IDEAS home Printed from https://ideas.repec.org/p/kei/dpaper/2009-017.html
   My bibliography  Save this paper

Spatial Diffusion of Innovation: A Spatial Panel Analysis of Electronic Toll Collecting Transponders in Japan

Author

Listed:
  • Yutaka Hamaoka

    (Faculty of Business and Commerce, Keio University)

Abstract

The spatial panel model is applied to a new data set: monthly data of the number of ETC (Electronic Toll Collecting) transponders newly installed in 47 Japanese prefectures. The model incorporates marketing variables and highway-related variables. Regarding the spatial panel model, this work estimates fixed-effect and random-effect model for spatial-lag model and spatial-error model. For each formulation, four types of weight matrix, geographical adjacency matrix, automobile traffic OD (Origin-Destination) table, telecommunication OD, and the inverse of the geographical distance are employed. Among estimated models, fit of "the fixed effect spatial-lag model with the inverse of distance as the weight matrix" is the best. The positive and significant spatial-lag parameter means diffusion in neighbor area promotes diffusion in other area. In case of the ETC transponder promotions, we find that the promotions at the early stage are effective but promotions at later stages are not. In addition to sales promotion of ETC transponders, the number of ETC gates and highway fee promotion for ETC drivers are also significant.

Suggested Citation

  • Yutaka Hamaoka, 2009. "Spatial Diffusion of Innovation: A Spatial Panel Analysis of Electronic Toll Collecting Transponders in Japan," Keio/Kyoto Joint Global COE Discussion Paper Series 2009-017, Keio/Kyoto Joint Global COE Program.
    • Handle: RePEc:kei:dpaper:2009-017
    as

    Download full text from publisher

    File URL: http://ies.keio.ac.jp/old_project/old/gcoe-econbus/pdf/dp/DP2009-017.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    2. Moscone, Francesco & Knapp, Martin & Tosetti, Elisa, 2007. "Mental health expenditure in England: A spatial panel approach," Journal of Health Economics, Elsevier, vol. 26(4), pages 842-864, July.
    3. László Mátyás & Patrick Sevestre (ed.), 2008. "The Econometrics of Panel Data," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75892-1, July-Dece.
    4. Patrick Sevestre & Laszlo Matyas, 2008. "The Econometrics of Panel Data," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00279977, HAL.
    5. Stremersch, S. & Tellis, G.J. & Franses, Ph.H.B.F. & Binken, J.L.G., 2007. "Indirect Network Effects in New Product Growth," ERIM Report Series Research in Management ERS-2007-019-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    6. Kakamu, Kazuhiko & Polasek, Wolfgang & Wago, Hajime, 2008. "Spatial interaction of crime incidents in Japan," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 276-282.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, Shuangzhe & Ma, Tiefeng & Polasek, Wolfgang, 2014. "Spatial system estimators for panel models: A sensitivity and simulation study," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 101(C), pages 78-102.
    2. Arturas Juodis, 2013. "Cointegration Testing in Panel VAR Models Under Partial Identification and Spatial Dependence," UvA-Econometrics Working Papers 13-08, Universiteit van Amsterdam, Dept. of Econometrics.
    3. repec:rri:wpaper:201303 is not listed on IDEAS
    4. Joseph P. Byrne & Alexandros Kontonikas & Alberto Montagnoli, 2013. "International Evidence on the New Keynesian Phillips Curve Using Aggregate and Disaggregate Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(5), pages 913-932, August.
    5. Cem Ertur & Antonio Musolesi, 2017. "Weak and Strong Cross‐Sectional Dependence: A Panel Data Analysis of International Technology Diffusion," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 477-503, April.
    6. Francesca Iorio & Stefano Fachin, 2014. "Savings and investments in the OECD: a panel cointegration study with a new bootstrap test," Empirical Economics, Springer, vol. 46(4), pages 1271-1300, June.
    7. Karaman Örsal, Deniz Dilan & Droge, Bernd, 2014. "Panel cointegration testing in the presence of a time trend," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 377-390.
    8. Vasudeva N. R. Murthy & Emmanuel Anoruo, 2009. "Are Per Capita Real GDP Series in African Countries Non-stationary or Non-linear? What does Empirical Evidence Reveal?," Economics Bulletin, AccessEcon, vol. 29(4), pages 2492-2504.
    9. Alexander Klemm & Stefan Parys, 2012. "Empirical evidence on the effects of tax incentives," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 19(3), pages 393-423, June.
    10. Ling Xiong & Shaozhou Qi, 2018. "Financial Development And Carbon Emissions In Chinese Provinces: A Spatial Panel Data Analysis," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 63(02), pages 447-464, March.
    11. Parent, Olivier & LeSage, James P., 2011. "A space-time filter for panel data models containing random effects," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 475-490, January.
    12. Patrizia Ordine & Giuseppe Rose, 2008. "Local Banks Efficiency and Employment," LABOUR, CEIS, vol. 22(3), pages 469-493, September.
    13. Brian Piper, 2014. "Factor-Specific Productivity," Working Papers 1401, Sam Houston State University, Department of Economics and International Business.
    14. Matyas, Laszlo & Balazsi, Laszlo, 2011. "The estimation of three-dimensional fixed effects panel data models," MPRA Paper 34976, University Library of Munich, Germany.
    15. Lawrence A. Plummer & Zoltán J. Ács, 2015. "Localized competition in the knowledge spillover theory of entrepreneurship," Chapters, in: Global Entrepreneurship, Institutions and Incentives, chapter 8, pages 145-160, Edward Elgar Publishing.
    16. Jaap H. Abbring, 0000. "Mixed Hitting-Time Models," Tinbergen Institute Discussion Papers 07-057/3, Tinbergen Institute, revised 11 Aug 2009.
    17. Heather Gibson & Stephen Hall & George Tavlas, 2015. "Are all sovereigns equal? A test of the common determination of sovereign spreads in the euro area," Empirical Economics, Springer, vol. 48(3), pages 939-949, May.
    18. Evren Ceritoglu, 2017. "The effect of house price changes on cohort consumption in Turkey," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 17(3), pages 1-99–110.
    19. Frauke Dobnik, 2013. "Long-run money demand in OECD countries: what role do common factors play?," Empirical Economics, Springer, vol. 45(1), pages 89-113, August.
    20. Daria Pus & László Mátyás & Cecilia Hornok, 2013. "Modelling Firm-Product Level Trade: A Multi-Dimensional Random Effects Panel Data Approach," CEU Working Papers 2013_2, Department of Economics, Central European University, revised 08 May 2013.
    21. Francesco Venturini, 2009. "The long-run impact of ICT," Empirical Economics, Springer, vol. 37(3), pages 497-515, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kei:dpaper:2009-017. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Global COE Program Office (email available below). General contact details of provider: https://edirc.repec.org/data/iekeijp.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.