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Assessing Misallocation in Agriculture: Plots versus Farms

Author

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  • Fernando M. Aragón
  • Diego Restuccia
  • Juan Pablo Rud

Abstract

We examine empirically whether the level of data aggregation affects the assessment of misallocation in agriculture. Using data from Ugandan farmers, we document a substantial discrepancy between misallocation measures calculated at the plot and at the farm levels. Estimates of misallocation at the plot level are much higher than those estimated with the same data but aggregated at the farm level. Even after accounting for measurement error and unobserved heterogeneity, estimates of misallocation at the plot level are extremely high, with nationwide agricultural productivity gains of 562%. Furthermore, we find suggestive evidence that granular data may be more susceptible to measurement error in survey data and that data aggregation can attenuate the relative magnitude of measurement error in misallocation measures. Our findings suggest caution in generalizing insights on measurement error and misallocation from plot-level analysis to those at the farm level.

Suggested Citation

  • Fernando M. Aragón & Diego Restuccia & Juan Pablo Rud, 2022. "Assessing Misallocation in Agriculture: Plots versus Farms," NBER Working Papers 29749, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:29749
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    Cited by:

    1. Peterson-Wilhelm, Bailey & Schwab, Benjamin, 2024. "How does recall bias in farm labor impact separability tests?," Food Policy, Elsevier, vol. 128(C).
    2. 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.
    3. Marijn Bolhuis & Swapnika Rachapalli & Diego Restuccia, 2021. "Misallocation in Indian Agriculture," Working Papers tecipa-709, University of Toronto, Department of Economics.
    4. James R. Stevenson & Karen Macours & Douglas Gollin, 2023. "The Rigor Revolution: New Standards of Evidence for Impact Assessment of International Agricultural Research," Annual Review of Resource Economics, Annual Reviews, vol. 15(1), pages 495-515, October.
    5. Stephen Ayerst & Loren Brandt & Diego Restuccia, 2023. "Distortions, Producer Dynamics, and Aggregate Productivity: A General Equilibrium Analysis," Working Papers tecipa-754, University of Toronto, Department of Economics.

    More about this item

    JEL classification:

    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity
    • O55 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Africa
    • Q1 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture

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