Regional Household Spending

Using the Consumer Spending

Microdata to Estimate 

Household Spending and Buying 

Power at Any Level of 

Regionality
Regional Household Spending

Using the Consumer Spending

Microdata to Estimate 

Household Spending and Buying 

Power at Any Level of 

Regionality
Households v Consumers
Households v Consumers

Consumer units include families, single persons 

living alone or sharing a household with others 

but who are financially independent, or two or 

more persons living together who share 

expenses.
Buying Power
Buying Power

Buying Power = Disposable Income

(= Income After Taxes)
Level of Regionality
Level of Regionality

Regional Hierarchy

U.S.
Level of Regionality

Regional Hierarchy

U.S.

Regions
Level of Regionality

Regional Hierarchy

U.S.

Regions

Divisions
Level of Regionality

Regional Hierarchy

U.S.

Regions

Divisions

States
Level of Regionality

Regional Hierarchy

U.S.

Regions

Divisions

States

Counties
Level of Regionality

Regional Hierarchy

U.S.

Regions

Divisions

States

Counties

Census Tracts
Level of Regionality

Regional Hierarchy

U.S.

Regions

Divisions

States

Counties

Census Tracts

Block Groups
Level of Regionality

Regional Hierarchy

U.S.

Regions

Divisions

States

Counties

Census Tracts

Block Groups

Blocks
The Original Purpose of the Consumer 

Expenditure Survey

To assist in constructing representative “market

baskets” which are then “priced” to form the

various Consumer Price Indexes (CPI-U being the

best known) and its components.
The Original Purpose of the Consumer 

Expenditure Survey

To assist in constructing representative “market

baskets” which are then “priced” to form the

various Consumer Price Indexes (CPI-U being the

best known) and its components.
Additional Uses of the Consumer 

Expenditure Data

Provides data to the Internal Revenue Service to calculate average

sales tax deductions on personal income tax forms.

Helps DOD in calculating Cost of Living allowances for military

personnel living off military bases in metro areas around the country.

Used by Department of Agriculture to construct guidelines for

nutritional benefits.

Used by government agencies and policy analysts to study the welfare

of various groups such as the elderly and low-income families and the

likely impact on these groups of various economic policies.
Yet More Uses

Used by the Department of Commerce to revise

the national income accounts.

Used by market researchers in analyzing the

demand for groups of goods and services.
Lets Take a Closer 

Look at These 

Purposes
The Original Purpose of the Consumer 

Expenditure Survey

To assist in constructing representative “market

baskets” which are then “priced” to form the

Consumer Price Index (CPI).
The Original Purpose of the Consumer 

Expenditure Survey

To assist in constructing representative “market

baskets” which are then “priced” to form the

Consumer Price Index (CPI).

NB: Calculating market baskets requires data 

on the average expenditures of consumer units 

by commodity type (UCC).
How About the Additional Uses?

Provides data to the Internal Revenue Service which allows it to calculate average

sales tax deductions on personal income tax forms.

Helps DOD in calculating Cost of Living allowances for military personnel living off

military bases.

Used by Department of Agriculture to construct guidelines for nutritional benefits

Used by government agencies and policy analysts to study the welfare of various

groups such as the elderly and low-income families and the likely impact on these

groups of various economic policies.
How About the Additional Uses?

Provides data to the Internal Revenue Service which allows it to calculate average

sales tax deductions on personal income tax forms.

Helps DOD in calculating Cost of Living allowances for military personnel living off

military bases.

Used by Department of Agriculture to construct guidelines for nutritional benefits

Used by government agencies and policy analysts to study the welfare of various

groups such as the elderly and low-income families and the likely impact on these

groups of various economic policies.

Each of these purposes require data on average

expenditures of CUs by type of expenditure.
... and Lastly

Used by the Commerce Dep’t to revise the national income accounts.

This requires data on aggregate expenditures of consumer units at the national

level, a need which is fully met by the published CE tables.

Used by market researchers to analyze demand for groups of goods and services.

This typically requires data at the sub-national level, which is met for 20-25 major

metros only.
Our Question

Can the PUMD data be used 

to estimate aggregate 

spending data for smaller 

levels of regionality?
Steps in Calculating the CE Tables 

(greatly simplified)

Step 1: Select households to be surveyed.

Step 2: Gather spending data from Consumer Units (CUs) 

within households.

Step 3. Calculate a final weight for each CU.

Step 5. Multiply the measured expenditures of each CU by its 

final weight.

Step 6. Sum the weighted expenditures to get Total Spending.

Step 7. Divide Total Spending by the number of CUs to get 

average spending for the U.S., Regions and selected MSAs.
Our Methodology

Step 1

Identify breakouts from the American 

Community Survey to be used as the 

weights


(N.B. Using the 5-year ACS data, 

these breakouts are available 

down to the census tract level)
Our Methodology

Step 2

Compile PUMD Interview and 

Diary Datasets together for 

years 2006-2016
Our Methodology

Step 3

Assign all CUs in the PUMD to 

one of the ACS household types 

by Census Division and 

Urban/Rural
Our Methodology

Step 3

Assign all CUs in the PUMD to 

one of the ACS household types 

by Census Division and 

Urban/Rural
Census Regions
Census Divisions

Our Methodology

Step 3

Assign all CUs in the PUMD to 

one of the ACS household types 

by Census Division and 

Urban/Rural

Urban vs. Rural Consumers

Gross Comparisons

Urban CU's Rural CU's

Pretax Income $71,578 $49,841

Total Spending $57,059 $45,031

Avg. Propensity to Consume 79.7% 90.3%

Avg. Propensity to Save 20.3% 9.7%

Home Ownership Rate 61% 79%

% Spent on Housing 33.4% 26.8%
Item Urban Rural % Difference

Rented dwellings 7.1 2.4 195.8%

Education 2.4 1.1 118.2%

Public and other transportation 1.2 0.6 100.0%

Reading 0.2 0.1 100.0%

Vehicle rental, leases, licenses, and other charges 1.1 0.7 57.1%

Household operations 2.4 1.6 50.0%

Owned dwellings 11.3 8.2 37.8%

Apparel and services 3.4 2.6 30.8%

Other lodging 1.3 1 30.0%

Alcoholic beverages 0.9 0.7 28.6%

Pensions and Social Security 10.9 8.5 28.2%

Personal care products and services 1.2 1 20.0%

Food away from home 5.4 4.8 12.5%

Cash contributions 3.3 3.1 6.5%

Life and other personal insurance 0.6 0.6 0.0%

Medical supplies 0.3 0.3 0.0%

Household furnishings and equipment 3.2 3.4 -5.9%

Vehicle insurance 1.9 2.2 -13.6%

Food at home 7.1 8.3 -14.5%

Entertainment 5 6.1 -18.0%

Vehicle finance charges 0.4 0.5 -20.0%

Utilities, fuels, and public services 6.8 8.6 -20.9%

Vehicle maintenance and repairs 1.5 1.9 -21.1%

Miscellaneous 1.5 1.9 -21.1%

Health insurance 5.2 6.8 -23.5%

Housekeeping supplies 1.1 1.5 -26.7%

Gasoline and motor oil 3.6 5.1 -29.4%

Medical services 1.4 2.1 -33.3%

Drugs 0.7 1.1 -36.4%

Vehicle purchases (net outlay) 6.8 11.8 -42.4%

Tobacco products and smoking supplies 0.6 1.2 -50.0%

Percent distribution of average expenditures of urban and rural households, 2015
Proposed Benefits of These 

Assignments

• Within-division tastes/spending patterns are 

assumed to be relatively homogeneous

• Between-division differences in 

tastes/spending patterns are assumed to be 

significant 

• Differences in spending patterns between 

urban and rural CUs within each division are 

known to be “significant”
Question: 

Do Divisions Provide Enough 

Observations for Multivariate 

Analysis with this many groups?
Population of Regions and Divisions

Region/Division

2017 

Region 

Population

2017 

Division 

Population

REGION I: NORTHEAST 56,470,581

Division I: New England 14,810,001

Division 2: Middle Atlantic 41,660,580

REGION 2: MIDWEST* 68,179,351

Division 3: East North Central 46,885,244

Division 4: West North Central 21,294,107

REGION 3: SOUTH 123,658,624

Division 5: South Atlantic 64,705,532

Division 6: East South Central 19,029,020

Division 7: West South Central 39,924,072

REGION 4: WEST 77,410,622

Division 8: Mountain 24,158,117

Division 9: Pacific 53,252,505
Metro Areas for Which Average Data is 

Published

Rank Metropolitan Statistical Area 2017 Pop Estimate

1 New York-Newark-Jersey City, NY-NJ-PA MSA 20,320,876

2 Los Angeles-Long Beach-Anaheim, CA MSA 13,353,907

3 Chicago-Naperville-Elgin, IL-IN-WI MSA 9,533,040

4 Dallas-Fort Worth-Arlington, TX MSA 7,399,662

5 Houston-The Woodlands-Sugar Land, TX MSA 6,892,427

6 Washington-Arlington-Alexandria, DC-VA-MD-WV MSA 6,216,589

7 Miami-Fort Lauderdale-West Palm Beach, FL MSA 6,158,824

8 Philadelphia-Camden-Wilmington, PA-NJ-DE-MD MSA 6,096,120

9 Atlanta-Sandy Springs-Roswell, GA MSA 5,884,736

10 Boston-Cambridge-Newton, MA-NH MSA 4,836,531

11 Phoenix-Mesa-Scottsdale, AZ MSA 4,737,270

12 San Francisco-Oakland-Hayward, CA MSA 4,727,357

13 Riverside-San Bernardino-Ontario, CA MSA 4,580,670

14 Detroit-Warren-Dearborn, MI MSA 4,313,002

15 Seattle-Tacoma-Bellevue, WA MSA 3,867,046

16 Minneapolis-St. Paul-Bloomington, MN-WI MSA 3,600,618

17 San Diego-Carlsbad, CA MSA 3,337,685

18 Tampa-St. Petersburg-Clearwater, FL MSA 3,091,399

20 Baltimore-Columbia-Towson, MD MSA 2,808,175

21 St. Louis, MO-IL MSA 2,807,338

25 Portland-Vancouver-Hillsboro, OR-WA MSA 2,453,168

26 Pittsburgh, PA MSA 2,333,367

33 Cleveland-Elyria, OH MSA 2,058,844

56 Urban Honolulu, HI MSA 988,650

134 Anchorage, AK MSA 400,888
Our Methodology

Step 4

Estimate Log-Log Regression of 

Spending on Income within the 

11-year PUMD dataset using 

fixed effects for the Urban/Rural 

divide and Year
Our Methodology

Step 4

This provides an estimate of 

spending by the median income 

household in urban and rural 

areas in each Census Division
Our Methodology

Note: The ACS provides 

estimates of median income in 

each census tract in the country 

by household type
Our Methodology

Step 5

Apply the regression results to 

the median income member of 

each household type in each 

Census Tract that lies within the 

respective Division
One Drawback of this Approach

Assumes that all households in 

each type have the same 

(median) income.


Alternate Step 5

Simulate the income distribution in 

each census tract using a gamma 

distribution with the given median 

and then apply the regression 

equation to each member of the 

distribution
Step 6

Sum the estimated spending across 

all household types to obtain an 

estimate of aggregate spending at 

the census tract level. This can be 

done for each category of spending 

– or for each UCC.
Result

Estimates of aggregate spending 

on each estimated expenditure 

group (or UCC) by households in 

every census tract in the U.S.
Implication

Aggregate Spending can be 

calculated for all counties, 

metros and states, as well as for 

radii around a selected point on 

a map.
www.householdspending.com
www.householdspending.com

Our website is not affiated with 

or endorsed by the BLS
www.householdspending.com

Login:

Spending@RegionalOneSource.com

Pw: workshop