Spatial effects are determinants of agricultural land prices in Brazil

Marques, Felipe César; Telles, Tiago Santos

doi:10.1590/1806-9479.2022.262420en

Acessibilidade / Reportar erro

Brasil

Revista de Economia e Sociologia Rural

Español English

Brasil

Español English

sumário « anterior atual seguinte »

Sumário

Article • Rev. Econ. Sociol. Rural 61 (3) • 2023 • https://doi.org/10.1590/1806-9479.2022.262420en copy

Spatial effects are determinants of agricultural land prices in Brazil

Authorship SCIMAGO INSTITUTIONS RANKINGS

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.

Keywords:
land market; land value; spatial econometrics; price dynamics; land use planning

Variable	Description	Year	Source
ln_price	Natural logarithm of bare land value - VTN (in Brazilian reais)	2020	Federal Revenue Service
Urb_degree	Degree of urbanization (%) in the municipality	2017	IBGE
Over_100ha	Proportion (%) of properties with more than 100 hectares in relation to the total of properties	2017	IBGE - Agricultural Census
Productivity	Value of agricultural production (in thousands of reais) per hectare of planted area	2020	IBGE - Municipal Agricultural Production
Soybean_area	Proportion (%) of soybean planted area in relation to total planted area	2020	IBGE - Municipal Agricultural Production
Credit_ha	Value of agricultural subsidy in the 2019-2020 harvest (in thousands of reais) per hectare of planted area	2019/ 2020	Central Bank and IBGE - Municipal Agricultural Production
Agricultural_ GDP	Proportion (%) of the gross domestic product (GDP) in the agricultural sector in relation to total municipal GDP	2018	IBGE
Per_capita_GDP	Municipal GDP per capita (in thousands of reais)	2018	IBGE
Owner	Proportion (%) of landowners in relation to total agricultural producers	2017	IBGE - Agricultural Census
Distance	Distance (in 100 km) to the nearest municipality with more than 500 thousand inhabitants	2020	IBGE and DATASUS

Variable	Parameter		Standard error
Urb_degree	0.002191	***	0.000310
Agricultural_GDP	0.001287		0.000872
Per_capita_GDP	0.001071	***	0.000398
Over_100ha	−0.007607	***	0.000988
Owner	0.000070		0.000720
Productivity	0.006085	***	0.001139
Credit_ha	−0.000241	***	0.000052
Distance	−0.092778	***	0.016964
Soybean_area	0.002493	***	0.000683
Constant	9.080633	***	0.131743
Fixed Effects (mesoregions)	Yes
Observations	2,448
R²	0.792
F	137.581	***
Moran's I (error)	0.265	***
ML (lag)	561.852	***
ML robust (lag)	101.288	***
ML (error)	464.016	***
ML robust (error)	3.452	*

Variable	Parameter		Standard error
Urb_degree	0.001217	***	0.000278
Agricultural_GDP	0.000927		0.000779
Per_capita_GDP	0.000227		0.000353
Over_100ha	−0.003177	***	0.001009
Owner	0.000872		0.000661
Productivity	0.004204	***	0.001079
Credit_ha	−0.000289	***	0.000045
Distance	−0.079555		0.076594
Soybean_area	0.002267	***	0.000735
W.Urb_degree	0.002173	***	0.000627
W.Agricultural_GDP	−0000003		0.001644
W.Per_capita_GDP	0.001601	**	0.000773
W.Over_100ha	−0.005236	***	0.001677
W.Owner	−0.002550	*	0.001337
W. Productivity	0.003076		0.001925
W.Credit_ha	0.000366	***	0.000134
W.Distance	0.057593		0.082199
W.Soybean_area	−0.000654		0.001107
W.ln_price	0.452450	***	0.022425
Constant	4.942867	***	0.263286
Fixed Effects (mesoregions)	Yes
Observations	2,448
Pseudo R²	0.812
Wald χ²	12568.583	***
Moran's I (error)	−0.018

Variable	Direct effects		Indirect effects		Total effects
Urb_degree	0.001486	***	0.004706	***	0.006192	***
Urb_degree	(0.000284)		(0.001047)		(0.001145)
Agricultural_GDP	0.000968		0.000719		0.001687
Agricultural_GDP	(0.0008)		(0.002793)		(0.003078)
Per_capita_GDP	0.000395		0.002944	**	0.003339	**
Per_capita_GDP	(0.000366)		(0.001321)		(0.001465)
Over_100ha	−0.003836	***	−0.011529	***	−0.015365	***
Over_100ha	(0.000981)		(0.002502)		(0.002577)
Owner	0.000659		−0.003724	*	−0.003065
Owner	(0.000666)		(0.002226)		(0.002406)
Productivity	0.004696	***	0.008601	***	0.013297	***
Productivity	(0.001068)		(0.003099)		(0.003303)
Credit_ha	−0.000265	***	0.000407	*	0.000142
Credit_ha	(0.00005)		(0.000235)		(0.000261)
Distance	−0.077422		0.037311		−0.040110
Distance	(0.072082)		(0.084085)		(0.030789)
Soybean_area	0.002303	***	0.000642		0.002945	*
Soybean_area	(0.000712)		(0.001659)		(0.001688)

Sociedade Brasileira de Economia e Sociologia Rural Av. W/3 Norte, Quadra 702 Ed. Brasília Rádio Center Salas 1049-1050, 70719 900 Brasília DF Brasil, - Brasília - DF - Brazil
E-mail: sober@sober.org.br

Acompanhe os números deste periódico no seu leitor de RSS

[1] Note: *** p < 0.01; * p < 0.1.