• Journal of Korean Society of Forest Science
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• v.90 no.2
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• pp.217-226
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• 2001

This study estimated the impacts of the building permit area change on the forest products import quantities in Korea. The first objective of this dissertation is to analyze whether there is any causal relationship between change in the building permit area and changes in the import quantities of forest products in Korea. Assuming that there is any causal relationship, the second objective is to evaluate the dynamics of the impacts of the building permit area change on the forest products import quantities in Korea. The relationship between the building permit area and the import quantity was represented by bivariate vector autoregressive or vector error correction model. Whether there is any causal relationship between change in the building permit area and changes in the import quantities of forest products was analyzed by the causality test of Granger. And the dynamics of the impacts of the building permit area change on the forest products import quantities were evaluated by variance decomposition analysis and impulse response analysis. The import quantity of forest products can be explained by the lagged building permit area variables and the lagged import quantity variables in Korea. Change in the building permit area causes change in the high-density fiberboard import quantity in Korea. In the bivariate model of the high-density fiberboard import quantity, after six months, the building permit area change accounts for about ten percent of variation in the import quantity, and its own change accounts for about ninety percent of variation in the import quantity. On the other hand, the impact of a shock to the building permit area is significant for about six months on the import quantity of high-density fiberboard in Korea. That is, if the building permit area change indeed had an impact on the import quantity of high-density fiberboard in Korea, it was only of a short-term nature.

• Journal of Korean Society of Forest Science
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• v.90 no.5
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• pp.663-671
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• 2001

This study estimated the impacts of the interest rate change on the forest products import quantities in Korea. The first objective is to analyze whether there is any causal relationship between change in the interest rate and changes in the import quantities of forest products in Korea. And the second objective is to evaluate the dynamics of the impacts of the interest rate change on the forest products import quantities in Korea. The relationship between the interest rate and the import quantity was represented by bivariate vector autoregressive model. Whether there is any causal relationship between change in the interest rate and changes in the import quantities of forest products was analyzed by the causality test. And the dynamics of the impacts of the interest rate change on the forest products import quantities were evaluated by variance decomposition analysis and impulse response analysis. The import quantity of forest products can be explained by the lagged interest rate variables and the lagged import quantity variables in Korea. Change in the interest rate causes change in the plywood import quantity in Korea. In the bivariate model of the plywood import quantity, after three months, the interest rate change accounts for about twenty percent of variation in the import quantity, and its own change accounts for about eighty percent of variation in the import quantity. On the other hand, the impact of a shock to the interest rate is significant for about six months on the import quantity of plywood in Korea. That is, if the interest rate change had an impact on the import quantity of plywood in Korea, it was only of a short-term nature.

• 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.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.1
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• pp.198-210
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• 2016

This study firstly aims to estimate a leading-price of Jeju flounders with various price-classes by fish weight and secondly plans to provide policy implications of flounder purchase projects by understanding dynamic changes and interactions among flounder producer price-classes caused by price impulses in the market. This study applies an unit root test for stability of data, uses a Granger causality test to estimate the leading-price among producer prices by fish weight, employs the vector autoregressive model to analyze statistical impacts among t-1 variables used in models, and finally utilizes impulse response analyses and forecast error variance decomposition analyses to understand dynamic changes and interactions among change rates of the producer prices caused by price impulses in the market. The results of the study are as follows. Firstly, KPSS, PP, and ADF tests show that the change rate of Jeju flounder monthly producer prices by fish weight differentiated by logarithm is stable. Secondly, the Granger causality test presents that the change rate of the 1kg flounder producer price strongly leads it of 500g, 700g, and 2kg flounder producer prices respectively. Thirdly, the vector autoregressive model indicates that the change rate of the 1kg producer price in t-1 period statistically, significantly influences it of own weight in t period and also slightly affects price change rates of other weights in t period. Fourthly, the impulse response analysis indicates that impulse responses of structural shocks for the change rate of the 1kg producer price are relatively more powerful in its own weight and in other weights than shocks emanating from price change rates of other weights. Fifthly, the variance decomposition analysis points out that the change rate of the 1kg producer price is relatively more influential than it of 500g, 700g, and 2kg producer prices respectively. In conclusion, the change rate of the 1kg Jeju flounder producer price leads the change rates of other ones and Jeju purchase projects need to be targeted to the 1kg Jeju flounder producer price as the purchase project implemented in 2014.

• Geomechanics and Engineering
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• v.3 no.3
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• pp.169-188
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• 2011

Response of buried flexible pipe-soil system is studied, through numerical analysis, with respect to deflection and buckling in a spatially varying soil media. In numerical modeling procedure, soil parameters are modeled as two-dimensional non-Gaussian homogeneous random field using Cholesky decomposition technique. Numerical analysis is performed using random field theory combined with finite difference numerical code FLAC 5.0 (2D). Monte Carlo simulations are performed to obtain the statistics, i.e., mean and variance of deflection and circumferential (buckling) stresses of buried flexible pipe-soil system in a spatially varying soil media. Results are compared and discussed in the light of available analytical solutions as well as conventional numerical procedures in which soil parameters are considered as uniformly constant. The statistical information obtained from Monte Carlo simulations is further utilized for the reliability analysis of buried flexible pipe-soil system with respect to deflection and buckling. The results of the reliability analysis clearly demonstrate the influence of extent of variation and spatial correlation structure of soil parameters on the performance assessment of buried flexible pipe-soil systems, which is not well captured in conventional procedures.

• Journal of the Korea Society for Simulation
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• v.20 no.2
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• pp.1-10
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• 2011

In queueing network analysis, arrival processes are usually modeled as renewal processes by matching mean and variance. The renewal approximation simplifies the analysis and provides reasonably good estimate for the performance measures of the queueing systems under moderate conditions. However, high variability in arrival process or in service process requires more sophisticated approximation procedures for the variability parameter of departure/arrival processes. In this paper, we propose an heuristic approach to refine Whitt's variability function with the k-interval squared coefficient of variation also known as the index of dispersion for intervals(IDI). Regression analysis is used to establish an empirical relationships between the IDI of arrival process and the IDI of departure process of a queueing system.

• Structural Engineering and Mechanics
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• v.68 no.5
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• pp.549-561
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• 2018

Sobol method is applied as a powerful variance decomposition technique in the field of global sensitivity analysis (GSA). The paper is devoted to increase convergence speed of the extracted Sobol indices using a new proposed sampling technique called genetic based Latine hypercube sampling (GBLHS). This technique is indeed an improved version of restricted Latine hypercube sampling (LHS) and the optimization algorithm is inspired from genetic algorithm in a new approach. The new approach is based on the optimization of minimax value of LHS arrays using manipulation of array indices as chromosomes in genetic algorithm. The improved Sobol method is implemented to perform factor prioritization and fixing of an uncertain comprehensive high speed rotor-bearing system. The finite element method is employed for rotor-bearing modeling by considering Eshleman-Eubanks assumption and interaction of axial force on the rotor whirling behavior. The performance of the GBLHS technique are compared with the Monte Carlo Simulation (MCS), LHS and Optimized LHS (Minimax. criteria). Comparison of the GBLHS with other techniques demonstrates its capability for increasing convergence speed of the sensitivity indices and improving computational time of the GSA.

• 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.

• Journal of Distribution Science
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• v.11 no.10
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• pp.63-72
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• 2013

Purpose - This study analyzes the relationship and dynamic interactions between stock price index, interest rate, price index, and housing price indices using Korean monthly data from 2000 to 2013, based on a VAR model. This study also examines Granger causal relationships among these variables in order to determine whether the time series of one is useful in forecasting another, or to infer certain types of causal dependency between stochastic variables. Research design, data, and methodology - We used Korean monthly data for all variables from 2000: M1 to 2013: M3. First, we checked the correlations among different variables. Second, we conducted the Augmented Dickey-Fuller (ADF) test and the co-integration test using the VAR model. Third, we employed Granger Causality tests to quantify the causal effect from time series observations. Fourth, we used the impulse response function and variance decomposition based on the VAR model to examine the dynamic relationships among the variables. Results - First, stock price Granger affects interest rate and all housing price indices. Price index Granger, in turn, affects the stock price and six metropolitan housing price indices. However, none of the Granger variables affect the price index. Therefore, it is the stock markets (and not the housing market) that affects the housing prices. Second, the impulse response tests show that maximum influence on stock price is its own, and though it is influenced a little by interest rate, price index affects it negatively. One standard deviation (S.D.) shock to stock price increases the housing price by 0.08 units after two months, whereas an impulse shock to the interest rate negatively impacts the housing price. Third, the variance decomposition results report that the shock to the stock price accounts for 96% of the variation in the stock price, and the shock to the price index accounts for 2.8% after two periods. In contrast, the shock to the interest rate accounts for 80% of the variation in the interest rate after ten periods; the shock to the stock price accounts for 19% of the variation; however, shock to the price index does not affect the interest rate. The housing price index in 10 periods is explained up to 96.7% by itself, 2.62% by stock price, 0.68% by price index, and 0.04% by interest rate. Therefore, the housing market is explained most by its own variation, whereas the interest rate has little impact on housing price. Conclusions - The results of the study elucidate the relationship and dynamic interactions among stock price index, interest rate, price index, and housing price indices using VAR model. This study could help form the basis for more appropriate economic policies in the future. As the housing market is very important in Korean economy, any changes in house price affect the other markets, thereby resulting in a shock to the entire economy. Therefore, the analysis on the dynamic relationships between the housing market and economic variables will help with the decision making regarding the housing market policy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7820-7830
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• 2015

Korean households' demand for food consumed away from home is on the steady increase. The ratio of eating-out expenditure of the household income, however, tends to decrease recently irrespective of income groups. This paper, therefore, aims to analyse the food-away-from-home expenditures of salary and wage earners' households by income decile group. The eating-out expenditure is modelled as a function of household income and then estimated using econometric methods such as regression, rolling regression, impulse response, and variance decomposition of forecast error. The regression results indicate that the higher the income decile group is, the lower the income elasticity of eating-out expenditure is, and the high income groups enjoy seasonal eating-out, the low groups do not. The coefficients of dynamic rolling regression are much smaller than those of static one, meaning that households tend to decrease the eating-out expenditure of their income. The impulse response analysis suggests that the eating-out expenditure increase of higher income groups lasts long relative to that of lower income groups. The variance decomposition, also, shows that household income plays much more important role in determining eating-out expenditure at the higher income groups than at the lower income groups.