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Geography and Agricultural Productivity: Cross-Country Evidence from Micro Plot-Level Data

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  • Tasso Adamopoulos
  • Diego Restuccia

Abstract

Why is agricultural productivity so low in poor countries relative to the rest of the world? Is it due to geography or constrained economic choices? We assess the quantitative role of geography and land quality for agricultural productivity differences across countries using high-resolution micro-geography data and a spatial accounting framework. Our rich spatial data provide in each cell of land covering the entire globe actual yields of cultivated crops and potential yields for 18 crops, which measure the maximum attainable output for each crop given soil quality, climate conditions, terrain topography, and a level of cultivation inputs. While there is considerable heterogeneity in land quality across space, even within narrow geographic regions, we find that low agricultural productivity in poor countries is not due to poor land endowments. If countries produced current crops in each cell according to potential yields, the rich-poor agricultural yield gap would virtually disappear, from more than 200 percent to less than 5 percent. We also find evidence of additional productivity gains attainable through the spatial reallocation of production and changes in crop choices.

Suggested Citation

  • Tasso Adamopoulos & Diego Restuccia, 2018. "Geography and Agricultural Productivity: Cross-Country Evidence from Micro Plot-Level Data," Working Papers tecipa-598, University of Toronto, Department of Economics.
  • Handle: RePEc:tor:tecipa:tecipa-598
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    Cited by:

    1. Dorinet, Elizavetta & Jouvet, Pierre-André & Wolfersberger, Julien, 2021. "Is the agricultural sector cursed too? Evidence from Sub-Saharan Africa," World Development, Elsevier, vol. 140(C).
    2. Tasso Adamopoulos & Loren Brandt & Jessica Leight & Diego Restuccia, 2022. "Misallocation, Selection, and Productivity: A Quantitative Analysis With Panel Data From China," Econometrica, Econometric Society, vol. 90(3), pages 1261-1282, May.
    3. Hernandez, M. & Britos, B. & Robles, M. & Trupkin, D., 2018. "Land market distortions: Theory and evidence from Guatemala," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277031, International Association of Agricultural Economists.
    4. Tasso Adamopoulos & Diego Restuccia, 2020. "Land Reform and Productivity: A Quantitative Analysis with Micro Data," American Economic Journal: Macroeconomics, American Economic Association, vol. 12(3), pages 1-39, July.
    5. Alvarez-Cuadrado, Francisco & Amodio, Francesco & Poschke, Markus, 2019. "Selection and Absolute Advantage in Farming and Entrepreneurship," IZA Discussion Papers 12878, Institute of Labor Economics (IZA).
    6. Gordon Menzies, 2018. "A Synthesis of the Lewis Development Model and Neoclassical Trade Models," Working Paper Series 46, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    7. Ryota Nakatani, 2017. "External Adjustment in a Resource-Rich Economy: The Case of Papua New Guinea," IMF Working Papers 2017/267, International Monetary Fund.
    8. Britos, Braulio & Hernandez, Manuel A. & Robles, Miguel & Trupkin, Danilo R., 2022. "Land market distortions and aggregate agricultural productivity: Evidence from Guatemala," Journal of Development Economics, Elsevier, vol. 155(C).
    9. Le, Kien, 2020. "Land use restrictions, misallocation in agriculture, and aggregate productivity in Vietnam," Journal of Development Economics, Elsevier, vol. 145(C).
    10. Jorge Alvarez & Claudia Berg, 2019. "Crop Selection and International Differences in Aggregate Agricultural Productivity," IMF Working Papers 2019/179, International Monetary Fund.
    11. Rodrigo Garcia‐Verdu & Alexis Meyer‐Cirkel & Akira Sasahara & Hans Weisfeld, 2022. "Importing inputs for climate change mitigation: The case of agricultural productivity," Review of International Economics, Wiley Blackwell, vol. 30(1), pages 34-56, February.
    12. Rivera-Padilla, Alberto, 2020. "Crop choice, trade costs, and agricultural productivity," Journal of Development Economics, Elsevier, vol. 146(C).
    13. Bruno Morando, 2021. "Market access and inefficient cropping patterns in Uganda," Economics Department Working Paper Series n309-21.pdf, Department of Economics, National University of Ireland - Maynooth.
    14. Bruno Morando, 2021. "Subsistence farming and factor misallocation:Evidence from Ugandan agriculture," Economics Department Working Paper Series n308-21.pdf, Department of Economics, National University of Ireland - Maynooth.
    15. Dorinet, Elizavetta & Jouvet, Pierre-André & Wolfersberger, Julien, 2021. "Is the agricultural sector cursed too? Evidence from Sub-Saharan Africa," World Development, Elsevier, vol. 140(C).

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    More about this item

    Keywords

    agriculture; land quality; productivity; spatial allocation; crop choice; cross-country.;
    All these keywords.

    JEL classification:

    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity

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