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Rural Land Trends

The recognized source for current Texas land value estimates and projected future trends.

The Texas Chapter of ASFMRA is the recognized source for current Texas land value estimates and projected future trends. Chapter members from all the regions of Texas provide data to develop the annual market study. This annual study was fostered in the late 1990’s in cooperation with Dr. Charles Gilliland, Research Economist at The Real Estate Center at Texas A&M University. The concept grew to include the information currently provided on these pages and the credibility of the data is well recognized by market participants. Individual members are located throughout the State to assist with specific valuation, consultation or management needs.

You can download free copies of the current and previous Texas Rural Land Value Trends books below. To order printed copies of the current book, please use the following order form:

Land Trends Order Form 2023

When quoting this publication — You may, on an occasional basis, disseminate portions of the Texas Rural Land Value Trends for noncommercial purposes to a limited number of individuals, provided you include all copyright and other proprietary rights notices with such portion of the publication in the same form in which the information appears.  The phrase, “Used with permission from the Texas Chapter of the American Society of Farm Managers and Rural Appraisers (ASFMRA)” must be included.  You may not modify any information from this publication and you shall be fully responsible for any consequences resulting in such use of the Texas Rural Land Value Trends data.

Moreover, the data contained herein is intended to be used for informational purposes only. The information contained herein does not constitute valuation analysis, and data regarding changes in land values shall not be used or applied to any specific property without support from subject property specific market data or paired sales analysis. Solely relying on this data for valuation purposes could generate flawed results.