The market price of land intended for agricultural use is closely and directly related to its long-term productivity which depends, inter alia, upon regional climatology and the individual farm's soil quality. Low-quality soils, consistently low precipitation, and/or high frequency of damaging hail are therefore negatively capitalized into land values. A market-price function for cropland was formulated in terms of indices for hail frequency and severity, precipitation and temperature during the growing season, along with a number of non-weather variables including soil quality, extent of irrigation, degree of urbanization, and effective tax rates. Detailed information for 577 land transactions during the years 1968 through 1973 was obtained from courthouse files and detailed soil surveys covering 12 counties in Colorado and Nebraska. Values of all of the variables in the price function were then calculated for each transaction. Multiple regression techniques were used to estimate the extent to which variations in the deflated value per acre could be attributed to differences in these variables. Although the use of temperature variables did not appear helpful in the estimation equation, their influences will be re-examined when appropriate evapo-transpiration data have been developed for the sample regions. Results indicate that late-season precpitation is a net disbenefit in terms of its effect on the value of cropland, with the turning point occurring near the end of July. The estimated value of early season precipitation is consistent with yield effects previously obtained in field plot experiments. Previous estimates of hail damage, which have relied on the records of crop-hail insurance claims, appear to understate the actual losses. The direct benefits of a hail suppression program could be greatly enhanced (or more than offset) by concomitant effects on total precipitation since the value of a 20% decrease in hail is roughly equivalent to that of an 8% increase in early season rainfall. The positive price effects of the combined weather variables over the range of the sample are estimated to be about three times as large as those associated with observed differences in soil quality.

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