Revisiting the relationship between land price and parcel size in agriculture
2020 (English) In: Land use policy, ISSN 0264-8377, E-ISSN 1873-5754, Vol. 97, article id 104771Article in journal (Refereed) Published
Abstract [en]
Hedonic land price models often use parcel size as an explanatory variable. Empirical analyses, however, are rather ambiguous regarding the direction and the size of the effect of this variable on farmland values. The objective of this paper is to investigate this size–price relation for agricultural land use in detail and to derive recommendations for an appropriate specification of hedonic land price models. Our analysis consists of three steps. First, we conduct a meta-analysis based on a comprehensive literature review. Second, we analyze a dataset of more than 80,000 agricultural land transactions in Saxony-Anhalt, Germany, using the nonparametric locally weighted scatterplot smoothing (LOWESS) estimator. This unconditional smoothing algorithm identifies negative size–price relations for very small and large plots, whereas it finds a positive relation for medium plots. We use this finding in our third step, a hedonic land price model, in which the size–price relation is modeled conditional on land and buyer characteristics. From these steps, we conclude that the complex relationship between land price and plot size cannot be captured by a simple functional form since it is affected by several economic factors, such as economies of size, transaction costs, and financial constraints.
Place, publisher, year, edition, pages Elsevier, 2020. Vol. 97, article id 104771
Keywords [en]
Hedonic model, Land prices, LOWESS, Parcel size, agricultural land, algorithm, hedonic analysis, land market, land use, land use change, land use planning, literature review, meta-analysis, price dynamics, transaction cost, Germany, Saxony-Anhalt
National Category
Economics
Identifiers URN: urn:nbn:se:hj:diva-54511 DOI: 10.1016/j.landusepol.2020.104771 ISI: 000558748500019 Scopus ID: 2-s2.0-85085647221 OAI: oai:DiVA.org:hj-54511 DiVA, id: diva2:1614336
2021-11-252021-11-252021-11-25 Bibliographically approved