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The Development of Econometric Model for Air Transportation Demand Based on Stationarity in Time-series
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 Title & Authors
The Development of Econometric Model for Air Transportation Demand Based on Stationarity in Time-series
PARK, Jeasung; KIM, Byung Jong; KIM, Wonkyu; JANG, Eunhyuk;
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 Abstract
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.
 Keywords
air transportation demand;co-integration;econometric model;jeju international airport;stationarity;time series data;
 Language
Korean
 Cited by
 References
1.
Air Transport Statistics, Korea Airport Cooperation.

2.
Air Transport Statistics, Korea Civil Aviation Development Association.

3.
Andreoni A., Postorino M.N. (2006), A Multivariate ARIMA Model to Forecast Air Transport Demand, European Transport Conference, Association for European Transport.

4.
Baik S. H., Kim S. S. (2008), Estimation of Air Travel Demand Models and Elasticities for Jeju-Mainland Domestic Routes, J. Korean Soc. Transp., 26(1), Korean Society of Transportation, 51-63.

5.
Cho S. I., Choi J. S. (2005), A Monte Carlo Experiment on the Power of Augmented Dickey-Fuller Unit Root Test, Statistics Study, 10, 165-188.

6.
Economics Statistics System, Bank of Korea.

7.
Enders W. (2010), Applied Econometric Time Series, 181-199, 401-413.

8.
Hendry D.F., Juselius K. (2000), Explaning Cointegration Analysis : Part 1, The Energy Journal, International Association for Energy Economics, 0(1), 1-42.

9.
Hendry D.F., Juselius K. (2001), Explaning Cointegration Analysis : Part II, The Energy Journal, International Association for Energy Economics, 0(1), 75-120.

10.
Hur N. K., Jung J. Y., Kim S. (2009), A Study on Air Demand Forecasting Using Multivariate Time Series Models, Applied Statistics Study, 22, 1009-1017.

11.
Jeju Development Institute (2008), Airfare Reduction Plan of Jeju Route.

12.
Johnston J., Dinardo J. (1997), Econometric Methods, 57-64.

13.
Kim B. J., Lee M. H. (2008), A Study on the Future Air Traffic Demand in Busan Metropolitan Area, Journal of the Korean Society for Aviation and Aeronautics, 16, 46-57.

14.
Kim M. J., Jang G. H. (2002), Financial Time Series Analysis(2nd), 413-429.

15.
Korea Transport Institute (2012), Air Transportation Demand Forecasting and Analysis.

16.
Lee Y. H., Ryu M. Y., Choi S. H. (2009), A Study on Forecasting Air Transport Demand Between South and North Korea, J. Korean Soc. Transp., 27(2), Korean Society of Transportation, 83-91.

17.
Ministry of Land (2010), Infrastructure and Transport,, General Plan for Mid and Long-term Airport Development(4th).

18.
Ministry of Land (2014), Infrastructure and Transport, Jeju Air Transportation Demand Investigation.

19.
Park E. K., Lee K. Y., Lee C. K. (2011), Analysis of The Relationships Between Major Economic Variables and Tourism Demand Using VECM: Case of Japanese Inbound Tourists, Tourism and Leisure Study, 56, 45-64.

20.
Suryani E., Chou S., Chen C. (2010), Air Passenger Demand Forecasting and Passenger Terminal Capacity Expansion: A System Dynamics Framework, Expert Systems With Applications 37, 2324-2339. crossref(new window)

21.
Tourism knowledge information system, Korea Tourism Organization.

22.
UK Department for Transport (2011), UK Aviation Forecasts.