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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 2 (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 4 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 6 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, 7 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, 8 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. 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