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: Within Groups: 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: Revisionist 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

Trends in Training by Education

Trends in Training by Experience

LPM estimates of training propensity: Main Effects

LPM estimates of training propensity: Interaction Effects

Trends in Training by Earnings

Conditional Salary Quartile Effects

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