• The Journal of Fisheries Business Administration
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• v.46 no.1
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• pp.93-107
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• 2015

This study aims to analyze causalities among Hairtail prices by distribution channel using a vector autoregressive model. This study applies unit-root test for stability of data, uses Granger causality test to know interaction among Hairtail Prices by distribution channel, and employes the vector autoregressive model to estimate statistical impacts among t-2 period variables used in model. Analyzing results of this study are as follows. First, ADF, PP, and KPSS tests show that the change rate of Hairtail price by distribution channel differentiated by logarithm is stable. Second, a Granger causality test presents that the producer price of Hairtail leads the wholesale price and then the wholesale price leads the consumer price. Third, the vector autoregressive model suggests that the change rate of Hairtail producer price of t-2 period variables statistically, significantly impacts change rates of own, wholesale, and consumer prices at current period. Fourth, the impulse response analysis indicates that impulse responses of the structural shocks with a respectively distribution channel of the Hairtail prices are relatively more powerful in own distribution channel than in other distribution channels. Fifth, a forecast error variance decomposition of the Hairtail prices points out that the own price has relatively more powerful influence than other prices.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.607-612
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• 2021

This study estimated the impact of the shock of housing price increase on the total fertility rate and the contribution of each variable to changes in the TFR. This study is differentiated by estimating the contribution rate of each variable to the fertility rate through the Shapley decomposition and the panel VAR's forecast error variance decomposition, which previous studies have not attempted. The main results of this study are as follows. First, the decline in the TFR in Korea has been strongly influenced by the recent decline in the total fertility rate, and this influence is expected to continue in the future. In the case of housing costs, in the past, housing sales prices had a relatively small contribution to changes in the total fertility rate compared to the jeonse prices, but their influence is expected to increase in the long term in the future. It has been demonstrated that private education expenses other than housing sale price and Jeonse price also acted as a major cause of the decline in the total fertility rate.

• Korea Trade Review
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• v.46 no.5
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• pp.115-130
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• 2021

The main purpose of this study is to analyze the causal relationship between import-export goods and transportation modes. To this end, five major commodity groups were selected from 2010 to 2018 such as Machinery and transport equipment (SITC 7), manufactured goods classified chiefly by material (SITC 6), chemicals and related products, n.e.s. (SITC 5), mineral, fuels, lubricants, and related materials (SITC 3), and miscellaneous manufactured articles (SITC 8). And using the panel VECM, the difference between transportation modes such as ports and airports was compared and analyzed through panel granger causality, Impulse response function, Forecasting error variance decomposition. As a result, it is confirmed that the causal relationship between major product groups and transportation modes showed different causal relationships depending on the characteristics of port and air transportation.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.1
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• pp.127-136
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• 2016

The purpose of this research is to conduct a comparative study on the characteristics of daily volatility spillovers across the stock markets of Korea, China, and Japan. We employ generalized spillover definition and measurement developed by Diebold & Yilmaz (2009, 2012). The sample period is January 5, 1993 to September 25, 2015. From a static full-sample analysis, we find that 8.60% of forecast error variance comes from volatility spillovers. From a 250-day rolling-sample analysis, we discover that there exist significant volatility fluctuations in the stock markets of Korea, China and Japan, expecially during the Asian Financial Crisis (1998-1999) and the US Credit Crisis (2008-2009) after the collapse of Lehman Brothers. From the net directional spillovers across three countries, we come upon that there is neither a definite leader nor a significant follower during the sample period.

• The Korean Journal of Applied Statistics
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• v.37 no.4
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• pp.509-523
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• 2024

This study estimates connectedness index among the US, China, Europe, Japan, and South Korea using monthly economic policy uncertainty (EPU) data from January 2000 to December 2023. The connectedness index allows us to analyze the effect of global economic uncertainty on domestic economic uncertainty. The EPU is used as a proxy for economic uncertainty. Inter-country connectedness index is computed from variance decomposition. The findings from forecast error variance decomposition show that three-fourths of total uncertainty comes from economic uncertainty in the own country and one-fourth of total uncertainty comes from economic uncertainty in the others. The analysis on net pairwise connectedness reveals that, even though the extent of the effect of economic uncertainty in one country from economic uncertainty in another country varies over time, economic uncertainty in South Korea, a small-open economy, is mainly affected by economic uncertainty in the others. The reverse situation rarely happens except in the specific occurrence such as the collapse of the credit bubble in 2003 and the subsequent years, the inter-Korean summit and North Korea-the US summit in 2018, and the period from the first outbreak of COVID-19 on the implementation of the government's severe regulation against COVID-19.

• East Asian Economic Review
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• v.22 no.3
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• pp.371-400
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• 2018

Although asset price is an important factor in determining changes in external balances, no studies have investigated it from the Chinese perspective. In this study, I empirically examine the underlying driving forces of China's trade balances, particularly the role of asset price and the real exchange rate. To this end, I estimate a sign-restricted structural vector autoregressive model with quarterly time series data for China, using the Bayesian method. The results show that changes in asset price affect China's trade balances through private consumption and investment. Also, an appreciation of the real exchange rate tends to deteriorate trade balances in China. Furthermore, forecast error variance decomposition results indicate that changes in asset price (stock price and housing price) explain about 20% variability of trade balances, while changes in the real exchange rate can explain about 10%.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.477-481
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• 2007

The purpose of this study is to provide the ideal forecasting model of cadastral survey work load through the Economeatric Analysis of Time Series, Granger Causality and VAR Model Analysis, it suggested the forecasting reference materials for the total amount of cadastral survey general work load. The main result is that the derive of the environment variables which affect cadastral survey general work load and the outcome of VAR(vector auto regression) analysis materials(impulse response function and forecast error variance decomposition analysis materials), which explain the change of general work load depending on altering the environment variables. And also, For confirming the stability of time series data, we took a unit root test, ADF(Augmented Dickey-Fuller) analysis and the time series model analysis derives the best cadastral forecasting model regarding on general cadastral survey work load. And also, it showed up the various standards that are applied the statistical method of econometric analysis so it enhanced the prior aggregate system of cadastral survey work load forecasting.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.141-154
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• 2002

Foreign investors'shares and their influences on the Korean stock market have never been larger and greater before since the market was completely open to foreign investors in 1992 Quantitatively and qualitatively as well, as a result, changes in the patterns of foreign investments have caused enormous effects on the interactions of major macroeconomic indices of the Korean economy. This paper is intended to investigate the causal relations of the four variables, foreigners'buy-sell ratios, stock returns, ￦/＄ exchange rates and $\yen$/＄ exchange rates, over the two time periods of the pre-IMF (1996.1.1-1997.8.15) and the post-IMF (1997.8.16-2000.6.15) based on the daily data of the variables. Granger Causality Test, Forecast Error Variance Decomposition(FEVD) using VAR model and Impulse Response Function were implemented for the empirical analysis.

• Environmental and Resource Economics Review
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• v.15 no.5
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• pp.799-826
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• 2006

Combining recent advances in causal flows with time series analysis, relationships among eight North American natural gas spot market prices are examined. Results indicate that price discovery tends to occur in excess demand regions and move to excess supply regions. Across North America, the U.S. Midwest region represented by Chicago spot market is the most important market for price discovery. The Ellisburg-Leidy Hub in Pennsylvania is important in price discovery, especially for markets in the eastern two-thirds of the U.S. Malin Hub in Oregon is important for the western markets including the AECO Hub in Alberta, Canada.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.91-101
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• 2021

The paper examines the impact of the COVID-19 pandemic on the stock market prices. The vector autoregression model (VAR) has been used in this analysis to survey 341 stocks on the Ho Chi Minh City Stock Exchange (HOSE) for the period from January 23, 2020 to December 31, 2020. The empirical results obtained from the analysis of 11 economic sectors suggest that there is a statistically significant impact relationship between COVID-19 and the healthcare and utility industries. Additional findings show a statistically significant negative impact of COVID-19 on the utility share price at lag 1. Analysis of impulse response function (IRF) and forecast error variance decomposition (FEVD) show an inverse reaction of utility stock prices to the impact of COVID-19 and a gradual disappearing shock after two steps. Major findings show that there is a clear negative effect of the COVID-19 pandemic on share prices, and the daily increase in the number of confirmed cases, indicate that, in future disease outbreaks, early containment measures and positive responses are necessary conditions for governments and nations to protect stock markets from excessive depreciation. Utility stocks are among the most severely impacted shares on financial exchanges during a pandemic due to the high risk of immediate or irreversible closure of manufacturing lines and poor demand for basic amenities.