IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v55y2021i5d10.1007_s11135-020-01081-8.html
   My bibliography  Save this article

Is internet penetration narrowing the rural–urban income inequality? A cross-regional study of China

Author

Listed:
  • Lei-Ju Qiu

    (Central University of Finance and Economics)

  • Shun-Bin Zhong

    (Central University of Finance and Economics)

  • Bao-Wen Sun

    (Central University of Finance and Economics)

  • Yu Song

    (University of Finance and Economics)

  • Xiao-Hua Chen

    (Central University of Finance and Economics)

Abstract

Internet penetration (NET) brings new opportunities as well as challenges to countries all over the world. It can narrow the rural–urban income inequality (RUI), because it increases the connections of rural areas to the urban areas from both the production side and consumption side. It can also enlarge the RUI, because the internet may be skill-biased. Meanwhile, income level and the RUI may lead to different local internet development. However, the relationship between NET and RUI remains unclarified. This study applies the method of bootstrap panel Granger causality to explore the causal relationship between NET and RUI. The estimation results show that the causal relationship between NET and RUI varies across different provinces and regions, which is in line with the hypothesis of the inverted U-shaped technological Kuznets curve (TKC). Specifically, the NET does Granger-cause RUI in two-fifths of China’s provinces, primarily in North China and East China, while RUI does not Granger-cause NET in China since the NET itself is largely dependent on government policies. Therefore, policymakers should develop fair internet development policies targeting the improvement of rural and urban income distribution.

Suggested Citation

  • Lei-Ju Qiu & Shun-Bin Zhong & Bao-Wen Sun & Yu Song & Xiao-Hua Chen, 2021. "Is internet penetration narrowing the rural–urban income inequality? A cross-regional study of China," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(5), pages 1795-1814, October.
    • Handle: RePEc:spr:qualqt:v:55:y:2021:i:5:d:10.1007_s11135-020-01081-8
    DOI: 10.1007/s11135-020-01081-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11135-020-01081-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11135-020-01081-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    References listed on IDEAS

    as
    1. Liu, Chun & Jayakar, Krishna, 2012. "The evolution of telecommunications policy-making: Comparative analysis of China and India," Telecommunications Policy, Elsevier, vol. 36(1), pages 13-28.
    2. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    3. Menzie D. Chinn & Robert W. Fairlie, 2007. "The determinants of the global digital divide: a cross-country analysis of computer and internet penetration," Oxford Economic Papers, Oxford University Press, vol. 59(1), pages 16-44, January.
    4. Nelson C. Mark & Masao Ogaki & Donggyu Sul, 2005. "Dynamic Seemingly Unrelated Cointegrating Regressions," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 797-820.
    5. Zhang, Xiaoqun, 2013. "Income disparity and digital divide: The Internet Consumption Model and cross-country empirical research," Telecommunications Policy, Elsevier, vol. 37(6), pages 515-529.
    6. Olena Ivus & Matthew Boland, 2015. "The employment and wage impact of broadband deployment in Canada," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 48(5), pages 1803-1830, December.
    7. Anders Akerman & Ingvil Gaarder & Magne Mogstad, 2015. "The Skill Complementarity of Broadband Internet," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(4), pages 1781-1824.
    8. Rudra P. Pradhan & Mak B. Arvin & Neville R. Norman & Sara E. Bennett, 2016. "Financial depth, internet penetration rates and economic growth: country-panel evidence," Applied Economics, Taylor & Francis Journals, vol. 48(4), pages 331-343, January.
    9. Rudra P. Pradhan & Mak B. Arvin & Mahendhiran Nair & Sara E. Bennett & John H. Hall, 2019. "The information revolution, innovation diffusion and economic growth: an examination of causal links in European countries," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(3), pages 1529-1563, May.
    10. Jorg Breitung, 2005. "A Parametric approach to the Estimation of Cointegration Vectors in Panel Data," Econometric Reviews, Taylor & Francis Journals, vol. 24(2), pages 151-173.
    11. Swamy, P A V B, 1970. "Efficient Inference in a Random Coefficient Regression Model," Econometrica, Econometric Society, vol. 38(2), pages 311-323, March.
    12. Sudeshna Ghosh, 2020. "Impact of economic growth volatility on income inequality: ASEAN experience," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(3), pages 807-850, June.
    13. Dumitrescu, Elena-Ivona & Hurlin, Christophe, 2012. "Testing for Granger non-causality in heterogeneous panels," Economic Modelling, Elsevier, vol. 29(4), pages 1450-1460.
    14. T. S. Breusch & A. R. Pagan, 1980. "The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 239-253.
    15. M. Hashem Pesaran & Aman Ullah & Takashi Yamagata, 2008. "A bias-adjusted LM test of error cross-section independence," Econometrics Journal, Royal Economic Society, vol. 11(1), pages 105-127, March.
    16. M. Hashem Pesaran, 2021. "General diagnostic tests for cross-sectional dependence in panels," Empirical Economics, Springer, vol. 60(1), pages 13-50, January.
    17. Vasilis Sarafidis & Donald Robertson, 2009. "On the impact of error cross-sectional dependence in short dynamic panel estimation," Econometrics Journal, Royal Economic Society, vol. 12(1), pages 62-81, March.
    18. Chris Forman & Avi Goldfarb & Shane Greenstein, 2012. "The Internet and Local Wages: A Puzzle," American Economic Review, American Economic Association, vol. 102(1), pages 556-575, February.
    19. Granger, Clive W. J., 2003. "Some aspects of causal relationships," Journal of Econometrics, Elsevier, vol. 112(1), pages 69-71, January.
    20. Qiu, Leiju & Zhao, Daxuan, 2019. "Urban inclusiveness and income inequality in China," Regional Science and Urban Economics, Elsevier, vol. 74(C), pages 57-64.
    21. Li, Raymond & Shiu, Alice, 2012. "Internet diffusion in China: A dynamic panel data analysis," Telecommunications Policy, Elsevier, vol. 36(10), pages 872-887.
    22. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    23. Gourieroux, Christian & Holly, Alberto & Monfort, Alain, 1982. "Likelihood Ratio Test, Wald Test, and Kuhn-Tucker Test in Linear Models with Inequality Constraints on the Regression Parameters," Econometrica, Econometric Society, vol. 50(1), pages 63-80, January.
    24. Bauer, Johannes M., 2018. "The Internet and income inequality: Socio-economic challenges in a hyperconnected society," Telecommunications Policy, Elsevier, vol. 42(4), pages 333-343.
    25. Briglauer, Wolfgang & Dürr, Niklas S. & Falck, Oliver & Hüschelrath, Kai, 2019. "Does state aid for broadband deployment in rural areas close the digital and economic divide?," Information Economics and Policy, Elsevier, vol. 46(C), pages 68-85.
    26. Rudra P. Pradhan & Samadhan Bele & Shashikant Pandey, 2013. "Internet-growth nexus: evidence from cross-country panel data," Applied Economics Letters, Taylor & Francis Journals, vol. 20(16), pages 1511-1515, November.
    27. Gao, Yanyan & Zang, Leizhen & Sun, Jun, 2018. "Does computer penetration increase farmers’ income? An empirical study from China," Telecommunications Policy, Elsevier, vol. 42(5), pages 345-360.
    28. Briglauer, Wolfgang & Dürr, Niklas S. & Falck, Oliver & Hüschelrath, Kai, 2019. "Does state aid for broadband deployment in rural areas close the digital and economic divide?," Information Economics and Policy, Elsevier, vol. 46(C), pages 68-85.
    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. Xiaofan Zuo & Zhisheng Hong, 2022. "The Impact of Internet Use on Perception of the Poor–Rich Gap: Empirical Evidence from China," Sustainability, MDPI, vol. 14(6), pages 1-18, March.
    2. Ayesha Afzal & Saba Fazal Firdousi & Ayma Waqar & Minahil Awais, 2022. "The Influence of Internet Penetration on Poverty and Income Inequality," SAGE Open, , vol. 12(3), pages 21582440221, August.
    3. Zhengxin Li & Chengjun Liu & Xihui Chen, 2022. "Power of Digital Economy to Drive Urban-Rural Integration: Intrinsic Mechanism and Spatial Effect, from Perspective of Multidimensional Integration," IJERPH, MDPI, vol. 19(23), pages 1-20, November.
    4. Shunbin Zhong & Mengding Li & Yihui Liu & Yun Bai, 2023. "Do Internet Development and Urbanization Foster Regional Economic Growth: Evidence from China’s Yangtze River Economic Belt," Sustainability, MDPI, vol. 15(12), pages 1-14, June.
    5. Haoyun Meng & Peidong Deng & Jinbo Zhang, 2022. "Nonlinear Impact of Circulation-Industry Intelligentization on the Urban–Rural Income Gap: Evidence from China," Sustainability, MDPI, vol. 14(15), pages 1-26, August.

    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. Hsueh, Shun-Jen & Hu, Yu-Hau & Tu, Chien-Heng, 2013. "Economic growth and financial development in Asian countries: A bootstrap panel Granger causality analysis," Economic Modelling, Elsevier, vol. 32(C), pages 294-301.
    2. Chu, Hsiao-Ping & Chang, Tsangyao, 2012. "Nuclear energy consumption, oil consumption and economic growth in G-6 countries: Bootstrap panel causality test," Energy Policy, Elsevier, vol. 48(C), pages 762-769.
    3. Philip Arestis & Ayşe Kaya & Hüseyin Şen, 2018. "Does fiscal consolidation promote economic growth and employment? Evidence from the PIIGGS countries," European Journal of Economics and Economic Policies: Intervention, Edward Elgar Publishing, vol. 15(3), pages 289-312, November.
    4. Ceyhun Can OZCAN & Murat ASLAN & Saban NAZLIOGLU, 2017. "Economic freedom, economic growth and international tourism for post-communist (transition) countries: A panel causality analysis," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(2(611), S), pages 75-98, Summer.
    5. Hsien-Hung Kung & Jennifer C. H. Min, 2013. "Military Spending and Economic Growth Nexus in Sixteen Latin and South American Countries: A Bootstrap Panel Causality Test," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 171-185, December.
    6. Chu, Hsiao-Ping, 2012. "Oil consumption and output: What causes what? Bootstrap panel causality for 49 countries," Energy Policy, Elsevier, vol. 51(C), pages 907-915.
    7. Tsangyao Chang & Hsiao-Ping Chu & Wen-Yi Chen, 2013. "Energy consumption and economic growth in 12 Asian countries: panel data analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 20(3), pages 282-287, February.
    8. Chang, Tsangyao & Chen, Wen-Yi & Gupta, Rangan & Nguyen, Duc Khuong, 2015. "Are stock prices related to the political uncertainty index in OECD countries? Evidence from the bootstrap panel causality test," Economic Systems, Elsevier, vol. 39(2), pages 288-300.
    9. Roula Inglesi-Lotz & Tsangyao Chang & Rangan Gupta, 2015. "Causality between research output and economic growth in BRICS," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(1), pages 167-176, January.
    10. Puente-Ajovín, Miguel & Sanso-Navarro, Marcos, 2015. "Granger causality between debt and growth: Evidence from OECD countries," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 66-77.
    11. Menyah, Kojo & Nazlioglu, Saban & Wolde-Rufael, Yemane, 2014. "Financial development, trade openness and economic growth in African countries: New insights from a panel causality approach," Economic Modelling, Elsevier, vol. 37(C), pages 386-394.
    12. Yilmaz Bayar & Mahmut Unsal Sasmaz & Mehmet Hilmi Ozkaya, 2020. "Impact of Trade and Financial Globalization on Renewable Energy in EU Transition Economies: A Bootstrap Panel Granger Causality Test," Energies, MDPI, vol. 14(1), pages 1-13, December.
    13. Khalil Mhadhbi & Chokri Terzi & Ali Bouchrika, 2020. "Banking sector development and economic growth in developing countries: a bootstrap panel Granger causality analysis," Empirical Economics, Springer, vol. 58(6), pages 2817-2836, June.
    14. Xie, Zixiong & Chen, Shyh-Wei & Wu, An-Chi, 2020. "The foreign exchange and stock market nexus: New international evidence," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 240-266.
    15. Furkan Emirmahmutoglu & Mehmet Bacilar & Nicholas Apergis & Beatrice D. Simo-Kengne & Tsangyao Chang & Rangan Gupta, 2016. "Causal Relationship between Asset Prices and Output in the United States: Evidence from the State-Level Panel Granger Causality Test," Regional Studies, Taylor & Francis Journals, vol. 50(10), pages 1728-1741, October.
    16. Cengiz Aytun & Cemil Serhat Akin, 2022. "Can education lower the environmental degradation? Bootstrap panel Granger causality analysis for emerging countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(9), pages 10666-10694, September.
    17. repec:ipg:wpaper:2014-466 is not listed on IDEAS
    18. Chia-I Pan & Tsangyao Chang & Yemane Wolde-Rufael, 2015. "Military Spending and Economic Growth in the Middle East Countries: Bootstrap Panel Causality Test," Defence and Peace Economics, Taylor & Francis Journals, vol. 26(4), pages 443-456, August.
    19. Ming Zhong & Tsangyao Chang & D. P. Tang & Yemane Wolde-Rufael, 2015. "The causal nexus between military spending and unemployment in the G7: a bootstrap panel causality test," Defence and Peace Economics, Taylor & Francis Journals, vol. 26(6), pages 609-622, December.
    20. Qiao, Hui & Chen, Siyu & Dong, Xiucheng & Dong, Kangyin, 2019. "Has China's coal consumption actually reached its peak? National and regional analysis considering cross-sectional dependence and heterogeneity," Energy Economics, Elsevier, vol. 84(C).
    21. Ceyhun Can OZCAN, 2016. "International trade and tourism for Mediterranean countries: A panel causality analysis," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(1(606), S), pages 203-212, Spring.

    More about this item

    Keywords

    Internet penetration; Rural–urban income inequality; Technological kuznets curve; Bootstrap panel granger causality;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • E2 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment
    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs

    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:spr:qualqt:v:55:y:2021:i:5:d:10.1007_s11135-020-01081-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.