selected as the major markets in the United States. Weekly'wholesale price and monthly unloads

data collected by the Market News Branch of the Fruit and Vegetable Division, Agricultural

Marketing Service of the USDA were utilized. The demand system was cast as an inverse

Rotterdam model and estimated in TSP. For more details on the model and estimation

procedures see Scott (pp 52-5).


Table E.1. Estimated monthly demand flexibilities by market and crop.
 Tomatoes Peppers Cukes Squash Eggplant Melon Strawberries
New York -0.2104 -0.4411 -0.2903 -0.2523 -0.1600 -.250 -.250
Chicago -0.2798 -0.2596 -0.3817 -0.2589 -0.1700 -.250 -.265
Atlanta -0.2766 -0.3347 -0.2519 -0.2954 -0.1601 -.250 -.255
Los Angeles -0.3384 -1.0124 -0.2533 -0.2543 -0.1500 -.250 -.250
 The demand system estimated by Scott was extended to include squash, eggplant,

watermelon, and strawberries. The estimated demand flexibilities are presented in Table E.1.

The relatively small estimated flexibilities suggests that the demand for winter fresh vegetables

is highly elastic.3

 As the inverse demand equations in the mathematical programming model reflect

aggregate demand, it was necessary to adjust the intercepts of the demand equations. This

adjustment was accomplished by first dividing the U.S. and Canada into four demand regions

as shown in Figure E.1. Using the 1990 census figures, the population in each region was

computed. There is no information to suggest that fresh winter vegetable demand is highly

differential across the four demand regions, so it was assumed that aggregate consumption is




 3In some cases, the estimated flexibility was so small that an adjustment was made so that
the mathematical programming model could be solved.

 162