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Technology adoption constraints and Laser Land Levelling: evidence from Karnataka, India

Author

Listed:
  • Lisa Capretti

    (Department of Social Sciences and Economics, Sapienza University of Rome)

Abstract
Climate-smart agriculture can address many of the challenges faced by agriculture in semi-arid areas. However, in many developing countries, the adoption and use of this kind of technology are still low. Knowledge constraints represent a critical barrier to adoption; hence, an effective extension system is key. In India, extension programs are characterized by partnerships involving the public sector, the private sector and NGOs. The latest approaches take advantage of mass media and video-based extension services. In this article, I assess the role of extension services on the adoption of laser land leveling among 604 households in the Indian state of Karnataka. Laser land leveling is a modern way of leveling fields using a laser machine; it also brings environmental, economic and social benefits. Using propensity score matching, I find that visiting the extension center Raita Samparka Kendra (RSK) or receiving visit from RSK officials at least once in a year increases the likelihood of using LLL. Furthermore, a causal mediation analysis reveals that after explaining the advantages of the technology and its cost, farmers develop a perception about the affordability of laser land leveling that mediates the treatment effects of the extension service on laser land leveling adoption. Another mechanism that mediates this relationship, even to a lesser extent, is the increase in farmers’ welfare, proxied by household expenditure.

Suggested Citation

  • Lisa Capretti, 2023. "Technology adoption constraints and Laser Land Levelling: evidence from Karnataka, India," Working Papers 1/23, Sapienza University of Rome, DISS.
    • Handle: RePEc:saq:wpaper:1/23
    as

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    File URL: http://www.diss.uniroma1.it/sites/default/files/allegati/DiSSE_Capretti_wp1_2023.pdf
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    References listed on IDEAS

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    1. Stefan Dercon & Daniel O. Gilligan & John Hoddinott & Tassew Woldehanna, 2009. "The Impact of Agricultural Extension and Roads on Poverty and Consumption Growth in Fifteen Ethiopian Villages," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(4), pages 1007-1021.
    2. Lori Beaman & Ariel BenYishay & Jeremy Magruder & Ahmed Mushfiq Mobarak, 2021. "Can Network Theory-Based Targeting Increase Technology Adoption?," American Economic Review, American Economic Association, vol. 111(6), pages 1918-1943, June.
    3. Wollni, Meike & Andersson, Camilla, 2014. "Spatial patterns of organic agriculture adoption: Evidence from Honduras," Ecological Economics, Elsevier, vol. 97(C), pages 120-128.
    4. Imai, Kosuke & Keele, Luke & Tingley, Dustin & Yamamoto, Teppei, 2011. "Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies," American Political Science Review, Cambridge University Press, vol. 105(4), pages 765-789, November.
    5. Tavneet Suri, 2011. "Selection and Comparative Advantage in Technology Adoption," Econometrica, Econometric Society, vol. 79(1), pages 159-209, January.
    6. Christopher B. Barrett & Asad Islam & Abdul Mohammad Malek & Debayan Pakrashi & Ummul Ruthbah, 2022. "Experimental Evidence on Adoption and Impact of the System of Rice Intensification," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(1), pages 4-32, January.
    7. Timothy G. Conley & Christopher R. Udry, 2010. "Learning about a New Technology: Pineapple in Ghana," American Economic Review, American Economic Association, vol. 100(1), pages 35-69, March.
    8. Muange, Elijah N. & Schwarze, Stefan & Qaim, Matin, 2014. "Social networks and farmer exposure to improved crop varieties in Tanzania," GlobalFood Discussion Papers 183635, Georg-August-Universitaet Goettingen, GlobalFood, Department of Agricultural Economics and Rural Development.
    9. Muange, Elijah Nzula & Schwarze, Stefan & Qaim, Matin, 2014. "Social networks and farmer exposure to improved cereal varieties in central Tanzania," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182645, European Association of Agricultural Economists.
    10. Sascha O. Becker & Marco Caliendo, 2007. "Sensitivity analysis for average treatment effects," Stata Journal, StataCorp LP, vol. 7(1), pages 71-83, February.
    11. Mottaleb, Khondoker A., 2018. "Perception and adoption of a new agricultural technology: Evidence from a developing country," Technology in Society, Elsevier, vol. 55(C), pages 126-135.
    12. Gracious M. Diiro & Abdoul G. Sam, 2015. "Agricultural technology adoption and Nonfarm earnings in Uganda: a Semiparametric analysis," Journal of Developing Areas, Tennessee State University, College of Business, vol. 49(2), pages 145-162, April-Jun.
    13. Raymond Hicks & Dustin Tingley, 2011. "Causal mediation analysis," Stata Journal, StataCorp LP, vol. 11(4), pages 605-619, December.
    14. Travis J. Lybbert & Nicholas Magnan & David J. Spielman & Anil K. Bhargava & Kajal Gulati, 2018. "Targeting Technology to Increase Smallholder Profits and Conserve Resources: Experimental Provision of Laser Land-Leveling Services to Indian Farmers," Economic Development and Cultural Change, University of Chicago Press, vol. 66(2), pages 265-306.
    15. Andre Croppenstedt & Mulat Demeke & Meloria M. Meschi, 2003. "Technology Adoption in the Presence of Constraints: the Case of Fertilizer Demand in Ethiopia," Review of Development Economics, Wiley Blackwell, vol. 7(1), pages 58-70, February.
    16. Katsushi S. Imai & Md. Faruq Hasan & Eleonora Porreca, 2015. "Do Agricultural Extension Programmes Reduce Poverty and Vulnerability? Farm Size, Agricultural Productivity and Poverty in Uganda," Discussion Paper Series DP2015-06, Research Institute for Economics & Business Administration, Kobe University.
    17. Kebede, Yohannes & Gunjal, Kisan & Coffin, Garth, 1990. "Adoption of new technologies in Ethiopian agriculture: The case of Tegulet-Bulga district Shoa province," Agricultural Economics, Blackwell, vol. 4(1), pages 27-43, April.
    18. Yohannes Kebede & Kisan Gunjal & Garth Coffin, 1990. "Adoption of New Technologies in Ethiopian Agriculture: The Case of Tegulet‐Bulga District, Shoa Province," Agricultural Economics, International Association of Agricultural Economists, vol. 4(1), pages 27-43, April.
    19. Barbara Sianesi, 2004. "An Evaluation of the Swedish System of Active Labor Market Programs in the 1990s," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 133-155, February.
    20. Alain de JANVRY & Elisabeth SADOULET & Manzoor DAR & Kyle EMERICK, 2016. "The Agricultural Technology Adoption Puzzle: What Can We Learn From Field Experiments?," Working Papers P178, FERDI.
    21. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881, September.
    22. Samuel Benin & Ephraim Nkonya & Geresom Okecho & Joseé Randriamamonjy & Edward Kato & Geofrey Lubade & Miriam Kyotalimye, 2011. "Returns to spending on agricultural extension: the case of the National Agricultural Advisory Services (NAADS) program of Uganda," Agricultural Economics, International Association of Agricultural Economists, vol. 42(2), pages 249-267, March.
    23. Barrett, Christopher B. & Islam, Asad & Pakrashi, Debayan & Ruthbah, Ummul, 2021. "Experimental Evidence on Adoption and Impact of the System of rice Intensification," Working Papers 309950, Cornell University, Department of Applied Economics and Management.
    24. Kyle Emerick & Manzoor H. Dar, 2021. "Farmer Field Days and Demonstrator Selection for Increasing Technology Adoption," The Review of Economics and Statistics, MIT Press, vol. 103(4), pages 680-693, October.
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    More about this item

    Keywords

    Climate-smart agriculture; Extension services; Mediation analysis;
    All these keywords.

    JEL classification:

    • Q15 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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