficiency change, technical change, and factor intensity. The third stage employs both parametric and semiparametric regression analyses to investigate convergence in labor productivity growth and the contribution of each of the three components to the convergence process. Factor intensity and efficiency change are found to be sources of labor productivity convergence while technical change is found to be a source of divergence. Policies that encourage investment in capital goods may help to mitigate disparities in labor productivity across the farm sector.
ISSN:	0895-562X 1573-0441