• Environmental and Resource Economics Review
• /
• v.21 no.1
• /
• pp.3-25
• /
• 2012

Generally speaking, firms, faced with a regulatory environment, are likely to use more or less inputs than optimal level due to allocative inefficiency of inputs. This paper, first, tests allocative efficiency of fuel inputs and calculates the divergence between the actual and optimal levels of each fuel input conditional on the optimal level of capital stock in Korean thermal power industry. Then, given that each fuel is efficiently allocated. potential reduction of $CO_2$ is estimated over the period 1987~2008. The null hypothesis of allocative efficiency with respect to all fuels is rejected, indicating that thermal power plants fail to attain cost minimization subject do market prices. Allocative efficiency between each pair of fuels is also tested; efficient uses of fuels relative to each other are all rejected. Empirical results indicate that coal and gas are used more and oil is used less than optimal level. On average, more than 10 million tons of $CO_2$ per year could be reduced by achieving allocative efficiency of fuels.

• Environmental and Resource Economics Review
• /
• v.23 no.3
• /
• pp.453-472
• /
• 2014

Analyzing the effects of carbon emissions trading, which is scheduled to be introduced in Korea in 2015, requires an accurate assessment of $CO_2$ abatement costs by both industries and firms. Firms faced with regulatory constraints are unlikely to minimize their production costs due to rising production costs caused by allocative inefficiency of inputs. The use of a distance function would results in underestimation of $CO_2$ abatement costs, because it fails to capture the allocative distortion costs. Recognizing the disadvantage of the previous approach, first, this paper tests for allocative efficiency of input for the Korean steel industry over the period 1990-2010, then derives the marginal $CO_2$ abatement costs by applying a cost function approach. The hypothesis of allocative efficiency in inputs is rejected and the steel industry pays an annual average cost of 92,000 won in removing an additional ton of $CO_2$ over the sample period.

• Environmental and Resource Economics Review
• /
• v.23 no.1
• /
• pp.43-65
• /
• 2014

In this paper, we test for allocative efficiency of productive inputs including electricity and measure the divergence between the actual and optimal level of electricity for the chemical products, which is a relatively highly electricity-intensive sector in Korean manufacturing industries, by estimating a shadow cost function. Supposing cost minimization subject to market prices was achieved, we derive the price elasticities of demand for each input and simulate the impact of a 10% increase in power rate on its demand and supply price by estimating jointly a cost function with an inverse supply relation. The null hypothesis of allocative efficiency of inputs is rejected over the period 1982-2006. On average, electricity is used more than optimal level by 98% per year. The demand for electricity decreases by 11.4%, and supply price, on average, falls by 0.08%, other things being equal.

• Journal of Korean Society for Quality Management
• /
• v.43 no.4
• /
• pp.533-544
• /
• 2015

Purpose: The purpose of this study is to analyze the cost efficiency of food industry in JeollaNamdo. And this study is focused on the correlation between the economic efficiency of food industry and its cost efficiency, based on the analysis of 372 food companies' data in JeollaNamdo in 2012. Methods: DEA cost minimization is the measurement of the cost efficiency of JeollaNamdo food industry in 2012. In this study, the CCR and BBC models have been employed to analyze the decomposing cost efficiency-technical efficiency, allocative efficiency, and scale efficiency respectively. And the Spearman rank correlation and Wilcoxon signed rank test also have been employed to check the correlation and difference between the ranking orders based on the efficiency scores respectively. Results: For the CCR model, mean cost efficiency was found to be 0.084(0.54 for allocative efficiency and 0.19 for technical efficiency). For the BCC model, mean cost efficiency was found to be 0.252(0.453 for allocative efficiency and 0.564 for technical efficiency). Average scale efficiency was found to be 0.38. In analyzing the results, this study argues that the optimal way to improve cost efficiency is by reducing inputs proportionally and changing their combination. Conclusion: The efficiency scores of the two models show high correlation, whereas, the differences between them are also found to be significant. Hence, it should be cautious to select a suitable model when we do the research.

• Korean Journal of Agricultural Science
• /
• v.48 no.1
• /
• pp.59-71
• /
• 2021

This study investigated the extent to which rice producers from the Ayeyarwaddy Region of Myanmar could improve their productivity if inputs were used efficiently in rice cultivation. To achieve this objective, simple random sampling was used to collect data from 300 rice growers in the study area. Data were analyzed with the translog stochastic frontier approach to understand the production efficiencies. The study further estimated the influencing factors that affect the efficiency levels of rice farmers. The empirical result reveals that the average technical, allocative, and economic efficiencies were at 76.11, 47.85, and 34.15%, respectively. This suggests that there is considerable room for improving rice production by better utilization of the available resources at the current level of technology. This study suggests that strenthening agricultural training programs and adoption of improved rice varieties may reduce overall inefficiencies among rice farmers in Myanmar. Factors like age, household size, education, farming experience, farm size, rice variety, training, and off-farm income have a significant impact on increasing/decreasing farmer's efficiency. Efficiency can be improved by establishing farmer field school programs to increase the scale of operations. The government should encourage young educated people to participate in paddy production and also intervene to reduce input prices and control the quality of seeds.

• Journal of Korean Society of Transportation
• /
• v.21 no.4
• /
• pp.113-132
• /
• 2003

Using nonradial data envelopment analysis(DEA) under assumptions of strong disposability and variable returns scale, this paper annually estimates productive. technical and allocative efficiencies of three publicly-owned rail transit properties which are different in terms of organizational type: Seoul Subway Corporation(SSC, local public corporation), the Seoul Metropolitan Electrified Railways sector (SMESRS) of Korea National Railroad(the national railway operator controlled by the Ministry of Construction and Transportation(MOCT)), and Busan Urban Transit Authority (BUTA, the national authority controlled by MOCT). Using the estimation results of Tobit regression analysis. the paper next computes their true productive, true technical and true allocative efficiencies, which reflect only the impacts of internal factors such as production activity by removing the impacts of external factors such as an organizational type and a track utilization rate. And the paper also computes an organizational efficiency and annually gross efficiencies for each property. The paper then conceptualized that the property produces a single output(car-kilometers) using four inputs(labor, electricity, car & maintenance and track) and uses unbalanced panel data consisted of annual observations on SSC, SMESRS and BUTA. The results obtained from DEA show that, on an average, SSC is the most efficient property on the productive and allocative sides, while SMESRS is the most technically-efficient one. On the other hand. BUTA is the most efficient one on the truly-productive and allocative sides, while SMESRS on the truly-technical side. Another important result is that the differences in true efficiency estimates among the three properties are considerably smaller than those in efficiency estimates. Besides. the most cost-efficient organizational type appears to be a local public corporation represented by SSC, which is also the most grossly-efficient property. These results suggest that a measure to sort out the impacts of external factors on the efficiency of rail transit properties is required to assess fairly it, and that a measure to restructure (establish) an existing(a new) rail transit property into a local public corporation(or authority) is required to improve its cost efficiency.

• Korean Journal of Agricultural Science
• /
• v.12 no.2
• /
• pp.333-340
• /
• 1985

In this paper, we discuss the role of allocative efficiency and X-efficiency in determining resource allocation under the share tenency. Economic efficiency of resource allocation is related to land reform. Classical and neoclassical schools insist that land reform must be achieved for agricultural development by more efficient use of inputs. According to them, there is no incentive for tenants to use inputs until $MVP{\ell}=wage$ under the share tenancy. But "equal efficiency" school's conclusions are different. They conclude that there is no productivity differences between owner cultivation and share tenancy, owing to monopoly power of landlords and/or landlords's transaction costs. Considering X-efficiency, the share tenancy is not as efficient as the owner cultivation. On the other hand, the productivity differences may be reverse, in which landlords cultivate their lands by wage contracts. Land reform--reduction of land rent or redistribution of land--will be benefitable not only for agricultural development, but also for resource allocation in farm management.

• KDI Journal of Economic Policy
• /
• v.12 no.2
• /
• pp.51-79
• /
• 1990

Research on technical efficiency, an important dimension of market performance, had received little attention until recently by most industrial organization empiricists, the reason being that traditional microeconomic theory simply assumed away any form of inefficiency in production. Recently, however, an increasing number of research efforts have been conducted to answer questions such as: To what extent do technical ineffciencies exist in the production activities of firms and plants? What are the factors accounting for the level of inefficiency found and those explaining the interindustry difference in technical inefficiency? Are there any significant international differences in the levels of technical efficiency and, if so, how can we reconcile these results with the observed pattern of international trade, etc? As the first in a series of studies on the technical efficiency of Korea's manufacturing industries, this paper attempts to answer some of these questions. Since the estimation of technical efficiency requires the use of plant-level data for each of the five-digit KSIC industries available from the Census of Manufactures, one may consture the findings of this paper as empirical evidence of technical efficiency in Korea's manufacturing industries at the most disaggregated level. We start by clarifying the relationship among the various concepts of efficiency-allocative effciency, factor-price efficiency, technical efficiency, Leibenstein's X-efficiency, and scale efficiency. It then becomes clear that unless certain ceteris paribus assumptions are satisfied, our estimates of technical inefficiency are in fact related to factor price inefficiency as well. The empirical model employed is, what is called, a stochastic frontier production function which divides the stochastic term into two different components-one with a symmetric distribution for pure white noise and the other for technical inefficiency with an asymmetric distribution. A translog production function is assumed for the functional relationship between inputs and output, and was estimated by the corrected ordinary least squares method. The second and third sample moments of the regression residuals are then used to yield estimates of four different types of measures for technical (in) efficiency. The entire range of manufacturing industries can be divided into two groups, depending on whether or not the distribution of estimated regression residuals allows a successful estimation of technical efficiency. The regression equation employing value added as the dependent variable gives a greater number of "successful" industries than the one using gross output. The correlation among estimates of the different measures of efficiency appears to be high, while the estimates of efficiency based on different regression equations seem almost uncorrelated. Thus, in the subsequent analysis of the determinants of interindustry variations in technical efficiency, the choice of the regression equation in the previous stage will affect the outcome significantly.