AGRICULTURAL PRODUCERS' WILLINGNESS TO PAY FOR REAL-TIME MESOSCALE WEATHER INFORMATION

Journal OfAgricullural and Resource Economics

Table 2. Comparison of Survey Respondent Characteristics to Charac-
teristics of Oklahoma Farms with Annual Sales Exceeding $10,000

U.S. Department ofCommerce

In table 2, characteristics of the survey respondents are compared to characteristics of
Oklahoma producers with agricultural sales exceeding $10,ООО/year. As the table indicates,
the respondents appear to be representative of Oklahoma’s commercial producers. The
sampling technique purposely overrepresented irrigators since they were perceived as
having the highest potential benefit from the Mesonet information. Cotton and peanut
farmers were also disproportionately represented in the returned surveys. Producers with
these higher value crops may have been more likely to have established a relationship with
the university and were therefore more likely to be included in the original mailing list.

The respondents were also asked to estimate their annual loss in crop and livestock sales
due to adverse weather conditions for the past five years. Only 6% indicated no losses due
to adverse weather. Thirty-seven percent indicated annual losses of $10,000 or more. On
average, the farmers and ranchers experienced weather-related losses each year totaling
$11,700. This represented 14.6% of their gross farm income. Data from the 1992 census of
agriculture classified 1.73% of Oklahoma’s planted cropland as “land on which all crops
failed.” Based on census data for average crop revenues from all crops, failed crops represent
an average loss in gross sales per farm of $ 13,473, which is similar to the loss reported by
the survey respondents.

The survey respondents’ choices among the willingness-to-pay categories are shown in
table 3 for the raw weather data and for the raw data plus value-added information.
Completed, useable surveys were received from 146 respondents. However, based on their
decisions not to respond to one of the willingness-to-pay questions, all 146 respondents were
not included for each model. In addition, for each willingness-to-pay question, there were
respondents who indicated that they would use the weather data only if it were provided

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