• The Journal of Industrial Distribution & Business
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• v.10 no.9
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• pp.53-60
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• 2019

Purpose - The objective of this paper is to discover if there exists a relationship between the economic index and distribution industry index in Korean. Because of the distribution industry boom in the recent years, a lot of interest in the relationship between the economic index and distribution industry index in Korean and the economy has been generated. This article examine on the mutual influence between economic index and distribution industry index in Korean. Research design, data, and methodology - For this purpose, we use the vector-auto regression model, impulse response function and variance decomposition of the economic index and distribution industry index, Granger causality test using weekly data on the economic index and distribution industry price index in korea. The sample period is covering from January 2, 2010 to August 31, 2019. The VAR model can also be linked to cointegration analysis. Cointegration Analysis makes possible to find a mechanism causing x and y to move around a long-run equilibrium (Engle and Granger, 1987). This equilibrium means that external shocks may separate the series temporarily at any particular time, but there will be an overall tendency towards some type of long-run equilibrium. If variables are found to have this tendency they are said to be cointegrated and a long-run relationship between these series is established. These econometric tools have been applied widely into economics and business areas to analyze intertemporal linkages between different time series. Results - This research showed following main results. First, from the basic statistic analysis of the economic index and distribution industry index in Korean, the economic index and the distribution industry index in korea have unit roots. Second, there is at least one cointegration between the economic index and distribution industry index in Korean. Finally, the correlation between of the economic index and the distribution industry index in korea is (+) 0.528876. Conclusions - We find that the distribution industry price index Granger cause the economic index in korea. As a consequence, the distribution industry index affect the economic index in Korean. The distribution industry index to the economic index is stronger than that from the economic index to the distribution industry index.

• Journal of Distribution Science
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• v.12 no.6
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• pp.49-57
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• 2014

Purpose - The world now recognizes environmental disruption as a serious issue when regarding growth-oriented strategies; therefore, environmental preservation issues become pertinent. Consequently, green distribution is continuously emphasized. However, studying the prediction and association of distribution and the environment is insufficient. Most existing studies about green distribution are about its necessity, detailed operation methods, and political suggestions; it is necessary to study the distribution service industry and environmental service industry together, for green distribution. Research design, data, and methodology - ARIMA (auto-regressive moving average model) was used to predict the environmental service and distribution service industries, and the Granger Causality Test based on VAR (vector auto regressive) was used to analyze the causal relationship. This study used 48 quarters of time-series data, from the 4th quarter in 2001 to the 3rd quarter in 2013, about each business type's production index, and used an unchangeable index. The production index about the business type is classified into the current index and the unchangeable index. The unchangeable index divides the current index into deflators to remove fluctuation. Therefore, it is easy to analyze the actual production index. This study used the unchangeable index. Results - The production index of the distribution service industry and the production index of the environmental service industry consider the autocorrelation coefficient and partial autocorrelation coefficient; therefore, ARIMA(0,0,2)(0,1,1)4 and ARIMA(3,1,0)(0,1,1)4 were established as final prediction models, resulting in the gradual improvement in every production index of both types of business. Regarding the distribution service industry's production index, it is predicted that the 4th quarter in 2014 is 114.35, and the 4th quarter in 2015 is 123.48. Moreover, regarding the environmental service industry's production index, it is predicted that the 4th quarter in 2014 is 110.95, and the 4th quarter in 2015 is 111.67. In a causal relationship analysis, the environmental service industry impacts the distribution service industry, but the distribution service industry does not impact the environmental service industry. Conclusions - This study predicted the distribution service industry and environmental service industry with the ARIMA model, and examined the causal relationship between them through the Granger causality test based on the VAR Model. Prediction reveals the seasonality and gradual increase in the two industries. Moreover, the environmental service industry impacts the distribution service industry, but the distribution service industry does not impact the environmental service industry. This study contributed academically by offering base line data needed in the establishment of a future style of management and policy directions for the two industries through the prediction of the distribution service industry and the environmental service industry, and tested a causal relationship between them, which is insufficient in existing studies. The limitations of this study are that deeper considerations of advanced studies are deficient, and the effect of causality between the two types of industries on the actual industry was not established.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.457-467
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• 2015

Despite the recent phenomena of Chonsei price increase, low interest rate and low growth, the indexes of financial and insurance industry production showed the results contrary to the common belief that the financial industry is sensitive to such financial crises. This is because the index of financial industry has continuously maintained a certain level of increase as opposed to the index of all industry production. Thus, this study aimed to analyze the dynamic correlation between the index of financial industry production and Chonsei price increase. A vector autoregression (VAR) model, which doesn't have a cointegrating relationship, was used to define the Chonsei price index and the indexes of all industry production and financial and insurance industry, which are macro economic variables, and describe the data. The results of the analysis on the time series data of 183 months from January 2000 to May 2015 showed that Chonsei price increase was not directly derived from the index of financial industry, but the finance industrial index affected Chonsei price increase.

• Journal of Korean Society of Forest Science
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• v.94 no.2 s.159
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• pp.82-89
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• 2005

The purpose of this paper is to investigate index numbers by conducting various comparisons among the widely used index formulas. The comparison is considered in three ways; 1) divergences in the magnitudes of index numbers due to the use of different formulas (Laspeyres, Paasche, Fisher, and Tornqvist); 2) the effect of selection of base year (fixed-year base vs. chain-type); 3) the degree of approximation of indirect to direct quantity index. The empirical application is to sawmills and planing mills industry of U.S. using a national time series data covering years of 1948-2000. The results show that the differences between Laspeyres and Paasche index can be substantial in some cases while the difference between Fisher and Tornqvist index is minimal. We also confirm that the selection of base year can cause significant divergences, especially when the variables undergo rapid price or quantity changes over time. We find that indirect quantity index approximates direct quantity index reasonably well in U.S. sawmill industry.

• Journal of Distribution Science
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• v.17 no.1
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• pp.11-19
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• 2019

Purpose - We document the impact of economic policy uncertainty (EPU) in the US and China on the dynamic spillover effect of macroeconomics such as stock price, housing price in Korea. Research design, data, and methodology - We use the nine variables to analyze the effect which produces a result among the EPU indexes of the US and China on economic variables which is the consumer price index (CPI), housing purchase price composite index, housing lease price, the stock price index in banking industry, construction industry and distribution industry, and composite leading indicator from January 1995 to December 2016 with the Vector Error Correction Model. Result - The US EPU index has significantly a negative relation on the CPI, housing purchase price index, housing lease price index, the stock price index in banking industry, construction industry, and distribution industry in Korea. Conclusions - We find the dynamic effect of the EPU indexes in the US and China on the macroeconomics returns in Korea. This study has an empirical evidence that the economy market in Korea is influenced by the EPU index of the US rather than it of China. The higher EPU, the more risky the economy of in Korea.

• Management & Information Systems Review
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• v.34 no.4
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• pp.67-81
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• 2015

The purpose of this study was to evaluate the effect of this factor on the macroeconomic variables for the healthcare industry market. First, the government bond interest rates and the exchange rate is the cause variable of drug industry index. Drug industry index is a mutual influence between the Call interest rate. Second, the medical equipment index haver mutual cause variable such as call rate index, government bond interest rates, and exchange rate. A current account balance variable is the cause variable of drug industry index. Third, the drug industry index has a negative relationship with a Call interest rate and an exchange rate. but it has a positive relationship with a government bond interest rates. the medical equipment index has a negative relationship with an exchange rate. but it has a positive relationship with a government bond interest rates.

• Korean Management Science Review
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• v.25 no.2
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• pp.111-127
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• 2008

This paper analyzes the technological competitiveness of aircraft-based industries that are the basis for the development of aircraft industry in Korea. By performing expert interviews with industry specialists in the field of aircraft technology, the paper categorizes eight fields that are fundamental to the development of the aircraft industry. By analyzing patents of G7 countries and Korea made in the US from 1995 to 2006 we were able to identify the technological specificities and competencies of each country. RTA (Revealed Technology Advantage) index and CII (Current Impact Index) are used to examine the technological specificity and technological competence respectively. Finally, by introducing the TCI (Technological Competitiveness Index) the paper is able to consider both the quantitative level and the qualitative level of patents for each field in the aircraft industry. By analyzing the TCI, the paper concludes that Korea has high technological prowess centered around IT industries such as semi-conductors/ electronics component, communication appliances and consumer electronics. Also Korea is relatively competitive in the precision instruments industry.

• Journal of Korea Technology Innovation Society
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• v.1 no.3
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• pp.364-373
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• 1998

This study examines the international competitiveness of the Korean information and telecommunication industry by using competitiveness index such as the RCA index, the Trade Specialization index, and the Total Factor Productivity. The results of this study show that the industry's competitiveness slightly decreases since 1995, but not its the total factor productivity. In conclusion, the industry has kept the competitiveness over all. Therefore, to keep or improve the competitiveness continuously, the industry is required the government's intensive investment and administrative support. And the industry should bring up by venture and small-medium-size-enterprises to have great economic impacts on other industries. Also, the increasing production and export promoting policy will be enhance the industry and improve nation's balance of trade.

• International Commerce and Information Review
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• v.7 no.4
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• pp.351-365
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• 2005

Korean auto mobile industry has been contributed to development on national economy for last 30 years. Especially, The fact is that latest increasement of Korean automobile selling is worthy of notice in U.S. market which is the biggest automobile market of the world. But development of automobile industry unattainable nothing of helping of auto parts industry. So, when we discuss about growth of automobile industry, we also have to consider role of auto parts industry at the same time. The purpose of this study was to analyze exporting competition of Korean auto parts in U.S. market by using Index of Export Bias and Market Comparative Advantage Index. For attaining the purpose of study, we classified the Korean auto parts which exported to U.S. market and the world by using the six units classification of the Harmonized System(HS). Also we measured Index of Export Bias and Market Comparative Advantage Index. Analyzing period was 1998-2004. The results of Index of Export Bias indicated that HS Code No. 8708.50, 8708.91 represented over 3 numerical value and 8708.92, 8708.60, 8708.39, 8708.29 represented over 2 numerical value. Additional results indicated that the Korean auto parts which gained exporting competition in the U.S. market were HS Code No. 8708.70, 8708.93, 8708.92. The products which will have exporting competition in the U.S. market would be HS Code No. 8708.99,

• The Journal of Fisheries Business Administration
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• v.36 no.2 s.68
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• pp.97-120
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• 2005

This study focused on manufactures of meat and fish products among food manufactures, made a time series data for the period from 1983 to 2002, and applied the data to Hecksher-Ohlin model to analyze the elements of pattern of export in food processing industries of Korea. The results are as follows; First, the average annual growth rate of constant exports has increased for meat product and fish product industries in Korea. But, for fish product industries, it has decreased at large since the mid-1990s. Second, the average annual growth rate of physical capital index has increased for meat product and fish product industry, The rate has been more higher for fish product industry than for meat product industry. Third, the average annual growth rate of labor index has decreased for both meat and fish products industries. Fourth, physical capital index has had no significant impact on constant exports for meat product industry, while labor index has had a significant impact on it. Fifth, physical capital index has had a significant impact on constant exports for fish product industry, while labor index has had no significant impact on it.