• 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 Korea Port Economic Association
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• v.32 no.4
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• pp.165-182
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• 2016

This study examines the competitiveness and cooperativeness among the container ports in East Asia by analyzing their monthly dynamics in eight years (2008-2015). Time series data on container throughput divided into origin and destination (O/D), such as the top six Chinese ports and the transshipment (T/S) ports such as Hong Kong, Busan, and Singapore, are computed with two methods based on the Vector Error Correction Model (VECM). The first Granger causality test results show that Busan T/S has significant bilateral relations with three Chinese O/D ports; and significant unidirectional relations with three other O/D ports. Shenzhen port has significant bilateral relations with Singapore, and has a significant unidirectional relation with Hong Kong port. Co-integrating test results showed that Busan holds negative co-integration with all Chinese O/D ports. Impulse response function (IRF) results show an opposite direction between paired ports. The ratios of the impulse from T/S ports are significantly high to one another in the short-run, but its power declines as time passes. The ratio of the impulse from the Chinese ports to T/S ports is less significant in the short-run period, however, it becomes more significant as time passes. The significance of most shocks was high in the second period, but was diluted after the sixth period.

• International Commerce and Information Review
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• v.16 no.4
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• pp.151-167
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• 2014

The aim of this study is to examine the relationship between globalization and income distribution in Korea. In order to identify the key determinants, the study investigates the effects of trade openness, inward and outward FDI flows, and per capita GDP on income distribution. The study uses methodology of unit root and co-integration technique as well as an error correction model over 1992 to 2011 by using annual data. The empirical findings showed that income inequality is reduced as trade openness and the per capita GDP increase. Meanwhile, income inequality is deteriorated as inward and outward FDI flows increased. In addition, the study revealed that the negative effect of inward FDI flows on income inequality is greater than that of outward FDI flows. This result supports the Feenstra and Hanson (1997) hypothesis. Overall the globalization process can be beneficial for the Korean economy, but its nature should be closely monitored regarding income distribution.

• International Journal of High-Rise Buildings
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• v.6 no.2
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• pp.149-163
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• 2017

With the intensification of urban development in Chinese cities, mixed land use in urban centers extends vertically into 3-D and expands its scale from a single building to commercial clusters. The multi-level pedestrian system in city centers also changed its role from one of traffic isolation to spatial integration, where transit nodes, street sidewalks, squares, building entrances, atriums, and corridors are interconnected, both horizontally and vertically, into a whole spatial system, within which pedestrian flows are guided and shopping facilities are arranged. This paper uses spatial configuration analysis of space syntax to examine the impacts of spatial patterns on movement distribution and the business performance of tenant mix in the multi-level commercial system of the Nanshan Commercial Cultural District in Shenzhen, China. The key objective is to better understand the interactions between the socio-economic variables and spatial design parameters of a shopping complex. The research findings point to the importance of multiplicity between syntactic variables and other spatial variables in influencing the pedestrian flows, business performance and tenant mix in highly complex commercial systems. Particularly noteworthy is the relationship between spatial accessibility measures and the location of escalators, and the ways in which individual commercial buildings are embedded into the overall spatial system. The study suggests that this may lead to the preliminary identification of the spatial qualities of effective vertical extensions of mixed land use in a high-density urban settings.

• International Area Studies Review
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• v.21 no.2
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• pp.3-20
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• 2017

Traditional co-integration analysis method is known to be difficult to clearly determine the relationship between the cointegrated variables. This study utilizes a fractional cointegation method and a causal analysis of time and frequency domain among the exchange rates of Korea, China and Japan. The results show that even though traditional cointegration methods did not clarify the existence of cointegration, exchange rates were fractionally cointegrated. Causal analysis of time domain and frequency domain provided somewhat different results, but the yen/dollar was useful for forecasting won/dollar and yuan/dollar. Proper use of causal analysis of frequency domain and fractional cointegration emthods may provide useful information that can not be explained from the traditional method.

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.416-427
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• 2018

As the loan size of real estate PF is huge, its market ripple effect gets bigger when overdue occurs. Accordingly, the management of the delinquency rate and macroeconomic analysis are required. As the preceding research mainly proceeded with microeconomic analysis through the real estate PF data of individual banks to evaluate importance of list or analyzed core factors for delinquency, it lacked research on comprehensive real estate PF size. In order to overcome the limitations of such data, this research studied real estate PF delinquency rate of the entire market and effect relationship by the size. The research utilized the size of real estate PF loans, money supply, interest rate, consumer price index(CPI), and GDP data. Also, it applied the first model of VECM as linear relationship between at least two or more variables, following the result of co-integration test. As a result of Granger-causality test, the real estate PF loans delinquency rate is influenced by their loan size, and as a result of impulse response analysis, the interest rate is shown to be affecting delinquency rate the most. Interest rate could risesomeday and aggravate the delinquency rate of real estate PF. Also, risk exposure could be serious as the loan size increases.Therefore, the management of real estate PF delinquency rate requires continuous monitoring, tracking and observing issued loans from a macro point of view. The plans to prevent delinquency will be necessary.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.531-540
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• 2007

In this research, we proposed a two-phase hybrid stock price forecasting model with cointegration tests and artificial neural networks. Using not only the related stocks to the target stock but also the past information as input features in neural networks, the new model showed an improved performance in forecasting than that of the usual neural networks. Firstly in order to extract stocks which have long run relationships with the target stock, we made use of Johansen's cointegration test. In stock market, some stocks are apt to vary similarly and these phenomenon can be very informative to forecast the target stock. Johansen's cointegration test provides whether variables are related and whether the relationship is statistically significant. Secondly, we learned the model which includes lagged variables of the target and related stocks in addition to other characteristics of them. Although former research usually did not incorporate those variables, it is well known that most economic time series data are depend on its past value. Also, it is common in econometric literatures to consider lagged values as dependent variables. We implemented a price direction forecasting system for KOSPI index to examine the performance of the proposed model. As the result, our model had 11.29% higher forecasting accuracy on average than the model learned without cointegration test and also showed 10.59% higher on average than the model which randomly selected stocks to make the size of the feature set same as that of the proposed model.

• International Area Studies Review
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• v.12 no.3
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• pp.153-169
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• 2008

This paper examines the recently empirical test for the two types of endogenous growth models, which one is more fitted to real data. We adopt the non-stationary panel data methodologies for seeking empirical implication by using productivity and R&D data in the OECD over the past two decades. The Empirical tests show that there is a robust relationship Total Factor Productivity and R&D variables implied by semi-endogenous growth model. The relationship suggested by fully endogenous growth theory, however, is sensitive to R&D variables. Therefore, the estimation results provide empirical evidence in favour of endogenous growth theory of R&D expenditure role for sustaining economic growth. The sustained Total Factor Productivity, however, is maintained by more increasing R&D inputs for overcoming diminishing return to R&D efforts.

• Korea Trade Review
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• v.48 no.1
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• pp.127-163
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• 2023

The objective of this study is to investigate the volatility spillover effects among BDI, CCFI and SCFI. This paper will divide the empirical analysis section into two periods to analyze and compare the differences in volatility spillover effect between shipping freight indices before and after the outbreak of COVID-19 separately. First, in order to compare the mean spillover impact and index lead-lag correlations in BDI and CCFI indices, along with BDI and SCFI indices before and after COVID-19, the co-integration analysis and the test of Granger causality built on the VAR model were utilized. Second, the impulse response and variance decomposition are employed in this work to investigate how the shipping freight index responds to shocks experienced by itself and other freight indices in a short period. Before the COVID-19 epidemic, the results demonstrated that the BDI freight index is the Granger cause of the variable CCFI freight index. But the BDI and CCFI freight indices have no apparent lead-lag relationships after COVID-19, and this empirical result echoes the cointegration test result. After the COVID-19 epidemic, the SCFI index leads the BDI index. This study employs the VAR-BEKK-GARCH joint model to explore the volatility spillover results between dry bulk and container transport markets before and after COVID-19. The empirical results demonstrate that after COVID-19, fluctuations in the BDI index still affect the CCFI index in the maritime market. However, there is no proof of a volatility spillover relationship between the BDI and SCFI after the COVID-19 epidemic. This study will provide an insight into the volatility relationship among BDI, CCFI and SCFI before and after the the COVID-19 epidemic occurred.

• Journal of Korea Water Resources Association
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• v.37 no.10
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• pp.869-880
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• 2004

The purpose of this study is to examine relationship between water consumption and economic growth in Korea, and to obtain policy implications of the results. To this end, we attempt to provide more careful consideration of the causality issues by applying rigorous techniques of Granger causality. Tests for unit roots, co-integration, and Granger causality based on an error-correction model are presented. The existence of bi-directional causality between water consumption and economic growth in Korea is detected. This finding has various implications for policy analysts and forecasters in Korea. Economic growth requires enormous water consumption, though there are many other factors contributing to economic growth, and water consumption is but one part of it. Thus, this study generates confidence in decisions to invest in the water supply infrastructure. Moreover, this study lends support to the argument that an increase in real income, ceteris paribus, gives rise to water consumption. Economic growth results in a higher proportion of national income spent on water supply services and stimulates further water consumption.