Econometric Forecasting Models for Air Traffic Passenger of Indonesia
Viktor Suryan(1*)
(1) Researcher and Engineer
(*) Corresponding Author
Abstract
One of the major benefits of the air transport services operating in bigger countries is the fact that they provide a vital social economic linkage. This study is an attempt to establish the determinants of the passenger air traffic in Indonesia. The main objective of the study is to determine the economic variables that affect the number of airline passengers using the econometrics model of projection with an emphasis on the use of panel data and to determine the economic variables that affect the number of airline passengers using the econometrics model of projection with an emphasis on the use of time series data. This research also predicts the upcoming number of air traffic passenger until 2030. Air transportation and the economic activity in a country are interdependent. This work first uses the data at the country level and then at the selected airport level for review. The methodology used in this study has adopted the study for both normal regression and panel data regression techniques. Once all these steps are performed, the final equation is taken up for the forecast of the passenger inflow data in the Indonesian airports. To forecast the same, the forecasted numbers of the GDP (Gross Domestic Product) and population (independent variables were chosen as a part of the literature review exercise) are used. The result of this study shows the GDP per capita have significant related to a number of passengers which the elasticity 2.23 (time-series data) and 1.889 for panel data. The exchange rate variable is unrelated to a number of passengers as shown in the value of elasticity. In addition, the total of population gives small value for the elasticity. Moreover, the number of passengers is also affected by the dummy variable (deregulation). With three scenarios: low, medium and high for GDP per capita, the percentage of growth for total number of air traffic passenger from the year 2015 to 2030 is 199.3%, 205.7%, and 320.9% respectively.
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Angkasa Pura II, 2015. Data of Air Traffic Passenger.
de Dios Ortúzar, J. & Simonetti, C., 2008. Modelling the Demand for Medium Distance Air Travel with the Mixed Data Estimation Method. Journal of Air Transport Management, 14(6), pp. 297-303.
Directorate General Civil Aviation Website, 2016. Air Traffic Data (Domestic and International). [Online]
Available at: http://hubud.dephub.go.id/?id/llu/index/filter:category,0
Faisal, 2002. Analisis Time Series Lalulintas Angkutan Udara Internasional di Indonesia.
Fu, X., Oum, T. H. & Zhang, A., 2010. Air Transport Liberalization and It's Impacts on Airline Competition and Air Passenger Traffic. Transportation Journal, pp. 24-41.
Henderson, J., 2009. Transport and Tourism Destination Development: An Indonesian Perspective. Tourism and Hospitality Research, 9(3), pp. 199-208.
Hill, R. C., Griffiths, W. E. & Judge, G. G., 2001. Undergraduate Econometrics. 2nd Edition ed. New Jersey: Jhon Wiley & Sons, Inc.
IATA, 2016. Exchange Rates and Aviation: Examining the Links. [Online]
Available at: https://www.iata.org/publications/economicbriefings/FX%20impacts%20on%20airlines%20(Dec%202015).pdf
Indonesia Bureau Statistic, 2016. Air Passenger Traffic Data Year 2003-2014 (Domestic). [Online]
Available at: https://www.bps.go.id/linkTabelStatis/view/id/1402
Indonesia Bureau Statistic, 2016. Indonesia GDP per Capita (Province). [Online]
Available at: https://www.bps.go.id/linkTabelStatis/view/id/1623
Lasmita, C. Y., 2010. The Patterns of Air Traffic Movements in Adi Sutjipto Airport.
Mubarak, T., 2014. Airport Passenger Demand Forecasting Using Radial Basic Function Neural Networks.
Profillidis, V. A., 2000. Econometric and Fuzzy Models for the Forecast of Demand in the Airport of Rhodes. Journal of Air Transport Management, Volume 6, pp. 95-100.
Saraswati, B. & Hanaoka, S., 2013. Aviation Policy in Indonesia and Its Relation to ASEAN Single Aviation Market. Journal of the Eastern Asia Society for Transportation Studies, Volume 10, pp. 2161-2176.
Wadud, Z., 2011. Modelling and Forecasting Passenger Demand for a New Domestic Airport with Limited Data. Transportation Research Record: Journal of the Transportation Research Board, pp. 59-68.
Wadud, Z., 2013. Simultaneous Modelling of Passenger and Cargo Demand at an Airport. Transportation Research Record: Journal of the Transportation Research Board, pp. 63-74.
Wang, B. et al., 2014. Future Change of Asian-Australian Monsoon Under RCP 4.5 Anthropogenic Warming Scenario. Climate Dynamics, 42(1-2), pp. 83-100.
World Bank, 2016. Air Transport, Passenger Carried. [Online]
Available at: http://data.worldbank.org/indicator/IS.AIR.PSGR
World Bank, 2016. East Asia and Pacific (Real GDP Growth). [Online]
Available at: http://www.worldbank.org/en/publication/global-economic-prospects
World Bank, 2016. Indonesia GDP per capita (constant LCU). [Online]
Available at: http://data.worldbank.org/indicator/NY.GDP.PCAP.KN?locations=ID
World Bank, 2016. Indonesia Population, Total. [Online]
Available at: http://data.worldbank.org/indicator/SP.POP.TOTL?locations=ID
World Bank, 2016. Offcial Exchange Rate (LCU per US$, period average). [Online]
Available at: http://data.worldbank.org/indicator/SP.POP.TOTL?locations=ID
Xiaowen, F., Hoon Oum, T. & Zhang, A., 2010. Air Transport Liberalization and Its Impacts on Airline Competition and Air Passenger Traffic. Transportation Journal, 49(4), pp. 24-41.
DOI: https://doi.org/10.22146/jcef.26594
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