Welfare Costs of Shopping Trips
One sentence summary: Welfare gains from removing traditional shopping-trip costs is about 4% for the average census block.
The corresponding academic paper by Hakan Yilmazkuday is available as a working paper here.
Abstract
Using data on the number of visitors at the store level, this paper investigates the welfare costs of traditional shopping-trips for the U.S. census blocks. The investigation is based on an economic model, where individuals living in census blocks decide on which store to shop from based on the corresponding shopping-trip costs and idiosyncratic benefits. The implications of the model suggest that the welfare gains from removing shopping-trip costs in percentage terms can be measured for each census block as the weighted average of log distance measures between shopping stores and census blocks. The corresponding results show that the welfare gains from removing shopping-trip costs is about 4% for the average census block, with a range between 0.021% and 18% across census blocks that is further connected to their demographic or socioeconomic characteristics. Certain practical policy implications follow regarding how shopping-trip costs can be reduced to achieve higher welfare gains.
Non-technical Summary
Despite the increasing trend in online shopping, 88.5% of sales in the U.S. is still through traditional shopping, which may be due several reasons including its convenience or urgency of shopping. Since traditional shopping requires leaving home and walking/riding to a shopping store, it results in not only travel costs but also time and opportunity costs. Nevertheless, the literature lacks a quantitative investigation regarding the corresponding welfare costs of traditional shopping.
This paper attempts to measure the welfare costs of traditional shopping trips at the U.S. census block group level. The empirical investigation is based on an economic model, where individuals living in census blocks decide on which store to shop from based on the corresponding shopping costs (increasing with distance to the store) and idiosyncratic benefits. The implications of the model suggest that the welfare gains from removing bilateral shopping costs (that we consider as the welfare costs of traditional shopping in this paper) in percentage terms can be measured for each census block as the weighted average of log current bilateral distance measures between shopping stores and census blocks, where weights are the bilateral probabilities of individuals (living in certain census blocks) shopping at certain stores.
The model is empirically tested by using SafeGraph cellphone location data that provide information on the total number of visitors at the store level, where the census block group of visitors regarding their residence (home) is also given. The estimation results based on about 75 million observations show that the bilateral probabilities of individuals (living in certain census blocks) shopping at certain stores decrease with the corresponding distance measures. Quantitatively, the elasticity of shopping probability from a store with respect to distance is estimated around 0.0767.
The estimated distance effects on the bilateral probabilities of individuals (living in certain census blocks) shopping at certain stores are removed in a counterfactual investigation to measure the welfare costs of traditional shopping. This is achieved for each census block in the data set. The corresponding results show that the welfare gains from removing bilateral shopping costs is about 4% for the average (or median) census block, with a range between 0.021% and 18% across census blocks. The heterogeneity of welfare gains across census blocks is further investigated in a secondary analysis, where it is shown that the welfare costs of traditional shopping increase with cars per capita as census blocks with higher per capita number of cars currently make shopping trips to more distant stores.
Regarding heterogeneity of welfare gains across demographic or socioeconomic groups, it is depicted that census block groups with a higher share of Asian people would benefit the least from removing shopping costs, whereas those with a higher share of American Indian and Alaska Native people would benefit the most from it. When the relationship between welfare costs of traditional shopping and family income is investigated, it is shown that there is evidence for a hump-shaped relationship between family income and welfare costs. Finally, it is depicted that census block groups with a higher share of an educational attainment of an elementary school diploma would benefit the least from removing shopping costs, and those with a higher share of an educational attainment of a high school diploma would benefit the most from it. Based on the implications of the model used, these results suggesting that certain demographic or socioeconomic groups would benefit less from removing costs of traditional shopping can be explained by such groups currently making shopping trips to relatively close-by stores so that they gain relatively less when shopping costs are removed.
This paper contributes to the literature by measuring bilateral shopping costs between individuals (residing in census blocks) and stores by using the corresponding distance between them, where price faced at the store is also considered; the remaining factors such as quality of service or convenience are captured by idiosyncratic benefits at the store level for each individual. Measuring the corresponding welfare gains from removing shopping costs at the census block level is the key innovation in this paper, where connecting the heterogeneity of welfare gains across census blocks to certain demographic and socioeconomic characteristics is a further contribution.
The corresponding academic paper by Hakan Yilmazkuday is available as a working paper here.