Measuring the Impacts of Generic Fluid Milk and Dairy Marketing

NICPRE 00-01; R.B. 2010-01While per capita fluid milk consumption has been declining for decades in the United States at about 1% per year, generic fluid milk marketing activities sponsored by fluid milk processors and dairy farmers have helped mitigate at least some of this decline. We estimate that these marketing efforts have had a positive and statistically significant impact on per capita fluid milk consumption. Specifically, over the period 1995 through 2009, we estimate that a 1% increase in generic fluid milk advertising expenditures resulted in a 0.037% increase in per capita fluid milk consumption when holding all other demand factors constant. Over the same period, we estimate that a 1% increase in generic fluid milk non-advertising marketing expenditures resulted in a 0.028% increase in per capita fluid milk consumption when holding all other demand factors constant. In terms of total consumption of fluid milk, generic fluid milk marketing activities increased fluid milk consumption by an average of 6.23 billion pounds per year on average. Stated differently, had there not been generic fluid milk marketing conducted by the two national programs, fluid milk consumption would have been 11.3% less than it actually was over this time period. Hence, the bottom line is that the fluid milk marketing efforts by fluid milk processors and dairy farmers combined have had a positive and statistically significant impact that is partially mitigating declines in fluid milk consumption. An average benefit-cost ratio was computed for the fluid milk processor program based on the period, 1999-2009. The benefit-cost ratio was 8.88, implying that, on average over the period 1999-2009, the benefits of MilkPEP marketing programs have been 8.88 times greater than the costs, i.e., every dollar invested in MilkPEP marketing yielded an additional $8.88 in industry net revenue. To make allowance for the error inherent in any statistical estimation, a 90% confidence interval was calculated for the average BCR. The estimated lower bound for the average BCR was 1.79. Hence, it is reasonable to conclude that this confidence interval gives credence to the finding that the benefits of the Fluid Program’s marketing activities have been considerably greater than the cost of the programs. In terms of the all-dairy product demand analysis, the average advertising elasticity for this period in terms of milk equivalents on a non-fat and fat basis was 0.036 and 0.056, respectively; a 1% increase in media advertising expenditures would increase per capita all-dairy product demand by 0.036% (non-fat basis) and 0.056% (fat basis). The average non-advertising marketing elasticity for this period was 0.016 (non-fat) and 0.017 (fat); a 1% increase in media advertising expenditures would increase per capita all-dairy product demand by 0.016% (non-fat) and 0.017% (fat). Thus, the total marketing (advertising and non-advertising) effort by dairy farmers and fluid milk processors has had a positive and statistically significant impact on dairy consumption. We calculated a benefit-cost ratio (BCR) for the Dairy Program for the period 1999 through 2009. The benefits of the Dairy Program were calculated as the change in dairy farmers’ net revenue (producer surplus) due to demand enhancement from all marketing activities under the Dairy Program by way of increased sales and higher prices. The costs of the Dairy Program were calculated as the differences in total assessment revenues before and after the national program was enacted. The results show that the average BCR for the Dairy Program was 6.20 (non-fat solids basis) and 9.85 (milk-fat basis) from 1999 through 2009. This means that each dollar invested in generic dairy marketing by dairy farmers during the period would return between $6.20 and $9.85, on average, in net revenue to farmers. These BCRs apply to all of the QP’s marketing programs, but exclude the longer-term (programs that have no impact within a year) demand expansion programs operated by DMI. The level of the marketing BCR suggests that the combined marketing programs supported by dairy farmers have been a successful investment. The estimated lower bounds for a 90% confidence interval for the average BCR in the non-fat and fat models were 3.84 and 1.18, respectively. Hence, it is reasonable to conclude that these confidence intervals give credence to the finding that the benefits of the Dairy Program’s marketing activities have been considerably greater than the cost of the programs. In addition to computing a BCR for the overall marketing efforts of dairy farmers, an average BCR was also calculated for generic advertising and non-advertising activities by dairy farmers. The average BCR for generic advertising in the non-fat model was 8.56 compared with 6.60 for non-advertising marketing activities, and this difference was statistically significant at the 1% level. The average BCR for generic advertising in the fat model was 15.06 compared with 8.41 for non-advertising marketing activities, and this difference was statistically significant at the 1% level. Hence, dairy farmers are receiving a higher return from their generic advertising activities than the non-advertising marketing activities