• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.1043-1051
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• 2013

We use a structural vector error correction model of the labor market to investigate the effect of shocks to Korean unemployment. We associate technology, labor demand, labor supply, and wage-setting shocks with equations for productivity, employment, unemployment, and real wages, respectively. Subsequently, labor demand and supply shocks have significant long-run and contemporaneous effects on unemployment, respectively.

• Korea Trade Review
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• v.43 no.3
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• pp.169-198
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• 2018

The purpose of this paper is to investigate the impact of exchange rate volatility on the export of Korean machinery intermediate goods to East Asian countries using the export demand model. In order to secure the validity of the estimation of the exchange rate volatility for the export of machinery intermediate goods, various methods of volatility measurement are used including the GARCH model, the moving average standard deviation and the 12-month fixed average standard deviation. The long-term relationship between variables was analyzed by applying the panel cointegration tests and DOLS & FMOLS panel estimations. Analysis results found that prior to the global financial crisis in 2008, the total exports of machinery and exchange rate volatility positively affect the exports of intermediate goods such as general machinery, electronic machinery and transportation equipment, but did not affect the exports of precision machinery intermediate goods. After the global financial crisis, however, exchange rate volatility negatively affected total exports and the exports of all machinery intermediate goods. When analyzing the period before and after the global financial crisis, it had a positive impact on exports of precision machinery intermediate goods and a negative effect on total exports and the exports of other machinery intermediate goods.

• Environmental and Resource Economics Review
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• v.32 no.4
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• pp.267-292
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• 2023

In this paper, we estimate a time series model of energy demand in the industrial sector with an asymmetric response to energy prices. Including the asymmetric response to energy prices in the model strengthens robustness of the cointegration relationship and reduces the variation of the estimated coefficients across the estimating methods. We find that rising energy prices have a larger impact on energy demand than falling energy prices, with the largest impact occurring when energy prices rise to new highs. The estimation results are partially improved when using gross output rather than value added as a measure of production. Using single equation methods to estimate the asymmetric response model, the elasticity of gross output ranged from 1.05 to 1.09 and the elasticity of price-rise ranged from -0.48 to -0.56, which is similar to the results of international studies.

• Korea Trade Review
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• v.48 no.3
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• pp.69-88
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• 2023

This study analyzes the dynamic characteristics of cargo volume (demand), ship fleet (supply), and freight rate (price) of container, dry bulk, and tanker shipping markets by using the VAR and VECM models. This analysis is expected to enhance the statistical understanding of market dynamics, which is perceived by the actual experiences of market participants. The common statistical patterns, which are all shown in the three shipping markets, are as follows: 1) The Granger-causality test reveals that the past increase of fleet variable induces the present decrease of freight rate variable. 2) The impulse-response analysis shows that cargo shock increases the freight rate but fleet shock decreases the freight rate. 3) Among the three cargo, fleet, and freight rate shocks, the freight rate shock is overwhelmingly largest. 4) The comparison of adjR² reveals that the fleet variable is most explained by the endogenous variables, i.e., cargo, fleet, and freight rate in each of shipping markets. 5) The estimation of co-integrating vectors shows that the increase of cargo increases the freight rate but the increase of fleet decreases the freight rate. 6) The estimation of adjustment speed demonstrates that the past-period positive deviation from the long-run equilibrium freight rate induces the decrease of present freight rate.

• The Korean Journal of Applied Statistics
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• v.25 no.1
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• pp.89-99
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• 2012

This study investigates the Granger-causality between economic growth and demand for electricity in Korea, using two quarterly time-series data (real GDP and electricity consumption) for 1970:Q1 through 2009:Q4. We apply Hsiao's sequential procedure to identify a vector autoregressive model to a decision of the optimal lags in the vector error-correction model because the two time-series data contain unit roots respectively and they are cointegrated. According to the empirical results in this study, we find that Hsiao's approach to the Granger-causality indicates a bidirectional causal relation between economic growth and demand for electricity in Korea. Following the Granger and Engle's approach, we also find the statistical evidence on (1) short-run bidirectional causality between real GDP and electricity consumption, (2) bidirectional strong causality between them, and (3) long-run unidirectional causality running from demand for electricity to economic growth. Our results show an inconsistency with the existing studies on Korea's case; however, the results appear to provide more meaningful policy implications for the Korean economy and its strategy of sustainable growth.

• Journal of Navigation and Port Research
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• v.44 no.1
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• pp.44-52
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• 2020

More accurate forecasting of port cargo in the global long-term recession is critical for the implementation of port policy. In this study, the Busan Port container volume (export cargo and transshipment cargo) was estimated using the Vector Autoregressive (VAR) model and the vector error correction (VEC) model considering the causal relationship between the economic scale (GDP) of Korea, China, and the U.S. as well as ARIMA, a single volume model. The measurement data was the monthly volume of container shipments at the Busan port J anuary 2014-August 2019. According to the analysis, the time series of import and export volume was estimated by VAR because it was relatively stable, and transshipment cargo was non-stationary, but it has cointegration relationship (long-term equilibrium) with economic scale, interest rate, and economic fluctuation, so estimated by the VEC model. The estimation results show that ARIMA is superior in the stationary time-series data (local cargo) and transshipment cargo with a trend are more predictable in estimating by the multivariate model, the VEC model. Import-export cargo, in particular, is closely related to the size of our country's economy, and transshipment cargo is closely related to the size of the Chinese and American economies. It also suggests a strategy to increase transshipment cargo as the size of China's economy appears to be closer than that of the U.S.

• Environmental and Resource Economics Review
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• v.25 no.2
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• pp.141-178
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• 2016

This paper, using AMR (Automatic Meter Reading) electricity data accurately measured in real time, analyses the characteristics and patterns of temperature effect on the industrial electricity usage. For this goal, the paper constructs and estimates a model which captures the properties of AMR time series including long-term trends, mid-term temperature effects, and short-term special day effects. Based on the estimated temperature response function and the temperature effect, we categorize the whole industry into two groups: one group with sharp temperature effect and the other with weak temperature effect. Furthermore, the industry group with sharp temperature effect is classified into a summer peak industry group and a winter peak industry group, based on the estimates of the temperature response function. These empirical results carry practical policy implications on the real time electricity demand management.

• Journal of Korean Society of Transportation
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• v.34 no.1
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• pp.95-106
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• 2016

Air transportation demand is consistently increasing in Korea due to economic growth and low cost carriers. For this reason, airport expansion plans are being discussed in Korea. Therefore, it is essential to forecast reliable air transportation demand with adequate methods. However, most of the air transportation demand models in Korea has been developed by simple regression analysis with several dummy variables. Simple regression analysis without considering stationarity of time-series data can bring spurious outputs when a direct causal relationship between explanatory variables and dependent variable does not exist. In this paper, econometric model were developed for air transportation demand based on stationarity in time-series data. Unit root test and co-integration test are used for testing hypothesis of stationarity.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.676-686
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• 2016

This study analyzed the long term relationship between the K-REITs' lending rate and interest rate variables based on ARDL (autoregressive distributed lag) and also examined the short term relationship based on the ARDL-ECM model. In the results of the empirical test, there is a co-integration relationship among the K-REITs' lending rate, 3 year government bond (rate), 3 year government bond (rate), corporation bond (rate) (AA-, 3year) and general fund loan rate. This means that the K-REITs' lending rate is related to the long term interest rate. The corporate general fund loan rate has a significant correlation with the K-REITs' lending rate in the long term relation and short term adjustment process. The establishment of a management plan by the REITs considering the trends in the corporate general fund loan rate in the decision making process for finance sector borrowings can be practically helpful for the K-REITs.

• 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.