Local Consumer Commerce: Frequently Asked Questions


The goal of the JPMorgan Chase Institute is to help decision makers appreciate the scale, granularity, diversity, and interconnectedness of the global economic system by using our unique lens to fill in the blind spots left by other data sources. We do this primarily with long form reports, but we also use our Local Consumer Commerce lens to provide an ongoing monitoring of economic conditions in 15 US cities. The LCC lens, comprised of over 20 billion credit and debit card transactions, is new and unique because it tracks actual consumer purchases across a variety of consumer and merchant groups. To help users acquaint themselves with this freely available resource, we have compiled a list of questions that we commonly hear when discussing our data resource.


Local Consumer Commerce is comprised of local, or “place-based”, expenditures on everyday goods and services by end users. It is local because for a transaction to be included, it must be made at a merchant that is physically located inside one of our 15 US cities. Everyday goods and services are those that are most frequently purchased from local retailers (e.g. groceries, restaurants, or clothing), and are often made with credit or debit cards. They would not include purchases of goods likely to be financed (e.g. cars). Table 1 identifies the inclusion criteria based upon whether the consumer and merchant live inside or outside of an LCC city.

Table 1 – Inclusion criteria for transactions based upon the location of the consumer and the merchant

Source: JPMorgan Chase Institute

View Text Version of table 1

By focusing on only the transactions at merchants located in the city, the LCC lens can speak to commercial activity that directly feeds into and supports local markets, jobs, and tax bases. Said differently, it separates out commercial activity that “leaks” out to other jurisdictions, and provides a more direct measure of the vibrancy of local markets.

The LCC lens is a powerful complement to public data sources because its advantages can help offset the disadvantages of public data sets. Three advantages, in particular, are administrative collection, a large sample size, and the ability to avoid a tradeoff between geographic granularity and reporting frequency:

  • Most public data sources, like the Survey of Consumer Finances (SCF), rely on respondents to provide historical information from personal recollection. The LCC lens is constructed on credit and debit card transactions that are administratively collected in the normal course of operations for JPMC.
  • Surveys tend to capture relatively small samples of the broader population. The Current Population Survey (CPS), for example, relies on a sample of about 60,000 households. By contrast, the administratively collected data JPMCI uses to build the LCCI relies on over 59 million consumers.
  • Local decision makers need information about local activity to better understand the local economy and the impact of policy interventions. The American Community Survey (ACS) 1-year estimate will report locally-relevant estimates (e.g. county or metropolitan area), but the reporting frequency is annual. On the other end of the spectrum, the Monthly Retail Trade Survey (MRTS) reports on retail activity each month, but at the national level. The LCC lens has both geographic granularity and high reporting frequency, insofar as it provides a city-level view of consumer behavior in every month.

To better understand the contributions of the LCC lens, it is useful to place it within context of existing data sources. The most commonly used indicator of US economic health is gross domestic product (GDP), which is the total value of goods produced and services provided by firm assets located in the country (see Figure 1). Broadly speaking, GDP is comprised of consumer spending, gross investment, government spending, and the net value of exports.

Figure 1 – Components of GDP

Figure 1 - Components of GDP (See Text Version) Figure 1 - Components of GDP (See Text Version)
Source: JPMorgan Chase Institute

View Text Version of figure 1

The first category—consumer spending—makes up more than two-thirds of GDP. A better understanding of this key source of economic activity can improve our understanding of the drivers behind economic growth. The consumer portion of GDP is defined as personal consumption expenditures (PCE), which is the amount of goods and services purchased by households and nonprofit institutions serving households who are resident in the United States. In other words, these are purchases by end users.

The LCC and PCE lenses contain data that can be used to better understand final consumption in the US, but there are some differences. First, while there is considerable overlap, there are some kinds of purchases that are included in LCC but not PCE, and vice versa (see Figure 2).

Figure 2 – Differences between LCC and PCE

Figure 2 - Differences between LCC and PCE (See Text Version) Figure 2 - Differences between LCC and PCE (See Text Version)
Source: JPMorgan Chase Institute

View Text Version of figure 2

Second, PCE is an aggregate measure of consumption for the entire US economy, and which is simultaneously its greatest strength and weakness. As a guide for how consumers are doing across the country, PCE is invaluable, but it offers limited insight into how consumers are doing in different places across the country. A better view of variation within the country enhances our collective understanding of economic drivers, which is where the LCCI offers an advantage. Since it is built on such a large set of geographically informed data, it can speak to economic activity in specific cities. This fine-grained view offers a more solid basis for tactical investment decisions by households and firms in their local markets.

About two-thirds of Gross Domestic Product (GDP) is comprised of the purchase of goods and services by individuals and non-profits. Any analysis of the economy and where it is heading must have good measures of this activity. However, new purchasing channels are reshaping consumers’ shopping behavior. For example, as the availability of online commerce expands, many merchants have less of a need to be physically close to consumers while other merchants are recognizing the need to be even closer just to compete. Alternatively, the proliferation of card and mobile payments creates new infrastructure needs for merchants and lessens the extent to which they must handle cash.

Older merchants, large and small, are finding their operating strategies tested by these changes. In addition to shifting patterns in consumer spending, we are also seeing increases in expenditure on services relative to expenditure on goods. This evolving dynamic tests our ability to understand how the economy works with conventional statistical measures. Commonly relied upon data sources were developed based upon an older, different looking market.

To understand market behavior, we must understand the strategies employed and decisions made by consumers and merchants. Market demand is driven by consumer preferences, and it is the role of firms to satisfy said demand. The way in which firms satisfy consumer demand (e.g. their chosen mix of labor and capital) determines how many people can be employed and what they get paid. The choices a firm makes, however, depend on which options bring the highest return on investment. If firms, as alluded to above, are making different choices about where they should be located, what implications does this have for who gets hired and where they live? To better understand questions like these, we need a better method of distinguishing which purchases are made from local merchants versus purchases from merchants that are located far from where consumers live.

As of June 2017, the LCC data asset is comprised of over 19 billion credit and debit transactions from over 59 million consumers in 15 US cities. (Since we are cumulatively building the data series, the number of transactions and consumers grows each month.) Credit and debit card transactions are particularly useful for this work because each transaction contains attributes of both the consumer and the merchant (see Figure 3). The base unit of analysis is the transaction; each contains the age and income of the consumer, the size and product type of the merchant, and the zip code of both the consumer and the merchant.

Figure 3 - The high volume of transactions provides a more granular view than other data sources

Figure 3 - The high volume of transactions provides a more granular view than other data sources (See Text Version) Figure 3 - The high volume of transactions provides a more granular view than other data sources (See Text Version)
Source: JPMorgan Chase Institute

View Text Version of figure 3

Our approach to business size involves identifying large and small merchants first, and then labeling all other merchants as medium-sized. Large businesses are those merchants that see over 8% market share, which we estimate as the merchant’s proportion of total spending for a given month, industry, and city. Note that because the market share concept relies on the intersection of month, industry, and city, a single merchant may be simultaneously designated as large in one city and medium or small in another. Alternatively, a merchant in a single city that is designated as large in one month may be medium the next if they cross below the 8% threshold in that city.

The identification of small businesses, by contrast, leverages industry specific definitions of small businesses from the Small Business Administration (SBA). Specifically, we use SBA’s industry-specific thresholds for employee count and revenue. Since a merchant may be comprised of multiple establishments in different cities, these thresholds apply to the national employment and revenue activity across the entire firm. To capture a relevant comparison for these thresholds from a merchant’s establishments that are contained in one city, we estimate the merchant’s nation-wide revenue by scaling the spending we observe in our 15 metro areas to estimate national spending. On the employment side, we do not see the number of people that work for the merchants that sell goods and services to the consumers in our LCC data. Consequently, we use data from Statistics of US Businesses program at the US Census to estimate the average number of employees per merchant for a given industry. We designate small businesses as those merchants with estimated revenue or an estimated employee count that is less than or equal to the SBA thresholds.

LCC data in some ways resembles the kind of information a consumer might find on their credit card statement. Each transaction includes a variety of information, inclusive of the merchant name, but it does not include information about individual items on the receipt for a given purchase. Consequently, our breakout of product types is a broad categorization of the kinds of goods and services provided by the merchant. We construct these product types by grouping similar Merchant Category Codes (MCC), which are codes used by card companies to categorize merchants.

In the case of fuel and restaurants, the range of goods and services offered by retailers with these product types is fairly narrow. The range is broader for durables, nondurables, and other services. Durable goods are those which are consumed over time. As a practical matter, they are typically defined as having a life span in excess of three years. In the LCC data set, merchants in this group sell goods like furniture, telecommunication equipment, building materials, and musical instruments. Nondurable goods are those that are consumed “immediately”, realized as a life span of less than three years. LCC merchants in the nondurable product type include, but are not limited to, bookstores, wholesale clubs, grocery stores, and clothing providers.

In addition to larger service providers, the other services product type captures many of the small service providers that are typically underrepresented in large surveys because 1) surveys are expensive to administer and are therefore biased towards respondents that account for a larger portion of the economy, and 2) many small service providers lack the administrative capacity to respond to large, complex surveys. Our data collection avoids these costs by capturing data from the transactions directly. Merchants in this group include, but are not limited to, accountants, taxicabs, tailors, and dentists.

Currently, LCC transactions come from merchants in 15 Core-Based Statistical Areas (CBSAs), or metropolitan areas: Atlanta, Chicago, Columbus, Dallas-Ft. Worth, Denver, Detroit, Houston, Los Angeles, Miami, New York, Phoenix, Portland (OR), San Diego, San Francisco, and Seattle. The choice of these cities was based upon data coverage, geographic distribution, and a desire to vary the city size and industrial base in our set.

When we use the LCC data asset to build the Local Consumer Commerce Index, we break up the 15 cities we track into three groups: small, mid-sized, and large. These groupings are useful for illustrating how local consumer commerce can grow quite differently depending on the characteristics of the city. We focus on population size for this grouping. Specifically, we ranked each of the cities by the population of the surrounding CBSA, and split them into three groups based upon that rank.

The LCC lens offers a deeper look into consumer activity at a local level and, in doing so, provides valuable information to economists, policymakers and government officials. The LCCI, realized as year-over-year spending growth across different consumer and merchant groups, uses this lens to provide an ongoing measure of commercial activity in our target cities. It is a frequently updated data resource for local decision makers and national stakeholders that care about the link between local and national economic activity. The LCCI offers unique advantages over existing measures of consumer activity:

  • The LCCI is built on actual, individual consumer transactions, instead of self-reported measures contained in other data sets; it is derived from a dataset that contains over 19 billion de-identified debit and credit card transactions from 15 major US cities.
  • Updated monthly, the LCCI’s geographically specific data provides a granular and timely view of economic activity within cities and their surrounding metro areas.
  • The LCCI has a broader view of small service providers than prominent retail surveys. For example, food trucks, personal services, and small medical providers are captured in the LCCI but largely absent from other sources. Note also that new businesses enter the LCC universe as soon as consumers start purchasing from them.
  • Finally, in addition to providing aggregated sales growth data, the LCCI slices the numbers along consumer age and income, business size and type, and the relationship between consumer and merchant location to provide deeper insight into local economies.

Despite some differences in the kinds of retail activity covered (see Figure 2), both the LCC data underlying the LCCI and the data used to generate estimates of the Personal Consumption Expenditures (PCE) component of GDP inform our view of consumption activity in the US The source data for PCE estimates come, in large part, from the Annual and Monthly Retail Trade Surveys (ARTS and MRTS), produced by the US Census Bureau. These surveys seek to capture aggregate sales volumes at retail and food service stores, as well as inventories held by retail stores. This mail-out/mail-back survey of 12,500 merchants across the country remains the most conceptually comprehensive measure of retail activity in the US.

Both the LCCI and MRTS are reported monthly and seek to measure final demand, but the lenses differ in important ways. As vital as the MRTS is, it relies entirely on self-reported data from a relatively small number of firms. The sample size limits the ability of the MRTS to speak to local conditions, which is why the MRTS only reports national numbers. The LCCI, by contrast, offers measured data on realized transactions from over 59 million consumers. The sheer volume of data permits us to report local estimates with confidence.

The goal for both the LCC and MRTS lenses is to capture purchases by end users. MRTS does this by asking a limited sample of firms about their sales, thereby avoiding business-to-business transactions. The LCC lens, by contrast, uses the card choices of consumers. We exclude virtually all business-to-business purchases by excluding commercial cards from our transaction set, though it is possible for small business owners to make purchases of factor inputs with their personal cards. Moreover, the MRTS targets firms that have been in existence long enough to have acquired employees, and it is structurally biased towards the inclusion of larger firms. By using card spending, the LCC lens can see spending at even short-lived merchants, as well as small service providers (e.g. hairdressers, small health providers, etc.) that are likely to be missed by MRTS. In short, neither source is perfect, but the limitations of one are often the strength of the other. As such, the LCCI provides a powerful and unprecedented complement to MRTS that is freely available to the public.

Often, the top line LCCI and MRTS growth figures are generally aligned; that is, they broadly move in the same direction, reflecting the overall path of the economy. But sometimes they diverge (see Figure 4) due to differences in the underlying data and the way in which it is collected. That is when the LCCI is best positioned to offer new insights into what is happening at the local level.

Figure 4 - MRTS vs LCCI (with and without "Other Services")