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Assessing the influence of neighborhood effects on the adoption of improved agricultural technologies in developing agriculture

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  • Langyintuo, Augustine S.
  • Mekuria, Mulugetta
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    Abstract

    Researchers generally assume spatial homogeneity when assessing the factors that influence farmers to adopt improved agricultural technologies. However, the potential for spatial heterogeneity is high due to, for example, neighborhood effects such as farmers sharing information about new technology. Ignoring spatial heterogeneity can result in biased or inefficient regression estimates and make inferences based on t and F statistics misleading. Using data collected from 300 randomly selected farmers in three districts of Mozambique during the 2003/04 crop season, a spatial Tobit model was specified to estimate which factors determined the adoption of improved maize varieties, after an initial diagnostic test rejected the null hypothesis of spatial homogeneity. On the basis of the empirical evidence, the paper makes policy recommendations to increase Mozambican farmers’ adoption of improved maize varieties and concludes by emphasizing the need to test and correct for spatial heterogeneity in technology adoption modeling to improve the efficiency of the estimated results.

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    Bibliographic Info

    Article provided by African Association of Agricultural Economists in its journal African Journal of Agricultural and Resource Economics.

    Volume (Year): 02 (2008)
    Issue (Month): 2 (September)
    Pages:

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    Handle: RePEc:ags:afjare:56960

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    Related research

    Keywords: Spatial Tobit model; Spatial heterogeneity; Spatial autocorrelation; Neighborhood effects; Maize farmers; Mozambique; Research and Development/Tech Change/Emerging Technologies;

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    Cited by:
    1. Pangapanga, Phiriinnocent & Thangalimodzi, Lucy Tembo, 2012. "Participation in pro poor agro based enterprises in Malawi: do households’ poverty levels change automatically?," MPRA Paper 39446, University Library of Munich, Germany.
    2. Cook, Aaron M. & Ricker-Gilbert, Jacob E. & Sesmero, Juan P., 2013. "How do African households adapt to climate change? Evidence from Malawi," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150507, Agricultural and Applied Economics Association.
    3. Qu, Xi & Lee, Lung-fei, 2012. "LM tests for spatial correlation in spatial models with limited dependent variables," Regional Science and Urban Economics, Elsevier, vol. 42(3), pages 430-445.
    4. Phiri, Innocent Pangapanga, 2011. "Modelling farmers’ choice of adaptation strategies towards climatic and weather variability: Empirical evidence from Chikhwawa district, Southern Malawi," Research Theses 134489, Collaborative Masters Program in Agricultural and Applied Economics.

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