• Title/Summary/Keyword: Intervention-ARIMA

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A Study on the Air Travel Demand Forecasting using ARIMA-Intervention Model (Event Intervention이 일본, 중국 항공수요에 미치는 영향에 관한 연구)

  • Kim, Seon Tae;Kim, Min Su;Park, Sang Beom;Lee, Joon Il
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.21 no.4
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    • pp.77-89
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    • 2013
  • The purpose of this study is to anticipate the air travel demands over the period of 164 months, from January 1997 to August 2010 using ARIMA-Intervention modeling on the selected sample data. The sample data is composed of the number of the passengers who in the domestic route for Jeju route. In the analysis work of this study, the past events which are assumed to have affected the demands for the air travel routes to Jeju in different periods were used as the intervention variables. The impacts of such variables were reflected in the presupposed demand. The intervention variables used in this study are, respectively, the World Cup event in 2002 (from May to June), 2003 SARS outbreak (from April to May), Tsunami in January 2005, and the influenza outbreak from October to December 2009. The result of the above mentioned analysis revealed that the negative intervention events, like a global outbreak of an epidemic did have negative impact on the air travel demands in a risk aversion by the users of the aviation services. However, in case of the negative intervention events in limited area, where there are possible substituting destinations for the tourists, the impact was positive in terms of the air travel demands for substituting destinations due to the rational expectation of the users as they searched for other options. Also in this study, it was discovered that there is not a binding correlation between a nation wide mega-event, such as the World Cup games in 2002, and the increased air travel demands over a short-term period.

A Study on the Outliers Detection in the Number of Railway Passengers for the Gyeongbu Line From Seoul to Major Cities Using a Time Series Outlier Detection Technique (시계열 이상치 탐지 기법을 활용한 경부선 주요도시 철도 승객수의 이상치 탐색 연구)

  • LEE, Jiseon;YOON, Yoonjin
    • Journal of Korean Society of Transportation
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    • v.35 no.6
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    • pp.469-480
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    • 2017
  • On April 1, 2004, KTX (Korea Train eXpress), the first HSR (High-Speed Rail) in Korea, was introduced to Gyeongbu Line. The introduction of the KTX service led to a change in the number of passengers for Gyeongbu Line. Previous studies have analyzed the pre and post-event changes of the intervening events by either simple statistics or intervention ARIMA analysis. However, the intervention ARIMA model has a limitation that several assumptions such as the occurrence time and the type of intervention events are necessary. To this end, this study analyzed the effects of intervention event on the number of passengers using the Gyeongbu line based on a time series outlier detection technique which can overcome limitations in the previous studies. The time series outlier detection technique can analyze the time, effect type and size of an intervention event without the assumption of the time and effect type of the intervention event. The data were collected from the Korea Transport Database (KTDB) for twelve years from 2003 to 2014 (144 months). The analysis results showed that the size of the influence type in the same intervention events was different across the major city routes, and the intervention event which could not be found by previous study methods was also found.

Forecasting and Analysis of Air Meteorological Service Charge using ARIMA-Intervention Time Series Model (ARIMA-개입모델을 이용한 항공기상정보 사용료 징수액 추정 및 적정성 연구)

  • Kim, Kwang-Ok;Park, Sung-Sik
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.26 no.3
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    • pp.9-22
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    • 2018
  • Korea meteorological administration(KMA) has started to levy air meteorological service charge on both national and foreign carriers since 2005. The charge has grown on 2010 and 2014 twice. However, KMA has still kept asking airlines to agree with another increase in the charge due to the low cost of goods recovery ratio of 7%. The air meteorological charge has changed from 2,210 KRW at the beginning to 11,400 KRW as of June 2018. According to ARIMA intervention time series analysis, it was proven national carriers would make a payment of 831 million KRW 2018 and 1,024 million KRW 2019, showing 186.2% and 123.2% increase compared to last year respectively. The total amount of charge for both national LCC and foreign airlines was aggregated up to 1,952 million KRW 2019, 227% bigger than the charge paid at 2017. Considering the 50% increase of consumer price index last decade, the increased charge would impair the global competitiveness of national carriers. It could be suggested that current air meteorological charge scheme be improved to apply overseas trend and for national carriers to have a competitive advantage in global aviation market.

Effects of maximum speed limit on Gyeongbu Expressway (경부고속도로 최고제한속도 상향에 따른 교통사고 영향 분석)

  • Song, Yinhua;Seong, Byeongchan
    • 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.

Intervention Analysis of Korea Tourism Data (개입모형을 이용한 한국의 입출국자 수의 분석)

  • Kim, Su-Yong;Seong, Byeong-Chan
    • The Korean Journal of Applied Statistics
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    • v.24 no.5
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    • pp.735-743
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    • 2011
  • This study analyzes inbound and outbound Korea tourism data through an intervention model. For the analysis, we adopt three intervention factors: (1) IMF bailout crisis in December 1997, (2) Severe Acute Respiratory Syndrome(SARS) outbreak in March 2003, and (3) Lehman Brothers bankruptcy in September 2008. The empirical results show that only the SARS factor lowered inbound tourism from April 2003 with a drastic decline in May 2003 and gradually decaying since then. However, all three factors significantly lowered tourism in the case of outbound tourism. Especially, the effect of the IMF is shown to be permanent from December 1997 and the effects of SARS and the Lehman Brothers bankruptcy abrupt and temporary with a gradual decay.

A Forecast of Shipping Business during the Year of 2013 (해운경기의 예측: 2013년)

  • Mo, Soo-Won
    • Journal of Korea Port Economic Association
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    • v.29 no.1
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    • pp.67-76
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    • 2013
  • It has been more than four years since the outbreak of global financial crisis. However, the world economy continues to be challenged with new crisis such as the European debt crisis and the fiscal cliff issue of the U.S. The global economic environment remains fragile and prone to further disappointment, although the balance of risks is now less skewed to the downside than it has been in recent years. It's no wonder that maritime business will be bearish since the global business affects the maritime business directly as well as indirectly. This paper, hence, aims to predict the Baltic Dry Index representing the shipping business using the ARIMA-type models and Hodrick-Prescott filtering technique. The monthly data cover the period January 2000 through January 2013. The out-of-sample forecasting performance is measured by three summary statistics: root mean squared percent error, mean absolute percent error and mean percent error. These forecasting performances are also compared with those of the random walk model. This study shows that the ARIMA models including Intervention-ARIMA have lower rmse than random walk model. This means that it's appropriate to forecast BDI using the ARIMA models. This paper predicts that the shipping market will be more bearish in 2013 than the year 2012. These pessimistic ex-ante forecasts are supported by the Hodrick-Prescott filtering technique.

Impact of District Medical Insurance Plan on Number of Hospital Patients: Using Box-Jenkins Time Series Analysis (Box-Jenkins 시계열 분석을 이용한 지역의료보험 실시가 병원 환자 수에 미친 영향)

  • Kim, Yong-Jun;Chun, Ki-Hong
    • Journal of Preventive Medicine and Public Health
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    • v.22 no.2 s.26
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    • pp.189-196
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    • 1989
  • In January 1988, district medical insurance plan was executed on a national scale in Korea. We conducted an evaluation of the impact of execution of district medical insurance plan on number of hospital patients: number of outpatients; and occupancy rate. This study was carried out by Box-Jenkins time series analysis. We tested the statistical significance with intervention component added to ARIMA model. Results of our time series analysis showed that district medical insurance plan had a significant effect on the number of outpatients and occupancy rate. Due to this plan the number of outpatients had increased by 925 patients every month which is equivalent to 8.3 percents of average monthly insurance outpatients in 1987, and occupancy rate had also increased by 0.12 which is equivalent to 16 percents of that in 1987.

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Prediction of Electricity Sales by Time Series Modelling (시계열모형에 의한 전력판매량 예측)

  • Son, Young Sook
    • The Korean Journal of Applied Statistics
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    • v.27 no.3
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    • pp.419-430
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    • 2014
  • An accurate prediction of electricity supply and demand is important for daily life, industrial activities, and national management. In this paper electricity sales is predicted by time series modelling. Real data analysis shows the transfer function model with cooling and heating days as an input time series and a pulse function as an intervention variable outperforms other time series models for the root mean square error and the mean absolute percentage error.

Forecasts of the BDI in 2010 -Using the ARIMA-Type Models and HP Filtering (2010년 BDI의 예측 -ARIMA모형과 HP기법을 이용하여)

  • Mo, Soo-Won
    • Journal of Korea Port Economic Association
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    • v.26 no.1
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    • pp.222-233
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    • 2010
  • This paper aims at predicting the BDI from Jan. to Dec. 2010 using such econometric techniues of the univariate time series as stochastic ARIMA-type models and Hodrick-Prescott filtering technique. The multivariate cause-effect econometric model is not employed for not assuring a higher degree of forecasting accuracy than the univariate variable model. Such a cause-effect econometric model also fails in adjusting itself for the post-sample. This article introduces the two ARIMA models and five Intervention-ARIMA models. The monthly data cover the period January 2000 through December 2009. The out-of-sample forecasting performance is compared between the ARIMA-type models and the random walk model. Forecasting performance is measured by three summary statistics: root mean squared error (RMSE), mean absolute error (MAE) and mean error (ME). The RMSE and MAE indicate that the ARIMA-type models outperform the random walk model And the mean errors for all models are small in magnitude relative to the MAE's, indicating that all models don't have a tendency of overpredicting or underpredicting systematically in forecasting. The pessimistic ex-ante forecasts are expected to be 2,820 at the end of 2010 compared with the optimistic forecasts of 4,230.