IDEAS home Printed from https://ideas.repec.org/a/eee/wdevel/v72y2015icp70-92.html
   My bibliography  Save this article

Assessing the Impact of Crop Diversification on Farm Poverty in India

Author

Listed:
  • Birthal, Pratap S.
  • Roy, Devesh
  • Negi, Digvijay S.

Abstract

Crop diversification into high-value crops (HVCs) can be a strategy to improve livelihood outcomes for farmers. Using data from a nationally representative survey, we establish that households diversifying toward HVCs are less likely to be poor, the biggest impact being for smallholders. Furthermore, using continuous treatment matching, we establish the relationship between degree of diversification (share of area dedicated to HVC) and poverty. Growers of HVCs need to allocate at least 50% area to HVCs to escape poverty. Effect of diversification on poverty is in general positive but it withers after a threshold probably because of constraints i.e., capital on smaller farms and labor on larger ones.

Suggested Citation

  • Birthal, Pratap S. & Roy, Devesh & Negi, Digvijay S., 2015. "Assessing the Impact of Crop Diversification on Farm Poverty in India," World Development, Elsevier, vol. 72(C), pages 70-92.
  • Handle: RePEc:eee:wdevel:v:72:y:2015:i:c:p:70-92
    DOI: 10.1016/j.worlddev.2015.02.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0305750X15000480
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.worlddev.2015.02.015?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. Weinberger, Katinka & Lumpkin, Thomas A., 2007. "Diversification into Horticulture and Poverty Reduction: A Research Agenda," World Development, Elsevier, vol. 35(8), pages 1464-1480, August.
    2. Michael Lechner, 2002. "Program Heterogeneity And Propensity Score Matching: An Application To The Evaluation Of Active Labor Market Policies," The Review of Economics and Statistics, MIT Press, vol. 84(2), pages 205-220, May.
    3. Birthal, Pratap Singh & Joshi, Pramod Kumar & Negi, Digvijay S. & Agarwal, Shaily, 2014. "Changing sources of growth in Indian agriculture: Implications for regional priorities for accelerating agricultural growth:," IFPRI discussion papers 1325, International Food Policy Research Institute (IFPRI).
    4. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
    5. Sergio Firpo, 2007. "Efficient Semiparametric Estimation of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 75(1), pages 259-276, January.
    6. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2005. "Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 151-184, February.
    7. Roy, Devesh & Thorat, Amit, 2008. "Success in High Value Horticultural Export Markets for the Small Farmers: The Case of Mahagrapes in India," World Development, Elsevier, vol. 36(10), pages 1874-1890, October.
    8. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometrica, Econometric Society, vol. 71(4), pages 1161-1189, July.
    9. Jayne, T. S. & Yamano, Takashi & Weber, Michael T. & Tschirley, David & Benfica, Rui & Chapoto, Antony & Zulu, Ballard, 2003. "Smallholder income and land distribution in Africa: implications for poverty reduction strategies," Food Policy, Elsevier, vol. 28(3), pages 253-275, June.
    10. Pratap Singh Birthal & Pramod Kumar Joshi & Devesh Roy & Amit Thorat, 2013. "Diversification in Indian Agriculture toward High-Value Crops: The Role of Small Farmers," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 61(1), pages 61-91, March.
    11. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    12. Jayne, Thomas S. & Mason, Nicole M. & Myers, Robert J. & Ferris, John N. & Mather, David & Sitko, Nicholas & Beaver, Margaret & Lenski, Natalie & Chapoto, Antony & Boughton, Duncan, 2010. "Patterns and Trends in Food Staples Markets in Eastern and Southern Africa: Toward the Identification of Priority Investments and Strategies for Developing Markets and Promoting Smallholder Productivi," Food Security International Development Working Papers 62148, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    13. Kassie, Menale & Shiferaw, Bekele & Muricho, Geoffrey, 2011. "Agricultural Technology, Crop Income, and Poverty Alleviation in Uganda," World Development, Elsevier, vol. 39(10), pages 1784-1795.
    14. Michela Bia & Alessandra Mattei, 2008. "A Stata package for the estimation of the dose–response function through adjustment for the generalized propensity score," Stata Journal, StataCorp LP, vol. 8(3), pages 354-373, September.
    15. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    16. Joshi, P.K. & Gulati, Ashok & Birthal, Pratap S. & Tewari, Laxmi, 2003. "Agriculture diversification in South Asia," MSSD discussion papers 57, International Food Policy Research Institute (IFPRI).
    17. Kosuke Imai & David A. van Dyk, 2004. "Causal Inference With General Treatment Regimes: Generalizing the Propensity Score," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 854-866, January.
    18. BIA Michela & FLORES Carlos A. & MATTEI Alessandra, 2011. "Nonparametric Estimators of Dose-Response Functions," LISER Working Paper Series 2011-40, LISER.
    19. Arne Bigsten & Sven Tengstam, 2011. "Smallholder Diversification and Income Growth in Zambia," Journal of African Economies, Centre for the Study of African Economies (CSAE), vol. 20(5), pages 781-822, November.
    20. Minten, Bart & Randrianarison, Lalaina & Swinnen, Johan F.M., 2009. "Global Retail Chains and Poor Farmers: Evidence from Madagascar," World Development, Elsevier, vol. 37(11), pages 1728-1741, November.
    21. Alain de Janvry & Elisabeth Sadoulet, 2010. "Agricultural Growth and Poverty Reduction: Additional Evidence," World Bank Research Observer, World Bank Group, vol. 25(1), pages 1-20, February.
    22. Joshi, P.K. & Joshi, Laxmi & Birthal, Pratap Singh, 2006. "Diversification and Its Impact on Smallholders: Evidence from a Study on Vegetable Production," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 19(2), July.
    23. Achterbosch, Thom J. & Allbritton, Amanda & Quang, Dang Viet & Eaton, Derek J.F. & de Jager, Andre & Meijerink, Gerdien W. & Njue, Evelyn & Ssonko, Robinah & Stallen, Marcel & Wertheim-Heck, Sigrid & , 2007. "Poverty Alleviation in the Horticulture Sector: Insights from Uganda and Vietnam," 106th Seminar, October 25-27, 2007, Montpellier, France 7908, European Association of Agricultural Economists.
    24. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," Review of Economic Studies, Oxford University Press, vol. 65(2), pages 261-294.
    25. Alberto Abadie & Guido W. Imbens, 2006. "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica, Econometric Society, vol. 74(1), pages 235-267, January.
    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. Pedro Gerber Machado & Arnaldo Walter & Michelle Cristina Picoli & Cristina Gerber João, 2017. "Potential impacts on local quality of life due to sugarcane expansion: a case study based on panel data analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 19(5), pages 2069-2092, October.
    2. Tesfaye, Wondimagegn & Tirivayi, Nyasha, 2020. "Crop diversity, household welfare and consumption smoothing under risk: Evidence from rural Uganda," World Development, Elsevier, vol. 125(C).
    3. Nguyen, Trung Thanh & Nguyen, Loc Duc & Lippe, Rattiya Suddeephong & Grote, Ulrike, 2017. "Determinants of Farmers’ Land Use Decision-Making: Comparative Evidence From Thailand and Vietnam," World Development, Elsevier, vol. 89(C), pages 199-213.
    4. Michler, Jeffrey D. & Josephson, Anna L., 2017. "To Specialize or Diversify: Agricultural Diversity and Poverty Dynamics in Ethiopia," World Development, Elsevier, vol. 89(C), pages 214-226.
    5. Varun Kumar Das & A. Ganesh-Kumar, 2019. "Off-the-farm livelihood choice of farm households in India," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2019-032, Indira Gandhi Institute of Development Research, Mumbai, India.
    6. Bagchi, Niladri Sekhar & Mishra, Pulak & Behera, Bhagirath, 2021. "Value chain development for linking land-constrained farmers to markets: Experience from two selected villages of West Bengal, India," Land Use Policy, Elsevier, vol. 104(C).
    7. Buisson, M.-C. & Balasubramanya, Soumya, 2019. "The effect of irrigation service delivery and training in agronomy on crop choice in Tajikistan," Papers published in Journals (Open Access), International Water Management Institute, pages 81:175-184..
    8. Birthal, Pratap S. & Hazrana, Jaweriah & Negi, Digvijay S., 2020. "Diversification in Indian agriculture towards high value crops: Multilevel determinants and policy implications," Land Use Policy, Elsevier, vol. 91(C).
    9. Krishna, V. & Vikraman, S. & Aravalath, L., 2018. "Caste-based social segregation and access to public extension services in India," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 276944, International Association of Agricultural Economists.
    10. Varun Kumar Das, 2018. "Looking Beyond the Farm and Household: Determinants of On-farm Diversification in India," Working Papers id:12945, eSocialSciences.
    11. Joshi, P.K., 2015. "Has Indian Agriculture Become Crowded and Risky? Status, Implications and the Way Forward," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 70(1).
    12. Ganesh Thapa & Anjani Kumar & Devesh Roy & P.K. Joshi, 2018. "Impact of Crop Diversification on Rural Poverty in Nepal," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 66(3), pages 379-413, September.
    13. Cheng Li & Xinjian Chen & Aiwu Jiang & Myung-Bok Lee & Christos Mammides & Eben Goodale, 2021. "Socioeconomic Determinants of Crop Diversity and Its Effect on Farmer Income in Guangxi, Southern China," Agriculture, MDPI, Open Access Journal, vol. 11(4), pages 1-15, April.
    14. Martin, Sarah M. & Lorenzen, Kai, 2016. "Livelihood Diversification in Rural Laos," World Development, Elsevier, vol. 83(C), pages 231-243.
    15. Raymond B. Frempong & David Stadelmann, 2017. "Does Female Education have a Bargaining Effect on Household Welfare? Evidence from Ghana and Uganda," CREMA Working Paper Series 2017-08, Center for Research in Economics, Management and the Arts (CREMA).
    16. Thapa, Ganesh & Kumar, Anjani & Joshi, Pramod Kumar, 2017. "Agricultural diversification in Nepal: Status, determinants, and its impact on rural poverty," IFPRI discussion papers 1634, International Food Policy Research Institute (IFPRI).
    17. Varun Kumar Das, 2018. "Looking beyond the farm and household: Determinants of on-farm diversification in India," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2018-023, Indira Gandhi Institute of Development Research, Mumbai, India.
    18. Digvijay S. Negi & Pratap S. Birthal & Devesh Roy & Jaweriah Hazrana, 2020. "Market access, price policy and diversification in Indian agriculture," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2020-009, Indira Gandhi Institute of Development Research, Mumbai, India.
    19. Varun Kumar Das & A. Ganesh-Kumar, 2018. "Farm size, livelihood diversification and farmer’s income in India," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 45(2), pages 185-201, June.
    20. Kazakova-Mateva, Yanka & Radeva-Decheva, Donka, 2015. "The role of agroecosystems diversity towards sustainability of agricultural systems," 147th Seminar, October 7-8, 2015, Sofia, Bulgaria 212250, European Association of Agricultural Economists.
    21. Jeetendra Prakash Aryal & Dil Bahadur Rahut & Sofina Maharjan & Olaf Erenstein, 2018. "Factors affecting the adoption of multiple climate‐smart agricultural practices in the Indo‐Gangetic Plains of India," Natural Resources Forum, Blackwell Publishing, vol. 42(3), pages 141-158, August.
    22. Sen, Biswajit & Venkatesh, P. & Jha, Girish K. & Singh, D.R. & Suresh A., 2017. "Agricultural Diversification and its Impact on Farm Income: A Case Study of Bihar," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 30(Conferenc).
    23. Johny, Judit & Wichmann, Bruno & Swallow, Brent M., 2017. "Characterizing social networks and their effects on income diversification in rural Kerala, India," World Development, Elsevier, vol. 94(C), pages 375-392.

    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. Birthal, Pratap Singh & Roy, Devesh & Negi, Digvijay S., 2015. "Agricultural diversification and poverty in India:," IFPRI discussion papers 1446, International Food Policy Research Institute (IFPRI).
    2. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    3. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2006. "Moving the Goalposts: Addressing Limited Overlap in the Estimation of Average Treatment Effects by Changing the Estimand," NBER Technical Working Papers 0330, National Bureau of Economic Research, Inc.
    4. Carlos A. Flores & Oscar A. Mitnik, 2009. "Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data," Working Papers 2010-10, University of Miami, Department of Economics.
    5. Halbert White & Karim Chalak, 2013. "Identification and Identification Failure for Treatment Effects Using Structural Systems," Econometric Reviews, Taylor & Francis Journals, vol. 32(3), pages 273-317, November.
    6. Sokbae Lee & Yoon-Jae Whang, 2009. "Nonparametric Tests of Conditional Treatment Effects," Cowles Foundation Discussion Papers 1740, Cowles Foundation for Research in Economics, Yale University.
    7. Carlos A. Flores & Alfonso Flores-Lagunes & Arturo Gonzalez & Todd C. Neumann, 2009. "Estimating the Effects of Lenght of Exposure to Traning Program: The Case of Job Corps," Working Papers 2010-3, University of Miami, Department of Economics.
    8. Lee, Ying-Ying, 2018. "Efficient propensity score regression estimators of multivalued treatment effects for the treated," Journal of Econometrics, Elsevier, vol. 204(2), pages 207-222.
    9. Birthal, Pratap Singh & Joshi, Pramod Kumar & Negi, Digvijay S. & Agarwal, Shaily, 2014. "Changing sources of growth in Indian agriculture: Implications for regional priorities for accelerating agricultural growth:," IFPRI discussion papers 1325, International Food Policy Research Institute (IFPRI).
    10. Andrea Ichino & Fabrizia Mealli & Tommaso Nannicini, 2008. "From temporary help jobs to permanent employment: what can we learn from matching estimators and their sensitivity?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 305-327.
    11. Chad D. Meyerhoefer & Muzhe Yang, 2011. "The Relationship between Food Assistance and Health: A Review of the Literature and Empirical Strategies for Identifying Program Effects," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 33(3), pages 304-344.
    12. Peter R. Mueser & Kenneth R. Troske & Alexey Gorislavsky, 2007. "Using State Administrative Data to Measure Program Performance," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 761-783, November.
    13. Rahul Singh & Liyuan Xu & Arthur Gretton, 2020. "Reproducing Kernel Methods for Nonparametric and Semiparametric Treatment Effects," Papers 2010.04855, arXiv.org, revised Apr 2021.
    14. V. Joseph Hotz & Guido W. Imbens & Jacob A. Klerman, 2006. "Evaluating the Differential Effects of Alternative Welfare-to-Work Training Components: A Reanalysis of the California GAIN Program," Journal of Labor Economics, University of Chicago Press, vol. 24(3), pages 521-566, July.
    15. Markus Gangl & Thomas A. DiPrete, 2004. "Kausalanalyse durch Matchingverfahren," Discussion Papers of DIW Berlin 401, DIW Berlin, German Institute for Economic Research.
    16. Ham, John C. & Li, Xianghong & Reagan, Patricia B., 2011. "Matching and semi-parametric IV estimation, a distance-based measure of migration, and the wages of young men," Journal of Econometrics, Elsevier, vol. 161(2), pages 208-227, April.
    17. Jones A.M & Rice N, 2009. "Econometric Evaluation of Health Policies," Health, Econometrics and Data Group (HEDG) Working Papers 09/09, HEDG, c/o Department of Economics, University of York.
    18. Tommaso Nannicini, 2007. "Simulation-based sensitivity analysis for matching estimators," Stata Journal, StataCorp LP, vol. 7(3), pages 334-350, September.
    19. James J. Heckman, 2008. "The Principles Underlying Evaluation Estimators with an Application to Matching," Annals of Economics and Statistics, GENES, issue 91-92, pages 9-73.
    20. Steven Lehrer & Gregory Kordas, 2013. "Matching using semiparametric propensity scores," Empirical Economics, Springer, vol. 44(1), pages 13-45, February.

    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:eee:wdevel:v:72:y:2015:i:c:p:70-92. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: http://www.elsevier.com/locate/worlddev .

    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: Nithya Sathishkumar (email available below). General contact details of provider: http://www.elsevier.com/locate/worlddev .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.