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Accounting for Neighborhood Influence in Estimating Factors Determining the Adoption of Improved Agricultural Technologies

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  • Langyintuo, Augustine S.
  • Mekuria, Mulugetta

Abstract

Researchers have traditionally applied censored regression models to estimate factors influencing farmers' decisions to adopt improved technologies for the design of appropriate intervention strategies. The standard Tobit model, commonly used, assumes spatial homogeneity implicitly but the potential for the presence of spatial heterogeneity (spatial autocorrelation or dependence) is high due to neighborhood influence among farmers. Ignoring spatial autocorrelation (if it exists) would result in biased estimates and all inferences based on the model will be incorrect. On the other hand, if spatial dependence is ignored the regression estimates would be inefficient and inferences based on t and F statistics misleading. To account for neighborhood influence, this study applied a spatial Tobit model to assess the factors determining the adoption of improved maize varieties in southern Africa using data collected from 300 randomly selected farm households in the Manica, Sussundenga and Chokwe districts of Mozambique during the 2003/04 crop season. Model diagnosis confirmed the spatial Tobit model as a better fit than the standard Tobit model. The estimated results suggest that farm size, access to credit, yield and cost of seed significantly influence maize variety adoption at less than 1% error probability while age of household head and distance to market influence adoption decisions at 5% error probability. The marginal effect analysis showed that convincing farmers that a given improved maize variety would give a unit more yield than the local one would increase adoption rate by 18% and intensity of use by 10%. Given that improved maize seeds are relatively more expensive than local ones, making credit accessible to farmers would increase adoption and intensity of use of improved maize varieties by 24% (15% being the probability of adoption and 8% the intensity of 2 use of the varieties). On the other hand, increasing seed price by a unit over the local variety would decrease the adoption rate by 12% and area under the improved variety by 6%. Targeting younger farmers with extension messages or making markets accessible to farmers would marginally increase the adoption and use intensity of improved maize varieties by only 0.4%. These results suggest that increasing field demonstrations to show farmers the yield advantage of improved varieties over local ones in Mozambique are essential in improving the uptake of improved varieties, which may be enhanced by making credit available to farmers to address the high improved seed costs. Alternatively, assuring farmers of competitive output markets through marketing innovations would enhance improved maize variety adoptions decisions. It may be concluded that the significance of the paper is its demonstration of the need to include spatial dependency in technology adoption models where neighborhood influences are suspected. Such an approach would give more credence to the results and limit the errors in suggesting areas to emphasize in individual or group targeting. The results thus have implications beyond the study area. Furthermore, the paper contributes to the scanty literature on the application of spatial econometrics in agricultural technology adoption modeling.

Suggested Citation

  • Langyintuo, Augustine S. & Mekuria, Mulugetta, 2005. "Accounting for Neighborhood Influence in Estimating Factors Determining the Adoption of Improved Agricultural Technologies," 2005 Annual meeting, July 24-27, Providence, RI 19521, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  • Handle: RePEc:ags:aaea05:19521
    DOI: 10.22004/ag.econ.19521
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    References listed on IDEAS

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    1. Ouma, James Okuro & De Groote, Hugo & Owuor, George, 2006. "Determinants of Improved Maize Seed and Fertilizer Use in Kenya: Policy Implications," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25433, International Association of Agricultural Economists.
    2. Kathleen P. Bell & Timothy J. Dalton, 2007. "Spatial Economic Analysis in Data‐Rich Environments," Journal of Agricultural Economics, Wiley Blackwell, vol. 58(3), pages 487-501, September.
    3. Langyintuo, Augustine S. & Mungoma, Catherine, 2008. "The effect of household wealth on the adoption of improved maize varieties in Zambia," Food Policy, Elsevier, vol. 33(6), pages 550-559, December.
    4. Njabulo Lloyd Ntshangase & Brian Muroyiwa & Melusi Sibanda, 2018. "Farmers’ Perceptions and Factors Influencing the Adoption of No-Till Conservation Agriculture by Small-Scale Farmers in Zashuke, KwaZulu-Natal Province," Sustainability, MDPI, vol. 10(2), pages 1-16, February.
    5. Langyintuo, Augustine S. & Mazuze, Feliciano M. & Chaguala, P.A. & Buque, I.A., 2006. "A Unified Methodology for Estimating the Demand for Improved Seed at the Farm Level in Developing Agriculture," 2006 Annual meeting, July 23-26, Long Beach, CA 21091, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. Acheampong, Patricia P. & Bonsu, Patterson O. & Omae, Hide & Nagumo, Fujio, 2016. "Disadoption of Improved Agronomic practices in Cowpea and Maize at Ejura-Sekyeredumase and Atebubu-Amantin Districts in Ghana," Sustainable Agriculture Research, Canadian Center of Science and Education, vol. 5(3).
    7. Kabayiza, Alexis & Owuor, George & Langat, K.J. & Mugenzi, Patrice & Niyitanga, Fidèle, 2021. "Determinants and Effect Evaluation of Credits on the Farm Outcome - a Micro-Perspective of Tea Production from Rwanda," 2021 Conference, August 17-31, 2021, Virtual 315091, International Association of Agricultural Economists.
    8. Raju Ghimire & Wen-Chi Huang, 2015. "Household wealth and adoption of improved maize varieties in Nepal: a double-hurdle approach," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 7(6), pages 1321-1335, December.
    9. Miftha Beshir & Menfese Tadesse & Fantaw Yimer & Nicolas Brüggemann, 2022. "Factors Affecting Adoption and Intensity of Use of Tef- Acacia decurrens -Charcoal Production Agroforestry System in Northwestern Ethiopia," Sustainability, MDPI, vol. 14(8), pages 1-15, April.
    10. Edward Martey & Prince Etwire & Alexander Wiredu & Wilson Dogbe, 2014. "Factors influencing willingness to participate in multi-stakeholder platform by smallholder farmers in Northern Ghana: implication for research and development," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 2(1), pages 1-15, December.

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