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March 2018 | Vol. 7 / No. 2

REGIONAL ECONOMIES

Consumer spending by state: BLS puts 

New Jersey to the test

By Taylor J. Wilson

The Bureau of Labor Statistics Consumer Expenditure Surveys (CE) program conducts surveys that provide 

data to produce average and total annual consumer expenditure estimates for a variety of goods and services at 

the national level. These estimates are produced by assigning a population weight to each interviewed 

consumer unit; this tells us how many other households that consumer unit represents. A consumer unit differs 

slightly from a household. That is, a household comprises the physical dwelling in which a consumer unit may 

live. In contrast, a consumer unit comprises either: (1) all members of a particular household who are related by 

blood, marriage, adoption, or other legal arrangements; (2) a person living alone or sharing a household with 

others or living as a roomer in a private home or lodging house or in permanent living quarters in a hotel or 
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motel, but who is financially independent; or (3) two or more persons living together who use their income to 

make joint expenditure decisions. The sum of the CE population weights is designed to equal the total U.S. 

population of consumer units.1

The CE national weight is calibrated to produce representative estimates of the population for several 

subnational geographies (e.g., census region, some metropolitan statistical areas) but since the surveys’

inception, it has never been calibrated to represent state level populations. Recently, CE has investigated the 

possibility of designing a supplemental weight, computed separately from the national weight, which could apply 

to interviewed consumer units in specific states.

This Beyond the Numbers article focuses on how New Jersey consumers allocate spending among the 

components of the market basket of total spending, and how their spending pattern differs from that of 

consumers at national and subnational geographies. By comparing expenditure data from the CE in conjunction 

with the state weights for New Jersey, the article explore economic questions related to the state. This is the first 

in a series of new experimental state weights that CE is producing for public use and making available with the 

public-use microdata. In addition, it examines spending on one of the largest components of the consumer 

market basket—housing—in greater depth for both New Jersey and the nation. All of the data used for the

proceeding analysis are from the public-use microdata, meaning they will differ slightly from the published 

estimates due to confidentiality edits.

Motivation for weight creation

Data users have long communicated a need for state-level expenditure estimates to conduct policy analysis that 

is state specific using the CE data. Due to the CE’s relatively small sample size, only a handful of states have

representation in the sample that is capable of supporting a state-level weight. Coverage is the most important 

criterion for determining if a state weight can reasonably be created. Large, sufficient samples can be drawn 

from the self-representing primary sampling units (PSU) (i.e. large geographic areas that are always sampled 

from) that some states’ geographies are covered by. This allows the reweighting of their sampled population to

be representative of that state. Each consumer unit is assigned a number that represents other non-sampled 

consumer units in that state—that consumer unit’s state weight. That consumer unit also has a national weight,

meaning the number of consumer units that consumer unit represents across the entire nation. When the weight 

for all consumer units sampled is added up, you will have the target population of the state. The target 

population is sourced from the Census Bureau. In addition, these values are calibrated to the socioeconomic 

characteristics available in the survey. This means the weight also includes the target populations for race, 

gender, household composition, etc.

Of all the eligible states, New Jersey was a natural first choice, due to its geographical boundary being almost 

entirely covered by self-representing metropolitan statistical areas (MSAs). Specifically, the New York MSA and 

the Philadelphia MSA include almost every county in the state. The CE public-use microdata already provide a 

state-level identifier in the data; however, that identifier is only useful for computing sample estimates as 

opposed to nationally weighted values for that state if enough consumer units happen to be sampled.2 With 

these new state weights, robust statistical inferences can be drawn about state-level expenditure and income 

estimates.
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Internal consistency

All consumer units sampled in New Jersey also reside in either the New York MSA or Philadelphia MSA. 

Weighted expenditure estimates for these MSAs are computed using the national weight. The New Jersey state 

weights, if operating appropriately when applied with expenditures, should produce estimates similar to these 

MSAs because they share a large percentage of the same consumer units. Table 1 provides evidence that the 

New Jersey state weights appear to perform as expected. These sorts of internal consistency checks are 

important for determining the statistical validity of any new data product.

(1) Nationally weighted estimates.

(2) State weighted estimates.

Note: Not all expenditure categories are reported in this table.

Source: U.S. Bureau of Labor Statistics, Consumer Expenditure Surveys Public-Use Microdata.

External validity

In addition to ensuring that state-weighted estimates are consistent with existing data products from CE data, 

the CE program assessed these state-weighted estimates with estimates from external data sources so that 

they are conceptually comparable to CE data. Every year, the CE program compares estimates of several key 

expenditure categories with estimates from the American Community Survey (ACS).3 The ACS is a useful 

comparison target because it is also a national representative household survey with the added benefit of 

already being calibrated at the state level. Due to differences in questionnaire design, scope, and coverage, the 

estimates will not match exactly with those from the ACS, but the values are reasonably comparable. The ACS 

samples in each individual state, so it is possible to compare state-weighted estimates from CE with ACS 

values.

The actual expenditure values between the two surveys are not useful for comparison but rather how different 

they are. This can be measured with a ratio of the two expenditure values from each survey. The closer the CE–

ACS ratio is to 1, the more similar the estimates from the two surveys are. Ideally, the New Jersey state weight 

will produce CE estimates that vary from the ACS New Jersey numbers to the same degree as the CE national 

estimates vary from the ACS national estimate. Generally, the results of the New Jersey CE–ACS comparison

are similar to those from the national CE–ACS comparison. The CE–ACS ratio for rent in New Jersey is 0.91,

whereas the same ratio for the nation as a whole is 0.95. Electricity and natural gas expenditures are at a ratio 

of 0.86 in both New Jersey and the nation. The results of the comparisons for those key expenditure items are 

Categories New York MSA(1) Philadelphia MSA(1) New Jersey(2)

Total expenditures $65,764 $60,504 $63,099

Food 9,190 8,649 8,641

Housing 24,308 20,047 23,617

Apparel 1,645 1,119 1,491

Transportation 6,828 8,188 7,295

Healthcare 4,260 4,800 5,239

Entertainment 2,277 2,496 2,097

Education 2,171 2,081 2,182

Table 1. Expenditure means of selected consumer expenditures item categories, by selected 

subnational geographies, 2016
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presented in charts 1 and 2 below. To visualize the ratio for each category, the expenditure amounts are 

presented.

Chart 1 above shows the average annual expenditures for the state of New Jersey on four comparable 

categories between Consumer Expenditure Survey data and American Community survey data. In each of the 

four presented categories, the expenditures are all relatively close to each other. With the exception of water, 

CE tends to underestimate ACS. However, these comparisons are only useful in comparing the efficacy of the 

CE New Jersey Weight to the ACS New Jersey weight if the relationship between the CE national weight and 

the ACS national weight is understood. As such, the four categories are compared below in chart two for the 

national level showing similar differences at the broader geography. Overall, because the New Jersey weight 

causes differences from ACS that are similar in magnitude to the National weight differences from ACS then the 

weight is performing as expected.
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Example of weight use: The market basket

Do urban consumers in New Jersey spend more on housing expenditures than U.S. urban consumers? State 

weight analysis can help answer this question. By using the weight, is possible to create a market basket of 

goods and services that New Jersey consumers are purchasing. In order to do this, the data are divided into 

categories of expenses and the shares of the total that each of these expenses makes up help the CE data user 

understand what U.S. consumers are spending their money on. Deciding how to divide up expenses is a nontrivial exercise. For the purposes of this analysis, the major item categories were selected to match the item 

categories the Consumer Price Index (CPI) uses in the national market basket. The larger the share the higher 

the ‘relative importance’ of the item is to the market basket compared to the other items in the basket.4 The New 

Jersey market basket for 2016 can be approximated reasonably from the shares of total weighted 

expenditures.5

The resulting market basket presented below may not be reflective of one’s individual purchasing experience.6

This is because any particular household’s market basket may differ significantly from that of the average U.S.

urban household. Table 2 shows the weighted shares of total expenditures by major item category for both New 

Jersey and the nation.
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(1) The CPI category is ‘Education and communication,’ for clarity only education is included here and communication is placed in ‘Other goods and

services.’

Source: U.S. Bureau of Labor Statistics, Consumer Expenditure Surveys, CPI shares of relative importance.

It is clear that consumers in New Jersey differ from the average U.S. urban consumer, as shares for several key 

components of the market basket, most notably housing, differ by several percentage points. This type of 

holistic analysis at spending patterns allows users to answer very general questions like the one posited at the 

beginning of this section. In the next section, housing is explored in greater depth as being the largest difference 

in spending patterns between New Jersey and U.S. households.

Example of weight use: housing in New Jersey

New Jersey is a unique state. Much of the landmass of the state is covered with the metropolitan sprawl of 

neighboring New York City and Philadelphia city centers. This results in a large population being packed into a 

comparatively small landmass. According to the 2010 Census, the state of New Jersey has the highest 

population density of any state at 467.2 persons per square kilometer. With such a large number of people living 

in a small space, New Jersey has a comparatively high demand for housing, and thus, living costs are higher in 

New Jersey, compared with national and subnational estimates.

Categories New Jersey shares National shares Absolute difference

Food and beverages 0.12 0.13 0.01

Housing 0.39 0.33 0.06

Apparel 0.03 0.03 0.00

Transportation 0.12 0.16 0.04

Medical care 0.09 0.08 0.01

Recreation 0.04 0.05 0.01

Education(1) 0.04 0.02 0.02

Other goods and services 0.19 0.20 0.01

Table 2. Shares of total expenditure, by major Consumer Price Index item categories, 2016
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According to the Census Bureau, New Jersey has ranked consistently as one of the most expensive places to 

buy a home for over half a century.7 Lower income families, whose housing costs mostly consist of monthly rent 

payments, are not insulated from the effect of higher home prices in the state, as these prices translate into 

higher rents so that landlords are able to cover their debt service payments. Chart 3 shows that costs for owned 

dwellings in New Jersey outpace other selected geographies. In addition, with the exception of San Francisco, 

New Jersey has the highest owned-dwelling expenditure compared to any MSA in absolute amount. Average 

rent for a dwelling in New Jersey is slightly lower than that for Washington, D.C., but higher than the national 

average by 21 percent. Looking at these figures as a percentage of total housing in each geography, users can 

equalize the relative cost of rent. Chart 4 shows that owned-dwellings expenditures still make up a larger 

proportion of total housing for the state of New Jersey than for Washington, D.C. or the nation as a whole.8

Owned-dwellings are 46% of total housing for New Jersey. Even San Francisco, is lower than this amount at 

36% of total housing even if their absolute amount is higher. As a direct result, the proportion of total housing 

expenditures consisting of rent is higher nationally than that for either New Jersey or Washington, D.C.
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Conclusion

Overall, the New Jersey state weights perform well on quality metrics like internal consistency and external 

validity. Estimates produced with the New Jersey state weights are consistent with internal data sources and 

perform favorably with external data sources. They add additional power to CE data by allowing users to explore 

economic conditions in the state. New Jersey consumers allocate a larger share of total expenditures to housing 

than the national average and expenditures on owned dwellings make up a larger proportion of housing 

expenditures in New Jersey compared with the national average. The results from an analysis of housing 

expenditures seem consistent with economic hypotheses about the state. More of this kind of research is 

forthcoming as CE explores the quality of the weights when the data are used in more rigorous statistical 

analyses. Looking forward, the CE program intends to publish the New Jersey weights annually in an 

experimental non-production capacity, and investigate other states as candidates for weight creation. These 

weights will remain experimental because there are no plans to place them into production capacity in the 

foreseeable future. Presently, the weights are used and evaluated by the public and other Bureau of Labor 

Statistic (BLS) researchers. Eventually, researchers will be able to examine the effects of economic shocks over 

time for these states and test more detailed hypotheses.
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This Beyond the Numbers article was prepared by Taylor J. Wilson, Economist in the Information and Analysis Section, Office of 

Prices and Living Conditions, Email: Wilson.Taylor@bls.gov, telephone: (202) 691-6550.

Upon request, the information in this article will be made available to individuals who are sensory impaired. Voice phone: (202) 

691-5200. Federal Relay Service: 1-800-877-8339. This article is in the public domain and may be reproduced without permission.

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NOTES

1 For more information about population totals and state weights documentation, see https://www.bls.gov/cex/stateweightspumd.pdf. 2 For more information about microdata and how to obtain these data that is available, see https://www.bls.gov/cex/pumd.htm. 3 For more information about comparisons between the American Community Survey and Consumer Expenditure Survey, see 

https://www.bls.gov/cex/cecomparison.htm#ACS. 4 Relative importance of item groups are obtained from the most recent 2 years of the Consumer Expenditure Survey and are the 

proportion of total expenditures in the super-index area that come from an item group. For more information, see https://

www.bls.gov/opub/hom/pdf/homch17.pdf. 5 For more information about the goods and services CPI covers, see https://www.bls.gov/cpi/questions-andanswers.htm#Question_7

6 For more information about how CPI measures price change, see https://www.bls.gov/cpi/questions-andanswers.htm#Question_5. 7 For more information about historic home values, see https://www.census.gov/hhes/www/housing/census/historic/values.html. 8 Owned-dwellings and rented-dwellings are the two components of housing. Owned-dwellings focuses on expenditures like 

mortgage interest and homeowner’s insurance where are rented dwellings consist primarily of rent and renter’s insurance, see

https://www.bls.gov/cex/pumd/2016/csxintstub.txt. SUGGESTED 

CITATION

Taylor J. Wilson, “Consumer spending by state: BLS puts New Jersey to the test ,” Beyond the Numbers: Regional Economies, vol. 

7, no. 2 (U.S. Bureau of Labor Statistics, March 2018), https://www.bls.gov/opub/btn/volume-7/consumer-spending-by-state-blsputs-new-jersey-to-the-test.htm