• International Journal of Highway Engineering
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• v.15 no.2
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• pp.169-181
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• 2013

PURPOSES : This study is to suggest the Influence of road capital to industry and productivity growth in South Korea. METHODS : Based on the literature review, The relevant policy questions addressed in this report are : cost reduction and Scale elasticities of road, effect of road capital stock on demand for labor, capital and materials, marginal effect of road, industry TFP growth decomposition. RESULTS : The marginal benefits of the road capital at the industry level were calculated using the estimated cost elasticities. Demand for the road capital services varies across industries as do the marginal effects. The marginal benefits are positive for the principal industries. This suggests that for these industries the existing stock of road capital may be under supplied. The contribution of road capital to TFP growth is positive in principal industries. The main contribution of road capital is in the manufacturing industries ; the magnitudes of contribution varies among industries. These results indicate that growth in exogenous demand is most important contributor to TFP growth. CONCLUSIONS : The road capital have a significant effect on employment, private capital and demand for materials inputs in all industries. At a given level of output, an increase in road capital lead to variety to demand for all inputs in all industries.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.1
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• pp.241-248
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• 2019

The purpose of this study is to investigate empirical evidences of productivity of life insurance institutions in Malaysia. Therefore, this study attempts to explore the productivity of the life insurance institutions in Malaysia. The overall findings show that the total factor productivity (TFP) has progressed by 2.5% per year during the study period from 2012 to 2016 in the Malaysian insurance industry. However, TFP change has declined from 2012 to 2015 and observed a negative growth in 2015-16 (3.3%). The highest productivity progress was documented during 2012-13 at a rate of 11.7% while the minimum productivity progress was during 2014-15 (only 0.2%). The results also indicate that the decomposition of TFP found that overall progress could mainly be attributed to technological change (TC). However, technical efficiency change (TEC) and pure technical efficiency change (PTE) have negative impact on TFP. The findings also show that most of the insurance companies have a steady growth. Therefore, this study will contribute new insights for the policy makers and insurance institutions to take appropriate steps in developing relevant policies for increasing productivity of insurance institutions in Malaysia.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.315-320
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• 2013

The aim of this study is to compare efficiency and Total Factor Productivity(TFP) between Korean and Japanese construction firms in Korea and Japan over the period of 2005-2011. The results of this study are as follows. Efficiency scores of Korean construction firms are 0.797, and Japanese construction firms are 0.921. Second, annual total factor productivity growth of Korean construction firms is 0.5% and technical progress do much for TFP decrease. However Japanese construction firms marked annual increasing of 2.5% of TFP. Third, technical progress contributed in TFP increase of construction firms in Korea. Korean construction firms, however, relatively lagged behind Japanese construction firms in technical progress. Therefore, Korean construction firms need strategies to achieve technical advances including adopting new technology or process innovation to maintain competitiveness, survive, and develop in the future competition with Japan.

• Journal of Technology Innovation
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• v.5 no.1
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• pp.15-43
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• 1997

This paper investigates empirically the relationship between various business portfolio properties (particularly technological properties) and chaebol's performance using data on the 50largest chaebols in Korea. In addition to the traditional indexes to measure diversification such as entropy index, we calculated inter-industry technological similarity using R'||'&'||'D expenditure data by industry and 1990 Input-output Table in korea, and obtained chaebol-level technological relatedness and internal transaction proportion from chaebols' business profile, inter-inustry technological similarity and 1990 input-output table. We applied factor analysis on 13 business portfolio property indexes and showed that they could be grouped into 3 dimensions. diversification scope, inter-business relatedness and degree of vertical integration. In this paper, using 50 largest chaebols' financial data (1989-1994), we analyzed empirically the effect of business portfolio properties on ROS(Return On Sales) which is conventional index for firm performance and on TFP(Total Factor Productivity) growth which is a pure measure of firm performance. To utilize the advantage of panel data, FEM(Fixed Effect Model) and REM(Random Effect Model) were used. The empirical result shows that the entropy index as a measurement of inter-business relatedness in not significant but technological relatedness index is significant. OLS estimates on pooled data were considerably different from FEM or REM estimates on panel data. By introducing interaction effect among the three variables for business portfolio properties, we obtained three findings. First, only VI(Vertical integration) has a significant positive correlation with ROS. Second, when using TFP growth as an dependent variable, both TR(Technological Relatedness) and VI are significant and positively related to the dependent variable. Third, the interaction term between TR and VI is significant and negatively affects TFP growth, meaning that TR and VI are substitutes. These results suggest strategic directions on restructuring business portfolio. As VI is increased, chaebols will get more profit. A higher level of either TR or VI will increase TFP growth rate, but increase in both TR and VI will have a negative effect on TFP growth. To summarize, certain business portfolio properties such as VI and TR can be considered "resources" themselves since they can affect profit rate and productivity growth. VI and TR have a synergy effect of change in profit rate and productivity growth. VI increases ROS and productivity growth, while TR increases productivity growth representing a technological synergy effect.t.

• KDI Journal of Economic Policy
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• v.36 no.2
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• pp.137-174
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• 2014

This paper examines whether the TFP growth of the Korean economy slowed down in 2000s based on growth accounting, focusing on how sensitive the results are to the particular aspects of the growth accounting method. There has been no consensus on this issue as the previous studies have provided very diverse results due to the differences in the details of the growth accounting method. Main results of this paper are as follows. First, it is how to calculate the labor income of the self-employed that has the most significant impacts on the estimated TFP growth. Measuring capital stock also matters. Second, the TFP growth of the Korean economy appears to be sustained in 2000s when the extreme assumptions on the labor income of the self-employed are excluded and capital stock is measured by the most frequently-adopted method in the previous studies. For more reliable estimation of the TFP growth, further studies on measuring the labor income of the self-employed are needed.

• International Area Studies Review
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• v.13 no.1
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• pp.123-143
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• 2009

This paper investigates the determinants of total factor productivity(TFP) growth in Korean logistics industry such as market share, ownership structure, age of firm, firm size and debt ratio. Using financial data on individual firms in Korean logistics industry, we first estimate firm-level TFP growth rate and then, regress the estimated TFP growth rate on individual firms market power and structural characteristics. Our empirical results show that logistics firms market share is negatively correlated with their TFP growth rate. Also, we find that older or larger firms are more likely to have higher TFP growth rate.

• Journal of Korea Technology Innovation Society
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• v.6 no.3
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• pp.328-344
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• 2003

This paper is aimed at analyzing the effect of Information Technology (IT) investment on the output growth and Total Factor Productivity (TFP) of Korean stock industry. Data on 24 stock firms for the eleven years (1991-2001) are used for the analysis. It is identified that there are both direct and indirect impacts of IT investment of the Korean stock industry on output growth. The total effect on output growth is 1.34 percentage point per year, which divided into a direct effect of investment in IT on the output growth is 1.97 and an indirect effect on the TFP is -0.63 percentage points per year. Results show that IT investment cannot contribute to increased stock industry productivity. Therefore, the Korean stock industry has not benefited from increased investment on IT in increasing productivity, implying the so-called productivity paradox has existed during the period.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.761-762
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• 2009

이 논문에서는 점진적 마이닝 기법을 사용하여 대용량 전력 사용량 데이터로부터 빈발 패턴들을 찾아내고, 빈발 패턴들을 기반으로 하여 분류 작업을 효과적으로 완성하는데 목적을 두고 있다. 이를 위하여 본 논문에서는 TFP-tree를 기반으로 하는 점진적 빈발 패턴 마이닝 기법 및 분류 알고리즘에 대해서 설명한다.

• Proceedings of the Technology Innovation Conference
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• 1996.12a
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• pp.265-295
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• 1996

This paper investigates empirically the relationship between various business portfolio properties (particularly technological properties) and chaebol′s performance using data on the 50 largest chaebols in Korea. In addition to the traditional indexes to measure diversification such as entropy index we calculated inter-industry technological similarity using R&D expenditure data by industry and 1990 Input-output Table in Korea, and obtained chaebol-level technological relatedness and internal transaction proportion from chaebols′business profile, inter-industry technological similarity and 1990 input-output table. We applied factor analysis on 13 business portfolio property indexes and showed that they could be grouped into 3 dimensions, diversification scope, inter-business relatedness and degree of vertical integration. In this paper, using 50 largest chaebols′financial data (1989-1994), we analyzed empirically the effect of business portfolio properties on ROS (Return On Sales) which is conventional index for firm performance and on TFP(Total Factor Productivity) growth which is a pure measure of firm performance. To utilize the advantage of panel data, FEM(Fixed Effect Model) and REM(Random Effect Model) were used. The empirical result shows that the entropy index as a measurement of inter-business relatedness is not significant but technological relatedness index is significant. OLS estimates on pooled data were considerably different from FEM or REM estimates on panel data. By introducing interaction effect among the three variables for business portfolio properties, we obtained three findings. First, only VI (Vertical integration) has a significant positive correlation with ROS. Second, when using TFP growth as an dependent variable, both TR(Technological Relatedness) and f[ are significant and positively related to the deepened variable. Third, the interaction term between TR and VI is significant and negatively affects TFP growth, meaning that TR and VI are substitutes. These results suggest strategic directions on restructuring business portfolio. As VI is increased, chaebols will get more profit. A higher level of either TR or W will increase TFP growth rate. but increase in both TR and VI will have a negative effect on TFP growth. To summarize, certain business portfolio properties such as VI and TR can be considered "resources" themselves since they can affect profit rate and productivity growth. VI and TR have a synergy effect of change in profit rate and productivity growth. VI increases ROS and productivity growth, while TR increases productivity growth representing a technological synergy effect.

• Asian-Australasian Journal of Animal Sciences
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• v.27 no.10
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• pp.1387-1393
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• 2014

This study aimed to estimate genetic correlation between carcass grading and retail productivity traits and to estimate the correlated response on retail productivity traits through selection for carcass grading traits in order to assess the efficacy of indirect selection. Genetic parameters were estimated with the data from 4240 Hanwoo steers using mixed models, and phenotypes included carcass weight (CWT), back fat thickness (BFT), eye muscle area (EMA), marbling (MAR), and estimated lean yield percentage (ELP) as the carcass grading traits, and weight and portion of retail cuts (RCW and RCP), trimmed fats (TFW and TFP) and trimmed bones (TBW and TBP) as the lean productivity traits. The CWT had positive genetic correlations with RCW (0.95) and TFW (0.73), but its genetic correlation with RCP was negligible (0.02). The BFT was negatively correlated with RCP (-0.63), but positively correlated with TFW and TFP (0.77 and 0.70). Genetic correlations of MAR with TFW and TFP were low. Among the carcass grading traits, only EMA was positively correlated with both RCW (0.60) and RCP (0.72). The EMA had a relatively strong negative genetic correlation with TFW (-0.64). The genetic correlation coefficients of ELP with RCP, TFW, and TFP were 0.76, -0.90, and -0.82, respectively. These correlation coefficients suggested that the ELP and EMA might be favorable traits in regulating lean productivity of carcass.