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

Balancing 

Respondents’ Confidentiality 

and Data User Needs

Aaron E. Cobet

Consumer Expenditure Surveys

Microdata Users Workshop

July 18, 2023
2 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

What is the Issue?

◼ Conflicting goals 

 Maximize data access

 Protect respondents identity
3 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Why is Confidentiality Important? 

◼ Ensure trust of respondents for 

their cooperation

◼ It’s the law 
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How Could Microdata Reveal 

Respondents’ Identity? 

Unique data points

 Names 

 Extreme income 
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How to Protect Respondents’ 

Confidentiality?

◼ Census removes 

direct identifiers, 

e.g. names

◼ BLS suppresses 

indirect identifiers, 

e.g. high income

Conceal revealing information
10 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

How to Conceal Indirect Identifiers?

◼ Topcode: Average numerical 

values above threshold

◼ Recode: Change item or CU 

characteristics 

◼ Suppress: Delete numerical value 

or delete entire record
11 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

How do we Topcode?

◼ Determine critical value

◼ Average values exceeding critical value 

◼ Replace exceeding values with topcoded values
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Topcoding Example

 -

 100

 200

 300

 400

 500

 600

0 2 4 6 8 10 12 14 16 18 20

Critical value 
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Topcoding Example

 -

 100

 200

 300

 400

 500

 600

0 2 4 6 8 10 12 14 16 18 20

Extreme values 
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Topcoding Example

 -

 100

 200

 300

 400

 500

 600

0 2 4 6 8 10 12 14 16 18 20

Topcoded values 
16 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

How to Determine Critical Values?

◼ Critical value is any value by a consumer 

unit above the specified percentiles: 

Expenditures: 99.5 %

Income: 97.0 % 
20 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

How do we Recode?

◼ Find revealing metadata

◼ Determine method: 

 Generalize information

 Change information

◼ Replace original metadata with recoded 

metadata
21 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Re-coding: Generalize Information

From Toyota Corolla 1999 

To Toyota 1990s 
22 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Re-coding: Change information

◼ Change states to comparable states

Delaware

New Jersey

Hi
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Suppression

◼ Erase aspect of the record

Example: State suppression

Example: Boat purchase 

◼ Exclude entire record

Example: Airplane purchase
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Reverse Engineering

5 = 3 + X 

What’s X?
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How to Prevent Reverse Engineering?

Prevent users to deduce protected 

information within files and across files

1. Find protected values

2. Protect them in all locations 

3. Protect related values 
27 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Reverse Engineering: Within File

◼ Income = Wages + taxes 

◼ 1000 = 800 + 200

◼ 1000 = 750 + 200

◼ 950 = 750 + 200 

◼ Critical value: 700 

◼ Topcode value: 750

Wages 

exceeds

the critical 

value
28 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Reverse Engineering: Within File

◼ Income = Wages + taxes 

◼ 1000 = 800 + 200

◼ 1000 = 750 + 200

◼ 950 = 750 + 200 

◼ Critical value: 700 

◼ Topcoded value: 750

Wages 

match 

the 

topcoded

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

Reverse Engineering: Within File

◼ Income = Wages + taxes 

◼ 1000 = 800 + 200

◼ 1000 = 750 + 200

◼ 950 = 750 + 200 

◼ Critical value: 700 

◼ Topcode value: 750

Wages 

and taxes 

match 

the 

income
30 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Reverse Engineering: Across Files

◼ Income: Topcoded income in FMLI

Topcode associated UCCs in ITBI 

◼ Expenditure: Topcoded expenditures 

in EXPN and FMLI

Topcode associated UCCs in MTBI
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How Do We Document?

Flag values

T: Topcoded value 

D: Valid value, unadjusted
32 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Impact of topcoding

◼ CE topcodes few observations

◼ Most affected data slices:

Geographic data non-self representing cities

Income for high earners 
33 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Impact of suppression of 

geographic variables, Percent

◼ 60 % of 

PSU 

suppressed

◼ 4 % of 

regions 

suppressed

Source: FMLI and FMLD files for 2018. 

0

10

20

30

40

50

60

70

PSU State Division Region
34 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Need More Data?

◼ Visiting researcher program

 Access to pre-topcoded CE microdata

 Requires application process

 www.bls.gov/rda/home.htm
35 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

Additional Information

◼ Protection of respondent confidentiality 

(www.bls.gov/cex/pumd_disclosure.htm)

◼ PUMD Getting Started Guide 

(www.bls.gov/cex/pumd-getting-started-guide.htm)

◼ Title 13 

(www.census.gov/history/www/reference/privacy_c

onfidentiality/title_13_us_code.html)
36 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

Aaron Cobet

Senior Economist, Consumer Expenditure Surveys

(202)-691-5018

Cobet.Aaron@bls.gov

Thank you!