Combining hedonic and negative exponential techniques to estimate the market value of land

Abstract

Given the importance of land valuation to various stakeholders, the objective of this research is to estimate a theoretically sound model to model the market value of land in Kansas, accounting for urban influence and site specific characteristics. The model is estimated using data on all sales of agricultural land in Kansas between 1996 and 2004. Results indicate that the upward, urban pressure on price is greater for Kansas City relative to Wichita. Kansas City had a much slower rate of decay than either Wichita or cities with a population of more than 10,000.

The effects of use values, amenities and payments for public goods on farmland prices: Evidence from Poland

“…The results imply that location, distance from the city and infrastructure are key factors for agricultural land prices and exert a much stronger marginal effect than the hedonic features contained in the shape coefficient. It is in the line with other researches which have identified land value as a negative exponential function of the distances to large cities and the nearest city with at least 10,000 residents (Tsoodle et al 2007). Similar conclusions have been formulated based on gravity models which measure urban influence by dividing county population by the squared distance of a county from business districts, as well as including both population and real income in urban areas (Guiling et al 2009).…”

Comparison of alternative sources of farmland values

“…Land value estimation is sensitive to variation in the number of sold tracts that possess features that generate premiums or discounts (Goodwin et al, 2003). Past research has shown that other common factors including recreational uses, urban influences, soil productivity, interest rates, government payments, cash rents, income, and population density affect the value of farmland (Plantinga and Miller, 2001;Burt, 1986;Guiling et al, 2009a, b;Henderson and Moore, 2006;Falk and Lee, 1998;Flanders et al, 2004;Tsoodle et al, 2007). While these are important determinants of farmland values, their effects are not estimated.…”

“…where the dependent variable y it is the transaction price (less improvements) per acre for the ith transaction in time period t. Previous research has shown that land value per acre decreases with increasing tract size (Guiling et al, 2009a, b;Tsoodle et al, 2006Tsoodle et al, , 2007, which prompts the inclusion of explanatory variables that represent the total acreage sold (Acres) and the acreage squared (Acres 2 ). Other explanatory variables include the percent of land assigned to each land use (Pcrop, Pirrig, Ppast, Ptimber) that is assigned based on assessors' judgments.…”

Farming and the Internet: Reasons for Non-Use

“…However, this classification does not clearly identify those farm households that are in more remote areas. Therefore, we use miles from a town with a population of at least 10,000 as our rurality proxy (similar to Beasley et al 2007, Tsoodle, Featherstone, and Golden 2007, Hartley 2004).…”