Economic Valuation of Military Checkpoint-Induced Travel Time Variability in Abuja, Nigeria (2012-2017)
top of page
Asian Institute of Research, Journal Publication, Journal Academics, Education Journal, Asian Institute
Asian Institute of Research, Journal Publication, Journal Academics, Education Journal, Asian Institute

Economics and Business

Quarterly Reviews

ISSN 2775-9237 (Online)

asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, managemet journal
asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, managemet journal
asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, managemet journal
asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, managemet journal
crossref
doi
open access

Published: 17 January 2020

Economic Valuation of Military Checkpoint-Induced Travel Time Variability in Abuja, Nigeria (2012-2017)

Ibrahim Gerarh Umaru, Abubakar Mohammed Tanko

Kaduna State University (Nigeria), Nigerian Defence Academy (Nigeria)

asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, management journal

Download Full-Text Pdf

doi

10.31014/aior.1992.03.01.176

Pages: 29-43

Keywords: Military Checkpoint, FCT Highways, Travel Time, Time Variability, Start Time, Insurgency, Destination

Abstract

Between 2009 and 2016, Nigeria witnessed insurgency attacks from such militant groups as Movement for the Emancipation of Niger Delta (MEND), Movement for the Actualization of the Sovereign State of Biafra (MASSOB) and O'odua People's Congress (OPC). The most vicious and infamous threat yet was from the self-styled terrorist group going by the name, Jama'atuahlus-sunnah lid-da'awatiwal Jihad, otherwise known as Boko Haram. The group claimed responsibility for spate of bombings recorded not only within the north-east region of the country but on private and public buildings, bus stations, shopping malls, recreation centres and markets in major cities such as Kaduna, Kano and Abuja, Nigeria. The apparent threat to national security and perhaps most importantly to lives in these cities led security operatives, especially the Military and the Police, to erect checkpoints at strategic locations along major arteries and roads adjudged to be of strategic interest to the terrorists as one of the effective measures to curtail the activity of the terror groups. One of the fallouts of this measure is the phenomenon of obstruction of traffic and delays in reaching travel destinations by commuters often referred to in technical terms as travel time variability. Using the Nolan and Small (1995) modified economic valuation model and the erection of military checkpoints on the three highways in Abuja-Nigeria between 2012 and 2016 as reference points, this study examines the implication of the travel time variability in the federal capital territory (FCT). The findings of the study show that the mounting of military checkpoints might have cost the FCT between N8.25 and N9.58 billion annually within the period. For the period under study (2012 - 2016), the FCT economy might have lost between N40 and N59 billion to obstruction and traffic congestion occasioned by the mounting of military checkpoints.

References

  1. Alcantara de Vasconcellos, E. (2005). Urban change, mobility and transport in Sao Paulo: three decades, three cities. Transport Policy, 12(2), p.91-104.
  2. Bates, J., Polak, J., Jones, P. and Cook, A. (2001). The valuation of reliability for personal travel. Transportation Research Part E: Logistics and Transportation Review, 37(2): 191-229.
  3. Beaud, M., Blayac, T. and Stephen, M. (2016). The impact of travel time variability and traveler’s risk attitudes on the values of time and reliability. Transport Research Part B, 93:207-224.
  4. Becker, G. (1965). A theory of the allocation of time. The Economic Journal, 75, 493-517.
  5. Biliyamin, I. A. and Abosede, B. A. (2012). Effects of congestion and travel time variability along Abuja-Keffi corridor in Nigeria. Global Journal of Research In Engineering, 12(3-E).
  6. Börjesson, M., and Eliasson, J. (2010). The value of time and external benefits in bicycle cost-benefit analyses. Selected proceedings of the 12th WCTR.
  7. Börjesson, M., Fosgerau, M. and Algers, S. (2009). The income elasticity of the value of travel time is not one number. In European Transport Conference, 2009. Leiden Leeuwenhorst Conference Centre, Netherlands. 2009-10-5 to 2009-10-7.
  8. Buchel, B. and Carman, F. (2018). Modelling probability distributions of public travel time components. 18thSwiss Transport Research Conference Monte Verita/Ascona, May 16-18, 2018.
  9. Chow, G.C. (1960). Tests of equality between sets of coefficients in two linear regressions. Econometrica, 28(3): 591-605.
  10. De Borger, B., and Fosgerau, M. (2006, August). Another test of the theory of reference-dependent preferences: the trade-off between money and time. In: European Transport Conference proceedings.
  11. De Borger, B., and Fosgerau, M. (2008). The trade-off between money and travel time: A test of the theory of reference-dependent preferences. Journal of Urban Economics, 64(1), 101-115.
  12. De Serpa, A. (1971). A theory of the economics of time. The Economic Journal, 81, 828-846.
  13. Evans, A. (1972). On the theory of the valuation of travel time savings. Scottish journal of Political economy, 19:1-17.
  14. FMI (2004). FMI 3-07.22: Counterinsurgency operations. October, 2004 (expires 1 October, 2006). Appendix C. Population and resources control. Available: www.GlobalSecurity.org. Accessed: 14/12/2016.
  15. Gujarati, D.N. and Porter, D.C. (2009). Basic econometrics 5thedition. Boston: McGraw-Hill.
  16. Jara-Díaz, S.R. (2000). “Allocation and valuation of travel time savings.” Handbook in Transport 1(2000): 303-319.
  17. Johnson, M. (1966). Travel time and price of leisure. Western economic journal4:135-145.
  18. Koster, P., Kroes, E., and Verhoef, E. (2008). Valuing the cost of car travel time variability. Working paper, VU University, Amsterdam, September, earlier version presented at the Kuhmo Necter Conference, Amsterdam, 2008
  19. Koster, P., Kroes, E., and Verhoef, E. (2011). Travel time variability and airport accessibility. Transportation Research Part B: Methodological, 45(10), 1545-1559.
  20. Mazloumi, E., Currie, G. and Rose, G. (2010). Using GPS data to gain insight into public transport travel time variability. Journal of Transportation Engineering, 136 (7): 623-631.
  21. McKnight, C.E., Levison, H.S., Ozkay, Kamga, K.C. and Paaswell, R.E. (2004). Impact of traffic congestion on bus travel time in northern New Jersey. Transportation Research Record. Available: www.citeseerx.ist.psu.edu. Access: 30/08/2017.
  22. Federal capital Territory Administration/Nigerian Institute of Transport Technology (FCTA/NITT, 2009). Final report on Abuja traffic and ridership survey. (Unpublished report)
  23. National Bureau of Statistics (NBS, 2012). Annual abstract of statistics. Abuja: National Bureau of Statistics.
  24. Noland, R. B. and K. A. Small (1995). Travel time uncertainty, departure time choice and the cost of morning commutes. Transportation Research Record, 1493, 150-158.
  25. Olatunde, R.A (2016). Impact of traffic congestion on commuter’s travel time in Lagos state. A thesis of the department of economics, Nigerian Defence Academy Kaduna.
  26. Oort, O. (1969). The evaluation of travelling time. Journal of Transport Economics and Policy, 3:279-286.
  27. Small, K. (1982). Scheduling of consumer activities work trip. America Economic Review 72:467-479.
  28. Srinivasan, S., and Rogers, P. (2005). Travel behavior of low-income residents: studying two contrasting locations in the city of Chennai, India. Journal of Transport Geography, 13(3), 265-274.
  29. Tagaris, E. Liao, K.J., Delucia, A.J., Deck, L., Amar, P. and Russell, A.G. (2009). Potential impact of climate change on air pollution-related human health effects. Environmental Science Technology 1, 43(13): 4979-88.
  30. Umaru, I.G. (2013). Research methodology: Principles and application in social and behavioral science. Jos, Nigeria: Olive de L’Afrique Consult/Eiwa Ventures
  31. van Oort, N., Sparing, D., Brands, T. and Goverde, R.M.P. (2015). Data driven improvements in public transport: The Dutch example. Public Transport, 7(3): 369-389.
  32. Wajek, M. and Hauger, G. (2017). Reliability of travel time: Challenges posed by a multimodal transport participation. IOP Guf. Series: Materials Science and Engineering, 245 (2017).
  33. Yamane, T. (1964). Statistics: An introductory analysis 3rd edition. New York: Harpen and Row Publishing.
bottom of page