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Analysing farmland rental rates using Bayesian geoadditive quantile regression

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

Abstract

Empirical studies on farmland rental rates so far have predominantly concentrated on modelling conditional means using spatial autoregressive models. While these models only focus on the central tendency of the response variable, quantile regression provides more detailed insight by modelling different points of the conditional distribution as a function of covariates. Based on data from the German agricultural census, this article contributes to the agricultural economics literature by modelling conditional quantiles of farmland rental rates semi-parametrically using Bayesian geoadditive quantile regression. Our results stress the importance of using semi-parametric regression models, as several covariates influence rental rates in an explicit non-linear way. Moreover, our analysis allows us to uncover potential heterogeneities of the estimated effects across the conditional distribution of rental rates. By explicitly modelling and visually presenting the spatial effects, we also provide additional insight into the spatial structure of German farmland rental rates.

Suggested Citation

  • Alexander März & Nadja Klein & Thomas Kneib & Oliver Musshoff, 2016. "Analysing farmland rental rates using Bayesian geoadditive quantile regression," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 43(4), pages 663-698.
  • Handle: RePEc:oup:erevae:v:43:y:2016:i:4:p:663-698.
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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. Danne, Michael & Buchholz, Matthias & Musshoff, Oliver, 2019. "An experimental analysis of German farmers’ decisions to buy or rent farmland," 165th Seminar, April 4-5, 2019, Berlin, Germany 288295, European Association of Agricultural Economists.
    3. Cord-Friedrich von Hobe & Marius Michels & Oliver Musshoff, 2021. "German Farmers’ Perspectives on Price Drivers in Agricultural Land Rental Markets—A Combination of a Systematic Literature Review and Survey Results," Land, MDPI, Open Access Journal, vol. 10(2), pages 1-22, February.
    4. Ngandu Balekelayi & Solomon Tesfamariam, 2020. "Geoadditive Quantile Regression Model for Sewer Pipes Deterioration Using Boosting Optimization Algorithm," Sustainability, MDPI, Open Access Journal, vol. 12(20), pages 1-24, October.
    5. Kualwik, Jacek, 2016. "Selected problems of farmland valuation and setting rents for its lease," Problems of Agricultural Economics / Zagadnienia Ekonomiki Rolnej 252639, Institute of Agricultural and Food Economics - National Research Institute (IAFE-NRI).
    6. Kuethe, Todd H. & Bigelow, Daniel P., 2018. "Bargaining Power in Farmland Rental Markets," 2018 Annual Meeting, August 5-7, Washington, D.C. 274113, Agricultural and Applied Economics Association.
    7. Hennig Solveigh & Breustedt Gunnar, 2018. "The Incidence of Agricultural Subsidies on Rental Rates for Grassland," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 238(2), pages 125-156, April.

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