RESEARCH Post-COVID Consumer Spending in New York City

Overall spending growth remained positive throughout the pandemic, excepting the immediate shock in April 2020. Figure 1 shows spending levels from January 2019 through August 2021, indexed to spending levels in 2019. In April 2020, overall spending on general goods was 7 percent below what it was in January 2019. By August 2021 overall spending was 26 percent higher than it was in January 2019—a level of spending growth that was strong even relative to pre-pandemic levels. (Office of the New York State Comptroller 2022)  

Figure 1: Spending growth online on general goods is stronger than offline spending, regardless of retailer type

While aggregate spending growth was generally strong over our observation period, spending varied substantially by product, retailer type, and channel. As our prior research demonstrates (Wheat et al. 2021a, 2021b, 2021c), spending growth on offline and online retail across a variety of products diverged in March 2020 and has settled into a new dynamic where online growth consistently outperforms offline growth. This pattern holds true for New Yorkers’ spending on general goods. Notably, this pattern holds across retailer types as well; online spending growth at other retailers is consistently higher than offline spending growth at top retailers.

An important nuance not presented in Figure 1 is that consumers can make both online and offline purchases from the same individual firm, ^[5] such that a firm could offset declining offline spending with online spending. Indeed, firms may even encourage this shift (the so-called “bricks and clicks” model). (Hortaçsu and Syverson 2015). This is important to remember because larger firms may have more resources to devote to developing and maintaining online services to complement their offline services. (Rodrigue 2020)

In addition to the growth of New Yorkers’ spending varying across our different categories, the relative amounts they spent in each category differed meaningfully throughout our study period. We find that New Yorkers shifted their spending towards online retailers and top retailers—and away from offline spending at other retailers—starting in March 2020. The starkest example of this is the drastic shift towards online spending at top retailers. However, these shifts reversed over the course of 2020 and 2021.

To measure how New Yorkers allocated their spending across our categories, we use a ratio of spending offline at other retailers to spending in each of the other three categories. This allows us to put a dollar value on the relative shares of each of these categories and roughly assess how consumers allocate spending, regardless of overall growth at a given time. For example, in Figure 2 we see that for every $1.00 New Yorkers spent offline at other retailers in January 2020, they spent $3.60 online at the top retailers. This figure rose to $12.76 for every $1.00 in April 2020 and fell to $3.77 for every $1.00 in August 2021. Alternatively, by August 2021 New Yorkers were spending relatively less offline at the top retailers than before the pandemic. New Yorkers spent $2.02 offline at top retailers for every $1.00 offline at other retailers in January 2020. This figure fell to $1.83 for every $1.00 by August 2021. This is interesting but should be interpreted with caution. As mentioned above, a limitation of this analysis is that online and offline spending done at the same retailer is presented in separate categories. Some of the decline in offline spending at the top retailers is being offset by online spending increases at those same retailers.

Figure 2: New Yorkers continue to allocate most of their spending to top retailers online

This may initially seem to contradict a common national narrative that the pandemic would provoke a drastic, durable shift in spending away from smaller, offline retailers. (Boyle 2021, D’Innocenzio 2020, Friedman 2020, Nassauer 2020) We do indeed observe a drastic shift, and only observe our series returning to pre-pandemic levels at the end of our study period. Moreover, a return to pre-pandemic patterns does not diminish the disruptions to revenues and expenses businesses faced during this time. It may also be the case that what may be a valid national narrative may not hold in the same ways in New York City, and what may be a valid narrative for the city is meaningfully different across neighborhoods. Further research at different levels of geographic granularity will help elucidate this.

A striking feature of Figure 2 is that for the entirety of our study period, the amounts New Yorkers spent offline at other retailers is always the lowest of the four categories. This is demonstrated by none of the other categories dipping below $1.00 (i.e. for every $1.00 New Yorkers spent offline at other retailers, they always spent at least $1.00 in each of the other categories). This is an empirical outcome about the structure of the market for this product in New York. As we demonstrate in Finding 3, offline spending at other retailers need not have the lowest share of spending. Finally, the drastic changes in spending patterns that occurred in the spring and early summer of 2020 may give the impression that smaller changes are not meaningful. However, small but durable changes in market share on the order of cents on the dollar, rather than multiples of dollars, may still be important in the long term for retailers with low margins.

The patterns we observe in New Yorkers’ spending on general goods do not generalize to all product types. We find that New Yorkers’ spending on groceries across our categories is notably different during the study period. In contrast to general goods spending, both online and offline spending at grocery stores increased in March 2020, with offline spending remaining notably positive. Like general goods spending however, online spending grew slower than offline spending regardless of retailer type before the pandemic and this switched after the pandemic.

Figure 3: Online grocery spending grew faster than offline spending after the pandemic, regardless of retailer type

We observed noticeable differences in spending by New Yorkers on general goods and groceries by channel and retailer type. As Figure 4 demonstrates, for every $1.00 New Yorkers spent offline at other retailers, they spent less than $1.00 in each of the other categories. For example, the spending ratio for top retailers was $0.80 in January 2020, and steadily declined to $0.67 by August 2021. It is relevant to note again that New York City may prove different than the rest of the country in this regard. The way people spend on food to consume at home in New York City may be different to other cities in the country, let alone suburban and rural areas.^[6]

Figure 4: New Yorkers continue to spend most of the grocery dollars offline at other retailers

The relatively low spending ratios of online grocery spending at top and other retailers illustrates that they remain a small part of the overall market, despite their high growth rates shown in Figure 3. It is also notable that New Yorkers spent more online at other retailers than they did online at the top retailers. The spending ratio for other retailers online was on average $0.04 higher than top retailers online for the length of the study period. As different types of retailers seek to navigate the changes and challenges of the post-COVID economy, the example of New York City grocers may be an interesting case study.

There was understandable concern that the pandemic may have greatly increased the success of the top retailers at the expense of others. The variation we observe in spending growth across types of retailers and channel does illustrate that there are meaningful differences in how the top retailers are growing relative to others online and offline. We also observe that for general goods spending, there was a drastic shift towards the top retailers online in the first months of the pandemic. However, this changed over the course of the rest of the pandemic, and the allocation of New Yorkers’ spending on general goods returned close to pre-pandemic levels. Other sectors of retail may be experiencing the post-COVID economy differently, and a reversion to pre-pandemic trends does not diminish the real challenges smaller retailers have faced over the past two years.

Longer-term trends toward online spending at top retailers may challenge inclusive growth more than the short-term COVID spike. In more recent months, the top general goods retailers received a smaller share of spending than they did during the height of the pandemic. This said, spending online at the top retailers is growing faster than all other spending categories and had the highest share of spending throughout the entire study period by far. While consumers’ move toward top retailers online may be small relative to the shifts we observe at the height of the pandemic, such changes can be impactful if they continue over the medium- to long-terms, especially for retailers whose margins are tight. Policymakers might usefully attend to these longer-term structural changes when considering programs to support all businesses.

Policymakers can tailor post-COVID economy business support programs to industry-specific needs. Our results show substantial differences in how consumers spend on groceries and general goods. Top online retailers of general goods continue to capture the largest share of consumer spend in the post-COVID economy. In contrast, smaller grocers still capture materially larger shares of consumer spend than top retailers in New York City, though both offline and online spending shares at top grocers are increasing. These differences suggest that decision makers could benefit from making distinctions based on sector and retailer type when assessing business support programs in general, and specifically for programs intended to facilitate the adoption of online sales. For example, a goods retailer may need technical assistance to understand the costs and benefits associated with offering delivery or pickup, how to leverage payment or online customer service platforms, or how to manage shipping logistics. In contrast, a professional services firm may benefit from innovative financing for new audiovisual equipment or infrastructure investments in higher speed broadband to improve the quality of their online services.

Further research can help local policymakers better support businesses and communities in the post-COVID economy. Studying consumer spending at different levels of geographic granularity is beyond the scope of this report but is critical to better understanding the post-COVID economy. In this case, analyses of post-COVID spending behavior in other cities or regions could provide context that would aid the interpretation of our results for New York City. Likewise, more geographically granular analyses of these patterns at the sub-city level can inform more targeted conversations about the experiences of New Yorkers in each of its local communities. More local analysis is critical to informing public policy, as the effects of neighborhood-level differences can be more important than cross-city differences. (Farrell et al. 2019)