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The Path Of Technology Diffusion: Which Neighbors To Learn From?

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  • Xiaobo Zhang
  • Shenggen Fan
  • Ximing Cai

Abstract

This study uses a panel data set of 25 years over 280 districts in rural India and applies a geographic information systems (GIS) program to investigate the regional neighborhood effect on the rate of diffusion of new technologies. The results show that in the technology diffusion process, the early successful adopters have a larger effect on neighboring adopters than do the early unsuccessful adopters. Hence, use of the aggregate or the simple average of adoption rate among neighborhoods as a proxy for the neighborhood effect, a common practice in the learning literature, may be inappropriate. We also find that education and irrigation play important roles in facilitating technology diffusion.

Suggested Citation

  • Xiaobo Zhang & Shenggen Fan & Ximing Cai, 2002. "The Path Of Technology Diffusion: Which Neighbors To Learn From?," Contemporary Economic Policy, Western Economic Association International, vol. 20(4), pages 470-478, October.
  • Handle: RePEc:bla:coecpo:v:20:y:2002:i:4:p:470-478
    DOI: 10.1093/cep/20.4.470
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    References listed on IDEAS

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    1. Foster, Andrew D & Rosenzweig, Mark R, 1995. "Learning by Doing and Learning from Others: Human Capital and Technical Change in Agriculture," Journal of Political Economy, University of Chicago Press, vol. 103(6), pages 1176-1209, December.
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    3. Schultz, Theodore W, 1975. "The Value of the Ability to Deal with Disequilibria," Journal of Economic Literature, American Economic Association, vol. 13(3), pages 827-846, September.
    4. Case, Anne, 1992. "Neighborhood influence and technological change," Regional Science and Urban Economics, Elsevier, vol. 22(3), pages 491-508, September.
    5. Melinda Smale & Richard E. Just & Howard D. Leathers, 1994. "Land Allocation in HYV Adoption Models: An Investigation of Alternative Explanations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 76(3), pages 535-546.
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    1. Shah, Md M.I. & Grant, Will J. & Stocklmayer, Sue, 2016. "Farmer innovativeness and hybrid rice diffusion in Bangladesh," Technological Forecasting and Social Change, Elsevier, vol. 108(C), pages 54-62.
    2. Arifovic, Jasmina & Karaivanov, Alexander, 2010. "Learning by doing vs. learning from others in a principal-agent model," Journal of Economic Dynamics and Control, Elsevier, vol. 34(10), pages 1967-1992, October.
    3. You, Liangzhi, 2012. "A tale of two countries: Spatial and temporal patterns of rice productivity in China and Brazil," China Economic Review, Elsevier, vol. 23(3), pages 690-703.
    4. Satadru Mukherjee, 2020. "Access to Formal Banks and New Technology Adoption: Evidence from India," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(5), pages 1532-1556, October.

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