Store Trading Area Data (Competitive/Demographic Characteristics): Market Metrics, a leading firm in the use of demographic data, used block level data from the U.S. Census to compute a store's trading area. A store's trading area refers to a geographical area around the store. It is calculated by finding the number of people needed to sustain a given level of sales for this area. Geographical boundaries (such as roads, railroad tracks, rivers, etc.) are considered when this trading area is formed. The demographic composition of the store's trading area is computed by summing up the assigned proportion of each of the U.S. Census blocks within the prescribed trading area.

The selection of variables is guided by a household production framework. For a further discussion of variable selection issues refer to Hoch et al. (1995). A total of eleven demographic and competitive variables are used to characterize a store's trading area. These variables summarize all the major categories of information that are available. Table 2 lists each variable along with their descriptive statistics. The statistics in the table are generated for the 83 stores in our sample. Four of the demographic variables measure general consumer characteristics: the percentage of the population over age 60 (Elderly), percentage of the population that has a college degree (Educ), the percentage of black and Hispanic persons (Ethnic), and the percentage of households with five or more members (Fam-size). The other demographic variables are: log of median income (Income), the percentage of homes with a value greater than $150,000 (House-val), and the percentage of women who work (Work-wom).

  
Table 2: Descriptive Statistics for Demographic/Competitive Variables Across Stores

The other four variables measure the competitive environment of the store's trading area. There are two broad types of stores for which we have information: warehouse and supermarkets. The warehouse stores are larger and use an everyday low pricing strategy (EDLP). Other supermarket stores use a high-low pricing strategy (Hi-Lo) similar to Dominick's. We have broken out competitive effects between these two groups since we expect that these two pricing strategies will have different effects. For each group we use two measures of competition: distance (in miles) and relative volume. Distance is doubled in urban areas to reflect poorer driving conditions, which approximates Market Metrics measure of driving times. Relative volume is the ratio of sales in the competitor to that of the Dominick's store. The warehouse competitor variables are computed with respect to the nearest warehouse store, and the supermarket competitor variables use an average of the nearest five competitors.

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