Volume List  / Volume 12 (1)

Article

THE CONNECTION BETWEEN SPATIAL AUTOCORRELATION AND BORDER CROSSING TRAFFIC

DOI: 10.7708/ijtte2022.12(1).10


12 / 1 / 140-154 Pages

Author(s)

Zsombor Szabó - Budapest University of Technology and Economics, Faculty of Transportation Engineering and Vehicle Engineering, Department of Transport Technology and Economics – H-1111 Műegyetem rakpart 3. Budapest, Hungary & KTI Institute for Transport Sciences Nonprofit Ltd., Directorate for Public Transport Services – H-1119 Than Károly utca 3-5. Budapest, Hungary -

Tibor Sipos - Budapest University of Technology and Economics, Faculty of Transportation Engineering and Vehicle Engineering, Department of Transport Technology and Economics – H-1111 Műegyetem rakpart 3. Budapest, Hungary & KTI Institute for Transport Sciences Nonprofit Ltd., Directorate for Research and Innovation – H-1119 Than Károly utca 3-5. Budapest, Hungary -


Abstract

Examining the traffic of border crossing points is a priority task due to the exploitation of the advantages of the national economy. An essential part in this process is the examination of the autocorrelation in the data. In this article, a theoretical approach was used: the geographically located physical parameters were removed, and random networks were generated and analysed to investigate the effect of autocorrelation. Spatial autocorrelation could explain up to nearly 50 percent of the effects with a well-chosen spatial weight matrix. This article can also be interpreted as the first element of a research series, thus defining future research directions and the steps of generalizability of the models is crucial.


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References:

Anderson, W.P.; Maoh, H.F.; Burke, C.M. 2014. Passenger car flows across the Canada–US border: The effect of 9/11, Transport Policy 35: 50–56. https://doi.org/10.1016/j.tranpol.2014.05.005.

 

Anselin, L. 1988. Spatial Econometrics: Methods and Models. Kluwer Academic Publishers, The Netherlands. 284 p.

 

Auerbach, F. 1913. Das Gesetz der Bevölkerungskonzentration (The Law of Population Concentration), Petermanns Geographische Mitteilungen 59: 74–76.

 

Avetisyan, M.; Heatwole, N.; Rose, A.; Roberts, B. 2015. Competitiveness and macroeconomic impacts of reduced wait times at U.S. land freight border crossings, Transportation Research Part A: Policy and Practice 78: 84–101. https://doi.org/10.1016/j.tra.2015.04.027.

 

Babu, D.; Balan, S.; Anjaneyulu, M.V.L.R. 2021. Population Synthesis for a City in a Developing Country, Periodica Polytechnica Transportation Engineering 49(2): 156–163. https://doi.org/10.3311/PPtr.14938.

 

Bansal, P.; Hörcher, D.; Graham, D.J. 2020. A Dynamic Choice Model with Heterogeneous Decision Rules: Application in Estimating the User Cost of Rail Crowding, arXiv preprint arXiv:2007.03682.

 

Barabási, A.-L.; Albert, R.; Jeong, H. 1999. Mean-field theory for scale-free random networks, Physica A: Statistical Mechanics and its Applications 272(1–2): 173–187. https://doi.org/10.1016/S0378-4371(99)00291-5.

 

Barabási, A.-L.; Albert, R.; Jeong, H. 2000. Scale-free characteristics of random networks: the topology of the world-wide web, Physica A: Statistical Mechanics and its Applications 281(1–4): 69–77. https://doi.org/10.1016/S0378-4371(00)00018-2.

 

Baráth, F.; Rimóczi, M. 2011. Közlekedési földrajz (Transport Geography). Műszaki Kiadó, Hungary. 292 p.

 

Bradbury, S.L. 2013. The impact of security on travelers across the Canada–US border, Journal of Transport Geography 26: 139–146. https://doi.org/10.1016/j.jtrangeo.2012.08.009.

 

Brown, M.W.; Anderson, W.P. 2015. How thick is the border: the relative cost of Canadian domestic and cross-border truck-borne trade, 2004–2009, Journal of Transport Geography 42: 10–21. https://doi.org/10.1016/j.jtrangeo.2014.10.006.

 

Burt, M. 2009. Tighter Border Security and Its Effect on Canadian Exports, Canadian Public Policy / Analyse de Politiques 35(2): 149–169.

 

Cats, O. 2017. Topological evolution of a metropolitan rail transport network: The case of Stockholm, Journal of Transport Geography 62: 172–183. https://doi.org/10.1016/j.jtrangeo.2017.06.002.

 

Cavallaro, F.; Dianin, A. 2020a. Efficiency of public transport for cross-border commuting: An accessibility-based analysis in Central Europe, Journal of Transport Geography 89: 102876. https://doi.org/10.1016/j.jtrangeo.2020.102876.

 

Cavallaro, F.; Dianin, A. 2020b. An innovative model to estimate the accessibility of a destination by public transport, Transportation Research Part D: Transport and Environment 80: 102256. https://doi.org/10.1016/j.trd.2020.102256.

 

Clauset, A.; Shalizi, C.R.; Newman, M.E.J. 2009. Power-Law Distributions in Empirical Data, SIAM Review 51(4): 661–703. https://doi.org/10.1137/070710111.

 

Cliff, A.; Ord, K. 1972. Testing for Spatial Autocorrelation among Regression Residuals, Geographical Analysis 4(3): 267–284. https://doi.org/10.1111/j.1538-4632.1972.tb00475.x.

 

Dijkstra, E.W. 1959. A Note on Two Problems in Connexion with Graphs, Numerische Mathematik 1: 269–271. https://doi.org/10.1007/BF01386390.

 

Getis, A.; 1991. Spatial interaction and spatial autocorrelation: a cross-product approach, Environment and Planning A 23: 1269–1277.

 

Gonzalez-Estrada, E.; Villasenor-Alva, J.A. 2020. goft: Tests of Fit for some Probability Distributions. Available from Internet: https://cran.r-project.org/web/packages/goft/goft.pdf.

 

Gross, J.; Ligges, U. 2015. nortest: Tests for Normality. Available from Internet: https://cran.r-project.org/web/packages/nortest/nortest.pdf.

 

Guidoum, A.C.; Boukhetala, K. 2020. Performing Parallel Monte Carlo and Moment Equations Methods for Itô and Stratonovich Stochastic Differential Systems: R Package Sim.DiffProc, Journal of Statistical Software 96(2): 1–82. https://doi.org/10.18637/jss.v096.i02.

 

Hagget, P. (Ed.). 2001. Geography: a global synthesis. Pearson Education Limited, United Kingdom. 627 p.

 

Hart, A.; Martínez, S. 2019. spgs: Statistical Patterns in Genomic Sequences. Available from Internet: https://cran.r-project.org/web/packages/spgs/spgs.pdf.

 

Horiguchi, T.; Sakakibara, T. 1998. Numerical simulations for traffic-flow models on a decorated square lattice, Physica A: Statistical Mechanics and its Applications 252: 388–404. https://doi.org/10.1016/S0378-4371(97)00628-6.

 

Hummels, D.L. 1999. Toward a Geography of Trade Costs. Available from Internet: https://ssrn.com/abstract=160533 or https://dx.doi.org/10.2139/ssrn.160533.

 

Illés, I. 2008. Regionális gazdaságtan – területfejlesztés (Regional Economics - Regional Development). Typotex, Hungary. 262 p.

 

Jung, W.-S.; Wang, F.; Stanley, H.E. 2008. Gravity model in the Korean highway, EPL (Europhysics Letters) 81(4): 48005. https://doi.org/10.1209/0295-5075/81/48005.

 

LeSage, J.P. 1998. Spatial Econometrics. Department of Economics University of Toledo, Spain. 273 p.

 

Limão, N.; Venables, A.J. 2001. Infrastructure, Geographical Disadvantage, Transport Costs, and Trade, The World Bank Economic Review 15(3): 451–479.

 

Mályusz, L.; Varga, A. 2018. An Estimation of the Learning Curve Effect on Project Duration with Monte Carlo Simulation, Periodica Polytechnica Architecture 49(1): 66–71. https://doi.org/10.3311/PPar.12759.

 

Massey, F.J. 1951. The Kolmogorov-Smirnov Test for Goodness of Fit, Journal of the American Statistical Association 46(253): 68–78. https://doi.org/10.1080/01621459.1951.10500769.

 

MATLAB, 2019. 9.7.0.1296695 (R2019b). The MathWorks Inc. USA. Millard, S.P. 2013. EnvStats: An R Package for Environmental Statistics. Springer, USA. 291 p.

 

Miltiadou, M.; Bouhouras, E.; Basbas, S.; Mintsis, G.; Taxiltaris, C. 2017. Analysis of border crossings in South East Europe and measures for their improvement, Transportation Research Procedia 25: 603–615. https://doi.org/10.1016/j.trpro.2017.05.445.

 

Moran, P.A.P. 1948. Some Theorems on Time Series: II The Significance of the Serial Correlation Coefficient, Biometrika 35(3/4): 255–260. https://doi.org/10.2307/2332344.

 

Moran, P.A.P. 1950. Notes on Continuous Stochastic Phenomena, Biometrika 37(1/2): 17–23. https://doi.org/10.2307/2332142.

 

Nagy, L.; Balogh, P. 2013. Ökonometria (Econometrics). Debreceni Egyetem Gazdálkodástudományok Centruma, Hungary. 160 p.

 

Odlyzko, A. 2015. The forgotten discovery of gravity models and the inefficiency of early railway networks, OEconomial 5(1): 157–192.

 

Okubo, T. 2004. The border effect in the Japanese market: A Gravity Model analysis, Journal of the Japanese and International Economies 18(1): 1–11. https://doi.org/10.1016/S0889-1583(03)00047-9.

 

Opasanon, S.; Kitthamkesorn, S. 2016. Border crossing design in light of the ASEAN Economic Community: Simulation based approach, Transport Policy 48: 1–12. https://doi.org/10.1016/j.tranpol.2016.02.009.

 

OpenStreetMap contributors. 2017. Planet dump retrieved from http://download.geofabrik.de/europe.html.

 

Park, J.; Kwon, C.; Son, M. 2014. Economic implications of the Canada–U.S. border bridges: Applying a binational local economic model for international freight movements, Research in Transportation Business & Management 11: 123–133. https://doi.org/10.1016/j.rtbm.2014.06.003.

 

Prato, C.G. 2009. Route choice modeling: past, present and future research directions, Journal of Choice Modelling 2(1): 65–100. https://doi.org/10.1016/S1755-5345(13)70005-8.

 

R Core Team. 2017. A language and environment for statistical computing. R Foundation for Statistical Computing. Austria.

 

Rietveld, P.; Bruinsma, F.R.; van Vuuren, D.J. 2001. Spatial graduation of fuel taxes; consequences for cross-border and domestic fuelling, Transportation Research Part A: Policy and Practice 35(5): 433–457. https://doi.org/10.1016/S0965-8564(00)00002-1.

 

Sipos, T.; Szabó, Z.; Török, Á. 2021. Spatial Econometric Cross-Border Traffic Analysis for Passenger Cars – Hungarian Experience, Promet - Traffic & Transportation 33(2): 233–246. https://doi.org/10.7307/ptt.v33i2.3641.

 

Szabó, Z.; Sipos, T. 2020. Térstatisztika a közlekedésben (Spatial statistics in transport), Műszaki Szemle 75: 1–7.

 

Szabó, Z.; Sipos, T.; Török, Á. 2017. Spatial Econometric Analysis of the Hungarian Border Crossings. In: MATEC Web of Conferences 134, 00057. https://doi.org/10.1051/matecconf/201713400057.

 

Szabó, Z.; Török, Á. 2018a. Tranzitforgalmak Magyarországon: Egy térökonometriai elemzés (Transit traffic in Hungary: A spatial econometric analysis). In: Proceedings of the VIII. Közlekedéstudományi konferencia, 201–212.

 

Szabó, Z.; Török, Á. 2018b. Magyarország határátkelőinek térökonometriai elemzése (Evaluating the Hungarian Border Crossings from Spatial Econometric Point of View), Közlekedéstudományi Szemle 68(4): 46–60. https://doi.org/10.24228/KTSZ.2018.4.4.

 

Szalóki, F. 2017a. M15 expressway – upgrade and widening to a 2+2 traffic lanes motorway between M1 Motorway and Rajka (HU-SK border). In: Proceedings of the XV. European Transport Congress and X. Budapest International Road Congress, 12–17.

 

Szalóki, F. 2017b. M70 expressway – upgrade and widening to a 2+2 traffic lanes motorway between Letenye and Tornyiszentmiklós at HU-SL border. In: Proceedings of the XV. European Transport Congress and X. Budapest International Road Congress, 18–24.

 

Tagai, G.; Pénzes, J.; Molnár, E. 2008. Methods of the analysis of integration effect on border areas – the case of Hungary, Eurolimes – Journal of the Institute for Euroregional Studies 6: 150–160.

 

Tobler, W.R. 1970. A Computer Movie Simulating Urban Growth in the Detroit Region, Economic Geography 46(sup1): 234–240. https://doi.org/10.2307/143141.

 

Varga, A. 2002. Térökonometria (Spatial econometrics), Statisztikai Szemle 80(4): 354–370.

 

Venables, W.N.; Ripley, B.D. 2002. Modern Applied Statistics with S. Springer, USA. 495 p.

 

von Neumann, J.; Ulam, S. 1949. The Monte Carlo method, Journal of the American Statistical Association 44(247): 335–341.

 

Yen, J.Y. 1976. Finding the K Shortest Loopless Paths in a Network, Management Science 17(11): 712–716. Zipf, G.K. 1949. Human behavior and the principle of least effort. Addison-Wesley Press, USA. 573 p.