IDEAS home Printed from
   My bibliography  Save this article

A spatial and economic analysis for telecommunications: Evidence from the European Union



This paper evaluates the role of a number of determinants of telecommunication services in the European Union. We use a logistic model with spatial covariates to estimate the demand function for telecommunications in the Union. Our results show that different types of interconnections generate diverse estimates for country specific demand. The impact on telecommunications from countries with spatial, economic or social similarities differs based on those characteristics. Omitted variable bias from not modeling spatial interdependence is limited in models under spatial connectivity criteria. This satisfies the statistical inference drawn by previous empirical studies regarding determinants of telecommunications.

Suggested Citation

  • Christos Agiakloglou & Sotiris Karkalakos, 2009. "A spatial and economic analysis for telecommunications: Evidence from the European Union," Journal of Applied Economics, Universidad del CEMA, vol. 12, pages 11-32, May.
  • Handle: RePEc:cem:jaecon:v:12:y:2009:n:1:p:11-32

    Download full text from publisher

    File URL:
    Download Restriction: Online access is restricted to ScienceDirect subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. Atkinson, A.B., 2000. "Increased Income Inequality in OECD Countries and the Redistributive Impact of the Government Budget," Research Paper 202, World Institute for Development Economics Research.
    2. Beblo, Miriam & Knaus, Thomas, 2001. "Measuring Income Inequality in Euroland," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 47(3), pages 301-320, September.
    3. Guillermo E. Perry & Omar S. Arias & J. Humberto López & William F. Maloney & Luis Servén, 2006. "Poverty Reduction and Growth : Virtuous and Vicious Circles," World Bank Publications, The World Bank, number 6997.
    4. Bernd Raffelhuschen & Laurence J. Kotlikoff, 1999. "Generational Accounting around the Globe," American Economic Review, American Economic Association, vol. 89(2), pages 161-166, May.
    5. Andrew Mason & Ronald Lee & An-Chi Tung & Mun-Sim Lai & Tim Miller, 2009. "Population Aging and Intergenerational Transfers: Introducing Age into National Accounts," NBER Chapters,in: Developments in the Economics of Aging, pages 89-122 National Bureau of Economic Research, Inc.
    6. Ann Harding & Richard Percival & Deborah Schofield & Agnes Walker, 2002. "The Lifetime Distributional Impact of Government Health Outlays," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 35(4), pages 363-379.
    7. Shorrocks, A F, 1982. "Inequality Decomposition by Factor Components," Econometrica, Econometric Society, vol. 50(1), pages 193-211, January.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. repec:eee:iepoli:v:39:y:2017:i:c:p:26-35 is not listed on IDEAS
    2. Agiakloglou, Christos & Gkouvakis, Michalis, 2012. "Causal interrelations among market fundamentals: Evidence from the Europen telecommunications sector," 23rd European Regional ITS Conference, Vienna 2012 60387, International Telecommunications Society (ITS).
    3. Agiakloglou, Christos & Gkouvakis, Michail, 2015. "Causal interrelations among market fundamentals: Evidence from the European Telecommunications sector," The Quarterly Review of Economics and Finance, Elsevier, vol. 55(C), pages 150-159.
    4. Agiakloglou, Christos & Polemis, Michael, 2015. "What determines demand for Telecommunications services? Evidence from the EU countries before and after liberalization," 26th European Regional ITS Conference, Madrid 2015 127119, International Telecommunications Society (ITS).

    More about this item


    decay effect; telephone traffic demand; spatial econometrics;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • L96 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Telecommunications


    Access and download statistics


    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:cem:jaecon:v:12:y:2009:n:1:p:11-32. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Valeria Dowding). General contact details of provider: .

    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.

    We have no references for this item. You can help adding them by using 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.