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Determinants Of Agricultural Land Abandonment In Postsoviet European Russia

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  • Prishchepov, Alexander V.
  • Radeloff, Volker C.
  • Muller, Daniel
  • Dubinin, Maxim
  • Baumann, Matthias

Abstract

Socio-economic and institutional changes may accelerate the rates and determinants of land-use and land-cover change (LULCC). Our goal was to explore the determinants of agricultural land abandonment in post-soviet Russia during the first decade of transition from-state command to market driven economy from 1990 to 2000. Based on economic assumptions of the profit maximization we selected and analyzed the determinants of agricultural land abandonment for one large agro-climatic and economic region of European Russia that covered 150,500 km2 and 67 districts in Kaluga, Rjazan, Smolensk, Tula and Vladimir provinces. We integrated maps of abandoned agricultural land (five Landsat TM/ETM+ footprints 185*185 km each with 30-m resolution), environmental and geographic determinants, and socioeconomic statistics and estimated logistic regressions at the pixel-level. Our results showed that agricultural land abandonment was significantly associated with lower average grain yields in the late 1980s, distances to villages, municipalities and settlements > 500 citizens, isolated agricultural areas within the forest matrix and distances from forest edges. Hierarchical partitioning showed that average grain yields in the late 1980s contributed the most in explaining the variability of abandonment (42%, of the explained variability), followed by location characteristics of the land. The results suggest that the underling driving forces such as massive decline of state subsidies for agriculture was a key contributor for the amount of abandonment and those areas socially, economically and environmentally marginal agriculture areas were the first to be left uncultivated.

Suggested Citation

  • Prishchepov, Alexander V. & Radeloff, Volker C. & Muller, Daniel & Dubinin, Maxim & Baumann, Matthias, 2011. "Determinants Of Agricultural Land Abandonment In Postsoviet European Russia," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 120390, European Association of Agricultural Economists.
    • Handle: RePEc:ags:eaae11:120390
    DOI: 10.22004/ag.econ.120390
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    References listed on IDEAS

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    1. Lerman, Zvi & Csaki, Csaba & Feder, Gershon, 2002. "Land policies and evolving farm structures in transition countries," Policy Research Working Paper Series 2794, The World Bank.
    2. Michael A Trueblood & Carlos Arnade, 2001. "Crop Yield Convergence: How Russia's Yield Performance Has Compared to Global Yield Leaders," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 43(2), pages 59-81, July.
    3. Holden, Ken & Klein, Philip A. & Lahiri, Kajal, 2001. "Introduction," International Journal of Forecasting, Elsevier, vol. 17(3), pages 329-332.
    4. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
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    More about this item

    Keywords

    Land Economics/Use;

    JEL classification:

    • Q15 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment

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