IDEAS home Printed from https://ideas.repec.org/p/tin/wpaper/20160031.html
   My bibliography  Save this paper

A Statistical Analysis of Industrial Penetration and Internet Intensity in Taiwan

Author

Listed:
  • Chia-Lin Chang

    (National Chung Hsing University, Taichung, Taiwan)

  • Michael McAleer

    (National Tsing Hua University, Taiwan; Erasmus University Rotterdam, the Netherlands, and Complutense University of Madrid, Spain)

  • Yu-Chieh Wu

    (National Chung Hsing University, Taichung, Taiwan)

Abstract

This paper investigates the effect of industrial penetration (geographic concentration of industries) and internet intensity (the proportion of enterprises that use the internet) for Taiwan manufacturing firms, and analyses whether the relationships are substitutes or complements. The sample observations are based on 153,081 manufacturing plants, and covers 26 two-digit industry categories and 358 geographical townships in Taiwan. The Heckman selection model is used to accommodate sample selectivity for unobservable data for firms that use the internet. The empirical results from two-stage estimation show that: (1) a higher degree of industrial penetration will not affect the probability that firms will use the internet, but will affect the total expenditure on internet intensity; (2) for two-digit SIC industries, industrial penetration generally decreases the total expenditure on internet intensity; and (3) industrial penetration and internet intensity are substitutes.

Suggested Citation

  • Chia-Lin Chang & Michael McAleer & Yu-Chieh Wu, 2016. "A Statistical Analysis of Industrial Penetration and Internet Intensity in Taiwan," Tinbergen Institute Discussion Papers 16-031/III, Tinbergen Institute, revised 07 Jan 2018.
    • Handle: RePEc:tin:wpaper:20160031
    as

    Download full text from publisher

    File URL: https://papers.tinbergen.nl/16031.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492, National Bureau of Economic Research, Inc.
    2. Garth Saloner & Andrea Shepard, 1995. "Adoption of Technologies with Network Effects: An Empirical Examination of the Adoption of Teller Machines," RAND Journal of Economics, The RAND Corporation, vol. 26(3), pages 479-501, Autumn.
    3. Danielle Galliano & Pascale Roux, 2008. "Organisational motives and spatial effects in Internet adoption and intensity of use: evidence from French industrial firms," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(2), pages 425-448, June.
    4. Chang, Chia-Lin & Oxley, Les, 2009. "Industrial agglomeration, geographic innovation and total factor productivity: The case of Taiwan," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(9), pages 2787-2796.
    5. Lal, K., 1999. "Determinants of the adoption of Information Technology: a case study of electrical and electronic goods manufacturing firms in India," Research Policy, Elsevier, vol. 28(7), pages 667-680, September.
    6. B. K. Atrostic & Sang V. Nguyen, 2005. "It and Productivity in U.S. Manufacturing: Do Computer Networks Matter?," Economic Inquiry, Western Economic Association International, vol. 43(3), pages 493-506, July.
    7. Edwin Mansfield, 1963. "The Speed of Response of Firms to New Techniques," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 77(2), pages 290-311.
    8. Greene, William H, 1981. "Sample Selection Bias as a Specification Error: Comment," Econometrica, Econometric Society, vol. 49(3), pages 795-798, May.
    9. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    10. Bertschek, Irene & Fryges, Helmut, 2002. "The Adoption of Business-to-Business E-Commerce: Empirical Evidence for German Companies," ZEW Discussion Papers 02-05, ZEW - Leibniz Centre for European Economic Research.
    11. Audretsch, David B & Feldman, Maryann P, 1996. "R&D Spillovers and the Geography of Innovation and Production," American Economic Review, American Economic Association, vol. 86(3), pages 630-640, June.
    12. Baptista, Rui & Swann, Peter, 1998. "Do firms in clusters innovate more?," Research Policy, Elsevier, vol. 27(5), pages 525-540, September.
    13. Goldfarb, Avi & Prince, Jeff, 2008. "Internet adoption and usage patterns are different: Implications for the digital divide," Information Economics and Policy, Elsevier, vol. 20(1), pages 2-15, March.
    14. Forman, Chris & Goldfarb, Avi & Greenstein, Shane, 2005. "How did location affect adoption of the commercial Internet? Global village vs. urban leadership," Journal of Urban Economics, Elsevier, vol. 58(3), pages 389-420, November.
    15. Lewis, H Gregg, 1974. "Comments on Selectivity Biases in Wage Comparisons," Journal of Political Economy, University of Chicago Press, vol. 82(6), pages 1145-1155, Nov.-Dec..
    16. Danielle Galliano & Pascale Roux, 2008. "Organisational motives and spatial effects in Internet adoption and intensity of use: evidence from French industrial firms," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(2), pages 425-448, June.
    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. Chang, C-L. & McAleer, M.J. & Wu, Y-C., 2016. "Industrial Penetration and Internet Intensity," Econometric Institute Research Papers EI2016-23, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Chia-Lin Chang & Michael McAleer & Yu-Chieh Wu, 2015. "Industrial Agglomeration and Use of the Internet," Documentos de Trabajo del ICAE 2015-09, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    3. Danielle Galliano & Pascale Roux & Nicolas Soulié, 2011. "ICT Intensity of Use and the Geography of Firms," Environment and Planning A, , vol. 43(1), pages 67-86, January.
    4. François Seck Fall & Luis Orozco & Al‐Mouksit Akim, 2020. "Adoption and use of mobile banking by low‐income individuals in Senegal," Review of Development Economics, Wiley Blackwell, vol. 24(2), pages 569-588, May.
    5. Martin, Ludivine, 2009. "Understanding the implementation of e-business strategies: Evidence from Luxembourg," MPRA Paper 13645, University Library of Munich, Germany.
    6. P.W. Miller & S. Rummery, 1989. "Gender Wage Discrimination in Australia: A reassessment," Economics Discussion / Working Papers 89-21, The University of Western Australia, Department of Economics.
    7. Verbeek, M.J.C.M. & Nijman, T.E., 1992. "Incomplete panels and selection bias : A survey," Discussion Paper 1992-7, Tilburg University, Center for Economic Research.
    8. Takashi Yamagata & Chris Orme, 2005. "On Testing Sample Selection Bias Under the Multicollinearity Problem," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 467-481.
    9. B. Ben Halima & N. Chusseau & J. Hellier, 2013. "Skill Premia and Intergenerational Skill Transmission: The French Case," Working Papers 285, ECINEQ, Society for the Study of Economic Inequality.
    10. Ross M. Stolzenberg & Daniel A. Relles, 1990. "Theory Testing in a World of Constrained Research Design," Sociological Methods & Research, , vol. 18(4), pages 395-415, May.
    11. James J. Heckman, 2008. "Econometric Causality," International Statistical Review, International Statistical Institute, vol. 76(1), pages 1-27, April.
    12. Danielle Galliano & Nicolas Souli�, 2012. "Organizational and Spatial Determinants of the Multi-unit Firm: Evidence from French Industry," Regional Studies, Taylor & Francis Journals, vol. 46(7), pages 907-926, October.
    13. Miguel Santolino & Catalina Bolancé & Manuela Alcañiz, 2011. "Factors affecting hospital admission and recovery stay duration of in-patient motor victims in Spain," IREA Working Papers 201119, University of Barcelona, Research Institute of Applied Economics, revised Oct 2011.
    14. Brian T. McCann & Jeffrey J. Reuer & Nandini Lahiri, 2016. "Agglomeration and the choice between acquisitions and alliances: An information economics perspective," Strategic Management Journal, Wiley Blackwell, vol. 37(6), pages 1085-1106, June.
    15. Coates, Dennis & Humphreys, Brad R. & Kane, John & Vachris, Michelle A., 2004. ""No significant distance" between face-to-face and online instruction: evidence from principles of economics," Economics of Education Review, Elsevier, vol. 23(5), pages 533-546, October.
    16. Katrin Hussinger, 2008. "R&D and subsidies at the firm level: an application of parametric and semiparametric two-step selection models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(6), pages 729-747.
    17. Miguel Santolino & Magnus Söderberg, 2014. "Modelling appellate courts’ responses in motor injury disputes," European Journal of Law and Economics, Springer, vol. 38(3), pages 393-407, December.
    18. Gary A.S. Cook & Hans Lööf & Naresh R. Pandit & Börje Johansson, 2012. "The influence of clustering on MNE location and innovation in Great Britain," Chapters, in: Charlie Karlsson & Börje Johansson & Roger R. Stough (ed.), Entrepreneurship, Social Capital and Governance, chapter 3, pages 53-82, Edward Elgar Publishing.
    19. Walid Hadhri & Mohamed Ayadi & Adel Ben Youssef, 2012. "Difference between Adoption and Access Frequency to Internet and Consumer Surplus," Post-Print halshs-00937177, HAL.
    20. Pe'er, Aviad & Keil, Thomas, 2013. "Are all startups affected similarly by clusters? Agglomeration, competition, firm heterogeneity, and survival," Journal of Business Venturing, Elsevier, vol. 28(3), pages 354-372.

    More about this item

    Keywords

    Industrial penetration; Internet intensity; Sample selection; Incidental truncation.;
    All these keywords.

    JEL classification:

    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:tin:wpaper:20160031. 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: Tinbergen Office +31 (0)10-4088900 (email available below). General contact details of provider: https://edirc.repec.org/data/tinbenl.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.