• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.415-423
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• 2021

Recently, an R-based point time series data validation system has been established for the statistical post processing and improvement of the National Center for AgroMeteorology-Land Atmosphere Modeling Package (NCAM-LAMP) medium-range prediction data. The time series verification system was used to compare the NCAM-LAMP with the AWS observations and GDAPS medium-range prediction model data operated by Korea Meteorological Administration. For this comparison, the model latitude and longitude data closest to the observation station were extracted and a total of nine points were selected. For each point, the characteristics of the model prediction error were obtained by comparing the daily average of the previous prediction data of air temperature, wind speed, and hourly precipitation, and then we tried to improve the next prediction data using Support Vector Machine( SVM) method. For three months from August to October 2017, the SVM method was used to calibrate the predicted time series data for each run. It was found that The SVM-based correction was promising and encouraging for wind speed and precipitation variables than for temperature variable. The correction effect was small in August but considerably increased in September and October. These results indicate that the SVM method can contribute to mitigate the gradual degradation of medium-range predictability as the model boundary data flows into the model interior.

• 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 Korea Water Resources Association
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• v.37 no.3
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• pp.185-193
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• 2004

The main purpose of this study is to investigate and evaluate the impact of climate change on the runoff and water resources of Yongdam basin. First, we construct global climate change scenarios using the YONU GCM control run and transient experiments, then transform the YONV GCM grid-box predictions with coarse resolution of climate change into the site-specific values by statistical downscaling techniques. The values are used to modify the parameters of the stochastic weather generator model for the simulation of the site-specific daily weather time series. The weather series fed into a semi-distributed hydrological model called SLURP to simulate the streamflows associated with other water resources for the condition of $2CO_2$. This approach is applied to the Yongdam dam basin in southern part of Korea. The results show that under the condition of $2CO_2$, about 7.6％ of annual mean streamflow is reduced when it is compared with the observed one. And while Seasonal streamflows in the winter and autumn are increased, a streamflow in the summer is decreased. However, the seasonality of the simulated series is similar to the observed pattern.

• The Southeast Asian review
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• v.27 no.4
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• pp.41-76
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• 2017

This paper analyses the market shares and the export similarity indexes (ESI) of Korea, Japan and China in ASEAN, and then identifies the determinants of Korea's exports to ASEAN countries using single equation cointegration approaches, such as fully modified OLS (FMOLS), dynamic OLS (DOLS), and canonical cointegration regression (CCR). Various regression results are as follows: As expected, Korea's real exports tend to increase as importing country's GDP grows. The competing third country's currency depreciation affects Korea's exports differently from country to country. Most notably, it doesn't significantly affect Korean exports in Malaysia, Indonesia and Thailand. These results suggest that bilateral or third country exchange rates are not that important or decisive factors to determine Korea's exports to ASEAN countries in the long-run while economic growth in ASEAN countries matters most.

• Journal of Technology Innovation
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• v.25 no.1
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• pp.61-89
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• 2017

This study aims to estimate empirically the respective impacts of R&D expenditure, R&D labor, overseas direct investment, commodity trade balance, and technology trade openness on technology balance of payments. To examine the presence of co-integration between them, this paper employed the ARDL-bounds test using time series data from 1981 to 2014, and the result shows that there is a stable long-run equilibrium relationship among them. Furthermore, we estimated long- and short-run coefficients of the technology balance of payments with respect to each variables based on long-run equilibrium equation and error correction model. As a result, the technology balance of payments respond negatively to R&D labor and technology trade openness, and R&D expenditure does produce positive effects in the long-run, while coefficients of overseas direct investment and commodity trade balance in the long-run are not statistically significant. Besides, according to results of error correction model, overseas direct investment only has clearly a positive effects in the short-run, in contrast, the short-term relationships between the other variables and the technology balance of payments could not definitively derived. This implies that it is necessary to procure and cultivate talented personnel, as well as to enlarge gradually technology trade size in order to improve technology balance of payments from a long-term point of view.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.453-459
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• 2021

The system marginal price of electricity is the amount paid to all the generating units, which is an important decision-making factor for the construction and maintenance of an electrical power unit. In this paper, we suggest a long-term forecasting model for calculating the system marginal price based on prices of natural gas and oil. As most variables used in the analysis are nonstationary time series, the long run relationship among the variables should be examined by cointegration tests. The forecasting model is similar to an error correction model which consists of a long run cointegrating equation and another equation for short run dynamics. To mitigate the robustness issue arising from the relatively small data sample, this study employs various testing and estimating methods. Compared to previous studies, this paper considers multiple fuel prices in the forecasting model of system marginal price, and provides greater emphasis on the robustness of analysis. As none of the cointegrating relations associated with system marginal price, natural gas price and oil price are excluded, three error correction models are estimated. Considering the root mean squared error and mean absolute error, the model based on the cointegrating relation between system marginal price and natural gas price performs best in the out-of-sample forecast.

• KDI Journal of Economic Policy
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• v.35 no.2
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• pp.107-131
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• 2013

In this paper, we test and estimate the stochastic non-fundamental trend in Korean stock market. For this, following Kim (2011), we exploit that the long-run equilibrium stock price may be decomposed into fundamental and stochastic non-fundamental trends (i.e., the sum of dividend innovations and a part that are orthogonal with the dividend innovations) by using the Beveridge-Nelson decomposition and projections. In this VAR construction, there is an error correction mechanism through which stock prices converge to their long-run equilibrium, which also contain the stated stochastic non-fundamental trend as well as fundamental trend. The estimation and test results using yearly data from the Korea (1976-2012) indicated that fluctuations in stock prices during that period can be explained mainly not by the stochastic non-fundamental trend but by the dividend trend. However, during some periods like after Seoul Olympic Games, we may observe the non-fundamental trend affected to the stock price variation.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.1
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• pp.37-45
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• 2015

Recent droughts in South Korea have had large economic and environmental impacts across the country. Changes in rainfall and hydrologic patterns due to climate change can potentially increase the occurrence of extreme droughts and affect the future availability of water resources. Therefore, it is necessary to evaluate drought vulnerability for water resources planning and management, and identify the appropriate mitigation actions to conduct a drought risk analysis in the context of climate change. The objective of this study is changes in the temporal trends of drought characteristics in South Korea to examine drought impacts under climate change. First, the changes of drought occurrence were analyzed by applying the Standardized Precipitation Evapotranspiration Index (SPEI) for meteorological data on 54 meteorological stations, and were analyzed for the past 30 years (1981-2010), and Representative Concentration Pathways (RCP) climate change scenarios (2011-2100). Second, the changes on the temporal trends of drought characteristics were performed using run theory, which was used to compare drought duration, severity, and magnitude to allow for quantitative evaluations under past and future climate conditions. These results show the high influence of climate change on drought phenomenon, and will contribute to water resources management and drought countermeasures to climate change.

• Journal of Korea Port Economic Association
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• v.38 no.2
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• pp.153-164
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• 2022

In this study, we estimate the quantile-regression framework of the shipping industry for the Capesize used ship, which is a typical raw material transportation from January 2000 to December 2021. This research aims two main contributions. First, we analyze the relationship between the Capesize used ship, which is a typical type in the raw material transportation market, and the freight market, for which mixed empirical analysis results are presented. Second, we present an empirical analysis model that considers the structural transformation proposed in the Hyunsok Kim and Myung-hee Chang(2020a) study in quantile-regression. In structural change investigations, the empirical results confirm that the quantile model is able to overcome the problems caused by non-stationarity in time series analysis. Then, the long-run relationship of the co-integration framework divided into long and short-run effects of exogenous variables, and this is extended to a prediction model subdivided by quantile. The results are the basis for extending the analysis based on the shipping theory to artificial intelligence and machine learning approaches.

• Review of Culture and Economy
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• v.21 no.3
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• pp.59-88
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• 2018

This study examines demand of the Korean TV VOD using monthly aggregate data and time series analysis models. In particular, the impact of box office attendance, number of IPTV subscribers, income and price of substitutes on TV VOD market is analyzed. Data on TV VOD download during the period 2013 January to 2018 June are used for the empirical analysis. TV VOD demand shows lower level of seasonality than box office attendance and the share of monthly top1 movie in TV VOD platform is also lower than that of box office attendance. The relationship between a movie's holdback and box office performance does not seem consistent. The empirical result of ARDL model reveals that in the short-run box office attendance, number of IPTV subscribers and price of substitutes have significant impact on TV VOD demand. The result on the long-term relation shows that income is the only determinant of TV VOD demand. The impact of box office attendance on TV VOD is not shown to be robust both for the short-term and long-term.