Spatial effects are determinants of agricultural land prices in Brazil

Abstract

This study aims to determine whether spatial effects are determinants of agricultural land prices in Brazil. For this purpose, data on the value of the bare land in municipalities in Brazil for 2020, provided by the Federal Revenue Service, were used. Although this database has national coverage, the contiguous data necessary for the application of spatial econometric models allowed us to cover the central-south region of the country. An exploratory spatial data analysis was performed, and the spatial Durbin econometric model was applied. Based on our results, there is a strong spatial dependence on land price, manifested both in the dependent variable, spatially lagged, and through the spillover effects of the independent variables. In addition, it was found that the degree of urbanization of a municipality, the municipal gross domestic product per capita, the average size of properties, the agricultural productivity, and the area dedicated to soybean planting in a rural property are also important determining factors in the pricing of agricultural land. Accordingly, it is possible to conclude that spatial effects influence the determination of agricultural land prices in Brazil.

Women farmers and community well‐being under modeling uncertainty

“…As outlined in Steel's (2020) comprehensive review of the modeling uncertainty literature, BMA has been introduced to provide a “theoretical mechanism to account for model uncertainty in terms of what variables should be included in the final specification of the model” (Conroy et al, 2021, p. 202). BMA is becoming more widely used and has been applied in agricultural economics by Balcombe and Rapsomanikis (2010) to assess the impact of research and development on agricultural productivity; Bryant and Davis (2008) to study U.S. meat demand; Brent (2017) to explore the demand for security in water rights in the western U.S.A.; Ker et al (2016) in a study of U.S. crop insurance premium rates; Chua et al (2001) to explore elasticities in a system of consumer demand equations; and Marques and Telles (2023) to explore the spatial determinants of agricultural land prices in Brazil. Given the growing interest in agricultural economics around the use of BMA to address issues of modeling uncertainty, applying this approach to the question of women farmers and community well‐being is a natural next step.…”

Soil erosion on arable land: An unresolved global environmental threat

“…Cost associated with off-site impacts of water erosion are substantial. For example those associated with: hydropower plants in Sao Paulo state, Brazil are estimated at USD 9.8 million per annum (Marques, 2019); all water and infrastructure sectors in UK are between GBP257 and GBP458 million per annum (Posthumus et al, 2015); the dredging of sediments and their disposal from rivers in Europe is estimated to cost EUR900 million per annum (Kuhlman et al, 2010); and 1995 estimates for the USA put the total cost of water erosion at USD7.4 billion per annum (Pimentel et al, 1995).…”