• Journal of Korea Trade
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• v.25 no.1
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• pp.18-33
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• 2021

Purpose - This paper investigates the causal relationship between logistics infrastructure development and the economic growth of Korea. Considering the industrial and economic structure of Korea, it is likely that logistics infrastructure is positively associated with the economic growth of the country. Design/methodology - The causal relationship between logistics infrastructure and economic development is estimated using Vector Autoregressive (VAR) and Vector Error Correction Model (VECM) considering long-run equilibrium between the two factors. To this end, a dataset consisting of 7 logistics infrastructure proxies and 5 economic growth indicators covering the period of 1990-2017 is used. Findings - It was found that causality, in general, runs from logistics infrastructure development to economic growth. Specifically, the results indicate that maritime transport is positively associated with the economic growth of Korea in terms of GDP and international trade. In addition, other modes of transport also have a positive impact on either the GDP or international trade of Korea. Originality/value - While existing studies in this area are based on either regional observations or a specific mode of transport, this study presents empirical evidence on causality between logistics infrastructure and the economic growth of Korea using a more comprehensive dataset. In addition, the findings in this paper can provide valuable implications for transport infrastructure development policies.

• Korea Trade Review
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• v.47 no.2
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• pp.133-154
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• 2022

The Baltic Capesize Index (BCI), which is used as an indicator for marine transportation of steel raw materials, is one of the key economic indexes for managing the risk of loss due to rapid market fluctuations when steel companies establish business strategies and procuring plans for raw materials. Still, the conditions of supply and demand of steel raw materials has been extremely affected by volatility shocks from drastic events like the financial crisis such as the Lehman Brothers incident and changes in the external environment such as COVID-19. And, especially since the 2008 financial crisis, endeavors to predict the market conditions of the steel raw material is becoming more and more arduous for the deepening uncertainty and increased volatility of BCI, which has been used as a leading indicator of the real economy. This study investigates the correlation between the steel raw material market and the marine transportation market by estimating the spillover effect of information between markets. The vector error correction model (VECM) was used to analyze information transfer based on the correlation between the BCI and crude steel production, capesize fleet supply, raw material price, and cargo volume.

• Journal of Korea Port Economic Association
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• v.23 no.4
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• pp.228-243
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• 2007

This study porvides an empirical overview of the import patterns of Incheon port using an Engle-Granger cointegration technique and Johansen's multivariate cointegraion methodology test to check the stationarity of the model. The empirical results show that the import in Incheon port related to the economic variables. This paper also applies rolling regression to our model, indicating that import are endogeneous to the economic variable.

• Korea Trade Review
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• v.42 no.6
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• pp.131-154
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• 2017

In international trade, transportation generally has the largest and direct impact on freight costs. However, it is also sensitive to external factors such as global economic conditions, global trade volume and exchange rate. Therefore, it is necessary to examine the relationship and influence of international trade in terms of external factors that affect the change of imports and exports by marine and air transportation through empirical analysis. In particular, the analysis of the impact of these external factors on marine and air transportation is an important topic when recent exchange rate changes are significant, and it is also necessary to analyze what transportation means are more sensitive to exchange rate changes. In this study, we use the Vector Error Correction Model to analyze the dynamic effects of changes in exchange rate and domestic and international economic conditions on marine and air transportation from January 2000 to March 2017. Respectively. Alos, Impulse response function and variance decomposition were examined.

• The Journal of Industrial Distribution & Business
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• v.9 no.5
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• pp.63-72
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• 2018

Purpose - This work analyzes, in detail, the specification of vector error correction model (VECM) and thus examines the relationships and impact among seven economic variables for USA - balance on current account (BCA), index of stock (STOCK), gross domestic product (GDP), housing price indices (HOUSING), a measure of the money supply that includes total currency as well as large time deposits, institutional money market funds, short-term repurchase agreements and other larger liquid assets (M3), real rate of interest (IR_REAL) and household credits (LOAN). In particular, we search for the main explanatory variables that have an effect on stock and real estate market, respectively and investigate the causal and dynamic associations between them. Research design, data, and methodology - We perform the time series vector error correction model to infer the dynamic relationships among seven variables above. This work employs the conventional augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root techniques to test for stationarity among seven variables under consideration, and Johansen cointegration test to specify the order or the number of cointegration relationship. Granger causality test is exploited to inspect for causal relationship and, at the same time, impulse response function and variance decomposition analysis are checked for both short-run and long-run association among the seven variables by EViews 9.0. The underlying model was analyzed by using 108 realizations from Q1 1990 to Q4 2016 for USA. Results - The results show that all the seven variables for USA have one unit root and they are cointegrated with at most five and three cointegrating equation for USA. The vector error correction model expresses a long-run relationship among variables. Both IR_REAL and M3 may influence real estate market, and GDP does stock market in USA. On the other hand, GDP, IR_REAL, M3, STOCK and LOAN may be considered as causal factors to affect real estate market. Conclusions - The findings indicate that both stock market and real estate market can be modelled as vector error correction specification for USA. In addition, we can detect causal relationships among variables and compare dynamic differences between countries in terms of stock market and real estate market.

• International Commerce and Information Review
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• v.14 no.3
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• pp.307-322
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• 2012

The purpose of this paper is to examine determinants of export to the East Asia region, using panel unit root, panel cointegration framework, panel VECM (vector error correction model), panel FMOLS (fully modified OLS). Different panel unit root tests confirm that the data series are integrated processes with unit roots. When applying cointegration tests to long-run effect for aggregate panel data, a primary concern is to construct the estimators in a way that does not constrain the transitional dynamics to be similar among different countries of the panel. The regression equations are estimated by various panel cointegration estimators. The panel data causality results reveal that exchange rates has unidirectional effects on export and GDP, and there exists bidirectional causality between export and GDP. Also, the results from the panel FMOLS tests overwhelmingly reject the null hypothesis of zero coefficient. The panel cointegrating vectors show that the export has positive relationship with the GDP and ODI (overseas direct investment).

• International Commerce and Information Review
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• v.19 no.2
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• pp.65-84
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• 2017

This paper attempts to investigate FDI Trade have been viewed a power affecting economic growth in Mongolia and five Central Asian countries(Kazakhstan, Uzbekistan, Kyrgyzstan, Kazakhstan and Turkmenistan) directly and indirectly using the Vector Error Correction Model. The results of empirical analysis based on data from 1995 to 2015 confirmed that FDI had a significant impact on economic growth in the rest of countries expect Kazakhstan and Turkmenistan, and Trade was not statistically significant for all countries. Accordingly we've come to below conclusion in consideration of the results of the statistics survey. It is urgently required to implement the policies on promoting foreign investment at first in order to recover economic decline though the international trading is considered important in developing the economics of developing countries. Especially, the landlocked countries, namely the countries having same border should focus on promoting the development of transport and freight forwarding systems between the countries, implementing the policies on trade relationships and foreign direct investments throughout the nation in consideration of the low- level of market economic conditions.

• Management & Information Systems Review
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• v.33 no.3
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• pp.93-104
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• 2014

This study investigates price discovery between BlueNext spot and futures in EU ETS carbon emission markets using vector error correction model, GG and Hasbruck information ratio. Especially EUA is European Union Allowances traded on the Emissions Trading Scheme. This emission asset attracts and increasing attention among operators, investors and brokers on emission markets. In this study, we found BlueNext spot and EUA futures market are cointegrated. Following the preceding studies, we judged that EUA futures market contribute to the price discovery process than BlueNext spot market when this GG and Hasbrouck information ratio for BlueNext market are larger than 0.5. In other words, the futures market of EUA plays a more dominant role in price discovery than the spot market.

• The Korean Journal of Applied Statistics
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• v.18 no.3
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• pp.503-519
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• 2005

Cointegration test is usually performed under the assumption that the cointegrating vector is constant for the whole sample period. Most previous studies have used conventional cointegration methods in testing for a stable long-run equilibrium relation among related variables. However they have overlooked that the long-run equilibrium may not the unique and the stable relation may not be guaranteed. This study develops the additional statistical tests for the stability of the estimated cointegrating vector. Three tests for the parameter stability of a cointegrated regression model are utilized and applied to identify the types of variations in the long-run relation between the domestic unemployment and the rotated macroeconomic variables of interest. The present paper finds that, there exists a stable but, time-varying long-run relation between those. The observed variation in cointegrating relations is generally characterized by a discrete one-time shift, rather than a gradually evolving random walk process which is attributable to the IMF financial and economic crisis.

• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.81-93
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• 2010

Korea experienced a financial crisis in 1997. Since then Korea economy has undergone severe change such as exchange rate regime from the market average exchange rate system to the free floating exchange rate system in 1997, and the currency rate fluctuation has been widening. We empirically analyze the determination of the Won/Dollar exchange rate based on the monetary approach. We employ Lucas (1982), Bilson (1978) and Frankel (1979) models and consider some mixed models. We make use of monthly data of money supply, income, interest rate, capital balance, terms of trade, and the yen/dollar exchange rate over the period 1990-2009. We compare the empirical results of cointegration tests and the vector error correction model(VECM) from the two regimes, the pre and post korean financial crisis. The won/dollar exchange rate has long-run relationship with the variables in the monetarist models in the two regimes. For the post crisis regime, the Bilson model is the best and the long run variables also affect the short run dynamics of the won/dollar exchange rate.