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Estimating the Impact of Weather on Agriculture

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  • Jeffrey D. Michler
  • Anna Josephson
  • Talip Kilic
  • Siobhan Murray

Abstract

This paper quantifies the significance and magnitude of the effect of measurement error in remote sensing weather data in the analysis of smallholder agricultural productivity. The analysis leverages 17 rounds of nationally-representative, panel household survey data from six countries in Sub-Saharan Africa. These data are spatially-linked with a range of geospatial weather data sources and related metrics. We provide systematic evidence on measurement error introduced by 1) different methods used to obfuscate the exact GPS coordinates of households, 2) different metrics used to quantify precipitation and temperature, and 3) different remote sensing measurement technologies. First, we find no discernible effect of measurement error introduced by different obfuscation methods. Second, we find that simple weather metrics, such as total seasonal rainfall and mean daily temperature, outperform more complex metrics, such as deviations in rainfall from the long-run average or growing degree days, in a broad range of settings. Finally, we find substantial amounts of measurement error based on remote sensing product. In extreme cases, data drawn from different remote sensing products result in opposite signs for coefficients on weather metrics, meaning that precipitation or temperature draw from one product purportedly increases crop output while the same metrics drawn from a different product purportedly reduces crop output. We conclude with a set of six best practices for researchers looking to combine remote sensing weather data with socioeconomic survey data.

Suggested Citation

  • Jeffrey D. Michler & Anna Josephson & Talip Kilic & Siobhan Murray, 2020. "Estimating the Impact of Weather on Agriculture," Papers 2012.11768, arXiv.org, revised Oct 2021.
  • Handle: RePEc:arx:papers:2012.11768
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    References listed on IDEAS

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    1. Kibrom A. Abay, 2020. "Measurement errors in agricultural data and their implications on marginal returns to modern agricultural inputs," Agricultural Economics, International Association of Agricultural Economists, vol. 51(3), pages 323-341, May.
    2. 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.
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    5. Aslihan Arslan & Nancy McCarthy & Leslie Lipper & Solomon Asfaw & Andrea Cattaneo & Misael Kokwe, 2015. "Climate Smart Agriculture? Assessing the Adaptation Implications in Zambia," Journal of Agricultural Economics, Wiley Blackwell, vol. 66(3), pages 753-780, September.
    6. Fernando M. Aragón & Francisco Oteiza & Juan Pablo Rud, 2021. "Climate Change and Agriculture: Subsistence Farmers' Response to Extreme Heat," American Economic Journal: Economic Policy, American Economic Association, vol. 13(1), pages 1-35, February.
    7. Salvador Barrios & Luisito Bertinelli & Eric Strobl, 2010. "Trends in Rainfall and Economic Growth in Africa: A Neglected Cause of the African Growth Tragedy," The Review of Economics and Statistics, MIT Press, vol. 92(2), pages 350-366, May.
    8. Amare, Mulubrhan & Jensen, Nathaniel D. & Shiferaw, Bekele & Cissé, Jennifer Denno, 2018. "Rainfall shocks and agricultural productivity: Implication for rural household consumption," Agricultural Systems, Elsevier, vol. 166(C), pages 79-89.
    9. Alfani, Federica & Arslan, Aslihan & McCarthy, Nancy & Cavatassi, Romina & Sitko, Nicholas, 2021. "Climate resilience in rural Zambia: evaluating farmers’ response to El Niño-induced drought," Environment and Development Economics, Cambridge University Press, vol. 26(5-6), pages 582-604, October.
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    11. David B Lobell & George Azzari & Marshall Burke & Sydney Gourlay & Zhenong Jin & Talip Kilic & Siobhan Murray, 2020. "Eyes in the Sky, Boots on the Ground: Assessing Satellite‐ and Ground‐Based Approaches to Crop Yield Measurement and Analysis," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(1), pages 202-219, January.
    12. Asfaw, S., 2018. "Market Participation, Weather Shocks and Welfare: Evidence from Malawi," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277029, International Association of Agricultural Economists.
    13. Asfaw, Solomon & Scognamillo, Antonio & Caprera, Gloria Di & Sitko, Nicholas & Ignaciuk, Adriana, 2019. "Heterogeneous impact of livelihood diversification on household welfare: Cross-country evidence from Sub-Saharan Africa," World Development, Elsevier, vol. 117(C), pages 278-295.
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    Cited by:

    1. McCarthy, Nancy & Brubaker, Josh & Mabiso, Athur & Cavatassi, Romina, 2022. "IFAD Research Series 87: Incorporating the Impact of Climate and Weather Variables in Impact Assessments - An Application to an IFAD Grain Storage Project Implemented in Chad," IFAD Research Series 329498, International Fund for Agricultural Development (IFAD).
    2. Randell, Heather & Gray, Clark & Shayo, Elizabeth H., 2022. "Climatic conditions and household food security: Evidence from Tanzania," Food Policy, Elsevier, vol. 112(C).
    3. Michler, Jeffrey D. & Josephson, Anna & Kilic, Talip & Murray, Siobhan, 2022. "Privacy protection, measurement error, and the integration of remote sensing and socioeconomic survey data," Journal of Development Economics, Elsevier, vol. 158(C).
    4. McCarthy, Nancy & Brubaker, Josh & Mabiso, Athur & Cavatassi, Romina, 2022. "IFAD Research Series 86: Incorporating the Impact of Climate and Weather Variables into Impact Assessments - An Application to an IFAD Production Project in Rwanda," IFAD Research Series 329321, International Fund for Agricultural Development (IFAD).
    5. Sarah A. Janzen & Jeffrey D. Michler, 2021. "Ulysses' pact or Ulysses' raft: Using pre‐analysis plans in experimental and nonexperimental research," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(4), pages 1286-1304, December.

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