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Analysing farmland rental rates using Bayesian geoadditive quantile regression

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  • März, Alexander
  • Klein, Nadja
  • Kneib, Thomas
  • Musshoff, Oliver

Abstract

Empirical studies on farmland rental rates have predominantly concentrated on modelling conditional means using spatial autoregressive models, where a linear functional form be- tween the response and the covariates is assumed. This paper extends the hedonic pricing literature by modelling conditional quantiles of farmland rental rates semi-parametrically using Bayesian geoadditive quantile regression models. The flexibility of this model class overcomes the problems associated with functional form misspecifications and allows us to present a more detailed analysis. Our results stress the importance of making use of semi- parametric regression models as several covariates influence farmland rental rates in an ex- plicit non-linear way.

Suggested Citation

  • März, Alexander & Klein, Nadja & Kneib, Thomas & Musshoff, Oliver, 2014. "Analysing farmland rental rates using Bayesian geoadditive quantile regression," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182752, European Association of Agricultural Economists.
  • Handle: RePEc:ags:eaae14:182752
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    References listed on IDEAS

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    Cited by:

    1. Demartini, Eugenio & Gaviglio, Anna & Gelati, Marco & Cavicchioli, Daniele, 2016. "The Lords of the Rent," 149th Seminar, October 27-28, 2016, Rennes, France 245705, European Association of Agricultural Economists.
    2. Kualwik, Jacek, 0. "Selected problems of farmland valuation and setting rents for its lease," Problems of Agricultural Economics, Institute of Agricultural and Food Economics - National Research Institute (IAFE-NRI).

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