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Data studies in baby naming
🇺🇸 Original Research
Original Research · April 2026 · babynames.help

Baby Names & Parental Income: The American Data

We analyzed the 50 most popular boy and girl names in America against estimated parental income. The patterns are striking — and measurable.

Naming trends and parental income are correlated across America. Using Social Security Administration birth records for 2023 cross-referenced with U.S. Census Bureau American Community Survey income data by race and ethnicity, we built a weighted income index for every name. The dollar figures represent a weighted average of median household income across the demographic groups that most commonly give each name — not a prediction for any individual family.

Names tied to higher income estimates tend to be classical or literary. Names at the lower end reflect different cultural communities where naming practices follow distinct patterns. Both are rational choices — the data simply maps the patterns at population level.

Boys & Girls — 🇺🇸 100 names
Boys 50
Rank â–¾ Name 2023 Births Est. Parent Income Index Tier
1Liam20,886$70,180
 20th %ile
Lower-Middle
2Noah19,088$70,799
 24th %ile
Lower-Middle
3Oliver14,782$80,399
 86th %ile
High
4James11,727$77,525
 67th %ile
Upper-Middle
5Elijah11,503$65,708
 4th %ile
Lower-Middle
6Mateo11,279$66,041
 6th %ile
Lower-Middle
7Theodore11,084$84,067
 98th %ile
High
8Henry10,988$82,284
 94th %ile
High
9Lucas10,882$80,398
 84th %ile
High
10William10,653$79,845
 78th %ile
Upper-Middle
11Benjamin10,212$78,128
 71th %ile
Upper-Middle
12Levi9,384$73,619
 45th %ile
Middle
13Sebastian8,890$70,737
 22th %ile
Lower-Middle
14Jack8,710$80,258
 82th %ile
High
15Ezra8,474$71,968
 29th %ile
Lower-Middle
16Michael8,416$72,792
 35th %ile
Middle
17Daniel8,391$74,644
 51th %ile
Middle
18Leo8,152$79,577
 76th %ile
Upper-Middle
19Samuel8,019$75,726
 55th %ile
Upper-Middle
20Owen8,011$81,825
 92th %ile
High
21Hudson7,951$81,816
 90th %ile
High
22Alexander7,909$76,160
 59th %ile
Upper-Middle
23Asher7,891$72,576
 33th %ile
Middle
24Luca7,804$77,786
 69th %ile
Upper-Middle
25Ethan7,802$79,343
 73th %ile
Upper-Middle
26John7,793$76,592
 63th %ile
Upper-Middle
27David7,413$75,839
 57th %ile
Upper-Middle
28Jackson7,325$83,797
 96th %ile
High
29Joseph7,268$76,625
 65th %ile
Upper-Middle
30Mason7,257$72,986
 37th %ile
Middle
31Luke7,244$73,321
 41th %ile
Middle
32Matthew7,221$70,091
 18th %ile
Lower-Middle
33Julian7,091$74,649
 53th %ile
Middle
34Dylan7,072$73,340
 43th %ile
Middle
35Jacob7,005$74,210
 47th %ile
Middle
36Elias7,003$69,126
 12th %ile
Lower-Middle
37Maverick6,979$68,386
 10th %ile
Lower-Middle
38Gabriel6,777$69,385
 14th %ile
Lower-Middle
39Logan6,704$71,713
 27th %ile
Lower-Middle
40Aiden6,692$76,422
 61th %ile
Upper-Middle
41Thomas6,620$80,547
 88th %ile
High
42Isaac6,606$74,542
 49th %ile
Middle
43Miles6,581$84,139
 100th %ile
High
44Grayson6,465$67,632
 8th %ile
Lower-Middle
45Santiago6,353$64,936
 2th %ile
Lower-Middle
46Wyatt6,269$80,042
 80th %ile
High
47Anthony6,265$72,483
 31th %ile
Middle
48Carter5,870$69,420
 16th %ile
Lower-Middle
49Jayden5,639$73,000
 39th %ile
Middle
50Ezekiel5,596$64,936
 2th %ile
Lower-Middle
Girls 50
Rank â–¾ Name 2023 Births Est. Parent Income Index Tier
1Olivia15,313$78,071
 65th %ile
Upper-Middle
2Emma13,579$77,678
 61th %ile
Upper-Middle
3Charlotte12,628$81,656
 88th %ile
High
4Amelia12,352$75,645
 45th %ile
Middle
5Sophia11,984$76,220
 49th %ile
Middle
6Mia11,395$75,731
 47th %ile
Middle
7Isabella10,853$71,655
 16th %ile
Lower-Middle
8Ava9,724$73,814
 29th %ile
Lower-Middle
9Evelyn9,113$87,784
 98th %ile
High
10Luna7,841$71,913
 18th %ile
Lower-Middle
11Harper7,792$89,678
 100th %ile
High
12Sofia7,665$74,875
 37th %ile
Middle
13Camila7,577$66,076
 4th %ile
Lower-Middle
14Eleanor6,757$86,851
 92th %ile
High
15Elizabeth6,600$74,640
 35th %ile
Middle
16Violet6,364$72,309
 27th %ile
Lower-Middle
17Scarlett6,311$74,089
 33th %ile
Middle
18Hazel6,181$79,460
 73th %ile
Upper-Middle
19Emily6,172$78,078
 67th %ile
Upper-Middle
20Lily6,170$82,410
 90th %ile
High
21Gianna6,143$68,080
 6th %ile
Lower-Middle
22Aurora6,080$76,759
 53th %ile
Middle
23Penelope6,065$77,067
 59th %ile
Upper-Middle
24Nora6,020$87,631
 96th %ile
High
25Aria6,018$78,276
 69th %ile
Upper-Middle
26Chloe5,987$81,382
 86th %ile
High
27Ellie5,968$87,483
 94th %ile
High
28Mila5,913$76,844
 55th %ile
Upper-Middle
29Avery5,874$75,117
 39th %ile
Middle
30Layla5,698$72,083
 20th %ile
Lower-Middle
31Abigail5,682$73,902
 31th %ile
Middle
32Ella5,659$79,097
 71th %ile
Upper-Middle
33Isla5,381$80,853
 84th %ile
High
34Eliana5,352$70,439
 12th %ile
Lower-Middle
35Nova5,274$60,290
 2th %ile
Lower-Middle
36Zoe5,188$75,376
 41th %ile
Middle
37Madison5,174$71,517
 14th %ile
Lower-Middle
38Ivy5,057$75,426
 43th %ile
Middle
39Grace4,904$77,033
 57th %ile
Upper-Middle
40Lucy4,882$80,042
 78th %ile
Upper-Middle
41Willow4,761$80,042
 78th %ile
Upper-Middle
42Emilia4,684$77,914
 63th %ile
Upper-Middle
43Riley4,637$72,144
 22th %ile
Lower-Middle
44Naomi4,494$72,244
 24th %ile
Lower-Middle
45Victoria4,449$68,831
 10th %ile
Lower-Middle
46Stella4,366$80,659
 82th %ile
High
47Elena4,276$76,666
 51th %ile
Middle
48Hannah4,117$80,140
 80th %ile
High
49Valentina4,086$68,769
 8th %ile
Lower-Middle
50Maya4,085$79,754
 76th %ile
Upper-Middle
← All countries

Methodology & Sources

Name Data

Top 50 names by gender from U.S. Social Security Administration (SSA) 2023 national birth records. The SSA publishes all names given to 5 or more babies per year.

Income Index

A demographic-income weighting method was used: (1) Birth counts by racial/ethnic group from New York State Vital Statistics 2021 (available breakdowns: White non-Hispanic, Black non-Hispanic, Asian, Hispanic); (2) National median household income by race/ethnicity from U.S. Census ACS 5-Year Estimates 2022 (variables B19013A, B19013B, B19013D, B19013I, fetched via the Census API); (3) For each name: weighted income = Σ(group births × group median income) / total group births. Names absent from the NY demographic data are assigned the national demographic-weighted average (~$66,500). These are population-level patterns, not individual predictions.

Limitations

  • Race and ethnicity mediate name–income correlations in the U.S.; this method captures that but cannot isolate it.
  • NY Vital Statistics are used as a demographic proxy; the pattern may differ in other states.
  • Any individual name appears at all income levels — these are aggregate signals, not labels.

Data inquiries: press@media.primespotpr.com

Name Database

Name origin, meaning, and cross-country frequency data sourced from babynames.help — the largest open baby-name database covering 190,000+ names across 40 countries (April 2026).

Story Angles for Journalists

This dataset is free to use with attribution to babynames.help. Press enquiries: press@media.primespotpr.com

The Wealth Ladder Hidden in a Name

Theodore, Miles, and Harper sit in the top income tier. Santiago, Ezekiel, and Nova sit at the bottom. A baby's name — before they speak a word — already correlates with their family's economic standing. What does that mean for social mobility?

Old Money Names Are Back

Classical and literary names (Henry, Eleanor, Oliver, Lily) dominate the High tier. Mass-market, multicultural, and virtue names cluster lower. Is American naming culture reinforcing — or merely reflecting — economic stratification?

The Hispanic Naming Gap

Almost every Hispanic-origin name in the top 50 (Mateo, Santiago, Elias, Gabriel) falls in the Lower-Middle tier. This data maps a structural income gap, not a cultural preference — a story about systemic inequality in plain sight.

Boys vs. Girls: A Different Class Pattern

The top girls' names skew slightly higher in income tier than boys'. Compare Harper ($89k) vs. Liam ($70k), Eleanor ($87k) vs. Noah ($70k). Are parents investing differently in daughters' "cultural capital"?

What No Parent Wants to Admit

Sociologists call this "cultural capital signalling" — naming as a class marker. Most parents will say they chose a name because they loved it. Yet the aggregate data, 20,000 births at a time, tells a remarkably consistent story.


Contact the Research Team

Full dataset, state-level breakdowns, and spokesperson comment available. Free to use with attribution.

Contact the Research Team Visit babynames.help