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Measuring liquidity in agricultural land markets

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  • Kionka, Marlene
  • Odening, Martin
  • Plogmann, Jana
  • Ritter, Matthias

Abstract

This paper contributes to the sparse empirical literature on measuring liquidity in agricultural land markets. Using data from Lower Saxony (Germany), we inspect the spatial and temporal variability of various liquidity indicators. We apply a panel vector autoregression (VAR) and Granger causality tests to examine the relationship between liquidity and prices and to identify further determinants of land market liquidity, such as supply shocks and clientele effects. Unlike in housing markets, no positive relationship between prices and market liquidity exists. We conclude that in agricultural land markets, a high demand from expanding farms absorbs supply shocks regardless of prevailing prices.

Suggested Citation

  • Kionka, Marlene & Odening, Martin & Plogmann, Jana & Ritter, Matthias, 2020. "Measuring liquidity in agricultural land markets," FORLand Working Papers 25 (2020), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    • Handle: RePEc:zbw:forlwp:252020
    DOI: 10.18452/22244
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    Cited by:

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    2. Maximilian Humpesch & Stefan Seifert & Alfons Balmann & Silke Hüttel, 2022. "How does tenancy affect farmland prices? Effects of lease status, lease term and buyer type," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 83(2), pages 242-263, September.

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    More about this item

    Keywords

    Agricultural land markets; liquidity indicators; panel vector autoregressive model; Granger causality;
    All these keywords.

    JEL classification:

    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness
    • Q24 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Land
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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