Land development in the United States is following two routes: expansion of urban areas and large-lot development (greater than 1 acre per house) in rural areas. Urban

There are a multitude of interdisciplinary values that people derive from rural land. Productivism focuses on the commodity values of rural land, such as the use of land as a commercial input into agricultural production, timber harvesting and mineral extraction. Productivistic uses and values of rural land have been the traditional focus of rural land policy and management in the United States. Many rural areas in the United States are moving into a postproductivism era. Postproductivism focuses on both commodity and amenity values of rural land.

Numerous theoretical approaches to farmland leasing contract choice have been developed with little consistent empirical support, particularly for the Corn Belt. A unique theoretical approach to explaining farmers' lease preferences is presented, using a combination of transaction cost economics and property rights theory. Results demonstrate that both transactional and certain producer characteristics are important motivators of contract choice.

Most land management policies, such as land retirement, have multiple objectives. This study uses a cellular automata simulation model to explore how various spatial characteristics of land parcels on a hypothetical landscape contribute to the efficacy of land retirement in the presence of multiple retirement objectives-– hydrological improvement, habitat improvement, and cost. Statistical analysis of the simulation results is used to tie particular spatial characteristics back to achievement of the three distinct objectives.

This study examines the role that attachment value plays in the formation of a willingness to accept price (WTA) for farmland. Attachment value is defined as the estimated or assigned worth of a socio-emotional good that binds one person or group to a physical object. The objective of this study is to determine if a differential exists between the market or assessed farmland price and the price a farmland owner would accept from a strange. Further this study aims to determine if attachment value has an affect on this differential.

Nature reserve planning models to maximize species protection are typically formulated for a single period using certain data. In practice, however, parcels must be acquired over time. The status of a parcel may change due to conversion to alternate land use. Populations of species to be protected may change, as well. A two-stage stochastic program that maximizes expected species protection with annual budget constraints is proposed where parcels available for set aside have associated probabilities of being available for acquisition and species coverage.

This study explores how property taxes affect the timing of development. The theoretical literature suggests that higher taxes increase the time to development, although there is some disagreement in the literature. We present a simple theoretical model to motivate an empirical model that explores how land use change decisions are made over time. A hazard model is used to predict factors that influence the time to development over an 11-year period in an urbanizing county in the Midwestern corn belt. The results suggest that higher taxes slow development, as expected.

This paper uses an analytical and econometric approach to analyze the farmland conversion process, including the effects of population growth, real estate markets, the agricultural-urban edge, and farm returns. We use a unique county-level dataset on farmland conversion for California that tracks conversions between agricultural, urban and other land uses.

This report summarizes the results of the North Dakota Land Valuation Model. This model is used annually to estimate average land values by county, based on the value of production produced on that land. The county land values developed from this procedure form the basis for the 2001 valuation of agricultural land for assessment of real estate taxes. The average all land value from this analysis is multiplied by the total acres of agricultural land on the county abstract to determine each county's total agricultural land value.