48 Monthly Labor Review February 2005

Worker Training

H

ow individuals obtain their skills and

how they are paid for the use of those

skills are concepts that are fundamental

to the field of labor economics. Productive skills

are often referred to as “human capital.” The

basic idea of human-capital theory is that

workers invest in their own skills in order to

earn higher wages, much as persons invest in

financial or physical assets to earn income.

Although this idea goes back at least to Adam

Smith, modern human-capital research was

originated in the late 1950s by economists

Theodore Schultz, Jacob Mincer, and Gary

Becker. Their ideas, focusing on investments

in and returns to education and training, have

provided the theoretical and empirical basis for

decades of ensuing research.1

Much of the empirical research on the topic

of human capital has analyzed the relationship

between education and wages. This focus on

education is due to the abundance of highquality data sources with information on both

education and wages. For example, analysts

using cross-sectional data from the Current

Population Survey (CPS) have found that individuals in the United States receive earnings

that are approximately 10 percent higher for

Worker Training

Worker training: what we’ve

learned from the NLSY79

The 1979 cohort of the National Longitudinal Survey

of Youth has been a wellspring of knowledge

about worker training and a valuable

means of empirically testing human-capital theory

Harley J. Frazis

and

James R. Spletzer

Harley J. Frazis and

James R. Spletzer are

research economists on

the Employment

Research and Program

Development Staff,

Office of Employment

and Unemployment

Statistics, Bureau of

Labor Statistics. E-mail:

frazis.harley@bls.gov or

spletzer.jim@bls.gov

every additional year of schooling they have

completed.2 Kenneth I. Wolpin’s article on education in this special edition of the Monthly

Labor Review shows that, over the 15-year

period between ages 25 and 39, a male college

graduate earns 80 percent more than a male high

school graduate without any college, and a male

high school graduate earns 57 percent more than

a high school dropout.

However, empirical research on training—the

other key component of human capital—has

lagged research on the economics of education.

The human-capital model yields straightforward

predictions about the relationship of on-the-job

training to wages, wage growth, and job mobility;

still, as will become clear, testing these predictions

requires good longitudinal microdata.

The need for high-quality longitudinal microdata with detailed information about wages,

mobility, and on-the-job training has led researchers to the National Longitudinal Surveys

for empirical analyses of training. This article

both provides a brief summary of the humancapital model as it relates to on-the-job training

and summarizes the empirical training literature,

with a special focus on the contributions that

analyses of the data from the 1979 cohort of the
Monthly Labor Review February 2005 49

National Longitudinal Survey of Youth (NLSY79) have made

to that literature.

The human-capital model

Models of competitive labor markets imply that wages paid

to workers reflect their productivity. For example, if education

makes workers more productive, then higher wages are paid

to more highly educated persons. Similarly, if on-the-job

training makes workers more productive, then trained workers

should receive higher wages than workers with no training.

But education and on-the-job training differ in one key aspect:

most workers finish their schooling before entering the labor

market, whereas most on-the-job training occurs during a

worker’s tenure with an employer. While education and onthe-job training are both productivity-enhancing investments, they potentially differ with regard to whether the

worker or the employer pays the costs.

Any investment in human capital involves current costs

and future benefits. The costs associated with on-the-job

training involve both direct costs, such as the salaries of the

persons doing the training and any costs of materials, and

indirect costs, such as the cost of taking trainees away from

their current productive tasks. The benefits of on-the-job

training accrue to both the firm providing the training and the

worker receiving the training: because the worker is more

productive after the training, the firm benefits from higher

productivity and greater output, and the worker benefits from

his or her higher productivity in the form of higher wages.

One key theoretical issue regarding on-the-job training

concerns the division of these costs and returns between the

firm and the worker.

Gary Becker made progress on this cost-sharing issue by

defining two types of training: general training and specific

training. Completely general on-the-job training is training

that provides the worker with skills that are productive at

firms other than his or her current employer. Examples of

completely general training are learning to use a wordprocessing or data-processing computer program that is

available for purchase by any firm, pilots learning to fly a

type of jet airplane that is in the fleet of several airlines, and

doctors learning a new surgical technique that could be

conducted at any hospital. By contrast, completely specific

on-the-job training is training that enhances the productivity

of the worker at only the firm providing the training. Examples

of completely specific training are astronaut training (presumably specific to the National Aeronautics and Space Administration), learning to drive a tank (presumably specific to the

U.S. Military), and learning to operate a machine that was

developed and is used by only one manufacturing firm to

produce its product. In the real world, almost all training

involves a combination of both general and specific skills.

In a competitive labor market, workers are paid for the

skills they possess. Becker reasoned that, because general

training provides skills which are useful at all firms, the firm

offering the general training will need to pay the trained worker

a wage that reflects these skills; otherwise the worker will

leave the firm to receive a higher wage at a different firm.

Anticipating this possibility, a profit-maximizing firm will not

pay any of the costs of general training because it cannot

extract any of the returns from the training. In that case, the

worker will pay all the costs of the general training—not just

the direct costs, but also the indirect costs that reflect the

worker’s lost productivity to the firm. Human-capital theory

thus predicts that, relative to workers who do not receive

training, workers who receive general training will be paid

lower wages while receiving the training and higher wages

after the training is complete. This hypothesis is depicted in

exhibit 1, which compares the wage profile of a worker who

receives no training with that of a worker who receives general

training.

Sharing the costs and returns of specific training is more

complicated. On the one hand, assume, for the moment, that,

as with general training, a worker pays all the costs and

receives all the benefits of specific training. In such a case, a

worker who might be fired or laid off after receiving the

training would receive no future returns from his or her

investment in specific training; thus, the worker would have

less incentive to pay for the training, because the decision to

lay the worker off is made by the firm. On the other hand,

assume that a firm pays all the costs and receives all the

benefits of specific training. In this case, the firm would

receive no future returns from the investment if the trained

worker quit for another job; thus, the firm would have less

incentive to pay for the training, because the decision to quit

is made by the worker. The solution to this dilemma is for the

worker and the firm to share the costs and returns of specific

training, with the exact division of the returns depending

upon the wage elasticity of the worker’s propensity to quit

and the firm’s propensity to lay the worker off.3 This sharing

is portrayed in exhibit 1: the wage profile of a worker who

receives specific training shows the worker paying some (but

not all) of the costs and receiving some (but not all) of the

returns.

The sharing of the costs and returns to training has

implications for worker mobility. Workers who have received

specific training have higher productivity at their current

employer than at other employers, and their wage at the

current employer is higher than the wage they could obtain

from other employers. This asymmetry results in workers with

specific training having lower probabilities of quitting than

workers with no specific training. Similarly, because the

productivity of workers with specific training exceeds their

wage, the employer is less likely to lay off workers with
 50 Monthly Labor Review February 2005

Worker Training

specific training relative to workers with no specific training.

By contrast, because workers with general training have the

same productivity at the current employer as at other employers, and because the wage they receive from their current

employer equals the wage they would expect from other

employers, the provision of general training does not lower

expected probabilities of quitting. Similarly, in the simple

model presented here, firms could replace a worker with

completely general training without loss of any productivity,

so the provision of general training does not lower expected

probabilities of layoffs.

In sum, this simple, yet elegant, human-capital model has

several testable predictions. First, training lowers the starting

wage: during training, a worker accepts a lower wage relative

to a worker not receiving training, all other things being equal.

Second, training raises future wages at the employer providing the training: a worker who has received on-the-job training

should receive higher wages relative to a worker with no

training—again, all other things being equal. Third, by

definition from the preceding two predictions, training raises

wage growth at the employer providing the training. Fourth,

the foregoing three predictions vary in magnitude as a

function of whether the training is specific or general. Finally,

specific training lowers worker mobility, whereas general

training has no effect on worker mobility, all other things

being equal.

These testable predictions provide the framework for

empirical analysis. It is obvious that several demands are

being placed on the data. First and foremost, there needs to

be information on training and individuals’ wages. Furthermore, longitudinal microdata are necessary for analyzing

wage growth and mobility. Finally, the information needs to

be quite detailed in order to distinguish general training from

specific training. The NLSY79 data satisfy all these criteria

and make up one of the few data sets that provide detailed

longitudinal information on all the necessary analytical

variables. It is not surprising, then, that much of what we

know about on-the-job training has come from analyses of

the NLSY79 data.

Before we turn to the empirical findings, the importance of

the phrase “all other things being equal” needs to be mentioned. A common finding from all data sets with training

information is that individuals who receive training are not a

random sample from the population of all workers. For example,

those who are college educated and those with higher ability are

more likely to receive training.4 This nonrandom selection affects

how we interpret the empirical analysis that follows. (This issue

is more fully explained later in the article.)

Exhibit 1. Wage profiles

General training

Specific training

No training

Time

Wages 
Monthly Labor Review February 2005 51

Empirical findings from the early literature

Early on in the development of human-capital theory,

economists recognized that on-the-job training was an

important source of investment in human capital. Because

on-the-job training data were not available, the earliest

attempts to measure such training were indirect. As has been

noted, models of competitive labor markets imply that workers

will be paid in accordance with their productivity. The

tendency of wages to increase with labor market experience

was interpreted as evidence of training-induced increases in

productivity. With additional assumptions, the wage-experience relationship could be used to infer an investment path

and returns to the training investment.

Mincer’s 1962 article attempted to estimate the amount of

training by comparing the earnings path of individuals with

 Table 1. Questions about training, NLSY79, 1988–20001

 Question Mean2

19. Since [date of the last interview] did you attend any training program

or any on-the-job training designed to help people find a job, improve job

skills, or learn a new job?

Yes: Continue to 20 .................................................................................... ............................................. .158

No: Skip to next section of questionnaire.................................................. ................................................. .842

20. Which category on this card best describes where you received

this training? [Code one only]

Business school.. ............................................................................................................................................... .030

Apprenticeship program ................................................................................................................................... .021

A vocational or technical institute ................................................................................................................... .097

A correspondence course .................................................................................................................................. .029

Formal company training run by employer or military training....................................................................... .375

Seminars or training program at work run by someone other than employer .................................................. .158

Seminars or training programs outside of work ..................................................................................................... .184

Vocational rehabilitation center ....................................................................................................................... .013

Other (Specify: __________) ......................................................................................................................... .078

21. Who paid for this training program? [Code all that apply]

Self or family .................................................................................................................................................... .139

Employer ......................................................................................................................................................... .739

Job Training Partnership Act ........................................................................................................................... .021

Trade Adjustment Act . ................................................................................................................................. .001

Job Corps Program ........................................................................................................................................... .001

Work Incentive Program .................................................................................................................................. .004

Veteran’s Administration .................................................................................................................................. .002

Vocation Rehabilitation .................................................................................................................................... .011

Other (Specify ________) ............................................................................................................................... .092

25. Altogether, for how many weeks did you attend this training? .................................................................. 5.7

31. How many hours per week (do/did) you usually spend in this training? ..................................................... 20.1

different amounts of education and assuming that returns to

training were the same as returns to schooling.5 Mincer’s

1974 book was probably more influential; in it, he showed

that if time spent in training increased the logarithm of wages

linearly, and if the percentage of working time spent in training

declined with experience in a linear manner, then wages would

be well described by a quadratic function of experience.6 The

quadratic earnings function was found to be a fair approximation of earnings and won wide acceptance.7

This evidence was clearly imperfect. Moreover, in the late

1970s, economists developed other theories to explain the

tendency of wages to rise with experience, ranging from

improvements in job matches through a worker’s career to

firms tilting their wage profiles to discourage shirking or

encourage more stable workers to apply.8 Evidently, more

direct measures of on-the-job training were needed.

1

 The training questions in 1988, 1996, 1998, and 2000 had a 2-

year reference period. The training questions in 1989–1994 had

a 1-year reference period.

2

 All entries are unweighted tabulations from the 1988–2000

NLSY79 microdata. The sample size for question 19 is N = 91,144.

All means for questions 20, 21, 25, and 31 are computed from the

sample of respondents who said “yes” to question 19. The mean

for question 25 is computed from the sample of respondents whose

training program had been completed by the date of the interview.
 52 Monthly Labor Review February 2005

Worker Training

Employment and Training Administration (ETA) of the U.S.

Department of Labor. The ETA was concerned with the efficacy

of various federally funded employment and training

programs in helping youths to acquire skills and secure

employment. Data collection during the 1979–86 interviews

was limited to only those training programs in which the

respondent had been enrolled for 1 month or more; analysis

of the microdata from 1988 to 2000 indicates that 66 percent

of completed training spells are less than 4 weeks in duration.

In 1987, when funding of the NLS shifted to the Department of

Labor’s Bureau of Labor Statistics, the collection of extensive

information on government training ceased, and the “Other

Training” section of the questionnaire was restructured. The

limitation of 1 month’s duration was dropped in the 1988 and

later questionnaires. The 1987 survey was an abbreviated

telephone interview, and only one question was asked about

whether any training or assistance had been received from

any government-sponsored program.

The key training questions from the 1988–2000 NLSY7 9

surveys are listed in table 1, along with unweighted means.

In each of the surveys between 1988 and 2000, the incidence

of training is elicited with the question, “Since [date of the

last interview] did you attend any training program or any

on-the-job training designed to help people find a job, improve

job skills, or learn a new job?” The statistics in table 1 tell us

that 15.8 percent of persons have received training since the

date of their last interview. 12

One advantage of a longitudinal survey such as the

NLSY79 is that one can examine the incidence of training over

several years. Table 2 reports the cumulative incidence of

training spells for the sample of individuals who responded

to every interview between 1989 and 1994. Surveys for these

6 years were chosen because each has an annual reference

period for the training question. Over the course of those 6

years, when individuals in the NLSY79 ranged from 24 to 37

years of age, 53.2 percent of respondents never received any

training. Of those persons who did get training at least once

during the 6-year period, roughly half (24.1/46.8) received

One such measure was included in the Panel Study of

Income Dynamics (PSID), a longitudinal survey administered

annually since the 1960s. In 1976 and 1978, the PSID asked the

question, “On a job like yours, how long would it take the

average new person to become fully trained and qualified?”

Articles by Greg J. Duncan and Saul Hoffman in 1979 and

James N. Brown in 1989 used this question to identify periods

of on-the-job training and adjust earnings equations

accordingly.9 The longitudinal structure of the PSID allowed

Brown to directly examine the effect of training on wage

increases, rather than inferring wage increases from crossperson comparisons. Both articles found a substantial effect

of training on wages, providing evidence for the humancapital interpretation of wage increases. However, the PSID

question clearly affords only a limited measure of on-the-job

training. As Duncan and Hoffman noted, the intensity of

training during the training period may vary between persons

with identical answers to the question, and the type of

training—formal, informal, or learning by doing—is

completely unspecified.

Aside from the NLSY79, other attempts to measure on-thejob training in surveys of individuals include earlier cohorts

of the National Longitudinal Surveys (NLS) and supplements

to the CPS in 1983 and 1991. Lee A. Lillard and Hong W. Tan

used the 1983 CPS and the early cohorts of the NLS to examine

training and its effect on labor market outcomes.10 The CPS

supplement asks what training was needed for the

respondent to obtain his or her current or previous job and

inquires about training to improve skills on the current job.

Because the CPS is not a longitudinal survey and because the

period during which the training took place is unclear, only

the association of training with differences in wages between

persons (which is substantial) can be examined; wage

changes due to training for a given individual cannot be

tracked. The training questions in the earlier cohorts of the

NLS are broadly similar to, but less extensive than, those in

the NLSY79 (and the employment data in the earlier cohorts

are not as good). Moreover, they cover only the “longest”

training event between surveys, so they do not provide a

comprehensive record of formal training. Exploiting the

longitudinal nature of the NLS to examine the effect of training

on wages several years later, Lillard and Tan found evidence

that training does depreciate.

Training data in the NLSY79

This section describes several of the key training questions

in the NLSY79 survey instrument. Readers interested in more

documentation about the NLSY79 training questions may

consult the NLS Users’ Guide.11 As mentioned there, the

training questions in the survey changed in the mid-1980s.

The initial, 1979–86 rounds of the NLSY79 were funded by the

Table 2.

Number of training spells Count Percent

 0 ................................... 4,307 53.2

 1 ................................... 1,947 24.1

 2 ................................... 994 12.3

 3 ................................... 516 6.4

 4 ................................... 208 2.6

 5 ................................... 99 1.2

 6 .............................. ..... 24 .3

NOTE: Entries are unweighted tabulations from the 1989–94 NLSY79

microdata.

Cumulative incidence of training, sample of

8,095 individuals who responded to each

interview, 1989–94
Monthly Labor Review February 2005 53

only one spell of training, and roughly one-quarter (12.3/46.8)

received two spells of training.

Individuals who answer “yes” to the question on the

incidence of training are then asked where they received their

training. The most frequent type of training is formal company

training (37.5 percent of all training spells); noncompany

seminars or training programs also are a frequent type of

training (34.2 percent of all training spells, broken down into 18.4

percent consisting of seminars or training programs outside of

work, and 15.8 percent seminars or training programs at work

run by someone other than the employer). Vocational or technical

institutes are the fourth most-frequent type of training (9.7

percent of all training spells). As mentioned later in the article,

researchers have found that this question about the type of

training provides important information about the generality

of training.

The next question in the training sequence asks who paid

for the training program. The most frequent response is “the

employer,” who pays for 73.9 percent of all training spells.

Researchers have made several interesting points regarding

this question. First, the question supplies some of the data

that are necessary to analyze the interesting theoretical

question of who pays for general and specific training. (The

empirical literature on the subject is summarized in a later

section of the article.) Second, many researchers restrict their

analyses to employer-paid training spells; the human-capital

model is an on-the-job training model, and deleting

nonemployer paid spells of training aligns the theory with

the empirical work.

The duration of training is just as important as the

incidence. Table 1 indicates that the mean completed training

spell lasts 5.7 weeks and 20.1 hours per week. Table 3 gives

statistics on the distribution of the duration of completed

training spells. The distribution of weeks of training is heavily

skewed to the right, with half of all completed training spells

less than or equal to 1 week in duration, but 5 percent greater

than 24 weeks. Total hours of training follow a similar pattern:

half of all completed training spells are less than or equal to

35 total hours, but 5 percent are greater than 520 total hours.

Empirical findings

Wages and wage growth. Lisa Lynch’s 1992 article in the

American Economic Review is the most prominent early

study using NLSY79 data to examine the effect of training on

wages.13 Lynch uses data from 1980 through 1983 to estimate

the effect of training on 1983 wages for youths who had

completed their education by 1980 with less than a college

degree. (Note that 1980 is too early to have a substantial

sample of college graduates from the 1979 survey.) She

classifies training as on the job, off the job, and apprenticeship, and she reports descriptive statistics showing that

4.2 percent of individuals received on-the-job training for an

average of 31.2 weeks, 14.7 percent of individuals received

off-the-job training for an average of 40.9 weeks, and 1.8

percent of individuals received apprenticeship training for

an average of 63.5 weeks. She takes advantage of the

longitudinal nature of the NLSY79 to construct measures of

cumulative weeks of training in each category.

Lynch estimates both an equation for 1983 wages and an

equation for wage growth from 1980 to 1983. The wage growth

equation is used to eliminate possible selection bias in the

wage-level equation: workers who receive training may have

some unobservable characteristic, such as high ability, that

is positively correlated with both wages and training. In that

case, because more able workers would get trained, comparing wage levels of different workers would bias wage

differentials between trained and untrained workers. But

examining wage changes for a given worker will correct this

source of bias if ability is fixed over time for a given individual.

Lynch’s wage-level equation implies that off-the-job training

and apprenticeship training from previous employers, and

on-the-job training and apprenticeship training with the

current employer, significantly raise wages. In addition, the

wage growth equation implies that off-the-job training and

apprenticeship training raise wages, but that on-the-job

training has no effect on wages.

In a later study paralleling Lynch’s methods, Jonathan

Veum uses data from the 1986–90 surveys to measure the

impact of training on wages.14 Unlike Lynch, Veum is able to

include in his analysis all training spells, whether they were

less than or greater than 1 month in duration. His 1990 wagelevel equation yields no statistically significant effect of any

form of training when training is measured continuously, but

does show some significant effects of company training and

off-the-job seminars when training is measured in terms of its

incidence. His results for wage growth between 1986 and

1990 are similar.

Daniel Parent uses a specification similar to that of Lynch

and Veum, with data from the 1979–91 surveys.15 Although

the wage growth equations in the earlier papers eliminate

bias due to unchanging personal characteristics, Parent notes

that jobs with higher wages may also have more training

Table 3. Distribution of training durations, NLSY79,

 1988–2000

Percentile Number of weeks Hours per week Total hours

Mean .............. 5.7 20.1 118.3

25th .................. 1 6 12

50th .................. 1 16 35

75th .................. 6 40 80

95th .................. 24 40 520

99th .................. 52 65 1,440

NOTE: Entries are unweighted tabulations from the 1988–2000 NLSY79

microdata.
 54 Monthly Labor Review February 2005

Worker Training

irrespective of the individual. Parent gets around this problem

by using information on the deviation of the stock of training

from within-job means. He finds fairly substantial effects of

both off-the-job and on-the-job training. His correction for

job bias substantially reduces the effect of apprenticeships,

although the effect of previous jobs’ apprenticeship training

remains statistically significant.

Paul Lengermann used the NLSY79 to examine the question

investigated by Lillard and Tan: How does the effect of

training on wages evolve over time?16 Unlike those researchers, Lengermann examines wage growth in contrast to

wage levels, so as to avoid bias due to the differing abilities

of workers. He examines both spells of training that lasted 4

weeks or longer (available throughout the sample) and spells

of training of less than 4 weeks (for which detailed information

is available only after 1986). His data cover 1979–93, and his

results indicate that (1) long spells of company training have

substantial effects on wages and (2) those effects do not

depreciate—indeed, they are estimated to increase from 4.4

percent in the first year to 8.2 percent after 9 years. The effect

of long spells of school-based training is not statistically

significant, although it also does not appear to depreciate.

Short spells of training, perhaps not surprisingly, have less

consistent effects.

So far, this article has concentrated on whether training

increases wages by a statistically significant amount, rather

than discussing the economic significance of the increase.

This approach reflects the emphasis in the papers presented.

Another question is, “Considering training as an investment,

how does the rate of return compare with that from other

investments, such as schooling?” Harley Frazis and Mark

Loewenstein investigate this question, using data from the

1979–2000 surveys of the NLSY79 .

17 Their analysis is

restricted to training at least partially paid for by the employer.

(See question 21 in table 1; for years prior to 1988, Frazis and

Loewenstein impute whether the employer pays for training.)

Like Parent, Frazis and Loewenstein control for jobs by

restricting their investigation to within-job wage changes.

Frazis and Loewenstein show that estimates of the effect

of training are highly dependent upon the assumed functional form of the relationship between wages and training.

They find that the best-fitting functional form is one in which

the logarithm of wages increases proportionately with the

cube root of training. Using linear hours instead of the cube

root results in a drastic underestimation of the effect of

training at typical values, which may explain the insignificant

effects found in some of the aforementioned papers. Frazis

and Loewenstein find that, in their base specification, the

median positive value of employer-financed training of 60

hours increases wages by about 5 percent, which, when

annualized, implies a rate of return of 159 percent.

Frazis and Loewenstein consider several explanations for

this very high estimated rate of return. Correcting for

promotions (for which the NLSY79 collected data in 1988–90

and 1996–2000), direct costs of training, and heterogeneity in

wage growth (as well as in wage levels) reduces estimated

rates of return to 30 to 40 percent. While this estimate is still

several times estimated rates of return to schooling in the

literature, Frazis and Loewenstein note that returns to training

appear to vary across jobs: managers and professionals have

higher rates of return than do blue-collar workers, for example.

In the presence of such variation, estimated rates of return

can be regarded as the return of training to the trained.

However, they are likely to be greater than the return that

could be realized by employees who did not receive training.

Frazis and Loewenstein’s research highlights the

strengths of the NLSY79 data set in studying training. The

large sample size, the long length of the panel, and detailed

survey data about other labor market information, such as

promotions, allow for relatively precise estimation of the

effects of training while controlling for confounding influences.

Mobility. The most prominent early article analyzing the

empirical relationship between worker mobility and training

was written by Lynch.18 Using data from the 1979–83 surveys

of the NLSY79, Lynch estimated the probability of leaving the

first job as a function of tenure for individuals who have

permanently left school. Her estimates show that young

persons who received formal on-the-job training from their

employer are less likely to leave their job, whereas those who

participated in training obtained from for-profit proprietary

institutions outside the firm are more likely to leave their job

(although this latter effect is not statistically different from

zero). These results are consistent with the human-capital

model if one makes the straightforward assumption that onthe-job training provides firm-specific skills and off-the-job

training provides general labor market skills.

Further analysis of how training affects worker mobility is

provided by Loewenstein and James Spletzer, who use

NLSY 7 9 data from the 1988–91 survey years.19 After

controlling for individual and job characteristics, they find

that individuals who have received company training have a

job separation rate that is 8 percent lower than individuals

without such training, and individuals who received school

training (business school, apprenticeship, vocational or

technical institute, or correspondence courses) have no

differences in job separation probabilities relative to persons

who did not receive school training. The mean job separation

rate in Loewenstein and Spletzer’s sample is 53 percent. Assuming that company training is more specific than general

and that school training is more general than specific, these

empirical results are consistent with the basic predictions

about worker mobility from the human-capital model.
Monthly Labor Review February 2005 55

Loewenstein and Spletzer use their empirical findings to

build on the predictions from the human-capital model.

Because the returns to specific training are lost when a job

match terminates, the model predicts that specific training

should be selectively provided to workers who are less likely

to leave the job. (Evidence supporting this theoretical

prediction is mentioned shortly). If there is uncertainty about

workers’ future mobility, and if information about the quality

of the employer-worker match is revealed over time, it may be

optimal to delay training as a means of avoiding making a

costly investment in a worker who may soon leave the firm.

Such a decision to delay training may be optimal even though

it entails forgoing the returns to training during the early part

of the employment relationship. Loewenstein and Spletzer

find that the NLSY79 data show a substantial amount of

delayed training; for example, their estimates show that a

similar proportion of workers get their first spell of training in

their second year of tenure as in their first year of tenure.

As part of his research mentioned earlier, Parent found

that both on-the-job and off-the-job training at the current

employer reduced a worker’s mobility, while training at

previous employers appeared to increase mobility, although

by a lesser magnitude. For workers with more than one spell

of employment, it is possible to correct for bias caused by

differences across workers in propensities to leave jobs.

When Parent makes this correction, the effect of training at

the current employer is strengthened.

It is interesting to flip the training-mobility relationship

around and ask whether individuals with higher expected

future job separation rates receive lower amounts of company

training. This is the question asked by Anne Beeson Royalty,

who uses NLSY79 data from survey years 1980–86 in her

analysis.20 She finds that a higher incidence of companyprovided training is given to individuals with lower estimated

probabilities of leaving the employer. Assuming that company training imparts firm-specific skills, Royalty’s analysis

shows that profit-maximizing employers target the provision

of specific training toward those individuals who are less

likely to leave.

General and specific training

Human-capital theory distinguishes between general human

capital, which is useful at many employers, and specific

human capital, which is useful only at the current firm.

Researchers have associated types of training that raise

wages at both current and future employers with general

human capital, and types of training that raise wages only at

the current employer with specific human capital. Furthermore, types of training that reduce mobility have been associated with specific training. Much of the empirical work in

the training literature has taken advantage of the wealth of

information in the NLSY79 data to explore the measurement

and theoretical implications of general and specific training.

The findings reviewed in this article up to now present a

fairly consistent fit between the theoretical human-capital

model and the empirical training results. From her wage-level

estimation, Lynch finds that wages are raised by on-the-job

training from the current employer, but not from previous

employers, whereupon she concludes that on-the-job training

is primarily specific. She also finds that off-the-job training

taken before the worker’s tenure on the current job does raise

wages, consistent with such training being primarily general.

Lynch’s analysis of mobility leads her to a similar conclusion:

that on-the-job training is more specific, whereas off-the-job

training is more general; Loewenstein and Spletzer’s analysis

of worker mobility finds similar results. The one study mentioned that does not slot nicely with the theoretical model is

Parent’s, which finds little difference between off-the-job and

on-the-job training, with similar returns for training provided

by current and previous employers (consistent with general

training) and with both reducing mobility (consistent with

specific training).

A detailed analysis of the costs and returns to training

within and across jobs was conducted by Loewenstein and

Spletzer.21 The motivation for this study was to analyze

questions in the NLSY79 that ask about who pays for the

training (question 21 in table 1). Recall from the discussion of

the human-capital model that there are two costs to employerprovided training: the direct costs, plus an indirect cost of

lower wages during training. It is assumed that asking workers

who pays for the training refers to direct costs only; it is a stretch

to believe that noneconomists would think of indirect costs

(lower wages due to reduced productivity) when answering this

survey question. Loewenstein and Spletzer find that employers

pay for 96 percent of formal company training spells. This

percentage is not surprising, because formal company training

almost surely has a large component of specificity and the

human-capital model predicts that employers will share the costs

of specific training with the worker. Loewenstein and Spletzer

also show that employers pay for 42 percent of training spells in

the aggregate category of “business school, apprenticeship,

vocational or technical institute, and correspondence course.”

This aggregate category, referred to as school training in the

discussion that follows, should have a large component of

generality, and according to the human-capital model,

employers should pay the direct costs of general training

only if they can pass on the costs to workers by paying them

lower wages during the training.

Loewenstein and Spletzer find no significant evidence that

workers receiving employer-provided training—either

general or specific—accept lower wages during the training

period. While this finding may seem to contradict the human

capital model, it is consistently found in the empirical
 56 Monthly Labor Review February 2005

Worker Training

literature—for example, by Lynch and Parent, as well as by

researchers using training data from employer surveys.22 The

most likely explanation for this anomaly is that it is due to

differences between trained and untrained workers that are

difficult to control for empirically. If workers who receive training

have higher ability than workers who do not receive training,

and if this higher ability is observable to the employer, but

unobservable to the data analyst, then workers who receive

training will have higher wages relative to workers who do not

receive training. Even if training lowers the starting wage, as is

predicted by the human-capital model, higher wages attributable

to differences in ability may make a lower starting wage difficult

to observe in the data when one compares wages of untrained

workers with wages of workers receiving training.

The human-capital model predicts that if employers are

paying both the direct and indirect costs of training, as the

NLSY79 data suggest, employers should also be realizing some

of the returns. The empirical strategy that Loewenstein and

Spletzer use to test this prediction is to compare the return to

training when a worker remains at the employer providing the

training with the return to training when the worker moves to

a new employer. Loewenstein and Spletzer find that the return

to training received from a previous employer is higher

relative to the return to training received from the current

employer when the training is arguably more general.

Lengermann reports a similar result for long spells of company

training. In combination with the absence of a starting-wage

effect, Loewenstein and Spletzer’s analysis shows that

employers pay for some of the costs of general training and

receive some of the returns. This finding is at odds with the

standard human-capital model, but can be reconciled with

several theoretical modifications to that model. For example,

minimum wages, liquidity constraints, or contract

enforcement considerations can result in the employer

sharing the costs and returns of general training.23

This evidence that employers share the costs and returns

of general training has led researchers to seek additional

questions that measure the generality of training. In 1993, for

the first and only time, the NLSY79 included the question “How

many of the skills that you learned in this training program do

you think could be useful in doing the same kind of work for

an employer DIFFERENT than [current employer]?” There are

five possible responses to this question: (1) all or almost all

of the skills, (2) more than half of the skills, (3) about half of

the skills, (4) less than half of the skills, and (5) none or almost

none of the skills. In follow-up research, Loewenstein and

Spletzer analyze the 1993 NLSY79 data and find that 63 percent

of workers receiving employer-provided formal training respond

that “all or almost all” of the skills they learned at one employer

are useful in doing the same kind of work for a different

employer.24 This finding suggests that the skills individuals are

learning in their employer-provided

training have a large general component.

Loewenstein and Spletzer estimate wage and mobility

equations with the 1993 general and specific training data as

the key explanatory variable. Their wage regressions show,

first, that there is no systematic relationship between the

degree of generality of the training and its wage return in the

job that provided the training and, second, that the return to

training received from previous jobs exceeds the return to

training received at the current job, for all degrees of

generality. If these results are compared with those from a

similar specification using data on the type of training

(question 20 in table 1) instead of on the degree of generality,

then the first result holds, whereas the second result holds

for school training, but not for company training. This finding

leads Loewenstein and Spletzer to discuss the pros and cons

of the two training measures. They hypothesize that the type

of training data conveys different information than does the

self-assessed generality of training data. For training to be

truly general, not only must the skills be useful at other

employers, but also, other employers must observe and value

the generality of those skills. The generality-of-training

question in the 1993 NLSY79 asks the individual’s opinion

about whether the skills learned in the training are useful

elsewhere, but this is not equivalent to asking alternative

employers about the transferability of skills. By contrast, the

question on type of training not only proxies for the

generality of the skills imparted by training, but also conveys

information about how likely other prospective employers

are to observe these skills. For example, school training might

easily be certified for other employers to see its value, but it

may be difficult for prospective employers to observe the

usefulness of skills learned in company training. Such

reasoning leads Loewenstein and Spletzer to speculate that

information on the type of training may be preferable to a

directly asked question as a measure of generality. However,

as they suggest, the evidence for such speculation is limited,

and the research community would benefit from asking the

question on degree of generality in more than 1 year.

HUMAN-CAPITAL THEORY GAINED ITS PRESENT PROMINENCE in labor

economics more than four decades ago. The simple humancapital model has empirically testable predictions regarding

the relationships among wages, mobility, and training. Testing

these predictions requires microdata with detailed

longitudinal information on training, individual wages, and

job mobility—data that were not available at the time humancapital theory was originally developed. As we celebrate the

25th anniversary of the NLSY79 cohort, we are not surprised

that much of the empirical knowledge about worker training

has come from analyses of the data in that survey.

But any good literature review raises as many questions

as it answers, and this article has tried to highlight some of
Monthly Labor Review February 2005 57

the issues that could benefit from further analysis and

enhancements to the questionnaire. Three specific topics

warrant mention. First, there is new theoretical and empirical

research into the topic of why employers appear to pay for

general training, and the NLSY79 data are likely to play an

important role in the continuing development of this literature.

Second, training is not always a well-defined concept, and

any survey’s measures of the incidence and duration of

training undoubtedly contain measurement error; analyzing

the amount, consequences of, and statistical remedies for

measurement error is a topic that is well worth exploring.25

Finally, any distinctions there are among formal training,

informal training, and learning by doing have been ignored in

this article; the NLSY79 has asked questions regarding

informal training, but economists have not yet studied the

responses to those questions in depth.26 

Notes

1

 See Gary Becker, “Investment in Human Capital: A Theoretical

Analysis,” Journal of Political Economy, October 1962, pp. 9–49,

and Human Capital: A Theoretical and Empirical Analysis with

Special Reference to Education (Cambridge, MA, National Bureau of

Economic Research, 1964); Theodore W. Schultz, “Investment in

Human Capital,” American Economic Review, March 1961, pp. 1–

17; and Jacob Mincer, “Investment in Human Capital and Personal

Income Distribution,” Journal of Political Economy, August 1958,

pp. 281–302.

2

 See David A. Jaeger, “Estimating the Returns to Education Using

the Newest Current Population Survey Education Questions,”

Economics Letters, March 2003, pp. 385–94.

3

 The formal mathematical model was worked out by Masanori

Hashimoto in “Firm-Specific Human Capital as a Shared Investment,”

American Economic Review, June 1981, pp. 475–82.

4

 This greater likelihood has been shown by many authors using

many data sets. For example, see the analysis of the National

Longitudinal Survey of the High School Class of 1972 (NLSHS72) data

by Joseph G. Altonji and James R. Spletzer, “Worker Characteristics,

Job Characteristics, and the Receipt of On-the-Job Training,”

Industrial and Labor Relations Review, 1991, pp. 58–79; the analysis

of Current Population Survey (CPS ) data by Norman Bowers and Paul

Swaim, “Recent Trends in Job Training,” Contemporary Economic

Policy, 1994, pp. 79–88; the analysis of Panel Study of Income

Dynamics (PSID) data by Greg J. Duncan and Saul Hoffman, “On-theJob Training and Earnings Differences by Race and Sex,” Review of

Economics and Statistics, 1979, pp. 594–603; and the analysis of the

NLSY79 data by the authors cited in the later sections of this article.

5

 Jacob Mincer, “On-the-job training: Costs, returns and some

implications,” Journal of Political Economy, October 1962, pt. 2,

pp. 50–79.

6

 Jacob Mincer, Schooling, Experience, and Earnings (New York,

Columbia University Press, 1974).

7

 Later research found that earnings profiles were better described

by a quartic function of experience; see Kevin M. Murphy and Finis

Welch, “Empirical Age-Earnings Profiles,” Journal of Labor

Economics, April 1990, pp. 202–29.

8

 See Boyan Jovanovic, “Job Matching and the Theory of

Turnover,” Journal of Political Economy, October 1979, pp. 972–

90; Edward Lazear, “Agency, Earnings Profiles, Productivity, and

Hours Restrictions,” American Economic Review, September 1981,

pp. 606–20; and Joanne Salop and Steven Salop, “Self-Selection and

Turnover in the Labor Market,” Quarterly Journal of Economics,

November 1976, pp. 619–27.

9 Greg J. Duncan and Saul Hoffman, “On-The-Job Training and

Earnings Differences by Race and Sex,” Review of Economics and

Statistics, November 1979, pp. 594–603; and James N. Brown, “Why

Do Wages Increase with Tenure? On-the-Job Training and Life-Cycle

Wage Growth Observed within Firms,” American Economic Review,

December 1989, pp. 971–91.

10 Lee A. Lillard and Hong W. Tan, “Private Sector Training: Who

Gets It and What Are Its Effects?” Research in Labor Economics,

vol. 13, 1992, pp. 1–62.

11 Found at http://www.nlsinfo.org/nlsy79/docs/79html/79text/

training.htm.

12 As mentioned in footnote 1 of table 1, the training questions in

1988, 1996, 1998, and 2000 have a 2-year reference period, whereas

the training questions in 1989–94 have a 1-year reference period.

13 Lisa M. Lynch, “Private Sector Training and the Earnings of Young

Workers,” American Economic Review, March 1992, pp. 299–312.

14

 Jonathan R. Veum, “Sources of Training and their Impact on

Wages,” Industrial and Labor Relations Review, July 1995, pp. 812–26.

15 Daniel Parent, “Wages and Mobility: The Impact of EmployerProvided Training,” Journal of Labor Economics, April 1999, pp.

298–317.

16 Paul A. Lengermann, “How Long Do the Benefits of Training

Last? Evidence of Long Term Effects across Current and Previous

Employers,” Research in Labor Economics, vol. 18, 1999, pp. 439–61.

17 Harley Frazis and Mark A. Loewenstein, “Reexamining the

Returns to Training: Functional Form, Magnitude, and Interpretation,” BLS working paper no. 367, Journal of Human Resources,

forthcoming, spring 2005.

18 Lisa M. Lynch, “The Role of Off-the-Job vs. On-the-Job

Training for the Mobility of Women Workers,” American Economic

Review Papers and Proceedings, May 1991, pp. 151–56.

19 Mark A. Loewenstein and James R. Spletzer, “Delayed Formal

On-the-Job Training,” Industrial and Labor Relations Review, October

1997, pp. 82–99.

20 Anne Beeson Royalty, “The Effects of Job Turnover on the

Training of Men and Women,” Industrial and Labor Relations Review,

April 1996, pp. 506–21.

21 Mark A. Loewenstein and James R. Spletzer, “Dividing the Costs

and Returns to General Training,” Journal of Labor Economics,

January 1998, pp. 142–71.

22 See, for example, John M. Barron, Dan A. Black, and Mark A.

Loewenstein, “Job Matching and On-the-Job Training,” Journal of Labor
 58 Monthly Labor Review February 2005

Worker Training

Economics, January 1989, pp. 1–19; and John M. Barron, Mark C.

Berger, and Dan A. Black, “Do Workers Pay for On-the-Job Training?”

The Journal of Human Resources, spring 1999, pp. 235–52.

23 For recent studies on the growing literature of why employers

may share the costs of, and returns to, general training, see John

Bishop, “What We Know about Employer-Provided Training: A

Review of the Literature,” Research in Labor Economics, vol. 16,

1997, pp. 19–87; Daron Acemoglu and Jorn-Steffen Pischke, “Why

Do Firms Train? Theory and Evidence,” Quarterly Journal of

Economics, February 1998, pp. 79–119, and “ The Structure of Wages

and Investment in General Training,” Journal of Political Economy,

June 1999, pp. 539–72; Alison Booth and Mark Bryan, “Who Pays

for General Training? New Evidence for British Men and Women,”

discussion paper no. 486 (Bonn, Institute for the Study of Labor (IZA),

2002); and Alison Booth and Gylfi Zoega, “Is Wage Compression a

Necessary Condition for Firm-Financed General Training?” Oxford

Economic Papers, January 2004, pp. 88–97.

24 Mark A. Loewenstein and James R. Spletzer, “General and

Specific Training: Evidence and Implications,” Journal of Human

Resources, fall 1999, pp. 710–33.

25 For an analysis of the extent of measurement error in training in

an employer data set, see John M. Barron, Mark C. Berger, and Dan A.

Black, “How Well Do We Measure Training?” Journal of Labor

Economics, July 1997, pt. 1, pp. 507–28. For a start on the extremely

complicated topic of statistical consequences of, and remedies for,

measurement error, see Harley Frazis and Mark Loewenstein,

“Estimating Linear Regressions with Mismeasured, Possibly

Endogenous, Binary Explanatory Variables,” Journal of Econometrics,

November 2003, pp. 151–78, and the working-paper version of

“Reexamining the Returns to Training.”

26 A first pass at analyzing these responses is Mark A. Loewenstein and

James R. Spletzer, “Formal and Informal Training: Evidence from the

NLSY79,” Research in Labor Economics, vol. 18, 1999, pp. 403–38.