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Stata/SE 18.0 — Results

. reg lwage educ exper tenure, robust

(output omitted)

─────────────────────────────────────────

lwage │ Coef. Std.Err. P

────────────┼────────────────────────────

educ │ 0.0891 0.0063 0.000

exper │ 0.0041 0.0017 0.016

tenure │ 0.0143 0.0032 0.000

_cons │ 0.4580 0.0992 0.000

─────────────────────────────────────────

R-squared = 0.159 N = 1,526

. reg lwage educ exper tenure female married, robust

(output omitted)

─────────────────────────────────────────

lwage │ Coef. Std.Err. P

────────────┼────────────────────────────

educ │ 0.0854 0.0058 0.000

exper │ 0.0039 0.0016 0.014

tenure │ 0.0128 0.0030 0.000

female │ -0.2964 0.0358 0.000

married │ 0.0534 0.0301 0.076

_cons │ 0.6271 0.1044 0.000

─────────────────────────────────────────

R-squared = 0.213 N = 1,526

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Publication-ready table

Table 1: Robustness — IV, Heckman, and Quantile Estimates

(1)
IV
(2)
Heckman
(3)
Qreg (p50)
Education0.0921***0.0867***0.0793***
(0.0142)(0.0068)(0.0071)
Experience0.0038**0.0044***0.0036**
(0.0018)(0.0016)(0.0019)
Female−0.3012***−0.2841***−0.2756***
(0.0372)(0.0345)(0.0401)
Mills ratio (λ)0.142**
(0.068)
First-stage F42.1
N1,5262,1041,526
R² / Pseudo R²0.1480.091

Notes: *** p<0.01, ** p<0.05, * p<0.1. Robust standard errors in parentheses. IV instruments education with distance to nearest college.

Publication-ready table

Table 3: Heterogeneous Returns to Education

(1)
Men
(2)
Women
(3)
Age < 40
(4)
Age ≥ 40
Education0.0762***0.0893***0.0912***0.0714***
(0.0074)(0.0081)(0.0079)(0.0085)
Experience0.0048***0.0031*0.0062***0.0021
(0.0019)(0.0018)(0.0024)(0.0021)
Urban0.1243***0.1189***0.1354***0.1081***
(0.0312)(0.0298)(0.0341)(0.0287)
N842684891635
R²0.1870.2040.1950.176

Notes: *** p<0.01, ** p<0.05, * p<0.1. Robust standard errors in parentheses. All specifications include tenure and a constant.

See how it looks in your paper

Journal of Labor Economics · Vol. 44, No. 2 · 2026

Returns to Education and Labor Market Experience:
Evidence from the Current Population Survey

Sarah M. Chen and David A. Rodriguez

Department of Economics, University of Michigan

Abstract

This paper re-examines the returns to education and labor market experience using data from the Current Population Survey (2018–2024). We estimate Mincerian wage equations with progressively richer specifications. Our preferred specification yields a return to education of 8.2 percent per year of schooling. IV estimates using distance to college as an instrument suggest modest upward bias in OLS, consistent with positive selection.

3. Results

Table 1 reports robustness checks using alternative estimators. The IV specification instruments education with distance to the nearest college. The first-stage F-statistic of 42.1 exceeds conventional thresholds for weak instruments. The Heckman selection model addresses potential sample selection, yielding a positive and significant Mills ratio.

Table 1: Robustness — IV, Heckman, and Quantile Estimates

(1)
IV
(2)
Heckman
(3)
Qreg (p50)
Education0.0921***0.0867***0.0793***
(0.0142)(0.0068)(0.0071)
Experience0.0038**0.0044***0.0036**
(0.0018)(0.0016)(0.0019)
Female−0.3012***−0.2841***−0.2756***
(0.0372)(0.0345)(0.0401)
Mills ratio (λ)0.142**
(0.068)
First-stage F42.1
N1,5262,1041,526
R² / Pseudo R²0.1480.091

Notes: *** p<0.01, ** p<0.05, * p<0.1. Robust standard errors in parentheses. IV instruments education with distance to nearest college.

The quantile regression at the median yields a somewhat smaller education coefficient of 0.079, suggesting that returns are higher in the upper tail of the conditional wage distribution. Across all three estimators, the gender gap remains large and precisely estimated.

3.2 Progressive Specifications

Table 2 presents our OLS estimates with progressive covariate adjustment. Column (1) reports the baseline Mincerian specification. Columns (2)–(4) add demographic controls, industry fixed effects, and region fixed effects. The return to schooling declines modestly from 8.9 to 7.9 percent.

Table 2: OLS Estimates with Progressive Controls

(1)
Baseline
(2)
+Demo.
(3)
+Ind. FE
(4)
+Region FE
Education0.0891***0.0854***0.0823***0.0792***
(0.0063)(0.0058)(0.0055)(0.0054)
Experience0.0041**0.0039**0.0035**0.0033**
(0.0017)(0.0016)(0.0015)(0.0015)
Female−0.2964***−0.2812***−0.2743***
(0.0358)(0.0341)(0.0338)
Married0.0534*0.04120.0389
(0.0301)(0.0289)(0.0287)
Industry FENoNoYesYes
Region FENoNoNoYes
N1,5261,5261,5261,526
R²0.1590.2130.2410.258

Notes: *** p<0.01, ** p<0.05, * p<0.1. Robust standard errors in parentheses.

The gender wage gap is substantial and persistent. The coefficient on Female implies that women earn approximately 27–30 log points less than men across all specifications. The marriage premium is positive but loses significance once we account for industry composition.

3.3 Heterogeneous Returns

Table 3 examines heterogeneity in the returns to education by gender and age. The returns to education are higher for women (0.089) than for men (0.076), and higher for workers under 40 (0.091) than for older workers (0.071). The urban premium is robust across all subgroups.

Table 3: Heterogeneous Returns to Education

(1)
Men
(2)
Women
(3)
Age < 40
(4)
Age ≥ 40
Education0.0762***0.0893***0.0912***0.0714***
(0.0074)(0.0081)(0.0079)(0.0085)
Experience0.0048***0.0031*0.0062***0.0021
(0.0019)(0.0018)(0.0024)(0.0021)
Urban0.1243***0.1189***0.1354***0.1081***
(0.0312)(0.0298)(0.0341)(0.0287)
N842684891635
R²0.1870.2040.1950.176

Notes: *** p<0.01, ** p<0.05, * p<0.1. Robust standard errors in parentheses. All specifications include tenure and a constant.

4. Discussion

Our estimates align closely with the meta-analytic findings of Card (1999) and the more recent work of Autor (2014). The finding that returns are higher for women than men is consistent with Dougherty (2005), who argues that female college graduates benefit disproportionately from access to professional occupations.

References

Autor, D. H. (2014). Skills, education, and the rise of earnings inequality. Science, 344(6186), 843–851.

Card, D. (1999). The causal effect of education on earnings. Handbook of Labor Economics, 3, 1801–1863.

Dougherty, C. (2005). Why are the returns to schooling higher for women than for men? Journal of Human Resources, 40(4), 969–988.

Mincer, J. (1974). Schooling, Experience, and Earnings. Columbia University Press.

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