IDEAS home Printed from https://ideas.repec.org/p/wbk/wbrwps/7150.html
   My bibliography  Save this paper

From tragedy to renaissance : improving agricultural data for better policies

Author

Listed:
  • Banerjee,Raka
  • Carletto,Calogero
  • Jolliffe,Dean Mitchell
  • Banerjee,Raka
  • Carletto,Calogero
  • Jolliffe,Dean Mitchell

Abstract

Agricultural development is an essential engine of growth and poverty reduction, yet agricultural data suffer from poor quality and narrow sectoral focus. There are several reasons for this: (i) difficult-to-measure smallholder agriculture is prevalent in poor countries, (ii) agricultural data are collected with little coordination across ministries of agriculture and national statistics offices, and (iii) poor analysis undermines the demand for high-quality data. This paper argues that initiatives like the Global Strategy to Improve Agricultural and Rural Statistics bode well for the future. Moving from Devarajan's statistical"tragedy"to Kiregyera's statistical"renaissance"will take a continued long-term effort by individual countries and development partners.

Suggested Citation

  • Banerjee,Raka & Carletto,Calogero & Jolliffe,Dean Mitchell & Banerjee,Raka & Carletto,Calogero & Jolliffe,Dean Mitchell, 2015. "From tragedy to renaissance : improving agricultural data for better policies," Policy Research Working Paper Series 7150, The World Bank.
  • Handle: RePEc:wbk:wbrwps:7150
    as

    Download full text from publisher

    File URL: http://documents.worldbank.org/curated/en/313131468194048389/pdf/From-tragedy-to-renaissance-improving-agricultural-data-for-better-policies.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Kilic, Talip & Zezza, Alberto & Carletto, Calogero & Savastano, Sara, 2017. "Missing(ness) in Action: Selectivity Bias in GPS-Based Land Area Measurements," World Development, Elsevier, vol. 92(C), pages 143-157.
    2. Chen, Shaohua & Ravallion, Martin, 2007. "The changing profile of poverty in the world," 2020 vision briefs BB01 Special Edition, International Food Policy Research Institute (IFPRI).
    3. H. Parker Willis, 1903. "The Adjustment of Crop Statistics: II," Journal of Political Economy, University of Chicago Press, vol. 11(3), pages 363-363.
    4. Beegle, Kathleen & Carletto, Calogero & Himelein, Kristen, 2012. "Reliability of recall in agricultural data," Journal of Development Economics, Elsevier, vol. 98(1), pages 34-41.
    5. Carletto, Calogero & Savastano, Sara & Zezza, Alberto, 2013. "Fact or artifact: The impact of measurement errors on the farm size–productivity relationship," Journal of Development Economics, Elsevier, vol. 103(C), pages 254-261.
    6. Davis, Benjamin & Winters, Paul & Carletto, Gero & Covarrubias, Katia & Quiñones, Esteban J. & Zezza, Alberto & Stamoulis, Kostas & Azzarri, Carlo & DiGiuseppe, Stefania, 2010. "A Cross-Country Comparison of Rural Income Generating Activities," World Development, Elsevier, vol. 38(1), pages 48-63, January.
    7. H. Parker Willis, 1903. "The Adjustment of Crop Statistics: III," Journal of Political Economy, University of Chicago Press, vol. 11(4), pages 540-540.
    8. Brian Dillon, 2012. "Using mobile phones to collect panel data in developing countries," Journal of International Development, John Wiley & Sons, Ltd., vol. 24(4), pages 518-527, May.
    9. Justin Sandefur and Amanda Glassman, 2014. "The Political Economy of Bad Data: Evidence from African Survey & Administrative Studies- Working Paper 373," Working Papers 373, Center for Global Development.
    10. Erich Battistin, 2002. "Errors in Survey Reports of Consumption Expenditures," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 C4-2, International Conferences on Panel Data.
    11. Deininger, Klaus & Carletto, Calogero & Savastano, Sara & Muwonge, James, 2012. "Can diaries help in improving agricultural production statistics? Evidence from Uganda," Journal of Development Economics, Elsevier, vol. 98(1), pages 42-50.
    12. World Bank, 2010. "Global Strategy to Improve Agricultural and Rural Statistics," World Bank Publications - Reports 12402, The World Bank Group.
    13. Beegle, Kathleen & De Weerdt, Joachim & Friedman, Jed & Gibson, John, 2012. "Methods of household consumption measurement through surveys: Experimental results from Tanzania," Journal of Development Economics, Elsevier, vol. 98(1), pages 3-18.
    14. Tiffen, Mary, 2003. "Transition in Sub-Saharan Africa: Agriculture, Urbanization and Income Growth," World Development, Elsevier, vol. 31(8), pages 1343-1366, August.
    15. Foster, Andrew D. & Rosenzweig, Mark R., 2008. "Economic Development and the Decline of Agricultural Employment," Handbook of Development Economics, in: T. Paul Schultz & John A. Strauss (ed.), Handbook of Development Economics, edition 1, volume 4, chapter 47, pages 3051-3083, Elsevier.
    16. Bryceson, Deborah Fahy, 2002. "The Scramble in Africa: Reorienting Rural Livelihoods," World Development, Elsevier, vol. 30(5), pages 725-739, May.
    17. John Gibson, 2002. "Why Does the Engel Method Work? Food Demand, Economies of Size and Household Survey Methods," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(4), pages 341-359, September.
    18. Katia Covarrubias & Longin Nsiima & Alberto Zezza, 2012. "Livestock and Livelihoods in Rural Tanzania : A Descriptive Analysis of the 2009 National Panel Survey," World Bank Publications - Reports 17886, The World Bank Group.
    19. Fermont, Anneke & Benson, Todd, 2011. "Estimating yield of food crops grown by smallholder farmers: A review in the Uganda context," IFPRI discussion papers 1097, International Food Policy Research Institute (IFPRI).
    20. Jolliffe, Dean, 2004. "The impact of education in rural Ghana: examining household labor allocation and returns on and off the farm," Journal of Development Economics, Elsevier, vol. 73(1), pages 287-314, February.
    21. Dorward, Andrew & Chirwa, Ephraim & Kelly, Valerie A. & Jayne, Thomas S. & Slater, Rachel & Boughton, Duncan, 2008. "Evaluation Of The 2006/7 Agricultural Input Subsidy Programme, Malawi. Final Report," Food Security Collaborative Working Papers 97143, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    22. Gibson, John, 2002. "Why Does the Engel Method Work? Food Demand, Economies of Size and Household Survey Methods," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(4), pages 341-359, September.
    23. Morten Jerven, 2013. "Agricultural Statistics," World Economics, World Economics, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 14(1), pages 1-10, January.
    24. Naeem Ahmed & Matthew Brzozowski & Thomas Crossley, 2006. "Measurement errors in recall food consumption data," IFS Working Papers W06/21, Institute for Fiscal Studies.
    Full references (including those not matched with items on IDEAS)

    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. Wollburg, Philip & Tiberti, Marco & Zezza, Alberto, 2021. "Recall length and measurement error in agricultural surveys," Food Policy, Elsevier, vol. 100(C).
    2. Zezza,Alberto & Mcgee,Kevin Robert & Wollburg,Philip Randolph & Assefa,Thomas Woldu & Gourlay,Sydney, 2022. "From Necessity to Opportunity : Lessons for Integrating Phone and In-Person Data Collectionfor Agricultural Statistics in a Post-Pandemic World," Policy Research Working Paper Series 10168, The World Bank.
    3. Chaoran Chen & Diego Restuccia & Raül Santaeulàlia-Llopis, 2023. "Land Misallocation and Productivity," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(2), pages 441-465, April.
    4. Jayasinghe, Maneka & Chai, Andreas & Ratnasiri, Shyama & Smith, Christine, 2017. "The power of the vegetable patch: How home-grown food helps large rural households achieve economies of scale & escape poverty," Food Policy, Elsevier, vol. 73(C), pages 62-74.
    5. Zezza, Alberto & Federighi, Giovanni & Kalilou, Amadou Adamou & Hiernaux, Pierre, 2016. "Milking the data: Measuring milk off-take in extensive livestock systems. Experimental evidence from Niger," Food Policy, Elsevier, vol. 59(C), pages 174-186.
    6. Abay,Kibrom A. & Barrett,Christopher B. & Kilic,Talip & Moylan,Heather G. & Ilukor,John & Vundru,Wilbert Drazi, 2022. "Nonclassical Measurement Error and Farmers’ Response to Information Reveal Behavioral Anomalies," Policy Research Working Paper Series 9908, The World Bank.
    7. John Gibson & Kathleen Beegle & Joachim De Weerdt & Jed Friedman, 2015. "What does Variation in Survey Design Reveal about the Nature of Measurement Errors in Household Consumption?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(3), pages 466-474, June.
    8. De Magalhães, Leandro & Santaeulàlia-Llopis, Raül, 2018. "The consumption, income, and wealth of the poorest: An empirical analysis of economic inequality in rural and urban Sub-Saharan Africa for macroeconomists," Journal of Development Economics, Elsevier, vol. 134(C), pages 350-371.
    9. Beegle, Kathleen & Carletto, Calogero & Himelein, Kristen, 2012. "Reliability of recall in agricultural data," Journal of Development Economics, Elsevier, vol. 98(1), pages 34-41.
    10. Sam Desiere & Lotte Staelens & Marijke D’Haese, 2016. "When the Data Source Writes the Conclusion: Evaluating Agricultural Policies," Journal of Development Studies, Taylor & Francis Journals, vol. 52(9), pages 1372-1387, September.
    11. Brzozowski, Matthew & Crossley, Thomas F. & Winter, Joachim K., 2017. "A comparison of recall and diary food expenditure data," Food Policy, Elsevier, vol. 72(C), pages 53-61.
    12. Carletto,Calogero & Deininger,Klaus W. & Muwonge, James & Savastano,Sara & Carletto,Calogero & Deininger,Klaus W. & Muwonge, James & Savastano,Sara, 2011. "Can diaries help improve agricultural production statistics ? Evidence from Uganda," Policy Research Working Paper Series 5717, The World Bank.
    13. Ugo Pica-Ciamarra & Derek Baker & Nancy Morgan & Alberto Zezza & Carlo Azzarri & Cheikh Ly & Longin Nsiima & Simplice Nouala & Patrick Okello & Joseph Sserugga, 2014. "Investing in the Livestock Sector : Why Good Numbers Matter, A Sourcebook for Decision Makers on How to Improve Livestock Data," World Bank Publications - Reports 17830, The World Bank Group.
    14. Ambler, Kate & Herskowitz, Sylvan & Maredia, Mywish K., 2021. "Are we done yet? Response fatigue and rural livelihoods," Journal of Development Economics, Elsevier, vol. 153(C).
    15. Arthi, Vellore & Beegle, Kathleen & De Weerdt, Joachim & Palacios-López, Amparo, 2018. "Not your average job: Measuring farm labor in Tanzania," Journal of Development Economics, Elsevier, vol. 130(C), pages 160-172.
    16. Joachim De Weerdt & John Gibson & Kathleen Beegle, 2020. "What Can We Learn from Experimenting with Survey Methods?," Annual Review of Resource Economics, Annual Reviews, vol. 12(1), pages 431-447, October.
    17. Deininger, Klaus & Carletto, Calogero & Savastano, Sara & Muwonge, James, 2012. "Can diaries help in improving agricultural production statistics? Evidence from Uganda," Journal of Development Economics, Elsevier, vol. 98(1), pages 42-50.
    18. Dang, Hai-Anh & Carletto, Calogero, 2022. "Recall Bias Revisited: Measure Farm Labor Using Mixed-Mode Surveys and Multiple Imputation," IZA Discussion Papers 14997, Institute of Labor Economics (IZA).
    19. Douglas Gollin & Christopher Udry, 2021. "Heterogeneity, Measurement Error, and Misallocation: Evidence from African Agriculture," Journal of Political Economy, University of Chicago Press, vol. 129(1), pages 1-80.
    20. Abay, Kibrom A. & Abate, Gashaw T. & Barrett, Christopher B. & Bernard, Tanguy, 2019. "Correlated non-classical measurement errors, ‘Second best’ policy inference, and the inverse size-productivity relationship in agriculture," Journal of Development Economics, Elsevier, vol. 139(C), pages 171-184.

    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:wbk:wbrwps:7150. See general information about how to correct material in RePEc.

    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: Roula I. Yazigi (email available below). General contact details of provider: https://edirc.repec.org/data/dvewbus.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.