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

2019 CE Survey Microdata Users’ Workshop

Sampling Methods and

Derivation of Sampling Weights

Brian T. Nix

Consumer Expenditure Survey

Statistical Methods Division

Bureau of Labor Statistics

July 18, 2019
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Overview

• History and Concepts

• Sample Selection

• Define PSUs

• Stratify and Select a Sample of PSUs

• Stratify and Select a Sample of Households

• Weighting the Households
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History of Sample Redesigns

• New sample of geographic areas selected every decade

• 1980 Census-Based Sample Design (1986–1995)

• 1990 Census-Based Sample Design (1996–2004)

• 2000 Census-Based Sample Design (2005–2014)

• 2010 Census-Based Sample Design (2015–2024)

• 2020 Census-Based Sample Design (2025–2034???)
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Concepts

 Target Population

– U.S. non-institutional civilian population

 PSU (Primary Sampling Unit)

– Geographic area used for sampling

– Cluster of contiguous counties

• (between 2 and 5 counties on average)

 CU (Consumer Unit)

≈ Household
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Sample Selection – Overview

• Geographic areas are randomly selected to 

represent the total U.S. 

• Households are randomly selected to 

represent the geographic areas

• Guiding principle:

“Randomness ensures representativeness.”
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Selection of PSUs

PSU 

class

Description CBSA/

Non-CBSA

Population Examples

Total

S

SelfRepresenting

Metropolitan

(urban)

Greater Than 

or Equal to 

2,500,000

S11A

S49D

Boston MA

Seattle WA

N

Non-SelfRepresenting

Metro- or 

Micropolitan

(urban)

Less Than 

2,500,000 Suppressed

R

Rural 

(also not SelfRepresenting)

Non-CBSA 

(rural) Suppressed
The Four Census Regions

8
The Nine Census Divisions

9
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Sample Selection:

CPI – 75 PSUs; CE – 91 PSUs

PSU 

Size

Region/Division Total

Northeast Midwest South West

01 02 03 04 05 06 07 08 09

S 1 2 2 2 5 0 2 2 7 23

N 2 4 8 4 12 6 8 4 4 52

R 1 1 2 2 2 2 2 3 1 16

Total 4 7 12 8 19 8 12 9 12 91
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Hypothetical PSU Selection
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Hypothetical PSU Selection (continued)



CBSA

2010 

Population

Probability 

of Selection

Augusta, GA-SC 564,873 0.9221

Jessup, GA 30,099 0.0491

Fitzgerald, GA 17,634 0.0288

Total 612,606 1.0000

CBSA 2010 

Population

Probability 

of Selection

Columbus, GA-AL 294,865 0.4783

Valdosta, GA 139,588 0.2264

LaGrange, GA 67,044 0.1088

Moultrie, GA 45,498 0.0738

Douglas, GA 42,356 0.0687

Thomaston, GA 27,153 0.0440

Total 616,504 1.0000


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Number of Addresses

 Local Target Sample Size

 Allocate 12,000 addresses in each survey to 

individual PSUs, proportional to each stratum’s 

population

 Minimizes CE’s nationwide variance
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Number of Addresses 

(continued)

Given the values of pi and rifor every index area i,

find the values of nithat

Minimize 

i=1

91

niri

NR −

pi

p

2

Subject 

to: 

i=1

91

ni = 12,000

ni ≥ 0, for i = 1 to 91
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Number of Addresses 

(continued)

where

 pi = population of the i-th index area;

 ri = productivity rate (eligibility rate times the response rate) of the i-th index area;

 ni = number of addresses allocated to i-th index area;

 p = i=1

41 pi

is the population of the United States;

 niri = expected number of interviewed households in the i-th index area;

 NR = i ∈USA niriis the expected number of interviewed households nationwide.
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 83% Eligibility rate

 (most of the missing 17% are unoccupied)

 60% Response rate

 50% Productivity rate (0.50 ≈ 0.83  0.60)

Calculating the Productivity Rate
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Selecting a Random Sample of Households

 Sort households from poor to rich based on 

information from Decennial Census and ACS

 Compute the sampling interval for each PSU

• Sampling interval = (# addresses in sampling frame) 

(# addresses in CE sample)

 Typical sampling intervals:

• Every 1,000th address (N and R PSUs)

• Every 5,000th address (S PSUs)
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Weighting Process
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Weighting Process

 Base Weight (~10,000)

Household + 9,999 others

 Non-interview Adjustment Factor (~1.75)

Type A: Refusal to Participate

 Calibration Adjustment Factor

Adjusts sample estimate to CPS Totals

About 1.15 for Interview Survey
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Weighting Process:

Calculating the Base Weight

(using hypothetical values)

 PSU Population 538,200

 MAF counts 224,250 housing units

 115 addresses allocated for each survey

 “Take Every” = 224,250 / 115  1,950

 Stratum population 2,800,000

 PSU Weight = 2,800,000 / 538,200  5.2025

 Base Weight = “Take Every” * PSU Weight

 1,950 * 5.2025 = 10,145
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Weighting Process:

Calculating the Final Weight

 Variable FINLWT21

 = Base Weight 

x Non-Interview Adjustment Factor 

x Calibration Adjustment Factor

 Around 20,000 for Interview Survey, 

40,000 for Diary Survey
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Conclusion

Both Sample Design and Weighting 

Work Together to Produce:

 Unbiased Estimates of U.S. Expenditures

 Subject to Allotted CE Budget
Contact Information

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Brian T. Nix

Mathematical Statistician

Statistical Methods Division

www.bls.gov/cex

202-691-6877

Nix.Brian@bls.gov