Measuring resource utilization in the labor market.
Hornstein, Andreas ; Kudlyak, Marianna ; Lange, Fabian 等
The U.S. unemployment rate increased substantially following the
Great Recession, reaching close to 10 percent in the fourth quarter of
2009. As of December 2014, the unemployment rate has declined by more
than 4 percentage points, faster than many policymakers forecasted at
the time. As unemployment rates declined, labor force participation
rates also declined by about 2 percentage points. This has raised doubts
on the ability of the unemployment rate alone to accurately represent
the state of resource utilization in the labor market. (1) Broader
measures than the standard unemployment rate may therefore be needed to
indicate resource utilization in the labor market.
In this article, we briefly review the extended unemployment
measures of the Bureau of Labor Statistics (BLS), which capture
individuals not usually counted as unemployed. Importantly, these
measures of unemployment assign the same weight to all nonemployed
individuals included in the measures despite there being substantial
differences in labor force attachment among the nonemployed. For
example, those nonemployed who are actively searching for work usually
have a higher transition rate to employment than those who express a
desire to work but do not actively engage in job search activities.
Presumably these persistent differences in transition rates reflect
differences in the degree of labor force attachment.
We therefore proceed to construct an alternative measure of labor
utilization--a nonemployment index--that accounts for differences in
labor market attachment among nonemployed individuals. Our approach
builds on recent advances in our understanding of how individuals
transition between labor market states, identifying labor market
attachment with observed average transition rates to employment. Since
we weight nonemployed individuals by their relative transition rates to
employment, our measure can cover all nonemployed individuals, and we
are not forced to draw arbitrary distinctions on who is to be included
in the set of nonemployed individuals as is necessary even for the usual
BLS extended measures of unemployment.
Even though broader measures of resource utilization, that is, the
extended BLS measures and our nonemployment index, may better reflect
the "true" state of the labor market, the standard
unemployment rate may still represent a valid signal of the cyclical
state of the labor market. (2) We find that prior to the Great Recession
the standard unemployment rate and broader measures of unemployment are
indeed moving closely together. Thus, the broader measures of resource
utilization and the more narrow standard unemployment rate provide the
same signal about the labor market prior to 2007.
After the Great Recession, however, there appears to be a break in
the relationship between the standard unemployment rate and the broader
measures of resource underutilization. Whether this break implies that
the standard unemployment rate understates or overstates the true degree
of resource underutilization in the labor market after the Great
Recession does however depend on the measure of "true"
resource underutilization. If one believes that the BLS measure--the
extended unemployment rate U6, which includes the marginally attached
and those working part time for economic reasons--best reflects the true
state of the labor market, then the standard unemployment rate
understates how much labor in the labor market is idle after 2007. If,
however, we believe that the nonemployed should be weighted by their
workforce attachment, then the standard unemployment rate overstated
true resource underutilization for most of the post-2007 period and
provides a more or less accurate representation of labor resource
underutilization as of 2014.
Our analysis thus shows that the standard unemployment rate will
not always accurately reflect "true" underlying resource
underutilization. In particular, taking the nonemployment index as a
"true" measure of labor resource underutilization, the
discrepancy (or lack thereof) between the signal and the true measure
depends on the composition of the nonemployed population by their degree
of work attachment.
More than 30 years ago, Flinn and Heckman (1983) pointed out that
the distinction between those being unemployed and those being out of
the labor force is not clear cut but a matter of degree. Recently, and
mostly in the context of estimating matching efficiency of the labor
market, Veracierto (2011), Diamond (2013), Elsby, Hobijn, and Sahin
(2013), and Hall and Schulhofer-Wohl (2013) have argued that it is
important to account for the job seekers out of the labor force in
addition to the unemployed. Furthermore, Hornstein (2012) and Krueger,
Cramer, and Cho (2014) have argued that even within the group of
unemployed the pattern of long-term unemployment suggests significant
differences in employability. (3) Kroft et al. (2013) explore how
differences in transition rates to employment across unemployed with
different unemployment duration and those out of the labor force (OLF)
shaped the evolution of the U.S. labor market over the Great Recession.
To our knowledge, our nonemployment index is the first measure that
consistently aggregates different categories of the nonemployed using
observed differences in employability. Similar measures of labor market
resource utilization were constructed for the United Kingdom (see Jones,
Joyce, and Thomas [2003]; and Schweitzer [2003]).
This article is structured as follows. We first characterize
differences in workforce attachment among the nonemployed in terms of
their average transition rates to employment. We then review the various
(extended) unemployment rates constructed by the BLS and construct an
alternative index of nonemployment that weights its components according
to their workforce attachment. Finally, we evaluate the quality of the
standard unemployment rate as a signal for broader measures of
nonemployment.
1. HETEROGENEITY OF NONEMPLOYMENT The BLS Classification Scheme
Among the most widely reported statistics from the BLS are the
shares of the working-age population who are currently employed,
unemployed, and OLF. These shares are estimated using responses from the
monthly Current Population Survey (CPS). A nonemployed respondent is
counted as unemployed if she has been actively looking for work in the
month preceding the survey week. Those neither employed nor actively
looking for work are classified as OLF. Starting with the comprehensive
revision of the CPS in 1994, the BLS provides additional detail on the
labor market attachment of the nonemployed based on survey responses as
to why an individual is not actively looking for work. The average
population shares for the different nonemployment categories in the CPS
are listed in Table 1, columns 1 through 3. We report these shares for
the period 1994-2014 and the years 2007 and 2010, that is, the year
prior to the Great Recession and the year when unemployment reached its
peak.
The unemployed can be subdivided based on their reported length of
unemployment. Short-term unemployment (STU) covers those who have been
unemployed for 26 or fewer weeks, while long-term unemployment (LTU)
encompasses those who have been unemployed for more than 26 weeks. On
average, only one-fourth of all unemployed report more than 26 weeks of
unemployment in any one month, but the share of LTU increased to close
to one-half following the Great Recession.4
The unemployed represent only one-tenth of those without
employment. The remaining nine-tenths are OLF.
Over nine-tenths of those OLF do not want a job. Among these
individuals we can distinguish between those who are retired, disabled,
currently in school, and the remainder. On average, the retired and
disabled account for about two-thirds of those who do not want work.
Following the Great Recession we saw a noticeable increase in the
disabled and those attending school.
While most OLF do not want a job, a little less than one-tenth
declare that they do want to work, even though they did not actively
look for work in the previous month. Those in this group who want a job,
are available for work, and searched for work within the last year (not
the last month) are classified as marginally attached. On average, about
one-fourth of those who want work are marginally attached, and there are
twice as many unemployed as there are marginally attached respondents.
Those marginally attached who did not search for a job during the last
month because they were discouraged over job prospects are classified as
discouraged. On average, discouraged individuals make up about one-third
of the marginally attached, but following the recession their share
increased noticeably.
Transition Rates to Employment
We are motivated to examine broader unemployment concepts since the
distinction between unemployment and OLF is not as sharp as one would
think. In fact, from month to month, roughly twice as many individuals
transition from OLF as opposed to unemployment to employment. We now
show that the transition rates to employment are indeed positive for all
nonemployed, but that there is also substantial heterogeneity in
transition rates among the nonemployed. We also show that the pattern of
average transition rates to employment among the nonemployed seems to be
consistent with the self-reported labor market attachment.
We first use the CPS microdata to construct transition
probabilities from nonemployment to employment using the short rotating
four-month panels in the CPS. In any month we observe the labor market
status in the current and following month for three-fourths of the
sample. Based on the responses to the CPS questions, we group the
nonemployed into the nine nonemployment segments discussed above: the
two duration segments of the unemployed, the three segments of OLF who
want a job (marginally attached, discouraged, other), and the four
segments of OLF who do not want a job (retired, disabled, in school, not
in school). We then construct the transition probabilities into
employment for each segment by matching the individual records from the
CPS microdata month to month. (5) The transition probability from a
particular segment of nonemployment to employment is the fraction of
that segment that exits to employment from one month to the next.
Table 1, columns 4 through 6, show annual averages of the monthly
probabilities of becoming employed for the two unemployment segments and
seven OLF segments averaged across 1994-2014, and for the years 2007 and
2010. The probability of becoming employed differs substantially among
these groups. The probability is highest for the short-term unemployed:
On average they have a 30 percent chance of finding a job within a
month. Next are the long-term unemployed and those OLF individuals who
want a job: They are about half as likely to become employed as are the
STU. (6) Then there is the group of those who do not want a job but who
are neither retired nor disabled: They are only one-fourth as likely to
become employed as are the STU. Finally, there is the group of retired
and disabled who are less than one-tenth as likely to become employed as
are the STU. (7)
In recessions the employment probabilities tend to fall for all
groups, but the ranking of the different groups in terms of their
transition probabilities to employment remains the same. (8)
Furthermore, the ranking of employment probabilities coincides with the
desire to work as stated in the survey: Those who actively search tend
to have higher transition rates to employment than those who want to
work but do not actively look for work, and those who want to work have
higher transition rates than those who do not want to work.
Classification by Labor Force Status Histories
The decomposition of the OLF nonemployed as to why they are not
actively looking for work is only available since 1994. (9) This is
unfortunate since the Great Recession is an exceptional event for the
period since 1994, and we therefore cannot tell whether broader measures
of labor market resource utilization performed differently during the
Great Recession than at other times of stress in the labor market. We
therefore consider an alternative measure of the labor force attachment
of the nonemployed that is based on individuals' observed labor
market histories and that can be constructed for the time period since
1976. This longer time period contains the recessions of the early 1980s
when standard measures of unemployment were of a magnitude similar to
the Great Recession.
For the period since 1976, Kudlyak and Lange (2014) use the panel
feature of the CPS to construct labor market segments based on
respondents' labor force status (LFS) histories, that is, their
status as employed, unemployed, or OLF in the current month and the
preceding two months. They define classes of LFS histories based on the
status in the current month, and whether the current status of a
nonemployed individual differs from the status in the preceding two
months in particular, if the nonemployed was employed (see Table 2).
Conditional on this decomposition of the nonemployed for each segment,
Kudlyak and Lange (2014) calculate the probability of being employed in
the next month. They find significant and persistent differences in the
employment probabilities for these segments.
In Table 2 we report the average population shares and employment
transition probabilities of the nonemployed for the Kudlyak and Lange
(2014) decomposition. (10) The population shares of the nonemployed
segments with different LFS histories for the full sample period,
1976-2014, and the post-1994 subsample are very similar. Nonemployed
individuals who were employed in at least one of the previous two months
have the highest chance of being employed again. For this group, active
search increases the probability of reemployment somewhat but not much.
Next are the nonemployed who have no recent employment experience but
are actively looking for work: Having no recent work experience reduces
the employment probability by more than half. Finally, there are the
nonemployed who are not actively looking for work and have no recent
employment experience: They are less than one-fourth as likely to find
work. Similar to the BLS classification by reason of nonemployment, the
employment transition rates decline significantly in a recession, for
example from 2007 to 2010 following the Great Recession, but the
relative rankings remain constant. (11)
Our evidence from employment transition rates suggests that clear
distinctions between being in and out of the labor force are not
possible and might not be useful for determining the degree of labor
utilization. This conclusion emerges for both methods of measuring labor
force attachment. For example, for the BLS classification by reason of
non-employment, those who are OLF but want to work have essentially the
same employment probabilities as the long-term unemployed, yet only the
latter are included in the standard unemployment rate. Similarly for the
Kudlyak and Lange (2014) classification based on LFS histories, even
though those nonemployed who are OLF with some recent employment
experience are more likely to become employed than those who are
unemployed with no recent employment experience, the latter and not the
former are included in the standard definition of the unemployment rate.
2. MEASURES OF RESOURCE UTILIZATION
The most widely used measure of resource utilization in the labor
market is the unemployment rate, U3 to be precise. The unemployment rate
is defined as the share of the unemployed, that is, those nonemployed
who are actively looking for work, in the labor force where the latter
is the sum of the employed and unemployed. We now briefly review the BLS
extended measures of unemployment that broaden the set of the
potentially employable working-age population, but weight all of these
potentially employable equally. Since we have argued above that labor
force attachment for the nonemployed is a matter of degree rather than
satisfying a simple in or out criteria, we then propose two alternative
indices of nonemployment that quantify the degree of labor force
attachment. These indices include all nonemployed members of the working
age population but weight the nonemployed according to their average
employment transition rate.
Extended Unemployment Rates from the BLS
The BLS constructs extended measures of unemployment that move
subgroups from OLF to unemployed. In particular, the U4 rate adds
discouraged workers from the marginally attached, and the U5 rate
includes all marginally attached. The corresponding unemployment rates
are defined as before with appropriately adjusted labor force measures.
In addition, the BLS publishes the U6 rate, which includes those
employed who are working part time for economic reasons (PTfER) in the
unemployment rate. (12) These individuals, sometimes referred to as
involuntary part-time workers, would have preferred to work full time
but had to work part time because they did not find full-time work or
because their hours had been reduced to part-time work. Including these
employed among the unemployed is usually motivated by the argument that,
like the unemployed, they are not employed as much as they would like to
be. For each of these extended measures of unemployment, the group that
is added receives the same weight as the unemployed who are part of U3.
(13)
Nonemployment Rates Adjusted for Labor Market Attachment
We now construct a nonemployment index (NEI) that is more
comprehensive than the unemployment rate but also accounts for the fact
that not all nonemployed are equally attached to the labor market. Our
proposed NEI is a weighted average of the population shares of the
various subgroups among the unemployed and OLF, where the weight for
each subgroup is given by the sample average of its employment
transition rate relative to the group with the highest transition rate.
Our index thus measures the effectively available labor resources in
units of the group with the strongest labor market attachment. (14) We
use sample averages of the transition rates to ensure that the variation
in the index over time is not driven by cyclical changes in relative
transition rates.
We construct two versions of the NEI. The first version uses the
BLS classifications of nonemployment for the period from 1994 on, NEI1
for short, and the second version uses the Kudlyak and Lange (2014)
classification scheme based on LFS histories from 1976 on, NEI2 for
short. Employment transition rates are defined relative to the
short-term unemployed for the BLS classification and relative to the
unemployed with some employment in the previous two months for the LFS
history classification.
For each NEI we also construct a version that incorporates those
working part time for economic reasons. We weight this group by the
product of its relative transition probability to full-time employment
and its "underutilization" rate. Analogous to the weighting of
the nonemployed, we normalize the transition rate relative to the
highest employment transition rate among the group of the nonemployed.
The underutilization rate is defined as the ratio of the difference of
the average weekly hours worked by those working full time and the
average weekly hours worked by those working part time for economic
reasons to the average weekly hours worked by those working full time.
Using the CPS microdata from January 1994 to December 2013, we find
that the average monthly transition probability from involuntary
part-time work to full-time work is 0.30, about the same as the
employment transition rate of the short-term unemployed. The average
work week of those working PTfER is 22.9 hours, about half of the work
week of those working full time, which is 44.5 hours. (15) Those working
part time for economic reasons therefore receive a weight of about
one-half in the nonemployment index. (16)
A First Look at Resource Utilization, 1976-2014
The qualitative features of the standard unemployment rate, the
extended unemployment rates, and the nonemployment rates are essentially
the same: They rise and fall together and all increase more following
the Great Recession than they did during the 2001 recession. The
standard unemployment rate U3 and the two extended unemployment rates U5
and U6 are displayed in the top panel of Figure 1, and the two
nonemployment indices, with and without PTfER, are displayed in the
bottom panel of Figure 1. The rates differ in their levels and to some
extent in their volatility.
[FIGURE 1 OMITTED]
It is common to assume that because of frictions in the labor
market there will always be some unemployment in the economy. In other
words, there is a natural rate of unemployment and policy should only be
concerned with deviations from that natural rate. For the standard U3
unemployment rate, the most frequently referenced estimate of the
natural rate is provided by the Congressional Budget Office (CBO), the
thin black line in the top panel of Figure 1. The CBO has the natural
rate increasing from about 5.2 percent in 1950, to 6.2 percent in the
late 1970s, from where it declines to 5 percent by 2000, and then
increases again to 5.5 following the Great Recession. According to the
CBO, the natural rate is essentially 5 percent with some upward
allowance made when actual unemployment is high.
By construction, the extended unemployment and nonemployment rates
are higher than the standard unemployment rate, but similar to the
standard unemployment rate, therefore one could define natural rates
that stay close to the respective lower bounds of these broader
utilization measures. Rather than constructing these alternative natural
rates, in the following we will study how well the standard unemployment
rate does as a signal for the broader utilization measures. This
approach is motivated by the fact that prior to the Great Recession the
standard unemployment rate was widely accepted as the relevant measure
of labor market utilization. If, following the Great Recession, we now
believe that a broader utilization measure is more appropriate, we would
like to know how closely the standard unemployment rate was correlated
with the broader measure prior to 2007 and in what way the relation
between the standard unemployment rate and the broader measure broke
down after 2007.
3. NARROW AND BROAD MEASURES OF UNEMPLOYMENT AFTER 2007
Pointing to the exceptionally large increase of discouraged workers
and those working PTfER after the Great Recession, it is often argued
that the standard unemployment rate understates the degree of resource
underutilization for this period. We now argue that while this may be
true for the BLS measure U6, for nonemployment measures that account for
differences in workforce attachment the standard unemployment rate
actually overstates "true" unemployment for this period.
In Figure 2 we plot monthly data of the standard unemployment rate
U3 against various broader measures of unemployment for the period 1994
to 2014. (17) The rows represent our different broad measures of
unemployment, U5, NEI1, and NEI2, and the right columns add those
working PTfER to these broader measures. For each panel we plot the
fitted line for a regression of U3 on the relevant broad measure of
unemployment for the sample period 1994 to June 2007, represented by the
red dots in the different panels. This sample represents the period when
presumably there was a close relationship between the standard
unemployment rate U3 and the alternative broader measures of
unemployment. If the actual U3 unemployment rate for the period after
June 2007 is consistently below (above) the fitted line for the pre-2007
sample, then we would say that U3 understates (overstates) true
unemployment relative to the pre-2007 relation. For the post-2007
period, we distinguish between the months from July 2007 to December
2013, blue dots, and the year 2014, green dots, the most recent period.
[FIGURE 2 OMITTED]
A close relationship between U3 and the extended BLS unemployment
rates for the time prior to June 2007 is apparent in the top row of
Figure 2, somewhat less so for U6 than for U5. However, for most of the
period after June 2007, U3 is consistently below what would have been
predicted based on U6 for the pre-2007 period but not so much for U5.
Given that including marginally attached workers in U5 does not have
much of an impact, the break in U6 is indeed almost exclusively
attributable to the exceptional increase of those working PTfER. Since
the increase of those working PTfER has persisted into 2014, U3
continues to understate unemployment relative to pre-2007.
Proceeding now to our nonemployment indices we also find a close
relationship between them and U3 for the pre-2007 period, somewhat less
so for NEI2 based on LFS histories than for NEI1 based on BLS
nonemployment categories. Contrary to the extended BLS unemployment
rates, we find that for the post-2007 period U3 actually overstates
unemployment relative to the NEIs that exclude those working PTfER. This
break relative to the pre-2007 relation is due to the exceptionally
large increase of long-term unemployment following the Great Recession.
Since our NEIs down-weight long-term unemployed significantly relative
to short-term unemployed, the NEIs increase less than U3 after the Great
Recession. Including those working PTfERs in the NEIs then reduces the
overstatement of U3 after 2007, since the exceptional increase in those
working PTfER compensates for the exceptional increase in long-term
unemployment. As of 2014, however, observations on U3 appear to be
consistent with the pre-2007 relationship between U3 and any of our NEI.
The magnitude of nonemployment after 2007 for any of our measures
is exceptional relative to the time period from 1994 to 2007. It is
therefore not obvious that the relationship between U3 and broader
measures of unemployment can be extrapolated from the pre-2007 period.
While the extended BLS measures of unemployment and the NEI that is
based on BLS nonemployment categories are only available from 1994 on,
we can construct the NEI that is based on LFS histories for the years
from 1976 on, a period that contains unemployment rates that are
comparable to the unemployment rates following the Great Recession. In
Figure 3 we plot the standard U3 unemployment rate against our versions
of the extended BLS unemployment rates and the NEI based on LFS
histories for the sample period from 1976 to 2014. (18)
[FIGURE 3 OMITTED]
The qualitative features of Figure 3 for the period following the
Great Recession are the same as in Figure 2. Relative to the pre-2007
period, the standard unemployment rate U3 understates "true"
unemployment for the BLS extended unemployment rates and overstates
"true" unemployment for the nonemployment index from 2007 to
2013. More recently, in 2014 U3 has been well in line with the NEIs but
it continues to understate unemployment relative to U6.
We can formalize our discussion by simply running a linear
regression of the standard unemployment rate U3 on the various broader
measures of unemployment for the full sample while allowing for a
structural break in the middle of 2007. In Table 3 we report the
coefficient of the parallel shift term of the relationship between U3
and the broader measures of unemployment. Relative to the pre-2007
period, U3 is "understated" by about 0.3 percentage points for
the extended BLS U6 unemployment rate, whereas it is
"overstated" for the NEIs by up to one percentage point in the
case of NEI2 for the sample 1976-2014.
4. CONCLUSION
All the measures of resource utilization in the labor market that
we review in this article suggest that as of 2014 nonemployment has
declined since the peak in 2010. In particular, even though the standard
unemployment rate is still above its 2007 level, it has declined
significantly. The decline in the standard unemployment rate is
occasionally discounted because extended measures of unemployment that
include those working part time for economic reasons seem to suggest
that, following the Great Recession, the standard unemployment rate has
understated "true" unemployment. In our view broader measures
of nonemployment need to account for the heterogeneity in workforce
attachment of the nonemployed. Extended measures of unemployment rates
provided by the BLS do not. We have constructed such alternative
measures of nonemployment and find that for most of the years following
the Great Recession the standard unemployment rate actually overstated
"true" unemployment and that as of 2014 the standard
unemployment rate provides a reasonably accurate measure of
"true" unemployment.
APPENDIX
Data for the BLS unemployment rates have been downloaded from
Haver. The time series for the CBO estimate of the natural rate of
unemployment has been downloaded from FRED. Data for the population
shares and employment transition rates for nonemployment by reason and
LFS history are from Kudlyak and Lange (2014).
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(1) See, for example, Appelbaum (2014) or Yellen (2014).
(2) For instance, the extended unemployment rate U6, which includes
the marginally attached and those working part time for economic
reasons, is by construction always greater than the standard
unemployment rate (U3). Even if U6 more accurately captures the totality
of all labor resources that are underutilized in the labor market, it is
possible that U3 provides a good indication of the state of the business
cycle in the labor market.
(3) Recent resume audit studies (Kroft, Lange, and Notowidigdo
2013; Erikson and Rooth 2014) confirm differences in employability
between the short-term and long-term unemployed.
(4) That the share of LTU has been exceptionally high since 2007 is
also evident from the fact that the average share of LTU for the period
from 1948-2007 was a mere 15 percent.
(5) Our matching procedure follows the algorithms described in
Madrian and Lefgren (1999) and Shimer (2012) The CPS microdata fields
are available at http://thedataweb.rm.census.gov/ftp/cps_ftp.html#cpsbasic.
(6) Note that the employment transition rates among the marginally
attached OLF do not differ much. In particular, there is no reason to
single out discouraged workers based on the likelihood of becoming
employed again.
(7) See also Fujita (2014).
(8) See Kudlyak and Lange (2014) for graphs of annual averages of
monthly job finding rates for the years 1994 to 2013.
(9) Prior to 1994, only individuals who were about to exit the
sample were asked about their desire to work. Thus, the job-finding
probabilities for the OLF segments by desire to work cannot be
constructed prior to 1994.
(10) We should note that there is month-to-month attrition in the
CPS sample that is in addition to the outgoing rotation groups. Since
the population shares of currently unemployed and OLF in the subsample
with complete three-month LFS histories are not the same as the
population shares in the full sample, cf Tables 1 and 2, this attrition
does not appear to be completely random.
(11) Again, see Kudlyak and Lange (2014) for time series of annual
averages of the transition rates.
(12) Unlike for U4 and U5, adding those working PTfER does not
increase the labor force in the definition of the unemployment rate.
(13) Bregger and Haugen (1995) provide a short history of the BLS
extended measures of unemployment.
(14) Our procedure to adjust available nonemployed for their
effective labor market attachment is similar to the quality adjustment
of employment, where one uses relative wages as measures of relative
labor efficiency. These quality-adjusted employment measures have a long
tradition in labor economics. For example Katz and Murphy (1992) use
this method to generate efficiency units of labor supply by education
group. In addition to weighting the nonemployed by their relative job
finding rate, one can consider the quality of jobs that different
segments of the nonemployed find. This investigation is beyond the scope
of the article.
(15) For these calculations we use reported "actual
total" hours worked. Alternatively, we could use "usual
total" hours worked, or "total" or "usual"
hours worked at the primary job. For these various hours measures, the
implied weight on those working part time for economic reasons in the
nonemployment index then ranges from 0.133 to 0.145. Thus our choice of
"hours worked" definition maximizes the weight for those
working part time for economic reasons.
(16) Hornstein, Kudlyak, and Lange (2014) and Hornstein et al.
(2014) use an ad hoc weight of 0.5 for those working part time for
economic reasons. This weighting choice also follows the pre-1994 BLS
definition for U6, Bregger and Haugen (1995).
(17) Scatterplots for annual averages of the monthly unemployment
and non-employment rates have the same qualitative features, but the
structural breaks estimated in Table 3 are no longer statistically
significant.
(18) Since information on marginally attached OLF is not available
prior to the 1994 comprehensive revision of the CPS, we approximate the
marginally attached nonemployed with the LFS history group that is
currently OLF and was not employed in the last two months. For the time
period from 1994 to 2007 when both series are available, the extended
unemployment rates U5 calculated using either the marginally attached or
the OLF without recent employment are closely aligned. Following Polivka
and Miller (1998), the number of those working PTfER is scaled by a
factor of 0.806 prior to the 1994 CPS redesign.
Andreas Hornstein is a senior advisor and Marianna Kudlyak is an
economist in the Research Department at the Federal Reserve Bank of
Richmond. Fabian Lange is an associate professor of economics at McGill
University. This article is a substantially revised version of
Hornstein, Kudlyak, and Lange (2014) and provides the background for
Hornstein et al. (2014). The authors thank Marisa Reed for excellent
research assistance. The views expressed in this article are those of
the authors and not necessarily those of the Federal Reserve Bank of
Richmond or the Federal Reserve System. E-mail:
Andreas.Hornstein@rich.frb.org; Marianna.Kudlyak@rich.frb.org;
Fabian.Lange@mcgill.ca.
Table 1 Nonemployment by BLS Categories
1 2 3 4 5 6
Share of Working-Age Employment
Population Probability
1994- 2007 2010 1994- 2007 2010
2013 2013
Unemployed
Short-term 3.0 2.5 3.5 28.0 29.7 21.8
Long-term 1.0 0.5 2.7 14.4 15.5 10.3
OLF, Want a Job
Marginally attached,
discouraged 0.2 0.2 0.5 13.1 16.5 10.7
Marginally attached,
other 0.4 0.3 0.3 12.7 14.9 10.2
Other 1.8 1.5 1.7 14.5 15.7 12.1
OLF, Do Not Want a Job
Other, in school 4.1 4.5 5.0 8.5 8.2 6.2
Other, not in school 7.4 7.2 7.0 7.5 8.1 6.9
Disabled 4.6 4.8 5.2 1.7 1.7 1.4
Retired 15.4 15.2 15.4 1.4 1.5 1.4
Notes: Share of working-age population and employment transition
probability in percent.
Table 2 Nonemployment by Labor Force Status Histories
1 2 3 4 5
Share of Working-Age
Population
1976- 1994- 2007 2010 1976-
2014 2014 2014
Currently Unemployed
Recent employment 1.3 1.2 1.1 1.4 38.8
No recent employment 1.1 1.1 0.8 1.5 17.1
Continuously unemployed 1.4 1.3 0.8 2.8 17.7
Currently OLF
Recent employment 2.9 2.8 3.0 2.6 27.7
No recent employment 1.3 1.3 1.0 1.9 9.6
Continuously OLF 30.9 30.2 30.4 31.1 2.0
6 7 8
Employment
Probability
1994- 2007 2010
2014
Currently Unemployed
Recent employment 39.2 40.7 34.2
No recent employment 16.0 17.2 9.6
Continuously unemployed 17.2 19.0 11.0
Currently OLF
Recent employment 27.1 27.8 27.6
No recent employment 9.5 9.6 7.1
Continuously OLF 1.8 1.8 1.5
Notes: The first set of rows covers those nonemployed who are
unemployed in the current month and the second set covers those
nonemployed who are OLF in the current month. For each group, the
first row (Recent employment) denotes those who have been
employed at least once in the previous two months; the second row
denotes those who have not been employed in any of the previous
two months but also not unemployed-OLF in both months; and the
last row denotes those who have been unemployed-OLF in both of
the previous two months. The share of working-age population and
the employment probability are in percent.
Table 3 Post-2007 Bias of the U3 Unemployment Rate
BLS Extended Unemployment
Rates, 1994-2014
U5 0.02 (0.02)
U6 -0.28 (0.05)
NEI Based on BLS
Nonemployment Categories,
1994-2014
Without WPfER 0.31 (0.05)
With WPfER 0.02 (0.05)
NEI Based on LFS
Histories, 1994-2014
Without WPfER 0.47 (0.09)
With WPfER -0.15 (0.07)
NEI Based on LFS
Histories, 1976-2014
Without WPfER 0.96 (0.07)
With WPfER 0.15 (0.05)
Notes: Coefficients c for a structural break in June 2007 in the
OLS regression U3(t) = a + b * X(t) + c * B(t) where B(t) is 1
after June 2007 and 0 before, and X (t) is a broad measure of
nonemployment as indicated in the subheaders and row titles. The
regression is performed on monthly data. The break coefficients
are in percentage points with standard error in parentheses.
NEI = nonemployment index as described in the article.
WPfER = working part time for economic reasons.
