IDEAS home Printed from https://ideas.repec.org/p/wbk/wbrwps/5717.html

Can diaries help improve agricultural production statistics ? Evidence from Uganda

Author

Listed:
  • Carletto,Calogero
  • Deininger,Klaus W.
  • Muwonge, James
  • Savastano,Sara
  • Carletto,Calogero
  • Deininger,Klaus W.
  • Muwonge, James
  • Savastano,Sara

Abstract

Although good and timely information on agricultural production is critical for policy-decisions, the quality of underlying data is often low and improving data quality could have a high payoff. This paper uses data from a production diary, administered concurrently with a standard household survey in Uganda to analyze the nature and incidence of responses, the magnitude of differences in reported outcomes, and factors that systematically affect these. Despite limited central supervision, diaries elicited a strong response, complemented standard surveys in a number of respects, and were less affected by problems of respondent fatigue than expected. The diary-based estimates of output value consistently exceeded that from the recall-based production survey, in line with reported disposition. Implications for policy and practical administration of surveys are drawn out.

Suggested Citation

  • 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.
    • Handle: RePEc:wbk:wbrwps:5717
    as

    Download full text from publisher

    File URL: http://documents.worldbank.org/curated/en/747881468110668485/pdf/Can-diaries-help-improve-agricultural-production-statistics-Evidence-from-Uganda.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. repec:wbk:wbpubs:25338 is not listed on IDEAS
    3. 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.
    4. repec:bla:obuest:v:64:y:2002:i:4:p:341-59 is not listed on IDEAS
    5. 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)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Bachewe, Fantu Nisrane & Berhane, Guush & Minten, Bart & Taffesse, Alemayehu Seyoum, 2015. "Agricultural growth in Ethiopia (2004-2014): Evidence and drivers," ESSP working papers 81, International Food Policy Research Institute (IFPRI).
    3. Anna Christine Durante & Pamela Lapitan & David Megill & Lakshman Nagraj Rao, 2018. "Improving Paddy Rice Statistics Using Area Sampling Frame Technique," ADB Economics Working Paper Series 565, Asian Development Bank.
    4. Bachewe, Fantu N. & Berhane, Guush & Minten, Bart & Taffesse, Alemayehu S., 2018. "Agricultural Transformation in Africa? Assessing the Evidence in Ethiopia," World Development, Elsevier, vol. 105(C), pages 286-298.
    5. 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.

    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. 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.
    2. 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.
    3. 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.
    4. Fiedler, John L. & Mwangi, Dena M., 2016. "Improving household consumption and expenditure surveys’ food consumption metrics: Developing a strategic approach to the unfinished agenda," IFPRI discussion papers 1570, International Food Policy Research Institute (IFPRI).
    5. Calogero Carletto & Dean Jolliffe & Raka Banerjee, 2015. "From Tragedy to Renaissance: Improving Agricultural Data for Better Policies," Journal of Development Studies, Taylor & Francis Journals, vol. 51(2), pages 133-148, February.
    6. Brzozowski, Matthew & Crossley, Thomas F. & Winter, Joachim K., 2017. "Does survey recall error explain the Deaton–Paxson puzzle?," Economics Letters, Elsevier, vol. 158(C), pages 18-20.
    7. Laura E. McCann & Jeffrey D. Michler & Maybin Mwangala & Osaretin Olurotimi & Natalia Estrada Carmona, 2024. "Food Without Fire: Nutritional and Environmental Impacts from a Solar Stove Field Experiment," Papers 2410.02075, arXiv.org.
    8. Backiny-Yetna, Prospère & Steele, Diane & Yacoubou Djima, Ismael, 2017. "The impact of household food consumption data collection methods on poverty and inequality measures in Niger," Food Policy, Elsevier, vol. 72(C), pages 7-19.
    9. Nicole Jonker & Anneke Kosse, 2013. "Estimating Cash Usage: The Impact of Survey Design on Research Outcomes," De Economist, Springer, vol. 161(1), pages 19-44, March.
    10. Campos, Rodolfo G. & Reggio, Iliana, 2014. "Measurement error in imputation procedures," Economics Letters, Elsevier, vol. 122(2), pages 197-202.
    11. 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.
    12. Conforti, Piero & Grünberger, Klaus & Troubat, Nathalie, 2017. "The impact of survey characteristics on the measurement of food consumption," Food Policy, Elsevier, vol. 72(C), pages 43-52.
    13. Abay, Kibrom A. & Berhane, Guush & Hoddinott, John F. & Tafere, Kibrom, 2021. "Assessing response fatigue in phone surveys: Experimental evidence on dietary diversity in Ethiopia," IFPRI discussion papers 2017, International Food Policy Research Institute (IFPRI).
    14. Ana Cinta G Cabral & Christos Kotsogiannis & Gareth Myles, 2019. "Self-Employment Income Gap in Great Britain: How Much and Who?," CESifo Economic Studies, CESifo Group, vol. 65(1), pages 84-107.
    15. Troubat, Nathalie & Grünberger, Klaus, 2017. "Impact of survey design in the estimation of habitual food consumption," Food Policy, Elsevier, vol. 72(C), pages 132-145.
    16. Ameye, Hannah & De Weerdt, Joachim & Gibson, John, 2021. "Measuring macro- and micronutrient consumption in multi-purpose surveys: Evidence from a survey experiment in Tanzania," Food Policy, Elsevier, vol. 102(C).
    17. Janz, Teresa & Augsburg, Britta & Gassmann, Franziska & Nimeh, Zina, 2023. "Leaving no one behind: Urban poverty traps in Sub-Saharan Africa," World Development, Elsevier, vol. 172(C).
    18. Dang, Hai-Anh & Carleto, Gero & Gourlay, Sydney & Abanokova, Kseniya, 2023. "Addressing Soil Quality Data Gaps with Imputation: Evidence from Ethiopia and Uganda," 2023 Annual Meeting, July 23-25, Washington D.C. 335648, Agricultural and Applied Economics Association.
    19. Sanae Tashiro, 2009. "Differences in Food Preparation by Race and Ethnicity: Evidence from the American Time Use Survey," The Review of Black Political Economy, Springer;National Economic Association, vol. 36(3), pages 161-180, December.
    20. Wilfred Catin Botchuin, 2023. "Inclusive Growth Analysis: Evidence from Côte d’Ivoire," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 76(1), pages 91-134.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:5717. 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.