Adult Education and the Structure of Earnings in the United States

Adult Education and the Structure of Earnings in the United States

Dave E. Marcotte

Department of Public Policy

UMBC

Introduction

Growth in U.S. earnings inequality persistent, but uneven.

Traditional explanation points to skill-biased demand shifts, and supply shifts rooted in Baby Boom.

“Revisionist” explanation: Growth is not persistent, and not due to demand shifts, rather to declining value of minimum wage.

Introduction

Implications of Traditional and Revisionist explanations very different.

Here, I consider the role of a factor not directly addressed by either: adult education or job training.

Why? Burgeoning training industry. Returns to training are sizeable. Stylized facts about training patterns suggestive.

Background Trends in earnings inequality

Overall: Growing since the 1960s Rapid acceleration in the 1980s Slowed in the 1990s

Within Groups: Persistent increase during period May have slowed in the 1990s

Between Groups: Unchanged in the 1970s Growth since then(?)

Where does growth bite: Mostly in the tails Esp. in the upper tail in the 1990s

Background source: Autor et al

(2005)

Background

Traditional explanations: Skill-biased technical change Supply shifts

Revisionist explanations: Growth has abated – and now mainly in upper tail. Consistent with decreasing value of minimum

wage in 1980s, and increasing value in 1990s. Residual increase due to composition effects.

Why would training matter?

Training increases earnings: ~6-10% Returns are substantial (Mincer estimates

returns on order of 40% -- Loewenstein, much higher)

Industry is growing rapidly.

Objectives:

Consider role training may have played Did participation increase?

Did trends vary between groups? How has training propensity changed across the

earnings distribution? Within comparable groups, could training be

associated with earnings dispersion?

Insights?

Assess role training may have played in b/w group inequality growth

Assess whether training exacerbated conditional or unconditional spread

Suggestive/Descriptive not Causal Data limitations Inherent empirical problems

Data: National Household Education Survey (NHES) Large cross-sectional sample of American

adults in 1995, 1999, 2001, and 2003. Detailed questions on participation in training

of various types during previous 12 months, along with demographic/economic information.

Inconsistencies.

Characteristics of NHES respondents

Table 1: Descriptive Statistics of Pooled NHES Sample

Variable Mean Std. Error

Salary (2005 $) $52,157.76 28547

Age 42.17 10.45

Female (0/1) 0.528 0.499

White (0/1) 0.775 0.417

Black (0/1) 0.113 0.317

Hispanic (0/1) 0.098 0.298

Dropout (0/1) 0.078 0.269

High School Graduate (0/1) 0.239 0.426

Some College (0/1) 0.287 0.452

College Graduate (0/1) 0.394 0.488

Work Related Training (0/1) 0.462 0.498

n 29,973

Trends in Work-Related Training

.4.5

4.3

.6P

rop.

Rep

ortin

g W

RT

1994 1996 1998 2000 2002 2004Year

Workers Reporting Work-Related Training

Trends in Training by Education0

.2.4

.6.8

Pro

p. R

epor

ting

WR

T

1994 1996 1998 2000 2002 2004Year

Dropouts HS GradsSome College College Grads

Workers Reporting Work-Related-Training: By Education

Trends in Training by Experience

.35

.4.4

5.5

.55

Pro

p. R

ep

ort

ing W

RT

1994 1996 1998 2000 2002 2004Year

< 10 yrs 10-20 yrs20-30 yrs >= 30 yrs

Workers Reporting Work-Related-Training: By Experience

LPM estimates of training propensity: Main Effects

Dep var: Work Related Training in Last 12 Mo.

Variable 10-20 Yrs. Experience 0.022

[0.020]20-30 Yrs. Experience 0.038

[0.020]*>30 Yrs. Experience -0.017

[0.022]HS Grad 0.097

[0.029]***Some College 0.202

[0.029]***College Grad 0.308

[0.028]***Note: Robust standard errors in brackets* significant at 10%; ** significant at 5%; *** significant at 1%

Model also includes controls for race, gender, year fixed effects and constant

LPM estimates of training propensity: Interaction EffectsEducation-time Interaction Terms

HS Grad * Year 1999 -0.01[0.083]

HS Grad * Year 2001 0.064[0.047]

HS Grad * Year 2003 0.106[0.046]**

Some College * Year 1999 0.008[0.082]

Some College * Year 2001 0.154[0.045]***

Some College * Year 2003 0.125[0.045]***

College Grad * Year 1999 0.019[0.081]

College Grad * Year 2001 0.138[0.044]***

College Grad * Year 2003 0.178[0.043]***

Trends in Training by Earnings

.3.4

.5.6

.7P

rop.

Rep

ortin

g W

RT

1994 1996 1998 2000 2002 2004Year

1st Quartile 2nd Quartile3rd Quartile 4th Quartile

Workers Reporting Work-Related-Training: By Earnings

Conditional Salary Quartile Effects

Salary Quartile 2 0.096[0.012]***



Salary Quartile-time Interaction TermsSalary Quartile 2 * Year 1999 0.02

[0.024]Salary Quartile 2 * Year 2001 0.018

[0.024]Salary Quartile 2 * Year 2003 0.027

[0.024]Salary Quartile 3 * Year 1999 -0.004






[0.020]**

Number of Observations 19,269R-squared 0.12Note: Robust standard errors in brackets* significant at 10%; ** significant at 5%; *** significant at 1%

Model also includes controls for education, exp., age, race, year fixed effects and constant

What Role for Training?

Overall trends consistent with supply response to a demand shift.

Training may have exacerbated between group inequality.

Training may be a cause of within group earnings differences. But, this is not changing over time.

Not clear how training could be associated with different trends above/below median.

What Role for Training?

Training received by those with more formal schooling.

Training received by those faring better than average.

Can training serve as a mechanism for redressing equality? Not as it stands Depends on the roots of current maldistribution.

Learning More

Training is dynamic – and capturing its effects is tough in the cross-section

NLSY estimate: 40% of increase in college/high school wage gap due to training.

Need for panel estimates

Documents

Adult Education and the Structure of Earnings in the United States