• Journal of the Korean Data and Information Science Society
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• v.11 no.2
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• pp.257-267
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• 2000

The purpose of this study is to analyse the economic effects of General Elections in Korea, in other words, to test the Political Business Cycle hypothesis using ARIMA-Intervention Analysis.

• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.725-732
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• 2016

This study analyzes the number of Jeju-bound tourists according to travellers' purposes. We classify the travellers' purposes into three categories: "Rest and Sightseeing", "Leisure and Sport", and "Conference and Business". To see an impact of MERS outbreak occurred in May 2015 on the number of tourists, we fit seasonal ARIMA-Intervention model to the monthly arrivals data from January 2005 to March 2016. The estimation results show that the number of tourists for "Leisure and Sport" and "Conference and Business" were significantly affected by MERS outbreak whereas arrivals for "Rest and Sightseeing" were little influenced. Using the fitted models, we predict the number of Jeju-bound tourists.

• Journal of Korea Port Economic Association
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• v.32 no.2
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• pp.25-37
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• 2016

The economy of South Korea has experienced two financial crises: the 1997 Asian financial crisis and the 2008 global financial crisis. These crises had a significant impact on the nation's macro-economic indicators. Furthermore, they had a profound influence on container traffic in container ports in Busan, which is the largest port in South Korea in terms of TEUs handled. However, the impact of the Asian financial crisis on container throughput is not clear. In this study, we assume that the two financial crises are independent and different, and then analyze how each of them impacted container throughput in Busan ports. To perform this analysis, we use an intervention model that is a special type of ARIMA model with input series. Intervention models can be used to model and forecast a response series and to analyze the impact of an intervention or event on the series. This study focuses on the latter case, and our results show that the impacts of the financial crises vary considerably.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.65-76
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• 2014

Housing prices are influenced by external shock factors such as real estate policy or economy. Thus, the intervention effect is important for the development of forecasting model for housing price index. In this paper, we examined the degree of effective power of external shock factors for forecasting housing price index and analyzed time series models for efficient forecasting of housing price index. It is shown that intervention models are better than other models in forecasting results using real data based on the accuracy criteria.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1715-1721
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• 2011

For an efficient railroad operations the demand forecasting is required. Time series models can quickly forecast the future demand with fewer data. As well as the accuracy of forecasting is excellent compared to other methods. In this study is proposed the intervention ARIMA model for forecasting methods of KTX passenger demand. The intervention ARIMA model may reflect the intervention such as the Kyongbu high-speed rail project second phase. The simple seasonal ARIMA model is predicted to overestimate the KTX passenger demand. However, intervention ARIMA model is predicted the reasonable results. The KTX passenger demands were predicted to be a week units separated by the weekday and weekend.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.719-731
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• 2017

In September 2010, the Korea government increased the speed limit on the Gyeongbu Expressway (Cheonan IC.-Yangjae IC) from 100 to 110 km per hour. This paper considers ARIMA-Intervention model to analyze the effects of the speed limit change on the incidences of traffic accidents and injuries. In addition, in order to investigate the effects more clearly, we also analyze the difference between the two lines of Cheonan IC-Yangjae IC and Busan IC-Cheonan IC. As a result, we observe that the numbers of accidents and injuries have increased after the speed limit change. The increases are strikingly distinctive in comparison to other lines (Busan IC-Cheonan IC) where there have been no changes in the maximum speed limit.

• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.237-252
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• 2013

An estimation model for premiums and components is essential to determine reasonable insurance premiums. In this study, we introduce diverse models for the estimation of property damage premiums(premium, depth and frequency) that include a regression model using a dummy variable, additive independent variable model, autoregressive error model, seasonal ARIMA model and intervention model. In addition, the actual property damage premium data was used to estimate the premium, depth and frequency for each model. The estimation results of the models are comparatively examined by comparing the RMSE(Root Mean Squared Errors) of estimates and actual data. Based on real data analysis, we found that the autoregressive error model showed the best performance.

• Journal of the Korea Computer Industry Society
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• v.4 no.12
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• pp.1033-1042
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• 2003

In this study, the economic population prediction by computer simulation has been studied by using statistical model. The forecast of future population based on that of the past is a very difficult problem as uncertain conditions are modeled in it. Even if a thought forecast is possible, world-wide cultures and the local culture emotion the cultures of the world and out country can not be predicted due to rapid change and the estimation of population is ‘nowadays more and more’ difficult to be made good guess. In the estimation of economic population, by using the census population from 1960 to 1990, and using ARIMA model developed by Box and Jenkins, the estimation has been done on the economic population until 2021 according to age as appeared table and appendix. This kind of forecast would have both good point and weak point of ARIMA model theory saying that prediction can be done only by the economic population.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.458-468
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• 2019

This research attempted to estimate monthly sales of food and beverage at the passenger terminal of Incheon int'l airport from June of 2015 to December 2020. This paper used ARIMA-Intervention model which can estimate the change of the sales amount suggesting the predicted monthly food and beverage sales revenue. The intervention variable was travel-ban policy against south Korea from P.R. China since July 2016 to December 2017 due to THAAD in south Korea. According to ARIMA, it was found normal predicted sales amount showed the slow growth increase rate until 2020 due to the effect of intervened variable. However, the monthly food sales in July and August 2019 was 20.3 and 21.2 billion KRW respectively. Each amount would increase even more in 2020 and the amount would increase to 21.4 and 22.1 billion KRW. The sales amount in 2019 would be 7.7 and 8.1 billion KRW and climb up 7.9 and 8.2 billion KRW in 2020. It was expected LCC passengers tend to spend more money for F&B at airport due to no meal or drink service of LCC or the paid-in meal and beverage service of LCC. The growth of sales of food and beverate will be accompanied with the growth of LCC according to estimated data.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.546-554
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• 2018

The Bulk market, unlike the line market, is characterized by stiff competition where certain ship or freight owners have no influence on freight rates. However, freights are subject to macroeconomic variables and economic external shock which should be considered in determining management or chartering decisions. According to the results analyzed by use of ARIMA Inventiom model, the impact of the financial crisis was found to have a very strong bearing on the BDI index. First, according to the results of the VEC model, the libor rate affects the BDI index negatively (-) while exchange rate affects the BDI index by positively (+). Secondly, according to the results of the VEC model's J ohanson test, the order ship volume affects the BDI index by negatively (-) while China's economic growth rate affects the BDI index by positively (+). This shows that the shipping company has moved away from the simple carrier and responded appropriately to changes in macroeconomic variables (economic fluctuations, interest rates and exchange rates). It is believed that the shipping companies should be more aggressive in its "trading" management strategy in order to prevent any unfortunate situation such as the Hanjin Shipping incident.