much higher percentage of produce consumption for higher-income shoppers (4.99% versus
3.83%). This disparity results from the fact that produce consumption is fairly evenly distributed
between fruit and vegetables for higher-income consumers (50.7% vs 49.3%), but highly skewed
toward vegetables for lower-income consumers (58.8% vs 41.2%). Since fruit is generally more
expensive than vegetables, this disparity for the two groups support the premise that income
serves to limit produce consumption bundles for lower-income consumers.
The final sub-category of fruit, fresh-cut fruit, provides empirical results that are
inconsistent with consumption theory. The own-price elasticity is positive, but not statistically
significant. Of course, fresh-cut fruit is less than 1% of total fruit consumption for both income
groups and this small percentage is the likely explanation for the insignificance of the estimated
parameters. Another factor surrounding fresh-cut fruit is that much of it is pre-ordered through
deli departments and therefore does not scan as produce sales. But despite the insignificance of
the own-price elasticity for fresh-cut fruit, prices paid by higher- and lower-income consumers
show greater price sensitivity for lower-income consumers ($3.36 vs $2.61).
Empirical Results for Vegetables
As shown in Table 3, store differences exist for all sub-categories of vegetables, but the
least difference is shown for major vegetables (corn, potatoes and tomatoes). This result is quite
plausible, given that major vegetables represent the largest share of produce consumption for
both higher- and lower-income consumers. With store 1 serving as the reference store, the
results for greens show upward shifts in the intercepts for stores 3 through 6. Sales of greens in
store 2 are shown to be statistically insignificant from those of store 1. Produce sales, the
variable used as a proxy for income, are shown to have positive and statistically significant