1 — U.S. BUREAU OF LABOR STATISTICS • bl s.gov

Expenditure Patterns of Low and High Income 

Groups by State: California, Florida, New Jersey, 

New York, and Texas

Grayson Armstrong

Economist

Division of Consumer Expenditure Surveys

Eastern Economic Association
2 — U.S. BUREAU OF LABOR STATISTICS • bl s.gov

State Estimates

First test estimates produced for three states (CA, FL, 

and NJ) using 2013 data.

First official weights 

published using 2016 data 

for three states in 2018.

Two additional states (NY

and TX) were added in 

2019.
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How do they work?

 Suppose the population of 

New Jersey was 20. 

 Each consumer unit in New 

Jersey is re-weighted to 

represent the population of 

New Jersey instead of the 

national population.

National Weight: 100

NJ Weight: 10

National Weight: 120

NJ Weight: 8

National Weight: 80

NJ Weight: 2
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How well do they work?

 Compare population targets to US Census. 

1. Add up the weights for Florida from PUMD.

~8.5 Million Consumer Units (CU)

2. Compute average number of people per CU 

with the weight. 

2.4 people per CU

3. Multiply and compare to Census value. 

8.5 * 2.4 = 20.4 million people

Approximately equal to the 20.6 million 

reported Florida population. 
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Who uses them?

 Academics

Researchers have been asking for greater 

geographic detail for a long time. This is an effort 

to provide it where we can. 

 Government

The New Jersey weights were utilized by the New 

Jersey State Government.

 You!

Curious individuals can now answer questions 

about state level expenditures. 
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Using the weights

 By taking national data and applying a state’s weight we can create data 

estimatesthat are representative of CUs within that state

 Here we’ve taken all 5 state weights and applied them to data from 2017 -

2018 and aggregated into 10 expenditure categories

Food, Housing, Apparel and services, Transportation, Healthcare, Entertainment, 

Education, Cash contributions, Personal insurance, All other expenses.

 We then further evaluated the data by examining the differences 

between income quintiles, focusing mainly on the lowest 20% and highest 

20% of incomes
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Trends across States

 In all 5 states the lowest income group allocates a greater proportion of 

expenditures to necessary items (food and housing) than the highest 

income groups

 The highest income groups spend more on personal insurance and 

pensions than the lower income groups

California’s top quintile has the highest share at 17%, where New York, New Jersey, 

and Texas all have 15% at the low end

Comparatively California’s lowest quintile only allocates 3% of expenditures on 

personal insurance, with New York having the lowest at only 1%
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The Necessity Gap

 Across all 5 states and nationally there is a gap in necessity (food + 

housing) expenditures between income quintiles

New York’s lowest group has the largest share at 65% of all expenditures, while 

low-income Texans have the lowest at 56%

New York’s top quintile has a necessity expenditure share of 44%, while Texas has 

42%

 Nationally this gap is 15%, New York and California have the highest gaps 

at 20% and 17%

 Texas has a 14% gap, while New Jersey and Florida both have the lowest 

at only 13%
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State vs National Trends

 Almost all the patterns displayed by the states also appear at the national 

level

 Nationally, necessities make up 57% of expenditures for the lowest 

income group, close to most states besides California and New York at 

61% and 65% respectively.

 Conversely, the personal insurance spending share for the highest group 

is 16% nationally, nearly the same as all 5 states
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Conclusion

 The state weights can be used to produce estimates of average 

annual expenditures and shares for selected states. Those 

examined here are close, but not identical to, national estimates

 The weights can be used to better aggregate and account for 

geographical patterns in spending where possible

 Our example shows clear patterns by income level that appear 

across state data as well as at the national level
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Interested?

 https://www.bls.gov/cex/csxresearchtables.htm#stateweights

Documentation

– How the weights are created

– How to utilize State Weights with PUMD

State weight files

Sample code
Contact Information

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Grayson Armstrong

Economist

Division of Consumer Expenditure Survey

(202)-691-6519

Armstrong.Grayson@bls.gov