Download The Changing Contours of Long-Term Unemployment The Need for

The Changing Contours of Long-Term Unemployment
The Need for a More Radical Policy
Oren M. Levin-Waldman
Since the meltdown in late 2007, unemployment has been over eight percent, with
increasingly more of those people falling into the ranks of the long-term unemployed — those
out of work for more than six months. The last time that the nation faced severe long-term
unemployment was during the period from 1991 to 1994, although the recession itself ran from
the summer of 1990 until the Spring of 1991. A sluggish recovery, however, still left an
unemployment rate of close to 8 percent as late as June of 1992. Now in the late 2000s with
increasingly more unemployed workers finding themselves among the pool of long-term
unemployed workers, the traditional paradigm of job creation predicated on monetary and fiscal
adjustments is no longer suited to the changing economic universe that resulted in more longterm unemployment. On one level, long-term unemployment can be accounted for by structural
changes. Jobs that used to pay middle class wages no longer exist. Moreover, with each
recession, employers may find that it is propitious to restructure their operations, thereby adding
to the unemployed rolls. But on another level, the problem might appear to be far more simple
than we recognize. Unemployment is really the product of the absence of effective demand. The
traditional approach to this problem has been to tinker with the money supply through interest
rates. And yet, this really represents a top-down approach when what is perhaps needed most is a
more grassroots bottom-up approach.
In this paper, using data from the Current Population Survey, I look at the demographics
of the long-term unemployed for the years 2007 to 2010 and compare them to the years 1991 to
1
1994 to see what changes have occurred specifically among the long-term unemployed. If longterm unemployment is merely a matter of the business cycle than traditional strategies might
help. But if it is the result of a truly deep recession, then policy outside the traditional box is
needed. The data will show that structural changes occurring between 2007 and 2010 are really
not that much worse than between 1991 and 1994. Rather, the nature of this recession resulted in
the composition of the long-term unemployed looking different. But because long-term
unemployment is a function of a particularly deep recession, a new approach is needed — one
which will allow people to increase their effective demand for goods and services.
Causes of Unemployment
The neoclassical synthesis suggests that unemployment is a function of wage rigidity, or
simply inflexible wages. In a perfectly competitive market, there really is no such thing as
unemployment because workers can simply lower their wages so that employers will demand
more of their services. Market clearing wages are achieved when the demand for labor s exactly
equal to the supply of labor. This is considered to be a full employment economy. In such a
market, there is no such thing as unemployment because wages either rise or fall until the
demand for labor is exactly equal to the supply of labor. At the wage at which demand equals
supply, all those willing and able to work at that wage will be employed. More people willing to
work result in the wage falling, thereby inducing firms to hire more workers, with the result
being that the supply of labor will once again equal demand. And when firms are unable to hire
as many workers as they would like, wages rise to induce additional people to enter into the
workforce until supply and demand are once again equal. As Assar Linbeck and Dennis Snower
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(1988) explain: “when incumbent workers have some power in wage determination, then (I) there
may be no natural rate of unemployment, and (ii) both supply-side and demand-side policies may
have lasting effects on the unemployment rate (p. 38).”
Unemployment, then, results because workers are inflexible in their wage demands. Their
inflexibility may stem from membership in unions that refuse to offer concessions, or it may
result from wage floors, such as minimum wages, that prevent workers from lowering their
wages below a certain point. Institutions that artificially raise wages and other regulatory policies
simply result in efficiencies. The problem with this model is that at best it represents a theoretical
construct with characteristics that simply do not exist in the real world. Underlying the
competitive market model is an assumption that as wage demands drop, overall prices will drop
too. Assuming that workers in response to a downturn in the business cycle drop their wage
demands in order to prevent unemployment, each firm that has reduced its labor costs will be
able to lower prices so that workers earning lower wages will be able to continue to maintain
effective demand for goods and services. And yet, this would appear to assume that labor is
indeed the principal factor of production. All firms have fixed costs that cannot be reduced.
There may indeed be a limit to how much prices can be reduced in response to wage flexibility.
There is no single supply and demand curve to explain what is happening in the market place as a
whole, rather there are multiple supply and demand curves because the overall market is
comprised of multiple sub-markets.
John Maynard Keynes (1964) famously argued that the introduction of more labor — in
excess of the supply — only leads to a decrease in money wages, which only results in lower
incomes of employed workers. Hyman Minsky (1986) also noted that “there is no presumption
3
that a fall in money wages will lower price-level-deflated wages. Thus the effects of changes in
labor market variables upon the labor supply and demand relations are such that an initial excess
supply of labor may not be eliminated (pp. 123-124).” Neoclassicals accept the Keynesian
formulation that the demand for labor is determined by aggregate demand, but independent of
price level deflated money wages they assume the market will achieve full employment. That is,
the labor market is not the determinant of employment and output. On the contrary, overall levels
of employment and output are determined by the aggregate levels of demand for a firm’s goods
and services. In a survey of business executives during the 1930s and 1940s, Richard Lester
(1946) observed that business executives, unlike economists, tend to think of costs and profits as
dependent upon the rate of output, and not the other way around. In other words, employment
levels were not determined by wage rates, but by the rate of output. Therefore, it ought not to
matter how much labor voluntarily deflates its wages in order to be employed. If there is no
demand for goods and services, there is no need to hire more workers regardless of how flexible
they may be in their wage demands.
There is yet another dimension to the problem, which would appear to have implications
for the long-term unemployed. Long-term unemployment is in most cases a consequence of
structural changes in the economy. Joseph Schumpeter (1975) famously argued that an efficient
market economy engaged in “creative destruction” whereby the old and obsolete are replaced by
the new and technologically more advanced. Although the model assumes that those who are
displaced due to creative destruction will be reabsorbed back into the economy, this reabsorption
may take time as many of the displaced lack the skills required of the technologically more
advanced. Some of the literature on rising income inequality, for instance, maintains that rising
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income inequality is due to structural changes in the economy that have resulted from a mismatch
between good-paying jobs and the skills available to workers. The main culprit is technological
change biased toward those with higher levels of education and skills (Juhn, Murphy and Pierce
1993). This school holds the labor market to be divided into a primary market, where high
premiums are placed on skilled workers, and a secondary market where unskilled workers are
trapped in the lowest-wage service sector of the economy. The growth in wage inequality
between the primary and secondary labor markets has been caused by the increasing skills
differentials between the two (Katz and Murphy 1992; Katz and Krueger 1992). The same
argument could easily be applied to the long-term unemployed. Structural changes in the
economy which have resulted in less skilled workers being laid off will inevitably result in their
being unemployed longer because their skills no longer match the needs of new employers. This
no doubt contributes to long-term unemployment as does changing economies. Employers
requiring workers with new skills are not going to ignore that need because workers suddenly
become more flexible in their wage demands. Competitive market theory understands this, but to
maintain the wage rigidity hypothesis, it focuses on public policies, i,.e. interventions, that get in
the way of taking new jobs at much lower pay. Now wage rigidity is manifested in reservation
wages and unemployment insurance, which some believe only props up reservation wages, and
general moral hazard.
Martin Feldstein and James Poterba (1984) argue that unemployment insurance creates a
disincentive to search for work because it raises workers’ reservation wages—the minimum
wages they will be willing to accept. Employees who lose their jobs are likely to find that the
wages at their next jobs are lower than the wages at their last jobs, but each individual has a
5
private reservation wage which is equal to his or previous wage. From a sample of unemployed
individuals, 24 percent indicated that they would accept a wage at less than 90 percent of their
last wage, and an additional 11 percent were willing to accept from 90-100 percent of their
previous wage. An additional 27 percent indicated that they would accept any wage equal to or
greater than the last wage, but nothing less. The cumulative percentage of reservation wage rates
was less than or equal to 62 percent of their previous wages. The remaining 38 percent of the
sample had a reservation wage greater than their previous earnings. About a quarter of those who
required a wage increase said that they would accept an increase of less than ten percent. But
fully 28 percent of those in the sample said that they would only return to work if they received a
wage which was 10 percent higher than their previous wage. High reservation wage ratios and
the high fraction of individuals requiring a wage increase were attributable to the system of UI
benefits. One’s reservation wage is higher because one has the luxury of collecting benefits and
taking longer to search for a job. Although UI reduces the cost of unemployment to the
individual, it can raise the unemployment rate in several different ways. For the individual who is
unemployed and looking for a job, the lower cost of unemployment implies a higher reservation
wage, and therefore a longer period of unemployment. And among those who are employed, the
low potential cost of unemployment induces temporary layoff in response to reductions in
product demand.
According to Gary Burtless (1990), current knowledge of the impact of UI on labor
supply is simply too fragile. UI offers something of value to people who become unemployed,
and as such it may increase the attractiveness of market work. Supplementing the incomes of
workers who become unemployed can slow down the process of reemployment. Still, it is
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impossible to predict which of these two effects will predominate. UI may increase the amount of
economically productive job search. It might raise the average productivity of workers by
improving the match between jobs and workers. In situations where there are two job vacancies
and two unemployed workers, it can be economically productive to subsidize workers so that
they sort themselves into the two jobs that maximize their joint output and earnings. This
ultimately would be the more efficient outcome.
Attempts to explain high unemployment rates that have characterized the economy since
the mid-1950s have centered around two alternative hypotheses. The first is the inadequateaggregate demand hypothesis, which maintains that unemployment increases when the rate of
growth of final demand for goods and services fails to keep pace with the rate of growth in
supply that is made possible by productivity increases and in the stock of productive resources.
The second is the rise-in-structural unemployment hypothesis, which holds that unemployment
has increased despite the presence of a generally adequate demand and a totally sufficient number
of job possibilities. That is, because of the changing structure of the economy, the demand for
certain types of workers, mainly blue-collar and goods producing workers is less. Each of these
hypotheses, however, leads to different policies. If the former, fiscal-monetary policy ought to be
enough to reduce unemployment. But if the latter, then fiscal-monetary policy unaccompanied by
labor market policies that would effectively restore the skills of the unemployed will not succeed
in reducing unemployment (Simler 1964).
Mainstream economics draws a sharp distinction between short- and long-run
unemployment. According to the conventional view, short term unemployment is strongly
influenced by monetary policy and other determinants of aggregate demand. In the long run,
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unemployment returns to a natural rate, which is determined by labor market frictions. But as
Laurence Ball (1999) argues. monetary policy and other determinants of aggregate demand do
actually have strong effects on long-term, as well as short-term unemployment. The conventional
view, then, holds that unemployment is determined by institutions such as labor unions,
unemployment insurance, and firing restriction. But the conventional wisdom may actually
overstate these factors. From the 1960s through the mid-1980s, unemployment trended upward
throughout the OECD countries. When jobs are destroyed by recession, short-term
unemployment is initially created, but if employment remains low then short-term unemployment
becomes long-term unemployment. What is needed is an expansion of demand. While labor
market reforms may compliment demand expansions, it is only when the unemployed are given
incentives to seek work that unemployment is most likely to decrease. A strong economy creates
jobs for them to find.
Still, the conventional view persists in the belief that unemployment is a function of wage
rigidity. Higher unemployment in Europe than in the U.S., for instance, is typically accounted
for by wage inflexibility. Although the policy mix with regards to employment policy has
traditionally focused on the interaction between monetary and budget policies, there are those
who believe that given the high level of unemployment in Europe, it is also necessary to bring
wage developments into the picture. Unemployment remained abnormally high during the 1980s
and 1990s (Collignon 1999). Equilibrium is achieved when both actors settle for a wage share
consistent with their expectations. What brings about this result is unemployment. The
persistence of high unemployment is then due to the rigidity in the labor market which prevents
wage setters from lowering real wages to the “consistent” level. From a short-term perspective,
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unemployment is the problem of inflexible labor markets. Flexibility in wages is assumed to be
necessary in part because capital stocks are assumed to be fixed. And yet, these assumptions beg
the question of just how flexible wages can be. Workers fix their living standards and various
commitments based on the wages they have been earning. Let’s assume that wage rigidity is the
problem. Workers are not going to be flexible if they believe that the maintenance of those living
standards requires having comparable wages, or the absence of assurance that wage flexibility
will result in lower of prices.
Sources of Long-Term Unemployment
According to Sylvia Allegretto and Devon Lynch (2010), the recession that began in 2007
also led to record breaking rates of long-term unemployment. Until the 2007-2009 recession, the
most persistent increases in the share of long-term unemployment were those that followed the
1990-91 and 2001 recessions. While the annual unemployment rate in 2009 was 9.3 percent, the
average long-term unemployment share was 31.5 percent. In 1983, by contrast, the annual
unemployment rate was 9.6 percent and the long-term unemployment share was 23.9 percent.
Also in 1983, 20 percent of the labor force had less than a high school degree, and 37 percent had
a high school degree but no more. But in the 2007-2009 recession, there was a dramatic 75.8
percent increase in the overall number of long-term unemployed. Although all educational levels
appeared to experience increases in long-term unemployed, the degree of increase was actually
the lowest among those without a high school degree (4.7 percent), and the highest for those with
at least a bachelor’s degree( 289.2 percent). They also point out that the aging of the workforce
was also considerable, with those in the 16-24 age cohort only accounting for 14 percent of the
9
labor force.
In the recession beginning in 2007, the nation saw a rise in long-term unemployment.
Daniel Aaronson, Bhashkar Mazumder, and Shani Schechter (2010) note that on entering 2010
the average length of an ongoing unemployment spell was more than 30 weeks. More than 40
percent of the labor force, and more than 40 percent of the unemployed were out of work for
more than 26 weeks. The last time that unemployment reached 10 percent during the early 1980s,
the share of the labor force out of work for more than 26 weeks was 26 percent. Even though
over the last few decades there has been a secular rise in long-term unemployment, the sharp
increase that occurred during 2009 was principally due to changes in the labor force, mainly the
aging of the population and the increased labor force attachment of women. But it was also due
to weak labor demand. Whereas long-term unemployment spells during the 1980s tended to be
concentrated among factory and machine workers who made up 29 percent of the labor force, by
2009, the same time the long-term unemployed population was sectorally more diverse.
If high unemployment is a function of market interventions, persistent unemployment —
long-term unemployment — is often considered to be a function of generous UI benefits. Peter
Kuhn and Chris Riddell (2010), for example, compared UI expenditures in New Brunswick,
Canada to Maine in the U.S. In New Brunswick, there were large increases in UI expenditures
during the 1950s and early 1970s, which may have reflected two major increases in program
generosity. Meanwhile in Maine, UI expenditures were constant over the same time period, and
were much smaller as a share of GDP. By the end of this time period, the UI share of GDP in
New Brunswick at 6 percent was about six times the share in Maine. It was estimated that a 27
percent increase in the amount of income associated with part-year work generated a 27 percent
10
increase in the share of men choosing a part-year option. And yet, their data did not provide
obvious support for the hypothesis that the industrial structure of New Brunswick was affected
by generous UI.
Similarly, Mark Partridge and Janice Partridge (1999) argue that the minimum wage is
positively related to long-term unemployment rates. Because, according to the standard model, a
minimum wage prevents workers from lowering their wage demands, employers will demand
less labor. If low-skilled workers with a low value of marginal product cannot take a job below
the minimum wage, the probability of them being offered a job at all will only diminish and the
duration of their unemployment will increase. And yet, it is also possible that a minimum wage
might have very little influence on long-term unemployment if the industries that employ a
disproportionate share of minimum wage workers have almost no unemployment to begin with.
Long-term unemployment could conceivably be a function of a mismatch between labor
market policy and labor market conditions. Stephan Thomsen (2009) notes that in many
countries, active labor market programs focus on particular sets of barriers to employment like
lack of motivation, lack of job search skills, and lack of marketable skills. Many of these
programs have been shown to be ineffective in reaching their intended goals. One reason they
may be ineffective is that people participating in such programs may actually be expected to
reduce their job search activity while in the program. Another reason that such programs might
be viewed as ineffective is that participation might be interpreted by employers that participants
are less likely to be productive. Another reason for their ineffectiveness may simply be inefficient
matches of job seekers to available programs. Available programs may not meet the needs of the
unemployed. High and persistent unemployment in most OECD countries since the 1970s led to
11
a shift from passive to active labor market policy. Countries in Europe principally employ four
categories of activities: training which is intended to increase human capital; supplemental
employment programs in the public sector; private sector schemes; and sanctions to improve job
search efficiency. To lower the risk of long-term unemployment, as well as to lower the rate of
unemployment, many OECD countries offer various labor market programs. And yet, in many
cases evaluations have only shown that at best they only have small positive effects on
participating individuals.
Long-Term Unemployed?
When looking at the long-term unemployed, the obvious question is whether they have
characteristics that are different than the short-term unemployed. In other words, what is it about
this sub-population that presupposes them to long-term spells? In Australia, for instance, Bruce
Chapman (1993) found the long-term unemployed to be disproportionately from the least
advantaged part of the labor force. The longer one is unemployed, the more disadvantaged one
becomes. Given a lack of success in finding a job individuals may reduce their job search
activity. As a result, they lose contact with the world of paid work, which means that they may
have less information about upcoming jobs. More importantly, rational employers rely on
“signals” as to the likely productivity of job applicants and one of those signals is how long that
person has been out of work. Long-term unemployment might suggest to employers that a
particular job candidate is an inferior worker.
Similarly, using longitudinal data for Canada, Matthew Robertson (1986) found that
unemployment concentration could be the result of a relatively few individuals experiencing
12
multiple spells of unemployment over a given period of time. As a result, much of their time is
spent unemployed in the process. For instance, a great deal of long-term unemployment was
found in seasonal occupations and industries. Long-term unemployment was found to be
concentrated among a minority of individuals experiencing extensive periods of time
unemployed and periodic unemployment spells.
On the other hand, Imano Nunez and Ilias Livanos (2010) suggest that in Europe those
with high levels of education are less likely to be unemployed and that when they are
unemployed their spells are likely to be less as well. Higher levels of education are generally
associated with low levels of unemployment because higher education generally leads to an
accumulation of human capital, which in turn is linked with higher productivity. An academic
degree acts as a signal of ability. Using data from the European Union’s Labor Force Survey
(LFS) they found that those with academic degrees had greater chances than those possessing a
medium level of education of being employed. Graduates were less likely to be long-term
unemployed than non-graduates. Nevertheless, the impact of higher education on long-term
unemployment was more moderate. Higher education did significantly improve the employment
prospects of graduates in Europe, as it reduces both the likelihood and duration of
unemployment. And yet, those with low-levels of education had a higher chance of being
employed than those with a medium education. This anomaly might be accounted for by the
positive relationship between education and reservation wages. Because individuals with low
educational attainment are more likely to accept any type of work because of their low
reservation wages, they are not as likely to remain unemployed as long as those with a medium
level of education whose reservation wages might be higher. Peter Davidson (2011) too notes
13
that the long-term unemployed have a low-skilled profile and face added barriers to employment
than simply the duration of unemployment.
Looking at long-term unemployment in Greece, Ilias Livanos (2007) found that long-term
unemployment was affected by both marital status and age. The odds of being long-term
unemployed for a single individual were 1.4 times greater compared to somebody who was
married. Also individuals in the 15 to 24 age cohort had lower odds of being unemployed when
compared to the 25 to 34 age cohort. The older a person was, the more likely that person was to
be among the long-term unemployed. Long-term unemployment was more affected by personal
attributes such as age, gender, marital status, and region of residence; and not necessarily by
qualifications. In sum, the literature would seem to suggest that single individuals with less
education or skills and those in the 25 to 34 age cohort, perhaps because they earn more, are
more likely to be unemployed long-term. While the long-term unemployed appear to come from
the least advantaged segments of the labor force, it still is not clear what it means to be among
the least advantaged. The least advantaged could refer to skills levels, demographics, or simply
having the misfortune to have been employed in certain industries and occupations.
Who are the Unemployed?
In the pages that follow I present data on the demographic composition of the
unemployed for the years 2007-2010 and compare them to the composition for the years from
1991-1994. The reason for using the 1990s as the frame of reference is because it was a period of
relatively high long-term unemployment, although the actual recession ended in 1991. Data is
drawn from the Current Population Survey. In comparing these two time periods the objective is
14
to see if demographics, particularly among the long-term unemployed have changed. But because
the CPS is individual level data, it can at best tell us about the demographic attributes of the
individual. For example, it can only tell us what type of demographics are to be found in say
industries and occupations. It cannot tell us what those industries and occupations require in
terms of qualifications and skills, or why certain people, for that matter, may not be hired and
others would be. Table 1 shows unemployment rates by educational categories and Table 2
shows the differences between those rates by category and the overall unemployment rate.
Table 1 Unemployment Rates by Educational Categories (Percent)
2007
Overall
No more than 12th grade
High School Graduate
Some College, No Degree
Associates Degree
BA Degree
Graduate and Professional
Degree
Overall
No more than 12th grade
High School Graduate
Some College, No Degree
Associates Degree
BA Degree
Graduate and Professional
Degree
2008
Change
2009
Change
2010
Change
4.8
8.3
+72.9
9.2
+10.8
8.3
-9.8
10.1
6.2
4.5
3.2
2.3
15.4
10.7
8.3
6.1
4.6
+50.5
+72.3
+72.9
+90.6
+100.0
16.0
12.2
9.5
6.8
4.9
+ 3.9
+14.0
+14.5
+11.5
+ 6.5
15.2
11.0
8.7
6.0
4.6
-5.0
-9.8
-8.4
-11.8
- 6.1
1.5
2.7
+ 44.4
2.9
+7.4
2.8
-3.4
1991
1992
Change
1993
Change
1994
Change
7.1
6.6
-7.0
6.4
-3.0
5.3
-17.2
12.6
8.0
6.5
4.5
3.3
11.9
7.6
5.8
4.6
3.4
-5.6
-5.0
-10.8
+ 2.2
+ 6.1
12.9
7.1
5.5
4.2
3.1
+8.4
- 6.6
- 5.2
- 8.7
- 8.8
10.5
5.8
4.9
3.6
2.7
-18.6
-18.3
-10.9
-14.3
-12.9
2.2
2.6
+18.2
2.2
-15.4
2.2
15
0
Table 2 Differences in Unemployment and Overall Unemployment and Educational Categories (Percent)
2007
No more than 12th grade
High School Graduate
Some College, No Degree
Associates Degree
BA Degree
Graduate and Professional
Degree
No more than 12th grade
High School Graduate
Some College, No Degree
Associates Degree
BA Degree
Graduate and Professional
Degree
2008
2009
2010
110>
29.2>
6.7<
50.0<
108.7<
85.5>
28.9>
0
36.1<
80.4<
73.9>
32.6>
14.5>
35.3<
87.8<
85.5>
32.5>
4.6>
28.3<
80.4<
220.0<
207.4<
210.3<
196.4<
1991
1992
1993
1994
77.5>
5.5>
9.2<
57.8<
115.2<
80.3>
15.2>
13.8<
43.5<
94.1<
101.5>
10.9>
16.4<
52.4<
106.5<
107.5>
9.4>
8.2<
47.2<
103.7<
222.7<
153.4<
190.1<
140.9<
Source: Author Calculations based on data Current Population Survey’s Annual March Supplement for 2008, 2009,
2010, and 2011.
Note: Each Annual Supplement measures the previous year. These figures are based on surveys of a sample size of
60,000 households nationwide. Overall unemployment figures do differ from monthly figures reported by the media.
One reason for this is that the Bureau of Labor Statistics releases monthly averages. The Annual Supplements reflect
annual averages. Also the BLS bases its figures on unemployment insurance claims filed. Here we are relying on
respondents to answer honestly whether they are unemployed based on whether they have been looking for work in
the four weeks prior to the survey.
Unemployment obviously rises for everybody during a recession, but what stands out is that
unemployment is higher among those with no more than a 12th grade education, High School
graduates, and those with only some college. It is lower among those with Associates Degrees,
BA degrees, and Graduate and Professional degrees. On the face of it this might appear to be
consistent with the skills mismatch hypothesis. Among those with lesser education
unemployment is higher than the national unemployment rates in each year, and it is lower
among those with more education. These trends appear to be similar during the two periods, but
with one difference. In the recession beginning in 2007, unemployment among those who had
16
some college but no degree was higher than the national rate as the recession deepened in 2009
and continued into 2010 after it was over. It was lower among this group from 1991 to 1994.
This, in and of itself, might suggest that the latter recession was particularly hitting those lacking
skills to the extent that having some college is considered the beginning of acquiring some skills.
To have some college with no degree might also suggest that no real skills were acquired because
the college education was never really completed. And yet, the percentage increase among all
educational categories was much greater during the 2007-2010 period than during the 1991-1994
period, which again would suggest that the recession beginning with the financial meltdown in
2007 was different than the deep recession during the 1990s.
Overall, unemployment during the 1990s never rose as high as it did in 2009 and 2010.
So while there was long-term unemployment, the recession of the 1990s may not have been
nearly as deep. What both periods appear to share in common is a sizeable percentage of longterm unemployed, defined as being unemployed for more than 26 weeks. Even comparing shortterm to long-term, we can begin to see some demographic differences between the two.
17
Table 3 Demographics of Long-term v. Short-term Unemployed
1-26
27+
1-26
2007
Education
No more than 12th grade
High School Graduate
Some College, no degree
Associates degree
BA degree
Graduate and Professional
Degree
1-26
27+
2010
63.6
73.7
68.1
71.1
68.7
36.4
26.3
31.9
28.9
31.3
60.0
56.6
57.7
61.3
57.9
40.0
43.4
42.3
37.7
42.1
55.9
57.7
57.0
55.6
58.4
44.1
42.3
43.0
44.4
41.6
73.3
26.7
69.7
30.3
53.8
46.2
54.1
45.9
1992
1993
1994
66.8
72.6
74.4
68.5
67.9
33.2
27.4
25.6
31.5
32.1
66.2
67.8
70.3
58.2
66.7
33.8
32.2
29.7
41.8
33.3
65.0
69.3
65.4
64.7
66.9
35.0
30.7
34.6
35.3
33.1
64.6
71.9
70.1
70.4
71.6
35.4
28.1
29.9
29.6
28.4
73.0
27.0
56.6
43.4
63.5
36.5
71.9
28.1
72.6
67.0
2008
27.4
33.0
71.9
61.0
1991
W hite
Black
27+
2009
27.9
31.2
25.3
30.8
27.2
2007
Race
W hite
Black
1-26
72.1
68.8
74.7
69.2
72.8
1991
No more than 12th grade
High School Graduate
Some College, No Degree
Associates Degree
BA Degree
Graduate and Professional
Degree
27+
2008
72.2
65.2
2009
28.1
39.0
58.9
54.2
1992
27.8
34.8
67.2
65.7
2010
41.1
45.8
1993
32.8
34.3
18
67.9
64.2
58.8
52.1
41.2
47.9
1994
32.1
35.8
71.5
62.8
28.5
37.2
1-26
2007
Age
16-19
20-24
25-34
35-44
45-54
55-64
65-72
73+
16-19
20-24
25-34
35-44
45-54
55-64
65-72
73+
65.9
72.7
71.2
73.4
71.4
67.4
73.1
66.7
1991
68.0
74.2
73.7
68.5
68.4
68.6
53.3
50.0
27+
34.1
27.3
28.8
26.6
28.6
32.6
26.9
33.3
32.0
25.8
26.3
31.5
31.6
31.4
46.7
50.0
2007
Sex
Male
Female
Male
Female
73.2
67.8
1991
70.4
71.7
1-26
2008
61.4
66.7
73.4
70.4
72.6
64.6
57.1
58.8
1992
71.4
73.3
69.6
66.1
58.7
58.0
61.5
57.1
27+
38.6
33.3
26.6
29.6
27.4
35.4
42.9
41.2
28.6
26.7
30.4
33.9
41.3
42.0
38.5
42.9
2008
26.8
32.2
29.6
28.3
71.3
66.6
1992
67.3
65.9
1-26
2009
52.5
59.5
59.9
58.5
58.4
52.7
47.2
61.1
1993
69.7
62.2
70.5
65.7
62.5
69.8
61.5
90.0
27+
47.5
40.5
40.1
41.5
41.6
47.3
52.8
38.9
30.3
37.8
29.5
34.3
37.5
30.2
38.5
10.0
2009
28.7
33.4
32.7
34.1
19
58.2
57.4
1993
67.2
66.2
1-26
2010
27+
57.5
55.4
59.0
58.8
54.6
56.8
54.1
30.8
42.5
44.6
41.0
41.2
45.4
43.2
45.9
69.2
1994
68.9
68.1
73.8
68.6
68.8
62.7
75.0
66.7
31.1
31.9
26.2
31.4
31.2
37.3
25.0
33.3
2010
41.8
42.6
32.8
33.8
58.5
54.7
41.5
45.3
1994
70.1
68.4
29.9
31.6
A recession obviously exacerbates the problem of long-term unemployment, but are some more
likely to be long-term than others? Between 2007 and 2010, the percentage of long-term
unemployed among those with less than a high school education rose by 58 percent, whereas
between 1991 and 1994, that same educational cohort saw an increase in long-term
unemployment by 6.6 percent. Between 2007 and 2010 the percentage of long-term unemployed
among high school graduates increased by 35.6 percent, compared to an increase in this cohort of
13.5 percent. Long-term unemployment among those with some college and no degree increased
by 70 percent between 2007 and 2010, compared to 16.8 percent between 1991 and 1994. For
those with Associates degrees, the increase was 44.2 percent compared to a 6 percent decrease
between 1991 and 1994. For those with a BA degree the increase between 2007 and 2010 was
52.9 percent compared to an 11.5 percent decrease between 1991 and 1994. The biggest increase,
however, between 2007 and 2010 is among those with graduate and professional degrees. Among
this educational cohort, long-term unemployment increased by 71.9 percent compared to only a
4.1 percent increase between 1991 and 1994. Although those without education and/or skills are
certainly affected by the recession beginning in 2007, a much greater percentage of those with
skills, advanced training and education appeared to be affected, compared to the last recession. On
one level, unemployment is a matter of the business cycle, but the huge increases in long-term
unemployment, especially among highly educated people would seem to suggest some serious
structural changes.
Between 2007 and 2010 long term unemployment among blacks increased by 45.2 percent
and among whites it increased by 50.4 percent. Between 1991 and 1994 long-term unemployment
among blacks increased by 6.9 percent and it increased by 2.5 percent among whites. Whereas the
20
increase in long-term unemployment among blacks was greater than among whites during the
1990s, it was greater among whites than among blacks in the latest recession. But perhaps the
biggest change from the 1990s to the late 2000s was among those over 72. Between 1991 and
1994, long-term unemployment among those older than 72 decreased by 33.4 percent, but it
increased by 101.8 percent between 2007 and 2010. Of course, it is also possible that during the
1990s, more of the elderly who were long-term unemployed simply decided to drop out of the
labor force and retire. That there is such an increase between 2007 and 2010 may reflect that there
have been more elderly in the workforce during this period than previously.
To understand the extent to which there may have been some more serious structural
changes, we need to look at industrial and occupational changes between the 1991-1994 period
and the 2007-2010 period.
21
Table 4 Short-term v. Long-term Unemployment by Industry
1-26
2007
Agriculture, forestry, fishing
Mining
Construction
Manufacturing
W holesale and Retail Trade
Transportation and Utilities
Information
Financial, Insurance, Real
Estate, and Rental/Leasing
Professional, Scientific,
Management, Administrative
Education, Health, and Social
Services
Arts, Entertainment, Recreation,
Accommodation, and Food Service
Other Service
Public Administration
Armed Forces
27+
27+
1-26
2009
27+
1-26
2010
27+
83.3
88.9
75.7
70.9
70.0
65.2
72.2
16.7
11.1
24.3
29.1
30.0
34.8
27.8
51.2
81.5
77.8
73.8
66.7
70.7
68.4
48.8
18.5
22.2
26.2
33.3
29.3
31.2
53.2
53.8
64.0
49.9
55.2
51.6
57.8
46.8
46.2
36.0
50.1
44.8
48.4
42.2
53.8
55.6
62.2
53.7
52.8
54.5
60.0
46.2
44.4
37.8
46.3
47.2
45.5
40.0
77.9
22.1
75.9
24.1
56.1
43.9
56.0
44.0
70.5
29.5
66.2
33.8
58.5
41.5
65.7
68.9
34.3
31.1
59.9
67.5
40.1
32.5
61.2
62.3
38.8
37.7
58.4
61.5
41.6
38.5
62.3
52.6
100.0
37.7
47.4
0
69.6
59.5
54.5
30.4
40.5
45.5
53.1
59.7
81.2
46.9
40.3
18.8
55.3
46.7
75.0
44.7
53.3
25.0
1991
Agriculture, forestry, fishing
Mining
Construction
Durable Goods
Nondurable Goods
Transportation, Communication
and Public Utilities
W holesale Trade
Retail Trade
Finance, Insurance & Real Estate
Business & Repair Services
1-26
2008
1992
1993
56.9
43.1
1994
73.0
67.9
72.3
72.9
72.1
27.0
32.1
27.7
27.1
27.9
73.7
86.4
66.0
72.8
64.8
26.3
13.6
34.0
27.2
35.2
69.8
86.7
70.7
70.6
59.4
30.2
13.3
29.3
29.4
40.6
59.8
66.7
76.3
80.0
62.8
40.2
33.3
23.7
20.0
37.2
72.1
69.8
70.4
78.8
67.3
27.9
30.2
29.6
21.2
32.7
73.1
65.3
66.7
67.4
56.5
26.9
34.7
33.3
32.6
43.6
64.9
71.2
68.2
63.5
61.7
35.1
28.8
31.8
36.5
38.3
72.2
78.9
68.8
70.6
56.2
27.8
21.1
31.2
29.4
43.8
22
Personal Services, incl private hhold
Entertainment and Recreation
Profession & Related
Public Administration
Never W orked
65.3
65.3
68.4
67.7
34.7
34.7
31.6
32.3
60.7
67.2
64.7
72.1
39.3
32.8
35.3
27.9
23
65.0
70.0
59.4
66.7
35.0
30.0
40.6
33.3
64.6
70.4
69.4
68.2
35.4
29.6
30.6
31.8
Long-term unemployment appears to have increased more in all industries between 2007 and
2010 than it did between 1991 and 1994. Between 1991 and 1994 the biggest increase in longterm unemployment was by 48.9 percent in Agriculture, Forestry, and Fishing. The second biggest
increase in long-term unemployment was in nondurable goods, which is part of manufacturing.
Nondurable goods production increased by 33.3 percent, although between 1991 and 1993 it
actually increased by 45.5 percent. After this, the biggest increase was in Financial, Insurance &
Real Estate, followed by Business and Repair services. In Financial, Insurance & Real Estate, the
increase in long-term unemployment between 1991 and 1994 was 38. 7 percent, although it again
increased by 72.2 percent between 1991 and 1993, and fell again. In Business and Repair
Services, the increase in long-term unemployment between 1991 and 1994 was 33.9 percent.
Between 1991 and 1993 the increase was only 17.1 percent. Long-term unemployment in
Professional and Related overall decreased between 1991 and 1994 by 3.2 percent, but it did
increase by 28.5 percent between 1991 and 1993.
Between 2007 and 2010, the biggest increases in long-term unemployment was in
Agriculture, Forestry and Fishing and in Mining: 176.6 percent and 300 percent respectively.
Afterwards the biggest increase was in Financial, Insurance, Real Estate, and Rental/Leasing,
where it increased by 81 percent. Long-term unemployment increased in Manufacturing by 55.6
percent, which was greater than the increase during the 1990s. In Wholesale and Retail Trade,
long-term unemployment increased by 59.1 percent, although between 2007 and 2009, which was
the actual recession, it actually increased by 72.2 percent. In Transportation and Utilities, longterm unemployment increased by 57.3 percent, and in Management and Administrative it
increased by 46.1 percent. The lowest increases in long-term unemployment were in Information,
24
Arts, Entertainment, Recreation, Accommodation and Food Service, Other Service, and Public
Administration, which was 30.7 percent, 21.3 percent, 23.8 percent, 18.6 percent, and 12.4
percent respectively.
Some of these differences clearly speak to the deepness of this recession compared to the
one in the 1990s. But it also speaks to a recession that affected more of a cross-section of the
American labor market. That there has been an increase in long-term unemployment in
Manufacturing since the 1990s surely speaks to the absence of demand for manufactured goods.
That there is a tremendous increase in the percentage of long-term unemployed in Financial, Real
Estate, and Rental is no doubt consistent with a recession that began as a financial crisis,
particularly in the sub-prime mortgage market, which then manifested itself in both the collapse of
American banks and the bottoming out of the housing market. A look at industries, however,
might not tell us enough. The real issue is what changes occurred in occupational composition.
This can be seen in Tables 5 and 6
25
Table 5 Short-term v. Long-term Unemployment by Occupation
1991
Executive, Admin and
Managerial
Professional specialty
Technicians and Related
support
Sales
Administrative support,
including clerical
Private Household
Protective Service
Service, excluding
household and protective
Farming, fishing & Forestry
Precision production, craft
and repair
Machine operatives, assemblers
and Inspectors
Transportation and materials
moving
Handlers, equipment cleaners,
helpers and laborers
Armed Forces
Never W orked
1-26
27+
1-26
1992
27+
1993
1-26
27+
1994
1-26
27+
72.0
64.6
28.0
35.4
66.2
68.5
33.8
31.5
66.2
67.0
33.8
33.0
81.4
79.0
18.6
21.0
80.0
73.6
20.0
26.4
64.4
63.8
35.6
36.2
48.5
68.4
51.5
31.6
68.2
70.2
31.8
29.8
69.3
66.7
75.0
30.7
33.3
25.0
68.1
53.8
62.5
31.9
46.2
37.5
70.7
52.4
61.5
29.3
47.6
38.5
68.3
52.6
52.9
31.7
47.4
47.1
63.5
74.2
36.5
25.9
62.0
69.3
38.0
30.7
62.0
70.9
38.0
29.1
62.8
57.4
37.2
42.6
74.1
25.9
67.5
32.5
65.8
34.2
70.5
29.5
68.9
31.1
68.1
31.9
64.2
35.8
72.0
28.0
76.6
23.4
78.9
21.1
77.7
22.3
79.7
20.3
68.5
100.0
31.5
0
63.2
100.0
36.8
0
67.0
100.0
33.0
0
68.4
100.0
31.6
0
26
Table 6 Short-term v. Long-term Unemployment by Occupation
2007
Management Occupations
Business and Financial operations
Computer and Mathematical
Architecture and Engineering
Life, Physical, and Social Science
Community and social service
Legal
Education, Training, and library
Arts, Design, Entertainment, sports
and Media
Healthcare practitioner and
Technical
Healthcare support
Protective service
Food Preparation and servicerelated
Building and grounds cleaning
and maintenance
Personal Care and service
Sales and Related
Office and Administrative
support
Farming, fishing, and forestry
Construction Trades and
Extraction
Installation, maintenance,
and repair
Production
Transportation and material
moving
Armed Forces and Military
2008
2009
2010
1-26
27+
1-26
27+
1-26
27+
1-26
27+
69.2
76.3
83.3
82.4
50.0
66.7
88.9
61.1
30.8
23.7
16.7
17.6
50.0
33.3
11.1
38.9
72.6
79.0
79.6
83.7
55.6
70.4
55.6
55.4
27.4
21.0
20.4
16.3
44.4
29.6
44.4
44.6
53.1
54.3
51.7
58.8
58.3
66.7
25.0
69.0
46.9
45.7
48.3
41.2
41.7
33.3
75.0
31.0
62.8
58.0
66.7
60.0
70.0
62.5
76.9
47.4
37.2
42.0
33.3
40.0
30.0
37.5
23.1
52.6
61.5
38.5
73.7
26.3
53.6
46.4
51.7
48.3
80.0
66.7
81.2
20.0
33.3
18.8
69.0
70.0
61.1
31.0
30.0
38.9
63.6
63.4
64.9
36.4
36.6
35.1
55.3
57.4
63.6
44.7
42.6
36.4
67.5
32.5
64.6
35.4
63.9
36.1
59.3
40.7
67.5
58.5
67.8
32.5
41.5
32.2
65.0
68.6
67.7
35.0
31.4
32.3
63.3
53.9
54.9
36.7
46.1
45.1
63.7
60.0
54.4
36.3
40.0
45.6
69.8
85.4
30.2
14.6
66.5
41.7
33.5
58.3
56.1
56.1
43.9
53.9
51.4
47.8
48.6
52.2
76.0
24.0
77.1
22.9
62.4
37.6
59.8
40.2
73.2
65.0
26.8
35.0
71.0
72.2
29.0
27.8
57.3
51.9
42.7
48.1
56.1
54.2
43.9
45.8
76.4
100.0
23.6
0
69.0
54.5
31.0
45.5
55.5
81.2
44.5
18.8
58.0
75.0
42.0
25.0
27
As with the changes in industrial composition, increases in long-term unemployment between
2007 and 2010 were considerably greater, and across the board, than between 1991 and 1994.
Again, this may speak more to the depths of the recession and the absence of aggregate demand to
get the economy going again. Between 1991 and 1994, increases in long-term unemployment do
not really exceed 60 percent, although between 1991 and 1993 there was a 157.5 percent increase
in long term unemployment among Technical and Related Support. Then among this occupational
category there was a 38.3 percent drop in long-term unemployment between 1993 and 1994.
Otherwise the increase in long-term unemployment among this occupational group is 59 percent
between 1991 and 1994. Between 1991 and 1993 long-term unemployment among Executive,
Administrative and Managerial increased by 19.6 percent, but then decreased by 45 percent
between 1993 and 1994. After Technical and Related Support the greatest increase in long-term
unemployment between 1991 and 1994 is in Private Household. Long-term unemployment did
increase overall by 13.9 percent among Precision, Production, Craft, and Repair between 1991
and 1994, although the increase among this occupational category was 32 percent between 1991
and 1993. Although long-term unemployment decreased by 10 percent among Machine Operators,
Assemblers, and Inspectors between 1991 and 1994, it had increased among this occupational
category by 15.1 percent between 1991 and 1993.
Between 2007 and 2010 long-term unemployment appears to increase substantially in
almost all occupations. Relative to other occupations, increases in long-term unemployment in
Management Occupations were not that substantial. The overall increase in Management
occupations between 2007 and 2010 was 20.1 percent, although it was actually 52.3 percent
between 2007 and 2009, the actual recession. Overall, between 2007 and 2010 long-term
28
unemployment in Business and Financial Operations did increase by 77.2 percent, although it too
actually increased by 92.8 percent between 2007 and 2009. Aside from Farming, Fishing, and
Forestry, which saw an increase of 257.5 percent between 2007 and 2010, the highest increases
were in Computer and Mathematical, Architecture and Engineering, and Health Practitioner and
Technical. Between 2007 and 2010 long-term unemployment in Computer and Mathematical
increased by 99.4 percent, but it increased by 177.2 percent between 2007 and 2009. Between
2007 and 2010, long-term unemployment increased by 127.3 percent in Architecture and
Engineering and by 123.5 percent in Healthcare Practitioner and Technical. After these two
occupational categories, the next highest increases were in Food Preparation and Service Related
(93.6 percent) and Transportation and Materials Moving (78 percent). After these, the next three
highest increases in long-term unemployment between 2007 and 2010 was in Construction Trades
and Extraction (67.5 percent), Installation, Maintenance, and Repair (63.8 percent), and Office
and Administrative Support (60.9 percent). Long-Term unemployment only increased by 30.9
percent in Production, although it did increase by 32.4 percent between 2007 and 2009. On the
face of it, it would appear that increases in long-term unemployment were higher in those
occupations paying more and lower in those paying less, which might lend some support to the
theory that reservation wages are responsible for exacerbating long-term unemployment.
Regression Analysis
The real question, however, is whether there are certain characteristics that would
predispose one to be among the ranks of the long-term unemployed. A logit regression analysis
can provide some clues as to whether certain variables are more likely to have an effect for being
29
long-term unemployed. It can also shed light on whether there were differences between lower
paying occupations from one period to another that would make long-term unemployment more
likely. With long-term unemployment — those being unemployed for more than 26 weeks — as
the dependent variable, I test for the effects of having a low educational attainment (less than a
high school graduate) being in the 18 to 24 age cohort, being black, being female, working in
manufacturing, working in trade, working in finance, working as executive or manager, working
as a production or craftsperson, working as a machine operative, and working as a laborer. All
variables are set to 1.
Table 7 Regression Coefficients 1991-1994
1991
Less than 12 th
Grade Education
.312
.000
18-24 years old
.840
.000
Black
-.032
.405
Female
-.135
.000
Manufacturing
.326
.000
Trade
.878
.000
Finance
.630
.000
Executive/Management
.322
.000
Production/Craftsperson
1.365
.000
Machinist/Operatives
1.252
.000
Laborer
1.132
. 000
Constant
3.572
.000
1992
1993
1994
.264
.000
.939
.000
.041
.300
-.179
.000
.342
.000
.880
.000
.610
.000
.322
.000
1.344
.000
1.212
.000
1.020
.000
3.596
.000
.278
.000
.836
.000
.086
.040
-.101
.000
.286
.000
.894
.000
.530
.000
.365
.000
1.303
.000
1.095
.000
1.116
.000
3.748
.000
.233
.000
.877
.000
-.025
.566
-.023
.000
.251
.000
.820
.000
.638
.000
.413
.000
1.263
.000
1.117
.000
1.120
.000
3.780
.000
Between 1991 and 1994, those most likely to be long-term unemployed were working in the
following occupations: Production/Craftsperson, Machinist/Operatives, and laborers. Those
30
working in the trade industry — sales, also had a high probability of being long-term unemployed,
as well as those in the 18-24 age cohort. People with low educational attainment and in the
manufacturing industries had lower relative probabilities of being long-term unemployed. The
determinants of long-term unemployment would appear to be one’s occupation, and not one’s
educational level or one’s industry. Those variables with the greatest effect for long-term
unemployment are low paying occupations, but also higher-skilled blue collar workers. That being
in the 18-24 age cohort has a strong positive effect might reflect their lack of experience, and that
in a market where jobs are tight employers would prefer to hire those with more experience.
Table 8 Regression Coefficients 2007-2010
2007
Less than 12 th Grade
Education
.510
.000
18-24 Years Old
.839
.000
Black
.002
.957
Female
-.242
.000
Manufacturing
.491
.000
Trade
.721
.000
Finance
.736
.000
Executive/Management
-.067
.290
Installer/Repair Person
.321
.000
Production
.444
.000
Constant
3.856
.000
2008
2009
2010
.518
.000
.678
.000
.031
.068
-.286
.000
.617
.000
.781
.000
.636
.000
.092
.071
.375
.000
.526
.000
3.564
.000
.490
.000
.566
.000
-.054
.000
-.397
.000
.643
.000
.716
.000
.586
.000
.148
.003
.386
.000
.496
.000
3.434
.000
.382
.000
.614
.000
.074
.035
-.334
.000
.377
.000
.723
.000
.461
.000
.136
.011
.516
.000
.596
.000
3.497
.000
Throughout the four year period those in the 18 to 24 age cohort appear to have a high likelihood
of being unemployed long-term, which again may speak to the relative lack of experience of this
31
group. Unlike the 1990s where occupational categories appeared to be the determinants of longterm unemployment, industry categories appear to be the determinants between 2007 and 2010.
At least through 2009, after the 18-24 age cohort, the highest probabilities for long-term
unemployment are in trade and finance, which is perhaps to be expected given that the recession
began with a meltdown in finance. What could be described as blue-collar occupations appear, at
least in relative terms to have less of an effect. And yet in 2010, which is considered a recovery
year, these occupational categories appear to have greater probabilities for long-term
unemployment than being in the finance industry. This might suggest that long-term
unemployment in this recession has less to do with structural changes that may have been key
during the 1990s and more to do with the depth of the recession. That the effect of manufacturing
in 2008 and 2009 is relatively strong, as the recession grows more severe, may have more to do
with the absence of aggregate demand, which will only be exacerbated by the actual depth of the
recession.
And yet, the question remains: is it simply a question of being in those industries and/or
occupations that are likely to predispose one to long-term unemployment, or might there also be a
relationship between industry and occupational characteristics and other characteristics such as
educational and income levels? Do all people in manufacturing, for instance, have the same
probability of being long-term unemployed? Are those in say middle income ranges in
manufacturing (because they may speak to the presence of blue collar workers) more likely to be
long-term unemployed than those in high income ranges in manufacturing (the executive class)?
Tables 9 and 10 show interaction regression coefficients in an attempt to address this question.
Again they are logistical regression coefficients with long-term unemployment being the
32
dependent variable, and with all variables being set to a value of 1.
Table 9 Labor M arket Coefficients 2007-2010
Production occupations
earning <$30,000
Production occupations
earning $30,000-59,999
Production occupations
with no more than 12grade
Installers/Repair with no
more than 12 grade
Installers/Repair earning
< $30,000
Installers/Repair earning
$30,000-59,999
Those with no more than
12th grade in Manufacturing
Those with a BA degree
in Manufacturing
Those in Manufacturing
earning , $30,000
Those in Manufacturing
earning $30,000-59,999
Those in Manufacturing
earning $100,000+
Those in Executive/Management occupations earning $100,000+
Those in Finance occupations
earning $100,000+
Those in Finance occupations
with Graduate/Professional degrees
Those in Executive/Management
occupations with Graduate/Professional
degrees
Those earning < $30,000
2007
2008
2009
2010
.673
.000
.416
.000
.616
.000
.493
.000
.426
.009
.411
.000
.708
.000
.514
.000
-.224
.116
.268
.032
-.155
.214
.201
.138
-.129
.396
.039
.823
.032
.802
.207
.130
1.163
.000
.965
.000
.927
.000
1.055
.000
.454
.011
.632
.000
.902
.000
.717
.000
.079
.535
-.273
.012
.143
.198
-.355
.004
.126
.398
.010
.934
.072
.568
.081
.547
.463
.000
.853
.000
.633
.000
.698
.000
.716
.000
.992
.000
.825
.000
.821
.000
-.039
.884
.462
.023
.339
.079
-.135
.588
-.506
.015
-1.085
.000
-.453
.007
.472
.005
.097
.701
-.532
.073
-.156
.500
-.924
.005
.437
.062
.471
.037
.318
.163
.691
.003
.444
.006
1.257
.457
.001
1.102
.425
.002
1.063
.086
.581
1.004
33
Those earning $100,000+
Constant
.000
.250
.022
4.240
.000
.000
.248
.000
3.880
.000
.000
.266
.000
3.848
.000
.000
-.183
.090
3.879
.000
In 2007, those earning less than $30,000 have the highest probability of being long-term
unemployed. This might conceivably reflect a low-skilled or less experienced segment of the labor
market. This trend nonetheless continues through 2008, 2009, and into 2010. In 2009, production
and craft workers both in the less than $30,000 and the $30,000 to $59,999 income ranges have
strong positive effects for being long-term unemployed. The positive effects for being long-term
unemployed are stronger for Installation and Repair workers in both the less than $30,000 and
$30,000 to $59,999 income ranges. There is a relatively strong positive effect for those in
manufacturing earning less than $30,000, but the effects are even stronger for those in
manufacturing earning between $30,000 and $59,999. Although in 2010, those earning less than
$30,000 have a high probability of being long-term unemployed, the probability is even higher
among Installation and Repair workers earning less than $30,000. Those in production
occupations earning in both the less than $30,000 and $30,000 to $59,999 income ranges do have
positive effects for being long-term unemployed. The positive effects are still stronger for those
working as Installers and Repair people in the $30,000 to $59,999 income range and those in
manufacturing in both the less than $30,000 and the $30,000 to $59,999 income ranges, although
the effects are stronger in the latter.
34
Table 10 Labor M arket Coefficients 1991-1994
Production/craft occupations
earning <$30,000
Production/craft occupations
earning $30,000-59,999
Production/craft occupations
with no more than 12grade
Machine, operatives, assemblers
earning < $30,000
Machine, operatives, assemblers
earning $30,000-59,999
Machine, operatives, assemblers
with no more than 12 grade
Laborers earning <,$30,000
Laborers earning $30,000-59,999
Laborers with no more than
12th grade
Those with no more than
12th grade in Manufacturing
Those with a BA degree
in Manufacturing
Those in Manufacturing
earning , $30,000
Those in Manufacturing
earning $30,000-59,999
Those in Manufacturing
earning $100,000+
Those in Executive/Management occupations earning $100,000+
Those in Executive/Management
occupations with Graduate/Professional
Those in Finance occupations
earning $100,000+
1991
1992
1993
1994
1.121
.000
1.160
.000
1.014
.000
.959
.000
2.071
.000
1.902
.000
1.845
.000
1.739
.000
.232
.001
.176
.015
.270
.001
.258
.002
.882
.000
.885
.000
.831
.000
.429
.001
1.965
.000
1.621
.000
1.641
.000
1.359
.000
.309
.009
1.279
.000
2.558
.000
.239
.049
1.168
.000
2.024
.000
.105
.416
1.146
.000
2.529
.000
.609
.000
1.098
.000
2.387
.000
.092
.370
.168
.119
.219
.054
.219
.061
-.349
.000
-.322
.000
-.528
.000
-.485
.000
.215
.086
.116
..359
.061
.656
.083
.564
.302
.000
.323
.000
.484
.000
.442
.000
.436
.000
.612
.000
.392
.002
.144
.295
-.020
.978
1.835
.000
.726
.148
.177
.714
.716
.188
-1.892
.001
-1.090
.031
.420
.334
.000
.875
.000
.854
.000
.699
.000
.229
.718
-.270
.731
.782
35
-20.258
-1.507
.054
Those in Finance occupations
with Graduate/Professional degrees
degrees
Those earning < $30,000
Those earning $100,000+
Constant
.595
.027
1.977
.000
-.112
.794
4.679
.000
.749
.002
1.891
.000
.594
.046
4.640
.000
.567
.053
1.854
.000
.925
.000
4.723
.000
1.332
.000
1.720
.000
.069
.828
4.616
.000
Although in the 1990s, those earning less than $30,000 have strong probabilities of being longterm unemployed, the probabilities appear to be higher within certain industries and among
certain occupations in the $30,000 to $59,999 income range. In 1991, the highest probabilities for
being long-term unemployed are among Production workers and Craftsmen, Machine Operatives,
and Laborers in the $30,000 to $59,999 income range. In 1992, the same trends appear to
continue, but there is one difference. Those in manufacturing earning more than $100,000 also
have a strong probability of being long-term unemployed. Here the probability is stronger than the
probabilities of being Production workers and Craftsmen, Machine Operatives, and Laborers in
the $30,000 to $59,999 income range. Interestingly, those at the high end of the income
distribution in manufacturing have a higher probability of being long-term unemployed than those
at the low end of the distribution. This could conceivably reflect the decline in manufacturing, as
there are fewer opportunities, particularly at the managerial levels. It is also conceivable that the
higher probability of those in Manufacturing in the $30,000 to $59,999 income range being longterm unemployed than those in the less than $30,000 income range is among unionized workers. It
could also reflect the shift of manufacturing jobs from the rustbelt states which are unionized to
right-to-work states which are not. There is a positive effect for being long-term unemployed
among those in Finance with Graduate and Professional degrees, but the effect is not as strong
36
relative to others. In 1994, the trends are similar to 1993. It is interesting that there are strong
negative effects which are statistically significant for being in an Executive/Management
occupation earning over $100,000. We see the same trends in 1994, but in this year there is a
strong probability that those in Finance with Graduate or Professional degrees will be long-term
unemployed.
Despite some variation, it would appear that the constant running through the two time
periods is that those at the low-end of the income distribution are highly likely to be among the
long-term unemployed, as are those working in occupations and in industries earning below
$30,000. Those in what we could characterize as blue-collar jobs earning between $30,000 and
$59,999 are the most likely to be long-term unemployed. That those in these occupations and
industries are more likely to be long-term unemployed in the $30,000 to $59,999 income group
than the less than $30,000 income group might suggest that as employers hiring following a
recession are exploiting the opportunity to hire workers whom they can pay less. That these
workers in the less than $30,000 income group still have high probabilities of being long-term
unemployed might suggest that these are low-wage and low-skilled workers who lack the skills
required for re-employment, especially in a changing economy. And yet, in simple terms, it means
that these jobs, especially those that were paying what we would call middle-class incomes, no
longer exist. As to why, it most likely is the case that the economy has changed, although less so
during the 2007-2010 period than during the 1991-1994 period. The differences between the two
income ranges aren’t nearly as stark during the 2007-2010 period as they are during the 19911994 period. A wider swath of jobs no longer exists.
What, then, has changed between one deep recession with long-term unemployment and
37
the current one? Trade and finance have stronger effects than in the past. Although the probability
of manufacturing as being a factor in long-term unemployment has increased, especially after
2007, trade and finance are still higher. Unlike the previous deep recession, low paying or bluecollar occupations appear to have lower probabilities. Some might attribute this to the lower
reservation wages associated with these jobs. And yet, as the recession appears to be easing,
especially going into 2010, the probability of finance also appears to be diminishing, which may
also reflect the various bank bailouts. What does become clear is that the structure of the economy
appears to be similar to the 1990s. While a higher percentage of those with low educational
attainment are unemployed relative to others, low educational attainment does not appear to be a
major determinant of long-term unemployment. Perhaps the question that is not so easily
answered in why the higher probability in 2010 for those working as Installers and repair persons
and those in production over those with low educational attainment? Are these occupational
categories necessarily low-paying and/or low skilled? And why specifically in the middle income
range? By itself, low educational attainment may be a proxy for low skills, but not when measured
against low skilled occupations. It could be that those with low educational attainment truly are in
the lowest-wage labor market, in which case their reservation wages would certainly be the
lowest. Or it may be that those in the occupations with the highest probabilities for long-term
unemployment are in industries hit the hardest by the lack of aggregate demand. That is, the
recession no doubt began at the top in the financial sector and then the housing market. But as it
rippled through the economy the effects were the same as they always were. As demand for goods
and services decline, firms laid workers off, thereby resulting in further unemployment as those
laid off now found that they too lacked the wherewithal to demand goods and services. If middle
38
class jobs have disappeared and what replaces them are lower paying jobs, the effect will
nonetheless be a reduction in aggregate demand because workers with lower incomes do have less
to spend.
Implications for Policy
If the source of long-term unemployment during the 2007-2010 period is ultimately the
depths of the recession rather than any further structural changes since the last, then the key issue
is the absence of aggregate demand. The conventional approach of monetarism is really
insufficient to address the problem because offering lower interest rates in an effort to jump start
investment will not create jobs if nobody is demanding their goods and services. Macroeconomic
policies predicated on the need to boost the purchasing power of individuals is what is needed. In
other words, the solution lies in a grassroots effort to get people buying things again. With the rise
of neoclassical economics, primarily since the 1980s, Keynesian economics has fallen into
disfavor. But as Franco Modigliani (2003) suggests, Keynes has been greatly misunderstood. For
Modigliani, the classical model is really a special case of The General Theory. It assumes an
economy in which wages are highly flexible, and that they will decline quickly in the face of
unemployment. That is, in the face of an excess supply of workers, their wage prices will decline
towards the equilibrium level, thereby reducing the excess supply. The fundamental problem with
the classical model, however, is that it is manifestly counterfactual. Consequently, it is unable to
provide a systematic explanation of unemployment or provide any guidance on how to control it.
On the contrary, The General Theory begins by rejecting the presence of the classical postulate
39
that wages and prices are sufficiently flexible in both directions — so that the demand for money
quickly adjusts to any given supply. Wages are actually “downward rigid” and will not fall in the
presence of excess supply of labor and if they do fall it will be very slowly. In the classical model,
there are two alternative ways of characterizing market equilibrium: when demand equals supply
and when price has reached a stable level. When prices do not fall in spite of the presence of an
excess supply, the two definitions are not equal. Keynes chose the second definition of
equilibrium which would be applicable regardless of whether prices were rigid or flexible. A
market simply achieves equilibrium at a point where the quantity and price stop adjusting. At the
heart of Keynes’s contribution is the proposition that savings equals investment. This follows
from a distinction that can be made between two components of demand: consumption which is
responsive to current income, and investment which is not related to current income but responds
to interest rates. Keynes concluded that it was investment that largely determined aggregate output
and employment. A return to full employment can only be achieved through appropriate policies,
specifically an increase in the money supply which creates an excess supply of money lowering
interest rates toward full employment. But in the spirit of savings equals investment, one might
want to increase the money flowing through the economy by increasing wages. In other words,
real wages, and increasing wages would increase demand, which would increase spending
resulting in more growth and profits that would then become savings that could be reinvested.
This might actually be more concrete than investment based on lower interest rates, which is still
borrowed rather than saved.
A wage policy that bolstered the middle class might be a means by which individuals
could be assured that they will continue to have purchasing power. This idea does have some roots
40
in institutional economics. John R. Commons , in particular, took the view that a decline in prices
and wages during recessions and depressions would only aggravate them by reducing purchasing
power and in turn leading to bankruptcy. For Commons, the answer lay in redistributing income
from profits to wages through collective bargaining agreements. Collective bargaining would both
prevent over savings and under-consumption, thereby assisting in maintaining purchasing power
and aggregate demand. Although he recognized that unions do have defects that might hinder
economic efficiency in various ways, he also believed that in most cases the benefits to society
would outweigh their costs (Kaufman 2003). The same argument could easily apply to a more
general wage policy, of which unionism is only one component.
A wage policy could be broadly defined as a set of institutions designed to bolster the
wages of the middle class. Historically these institutions assumed the form of labor policies that
allowed for unionization and collective bargaining, and specific wage floors. Traditionally, wage
floors assumed the form of federal and state minimum wage legislation. More recently, they have
assumed the form of Living Wage ordinances at the local level, and also broader proposals for
basic and/or minimum incomes (Van Parjis 1992; White 2003). Sidney Weintraub (1972) argued
for what he termed an “incomes policy” which would serve as an essential compliment to both
monetary and fiscal policy. The term “incomes policy” was often used as a euphemism for wage
restraint. Milton Friedman, for instance, called for a steady growth of roughly three percent in the
money supply to maintain a balance, because he assumed that money wages would be constrained.
Wages would increase to match productivity (which was roughly rising at three percent per year
overall), but faster wage growth would be harder to achieve. For Weintraub, the traditional tools
of economic growth were insufficient by themselves. The problem with fiscal policy was that it
41
involved huge expenditures of public monies, and unless it was properly targeted it was not going
to have the desired effects. Moreover, increased spending would only necessitate new taxes. And
the problem with monetary policy was that it too had a cost. Implemented by the Fed whose
primary constituency is the banking industry, the Fed could generally be relied upon in response to
rising inflation to apply the breaks with higher interest rates and reserve requirements, thereby
causing unemployment. But increased taxes due to increased spending only leads workers to seek
higher wages to pay the increased tax, thereby exacerbating inflation. Although economists were
often quick to apply the breaks to control for inflation, they were not the ones who would lose
their jobs as a result. Rather “The unemployed are thus the innocent lambs led to slaughter
through conventional tactics (pp. 117-118).” Rather if wages could be stabilized, then price
stability would avert economic damage resulting from convenient stabilization tools. An incomes
policy, in other words, would be a necessary compliment to these traditional tools.
While Weintraub saw wage policy as a compliment to other economic policy aimed at
achieving greater employment, it stands to reason that wage policy could at a minimum serve to
prevent long-term unemployment, if not form the basis of a jobs policy in its own right. Oren
Levin-Waldman (2011), for instance, looked at census data from 1962 to 2008 where he divided
the income distribution into wage contours — wage intervals. Starting from the statutory
minimum wage to 25 percent above as the first contour, he constructed nine additional contours,
which altogether encompassed up to 69 percent of the labor market. In years when the minimum
wage increased, the median wage in each of the ten contours also increased. In years when the
minimum wage did not increase, the median wage in each contour remained unchanged. During
periods when there had been no increases in the minimum wage, such as from 1981 to 1989, for
42
instance, there had been no increases in median wages during those periods. This would suggest
that the minimum wage has broader effects than commonly supposed. Contrary to the neoclassical
model that holds the minimum wage to have adverse employment consequences, the minimum
wage also has positive welfare benefits for the middle class.
To the extent that this is true, had a viable wage policy been in place, not only might wage
stagnation have been arrested, but the financial meltdown following the sub-prime crisis might not
have occurred, or would have been less likely to have occurred because people would have been
in a better position to pay off their mortgages. Although a wage policy would most likely have no
impact on the regular business cycle, it is quite possible that a policy in place that enables
individuals to maintain purchasing power, without necessarily having to resort to credit card debt,
will likely prevent the depths of a recession that we have been witness to beginning in 2007. A
wage policy will not necessarily jump start the economy to provide relief to the long-term
unemployed, but it in conjunction with other policies can be used hopefully to prevent long-term
unemployment in the future.
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