Inflation and the U.S. Census Bureau’s Economic Indicator Programs 

Paul Bucchioni, John Hatley, James Hunt, Scott Scheleur, and Deanna Weidenhamer, U.S. Census Bureau

September 2022 

In the recent July 2022 Consumer Price Index (CPI) published by the Bureau of Labor Statistics (BLS), the 

price index for All Urban Consumers (CPI-U) reached a growth rate of 8.5% from July 2021 for All Items. 

Drilling into the release provides even more evidence of these price impacts. The CPI-U for Food 

increased 10.9% on a year-over-year basis, highest since March 19791. See Figure 1 below for a look at 

the 12-month increases in the CPI-U for All items, Food, Energy, and All items less food and energy. 

 

Figure 1: 12-month percentage changes, BLS, Consumer Price Index, July 20222

U.S. Census Bureau Economic Indicators 

The Census Bureau produces 13 economic indicators on either a monthly or quarterly frequency. These 

indicators (and related non-indicator products) are known for their quality, consistency, and longevity. 

These official statistics are often referred to as the “gold standard” for the sectors and topics they 

measure. Public and private data users utilize these indicators for everything from metrics on the 

current state of the economy to forecasting future economic performance. In addition, our sister 

agency, the Bureau of Economic Analysis (BEA), feeds the results of many of these surveys into the 

quarterly calculation of the Gross Domestic Product (GDP). 

1

 Consumer Price Index release, Bureau of Labor Statistics, July 2022, Table 7. Consumer Price Index for All Urban 

Consumers (CPI-U): U.S. city average, by expenditure category, 12-month analysis table 

2

 Consumer Price Index release, Bureau of Labor Statistics, July 2022, Graphics for Economic News Release
While these indicators provide insights into the U.S. economy, many of these indicators are presented 

on a nominal basis. That is, there are no price adjustments applied to those economic indicator 

estimates. Without these adjustments, it can be challenging to identify the true underlying trend from 

these indicators released each month/quarter. 

The BEA, as part of the GDP calculation, does translate the nominal estimates generated from these 

indicators into real estimates primarily utilizing Census Bureau data in conjunction with the Consumer 

Price Index (CPI) and Producer Price Index (PPI) from the Bureau of Labor Statistics. This results in a 

comprehensive presentation of quarterly data on a real basis for use in understanding how the U.S. 

economy performed in any quarter. 

While these real estimates generated each quarter present the underlying trends, how might one 

attempt to create approximations of real dollar estimates for a given indicator release? To investigate 

this, we can look at the Advance Monthly Sales for Retail and Food Services. 

Advance Monthly Sales for Retail and Food Services 

The Advance Monthly Sales for Retail and Food Services (often referred to as MARTS) has been a highly 

sensitive principal federal economic indicator since the 1950s. Released approximately two weeks after 

the reference month, the MARTS estimates are a closely monitored barometer of consumer spending 

and is one of the first economic indicators released by the Census Bureau each month. 

The MARTS3 estimates are based on a monthly survey of approximately 5,500 retail and food services 

businesses. Each month, these businesses are asked to provide sales for the preceding month, but no 

price or quantity information. This sample is a sub-sample of the larger Monthly Retail Trade Survey 

(MRTS), which collects sales, end-of-month inventories, and e-commerce sales from approximately 

13,000 retail and food services businesses. After the MARTS release, the sales estimates are replaced 

the following month by estimates from this larger MRTS3 sample. 

The MARTS presents nominal sales on both a not adjusted and seasonally adjusted4 basis, as well as 

month-to-month, quarter-to quarter, year-to-year, and cumulative year-to-date trends for the retail 

sector and food services sub-sector as defined by the North American Industry Classification System 

(NAICS). These estimates are price adjusted by the BEA and fed into their respective components within 

the Personal Consumption Expenditures (PCE) piece of the GDP. 

The MARTS data can be misleading if you do not acknowledge the role inflation (or any price change) 

plays in the trends shown in the release. In certain cases, the price change can be the primary reason for 

a nominal increase or decrease and potentially obscure an underlying trend that could even be in the 

3 Estimates in the MARTS and MRTS releases are subject to sampling and nonsampling error. Additional 

information on the survey methodology, including sampling and nonsampling error, may be found at 

https://www.census.gov/retail/how_surveys_are_collected.html

4

 The seasonal adjustment for MARTS includes adjustment for seasonal variation, as well as holiday and tradingday differences. More information can be found at https://www.census.gov/topics/research/seasonaladjustment.html
opposite direction. With that in mind, we examined options to conduct some high-level price 

adjustment using MARTS data and corresponding CPI-U series as inputs. 

Price Adjustment Approach 

As we look to price adjust MARTS estimates to shed light on underlying retail trends, it’s important to 

understand that this is an attempt to utilize high-level data from Census and BLS to roughly approximate 

real retail spending. This is not an attempt to approximate the real spending estimates that the BEA will 

show in their quarterly GDP release nor their monthly consumer spending estimates. 

The MARTS release5 contains monthly estimates for Retail Trade (NAICS sector 44-45) and Food services 

(NAICS subsector 722). In addition, MARTS includes estimates for the twelve (12) 3-digit NAICS 

subsectors within retail trade. Utilizing CPI-U estimates from the BLS’ Consumer Price Index (CPI) release 

in conjunction with the MARTS related estimate, we can generate aggregate price adjustments. Some 

examples: 

MARTS Series Name CPI-U Name

Retail Trade and Food Services All Commodities Index

Grocery Stores Food at Home

Gasoline Stations Gasoline (all types)

Food Services & Drinking Places Food Away from Home

 Table 1. MARTS time series matched to a comparable BLS CPI-U price index. 

By utilizing these series from both agencies, a direct calculation can be done using these two series to 

price adjust the nominal MARTS series. While these methods may not generate the most precise price 

adjusted data, they can serve as a measure for how prices are impacting the nominal trends published 

each month. 

The process used was to take the nominal sales number for the series and divide by the deflator to price 

adjust the estimates. This deflator was developed by dividing the BLS price series by the 2012 average 

for that same price series to index it. 

For simplicity, the BLS CPI-U All Commodities price index6, rebased to 2012, was used as the deflator for 

Retail Trade and Food Services. This series was chosen as the closest representation of the coverage of 

retail sales and food services that is found in the MARTS release since it excludes key sectors like 

services, housing, education, etc. 

This produces a real dollar series one can use to better understand the indicator estimates. This is a 

different approach from how this is normally done where weighted percentages would be used for each 

component price index to derive an aggregate fixed-weight deflator. Taking this more detailed approach 

could be an avenue pursued later but for the purposes of this illustration of price impacts, this direct 

5

 The MARTS release referenced in this release is the July 2022 release which can be found at: 

https://www2.census.gov/retail/releases/historical/marts/adv2207.pdf. The most up-to-date retail data can 

always be found at https://www.census.gov/retail/index.html

6

 The BLS CPI-U All Commodities price index is BLS series CUUR0000SAC which can be found in Table 3 of the CPI 

release each month at https://www.bls.gov/news.release/cpi.t03.htm
approach can be used as an approximation. See figure 2 for a look at the original nominal time series 

versus the real dollar series using fixed weights that results from this method. 

Figure 2. Nominal vs Real Dollar estimates for Retail & Food Services using CPI-U for All Commodities 

 

Using the calculated real dollar estimates shown in figure 2, this process allows calculations of real dollar 

month-to-month percent changes that can be compared against their nominal counterparts. See figure 

3 below for this presentation. 

Figure 3. Nominal vs Real Dollar month-to-month percent changes for Retail & Food Services using CPI-U for All Commodities 
Similarly, calculations can be done for year-over-year percent changes. Figure 4 presents those results. 

As with the month-to-month percent changes in figure 3, one can see how the percent changes vary 

between a nominal and real dollar basis and the different perspective of consumer spending trends. 

Herein lies the value of adjusting for price changes. 

Figure 4. Nominal vs Real Dollar year-to-year percent changes for Retail & Food Services using CPI-U for All Commodities 

Summary 

Since the U.S. Census Bureau does not publish real dollar estimates for many of its economic indicators, 

interpreting the meaning of changes in any given month can be a challenge. Utilizing time series from 

the U.S. Census Bureau along with corresponding price indices from the BLS’ Consumer Price Index can 

provide users with a method to better understand the impacts price changes may be having on the 

estimates. 

The methods presented here for the MARTS do have their limitations. The sales estimates collected 

each month do not have unit or quantity information and the sample is not controlled to ensure 

representative product coverage7 within each NAICS subsector. The methods above also do not try to 

decompose the estimates to a finer level of detail to use more precise price indices in creating price 

adjusted estimates. That’s what the BEA does as part of the GDP calculations each quarter. 

7

 The monthly retail samples are controlled to ensure the representativeness of the NAICS industries within a 

published level, but this does not guarantee the selected companies have a similar product composition to the 

universe. For more information, see https://www.census.gov/retail/how_surveys_are_collected.html
This effort was done to provide some insight on the price impacts to retail sales and the results should 

be used with caution. However, the type of price adjustment presented has value for helping data users 

better understand the role prices may be playing in the nominal estimates released each month. 

We want to hear from YOU! Email all feedback to eid.retail.indicator.branch@census.gov