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date: 15 October 2019

Abstract and Keywords

Farmland has long represented a significant component of both farm sector and farm household assets. This chapter provides a comprehensive overview of significant developments in modeling farmland values, with attention to methodological challenges and recent modeling innovations. After outlining the capitalization model that provides the theoretical underpinnings for most farmland value studies, the merits and efficacy of dynamic models using aggregate data, as well as increasingly popular cross-sectional hedonic models that use spatially disaggregate data are presented. Estimation issues in hedonic models are reviewed, with a focus on those deserving special consideration in the context of farmland values such as spatial dependence and heterogeneity and sample selection bias. Promising future research directions include greater use of nonparametric approaches, quasi-experimental designs, panel data analyses, and structural econometric models, which take advantage of spatially explicit farmland values data but avoid the restrictive assumptions of standard spatial lag and spatial error models.

Keywords: farmland values, capitalization model, dynamic models, hedonic models, sample selection bias, spatial dependence

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