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This study aims at estimating the percent impact on the price of farmland of the following physical attributes: size, soil quality, water rights, connectivity and location. To this effect, all the farm sales occurred in the province of Talca between 2003 and 2006 were examined, directly from the corresponding title deeds, at the Conservador de Bien...
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This study aims at estimating the percent impact on the price of farmland of the following physical attributes: Size, soil quality, water rights, connectivity and location. To this effect, all the farm sales occurred in the province of Talca between 2003 and 2006 were examined, directly from the corresponding title deeds, at the Conservador de Bien...
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... [3,6,7,20,28,29,33,45]. H -Good access [3,6,16,17,20,28,30,34,35,36,39,41,47]. I -Macroeconomic conditions [7,32,38,42,43,44,48]. ...
... I -Macroeconomic conditions [7,32,38,42,43,44,48]. L -Land characteristics L1 -Water rights [7,16,30,34,36,45,47,49,50,51]. L2 -Soil productivity [2,20,29,28,41,6,3,17,33,34,35,30,36,52,50,37,45]. ...
... L -Land characteristics L1 -Water rights [7,16,30,34,36,45,47,49,50,51]. L2 -Soil productivity [2,20,29,28,41,6,3,17,33,34,35,30,36,52,50,37,45]. L3 -Climate [2,17,20,29,32,39,43,49]. ...
This article aims to perform a literature review on the topic of farmland valuation, covering the determinants of farmland value and the models that are used to price land. To do so, recent literature on the topic was combined with classical and well-known papers. All the factors considered in these papers to explain farmland prices and/or to model them were retrieved, presented, and compared. Then, the main models proposed in the literature are presented and their suitability and goals are explained. This study can help academics as it gives an overview of the current state of the art, summarizes the main factors proposed by researchers to explain farmland prices, and sheds light on new lines of research. Besides that, it is also relevant for policymakers because farmland valuation and its use have implications on society and on urban planning, which is a hot topic under discussion.
... We found that land area decreases land value, both for agricultural and housing uses. This result is in line with the finding of [51][52][53][54][55] that the economic value decreases with an increase in land area. The intensity of labor and input use declines with increasing farm size; hence, the productivity of the land and hence net return declines. ...
... The accessibility variables (distance to irrigation, the nearest market, and the road) show a negative effect. This result is in line with the results from [54][55][56][57]. A great distance to the nearest 2 In this study, we do not systematically assess the impact of urbanization on agricultural activities in the peri-urban area. ...
Agricultural land conversion (ALC) is an incentive-driven process. In this paper, we further investigate the inter-relationship between land economic value (LEV) and ALC. To achieve this goal, we calculated the LEV for agricultural and non-agricultural (housing) uses in two areas of East Java, Indonesia. The first area represents peri-urban agriculture, which is facing rapid urbanization and experiencing a high rate of ALC. The second area represents rural agriculture, with zero ALC. Furthermore, we identified factors affecting LEV in both areas for both uses. The results of this study show that agricultural land yielded a higher economic benefit in rural areas. Conversely, compared to agricultural land, housing in urban areas yields a value that is seven times higher. Moreover, agricultural land was shown to yield a higher profit after conversion. Ironically, a similar comparison does not exist in rural areas. Agricultural land yielded a value that was only 19% higher, indicating that agricultural land can easily be converted. This is also proven by the growing number of new urban cores in the periphery area. There are several factors affecting land economic value, such as agricultural use, soil fertility, accessibility, and cropping pattern, which are important variables. Meanwhile, the accessibility and location of peri-urban areas increase the land value for housing.
Using spatial regression models, we detect determinants of farmland’s prices in a rural area located in the upper Treviso plain (Veneto region, Italy). Econometric analysis is based on a Spatial linear regression model able to account for spatial lags in the data. Estimates show which intrinsic and extrinsic characteristics have the greatest influence on price, and how buyers and sellers’ profiles also matter on the price determination. Our application fosters spatial regression models in rural real estate market analysis and appraisal, and highlights that in the area under study the farmland’s prices are significantly affected by factors that are rarely considered in the literature, such as sellers and buyers’ profiles, the land use in the context where the sold plot is located matters, the hydraulic risk of the area and the presence of large infrastructures.
In 2000, to efficiently implement land-use policies, the Taiwanese government amended the Agricultural Development Act by easing restrictions on agricultural land purchases. As a result of increasing land development and investment needs, agricultural land prices have surged. This study aims to examine whether agricultural land prices in Pingtung County are affected by land control policy measures, the pressure of agricultural land conversion and the degree of urbanization. A multilevel analysis approach was used to analyze land price differences in townships in Pingtung County. The estimation results derived from the null model indicated significant differences between the mean land price in each administrative division. Specifically, the ratio of agricultural land prices affected by differences in Level 2 township-related factors was 21.8%, while the ratio of those affected by differences in Level 1 land-related factors was 78.2%. An empirical intercepts-and-slopes-as-outcomes regression model demonstrated that Level 2 township-related factors, such as the pressure of agricultural land conversion and the degree of urbanization, had cross-level, direct and positive impacts on agricultural land prices; while Level 1 land-related factors, such as lot size control measures on farmhouse construction and land-use zoning, had positive and significant impacts on agricultural land prices.
Agricultural land conversion (ALC) is an incentive–driven process. In this paper we further investigate the inter–relationship between land economic value (LEV) and ALC. To achieve this goal, we calculated LEV for agricultural and non-agricultural (housing) uses in two areas in East Java, Indonesia. The first area represents suburban agriculture, facing rapid urbanization and experiencing high rate of ALC. The second area represents rural agriculture with zero ALC. Furthermore, we identified factors affecting LEV in both areas for both uses. The resut of this study show that agricultural land yielded higher economic benefit in rural area. Conversely, comparing to agricultural land, housing creates 7 times higher value in urban area. Moreover, agricultural land shown to create higher profit after converted. Ironically, the similar comparison doesn’t exists in rural area. Agricultural land only yielded 19% more value, indicate that agricultural land can be easily converted. It is also proven by the growing number of new urban core in the periphery area. There are several factors affecting land economic value, for agricultural use, soil fertility, accessibility, and cropping pattern are important variables. While accessibility and location in urban area increases land value for housing.
Research on the determinants that influence the price of farmland has regained interest in the past decade since agricultural land values are an important source of information for tracing the distribution of benefits generated by agricultural growth. This study’s objective is to identify the determinants of the value of agricultural land in Chile for the period 1978-1998 and for the period 1999-2008 so as to analyze the evolution of the factors that determine the price of agricultural land between these two periods. The explanatory power of the estimated hedonic land price model is significantly greater for the period 1978-1998 (R2= 67%). The lower explanatory power of the model for the period 1999-2008 (R2= 29%) indicates that factors not accounted for in the model have increased its importance during the past decade. Thus, a different set of factors determine farmland value for each time period. Further research is required to identify the determining factors of farmland value during the last decade. Some variables maintained their relative importance during both time periods. This is the case of the importance of the distance between the farm and Santiago, ranked second in both periods, and total farm surface, ranked fifth. All other variables present changes in their relative importance. Price trend increases from third rank to the first rank in the last decade. Price of the most important agricultural product increases 5 positions, ranking third during the period 1999-2008. The distance of the farm to the regional capital increases from the last position during period 1978-1998 to the fourth position during the last decade. Other factors that increased their importance are the interaction between the distance to Santiago with the time trend and the presence of constructions. The variables that reduce their relative importance are the farmland aptitude variables.
