지방정부관료제의 효율성 평가: 보건소를 중심으로
Evaluating the Efficiency of Local Government Bureaucracy: With Application to Public Health Centers
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This study measured the efficiency of the fourteen public health centers in Jeonbuk Province using the output-oriented data envelopment analysis(DEA) in order to analyze inefficiencies in local government bureaucracy. This paper measured efficiency scores adjusted for environmental variables such as population, area by local government, and the type of location, compared those scores with traditional efficiency scores not corrected for them, suggested scale efficiency scores, and conducted returns to scale(RTS) analysis. The method of controlling for environmental variables is that efficiency scores from the traditional DEA model based on traditional inputs and outputs are regressed against a set of environmental variables using Tobit regression and then statistically significant environmental variables are incorporated into the standard DEA model along with traditional inputs and outputs. Technical efficiency scores and pure technical efficiency scores adjusted for environmental variables increased by about 21% and 15%, respectively, as compared with those scores not controlled for them. The implications of this article are as follows. First, the efficiency of local government bureaucracy such as public health centers needs to be analyzed by adjusting for environmental variables. Second, inefficient public health centers need to seek to operate at optimal scale by analyzing their scale efficiency and returns to scale.
Abstract
This study measured the efficiency of the fourteen public health centers in Jeonbuk Province using the output-oriented data envelopment analysis(DEA) in order to analyze inefficiencies in local government bureaucracy. This paper measured efficiency scores adjusted for environmental variables such as population, area by local government, and the type of location, compared those scores with traditional efficiency scores not corrected for them, suggested scale efficiency scores, and conducted returns to scale(RTS) analysis. The method of controlling for environmental variables is that efficiency scores from the traditional DEA model based on traditional inputs and outputs are regressed against a set of environmental variables using Tobit regression and then statistically significant environmental variables are incorporated into the standard DEA model along with traditional inputs and outputs. Technical efficiency scores and pure technical efficiency scores adjusted for environmental variables increased by about 21% and 15%, respectively, as compared with those scores not controlled for them. The implications of this article are as follows. First, the efficiency of local government bureaucracy such as public health centers needs to be analyzed by adjusting for environmental variables. Second, inefficient public health centers need to seek to operate at optimal scale by analyzing their scale efficiency and returns to scale.
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