Agricultural Economics Department


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The authors would like to express their sincere appreciation to the Federal Land Bank of Omaha for their cooperation in providing the necessary data and initial funding for this project.

The authors wish to acknowledge the helpful comments on previous drafts by James B. Hassler, Maurice P. Baker, George H. Pfeiffer and Michael Lundeen.

Gradate Research Assistance, Instructor, and Associate Professor, respectively, Dept. of Agricultural Economics, University of Nebraska-Lincoln. Names appear in alphabetical order; no assignment of senior authorship is made.


Land Value expectations are important to land owners, agricultural producers, lenders, governmental agencies, and other parties. Greater understanding of land values and the factors involved in their determination is therefore beneficial to the decision-making process.

The analysis of farmland values has been a major focus on the agricultural economics profession for several decades. Early research focused primarily on the measurement of the relationship of income levels to land values. In more recent years, econometric models have attempted to uncover additional economic factors which influence the value of farmland.

Econometric models have used many quantification techniques ranging from single-equation ordinary least squares regression to systems-of-equations simulation. Data bases utilized in these studies have also been diverse, ranging from private survey information to Census of Agriculture data, the latter being the most common.

Many of the models have received criticism for being too broad geographically or insensitive to value changes over time. In particular, models of the U.S. farmland market have needed to assume homogeneity of land its use throughout the nation. also, the utilization of nationally-aggregated time-series data perceivably smooths-out any short-term fluctuations in farmland values caused by varying expectations on the part of the market participants.

The very nature of the farmland market necessitates a more regionalized time-specific study. the analysis should allow for spacially-sensitive factors to merge into the value estimation process which are otherwise forgone when more general, aggregated data are used.

The primary focus of this study is to gain a clearer understanding of the Nebraska farmland market and the components which influence land values. While identification of the relevant factors that influence agricultural land values has been the focus of several recent studies, the specific nature of this study's data source provides a unique opportunity to analyze the agricultural real estate market by sub-state regions.