• 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.

• KDI Journal of Economic Policy
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• v.11 no.3
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• pp.39-59
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• 1989

본고(本稿)는 Sims가 개발한 방법을 이용하여 우리나라와 같이 경제구조(經濟構造)가 급히 변하는 상황에서의 경제예측(經濟豫測)의 정확도(正確度)를 제고하고자 하는 시도의 일환이다. 본고(本稿)는 예측자의 사전신뢰(事前信賴)를 이용하여 계수의 값에 대하여 사전제약(事前制約)을 부과(賦課)하고 시간변동(時間變動)을 허용하는 변동계수(變動係數)벡타자귀(自歸)(TBVAR)모형(模型)의 추정방법뿐만 아니라 사전제약(事前制約)의 모수(母數)를 선택하는 방법과 오차(誤差)의 분산(分散)이 자기회귀(自己回歸)할 경우의 대처방법 등 예측(豫測)의 정확도(正確度)를 제고시키는 데 실제 사용되는 방법을 설명하고, 6변수모형(變數模型)을 이용하여 TBVAR 모델의 정확도(正確度)를 타(他) 모델과 비교한다. 정부건설(政府建設), 총통화(總通貨), 사채시장이자율(社債市場利子率), 민간건설(民間建設), 실질(實質)GNP 및 소비자(消費者) 물가지수(物價指數) 등 6변수(變數)에 대한 예측의 정확도를 "타일 U"값을 기준으로 비교할 때 TBVAR은 시간변동(時間變動)을 고려하지 않고 사전제약(事前制約)만 적용한 BVAR이나 사전제약(事前制約)도 적용하지 않은 VAR보다 대부분의 변수의 예측에 있어 더 정확하며 민간건설(民間建設)을 제외하고는 OLS보다 예측오차(豫測誤差)가 작게 나타난다.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.799-807
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• 2011

This study investigates long and short run responses of variables to exogenous shocks by imposing prior restrictions on a contemporaneous structural shock coefficient matrix of the model to identify shocks by endogenous variables in the vector autoregression. The relative importance of each structural shock in variation of each variable is calculated through the identification of proper restrictions (not based on any specific theory but on researcher judgment corresponding to actual situations) and an estimation of the structural vector autoregression. The results of the analyses are found to maintain consistency.

• KDI Journal of Economic Policy
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• v.29 no.2
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• pp.1-40
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• 2007

This paper mainly estimates a trajectory of GDP induced by variations in fiscal expenditure and taxation policy using three variable structural VAR models. By assigning different combinations of identifying restrictions on the disturbances and measuring the corresponding fiscal multipliers, we compare how robust the estimated values of fiscal multipliers are with respect to the restrictions. Then, considering the dependency of Korean economy on the foreign sector, we extend the three variable SVARs to four variable ones by adding a variable reflecting external shocks. Empirical analyses into the Korean quarterly data (from 1979 to 2000) with the three variable SVARs reveal that the size and the significance of the estimated fiscal multipliers in Korea are very small and low or they decay very fast. Results from the four variable SVARs confirm these results while the significance of the effectiveness of fiscal policy is enhanced in some cases.

• Journal of the Korean Data and Information Science Society
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• v.22 no.3
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• pp.401-412
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• 2011

This study uses a vector error correction model to analyze the daily time series data of the spot price of EUA (European Union Allowance). As endogenous variables, five variables are considered for the analysis, including prices of crude oil, natural gas, electricity and coal in addition to carbon price. Data period is Phase 2 period (April 21, 2008 to March 31, 2010) to avoid Phase 1 period (2005-2007) where the EUA prices were distorted. Unit-root and cointegration test results reveal that all variables have a unit root and cointegration vectors exist, so a vector error correction model is adopted instead of a vector autoregressive model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.2
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• pp.245-256
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• 2024

Since 2020, quantitative easing and easy money policies have been implemented for the purpose of economic stimulus. As a result, real estate prices have skyrocketed. In this study, the relationship between sales and rental prices by housing type during the period of soaring real estate prices in Busan was analyzed spatio-temporally. Based on the actual transaction price data, housing type, transaction type, and monthly data of district units were constructed. Among the spatio-temporal analysis models, the SpVAR, which is used to understand the temporal and spatial effects of variables, and the GSTAR, which is used to understand the effects of each region on those variables, were used. As a result, the sales price of apartment had positive effect on the sale price of apartment, row house, and detached house in the surrounding area, including the target area. On the other hand, it was confirmed that demand was converted to apartment rental due to an increase in apartment sales prices, and the sale price fell again over time. The spatio-temporal spillover effect of apartments was positive, but the positive effect of row house and detached house were concentrated in the original downtown area.

• Environmental and Resource Economics Review
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• v.33 no.2
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• pp.135-157
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• 2024

In this study, we analyzed the changes in copper consumption according to copper price fluctuations and identified the domestic copper price elasticity. A total of 408 time series data from January 1989 to December 2022 were analyzed using the vector autoregressive (VAR) model with net import volume, price, and production index as variables. In addition, to identify changes in the correlation between variables over time, the dynamic relationship between variables was identified using the time-varying vector autoregressive (TV-VAR) model. As a result of the analysis, it was confirmed that the negative price elasticity for copper is -0.1835. In addition, the interquartile range was -0.3130 ~ 0.0886, with no consistent trend over time, but mainly negative elasticity. This study can be used to quantify the expected impact of various policy proposals and changes related to minerals.

• KDI Journal of Economic Policy
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• v.14 no.1
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• pp.121-145
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• 1992

This paper examines characteristics of time series data related to the construction investment(stationarity and time series components such as secular trend, cyclical fluctuation, seasonal variation, and random change) and surveys predictibility, fitness, and explicability of independent variables of various models to build a short-term construction investment forecasting model suitable for current economic circumstances. Unit root test, autocorrelation coefficient and spectral density function analysis show that related time series data do not have unit roots, fluctuate cyclically, and are largely explicated by lagged variables. Moreover it is very important for the short-term construction investment forecasting to grasp time lag relation between construction investment series and leading indicators such as building construction permits and value of construction orders received. In chapter 3, we explicate 7 forecasting models; Univariate time series model (ARIMA and multiplicative linear trend model), multivariate time series model using leading indicators (1st order autoregressive model, vector autoregressive model and error correction model) and multivariate time series model using National Accounts data (simple reduced form model disconnected from simultaneous macroeconomic model and VAR model). These models are examined by 4 statistical tools that are average absolute error, root mean square error, adjusted coefficient of determination, and Durbin-Watson statistic. This analysis proves two facts. First, multivariate models are more suitable than univariate models in the point that forecasting error of multivariate models tend to decrease in contrast to the case of latter. Second, VAR model is superior than any other multivariate models; average absolute prediction error and root mean square error of VAR model are quitely low and adjusted coefficient of determination is higher. This conclusion is reasonable when we consider current construction investment has sustained overheating growth more than secular trend.

• International Area Studies Review
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• v.16 no.1
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• pp.3-27
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• 2012

This paper adopts recently developed panel unit root test that is cross-sectionally robust. Cointegration test is also used to find whether regional house prices are in line with gross regional domestic production (GRDP) in the long run in Korea during 1989-2009. Based on the panel VECM and the panel ARDL models, we examine causal relationships among the variables and estimate the long-run elasticity. We find evidence of cointegration and bidirectional causal relationships between regional house prices and GRDP. The results of long-run estimates, using both fixed effect and ARDL models, show that house prices positively and significantly influence on the GRDP and vice versa. Together with these results, the findings of ARDL-ECM imply that there exists a long-run equilibrium relationship between house prices and regional economic variables even if there is a possibility of short-run deviation from its long-run path.

• The Korean Journal of Financial Management
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• v.26 no.1
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• pp.1-29
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• 2009

As foreign investors' share holdings in Korean firms have dramatically increased since 1998 following the financial deregulation on the limit of foreign stock investment, the concern over the negative impacts the foreign investors would bring on the firms' financial policy has been growing too. Foreign investors were perceived to require the firms of excessive payments of cash dividends sometimes with threat of hostile takeover trials detering the firm from investing its cash flow in the physical facilities and RandD eroding their potential growth capabilities. We examine the impact of foreign investment on the firms' dividend policy using 234 listed firms' panel data over the sample periods of 1998 to 2005 employing various panel regression methodology. Foreign shareholders are found not to be related or even negatively related to the payout ratio(dividend/net income), but positively and statistically significantly related to the ratio of cash dividends to book of asset, negatively to the dividend yields. Considering the payout ratio is the most appropriate measure for the dividend payment, we can not support the arguments that the foreign investors' holdings have induced the excessive dividend level in Korean firms.