• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.319-325
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• 2001

In this note, we propose a simple fuzzy linear regression model for fuzzy input-output data based on Tanaka's approach. Then an LP-based method to derived the satisfying solution of the decision making is developed.

• Journal of Korea Trade
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• v.27 no.5
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• pp.113-136
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• 2023

Purpose - Global production chains and their impacts on economic growth have drawn extensive attention from researchers. Close relationships among global production chains, export and economic growth have been illuminated, as evidenced by the fast and stable economic growth of East Asian economies. These economies perform various roles within global production chains using offshoring, in which the impact of import on domestic gross output is as strong as that of export. The impact of import on economic growth would depend on whether imported inputs substitute or complement domestic inputs production, which is likely to vary according to individual countries' functions within global production chains. The economic growth of concerned countries would also be diverse. However, little attention has been paid to the impact brought by imports compared to its significance. Design/methodology - The principal methodology used in this paper is structural decomposition analysis (SDA), widely chosen to elucidate the impact of various factors on domestic gross output using input-output tables. This paper extracts trade data of six Asian economies from the World Input-Output Database (WIOD) 2016 release that covers 43 countries for the period 2000-2014. The extracted data is then categorised into 37 sectors. First, this paper calculates the Feenstra-Hanson Offshoring Index (OSI) of each country. It then applies SDA to measure the changes in each economy's gross output, export, import input coefficients, and domestic input coefficients. Finally, after taking the first difference from pooled time-series data, it estimates the correlations between imported input coefficients and OSI using the ordinary least square (OLS) method. Findings - The main findings of this paper can be summarised as follows. Firstly, all six countries have increasingly engaged in global production chains, as evidenced by the growing size of OSI. Secondly, there are negative correlations in five countries except Japan, with sectoral differences. Thirdly, changes in import input coefficients are not negative in all six countries, indicating that offshoring does not necessarily substitute for domestic inputs production but does complement it and, therefore, fosters their economic growth. This is observed in China, Indonesia, Korea and Taiwan. Offshoring has led to an increase in the use of imported inputs, which has, in turn, stimulated domestic inputs production in these countries. Originality/value - While existing studies focus on the role of export in evaluating the impact of participating global production chains, this paper explicitly examines the unexplored impact of import on domestic gross output by considering both the substitution and the complementary effect, using the WIOD. The findings of this paper suggest that Asian economies have achieved fast and stable economic growth not only through successful export management but also through effective import management within global production chains. This paper recommends that the Korean government and enterprises carefully choose offshoring strategies to minimise disruption to domestic production chains or foster them.

• Journal of the Korean Regional Science Association
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• v.15 no.3
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• pp.1-13
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• 1999

Since the 1990's, the most important environmental issue on the earth is characterized by "global worming problem". The United Nations Framework Convention on Climate Change (UNFCCC) plays an significant role to solve this problem on a worldwide scale. The main purpose of this paper is to analyse the impact of $CO_2$ reduction on the Daegu regional economy through 1995 regional input-output coefficients derived from the 1995 national input coefficients table by using non-survey method. The sectoral impacts on output, income, and employment were computed under the decline-unequalized assumption in final demand influenced by $CO_2$ reduction. This article has six main sections. Section 1 is an introduction to this paper. Section 2 explains briefly the derivation method of the regional technical coefficients. Section 3 describes the model building through input-output multipliers. In section 4 regional data on output, income, employment and final demand are computed to estimate the regional impacts. Section 5 deals with impact analysis on the Daegu economy. Section 6 contains a brief summary and concludintg remarks. The research findings of this study can be summarized as follows. In 1995, under the assumption of 10% decrease on an average in final demand sectors, the economy of the region studied decreased \3600 billion of output, ￦1114 billion of income, and 49919 man-years of employment. The percent ratios of each value to the total showed 9.4%, 9.7%, and 9.2%, respectively. The dominant sectors associated with impact analysis within the region are chemicals and chemical products, paper, printing and publishing, and textiles and leather, etc; nevertheless, the least dominant sector is non-metallic mineral products. products.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.445-449
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• 2005

Yen et al. [Fuzzy Sets and Systems 106 (1999) 167-177] calculated the fuzzy membership function for the output to find the non-symmetric triangular fuzzy number coefficients of a linear regression model for all given input-output data sets. In this note, we show that the result they obtained in their paper is invalid.

• Journal of the Korean association of regional geographers
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• v.8 no.4
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• pp.480-491
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• 2002

The purpose of this study is to construct interregional input-output table for multi-regions using non-survey methods. Despite of wide use of interregional input-output table, there have been continuing debates with respect to it's accuracy mostly when it is constructed by non-survey method. The best ideal one is to construct through real survey, while we must pay much time and cost. With regard to this concern, Hulu and Hewings developed a step by step method for the estimation of interregional input coefficients for the Indonesian economy which might be a challenge for the limitation of location quotient method, for which Round pointed out earlier. A five regions interregional input-output table for Korea is developed in this study by expanding Location Quotient method. Some development was made, however, according to the degree of collection of data and the assumption in treating the interregional flows. Finally, a comparison was made for the accuracy of input coefficients between the real surveyed and derived ones.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.5
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• pp.120-125
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• 2007

Burning the fossil fuel in the thermal power plants causes green house gas emission. Monitoring of CO2 emission of the thermal power plants is growing more important because the amount produced by them is more than 20 percent of national total emission. This paper proposes a method to calculate the amount of the CO2 emission w.r.t. generator[MW] output using the input-output coefficients of the thermal power plants. The power flow computation together with the CO2 emission calculation are demonstrated in a sample power system.

• Journal of the Korea Safety Management & Science
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• v.14 no.4
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• pp.313-319
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• 2012

SW industry is important at entire industry in Korea and also one of new growth engine industry. This paper deals with the economic effect of SW industry through input-output analysis. We reconstruct the SW industry by extracting and combining SW portion from other industries of the inter-industry relation table. We obtain that production inducement coefficients, value added inducement coefficients, employment inducement coefficients, and job position inducement coefficients are higher than average inducement coefficients of all industries.

• Journal of Distribution Science
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• v.14 no.10
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• pp.21-27
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• 2016

Purpose - This study analyzes economic relations and mutual influence in the global equipment manufacturing industry (EMI) and China's influence. Research design, data, and methodology - Data were collected from the World Input-Output Database (WIOT), looking at 16 countries. The sample time period was 2002-2011. Influence and motivation coefficients were calculated. Results - 1) China's EMI showed a very strong influence coefficient, even surpassing world industrial powers like Japan, the USA, Germany, and Korea. 2) As for influence on added-value, China's EMI motivation coefficient was ranked third in 2011, which meant it had a negligible effect on added-value. 3) From 2002 to 2011, both the influence and motivation coefficients of China's EMI rose. Conclusions - China's EMI has strong influence and motivation coefficients. It has a significant impact on the world EMI, especially on the total output of the global EMI. Additionally, during 2002 to 2011, the ranking of China's EMI motivation coefficient improved year over year, and its economic efficiency obviously improved. By 2011, China's EMI's international influence was second only to the US and Japan.

• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.449-455
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• 2004

Support vector machine (SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate interval regression models for crisp input-output data. The proposed method is based on quadratic loss SVM, which implements quadratic programming approach giving more diverse spread coefficients than a linear programming one. The proposed algorithm here is model-free method in the sense that we do not have to assume the underlying model function. Experimental result is then presented which indicate the performance of this algorithm.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.194-203
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• 2008

Iterative learning control (ILC) is a simple and effective method for the control of systems that perform the same task repetitively. ILC algorithm uses the repetitiveness of the task to track the desired trajectory. In this paper, we propose a PID (proportional plus integral and derivative) type ILC update law for control discrete-time single input single-output (SISO) linear time-invariant (LTI) systems, performing repetitive tasks. In this approach, the input of controlled system in current cycle is modified by applying the PID strategy on the error achieved between the system output and the desired trajectory in a last previous iteration. The convergence of the presented scheme is analyzed and its convergence condition is obtained in terms of the PID coefficients. An optimal design method is proposed to determine the PID coefficients. It is also shown that under some given conditions, this optimal iterative learning controller can guarantee the monotonic convergence. An illustrative example is given to demonstrate the effectiveness of the proposed technique.