Post-COVID consumer spending in New York

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Consumer retail activity changed dramatically after the onset of the COVID-19 pandemic, in terms of amounts of money spent, types of goods and services purchased (Wheat et al. 2021b), distances traveled (Farrell et al. 2020), online retail use (Wheat et al. 2021a), or combinations of health risks and government restrictions encountered (Wheat et al. 2021c). Less measured but no less concerning are the potential shifts of consumers from small retailers to large retailers. This can be important as a cause or consequence of how different types of retailers have behaved since March 2020. Additionally, insights into consumer spending behavior can help inform how policy makers and business leaders consider the challenges faced by different types of retailers in the short term. future.

We use the credit and debit card transactions of approximately 1.5 million people to describe consumer consumption behavior across retailer types (corresponding roughly to size) and shopping channels (online and offline). We focus on general merchandise and grocery purchases. While the overall spending growth for these products is strong, we find that the growth is not necessarily shared equally across different types of retailers. While the pandemic has caused a precipitous divergence in the share of spend captured by different retailer types, spend shares by retailer type are returning to their pre-pandemic state. Importantly, we see very different results across product types, suggesting that businesses, consumers or neighborhoods may need supports tailored to specific sectors of the retail economy.

Sample

Our sample for this study is composed of debit and credit card transactions from a sample of approximately 1.5 million Chase customers who lived in the Central Statistical Area of ​​New York-Newark, NY-NJ-CT- PA between January 2019 and August 2021. For a person’s transactions to be included in our sample, the person must have:

  1. made ten or more transactions across all Chase credit and checking accounts they hold, and;
  2. lived in a ZIP Code Tabulation Area (ZCTA) that is part of New York City for the month in question.

Restricting our analysis to people who are regularly active in each month of our study period avoids presenting Chase’s customer growth as representative of the spending growth of New Yorkers in general. Although Chase customers cannot enter and exit the sample based on their activity, we allow entry and exit based on location. Take, for example, someone who lived in Manhattan ZIP Code 10027 from January 2019 to February 2021, then moved out of town in March 2021 and did not return. From January 2019 to February 2021, their transactions would be included in the expenditures we measure. However, from March 2021 to August 2021, their transactions would not be included in our measurements.

We focus on retailers selling two types of products for this analysis: general merchandise and groceries. General merchandise retailers include department stores, discount stores, large online retailers selling a variety of products, and other retailers like florists and bookstores that sell everyday products. Grocery retailers include merchants who sell food for consumption at home. This includes traditional grocery stores, bakeries, specialty food stores, and some online grocery delivery services.

Methodology

The main distinction between retailers in this report is whether a retailer is ranked among the top retailers or not. Throughout this report, these two groups will be referred to as “large retailers” and “other retailers”. While there are many ways to measure the size and market power of companies, for the purposes of this report, we have ranked companies based on rough measures of market share, number of establishments, and size. geographic footprint.

We first identified the top 100 properties based on their New York-Newark, NY-NJ-CT-PA Central Statistical Area market share for spend in a given year (2019, 2020 and 2021), through a given channel (online and offline), and for a given product (general merchandise and groceries). For example, in one iteration of this process, we identified the 100 establishments with the largest market share for offline grocery stores in 2019. For each business represented in this list, we then counted the number of establishments that they list on their website and identified where these establishments are located. Finally, we categorized the companies as top retailers or other retailers using the scheme in Table 1. If a company is not represented in the list of establishments with the highest market share, it is automatically categorized as other retailers .

Combining our view of shopping channel with our view of retailer types allowed us to create four categories for New Yorkers’ spending: offline transactions made at top retailers (labeled Offline, Top Retailer in figures below), offline transactions made at other retailers (Offline, Other Retailer), online transactions made at top retailers (Online, Top Retailer) and online transactions made at other retailers (Online, Other Retailer). These categories are the basis of this analysis.

Table 1: How we assign retailer type after identifying top companies

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