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Consumer Checkpoint
Still smiling
05 May 2022
Consumer Checkpoint is a regular publication from the Bank of America Institute. It aims to provide a holistic and real-time estimate
of US consumers’ spending and their financial well-being, leveraging the depth and breadth of Bank of America proprietary data.
Key talking points
• Bank of America data shows consumers are still spending. Total payments were up 25% YoY in April, with growth elevated
due to the timing of tax payments. Transactions, up 8%, provide a more normalized indication of healthy consumer demand
this month.
• Total credit and debit card spending was up 13% YoY in April, compared to 11% in March. Travel and entertainment spending
continues to elevate growth.
• Card spending per household is up around 23.7% in the 28-days to April 30 compared to the same period in 2019, with
spending on this measure up 33.1% amongst lower income households. Lower income average spending growth appears to
have flattened over recent weeks, but this may represent usual seasonality.
• The pandemic saw a big swing towards goods and away from services spending. This now looks to have substantially reve rsed
as the economy emerges from the latest pandemic wave.
Easter bunny arrives with spring in its step
Still smiling. Bank of America aggregate credit and debit card spending was up 13% YoY in April. Within this, credit card
spending rose by 22% YoY, while debit card spending increased by 6% over the same period.
While higher inflation is leading to higher spending it is clear consumer strength goes beyond this, with aggregate spending
growth exceeding current US consumer price inflation of 8.5% in March. There is sustained strength observed in travel and
entertainment; spending at airlines and travel agencies is up over 60% YoY, and spending at event ticket agencies is up 140%. As
discussed in our Consumer Morsel, (see report) ‘Three reasons to be cheerful’
, the strength of the labor market is likely
alleviating some of the pain of higher prices for those on lower incomes.
As Exhibit 1 indicates, in 2021, card spending per household was rising sharply around this period, reflecting the third Econom ic
Impact Payment ('EIP3') and the re-opening of the economy. This makes the 2022 year-on-year growth rate comparison
stretching (ie difficult to be very strongly positive) but even so card spending per household is still rising in 2022 on this basis.
Also, compared to earlier years, it is significantly higher – the three-year growth rate in the 28-days to April 30 was 23.7%.
I NSTITUTE
Accessible version
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Exhibit 1: Average daily total card spending per household (rolling 28-day averages, indexed to 2019 average spend)
Average daily card spending is climbing in 2022 and is higher than each of the last three years
Source:
Bank of America Internal Data
Lower income spending rising sharply over pre-pandemic level. It is really in lower income households (<$50k) where the
comparison to 2021 is very ‘challenging’ (ie very difficult to get high positive growth rates on a year earlier) as illustrated in
Exhibit 2. This group’s spending was really ramping up as stimulus checks were paid and people re-engaged with the economy at
this time in 2021. In 2021 households with higher income (>$125k) saw a smaller lift in spending per household. Overall though,
the lower income group is tracking much larger increases in spending compared to pre-pandemic 2019 spending levels In the
most recent monthly data, there has been some flattening in spending, particularly among lower income households, but it is too
early to say if this simply represents the normal seasonal pattern.
Exhibit 2: Average daily total card spending per household with
income below $50k (rolling 28-day averages, indexed to 2019
average spend)
Card spending for households with incomes below $50k was rising
very strongly in 2021. In 2022 it is still managing to increase relative
to 2021
Bank of America Internal Data
Exhibit 3: Average daily total card spending per household with
income above $125k (rolling 28-day averages, indexed to 2019
average spend)
In 2021 households with incomes above $125k saw a smaller lift in
spending per household
Source:
Bank of America Internal Data
0
25
50
75
100
125
150
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2019 2020 2021 2022
50
75
100
125
150
Jan Mar May Jul Sep Nov
2019 2020 2021 2022
50
75
100
125
150
Jan Mar May Jul Sep Nov
2019 2020 2021 2022
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Interestingly, the picture of a relatively strong performance in spending am ong lower income households is supported by the
latest BofA US Consumer Confidence Indicator (Exhibit 4) which is produced by the BofA Global Research team (refer to
methodology below). Recent confidence level readings in 2022 have seen stability in the consumer confidence of the lower
income consumer, while the confidence of higher income consumers has fallen. This is despite considerable amount of news-
flow around inflation and price rises, which might have been expected to dent the confidence of lower income groups. One
explanation could be the strength of the labor market and wage growth is helping offset some inflationary concerns.
Exhibit 4: BofA US Consumer Confidence Indicator by income groups (% Daily weighted moving average)
Sentiment of higher income consumers have plunged, while it is holding up better for lower income groups
Source:
BofA Global Research
The indicator identified as the BofA US Consumer Confidence Indicator above is intended to be an indicative metric only and m
ay not be used for reference purposes or as a measure of performance for any financial
instrument or contract, or otherwise relied
upon by third parties for any other purpose, without the prior written consent of BofA Global Research. This indicator was not created to act as a benchmark. The 28 day rolling
moving average is weighted by the daily sample size during the 28
-day window. Average sample size: 2,914 per 28-day window (14-day 1,460). Data through April 21.
Rotation, Rotation, Rotation
The successive waves of the pandemic saw households holding back on services spending, both through choice and by mandate,
with the initial strict lockdowns closing restaurants, theatres and travel for example. But, as the US has re-opened following the
omicron wave, there has been a resumption of services spending. As Exhibit 5 shows, the ratio of household card spending on
‘goods’ (as measured by retail sales categories less restaurants) and ‘services’ (the remaining part of card spending) is now more
or less back at 2019 levels for both higher and lower income households.
As a result, the recent momentum in services spending per household, up over 20% in the three years to April 2022, may be
expected to slow eventually. At the same time, higher goods prices for things like fuel and food are likely to support goods
spending, even if volumes are pressured.
20%
25%
30%
35%
40%
45%
50%
55%
Jan 21 Apr 21 Jul 21 Oct 21 Jan 22 Apr 2 2
<=50k >125k
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Exhibit 5: The monthly ratio of card spending per household on retail ex restaurants (‘goods’) to ‘services’
During lockdowns spending on goods rose relative to services spending. In the current period the ratio is more in line with the level in 2019.
Source:
Bank of America Internal Data
Broader payments data supports growth
For April, Bank of America payments data supports the robust story coming out of credit and debit card spending. Growth across
all channels was up 25% YoY in April, elevated due to the timing of this year's tax payment deadline relative to last year.
Transaction growth, a more normalized indicator this month, was up 8%.
Zooming out on a longer time horizon underscores the strong growth we've observed as compared to pre-pandemic. April year to
date total payments and card spending was up 17% YoY and 15% respectively, topping the pre-pandemic growth rates.
Overall, internal Bank of America data continues to paint a healthy picture of the consumer.
Exhibit 6: Year-to-date total payments and credit/debit payments (% y/y) and net change in confirmed US coronavirus cases (‘000s)
Cumulative year-to-date payment growth rose slightly in April, and remains very strong compared to growth in the period 2019-2020
Source: Bank of America Internal Data , Bloomberg
0
0.6
1.2
1.8
2.4
Jan 19 Jul 19 Jan 20 Jul 20 Jan 21 Jul 21 Jan 22
Household income <$50k Household income >125k
0
5,000
10,000
15,000
20,000
25,000
-20%
0%
20%
40%
Jan 19 Jul 19 Jan 20 Jul 20 Jan 21 Jul 21 Jan 22
Net change in confirmed covid cases (rhs) Total Payments YTD Credit and Debit YTD
March 2020 EIP1: $1200
per eligible adult
March 2021 EIP3: $1400
per eligible adult
Jan 2021 EIP2: $600
per eligible adult
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Contributors
David Tinsley
Director, Bank of America Institute
Acknowledgments
Yanghong Shao
Senior Vice President, Global Risk Analytics
Ana Maxim
Senior Vice President, Consumer and Small Business
Jonathan Kaplan
Senior Vice President, Digital and Marketing
Methodology
Selected Bank of America transaction data are used to inform the macroeconomic views expressed in this report and should be
considered in the context of other economic indicators and publicly available information. In certain instances, the data may
provide directional and/or predictive value. The data used are not comprehensive; they are based on aggregated and anonymized
selections of Bank of America data and may reflect a degree of selection bias and limitations on the data available.
Total payments include total credit card, debit card, ACH, wires, billpay, person-to-person, cash and checks. The payments data
represents aggregate spend from Retail, Preferred, Small Business and Wealth Management clients with a deposit account or
credit card. Data is not adjusted for seasonality, processing days or portfolio changes, and may be subject to periodic revisions.
Aggregate card spend is based on processing date while the ‘per household’ measure is based on transaction date.
Bank of America credit/debit card spending per household include spending from active US households only. Only card holders
making a minimum of five transactions a month are included in the dataset. Spending from corporate cards are excluded. Data
regarding merchants who receive payments are identified and classified by the Merchant Categorization Code (MCC) defined by
financial services companies. The data are mapped using proprietary methods from the MCCs to the North American Industry
Classification System (NAICS), which is also used by the Census Bureau, in order to classify spending data by subsector.
Spending data may also be classified by other proprietary methods not using MCCs.
Additional information about the methodology used to aggregate the data is available upon request.
BofA US Consumer Confidence Indicator – methodology explained
The survey data for the BofA Consumer Confidence Indicator (BCCI), produced by the BofA Global Research US Economics team, is
collected online by survey company RIWI using "Random Domain Intercept Technology" (RDIT). This directs respondents who enter
an incorrect or lapsed URL address to a randomized survey site. The individuals who make these errors should constitute a random
and representative sample of the US online population. There may be advantages and disadvantages to this methodology.
The potential advantage is that RIWI is able to sample from hard-to-reach areas such as rural and underrepresented populations.
Moreover, while the data collected are not a fully randomized sample, Matthias Schonlau and Mick P. Couper find in their paper
(Statistical Science 2017, Vol. 32, No. 2, 279-292) that RIWI's methodology is a "near-probability" sample akin to " stopping
passersby on the street for an interview on the spot".
One potential disadvantage of this method is that the survey collects less comprehensive personal data about respondents,
meaning it is not possible to weight the sample with as many variables as some pollsters. That said, RIWI provides respondent
weight values which are generated post-stratification to match the age and gender of the US population based on data from the
Census Bureau. But there is a risk that the sample is skewed towards heavy internet users.
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Every survey method has advantages and disadvantages. At the least, the method employed is not currently used to construct a
measure of US consumer confidence so it should provide a potentially useful alternative view.
The aim is to achieve approximately 2,500 responses per month for each question. However, because some respondents choose
not to respond to all questions, it will not be possible to achieve the same sample size for every question. Moreover, the results
that are conditioned on demographic factors may further reduce the sample size and not capture the full universe of responses.
Under each chart, a note is made of the sample size that the analysis is based on each month. The confidence interval of the
responses is wider for results based on a smaller sample. The survey period will usually run the full calendar month.
Survey questions
The full survey generally includes 10 questions each month: three nonrotating questions on current conditions and future
expectation for personal finances and the economy (possible responses in italics) and a few questions on various topics such as
Covid sentiment, supply shortages, financial/credit conditions, and the labor market.
Nonrotating questions
1. Over the past year, your financial position has:
Improved a lot, improved a little, not changed, worsened a little, worsened a lot
2. Compared to a year ago, the US economy has:
Improved a lot, improved a little, not changed, worsened a little, worsened a lot
3. Do you expect the US economy over the next 12 months to:
Improve a lot, improve a little, not change, worsen a little, worsen a lot
Constructing the BofA US Consumer Confidence Indicator
Answers to questions 2 and 3 are used to construct the US Consumer Current Conditions Indicator and
US Consumer Expectations Indicator, respectively. For each question, a daily diffusion index is calculated that is equal to the sum
of the share of respondents reporting a "positive" response (e.g. improved a lot or improved a little) and half of the share of
respondents reporting a "neutral" response (e.g. not changed).
Each daily response is then weighted by the number of responses to total responses over the 28 day period to arrive at the
diffusion index for the 28 day period. This therefore, emphasizes days where more responses are made rather than treating each
day equally.
Finally, the BofA US Consumer Confidence Indicator is the simple average of the US Consumer Current Conditions Indicator and the
US Consumer Expectations. This indicator is useful as another measure of consumer confidence and is potentially advantageous to
preexisting consumer confidence measures (e.g. Conference Board, University of Michigan) because it can be updated on a timelier
basis.
In addition to the limitations noted above about the survey, the length of the survey is one potential limitation. Since the survey
has only been conducted since 2018, there is not enough history to fully understand how this measure of consumer confidence
could evolve over the business cycle.
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Disclosures
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dedicated to uncovering powerful insights that move business and society forward. Drawing on data and resources from across the bank and the world, the Institute delivers
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expressed herein are solely those of the Bank of America Institute and any individual authors listed, and are not the product of the BofA Global Research department or any other
department of Bank of America Corporation or its affiliates and/or subsidiaries (collectively Bank of America). The views in these materials may differ from the views and opinions
expressed by the BofA Global Research department or other departments or divisions of Bank of America. Information has been obtained from sources believed to be reliable, but
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