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

BLS Distributional Statistics

with focus on “Distributions of PCE and CE Consumption”

Thesia I. Garner

Chief Researcher, Division of Price and Index Number Research (DPINR)

FESAC Meeting, June 10, 2022 

Session 2: Distributional Measures at Census, BEA, and BLS 

12:00-1:55 p.m.; presentation #3

version prepared for release June 2, 2022
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Topic 1

Distributional Statistics Produced in Regular Series

Topic 2

Distributional Statistics Research
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Topic 1

Distributional Statistics Produced in Regular Series
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Regular Series

1. Employment and Unemployment (OEUS) statistics

2. Compensation and Working Conditions (OCWC) statistics

3. Productivity (OPT) statistics

4. American Time Use Survey (ATUS) statistics

5. Consumer Price Indexes (CPI) statistics

6. Consumer Expenditure Survey (CE) statistics
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Employment Related Distributional Statistics

 National Compensation Survey

 Compensation percentile estimates – employer costs for 

wages and benefits by wage percentile

 https://www.bls.gov/ect/compensation-percentileestimates.htm

 Employee benefits –averages for access and participation by 

wage category

 https://www.bls.gov/ncs/ebs/

 Occupation Injuries and Illnesses

 Nonfatal cases requiring days away from work

 Workplace injuries available by age, race, gender

 https://www.bls.gov/iif/

 Occupational Requirements Survey

 By occupation and occupation groups

 Percentiles of length of workday sitting or standing, 

maximum weight lifted or carried, time associated with 

requirements (education, training, experience)

 https://www.bls.gov/ors/

Employment and Unemployment Occupation and Wages

 Employment 

 Provide statistics such as

– Average earnings and hours by industry of employment

– Average wages by occupational employment 

 https://stats.bls.gov/bls/employment.htm

 Unemployment

 Labor market status by demographic characteristics 

https://stats.bls.gov/bls/unemployment.htm

 Special Reports

– Working poor

– Characteristics of minimum wage workers

– Women in the labor force: a data book

– Labor force characteristics by race and ethnicity

– Highlights of women’s earnings
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Other Distributional Statistics

 Dispersion Statistics on Labor Productivity– joint 

with Census

 Dispersion of labor and total factor productivity for people 

across establishments by year and 4-digit industry

 Standard deviation, interquartile range, 90-10 range 

 https://stats.bls.gov/bls/productivity.htm

Productivity American Time Use

 Produces nationally representative estimates of 

how, where, and when Americans spend their time

 Provides data on full range of nonmarket activities 

from childcare to volunteering

 Annual (and some quarterly) time use averages and 

percentage estimates

 Day of week

 Presence and age of household children

 Respondent age, sex, educational attainment, race and 

ethnicity, employment status, marital status, occupation and 

industry, job holding status, class of worker, earnings

 https://stats.bls.gov/tus/
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Prices and Living Conditions Distributional Statistics

 Indexes

 CPI-U: Consumers living in urban areas

 R-CPI-E: Based on CUs with age of reference person or 

spouse, living in urban areas only

 CPI-W: Wage earners living in urban areas only

 C-CPI-U: U.S. city average only

 All but C-CPI-U published by

 Census region

 Census division

 Select self-representing cities (metro areas)

 https://stats.bls.gov/cpi/

 Diary and Interview integrated statistics

 Means published by

 Income before taxes, quintiles of income before taxes, 

deciles of income before taxes

 Region of residence, population size of area, type of area of 

CU, State (selected states), MSA

 Composition of CU, household size, number of earners, 

housing tenure, 

 Characteristics of reference person: education level, age of 

reference person. generation of reference person, age range 

of reference person, Hispanic origin of reference person, 

occupation of reference person, race of reference person

 https://stats.bls.gov/cex/

Consumer Price Index Consumer Expenditure Surveys
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Topic 2

Distributional Statistics Research
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Distribution Statistics: Research Examples

1.Employment/work/time use

a. Growing wage inequality in the U.S. (2020 & forthcoming Journal Labor Economics by

Handwerker), wage inequality and growth during the 2000s (forthcoming MLR by Dey, 

Handwerker, Piccone, & Voorheis)

b. Distribution of overall compensation (update of Pierce 2010)

c. Dispersion of labor productivity by establishment task/skill intensity

d. Contract with outside vendor to impute time use to CE Survey data for consumption 

2.Prices and expenditures/consumption

a. Demographic subgroup CPIs

b. Consumption expenditures & consumption

1. Distribution of Personal Consumption Expenditures (PCE)

2. BLS Comprehensive Consumption Initiative and distribution of consumption
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Follow OECD 2013 Framework for Underlying Concepts

 Consumption expenditure - value of consumption goods and services used or paid for 

by a household to directly meet its needs

 Purchase of select goods and services in the market

 In-kind transfers from employers (e.g., health insurance)

 Household’s own production of goods and services consumed

– Owner-occupied housing

– Owned vehicles

– Durables

– Other (e.g., child/elder care, meals)

 In-kind transfers from other households and from businesses

 Actual final consumption - sum of 

 Consumption expenditure 

 Public in-kind transfers

Source: OECD (2013), OECD Framework for Statistics on the Distribution of Household Income, Consumption and Wealth, OECD Publishing, Paris, Chapter 5. 

Household Consumption, p.104. 
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Framework Comparison

Item

Consumption Exp. or 

Final Consumption 

(OECD /PCE) 

Proposed BLS 

Consumption

Planned

Research

Acquisition cost of services and non-durable goods Yes Yes n/a

Financial services Yes Yes n/a

Service flow from housing Yes Yes n/a

Service flow from vehicles * Yes/No Yes Yes

Service flow from other durable goods * Yes/No Yes No

In-kind receipt of goods and services ** Yes/Partial Yes Yes

Other home production * Yes/No Yes Yes

Interhousehold transfers (including gifts received) * Yes/No Yes Yes

Health*** Yes Partial Yes

Education Yes ?? Not yet

* Yes/no: in OECD, not PCE

** PCE rents reflect what subsidized (e.g., rent-control, section 8, public housing) renter paid, not flow of services

*** Restricted to health insurance for BLS consumption
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Framework Comparison

** No/Yes: Not OECD but in PCE

Item

Consumption Exp 

or Final Consump. 

(OECD /PCE) 

Proposed BLS 

Consumption

Planned 

Research

Gifts of goods & services given outside household Yes No No

Life insurance/other personal insurance Yes No No

Purchase price of vehicles ** No/Yes No No

Purchase price of other durables ** No/Yes No No
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Topic 2.b.1

Distribution of PCE over People Living in “Households”

Researchers: S. Curtin, T. Garner, B. Martin, and B. Matsumoto
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Overview of Research

 Why produce distributional PCE accounts?

 Large demand for household distributional information in line with national accounts totals

 OECD and Eurostat launched an expert group to develop distributional results on income, consumption 

and savings in line with national accounts aggregates

 Developed methodology to compile distributional results in line with national accounts on the basis of 

available micro data sources

 This project

 Problem: PCE available only at for total population; no household characteristics available

 Potential solution: assign PCE aggregates to consumer units in the CE such that distributional analysis 

possible

 Potential drawback: assumptions made regarding scaling up unlikely to reflect reality

 Work being done in coordination with BEA

 Results by percentiles and for demographic groups (only select results presented today)
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Method to Produce PCE-defined Consumption Expenditures

 Start with CE

 Use Interview as base (represents ~ 95% of total expenditures)

 Apply statistical matching to impute the remaining 5% from the Diary

 To represent 2019 annual estimates, use Interviews with reference period November 2018 –

February 2020

 Organize CE to match PCE category definitions

 Add what not included in CE for health care using administrative data

 Center for Medicare and Medicaid Services (CMS) National Health Expenditure (NHE) 

 Medical Expenditure Panel Survey (MEPS-IC) from the Agency for Healthcare Research and Quality

 Scale up CE to PCE major product aggregates, e.g., 

 2019 PCE for Healthcare = $2,450,839 million

 CU “X” had 0.000005% of total PCE-defined CE healthcare spending 

 CU “X” assigned 0.000005%*$2,450,839 million (PCE healthcare total $) as CU “X’s” expenditure
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Most Health Care Spending Not in CE but Can Be Added at 

the Consumer Level

Preliminary Estimates 2019

CE to PCE Ratios

PCE Category

Diary imputed to 

Interview before 

adjustments

+ Adjustment to split CE OOP 

health insurance premium 

into PCE categories

+ With imputations for 

benefits before scaling up

Pharmaceuticals and other 

medical goods 0.16 0.27 0.68

Health care services 0.05 0.20 0.80

Health insurance premium 

(net for split) 1.85 0.19 0.79

NOTE: ranking of eq. PCE expenditures after scaling up 
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CE/PCE Ratios After All Adjustments to CU Expenditures 

but before “Scaling up” to PCE Totals

Preliminary Estimates 2019

CE/PCE before scaling up CE/PCE published CE/PCE published 

“comparables”

PCE less final Cons. Exp. of NPISHs 0.70 0.60 0.73

Durable goods 0.56 0.59 0.65

Nondurable goods 0.63 0.52 0.53

Services 0.75 0.63 0.87

Source for published CE/PCE: https://stats.bls.gov/cex/cecomparison/pce_profile.htm
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Method to Produce Distributions

 Apply square root of consumer unit size equivalence scale

 Assign equivalized CE-PCE expenditures to each person within CU

 Rank people by equivalized values (population weighted) 

 Shares and rank percentiles based on equivalized values (population weighed)
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0-20%

9%

20-40%

14%

40-60%

17%

60-80%

23%

80-99%

33%

Top 1%...

Shares of “Equivalized PCE” by Distribution of Population 

Preliminary Estimates 2019

For example...

33% of Equivalized PCE accounted for by 

the population within 80-99th

equivalized CE-PCE expenditure 

percentile range

NOTE: Shares and rank percentiles based on CExp

scaled up to PCE, referred to a “Equivalized PCE”
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Composition of “Equivalized PCE” by Quintile

Preliminary Estimates 2019 

For example...

23.5% of PCE

accounted for by 

households in the 

bottom quintile, is 

for Health Care

4.2% 5.7% 7.8% 10.7% 15.5%

28.8% 26.0% 23.9% 21.8% 16.2%

19.8% 18.5% 18.5% 18.9% 19.3%

23.5% 23.7% 20.6% 17.6%

12.4%

23.6% 26.1% 29.2% 31.0% 36.6%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0-20% 20-40% 40-60% 60-80% 80-100%

Distribution of Eq. CE-PCE within Decile

Quintile of Population based on Rank of Eq. PCE

Other Services

Health Care Services

Housing (including Utilities) Services

Non-Durable Goods

Durable Goods

NOTE: ranking of eq. PCE expenditures after scaling up 
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Equivalized PCE: Aggregate Inequality Indices & Lorenz

Curve 

Preliminary Estimates 2019

Aggregate Inequality Indices

Gini 0.28

Thiel 0.14

Mean log dev. 0.13

90/10 ratio 3.40

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Cum .Share of Equivalized Expenditure

Decile of Population Based on Rank of Equivalized CE-PCE

Perfect equality

Total
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Equivalized PCE: Concentration Curves by PCE Product 

Preliminary Estimates 2019

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Cum .Share of Equivalized Expenditure

Decile of Population Based on Rank of Equivalized CE-PCE

Perfect equality

Health Services

Nondurables

Housing (including Utilities)

Services

Other Services

Durables
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Topic 2.b.2

BLS Initiative to Produce a Comprehensive Consumption 

Measure and Distributional Statistics

Researchers: S. Curtin, T. Garner, B. Matsumoto, and J. Schild 
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BLS Initiative Focuses on Consumption as a Well-being 

Outcome as A Function of Resources and Processes

For other outcomes: https://www.oecdbetterlifeindex.org/

Processes

Skills (e.g., education, 

financial management, 

efficiency in converting 

inputs to outcomes)

Degree of resource 

allocation (power)

Circumstances (CU 

composition, disability)

Preferences, subjective 

assessments of wellbeing

Available Resources

Income, in-kind 

transfers

Asset (financial)

Asset (nonfinancial)

Debt (access and 

use)

Time

Outcomes (e.g.,)

1. Consumption

2. Health status

3. Material deprivation

4. Life satisfaction

5. Happiness
25 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

Overview of Research

 Why produce a comprehensive measure of consumption?

 Large demand for measure that reflects how people live, not just how they could live

 Period of COVID-19 showed us that more goods and services are produced by household members 

consumption of these missing in current measures of economic well-being at the household level

 Supports work and recommendations 

– OECD Framework of Final Consumption (2013)

– Interagency Technical Working Group (ITWG) on Evaluating Alternative Measures of Poverty (2021)

– CNSTAT Panel An Integrated System of U.S. Household Income, Wealth, and Consumption Data and Statistics 

to Inform Policy and Research (present)

 This project

 Problem: Consumer Expenditure Survey is not designed to measure consumption

 Potential solution: identify goods and services for which consumption values missing; impute values

 Potential drawback: assumptions regarding imputations influenced by use (e.g., treatment of health)

 With support of academics (e.g., Consumption Symposium 2021), and others in federal agencies

 Results by percentiles and for demographic groups (only select results presented today)
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Method to Produce CE Consumption Measure

 Start with CE

 Use Interview as base (represents ~ 95% of total expenditures)

 To represent 2019 quarterly estimates, use Interviews with reference period January 2019 –

February 2020

 Identify categories of consumer expenditures to exclude

 Add what not included in consumer expenditures
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Comprehensive Measure of Consumption

Item Current Planned

Research

Acquisition cost of services and non-durable goods Yes n/a

Service flow from housing Yes n/a

Service flow from cars and trucks Yes Yes

In-kind receipt of goods and services (currently only: NSLP, LIHEAP, WIC, rental 

assistance) Yes Yes

Gifts of goods & services given outside household* Yes Yes

Other home production ** No Yes

Interhousehold transfers (including gifts received) No Yes

Health*** No Yes

Education No Not yet

* Future: subtract for within household consumption

** Contract with outside vendor to estimate

***Restricted to health insurance
28 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

Construction of Comparison Measures

Measure Base Not Included Addition

Consumption 

Expenditures

CE Publication Definition 

of Total Expenditures 

(e.g., mortgage interest 

payments, net purchase 

price of vehicles)

Cash contributions; allocations to and purchases 

of life insurance, endowments, annuities, and 

other personal insurance; retirement, pensions, 

and Social Security

After Tax and 

Transfer Income

CE Defined After Tax 

Income

LIHEAP, NSLP, WIC, 

rental assistance inkind transfers
29 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

Method to Produce Distributions

 Measures

 Consumption quarterly

 Consumption expenditures quarterly

 After tax and transfer (TT) income divided by 4

 For each measure

 Apply square root of consumer unit size equivalence scale

 Assign equivalized value to each person within CU

 Rank people by equivalized values (population weighted) 

 Shares and rank percentiles based on equivalized values (population weighed)
30 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

Shares of Equivalized Consumption & Equivalized After TT 

Income by Quintile

Preliminary Estimates 2019

NOTE: Quintiles based on rank of population by equivalized consumption or after tax and transfer income

0-20%

9%

20-40%

13%

40-60%

17%

60-80%

23%

80-100%

38%

Consumption 0-20%

5%

20-40%

11%

40-60%

16%

60-80%

23%

80-100%

45%

After TT Income
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Housing (including Utilities) as Share of Total 

Consumption by Quintile

Preliminary Estimates 2019

61.1% 62.3% 61.3% 61.1% 59.0%

38.9% 37.7% 38.7% 38.9% 41.0%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0-20% 20-40% 40-60% 60-80% 80-100%

Ranked by Consumption

Housing

Other

57.6% 60.1% 61.5% 62.4% 59.9%

42.4% 39.9% 38.5% 37.6% 40.1%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0-20% 20-40% 40-60% 60-80% 80-100%

Ranked by After TT Income
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Aggregate Inequality Indices & Lorenz Curves of 

Consumption, Consumption Spending, and After TT Income 

Preliminary Estimates 2019

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Cum Shares of Eq. C, CExp, or Y

Decile of Population based on Separate Rank of Eq. C, CExp, Y

Perfect Equality

Consumption

Consumption Exp.

After TT Income

Aggregate Inequality Statistics

Consumption

Gini 0.29

Thiel 0.14

Mean log deviation 0.14

90/10 ratio 3.57

Consumption Spending

Gini 0.37

Thiel 0.25

Mean log deviation 0.23

90/10 ratio 5.22

After Tax and Transfer Income

Gini 0.39

Thiel 0.33

Mean log deviation 0.31

90/10 ratio 5.82
33 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

Summary of Research Activities

 Distributional analyses regarding employment, unemployment, wages, 

compensation, productivity, and time use

 Distributional PCE accounts and inequality

 Refinements to CE allocations and adjustments

 Update to more recent time periods

 Comprehensive measure of consumption focused on inequality and poverty

 Move closer to OECD definitions of “consumption expenditures” and “final consumption”

 Add health insurance

 Add home production

 More consideration for including education (consumption for some, investment for others)

 Joint distribution of consumption, income, and wealth

 Progress posted on https://www.bls.gov/cex/consumption-home.htm
34 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

Contact

Thesia I. Garner

Chief Researcher, Division of Price and Index Number Research (DPINR)

Bureau of Labor Statistics

Washington, DC 20212

Garner.Thesia@BLS.gov