^0.058 At
DIFFERENTIAL EFFECTS ON POST-SCHOOL TRAINING ON
EARLY CAREER TRAINING
by
Lisa M.
WP# 3358-91 -BPS
Lynch
November 1991
DifTerential EfTects of Post-School Training
on
Early Career Mobility
by
Lisa
MIT
M. Lynch
and NBER
November 1991
*I would like to thank participants of seminars at MIT, Boston College, the U.S.
Department of Labor, the World Congress of the Econometric Society in Barcelona, Spain,
and Uppsala University, Uppsala Sweden. This project was funded by the U.S. Department
of Labor, Bureau of Labor Statistics under grant number E-9-J-9-0049. Opinions stated in
this paper do not necessarily represent the official position or policy of the Department of
Labor.
Author's Address:
Professor Lisa
M. Lynch
IRI Associate Professor of Industrial Relations
E52-563, MIT Sloan School of Management
50 Memorial Drive
Cambridge,
MA 02139
1
While the number of studies on the incidence of private-sector training and
on wages and productivity has been increasing (recent
Barron
(1991),
Hoffman
virtually
et.
(1979), lillard
no
impact
studies include Altonji
and Spletzer
Brown
Duncan and
(1988), Bartel (1989), Bishop (1991),
al.
its
(1989),
and Tan (1986), Lynch (1992), and Mincer(1988)) there has been
analysis of the impact of private-sector training
young workers. Yet firms
that
make investments
about the turnover of their trainees.
on the mobility patterns of
in workers' training are very
concerned
At the same time there are other forms of
private-
sector training such as training programs provided by proprietary institutions off-the-job that
individuals can use to
lack of analysis
move
out of dead end jobs and into a higher paying career track.
The
on training and mobility has been due primarily to the lack of detailed
information on the timing and source of private-sector training and employment spells
the United States.
in
Surveys of employers' training practices are useful for examining the
impact of training on wages and productivity but they are
less useful for
examining the
patterns of job changes of workers and the role of training in these changes. Longitudinal
surveys of individuals that follow workers over time and across employers, are
much more
useful for examining this type of issue.
This paper focuses on the role of different types of training on the probability of
leaving an employer.
In
Lynch (1992) the impact of private-sector training on the
determinants of wages and wage growth of young workers was examined and the following
conclusions were reached.
be highly firm specific
Company provided
First,
formal company provided training, or ON-JT, appears to
in the U.S. and, therefore, not portable
training raises
wages
in the current
from employer
to employer.
job but has no effect on the wages
earned in subsequent employment.
Second, formal training received from
proprietary institutions, or OFF-JT, has
but
it
little
effect
'for-profit'
on the wages earned on the current job
does raise the expected wage in subsequent employment. Finally, there are important
differences by race, gender and education level in the probability of receiving different types
of formal training and the impact this training has on wages and wage growth.
These findings have several implications
implication
is
that
if
company provided
of leaving an employer should decline
training.
An
additional implication
programs they are more
training allows a
training
if
is
is
primarily firm specific then the probability
a young worker has experienced
that
if
workers participate
likely to leave the current
young worker
to
employer.
the factors that influence the probability of
profit'
on-the-job
in off-the-job training
In this case, off-the-job
company provided
new
this
paper examines
entrants leaving their
training, apprenticeships
first
in detail
job including the
and training from
'for-
proprietary institutions.
There are a variety of explanations of why young workers change
status so often in the early years of their careers
stable
some
change career paths and find a 'better match'. Using data
from the National Longitudinal Survey Youth cohort, NLSY,
differential effects of
on mobility. One
for the impact of training
employment.
and then seem
their
to 'settle
For example, young workers are more hkely
to
employment
down' into more
be
laid off in a
downturn than older more experienced workers. There are other explanations of the higher
turnover rates of young workers, however, that have
little
to
do with the
state of
Such theoretical explanations include job search, job matching and on-the-job
search theory, as detailed by
Lippman and McCall
demand.
training.
Job
who
earn
(1976), predicts that workers
more
relative to their alternative
learning
wage are
less likely to quit
model (1979a, 1979b, 1984) both workers and firms
On
'learn'
about the unobserved
in this
the one hand, 'better' workers remain with employers longer leading to
On
negative duration dependence in the probability of leaving a job.
'bad'
In the Jovanovic
There are two main predictions on turnover
characteristics of each other over time.
framework.
a job.
matches are revealed the turnover probability
of on-the-job training within the
human
capital
will rise
the other hand, as
over time. Finally, the process
model as described by Mincer (1974) implies
that as workers acquire firm-specific training, their productivity and, consequently wages, will
rise.
Therefore, the probability of leaving an employer will
since the
wage
will rise relative to the alternative
likely to lay off those
workers
in
whom
fall
with training and tenure
wage. In addition, employers
they have invested in specific
All of these theories are not mutually exclusive and clearly
will
be
less
skills.
some combination
of
all
of these factors influences the probability of a young worker remaining with an employer.
Consequently,
it
theories. Rather,
is
it
not the purpose of this paper to distinguish between these different
would be more useful
if
precise data
on employment
spells
and training
could be found in order to establish the links between different types of training and
turnover behavior.
There have been
role of training,
relatively
demand and
few empirical studies that have attempted to examine the
other factors in predicting the probability of leaving an
employer. Recent exceptions include Gritz (1988) and Mincer (1988). Gritz used data from
the early years of the
between
NLSY
and found that private sector training (not distinguishing
different sources of training) increased the
amount of time
in total
employment
for
females but decreased the amount of time males were employed. Gritz's study used data
from the very early years of the
NLSY when
most of the observed training
spells occurred
before the detailed employment history in the survey begins. Mincer used data on training
and mobility from the Panel Study of Income Dynamics, PSID. The training variable comes
from the answer
yours
how
While
to the following question in the 1976
long does
it
new person
take the average
this is potentially a
to
and 1978 interviews: "On a job
become
very broad measure of training
training has actually occurred for the specific respondent.
PSID data to observe when
and qualified?"
does not measure
it
It is
how much
also not possible with the
the training occurred during an employee's tenure with the firm.
Using data from the
NLSY
possible to examine in
it is
possible in the past the role of training, the general state of
characteristics in determining turnover.
sector training for
fully trained
like
young workers
In particular,
I
United States
in the
more
detail than has
been
demand, and other personal
examine the incidence of privatein the early years after they
completed school; the timing of employer provided training versus training received
have
off-the-
job from proprietary institutions over a worker's tenure on the job; and the impact of
different types of private sector training
on the probability of leaving an employer.
Empirical Framework
For the analysis presented
NLSY
is
in this
paper a subsample of the
NLSY
is
used.
The
a survey of 12,686 males and females (who were 14 to 21 years of age at the end
of 1978) and contains detailed data on education, jobs, military service, training programs
marital status, health and attitudes of young workers.
interviewed every year since 1979 on
all
The respondents have been
aspects of their labor market experience.
The
The data on
response rate in 1985 was over 95 percent of the original cohort.
training (other than governmental training or schooling) received are
comprehensive data available on private sector
training.
the most
Respondents were asked about
what types of training they had received over the survey year (up to 3
longest)
some of
types of
spells not just the
and the dates of training periods by source. Potential sources of training included
business college, nurses programs, apprenticeships, vocational and technical institutes, barber
or beauty schools, correspondence courses and
training
company
programs are independent from training received
program which
is
All of the types of
training.
in
a formal regular schooling
However, the questions ask about
included in the schooling variables.
only those spells of training that lasted at least 4 weeks (they did not have to be
This suggests that the
spells
NLSY
measure of training
than informal on-the-job training.
training
was dropped from the
this restriction
affect the
NLSY
is
survey.
capture formal training
weeks or more of
therefore possible to see the impact of
It is
on the measurement of the incidence of
of off-the-job training or apprenticeships.
likely to
In 1988 this restriction of 4
measurement of the incidence of company
who were 25
more
full time).
training.
training
The
restriction only
and not the reported incidence
For a sample of non college graduates
years old, 3.8 percent had four weeks or
seems
more of company
in
1988
training while 10,2
percent had company training of any length. The following percentages of females(males)
had 4 weeks or more of on-the-job training versus
7.1%(12.9%). Therefore,
4
week
restriction
underestimated.
in the following analysis
OJT
of any length
-
1.4%(5.9%) versus
which uses data from 1979-1987 when the
apphed, the number of company provided training spells with be
However, from the point of view of
firms, the turnover probabihties of
those trainees in the longer spells of training
The
is
a major concern.
training data are separated into three categories
~ company
training (ON-JT),
apprenticeships (APPT), and training obtained outside the firm (OFF-JT).
training obtained
OFF-JT includes
from business courses, barber or beauty school, nurses programs,
vocational and technical institutes and correspondence courses.
Each of these three
types
of training are allowed to have different effects on the probability of leaving an employer.
For the empirical work
subsample
in the
NLSY
I
from the
have excluded the 1280 respondents in the military
analysis.
I
have also deleted any respondent
completed school before the 1979 interview year. The
young workers who have
left
--
those
who
their first four years in the labor
had
to
have obtained a job
not include anyone
market
in the first
who completed
reduced. In addition,
(1979-1983).
Therefore, this sample
I
this
a pooled sample of
made up
after leaving school.
of 5 waves of school
They are then followed
year after 'permanently' exiting school.
to
model the decision
was a period
entry into the labor market given the high
in
for
In addition, the respondents
school before 1979 the sample size
do not attempt
Obviously
is
1979, 1980, 1981, 1982 and 1983.
left in
is
has
school and not returned to school for at least four years
('permanently' out of school).
leavers
sample
final
who
is
Since
I
do
substantially
to leave school over the period
which many young people may have delayed
I
include
dummy variables
work would
benefit
from a complete
unemployment
for year of entry in the following analysis but future
rate.
modeling of the schooling / employment / training decisions taken by young workers.
The
first
empirical
work estimates the determinants of the turnover
job after leaving school permanently for
this
probability for the
sample. Characteristics of this sample are
presented in Table
their first
1.
As can be seen
employer during the
employment (including those
first
still
in this table,
almost three quarters of the sample
The average duration of
four years after school.
employed
after four years)
left
was about a year and a
half.
Almost seventeen percent of the sample experienced some form of formal training during
their first job but the distribution of this job training
by source varied substantially by
demographic group. College graduates were much more
likely to
of
ON-JT while
in
some form of OFF-JT.
of
OFF-JT but
those with just a high school diploma were
Women
there was
little
were more
than
It is
some of
this
some form
to have received
ON-JT
important to note that some of the
demographic group are extremely small and
interpreting
men
have participated
likely to
difference in the probability of receiving
(not controlling for other factors).
training by
likely
more
have received some form
needs to be kept
by gender
cell sizes for
mind when
in
the following results.
Table 2 presents more detailed information on the relationship between tenure on
the job with the
first
employer and the various types of
over 80 percent of the sample have
market. Those
who
left their
any formal ON-J-T (only
1.3
more (8.1%). The pattern
a quarter of those
this
who
is
left their first
employer
%)
training.
who
were much
stayed with their
a bit different with participation in
left their first
first
panel shows that
employer by the fourth year
relatively early
than those
The
in the labor
less likely to
first
have had
employer 3 years of
OFF-J-T programs. Almost
job between 2-3 years received OFF-J-T.
However,
percentage drops dramatically for those with 3 or more years on the job to only 11.7
percent.
The second panel
is
perhaps even more interesting. This panel shows, conditional
8
on having participated
in
one of the types of private
during the tenure with the employer.
that
it
is
a
(Weiss and
'test'
programs as a way to
Workers who
imply that
However,
on the job
fail
we
is
when
that training spell begin
discussed in Lynch (1992) one view of training
(1990)).
is
In other words, firms use formal training
avail themselves of private information
the test leave the firms and those
who
known
only by the workers.
This would
pass do not leave.
should observe ON-J-T occurring early in a workers's tenure with the firm.
in this
second panel we see that 60 percent of ON-J-T spells began after one year
at the firm.
firms(workers)
Wang
As
training,
make
a match, and
if
This seems to be more consistent with a job matching story where
a determination within the
yes, the firm
measure of training used
in this
first
6-12 months on whether or not there
then invests in more costly formal ON-J-T.
paper only captures
spells that last
4 weeks
Since the
it
may be
possible that shorter formal or informal training spells are used early in the career with an
employer as an indication of match quality and longer training
examined the timing of on-the-job training
their
employer for more than 3 years.
trainees, (note the
sample
after the first year
on the
size
is
spells follow later.
for those individuals
For
this
I
who had remained
also
with
subsample, as for the larger group of
becoming quite small) the majority began
their training
job.
Contrary to the timing of ON-J-T spells almost 60 percent of spells of OFF-J-T began
within the
first
year with an employer. This
to obtain training that they
need
may be due
to
for their current job, or
employees going outside the firm
employees deciding that there
is
not a job match and seeking a training program that will allow them to leave their current
employer and get a better job.
While off-the-job training may be funded by either the
individual worker or the firm, there
of those
who
participate in
is
evidence in the
OFF-JT pay
1988 survey that the majority
for the training themselves.
most apprenticeships begin very early
surprisingly,
NLSY
in the
Finally
and not
tenure with an employer.
A convenient method for analyzing the determinants of the probability of leaving an
employer
is
estimating the hazard rate or failure rate as
it is
called in renewal theory.
The
hazard rate or turnover probability can be expressed as follows:
where
g(t)dt
is
g(t)dt/(l
employment. In
this
employed
G(t))
at
time
t,
and
t
is
t
and
h(t;z)
=
ho(t)e
t
+ dt,
is
characteristics including training.
The Cox model
censoring and
in the sense that
is
nonparametric
G(t)
is
used:
zB
an arbitrary and unspecified base-line hazard function and z
it
1 -
the duration of the current spell of
paper the following Cox proportional hazards model
(2)
ho(t) is
-
the probability of leaving an employer between time
the probability of being
where
=
h(t)
(1)
is
it
is
a vector of
convenient for dealing with right
involves an unspecified base-line
hazard instead of making further distributional assumptions such as those required for the
Weibull or Log-logistic hazard. However,
whether or not there
is
is
this
means
that
it
will
not be possible to measure
negative or positive duration dependence in employment, but this
not a key focus of this paper.
10
Another possible empirical approach
probability of leaving an employer over
strategy
is
that the choice of the interval
to estimate a logit or probit
is
some
is
interval.
somewhat
model of the
The problem with
arbitrary.
this estimation
In addition,
to incorporate time varying regressors such as training into this approach.
0-1
it is
not easy
However, the
hazard framework can easily allow for time varying factors or covariates such as training.
The hazard
including time varying covariates
h(t;z(t))
(3)
where
z(t) is
a vector of
all
fixed
of
variables
-
modified as follows:
= ho(t)e^W«
and time varying covariates.
Oakes (1984) the components of the vector
categories
is
treatments
z(t)
that
As
discussed in
Cox and
can be divided into the following three
with
vary
time;
intrinsic
properties
of
individuals/jobs that are time invariant; and exogenous time varying variables.
Obviously the different types of private sector training are the 'treatment' variables
of interest. Examples of time invariant personal and job characteristics include gender, race,
education, occupation, industry, union status, location of the job in an urban area, and
whether or not the respondent
purpose of
is
Time
disabled.
this study include the local
varying 'exogenous' variables for the
unemployment
rate, marital status
and the number
of children.
Empirical Results
The
results obtained
from estimating the Cox proportional hazard with time varying
covariates are presented in Tables 3 and 4.
The time
11
varying covariates are indicted by an
The time
asterisk.
equation
seemed
that
1,
invariant intrinsic characteristics of the individuals/jobs in Table 3,
to influence the probabiHty of leaving
disabled, union status, race,
and school
level.
an employer included being
Disabled respondents were more likely to
leave their employer while being employed in a job covered by a collective agreement or
being a college graduate significantly lowered the probability of leaving the
Blacks were more likely to have shorter durations on their
hispanics.
gender.
There was no
Therefore,
it
significant effect
first
employer.
first
job than whites and
on the length of time with the
employer by
first
appears that employer concerns of investing in female employees
because they have a higher probability of leaving an employer are not upheld by
There were
significant differences in expected length of
Those with a high school degree or
less
were more
this data.
employment by school attainment.
likely to leave their
employer, whereas
those with a college degree were less likely to leave.
Of
the
time varying 'exogenous' covariates the local unemployment rate was
significant implying that those
leave their employer.
who
The hurdle
lived in high
for youths in high
getting a job rather than keeping one.
significant effect
With regards
JT were much
of
likely to
less likely to leave their
OFF-JT
more
seemed
job. Finally, those
to
workers
have no
who were
young people who had some formal ON-
employer while those who participated
in
some form
ON-JT
is
more
likely to leave.
is
of children
to be
their first employer.
to the training variables, those
OFF-JT were more
specific while
remain with
first
we^^e less likely to
unemployment areas seems
The number
on the expected duration of the
married were more
unemployment areas
'general'.
This seems to suggest that
These findings are consistent with the
12
firm
results
on
tr ainin g
and wages found
in
Lynch (1992).
In equation 2 the hazard
The
is
re-estimated including industry and occupation dummies.
inclusion of industry and occupation does not change the coefficients or significance of
with the exception of college which becomes insignificant. Those
the variables in equation
1
young workers employed
in construction,
wholesale and
and professional services were much more
manufacturing.
to
remain with
The
retail,
and business,
likely to leave their
repair, personal
employers than those in
only significant occupation was managers with managers
more
likely
their first employer.
In equation 3 of Table 3 an additional variable
is
added which
is
the difference
between the log of the current wage (which varies with time) and a log predicted wage. The
predicted
wage
is
obtained by the formula in Table
from a log wage equation for the
starting
wage
1
which uses the estimated coefficients
for this sample.
Those individuals who were
being paid less than their predicted alternative wage were more likely to leave their
employer as shown
from equations
1
in
both equations 3 and 4 of Table
Now
examined. Again,
is
how
of the previous findings
re-estimated for various demographic groups
the results change dramatically depending
it is
important to remember that some of the
care must be taken in interpreting the results in Table
to see
None
and 2 are altered very much.
In Table 4 the proportional hazard
of interest.
3.
4.
the results from the previous table change
upon which sub-group
cell sizes
Nevertheless,
when
is
are very small so
it is
the sample
interesting
is
divided into
demographic categories of interest. For example, males, females, and blacks who were high
school dropouts had a shorter expected duration on the
13
first
job after they
left
school.
However, being a male or black high school graduate had no
effect
on the duration of
employment, while being a female high school graduate lowered the duration of
employment.
Male and black
employment, while there was no
remaining with their
The
first
college
graduates had longer expected durations of
effect of a college
degree on the probability of females
employer.
differences by race and gender are even starker
For women, having additional children
regressors and the effect of training.
lowered the expected duration of their
additional children.
first
job relative to those
At the same time, there was no
duration of male or black employment.
for
ON-JT and OFF-JT were
males and blacks. However,
first
job for females while
When
the sample
emerge. For example, those
effect of children
ON-JT
significantly
did not have
on the expected
effect of marital status for blacks.
insignificant determinants of the duration of
OFF-JT
is
women who
varying
Being married lowered the probability of leaving
an employer for males and females but there was no
Finally,
when one examine time
employment
increased the length of time in employment in the
increased their turnover probability.
divided by educational attainment other interesting results
who were
high school graduates or had
some post high school
education and were covered by a collective agreement, were less likely to leave their
employer. For the sample as a whole there was no difference in the probability of leaving
an employer between males and females.
However, when the sample was divided by
educational level, males were less Hkely to leave their employer than females
than a high school degree or
if
they had
some
if
they had a college degree, but they were
more
if
they had less
likely to leave
post high school education. In addition, being black raised the probability
14
of leaving an employer only
if
the young worker had a high school degree.
Race was not
a significant factor for any of the other educational groups.
The number
of children
seemed
to affect the duration of
employer only for high school graduates, while marital status was
employment with the
first
significant only for college
graduates and high school dropouts. In addition, the unemployment rate was only significant
for high school graduates. Finally,
ON-JT appeared
respondent had a high school degree or
less,
while
to lower the turnover probability
OFF-JT seemed
Given the small
for those with a high school degree.
drawing conclusions on variables that are
insignificant,
cell sizes
if
the
to raise this probability
one must be cautious
in
but the different effects of variables
of interest by race and gender are quite striking.
Conclusions
This paper has focused on the link between training and the probability of leaving
an employer.
A high percentage of ON-J-T spells begin after young workers have remained
with their employer for at least one year. This seems to be consistent with a job matching
story
where firms(workers) make a determination within the
or not there
is
a match, and
if
yes, the firm
contrast to the pattern associated with
begin within the
first
first
6-12 months on whether
then invests in more costly formal ON-J-T. In
ON-J-T spells, almost 60 percent
year with an employer. This
may be due
to
of spells of OFF-J-T
employees going outside
the firm to obtain training that they need for their current job, or employees deciding that
there
is
not a job match and seeking a training program that will allow them to leave their
ciurent employer and get a better job.
There are
significant differences in the patterns of job mobility
15
by race and gender.
Overall there
is
no difference
However, when the sample
is
divided by race, gender, and educational attainment there are
important differences between males and females.
little
a
significant
men
to
and positive
Among
effect
are
have shorter
more
spells their first job, but there
more
in the U.S.
general.
among
likely to leave their
Evidence presented
workers
on the probability of
women
high school dropouts and college graduates
school graduates. In contrast,
men
For example, children appear
have
to
on the probability of males leaving an employer. At the same time, they have
affect
employer.
an employer by gender.
in the probability of leaving
The
in
those
are
more
than
no gender difference among high
post high school education
Lynch (1992) indicated that on-the-job training
training are
likely
employer.
results presented in
would be consistent with firm
women
who have had some
appeared to be quite firm
Those with on-the-job
is
not remaining with their
more
specific
specific training.
young
whereas off-the-job training appeared
Tables 3 and 4 seem to reinforce
likely to
for
remain longer with
Although
women
their
this conclusion.
employer which
are less likely to receive
on-the-job training the finding of on-the-job training lowering the probability of leaving an
employer was particularly strong for women. This may be because
women realize
that
many
employers are reluctant to invest in their training so that when they do receive company
training they are
training are
more
training being
more
likely to
remain with that employer. Those who obtain off-the-job
likely to leave their
more
general.
educational attainment
we
employer and
Again,
when
this
would be consistent with
the sample
is
off-the-job
divided by race, gender and
see that the off-the-job training variables are only significant in
the equation for females.
16
Overall
it
appears that blacks are more
true for those blacks
who
likely to leave their
employer but
received just a high school diploma. There does not
this
is
seem
only
to
be
any significant difference in the results for hispanics relative to whites. Finally, there does
seem
to
be some evidence that blacks who receive some on-the-job training have longer
expected job durations in their
While
this
first
job.
paper has attempted to shed new
young workers and the consequences of this on
issues that
of the
first
light
on the
skill
formation process of
their patterns of mobility there are
still
many
remain unresolved. This paper has modeled the determinants of the duration
job after school, not subsequent employment. As the
should examine
how some
NLSY
age future research
of the gender, race, and educational differences change over time.
17
REFERENCES
Joseph G. and Spletzer, James R. 1991. "Worker Characteristics, Job
Characteristics, and the Receipt of On-the-Job Training", Industrial and Labor
Relations Review October, 45, pp. 58-79.
Altonji,
.
Barron, John M., Black,
Dan
A.,
and Loewenstein, Mark A. 1987. "Employer Size: The
Wages and Wage
Implications for Search, Training, Capital Investment, Starting
Growth", Journal of Labor Economic January, 5, pp. 76-89.
.
Aim. 1989.
Bartel,
Productivity:
"Formal Employee Training Programs and Their Impact on Labor
Evidence from a Human Resource Survey", NBER working paper
3026.
'The Impact of Previous Skill Development on Current Productivity,
Training Requirements and Turnover", mimeo, Cornell University.
Bishop, John 1991.
Brown, James N. 1989. "Why
Do Wages
Review December,
.
Economic
Increase with Tenure?" American
79, pp. 971-91.
Cox, D.R. and Oakes, D. 1984. Analysis of Survival Data London:
.
Chapman and
Hall.
Duncan, Greg J., and Hoffman, Saul. 1979. "On-the-Job Training and Earnings Differences
by Race and Sex", Review of Economics and Statistics November, 61, pp. 594-603.
.
Mark, 1988. "The Impact of Training on the Frequency and Duration of
Employment", mimeo. University of Washington.
Gritz, R.
Jovanovic, Boyan, 1979a. "Job Matching and the Theory of Turnover", Journal of Political
Economy October, 87, 972-90.
.
Jovanovic, Boyan,
"Firm-Specific Capital and Turnover", Journal of Political
1979b.
Economy December,
.
87, 1246-60.
"Matching, Turnover, and Unemployment", Journal of Political
February, 92, 108-22.
Jovanovic, Boyan, 1984.
Economy
Lillard,
and Tan, Hong. 1986 Private Sector Training:
Effects? Rand Corporation R-3331, March.
Lee
its
.
A.,
Who
Gets
and What are
.
Lippman, Steven and McCall, John, 1976. 'The Economics of Job Search:
I",
it
Economic Inquiry June,
.
14, 155-89.
18
A
Survey, Part
Lynch, Lisa M. 1992. "Private Sector Training and the Earnings of
Young Workers",
American Economic Review March.
.
Mincer,
J.
1974. Schooling. Experience and Earning s.
New
York:
Columbia University
Press.
Mincer,
J,
1988.
"Job Training,
Wage Growth and Labor
Turnover",
NBER
working
paper no. 2090, August.
Wang, R. 1990. "A Sorting Model of Labor Contracts: ImpUcations for
Layoffs and Wage-Tenure Profiles", mimeo, Boston University, June.
Weiss, A- and
19
TABLE
Variable:
1
-
SAMPLE CHARACTERISTICS
(N = 2522)
TABLE
2
-
CHARACTERISTICS OF PRIYATE-SECTOR TRAINING
Completed Tenure by
% with Training by type
Completed Tenure
% of sample
1-26 weeks
33%
27 -52 weeks
20%
1.5%
11.8%
0.9%
2 years
19%
2.6%
15.6%
2.4%
2-3years
7%
6.6%
23.6%
0.5%
3-4years
21%
8.1%
11.7%
0.8%
1 -
ON-JT
1.3%
Conditional on having training in
Year
During
1st
2nd
3rd
1st
year
2nd year
-
-
-
ON-JT
OFF-JT
39.8%
57.2%
25.6%
3rd year
18.8%
4th year
15.8%
OFF-JT
0.7%
10.6%
1st
job
APT
APT
•
when did
it
begin?
TABLE
Variable
3
-
DETERMINANTS OF THE PROBABILITY OF LEAVING EMPLOYER
TABLE
4
-
DETERMINANTS OF THE PROBABILITY OF LEAVING EMPLOYER
BY DEMOGRAPHIC GROUP
Males
Variable
Urban
-.06
(-0.94)
#
Children*
Disabled
-.08
Females
Blacks
-.03
-.01
(-0.37)
(-0.11)
.20
.09
(-0.71)
(2.83)
(0.89)
-.14
.41
.53
(-0.67)
(3.01)
(2.40)
Married*
-.36
(-2.84)
(-1.66)
(-0.27)
Union
-.15
-.44
-.47
(-1.73)
(-4.40)
(-3.67)
Black
.10
(1.30)
Hispanic
.03
(0.35)
-.13
-.05
.10
(1.17)
.02
(0.26)
Male
.05
(0.44)
Less than H.S.
High School
.39
.93
.55
(3.48)
(7.72)
(3.14)
.08
.31
.19
(0.81)
College
-.53
(3.74)
(1.52)
-.04
-.54
(-3.79)
(-0.32)
(-2.40)
Medium Urate*
-.18
-.16
-.15
(-2.27)
(-2.02)
(-1.28)
High Urate*
-.23
-.10
-.34
(-2.66)
(-1.17)
(-2.35)
ON-JT*
-.27
-.36
-.66
(-1.19)
(-1.70)
(-1.43)
OFF-JT*
Apprentice*
.03
.19
(0.27)
(2.09)
-.03
(-0.13)
Log Wage
Diff*
Log Likelihood
Number
of Obs.
.08
(0.57)
.61
-.27
(1.21)
(-0.65)
-.55
-.79
-.62
(-6.18)
(-8.44)
(-4.56)
-6337.3
-6879.4
-2546.9
1208
1314
535
24
TABLE
4
DETERMINANTS OF THE PROBABILITY OF LEAVING EMPLOYER
BY DEMOGRAPHIC GROUP (continued)
Variable
< H.S.
H.S.
Post H.S.
Urban
-.26
-.03
-.03
(-2.01)
(-0.54)
(-0.24)
#
Children*
.06
(0.40)
.12
(1.61)
College
.08
(0.50)
.11
-.03
(0.88)
(-0.13)
Disabled
-.28
Married*
-.53
(-2.81)
(-0.52)
(-1.08)
(-3.22)
Union
-.19
-.20
-.46
-.32
(-1.12)
(-2.47)
(-2.70)
(-0.92)
Black
Hispanic
Male
Medium Urate*
High Urate*
ON-JT*
OFF-JT*
Apprentice*
Log Wage
Diff*
Log Likelihood
Number
of Obs.
^238
.40
-.25
(-0.77)
(2.80)
-.04
-.16
.68
(1.90)
-.55
(-1.55)
.18
-.07
(1.33)
(-0.33)
.02
.15
(0.12)
(2.03)
.20
.01
-.08
(1.45)
(0.15)
(-0.54)
.10
(0.37)
-.38
.005
.22
-.32
(-3.03)
(0.08)
(1.93)
(-2.26)
-.15
-.18
-.15
-.12
(-0.97)
(-2.38)
(-1.05)
(-0.74)
-.19
-.19
-.18
-.08
(-1.10)
(-2.34)
(-1.18)
(-0.48)
-1.19
-.35
-.26
-.12
(-1.65)
(-1.34)
(-0.83)
(-0.48)
-.13
.11
.21
.03
(-0.52)
(1.41)
(1.22)
(0.08)
.58
-.20
.43
(0.43)
(-0.68)
(0.83)
-.34
-.76
-.84
-.67
(-2.30)
(-8.30)
(-4.84)
(-4.00)
-1625.1
-7450.2
-1921.5
-1288.9
363
1363
439
357
.22
25
^Jl9
(1.12)
Date Due
Lib-26-67
MIT LIBRARIES
3 9080
917 7630