IDEAS home Printed from https://ideas.repec.org/p/zbw/itse13/88531.html
   My bibliography  Save this paper

Impact of broadband speed on household income: Comparing OECD and BIC

Author

Listed:
  • Rohman, Ibrahim Kholilul
  • Bohlin, Erik

Abstract

This paper aims to measure the impact of broadband speed access and upgrades on the household income based on a survey comprising 20,000 respondents in eight OECD and three BRIC countries in 2010 (Brazil, India and China). The study is novel, as most previous studies on broadband emphasize the penetration rate as the variable of interest. Moreover, by digging deeper on broadband speed (rather than broadband penetration rate), the problem concerning broadband definition that varies between countries can also be avoided. To investigate the impacts, a treatment effect model is employed using the Propensity Score Matching (PSM). Two aspects are being investigated: the impact of broadband access and the impact of varying broadband speeds on income. For access impact analysis, the samples are one with broadband access at a particular speed level against the other without the broadband access. Moreover, for the speed upgrades, the comparisons are carried out at various speed levels, e.g. users with 2 Mbps compared with the ones with 512 kbps. The results reveal that obtaining access to 0.5 Mbps in the OECD countries would not be expected to yield an increased income. The study suggests a minimum speed requirement where the households are expected to benefit from broadband lies somewhere between 2 Mbps and 4 Mbps. For BIC countries, however, the impact is already visible at 0.5 Mbps. At this speed, broadband users have a greater likelihood to gain 800 USD compared with the unconnected ones which is equivalent to 70 USD per month per household. For speed upgrades, the speed level giving the highest benefit to income in BIC and OECD countries is the same (4 to 8 Mbps), even though higher speed levels (8 to 24 Mbps) seems to contribute more in OECD than BIC countries. Note that the survey was carried out in 2010 when the sample average speed level in OECD countries was only about 4-5 Mbps and 2 Mbps in BIC countries. The analysis is supported by a reasonably strong statistical significance in OECD but not for the BIC countries due to sample limitation.

Suggested Citation

  • Rohman, Ibrahim Kholilul & Bohlin, Erik, 2013. "Impact of broadband speed on household income: Comparing OECD and BIC," 24th European Regional ITS Conference, Florence 2013 88531, International Telecommunications Society (ITS).
  • Handle: RePEc:zbw:itse13:88531
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/88531/1/774543450.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jacob A. Mincer, 1974. "Introduction to "Schooling, Experience, and Earnings"," NBER Chapters, in: Schooling, Experience, and Earnings, pages 1-4, National Bureau of Economic Research, Inc.
    2. Arthur Grimes & Cleo Ren & Philip Stevens, 2012. "The need for speed: impacts of internet connectivity on firm productivity," Journal of Productivity Analysis, Springer, vol. 37(2), pages 187-201, April.
    3. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1, January.
    4. Petra E. Todd & Kenneth I. Wolpin, 2010. "Structural Estimation and Policy Evaluation in Developing Countries," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 21-50, September.
    5. Brian E. Whitacre & Bradford F. Mills, 2007. "Infrastructure and the Rural—urban Divide in High-speed Residential Internet Access," International Regional Science Review, , vol. 30(3), pages 249-273, July.
    6. Card, David, 2001. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," Econometrica, Econometric Society, vol. 69(5), pages 1127-1160, September.
    7. Jacob A. Mincer, 1974. "Schooling and Earnings," NBER Chapters, in: Schooling, Experience, and Earnings, pages 41-63, National Bureau of Economic Research, Inc.
    8. McKinion, J. M. & Turner, S. B. & Willers, J. L. & Read, J. J. & Jenkins, J. N. & McDade, John, 2004. "Wireless technology and satellite internet access for high-speed whole farm connectivity in precision agriculture," Agricultural Systems, Elsevier, vol. 81(3), pages 201-212, September.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Kongaut, Chatchai & Bohlin, Erik, 2014. "Impact of broadband speed on economic outputs: An empirical study of OECD countries," 25th European Regional ITS Conference, Brussels 2014 101415, International Telecommunications Society (ITS).
    2. Koutroumpis, Pantelis, 2019. "The economic impact of broadband: Evidence from OECD countries," Technological Forecasting and Social Change, Elsevier, vol. 148(C).

    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. Harmon, Colm & Hogan, Vincent & Walker, Ian, 2003. "Dispersion in the economic return to schooling," Labour Economics, Elsevier, vol. 10(2), pages 205-214, April.
    2. Gregorio Caetano & Miguel Palacios & Harry A. Patrinos, 2019. "Measuring Aversion to Debt: An Experiment Among Student Loan Candidates," Journal of Family and Economic Issues, Springer, vol. 40(1), pages 117-131, March.
    3. Saïd Hanchane & Abraham Lioui & David Touahri, 2006. "Human capital as a risky asset and the effect of uncertainty on the decision to invest," Working Papers halshs-00010139, HAL.
    4. Berger, Johannes & Strohner, Ludwig, 2020. "Documentation of the PUblic Policy Model for Austria and other European countries (PUMA)," Research Papers 11, EcoAustria – Institute for Economic Research.
    5. Flabbi, Luca & Paternostro, Stefano & Tiongson, Erwin R., 2008. "Returns to education in the economic transition: A systematic assessment using comparable data," Economics of Education Review, Elsevier, vol. 27(6), pages 724-740, December.
    6. Maria Manuel Campos & Hugo Reis, 2018. "Returns to schooling in the Portuguese economy: a reassessment," Public Sector Economics, Institute of Public Finance, vol. 42(2), pages 215-242.
    7. Niklas Engbom & Christian Moser, 2017. "Returns to Education through Access to Higher-Paying Firms: Evidence from US Matched Employer-Employee Data," American Economic Review, American Economic Association, vol. 107(5), pages 374-378, May.
    8. Balestra, Simone & Backes-Gellner, Uschi, 2017. "Heterogeneous returns to education over the wage distribution: Who profits the most?," Labour Economics, Elsevier, vol. 44(C), pages 89-105.
    9. Tobias Klein, 2013. "College education and wages in the U.K.: estimating conditional average structural functions in nonadditive models with binary endogenous variables," Empirical Economics, Springer, vol. 44(1), pages 135-161, February.
    10. Justin L. Tobias, 2003. "Are Returns to Schooling Concentrated Among the Most Able? A Semiparametric Analysis of the Ability–earnings Relationships," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(1), pages 1-29, February.
    11. Kentaro Shimada & Zeba Khan & Suguru Mizunoya & Ayako Wakano, 2016. "An Update of the Returns to Education in Kenya: Accounting both endogeneity and sample selection biases," Discussion Papers in Economics and Business 16-18, Osaka University, Graduate School of Economics.
    12. Ivar Kolstad & Arne Wiig, 2015. "Education and entrepreneurial success," Small Business Economics, Springer, vol. 44(4), pages 783-796, April.
    13. Phanhpakit ONPHANHDALA & Terukazu SURUGA, 2006. "Education and Earnings in Lao PDR: Regional and Gender Differences," GSICS Working Paper Series 4, Graduate School of International Cooperation Studies, Kobe University.
    14. Cunha, Flavio & Heckman, James J., 2007. "Identifying and Estimating the Distributions of Ex Post and Ex Ante Returns to Schooling," Labour Economics, Elsevier, vol. 14(6), pages 870-893, December.
    15. Magnac, Thierry & Pistolesi, Nicolas & Roux, Sébastien, 2013. "Post schooling human capital investments and the life cycle variance of earnings," TSE Working Papers 13-380, Toulouse School of Economics (TSE).
    16. Yamarik Steven J, 2008. "Estimating Returns to Schooling from State-Level Data: A Macro-Mincerian Approach," The B.E. Journal of Macroeconomics, De Gruyter, vol. 8(1), pages 1-16, August.
    17. Saule Kemelbayeva, 2020. "Returns to schooling in Kazakhstan: an update using a pseudo-panel approach," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 10(3), pages 437-487, September.
    18. Angel de la Fuente & Antonio Ciccone, 2003. "Human capital in a global and knowledge-based economy," UFAE and IAE Working Papers 562.03, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    19. Serneels, Pieter & Beegle, Kathleen & Dillon, Andrew, 2017. "Do returns to education depend on how and whom you ask?," Economics of Education Review, Elsevier, vol. 60(C), pages 5-19.
    20. Imed Limam & Abdelwahab Ben Hafaiedh, 2017. "Education, Earnings and Returns to Schooling in Tunisia," Working Papers 1162, Economic Research Forum, revised 12 Jun 2017.

    More about this item

    Keywords

    broadband; speed; household income; OECD; BICs; propensity score matching; treatment effect;
    All these keywords.

    JEL classification:

    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • N84 - Economic History - - Micro-Business History - - - Europe: 1913-

    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:zbw:itse13:88531. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: http://www.itseurope.org/ .

    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.