Farmland Values Research Articles

Population, Income, and Farmland Pricing in an Open Economy

Farmland valuation models usually incorporate local purchasing power as one of the pricing factors. A plausible rationale is that a larger population and higher income per capita imply increasing demand for agricultural products and farmland. In this paper, we study the relationship between the agricultural land prices, the regional population, and income per capita in an open economy setting in nominal and real variable terms using data from 1929 to 2018 at the state level. We show that in most areas of the United States, agricultural land prices are less affected by the state population or personal income. The valuation of agricultural land should not factor in the local purchasing power factors, with a few exceptions.

The Effect of Land Use Restrictions Protecting Endangered Species on Agricultural Land Values

This article examines the effect of U.S. Endangered Species Act (ESA) regulations on agricultural values. Agricultural development is an important contributor to habitat and biodiversity loss in the United States. The ESA attempts to limit this loss by prohibiting habitat destruction on private lands, but this practice is controversial because it places much of the burden for conservation on farmers. I measure the effect of these restrictions on agriculture using a hedonic analysis of county‐level agricultural land values, profits, and revenues reported in the last four rounds of the agricultural census. Results provide strong evidence that ESA regulations depress these three economic measures in dryland areas, which includes counties with less than 1% of agricultural land in irrigation. Specifically, I find that farmland value and profit decline 4% after listing on average at the county level in dryland areas with protected habitat. There is no evidence that values are affected in irrigated counties.

Prices paid for farmland in Ontario: Does buyer type matter?

AbstractIn the wake of the substantial increases in farmland values that have occurred in Ontario since 2008, concerns have been expressed regarding the potential influence of nonfarmer buyers, such as investment companies and foreign buyers, on prices paid for farmland. To examine whether these concerns may be warranted, this paper estimates the impact of nonfarmer buyers on sale prices for farmland in Ontario, using a hedonic approach and farmland sales data from 2002 to 2016. Analysis is also conducted to determine whether marginal implicit prices of specific farm attributes differ between farmer buyers and nonfarmer buyers. The results indicate that nonfarmer buyers have paid higher prices for farmland, but only in near‐urban areas. In addition, differences in marginal implicit prices for farmland attributes are found, where farmer buyers value more highly attributes related to the agricultural productivity of the property while nonfarmer buyers value more highly attributes related to nonagricultural use. These results imply that the higher prices paid by nonfarmers may be attributable to the bid‐rent theory, as nonfarmers may be bidding more than farmers for farmland in near‐urban areas due to higher expected returns from future urban use of the land.

Can environmental disamenities increase land values? A case study of manufacturing factories on farmland

The theory of ‘not in my backyard (NIMBY)’ in the environmental economics literature shows that disamenities can reduce land or property values. In contrast to prior research, this study provides an interesting case study to show that environmental disamenities can increase farmland values. Using population-based farmland sales data drawn from administrative profiles in Taiwan, we estimate the impacts of manufacturing factories on farmland sales prices. The regression discontinuity design is applied to identify these causal effects. We find that the presence of manufacturing factories increase farmland sales prices by 21.4 percent, ceteris paribus. The positive effects are more pronounced for farmland with manufacturing factories that produce soil and heavy metal waste. We argue that these contradictory findings to the NIMBY literature are attributable to loose law enforcement measures due to the low detection rate and penalties on illegal uses of farmland. Strict law enforcement and policy reforms are needed to remove these distortions of farmland use.

Measuring the effectiveness of land consolidation: An economic approach based on selected case studies from Poland

Land consolidation projects (LCP) are the most effective method for quick amendment of poor land fragmentation parameters. At the same time, they are costly due to both a long time horizon and auxiliary projects, in particular, road construction and improvement of field drainage or irrigation systems. The range of changes in parcel arrangement after consolidation varies, as does the economic efficiency of LCPs related to the changes. The paper proposes a approach to the assessment of LCPs that takes into account the production and income effects, which influence the income of farmers participating in consolidation processes, and potential benefits, such as the increased value of farmland and the effect of improved quality of cadastral documentation. Static and dynamic economic feasibility indices were calculated. In the latter case, a thirty-year life of the project and a 2.5 % discount rate were assumed. The study involved six projects completed in Poland under the European Union Rural Development Programme 2007–2013. The effectiveness of the investments was found to vary significantly. The calculated payback period was most often a few to several dozen years, depending on the project, index, and scope of considered effects. It has been demonstrated that if potential economic rents are included, the estimated payback period for an LCP can be reduced several times. It was further concluded that it is necessary to develop a method for the valuation of non-production effects of LCPs such as social, environmental, and landscape benefits.

Spatial effects and endogeneity in a Ricardian model of climate change: an application to a Mediterranean region

ABSTRACT The relationship between land values, climate and landscape diversity is investigated for a region of the Mediterranean where climate impacts are expected to be particularly severe. The Ricardian approach is applied, and spatial correlation and endogenous selection of farm type are accounted for. The analysis is at the farm level, and it is completely geocoded. It is found that farmland value is affected by both climate and landscape agrobiodiversity, and that their impacts differ across models. However, landscape agrobiodiversity is extremely significant, and it greatly contributes to sustaining the mean level of land value. The results show that spatial correlation and the endogenous nature of adaptation substantially affect impacts assessment and suggest that spatial dependence and adaptation should not be overlooked in Ricardian models.

Following the Market? Hedonic Farmland Valuation Using Sales Prices versus Self-reported Values

Many farmland valuation studies rely on survey estimates to form the dependent variable in a first-stage hedonic model. This study, based in New York State, provides a microscale comparison of transaction prices and producers’ market value estimates from the U.S. Department of Agriculture’s June Area Survey. Although we find similar weighted value distributions, regression results identify differences in marginal effect estimates and illustrate how market thinness plays a role in the comparability of observed transaction prices and self-reported values. The findings have implications for future hedonic studies, including insights into behavioral differences concerning how farmers and market participants perceive the value of farmland.

Revisiting the relationship between land price and parcel size in agriculture

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.

How does the land market capitalize environmental, historical and cultural components in rural areas? Evidences from Italy

Farmland can supply a wide variety of ecosystem services, i.e. provision of food and fibre, as well as regulating, supporting, recreational, aesthetic and cultural services. In addition, farmland can be characterized by the presence of anthropic elements, i.e. archaeological sites and historical rural buildings, from which the community can obtain further non-material benefits, namely cultural heritage values, recreation and tourism, etc. However, all these services and land components can be strongly influenced by different levels of farming intensity, a condition that can damage their capacity to supply the related functions (public goods). Such land-market failures could be adjusted by acquiring information on how the above non-farming characteristics, i.e. environmental, historical and cultural determinants, are capitalized in farmland value when farming intensity varies.To this aim, a real estate survey was carried out in Italy in order to investigate the land market of traded farms cultivated under specific crops and located in two areas with different levels of farming intensity. The analysis considered farming and non-farming determinants of selling price and used a hedonic model method based on the ordinary least squares regression corrected for spatial autocorrelation. The results highlighted that the farming determinants were capitalized in selling price as expected in both areas, while the impacts of the non-farming characteristics were extremely diversified between the areas. In the extensively farmed area, the environmental, historical and cultural determinants tended to be positively capitalized, thus favouring their preservation. However, in the intensively farmed area, these were positively or negatively capitalized according to whether or not their overexploitation could allow increased yields, respectively. In yet other cases, some non-farming determinants were not capitalized at all in either area. These trends provided useful insights for the design of ad hoc market-based schemes able to enhance land market functioning and the maintenance of these components in agricultural areas with different levels of farming intensity.

Use of panel time-series data with cross-section dependence in evaluating farmland valuation: a cautionary note

ABSTRACT The note highlights how misspecification of cross-section dependence structure in panel time-series data can lead to erroneous conclusions on farmland valuation. Combining the sample information from time-series and cross-section dimensions by using panel time-series data can improve inference on the net present value hypothesis for farmland. However, cross-section dependence must be addressed to take advantage of the additional information from this type of data. We consider three classes of panel unit root models that account for cross-section dependence through (1) common factor extraction, (2) block bootstrapping and (3) spatial dependence to explore whether farmland values can be explained by their economic fundamentals, given that the appropriate cross-section specification is implemented in testing. Results show that only spatial dependence approach accurately characterizes cross-section dependence in the Iowa panel time-series data, highlighting the importance of model selection when using data with cross-section dependence. Once the econometric model is specified with the underlying spatial cross-section dependence structure, the market valuation of Iowa farmland is mainly determined by fundamentals as predicted by the net present value model.

Potential impacts of COVID‐19 on Canadian farmland markets

AbstractEvidence from the past 50 years suggests that changes in Canadian farmland values are influenced by farming returns, real interest rates, and exchange rates. Residential and commercial development also affects the value of farmland close to major urban centers. The COVID‐19 economic shutdown is expected to reduce crop and livestock returns, which will put downward pressure on farmland values. The magnitude of this downward pressure will depend on the extent and the length of the recession. The evolution of interest rates over the next months and years could have a significant impact on farmland values. Historically, low real interest rates have coincided with higher farmland values, whereas high real interest rates have caused significant reductions in farmland values. The development value of farmland close to major cities could be negatively impacted by a sharp downturn in residential and commercial property markets.

Insecure Land Tenure, Social Protection, and Resource Misallocation: Evidence from China's Agricultural Sector

Smallholder farmers usually face insecure land rights and limited social protection, so that farmland serves as an important safety net against income shocks. Safety-net value of farmland makes the loss of land rights extra costly and strengthens the well-documented incentive for self-cultivation as an informal way of protecting land rights. This article provides theoretical and empirical evidence of allocative effects of the non-productive value of farmland. Further, employing survey data from China, sector-level simulations show that eliminating the non-productive value would significantly increase the consolidation of land, raise smallholder income, and expand labor supply away from smallholders’ own land.

Examining the Relationships between Land Values and Credit Availability

Given the changes made to the agricultural lending system since the 1980s farm crisis, we investigate the current effects of credit availability on land values. Using data from Federal Reserve Agricultural Credit Surveys, we measure credit availability and perform county-level panel fixed effects estimations controlling for land value determinants, credit availability factors, and county and macroeconomic factors. We build an indicator of increased credit availability and find that estimating farmland values with different factors of credit availability separately could mask combined effects. When conditions for credit availability increase or remain unchanged from the previous year, land values may increase by up to 25%. While higher credit availability may facilitate land acquisition, it can also put upward pressure on land values.

Examining the Relationships between Land Values and Credit Availability

Given the changes made to the agricultural lending system since the 1980s farm crisis, we investigate the current effects of credit availability on land values. Using data from Federal Reserve Agricultural Credit Surveys, we measure credit availability and perform county-level panel fixed effects estimations controlling for land value determinants, credit availability factors, and county and macroeconomic factors. We build an indicator of increased credit availability and find that estimating farmland values with different factors of credit availability separately could mask combined effects. When conditions for credit availability increase or remain unchanged from the previous year, land values may increase by up to 25 percent. While higher credit availability may facilitate land acquisition, it can also put upward pressure on land values.

Roads, Participation in Markets, and Benefits to Agricultural Households: Evidence from the Topography-Based Highway Network in Nepal

This paper identifies the role of roads in improving agricultural livelihoods and examines the key market mechanisms through which improved connectivity translates into economic gains for agricultural households. I use a rigorous identification strategy based on the rugged terrain that significantly influences the design and costs of constructing roads in Nepal, along with new geospatial data to find a positive impact of roads on farmland values. A 1% decrease in distance to a road raises the market price of an agricultural plot from 0.1% to 0.25%. This increase in land value is underpinned by increased participation by households in agricultural markets and improved farm production and incomes. The results also suggest that a decrease in the distance to a road contributes to the commercialization of agriculture and increases the use of fertilizer in agricultural production, thus reducing the unit cost of fertilizers.

Temperature thresholds and the effect of warming on American farmland value

Many studies suggest that warming is harmful to American crop yields because of a temperature threshold near 30 °C whereupon yields abruptly fall. This study uses a flexible daily temperature bin specification in a Ricardian model to measure the response of farmland value to daily temperature. The analysis does not find evidence that high temperatures are particularly harmful to farmland or cropland value in the Eastern United States. Instead, temperature has a smooth hill-shaped effect on farmland value with a peak temperature of about 18 °C. Nonetheless, the Ricardian model predicts that cropland values would fall linearly by 15%/°C with uniform warming, while farmland values of mixed farms would fall far less.

The Opportunity Cost of the Conservation Reserve Program: A Kansas Land Example

AbstractThe effects of the Conservation Reserve Program (CRP) on farmland values is investigated using a set of parcel‐level data for land sales in Kansas over the period 1998 to 2014. The sales data are used to estimate a hedonic model of land values that allows for the opportunity cost of CRP enrollment to vary across space and time. Factors impacting the opportunity costs include the relative productivity of land, returns to farming, and the time remaining under the CRP contracts. We find that the discount associated with having land under CRP contract averages 7%.

Climate change impacts on farmland value in Bangladesh

Many studies have examined the effects of climate change on farmland value in developed countries, but our understanding of the impact of climate change on farmland value is still very limited, especially in developing countries. In this study, we aimed to assess the effects of climate change on farmland value in Bangladesh using the Ricardian model. Household-level data collected from seven selected agroecological zones in Bangladesh were used to estimate the relationships among farmland value and long-term climate, farm household, and policy variables. The results showed that the current land values of farmers are sensitive to climate. A new variable called “flooding” was added to the Ricardian model, and the results indicated that floods are responsible for reductions in farmland value, especially in lowland areas. Among the socio-economic variables, the availability of extension services and access to irrigation facilities were positively correlated with farmland value. The estimated marginal impact results suggested that increases in temperature were associated with losses in small farmland value, whereas the precipitation levels in both seasons positively influenced farmland value. Selected global climate models predicted that climate change would have a negative impact on land value depending on the climate model and source of farm income. The empirical findings obtained from this study are expected to contribute to the formulation of sustainable adaptation strategies to maintain farm productivity and farmland value in Bangladesh in the context of climate change.

Assessing the Performance of Land Consolidation Projects in Different Modes: A Case Study in Jianghan Plain of Hubei Province, China.

Land consolidation is essential in China for improving land use efficiency and supporting rural public space governance. Previously, the implementation of land consolidation projects (LCPs) had been mainly led by governments in China. In recent years, the Chinese government vigorously promoted land consolidation, and land consolidation in the corporation-leading mode (CLM) has emerged. This study focused on investigating the performance of CLM projects and the difference in performance levels between the CLM projects and the government-leading mode (GLM) projects. Based on the improved extensible matter–element model, the performance levels of 14 LCPs in GLM and CLM of Jianghan Plain, Hubei Province and related impact factors were analyzed. A set of evaluation indices was selected based on the “process-based thinking and logic”. Results showed that: (1) performance levels of the 14 LCPs are different, most of the projects in the GLM have ordinary or poor performance, while most of the projects in the CLM have excellent or good performance; (2) factors affecting the performance levels of LCPs are also different in the two modes. The main influencing factors in the CLM were the poor access to field roads, insufficient shelterbelt planting, and low land reclamation efficiency, while the insufficient shelterbelt planting, low annual output value of farmland and grain production capacity, low increase rate of agricultural labor production, and low land reclamation efficiency were the main influencing factors in the GLM; (3) comparative analysis of the two modes revealed that LCPs in the CLM have clear investment directions, high output benefits, and obvious advantages in the development of modern agriculture when compared with the GLM. To achieve improving the performance levels of LCPs, policy makers should actively innovate the implementation mode of LCPs and encourage all kinds of agricultural corporations to participate in land consolidation.

Weather and Crop Management Impact on Crop Yield Variability

This research is primarily designed to examine crop yield variation due to change in weather pattern and crop management activities by exploring a comprehensive list of factors (e.g. environmental, economic etc.). Given that existing literature indicates significant effects when farmland value is regressed on weather variables, a natural question is to ask whether major agricultural crop yields responds to change in historical weather pattern. To answer this question, this study relies on a state level panel dataset including agricultural and high-resolution weather data covering the period 1997-2018. Using a Seemingly Unrelated Regression (SUR) approach, this study estimates how crop spatial distribution patterns have impacted crop yield variation in response to weather in United States Greater Midwest region. Key findings indicate that changes in crop management activities correspond closely to estimate of both crop price and weather effects. Additionally, corn yield response to weather change varies with crop spatial distribution pattern, with distinct impacts on the magnitude and even the direction at the state level. Further, revenue of corn, soybeans, wheat and their respective lagged yields have positive and significant effect to respective crop yields. Finally, a major crop yield does vary across region due to variation of crop prices, precipitation and temperature. These findings have useful implications for agriculture sector on how historical weather trends have affected crop yield and distribution pattern.