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

COMPARING ECONOMIC STATUS OF YOUNG 

ADULTS IN DIFFERENT GENERATIONS

WHEN I WAS YOUR AGE II:

Geoffrey Paulin, Ph.D.

Senior Economist

Division of Consumer Expenditure Surveys

CNA Insurance

August 8, 2023

Virtual Event
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“It is almost axiomatic that each generation of Americans believes that the next 

generation will be better off, or at least that this has been so historically....

[However, for] a new generation now coming of age ... the expectations ... are 

contradictory: some argue that the group is, or will likely be, better off than its 

predecessors, while others argue that it is, or will likely be, worse off.”

Thus wrote a sage, about Millennials.

(Source: “Fun facts about Millennials: comparing 

expenditure patterns from the latest through the 

Greatest generation.” Paulin, Monthly Labor 

Review, March 2018 

[https://www.bls.gov/opub/mlr/2018/article/funfacts-about-millennials.htm])
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This work analyzes data from the Consumer Expenditure Surveys (CE) to see 

how Millennials in young adulthood (25 to 34 years old in 2019) compare to 

their predecessors at the same age. These are:

◼ Generation Xers (2000)

◼ Baby Boomers (1984)
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Questions:

◼ Why these years?

◼ Who was better off when?

◼ And what are the Consumer Expenditure Surveys?
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Let’s tackle the last one first.
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Introduction To

The Consumer Expenditure Survey (CE):

Mission, Survey Methods, and Data Provided for Public Use
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The Consumer Expenditure Surveys 

(CE):

◼ Comprise the most detailed source of expenditures collected 

directly from consumers by the Federal government.

◼ Include information on demographics and income, as well as 

expenditures.

◼ Results are published annually in various formats, including 

tables and microdata files.
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The CE is used to obtain the “market basket” 

of goods and services needed to estimate 

the Consumer Price Index (CPI).
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Data in the survey are collected 

from “consumer units...”

...which are categorized in publication by 

characteristics of the “reference person.”
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A Consumer Unit is:

A single person, or group of persons who live 

together and who share responsibilities for 

most major expenditures. 
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The “Reference Person” is the first person 

named...

...when the respondent is asked, “Who is responsible for 

owning or renting this home?”

Reference

Person

I and my 

husband

Reference

Person

My 

husband 

and I.
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There are actually two components to the 

CE ....

The Interview survey and the Diary survey.
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The Interview Survey is...

◼Designed to collect detailed information on “bigticket” and recurring expenditures, and global 

estimates on others (such as food at home).

◼Collected every three months for four* 

consecutive quarters.

◼A rotating-panel survey.

◼Comprises more than 5,000 “consumer units” 

interviewed each quarter.

*The bounding interview was discontinued in February 2015, yielding a total of four, rather than five, consecutive

 quarterly interviews..
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The Diary survey is designed to capture “small-ticket” and frequently 

purchased items for which expenditures would be difficult to recall 

over a three month period. 

So tell me, by gum.

In the last three months did you

buy gum? ?
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Additional Facts about the

Diary Survey: 

◼ The Diary survey is conducted 

independently from the 

Interview survey.

◼ One diary is placed with 

participating families (“CUs”) 

each week for two consecutive 

weeks.

◼ Approximately 12,000 diaries 

are placed with families each 

year.
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Results are integrated before publication 

of the data in tables.

+ =
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Table formats:

◼ Annual:

January to December: 1984 onward.

July to June: 2011-12 onward, starting March 27, 2013 

◼ Two-year Tables (January year1-December year2):

Cross-tabulated data (e.g., age by income): 1986-87 

onward

Selected MSA tables: 1986-87 onward

Other (e.g., population size): Various start dates
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Experimental research tables:

◼ Special tabulations in development for official 

publication

◼ Subject to change (as “experimental” implies)

◼ Current examples include:

Detailed, prepublished data for all consumer units, 

previously only available on request

High income groups, including $150,000 to $199,999 and 

$200,000 and more

Generational groups (“Millennials,” “Generation X,” etc.)
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Microdata formats:

◼ Online, free download:

Interview: 1980-81; 1984-1989 (FMLI only); 1990 onward

Diary: 1980-81, and 1990 onward

◼Paradata:

Data on Interview Survey collection process

Available 2009 onward
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Why do generations “matter?”
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Many reasons:

◼ As noted in the opening, “everyone” wants their children (the 

next generation) to be better off than “they” were growing 

up.

◼ Events happening personally or to society at large can shape a 

person’s outlook or activities, especially those taking place 

early in life.

◼ The current generation’s attitudes and behaviors can affect 

later, and even past (but still living) generations (voting 

patterns, economic policy, social or cultural norms, etc.)
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Of course, some things never change....

Ha! Ya think YOU got 

it bad? Well, things 

were a lot WORSE 

back in MY day, ya 

young whippersnapper!

Josephus T. Blough,

Perennial Portrayer 

of Passé Progenitors 

of Present-Day 

Persons.
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Returning to our questions:

◼ Why these years?

◼ And why start with 1984? Does it have to do 

with that novel, by George? Or... well....
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No. It’s something else.

1984 is the first year for which 

continuing annual CE data are 

available in a consistent format.
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O.k., so 1984 starts the current data series, but why 

2019 and 2000? What gives?

◼ True, 2021 data are now available, and 2022 are coming soon.

But the onset of the COVID-19 pandemic in March 2020 confounds 

analysis. If young adults are worse off in 2021 or 2022 than their 

predecessors, how much is long-term trend, and how much is a 

COVID-19 effect?

◼ Why 2000 for the middle, when it is 19 years before 2019, but 

only 16 years after 1984?

Yes, it would be more logical to use 2001 (18 years before 2019) and 

1984 (17 years before 2001), or 2002 (17 years before 2019) and 

1984 (18 years before 2002)

BUT:
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Consider 2001.

◼ What everyone remembers:

September 11 (and rightly so).

◼ What everyone forgets:

Tax cuts.

Recession.

Start of the housing bubble.

◼ With either 2001 or 2002 as the “midpoint year,” these 

“outside” effects, like the pandemic, are either starting or 

lingering, confounding comparisons to other periods.

◼ The “Millennial” year of 2000 is most similar to 1984 and 2019 

in terms of the business cycle.
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Looking back:

Question Two was “Who was better off 

when?”
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Which raises its own question: “How do we 

know?”
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Perhaps you know the old joke:

Which weighs more—a pound of gold or a 

pound of feathers?
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Note the measure here is weight, which on 

Earth, is the same as mass. But what if we 

measure by:

◼ Volume? A pound of feathers takes up more space.

◼ Density (Mass/Volume)? Gold is more dense.

◼ Resale Value? Again, Gold is worth a lot more, ounce per 

ounce.
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In other words:

Measurement matters.
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Here, our main measure is Engel’s Proposition.

I SAID “ENGEL’S PROPOSITION,”

NOT “ANGLES, PREPOSITION!”

Of
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Syllogistic Reasoning:

◼ Engel’s Finding (1857): The larger the income, 

the smaller the share allocated to food.

◼ Axiom: The smaller the share allocated to 

food, the more “left over” for other spending.

◼ Conclusion: Smaller food shares indicate 

higher social welfare/economic status.
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Note that “Food” has two 

components:

◼ Food at home 

Food purchased at grocery stores and similar 

outlets

“Necessity” component

◼ Food away from home

Food purchased from restaurants and similar 

establishments

“Luxury” component
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Some data

And now, let’s examine some data.
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Let’s start with demographics.
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The percentage of consumer units (CUs) with reference person 

age 25-34 declines over time, but more slowly from 2000 (17.3) 

to 2019 (16.2) than from 1984 (22.2) to 2000. 
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This is consistent with lower birthrates observed after 

the so-called “baby boom” following World War II for 

which the eponymous generation is named. 
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CU composition has changed, too.

Source: Table in unpublished work by author, “When I was your age...,” produced using microdata.

Table 1: Composition of Consumer Units with Reference Persons Aged 25-34 (Percent Distribution by 

Year)

Family type 1984 1999 2015

Single person 25.3 23.4 24.6

Two or more persons:

Married couples 58.2 51.3 43.0

Married couples only 13.9 11.0 12.0

Married couples with all children under 18 41.7 36.1 28.6

Other married couples, incl. with children 18 or older 2.7 4.2 2.4

Single parents 8.6 11.6 10.7

Single father 0.5 0.6 0.8

Single mother 8.1 11.0 9.9

Other, including unmarried partners 7.9 13.7 21.7
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As has race and ethnicity.

Sources: Published tables (Black); Table in unpublished work by author, produced using microdata.

REASON: Hispanic ethnicity was not published in tables until 2003.

Note: Hispanics can be of any race, so adding all race/ethnicity categories will yield more than 100 percent.

Categories for White and other races/Not Hispanic or Latino are omitted from table.

Table 2: Race and Ethnicity of Reference Persons Aged 25-34, Percent Distribution by Year

Race and Ethnicity of Reference Person 1984 1999 2015

Black 10 15 15

Hispanic or Latino 6 14 17
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Educational attainment has risen steadily, with 

1994 looking like a “pivot point.”

0%

10%

20%

30%

40%

50%

60%

70%

80%

1984 1989 1994 1999 2004 2009 2014 2019

Educational Attainment for CUs with Reference Person 25-34

High School or Less At Least Some College
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Considering only the years of interest, 

educational attainment looks like this:

43%

38%

27%

57%

62%

73%

0%

10%

20%

30%

40%

50%

60%

70%

80%

1984 2000 2019

Educational Attainment by Selected Years, CUs with Reference Person 25-34

High School or Less At Least Some College

The proportion of reference persons who have at least attended college rises from 4 in 7, to 5 in 8, to 3 in 4!
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Similarly, one can examine 

“snapshots” of housing tenure...

43%

39%

33%

5%

7% 7%

52%

54%

59%

0%

10%

20%

30%

40%

50%

60%

70%

1984 2000 2019

Housing Tenure for Reference Persons 25-34, Selected years

Homeowners with Mortgage Homeowners, without Mortgage Renters
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...But examining trends “develops” into a 

“bigger picture.”

0%

10%

20%

30%

40%

50%

60%

70%

1984 1989 1994 1999 2004 2009 2014 2019

Housing Tenure Rates, Reference Persons 25-24

Homeowners with Mortgage Homeowners, without Mortgage Renters

Note that homeownership with mortgage rises substantially in the “housing 

bubble” period (2001-2008), and falls steadily thereafter.
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Educational attainment and housing tenure stand in 

contrast to the other characteristics just described:

◼ The first are purely existential—there is no 

“choice” to them, they just “are.”

◼ However, college education and 

homeownership involve choice, and are 

generally considered to be “good” things.

◼ But there is something more to consider:
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If student loans/“exotic” mortgages are increasingly common to finance everincreasing tuition rates/home purchases, are the Millennials (and their successors) 

“better off” with more education and/or homeownership?
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Now, let’s talk about money....
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When discussing “economic status” and 

“money,” the first thing that comes to 

mind is likely income...
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...But using historical income data in CE 

can involve some “tricky” maneuvers....
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Prior to 2004, income data were:

◼ Subject to nonresponse bias.

◼ Published based on a “complete reporter” 

definition, that did little to solve the problem. 

Example: The same CU could be defined as 

“complete” or “incomplete,” just by changing 

the reference person! 
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Starting with 2004 data, multiple 

imputation takes effect.

In this technique, different values are estimated for each missing data point.
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To address the break in series, this work 

uses total expenditures, in line with the 

“Permanent Income Hypothesis.”

Permanent Income... ...Transitory Income
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In the interest of brevity....

◼ Was posited by Milton Friedman (1957);

◼ States that expenditures are not made based only on current 

income (money received today), but expectations of future income;

◼ “Allows” expenditures to proxy for income, or at least, many 

authors do so.

The “Permanent Income Hypothesis:”
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And so shall we here!
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Comparing “snapshots,” this is 

what we see:

$62,795

$66,187 $65,395

$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

$70,000

1984 2000 2019

Total Expenditures (Real $2022), CUs with Reference Person 25-34
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It appears GenXers are best off, with 

Millennials a close second:

◼ Increase in expenditures for Boomers to GenX: 

5.4 percent;

◼ Increase in expenditures for GenX to 

Millennials: -1.2 percent. (Negative 

increase=decrease);

◼ Increase for Boomers to Millennials (because, 

according to the stereotype, EVERYONE 

ignores GenX): 4.1 percent.
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But Caveats Apply:

◼ Differences shown here are not tested for 

statistical significance.

◼ What a difference a year makes!

When looking at 1984 and 1999 (not 2000), the 

increase is only 1.1 percent;

And for 1999 to 2015 (from the original work), the 

increase is another 1.2 percent. Timing matters!
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Here, again, is the “big picture:”

$56,000

$58,000

$60,000

$62,000

$64,000

$66,000

$68,000

$70,000

1984 1989 1994 1999 2004 2009 2014 2019

Real ($2022) Total Expenditures, CUs with Reference Person 25-34 

Years Old

Total Expenditures, $2022

CAVEAT: The “default” graph starts the Y-axis at $56K, instead of $0, thus exaggerating the “roller coaster.”

But it makes clear that years of comparison matter, so axis is left unadjusted.
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Caveats about using total expenditures to 

measure “well-being” also apply:

◼ In times of rapid price change, such as the recent 

inflationary period, real expenditures—even after 

controlling for price change—may rise faster than 

real income. So, increased “permanent” income 

makes it look like a group is better off, when it is 

actually worse off.

◼ Goods and services available for purchase change 

over time in quality and just plain availability. Some 

may not even exist in earlier periods:
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Cellphones in 1984, anyone?
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Enter Engels’ Proposition, Stage 

Right.
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Here, we consider shares of 

expenditures.

◼ We discussed the theory behind this before—

smaller shares for necessities implies better 

“economic status.”

◼ Shares also change more slowly (generally) 

than expenditures, even during times of rapid 

price change (again, your experience may 

vary), and thus can be more helpful than 

analyzing even “real” dollar expenditures.
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Let’s start with basic necessities:

◼ Food (at home)

◼ Apparel and services

◼ Housing (mortgage/rent and utilities)
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Before “Moving In” to “Housing:”

◼ In CE, “Housing” includes furniture, lawn and 

garden supplies, etc. that are not “basic 

necessities.”

◼ Utilities are often included in rent, so “basic” 

here includes them for all CUs considered.

◼ Mortgage principal is not considered an 

expenditure in CE. However, it is added in 

here to make better sense of the outcomes.
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Shares for food at home...

8.2%

7.6%

6.7%

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

9.0%

1984 2000 2019

Food at home (Share of Total Expenditures), CUs with Reference 

Person 25-34
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...And Apparel and Services...

6.1%

5.3%

3.3%

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

1984 2000 2019

Apparel and Services (Share of Total Expenditures), CUs with 

Reference Person 25-34

...Are consistent with improved economic status for each generation.
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But Basic Housing is the opposite!

25.6%

27.7%

30.1%

23.0%

24.0%

25.0%

26.0%

27.0%

28.0%

29.0%

30.0%

31.0%

1984 2000 2019

Basic Housing (Share of Total Expenditures), CUs with Reference 

Person 25-34
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Hey, there, not so fast!

Dang it, Ernst! 

I had faith in 

you!
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Could it be younger generations:

◼ Are buying larger homes?

◼ And taking advantage of those lower food at 

home/apparel and services/possibly other 

shares to afford this?

◼ And what about shares of “luxury” goods 

(food away from home, etc.)?
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We’ll find out after a word from 

our sponsor...
72 — U.S. BUREAU OF LABOR STATISTICS TATISTICS • bls.gov bls.gov

...Just kidding.*

*But if you identified with the text, or could identify the product,

you may be a GenXer (or older!)
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Looking at luxuries, food away 

from home...

5.8%

5.9%

6.2%

5.6%

5.7%

5.8%

5.9%

6.0%

6.1%

6.2%

6.3%

1984 2000 2019

Food Away from Home (Share of Total Expenditures), CUs with 

Reference Person 25-34
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...and Entertainment appear to tell 

opposite stories...

5.4%

4.8%

4.2%

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

1984 2000 2019

Entertainment (Share of Total Expenditures), CUs with Reference 

Person 25-34
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Food away from home says, “Better off!” 

while Entertainment says, “Worse off!”

◼ Again, there are factors to consider:

Entertainment includes a lot of different items 

(fees and admissions, digital media recorders and 

players, cable and satellite television services, 

games—virtual or not, pets, etc.)

Some of these items did not exist in 1984, or can 

be produced at higher quality and lower prices 

today. 
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Consider computers:

◼ While technically part of housing, think of a 

computer that sold for $2,000 in 1984 

compared to a computer that sold for $2,000 

in 2019.

◼ Now consider that $2,000 in 1984 was 

equivalent to nearly $5,000 in 2019 spending 

power.
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I think I made my point.
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And what about other measures, 

like vehicle ownership?

84

85

86

87

88

89

90

91

1984 1989 1994 1999 2004 2009 2014 2019

Percent Ownership/Leasing

Percent Distribution: At least one vehicle owned or leased, CUs with 

Reference Person 25-34

Again, do not be fooled by the “roller coaster.”

The rate ranges from 85 to 90 percent over the whole period.

Verdict: Not different.
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So, what have we “mist?”
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Percent reporting.

◼ Available in detailed “unpublished, but releasable” 

tables.

◼ Shows whether more or fewer CUs are buying goods 

or services (of any type available) over time.

◼ Useful for computing mean of those reporting. (If 

overall mean rises, are more CUs purchasing, or 

those who purchase spending more per unit?)
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CE has other demographics not described 

here, in the interest of time.

◼ Number of earners per consumer unit.

◼ Family size.

◼ Occupation of reference person.
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On that last point, tabular data are 

available for singles by age.

◼ Advantages:

 They allow for comparison of single males and single females within 

each time period.

 They allow for comparison of change over time for males, and for 

females, separately. (And then, changes themselves can be 

compared—which group changed the least/most?

◼ Disadvantages:

 They are two-year tables due to sample size. So, each mean is an 

“annual mean over two years,” which may confuse some users.

 They start in 1988-89, so cannot go back as far as the current 

presentation does.
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Another point about singles:

◼ Not available on tables (only through 

microdata) is the number of single 25-34 year 

olds within a household.

◼ If the proportion is increasing over time, this 

could mean more young adults are moving in 

with parents, etc., rather than living 

independently.
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Continuing with this thought, the 

results are open to interpretation:

◼ Resolved: More singles living with parents 

indicates a decrease in economic status.

They are unable to make it on their own, indicating 

hardship.

◼ Resolved: More singles living with parents 

indicates an increase in economic status.

Instead of paying high rent, they put that money toward a 

down payment for an owned home, saving for retirement, 

etc.
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CE asks only about outcomes, 

not motivations.

So, these issues are 

beyond its scope to 

address.
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Hopefully, you learned a lot 

today, at least about the CE data 

and what they can offer.

But want to learn more?
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Join Us!

The Consumer Expenditure Survey Microdata Users’ Workshop 

July 2025

Virtual Event
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The End.
Contact Information

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

Geoffrey Paulin, Ph.D.

Senior Economist

Division of Consumer Expenditure Surveys 

www.bls.gov/cex

paulin.geoffrey@bls.gov