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Econometric Modeling of Passenger Demand for International Air Transport in Nigeria Airports

Received: 29 June 2017     Accepted: 27 July 2017     Published: 25 August 2017
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Abstract

The paper is aimed at examining the econometric modeling of passenger demand for international air transport in Nigeria Airports with the objective of examining the relationship between the international passenger demand in Nigeria airports and economic variables. 91.2% of the dependent variable can be well explained by the independent variables and the unexplained variables or the error term is 8.8%. The fact that the coefficient of explanation (R Square) is very high, this is a sign that there is a problem of multicolinearity and the Durbin Watson value (3.443) which is greater than 2 also signifies there is a problem of autocorrelation or serial correlation. The significance level of the computed test statistics is 1.29 which is more than the significance level (0.05), hence we cannot reject the null hypothesis which states that there is no statistical significant relationship between % change in international Passenger Traffic (Annual) and % change in economic indicators (Consumer Inflation Price (CPI), Naira value to Dollar and Gross Domestic Product). It is therefore concluded that the economic indicators cannot give a good forecast of international air transport demand because the model suffers from serial correlation, multicolinearity and insignificance of the test.

Published in American Journal of Traffic and Transportation Engineering (Volume 2, Issue 4)
DOI 10.11648/j.ajtte.20170204.11
Page(s) 39-44
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Air Transport, Demand, Trend Analysis, Transportation

References
[1] Cole S. (1998). Applied Transport Economics. London: Kegan Page Ltd.
[2] Adeniran A. O. and S. Ayinde O. (2017). Efficiency of Nigerian Transport System: Lessons Derived from the Developed Nations. Developing Country Studies www.iiste.orgISSN 2224-607X (Paper) ISSN 2225-0565 (Online) Vol. 7, No. 2, 2017. Pp. 87-93.
[3] Jean-Paul Rodrigue, Claude Comtois and Brian Slack (2006). Geography of Transport Systems. First published 2006 by Routledge.
[4] Aderamo A. J. (2010). Demand for Air Transport in Nigeria. Journal of Economics, 1 (1): 23-31 (2010).
[5] Windows Internet Explorer (2011). Air Transportation System- definition of air transport.
[6] International Civil Aviation Organization (ICAO).
[7] Airport Cooperative Research Program (ACRP) Synthesis 48. How Airports Measure Customer Service Performance. A Synthesis of Airport Practice. Transportation Research Board of the National Academics, 2013.
[8] Anne Graham (2003). Managing Airports. Butterworth-Heinemann Publications. ISBN: 0 7506 5917 3.
[9] ENO Foundation for Transportation, 1986.
[10] Ogunbodede E. F. (2006). Air Transportation in Nigeria: Past, Present Lessons and Challenges for the Aviation Industry. Journal of Geography and Planning Sciences, 1(1): 145-164.
[11] Adeyemi O. (2001). Moving Nigeria Forward: TheDevelopment Planning Approach. Ibadan: Ibadan University Press.
[12] Afolayan, O. S., Asaju, A. J. & Malik, N. A. (2012). Variation in Spatial Trend of Passengers and Aircrafts Movement in Nigerian International Airports. International Journal of Humanities and Social Science Vol. 2 No. 10 (Special Issue) May, 2012. Pp. 126-133.
[13] Federal Airports Authority of Nigeria.
[14] Nirametrics (2016). Nigeria Air Passenger Traffic [Online, Accessed, 2017].
[15] National Bureau of Statistics, 2017.
[16] Draper N. R., Smith H. (1981). Applied Regression Analysis. New York: John Wiley & Sons.
[17] Gujarati Damodar N. (2003). Basic Econometrics. Fourth Edition. Tata McGraw-Hill Publishing Company Limited, New Delhi, India The McGraw-Hill Companies, Inc.
[18] Greene W. (1993). Econometric Analysis. Second edition. Macmillan, New York, p. 791. Greene W. H. (2004). Econometric Analysis. Fourth edition, Prentice Hall International Upper Saddle River, USA.
Cite This Article
  • APA Style

    Adetayo Olaniyi Adeniran, Adedayo Ayomide Adeniran. (2017). Econometric Modeling of Passenger Demand for International Air Transport in Nigeria Airports. American Journal of Traffic and Transportation Engineering, 2(4), 39-44. https://doi.org/10.11648/j.ajtte.20170204.11

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    ACS Style

    Adetayo Olaniyi Adeniran; Adedayo Ayomide Adeniran. Econometric Modeling of Passenger Demand for International Air Transport in Nigeria Airports. Am. J. Traffic Transp. Eng. 2017, 2(4), 39-44. doi: 10.11648/j.ajtte.20170204.11

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    AMA Style

    Adetayo Olaniyi Adeniran, Adedayo Ayomide Adeniran. Econometric Modeling of Passenger Demand for International Air Transport in Nigeria Airports. Am J Traffic Transp Eng. 2017;2(4):39-44. doi: 10.11648/j.ajtte.20170204.11

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  • @article{10.11648/j.ajtte.20170204.11,
      author = {Adetayo Olaniyi Adeniran and Adedayo Ayomide Adeniran},
      title = {Econometric Modeling of Passenger Demand for International Air Transport in Nigeria Airports},
      journal = {American Journal of Traffic and Transportation Engineering},
      volume = {2},
      number = {4},
      pages = {39-44},
      doi = {10.11648/j.ajtte.20170204.11},
      url = {https://doi.org/10.11648/j.ajtte.20170204.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtte.20170204.11},
      abstract = {The paper is aimed at examining the econometric modeling of passenger demand for international air transport in Nigeria Airports with the objective of examining the relationship between the international passenger demand in Nigeria airports and economic variables. 91.2% of the dependent variable can be well explained by the independent variables and the unexplained variables or the error term is 8.8%. The fact that the coefficient of explanation (R Square) is very high, this is a sign that there is a problem of multicolinearity and the Durbin Watson value (3.443) which is greater than 2 also signifies there is a problem of autocorrelation or serial correlation. The significance level of the computed test statistics is 1.29 which is more than the significance level (0.05), hence we cannot reject the null hypothesis which states that there is no statistical significant relationship between % change in international Passenger Traffic (Annual) and % change in economic indicators (Consumer Inflation Price (CPI), Naira value to Dollar and Gross Domestic Product). It is therefore concluded that the economic indicators cannot give a good forecast of international air transport demand because the model suffers from serial correlation, multicolinearity and insignificance of the test.},
     year = {2017}
    }
    

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    T1  - Econometric Modeling of Passenger Demand for International Air Transport in Nigeria Airports
    AU  - Adetayo Olaniyi Adeniran
    AU  - Adedayo Ayomide Adeniran
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    N1  - https://doi.org/10.11648/j.ajtte.20170204.11
    DO  - 10.11648/j.ajtte.20170204.11
    T2  - American Journal of Traffic and Transportation Engineering
    JF  - American Journal of Traffic and Transportation Engineering
    JO  - American Journal of Traffic and Transportation Engineering
    SP  - 39
    EP  - 44
    PB  - Science Publishing Group
    SN  - 2578-8604
    UR  - https://doi.org/10.11648/j.ajtte.20170204.11
    AB  - The paper is aimed at examining the econometric modeling of passenger demand for international air transport in Nigeria Airports with the objective of examining the relationship between the international passenger demand in Nigeria airports and economic variables. 91.2% of the dependent variable can be well explained by the independent variables and the unexplained variables or the error term is 8.8%. The fact that the coefficient of explanation (R Square) is very high, this is a sign that there is a problem of multicolinearity and the Durbin Watson value (3.443) which is greater than 2 also signifies there is a problem of autocorrelation or serial correlation. The significance level of the computed test statistics is 1.29 which is more than the significance level (0.05), hence we cannot reject the null hypothesis which states that there is no statistical significant relationship between % change in international Passenger Traffic (Annual) and % change in economic indicators (Consumer Inflation Price (CPI), Naira value to Dollar and Gross Domestic Product). It is therefore concluded that the economic indicators cannot give a good forecast of international air transport demand because the model suffers from serial correlation, multicolinearity and insignificance of the test.
    VL  - 2
    IS  - 4
    ER  - 

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Author Information
  • Department of Transport Management Technology, Federal University of Technology, Akure, Nigeria

  • Department of Geography, University of Ibadan, Ibadan, Nigeria

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