1 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

Estimating State Expenditures 

for New Jersey, Florida, and 

California

Susan L. King

Mathematical Statistician

OPLC/SMD

Survey Methods Symposium and CE Microdata 

Users’ Workshop 

July 20, 2017
2 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Objective

 CE Survey designed to produce unbiased 

national and regional expenditure estimates

 Modify the national base weight equation 

using U.S. Census tracts, allowing CE to 

calculate state weights for selected states

 Provide an extra set of weights on CE’s Public 

Use Microdata to allow users to make state 

estimates for their research projects

 Research in progress
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Simulated Design 2010 CE PSUs
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Census Tracts

 Small, relatively permanent, contiguous areas 

within a County or equivalent entity

 Locally updated before decennial census

 Optimum size 4,000 people, but can range 

from 1,200 to 8,000 people

 Vary in geographical size

 Maintained from census to census
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Stratification

 Census tracts in a state are assigned to one of 

five strata

 Each stratum has approximately equal, 

population--constrained clustering algorithm

median household property value

median household income

 Each sampled household has a U.S. Census 

Tract and is assigned to a stratification group
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Base Weights State Estimates

State Base Weight = 1

Probability of Selection x

(Within PSU Sampling Interval)

Where

Probability of Selection = 

Sum of CE′s Tract Populations in a Stratum

Sum of the State Tract Populations in a Stratum
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Other Weight Adjustments

 Control Factor Weight

Adjust for multiple housing units where one 

housing unit was expected

 Non-Interview Adjustment Weight

Cell collapsing procedure that accounts for refusal 

to participate

 Calibration Adjustment Weight

Adjusts weights to known population counts
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Calibration Constraints

 Total number of consumer units in a state

 Total number of homeowner consumer units 

 Total state population by age

Age 14-24

Age 25-34

Age 35-44

Age 45-54

Age 55-64

Age 65-74

Age 75 +
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Variance State Estimates

 Jackknife

U.S. Census Tracts are unique within a county, CTY_TRACT, i, 

and nnh is the number of CTY_TRACTs in stratum h

Calculate the full sample mean for expenditures, θθ�

Calculate the replicate mean for expenditures, θθ� hii

– Set the weight of CTY_TRACT i in stratum h = 0

– Re-weight the other CTY_TRACTs in stratum h, by nnh−1

nnh

– Weights in other stratum remain at their original weight

VV θθ = ∑h=1

5 nnh

nnh−1 ∑ii=1

nnh θθ� hii − θθ� 2
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New Jersey

 2,010 U.S. Census Tracts

 1,397 CUs (2013 Interview & Diary + 

2014 Quarter 1 Interview)

 557 tracts with CUs
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New Jersey
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New Jersey Design 2000
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New Jersey Design 2010
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Results for New Jersey

CE Estimated State Expenditures CE’s MSA Tables

Design 2000 Design 2010

New 

York Philadelphia

Expenditure Category Mean ($) SE ($) Mean ($) SE ($) Mean($) Mean ($)

Average annual 

expenditures 65,165 2,408 65,277 2,662 63,193 57,907

Food 7,842 524 7,735 556 7,329 7,263

Housing 25,064 850 25,074 827 25,046 20,475

Transportation 9,177 790 9,118 906 8,442 9,500

Healthcare 3,857 228 3,945 260 3,937 4,386

Personal insurance 

and pensions 6,950 469 7,030 487 6,993 5,800
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Comparison to ACS

 ACS Public Use Microdata Sample (ACS-PUMS)

Sample in every state

Ask questions on housing, providing comparisons 

to CE

– CE asks more detailed questions 

CE calibrates to Current Population Survey (CPS)

ACS–PUMS calibrates to Census Population 

Estimates (PEP)
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Expenditure Comparison Between 

CE and ACS – New Jersey

National New Jersey

Expenditure CE ($) ACS ($) CE/ACS CE ($) ACS ($) CE/ACS

Electricity and

Natural Gas 1,814.16 2,117.00 0.86 2,308.24 2,667.57 0.87

Rented 

Dwellings 3,323.61 4,220.06 0.79 4,507.20 5,167.57 0.87
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Florida

 4,245 U.S. Census Tracts

 2,858 CUs (2013 Interview & Diary + 

2014 Quarter 1 Interview)

 716 tracts with CUs
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Florida
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Simulated Florida Design 2010
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Results for Florida

CE Estimated State Expenditures Miami MSA

Expenditure Category Mean ($) SE ($) Mean ($)

Average annual 

expenditures 45,944 1,787 43,066

Food 6,142 370 5,610

Housing 16,719 591 16,981

Transportation 8,304 629 7,243

Healthcare 2,976 177 2,433

Personal insurance and

pensions 4,895 427 4,823
21 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Expenditure Comparison Between 

CE and ACS – Florida

National Florida

Expenditure CE ($) ACS ($) CE/ACS CE ($) ACS ($) CE/ACS

Electricity and

Natural Gas 1,814.16 2,117.00 0.86 1,671.94 1,905.32 0.88

Rented 

Dwellings 3,323.61 4,220.06 0.79 3,605.01 4,229.70 0.85
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California

 8,057 U.S. Census Tracts

 4,912 CUs (2013 Interview & Diary + 

2014 Quarter 1 Interview)

 1,472 tracts with CUs
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California
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Simulated California Design 2010
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Results for California

CE Estimated 

State 

Expenditures CE’s MSA Tables

Los Angeles San Francisco San Diego

Expenditure Category Mean ($) SE ($) Mean ($) Mean ($) Mean ($)

Average annual 

expenditures 58,583 1,358 55,546 68,765 63,189

Food 7,441 258 7,278 8,152 6,936

Housing 22,574 519 21,501 25,663 23,774

Transportation 8,566 372 8,315 9,404 10,319

Healthcare 3,352 149 3,178 4,459 4,395

Personal insurance 

and pensions 6,457 250 5,926 8,438 7,162
26 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Expenditure Comparison Between 

CE and ACS – California

National California

Expenditure CE ($) ACS ($) CE/ACS CE ($) ACS ($) CE/ACS

Electricity and

Natural Gas 1,814.16 2,117.00 0.86 1,449.44 1,723.91 0.84

Rented 

Dwellings 3,323.61 4,220.06 0.79 6,315.01 7,148.09 0.88
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Future Products

 New Jersey 2016 will be on CE PUMD

 Separate database -- available late fall

 5 quarters Interview and 4 quarters Diary Survey

 Variables: NEWID, STATE, QINTRVYR, QINTRVMO,

STATE_WGT

 Information on variance calculation supplied 

later

 Merge state weight data by STATE and NEWID

with CE PUMD and proceed as usual
28 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Conclusion

 Range of conditions tested

Census Tracts and CUs

Self-representing and non-self-representing PSUs

 Expenditure estimates are similar for

Both Designs in NJ

MSA tables and ACS comparisons

 Promising approach for calculating state 

weights producing consistent expenditure 

estimates with varying types of PSUs
Contact Information

29 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

Susan L. King

Mathematical Statistician

OPLC/SMD

202-691-6895

king.susan@bls.gov