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Date: Thursday, 17 Apr 2014 20:37

At a recent speech in Miami, Atlanta Fed President Dennis Lockhart had this to say:

Wage growth by most measures has been very low. I take this as a signal of labor market weakness, and in turn a signal of a lack of significant upward unit cost pressure on inflation.

This macroblog post examines whether the data support this assertion (answer: yes) and whether wage inflation is more sensitive to some measures of labor underutilization than other measures (answer: apparently, yes). San Francisco Fed President John Williams touched on the latter topic in a recent speech (emphasis mine):

We generally look at the overall unemployment rate as a good yardstick of labor market slack and inflation pressures. However, its usefulness may be compromised today by the extraordinary number of long-term unemployed—defined as those out of the workforce for six months or longer... Standard models of inflation typically do not distinguish between the short- and long-term unemployed, because they're assumed to affect wage and price inflation in the same way. However, recent research suggests that the level of long-term unemployment may not influence inflation pressures to the same degree as short-term unemployment.

And Fed Chair Janet Yellen said this at her March 19 press conference:

With respect to the issue of short-term unemployment and its being more relevant for inflation and a better measure of the labor market, I've seen research along those lines. I think it would be tremendously premature to adopt any notion that says that that is an accurate read on either how inflation is determined or what constitutes slack in the labor market.

The research to which President Williams refers are papers by economists Robert Gordon and Mark Watson, respectively. (For further evidence, see this draft by Princeton economists Alan Krueger, Judd Cramer and David Cho.)

The analysis here builds on this research by broadening the measures of labor underutilization beyond the short-term and long-term unemployment rates that add up to the standard unemployment rate called U-3. The U-5 underutilization measure includes both conventional unemployment and "marginally attached workers" who are not in the labor force but who want a job and have actively looked in the past year. The difference between U-5 and U-3 is a very close proxy for the number of marginally attached relative to the size of the labor force.

U-6 encompasses U-5 as well as those who work less than 35 hours for an economic reason. The difference between U-6 and U-5 is a very close proxy for the share of "part-time for economic reason" workers in the labor force. These nonoverlapping measures of labor underutilization rates are all shown in the chart below.


The series are highly correlated, making it difficult to isolate the impact of any particular labor underutilization rate on wage inflation (e.g., "How much will wage inflation change if the short-term unemployment rate rises 1.0 percentage point, holding all of the underutilization measures in the above figure constant?").

We follow the approach of Staiger, Stock, and Watson (2001) by using state-level data to relate wage inflation to unemployment in a so-called "wage-Phillips curve." Because the 2007–09 recession hit some states harder than others, we can use the cross-sectional variation in outcomes across states to arrive at more precise estimates of the separate impacts of the labor underutilization measures on wage inflation (see the chart).


Five-year state-level wage inflation rates for 2008–13, using monthly Current Population Survey(CPS) microdata, are shown on the vertical axis. The CPS microdata are also used to construct all of the labor underutilization measures. Each circle represents an individual state (red for long-term unemployment and blue for short-term unemployment), and each circle's area is proportional to the state's population share. Two noteworthy states are pointed out for illustration. North Dakota has had lower unemployment and (much) higher wage inflation than the other states (presumably because of its energy boom). And California has had higher unemployment and (somewhat) lower wage inflation than average. Even after excluding North Dakota, we see a clear negative relationship between wage inflation and underutilization measured with either short-term or long-term unemployment.

Because short-term and long-term unemployment are highly correlated (also apparent in the above plot), one can't tell visually if one underutilization measure is more important for wage inflation than the other. To make this assessment, we need to estimate a regression. The regression—which also includes both U-5 minus U-3 and U-6 minus U-5—adjusts wages for changes in the composition of the workforce. This composition adjustment, also made by Staiger, Stock and Watson (2001), controls for the fact that lower-skilled workers tend to be laid off at a disproportionately higher rate during recessions, thereby putting upward pressure on wages. The regression also weights observations by population shares.

The regression estimates imply that short-term unemployment is the most important determinant of wage inflation while U-6 minus U-5—the proxy for "part-time for economic reason" workers—also has a statistically significant impact. The other two labor underutilization measures do not affect wage inflation statistically different from zero. Rather than provide regression coefficients, we decompose observed U.S. wage inflation for 1995–2013 into contributions from the labor underutilization measures, workforce composition changes, and everything else (see the chart).


Both short-term unemployment and workers who are part-time for economic reasons have pushed down wage inflation. But the "part-time for economic reason" impact has become relatively more important recently because of the stubbornly slow decline in undesired part-time employment.

Photo of Patrick HigginsBy Pat Higgins, a senior economist in the Atlanta Fed's research department


Author: "macroblog" Tags: "Employment, Labor Markets, Unemployment"
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Date: Thursday, 10 Apr 2014 18:50

As a follow up to this post on recent trends in labor force participation, we look specifically at the prime-age group of 25- to 54-year-olds. The participation decisions of this age cohort are less affected by the aging population and the longer-term trend toward lower participation of youths because of rising school enrollment rates. In that sense, they give us a cleaner window on responses of participation to changing business cycle conditions.

The labor force participation rate of the prime-age group fell from 83 percent just before the Great Recession to 81 percent in 2013. The participation rate of prime-age males has been trending down since the 1960s. The participation rate of women, which had been rising for most of the post-World War II period, appears to have plateaued in the 1990s and has more recently shared the declining pattern of participation for prime-age men. But the decline in participation for both groups appears to have accelerated between 2007 and 2013 (see chart 1).

140410_1

We look at the various reasons people cite for not participating in the labor force from the monthly Current Population Survey. These reasons give us some insight into the impact of changes in employment conditions since 2007 on labor force participation. The data on those not in the official labor force can be broken into two broad categories: those who say they don't currently want a job and those who say they do want a job but don't satisfy the active search criteria for being in the official labor force. Of the prime-age population not in the labor force, most say they don't currently want a job. At the end of 2007, about 15 percent of 25- to 54-year-olds said they didn't want a job, and slightly fewer than 2 percent said they did want a job. By the end of 2013, the don't-want-a-job share had reached nearly 17 percent, and the want-a-job share had risen to slightly above 2 percent (see chart 2).

140410_2

Prime-Age Nonparticipation: Currently Want a Job
Most of the rise in the share of the prime-age population in the want-a-job category is due to so-called marginally attached individuals—they are available and want a job, have looked for a job in the past year, but haven't looked in the past four weeks—especially those who say they are not currently looking because they have become discouraged about job-finding prospects (see the blue and orange lines of chart 3). In 2013, there were about 1.1 million prime-age marginally attached individuals compared to 0.7 million in 2007, and the prime-age marginally attached accounted for about half of all marginally attached in the population.

140410_3

The marginally attached are aptly named in the sense that they have a reasonably high propensity to reenter the labor force—more than 40 percent are in the labor force in the next month and more than 50 percent are in the labor force 12 months later (see chart 4). This macroblog post discusses what the relative stability in the flow rate from marginally attached to the labor force means for thinking about the amount of slack labor resources in the economy.

140410_4

Prime-Age Nonparticipation: Currently Don't Want a Job
As chart 2 makes evident, the vast majority of the rise in prime-age nonparticipation since 2009 is due to the increase in those saying they do not currently want a job. The largest contributors to the increase are individuals who say they are too ill or disabled to work or who are in school or training (see the orange and blues lines in chart 5).

140410_5

Those who say they don't want a job because they are disabled have a relatively low propensity to subsequently (re)enter the labor force. So if the trend of rising disability persists, it will put further downward pressure on prime-age participation. Those who say they don't currently want a job because they are in school or training have a much greater likelihood of (re)entering the labor force, although this tendency has declined slightly since 2007 (see chart 6).

140410_6

Note that the number of people in the Current Population Survey citing disability as the reason for not currently wanting a job is not the same as either the number of people applying for or receiving social security disability insurance. However, a similar trend has been evident in overall disability insurance applications and enrollments (see here).

Some of the rise in the share of prime-age individuals who say they don't want a job could be linked to erosion of skills resulting from prolonged unemployment or permanent changes in the composition of demand (a different mix of skills and job descriptions). It is likely that the rise in share of prime-age individuals not currently wanting a job because they are in school or in training is partly a response to the perception of inadequate skills. The increase in recent years is evident across all ages until about age 50 but is especially strong among the youngest prime-age individuals (see chart 7).

140410_7

But lack of required skills is not the only plausible explanation for the rise in the share of prime-age individuals who say they don't currently want a job. For instance, the increased incidence of disability is partly due to changes in the age distribution within the prime-age category. The share of the prime-age population between 50 and 54 years old—the tail of the baby boomer cohort—has increased significantly (see chart 8).

140410_8

This increase is important because the incidence of reported disability within the prime-age population increases with age and has become more common in recent years, especially for those older than 45 (see chart 9).

140410_9

Conclusions
The health of the labor market clearly affects the decision of prime-age individuals to enroll in school or training, apply for disability insurance, or stay home and take care of family. Discouragement over job prospects rose during the Great Recession, causing many unemployed people to drop out of the labor force. The rise in the number of prime-age marginally attached workers reflects this trend and can account for some of the decline in participation between 2007 and 2009.

But most of the postrecession rise in prime-age nonparticipation is from the people who say they don't currently want a job. How much does that increase reflect trends established well before the recession, and how much can be attributed to the recession and slow recovery? It's hard to say with much certainty. For example, participation by prime-age men has been on a secular decline for decades, but the pace accelerated after 2007—see here for more discussion.

Undoubtedly, some people will reenter the labor market as it strengthens further, especially those who left to undertake additional training. But for others, the prospect of not finding a satisfactory job will cause them to continue to stay out of the labor market. The increased incidence of disability reported among prime-age individuals suggests permanent detachment from the labor market and will put continued downward pressure on participation if the trend continues. The Bureau of Labor Statistics projects that the prime-age participation rate will stabilize around its 2013 level. Given all the contradictory factors in play, we think this projection should have a pretty wide confidence interval around it.

Note: All data shown are 12-month moving averages to emphasize persistent shifts in trends.

Melinda PittsBy Melinda Pitts, director, Center for Human Capital Studies,

John RobertsonJohn Robertson, a vice president and senior economist in the Atlanta Fed's research department, and

Ellyn TerryEllyn Terry, a senior economic analyst in the Atlanta Fed's research department

Author: "macroblog" Tags: "Business Cycles, Employment, Labor Marke..."
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Date: Wednesday, 09 Apr 2014 14:56

Introduction
The rate of labor force participation (the share of the civilian noninstitutionalized population aged 16 and older in the labor force) has declined significantly since 2007. To what extent were the Great Recession and tepid recovery responsible?

In this post and one that will follow, we offer a series of charts using data from the Current Population Survey to explore some of the possible reasons behind the 2007–13 drop in participation. This first post describes the impact of the changing-age composition of the population and changes in labor force participation within specific age cohorts—see Calculated Risk posts here and here for a related treatment, and also this recent BLS study. The next post will look at the issue of potential cyclical impacts on participation by examining the behavior of the prime-age population.

Putting the decline in context
After rising from the mid-1960s through 1990, the overall labor force participation rate was relatively stable between 1990 and 2007. But participation has declined sharply since 2007. By 2013, participation was at the lowest level since 1978 (see chart 1).

140407_1

For men, the longer-term declining trend of participation accelerated after 2007. For women, after having been relatively stable since the late 1990s, participation began to decline after 2009. The decline for both males and females since 2009 was similar (see chart 2).

140407_2

The impact of retirement
One of the most important features of labor force participation is that it varies considerably over the life cycle: the rate of participation is low among young individuals, peaks during the prime-age years of 25 to 54, and then declines (see chart 3). So a change in the age distribution of the population can result in a significant change in overall labor force participation.

140407_3

The age distribution of the population has been shifting outward for some time. This is a result of the so-called baby boomer generation—that is, people born between 1946 and 1964 (see chart 4). The oldest baby boomers turned 62 in 2008 and became eligible for Social Security retirement benefits.

140407_4

At the same time the age distribution of the population has shifted out, the rate of retirement of older Americans has been declining. Retirement rates have generally been drifting down since the early 2000s (see chart 5). The decline in age-specific retirement rates has resulted in rising age-specific labor force participation rates. For example, from 1999 to 2013, the share of 62-year-old retirees declined from 38 percent to 28 percent. The BLS projects that this trend will continue at a similar pace in coming years (see table 3 of the BLS report).

140407_5

Although the decline in the propensity to retire has put some upward pressure on overall labor force participation, that effect is dominated by the sheer increase in the number of people reaching retirement age. The net result has been a steep rise in the share of the population saying they are not in the labor force because they are retired (see chart 6).

140407_6

Participation by age group
Individuals aged 16–24
The labor force participation rate for young individuals (between 16 and 24 years old) has been generally declining since the late 1990s. After slowing in the mid-2000s, the decline accelerated again during the Great Recession. However, participation has been relatively stable since 2009 (see chart 7). Nonetheless, the BLS projects that the participation rate for 16- to 24-year-olds will decline further, albeit at a slower pace than it declined between 2000 and 2009, and will fall a little below 50 percent by 2022.

140407_7

The change in participation among young people can be attributed almost entirely to enrollment rates in education programs (see here) and lower labor force participation among enrollees (see chart 8). The change in the share of 16- to 24-year-olds who say they don't currently want a job because they are in school closely matches the change in labor force participation for the entire cohort.

140407_8

Individuals aged 25–54 (prime age)
Generally, people aged 25 to 54 are the group most likely to be participating in the labor market (see chart 3). These so-called prime-age individuals are less likely to be making retirement decisions than older individuals, and less likely to be enrolled in schooling or training than younger individuals.

However, the prime-age labor force participation rate declined considerably between 2007 and 2013, and at a much faster pace than had been seen in the years prior to the recession (see chart 9). Reflective of the overall gender-specific participation differences seen in chart 2, the decline in prime-age female participation did not take hold until after 2009, and since 2009 the decline in both prime-age male and female participation has been quite similar. Nevertheless, the BLS projects that prime-age participation will stabilize in coming years and prime-age participation in 2022 will be close to its 2013 level.

140407_9

Implications
The BLS projects that participation by age group will look like this in 2022 relative to 2013 (see chart 10).

140407_10

Participation by youths is projected to continue to fall. The participation of older workers is projected to increase, but it will remain significantly lower than that of the prime-age group. Combined with an age distribution that has also continued to shift outward (see chart 11), the overall participation rate is expected to decline over the next several years from its 2013 level of around 63.3 percent. From the BLS study:

A combination of demographic, structural, and cyclical factors has affected the overall labor force participation rate, as well as the participation rates of specific groups, in the past. BLS projects that, as has been the case for the last 10 years or so, these factors will exert downward pressure on the overall labor force participation rate over the 2012–2022 period and the rate will gradually decline further, to 61.6 percent in 2022.

140407_11

However, an important assumption in the BLS projection is that the post-2007 decline in prime-age participation will not persist. Indeed, the data for the first quarter of 2014 does suggest that some stabilization has occurred.

But separating what is trend from what is cyclical is challenging. The rapid pace of the decline in participation among the prime-age population between 2007 and 2013 is somewhat puzzling. Could this decline reflect a temporary cyclical effect or something more permanent? A follow-up blog will explore this question in more detail using the micro data from the Current Population Survey.

Note: All data shown are 12-month moving averages to emphasize persistent shifts in trends.

 

Melinda PittsBy Melinda Pitts, director, Center for Human Capital Studies,

John RobertsonJohn Robertson, a vice president and senior economist in the Atlanta Fed's research department, and

Ellyn TerryEllyn Terry, a senior economic analyst in the Atlanta Fed's research department

Author: "macroblog" Tags: "Business Cycles, Employment, Unemploymen..."
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Date: Tuesday, 18 Mar 2014 17:17

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A little more than a week ago, all eyes were on the February Employment Situation report released by the U.S. Bureau of Labor Statistics. The Establishment Survey surprised on the upside: nonfarm payrolls rose 175,000 in February, and payrolls were revised upward for December and January. The Household Survey indicated that the unemployment rate edged up slightly to 6.7 percent in February from 6.6 percent the prior month, and the labor force participation rate held steady at 63.0 percent.

These are some of the facts on the table as the Federal Open Market Committee meets today and tomorrow and, judging from recent comments from the folks who will be at that meeting, those facts (and more like them) will be very much front of mind.

These days, multiple tools are available to assist both casual and expert observers in navigating the rich and sometimes baffling story of labor markets in the post-Great Recession world. Just last week, you could find a new "Guide for the Perplexed" on labor market slack in The New York Times and an interactive feature on the "Eight Different Faces of the Labor Market" at the New York Fed's Liberty Street Economics blog. And that's not to mention the most recent update of the Atlanta Fed’s own 13-headed Labor Market Spider Chart.

All of these contributions reflect a great deal of effort to understand the story of what's happening in labor markets. As part of that effort, our colleagues across the Federal Reserve System have been taking deeper dives into employment statistics and reaching out into their communities to get a better understanding of labor force dynamics and workforce development issues. This research can be found on the various Reserve Bank and Board websites.

To facilitate access to that work, the Atlanta Fed's Center for Human Capital Studies has worked to bring those resources together in the Federal Reserve Human Capital Compendium (HCC). We are pleased to announce that we have recently enhanced the HCC so you can perform simple or advanced searches that allow you to research whatever facet of that research strikes your fancy (see the figure):

We encourage you to take your own deeper dive into the latest research across the Federal Reserve System by browsing the HCC or searching out those labor topics that have piqued your interest lately.

Photo of Whitney MancusoBy Whitney Mancuso, a senior economic analyst in the Atlanta Fed's research department

Author: "macroblog" Tags: "Employment, Labor Markets, Unemployment"
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Date: Saturday, 08 Mar 2014 15:59

Today's employment report for the month of February maybe took a bit of drama out of one key question going into the next meeting of the Federal Open Market Committee (FOMC): What will happen to the FOMC's policy language when the economy hits or passes the 6.5 percent unemployment rate threshold for considering policy-rate liftoff? With the unemployment rate for February checking it at 6.7 percent, a breach of the threshold clearly won't have happened when the Committee meets in a little less than two weeks.

I say "maybe took a bit of drama out" because I'm not sure there was much drama left. All you had to do was listen to the Fed talkers yesterday to know that. This is from the highlights summary of a speech yesterday by Charles Plosser, president of the Philadelphia Fed...

President Plosser believes the Federal Open Market Committee has to revamp its current forward guidance regarding the future federal funds rate path because the 6.5 percent unemployment threshold has become irrelevant.

... and this from a Wall Street Journal interview with William Dudley, president of the New York Fed:

Mr. Dudley, in a Wall Street Journal interview, also said the Fed's 6.5% unemployment rate threshold for considering increases in short-term interest rates is "obsolete" and he would advocate scrapping it at the Fed's next meeting March 18–19.

From our shop, Atlanta Fed president Dennis Lockhart echoed those sentiments in a speech at Georgetown University:

Given that measured unemployment is so close to 6.5 percent, the time is approaching for a refreshed explanation of how unemployment or broader employment conditions are to be factored into a liftoff decision.

That statement doesn't mean we in Atlanta are disregarding the unemployment rate altogether. We have for some time been describing the broader net we have cast in fishing for labor market clues. One important aspect of that broader perspective is captured in the so-called U-6 measure of unemployment, about which President Lockhart's speech gives a quick tutorial:

The data used to construct the unemployment rate come from a survey of households conducted by the Census Bureau for the Bureau of Labor Statistics. To be counted as a participant in the labor force, a respondent must give rather specific qualifying answers to questions in the survey...

Those who are available, have looked for work in the past year, but have not recently looked for work are labeled "marginally attached." They are not in the official labor force, so they are not officially unemployed. You might say they are a "shadow labor force"...

One measure that counts the marginally attached in the pool of the unemployed is U-6.

U-6 also includes working people who identify themselves as working "part time for economic reasons." These are people who want to work full time (defined as 35 hours or more) but are able only to get fewer than 35 hours of work.

The "shadow labor force" comment is based on these observations. First, in President Lockhart's words:

The makeup of the class of marginally attached workers is quite fluid. About 40 percent of the marginally attached in any given month join the official labor force in the subsequent month.

There is no new story there. The frequency with which people move from marginally attached to in the labor force has been stable for quite a while (see the chart):


President Lockhart's second observation regarding the marginally attached is more important:

But only about 10 percent of those who move into the labor force find a job right away. In effect, they went from unofficially unemployed to officially unemployed.

The chart below depicts this observation:


Relative to before the Great Recession, the frequency with which people transitioned from marginally attached to employment has fallen by about 5 percentage points.

That decline is related to this conclusion (again from President Lockhart):

Here's my point: what U-6 captures matters. Measures such as marginally attached and part time for economic reasons became elevated in the recession and have not come down materially. Said differently, broader measures of unemployment like U-6 suggest that a significant level of slack remains in our employment markets.

It is not that we have failed to see progress in the U-6 measure of labor market slack. In fact, since the end of the recession, the U-6 unemployment rate has declined about in tandem with the standard official unemployment rate (designated U-3 by the U.S. Bureau of Labor Statistics; see the chart):


What is the case is that we have failed to undo the outsized run-up in the marginally attached and people working part-time for economic reasons that occurred during the recession (see the chart):


One interpretation of these observations is that the relative increase in U-6 represents structural changes that cannot be fixed by policies aimed at stimulating spending. But we are drawn to the fact, described above, that the marginally attached are flowing into the labor market at the same pace as before the recession, but they are finding jobs at a much slower pace, making us hesitant to fully embrace a structural interpretation.

Or, as our boss said yesterday:

As a policymaker, I am concerned about the unemployed in the official labor force, but I am also concerned about the unemployed in the shadow labor force. To get close to full employment, as I think of it, would involve substantial absorption of this shadow labor force. I do not think we're near that point yet. This is one of the reasons I support continuing with a highly accommodative policy and deferring liftoff for a while longer.

But if you are looking for some good news, here it is: Though the official unemployment rate has been essentially flat for the past three months, the broader U-6 measure that we are monitoring closely has fallen by half a percentage point. More of that, and we will really be getting somewhere.

Photo of Dave AltigBy Dave Altig, research director and executive vice president at the Atlanta Fed


Author: "macroblog" Tags: "Employment, Labor Markets, Unemployment"
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Date: Wednesday, 26 Feb 2014 23:03

A recent Wall Street Journal blog post caught our attention. In particular, the following claim:

It’s not size that matters—at least when it comes to job creation. The age of the company is a bigger factor.

This observation is something we have also been thinking a lot about over the past few years (see for example, here, here, and here).

The following chart shows the average job-creation rate of expanding firms and the average job-destruction rates of shrinking firms from 1987 to 2011, broken out by various age and size categories:

In the chart, the colors represent age categories, and the sizes of the dot represent size categories. So, for example, the biggest blue dot in the far northeast quadrant shows the average rate of job creation and destruction for firms that are very young and very large. The tiny blue dot in the far east region of the chart represents the average rate of job creation and destruction for firms that are very young and very small. If an age-size dot is above the 45-degree line, then average net job creation of that firm size-age combination is positive—that is, more jobs are created than destroyed at those firms. (Note that the chart excludes firms less than one year old because, by definition in the data, they can have only job creation.)

The chart shows two things. First, the rate of job creation and destruction tends to decline with firm age. Younger firms of all sizes tend to have higher job-creation (and job-destruction) rates than their older counterparts. That is, the blue dots tend to lie above the green dots, and the green dots tend to be above the orange dots.

The second feature is that the rate of job creation at larger firms of all ages tends to exceed the rate of job destruction, whereas small firms tend to destroy more jobs than they create, on net. That is, the larger dots tend to lie above the 45-degree line, but the smaller dots are below the 45-degree line.

As pointed out in the WSJ blog post and by others (see, for example, work by the Kauffman Foundation here and here), once you control for firm size, firm age is the more important factor when measuring the rate of job creation. However, young firms are more dynamic in general, with rapid net growth balanced against a very high failure rate. (See this paper by John Haltiwanger for more on this up-or-out dynamic.) Apart from new firms, it seems that the combination of youth (between one and ten years old) and size (more than 250 employees) has tended to yield the highest rate of net job creation.

John RobertsonBy John Robertson, a vice president and senior economist in the Atlanta Fed’s research department, and

Ellyn TerryEllyn Terry, a senior economic analyst in the Atlanta Fed's research department


Author: "macroblog" Tags: "Economic conditions, Employment, Labor M..."
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Date: Friday, 21 Feb 2014 14:33

Will the Federal Open Market Committee's (FOMC) current large-scale asset purchase program, so-called QE3, continue to melt away as spring arrives? The release of the minutes from the January meeting of the FOMC, along with commentary from various participants in that meeting (noted in rapid succession here, here, and here, for example) have left the distinct impression that the answer is most probably yes.

The anticipated winding down of asset purchases almost inevitably invokes a habit of language concerning what it all means for the stance of monetary policy. From the New York Times, for example, we have this (emphasis added):

When Federal Reserve officials last met at the end of January, they were surprised by the strength of the economy, cheered by the optimism of consumers and convinced they should continue to dismantle the Fed's economic stimulus campaign, according to an account the Fed released Wednesday.

The sentiment expressed in that highlighted passage is front and center at the G-20 meetings, currently taking place in Australia (again, emphasis added):

Setting the scene for this weekend's Group of 20 meetings, Australian Treasurer Joe Hockey's main challenge was to avoid appearing partial in the escalating blame-game between the U.S. and developing countries over the recent exodus of capital from emerging markets….

Emerging market countries like India and Brazil have blamed the wide-scale selloff in local stocks, bonds and currencies on the Federal Reserve's plan to exit gradually from monetary-stimulus policies, which last year began sending investors into a panic.

Here's the thing. It is not at all clear that winding down asset purchases means an exit from or dismantling of monetary stimulus, gradual or otherwise. In Atlanta Fed President Dennis Lockhart's words yesterday:

In our public remarks over much of last year, my colleagues and I stressed a couple of very important messages. First, even with the phase-out of asset purchases, the basic stance of policy remains highly accommodative. To translate, the Committee intends to keep interest rates very low. The second message was that the QE program and the Fed's policy interest-rate target are two separate tools of policy. Consequently, we can wind down the asset purchases—a program that was meant to provide temporary, supplemental "oomph" to the low interest-rate policy—and preserve the accommodative positioning of policy appropriate for the reality of our economic situation.

But those are not just words. Several months back, Jim Hamilton publicized the work of Cynthia Wu and Dora Xia (former and current students of his), who have developed a method of using term structure data to infer the "shadow," or implicit, monetary policy rate. (Follow-up posts appeared thereafter at Econbrowser—here and here—and from the crew here at macroblog.)

Just recently, the Wu-Xia data has been updated, giving us a first glance at the post-taper shadow policy rate (see the chart):

Both Treasury yields and the shadow policy rate did in fact spike last June following then-Chairman Ben Bernanke's post-FOMC press conference, wherein he signaled that the asset-purchase taper was indeed on the table. But he also made the point that bringing down the QE pillar of the Fed's policy mix is decidedly not the same thing as bringing monetary stimulus to an end, a message that was subsequently emphasized by Fed officials many times, in many forums.

Though financial market participants may have been convinced that the taper meant tightening initially, it does appear that communications and forward guidance have done the trick of more than reversing that initial impression. At the very least, the Wu-Xia calculations are consistent with that interpretation.

David Altig By Dave Altig, executive vice president and research director at the Atlanta Fed

Author: "macroblog"
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Date: Tuesday, 11 Feb 2014 21:04

This analysis is a companion piece to my Atlanta Fed colleague John Robertson's recent macroblog post. John's blog highlighted some findings of a recent New York Fed study by Samuel Kapon and Joseph Tracy on the employment-to-population (E/P) ratio. Their work has received considerable attention in the media and blogosphere (for example, here, here, and here). Kapon and Tracy's final chart (reproduced below) has received particular scrutiny.


The blue line represents the authors' estimate of the demographically adjusted E/P ratio purged of business-cycle effects. This line can be thought of as "trend." The chart shows that as of November 2013, the E/P ratio was only –0.7 percentage point below trend. Was the "gap" between actual and trend E/P really this small?

Attempting to answer this question requires digging into the details of Kapon and Tracy's method for estimating trend. One key excerpt is the following:

To overlay our demographically adjusted E/P ratio with the actual E/P ratio, we need to adopt a normalization… [W]e adopt the normalization that over the thirty-one years in our data sample [1982–2013] any business-cycle deviations between the actual and the adjusted E/P ratios will average to zero.

This methodology seems reasonable since one might typically expect business cycle effects to average out over 30 years. However, the 1982–2013 sample period is somewhat unusual in that the unemployment rate was elevated at both the starting and ending points.

The chart below shows estimates of three labor market gaps derived from the Congressional Budget Office's (CBO) estimates—released on February 4, 2014—of the potential labor force and the long-term natural rate of unemployment. (This rate is often referred to as the nonaccelerating inflation rate of unemployment, or NAIRU, and refers to the level of unemployment below which inflation rises.)


On average, the trend E/P ratio is below the actual rate by 0.86 percentage point. If one were to normalize the Kapon and Tracy E/P trend so that its average value was equal to CBO's trend, then the November 2013 E/P gap is about 1.5 percentage points. Whether or not the CBO estimate is the right benchmark is a matter of taste. CBO's recent estimate of NAIRU in the fourth quarter of 2013—5.5 percent—is lower than the 6 percent median estimate from the Survey of Professional Forecasters in the third quarter of 2013.

A second, more subtle issue in the Kapon and Tracy analysis is their treatment of cohorts:

We divide these individuals into 280 different cohorts defined by each individual's decade of birth, sex, race/ethnicity, and educational attainment. We assume that individuals within a specific cohort have similar career employment rate profiles. We use the 10.2 million observations [of CPS microdata] to estimate these 280 career employment rate profiles.

A well-known 2006 Brookings paper by Stephanie Aaronson and other Fed economists modeled trend labor force participation rate(LFPR) using birth-year cohorts. With estimates of trend LFPR and NAIRU, we can back out a trend E/P ratio. The chart below, adapted from Aaronson et al., plots age-group LFPRs against birth year.


We see that successive birth-year cohorts born between 1925 and 1950 had steadily increasing labor force attachment. Attachment for more recently born cohorts has leveled off and even declined slightly. People born in the 1990s have very low labor force attachment by historical standards. The inclusion of the "1990s—decade of birth" dummy variable in the Kapon and Tracy research probably implies that their model is interpreting much of this decline as structural. However, an alternative interpretation is that the decline is cyclical, because persons born after 1990 have been in an environment of high unemployment for most of their short working lives.

To gauge the sensitivity of trend or structural LFPR to how the youngest cohorts are treated, I used a stripped-down version of a model similar to Aaronson et al. Monthly LFPRs are modeled as a function of age, sex, birth date, and the CBO's estimate of the output gap during the January 1981 to January 2014 period. Time series published by the U.S. Bureau of Labor Statistics for 30 different age-sex cells are used so that the regression has 11,550 observations. Structural LFPR is constructed with the fitted values of the regression with a value of 0 percent for the output gap at all points in time. The trend E/P ratio is then backed out with the CBO's estimate of NAIRU.

The model is run with two different assumptions: First, following the approach of Aaronson et al., people born after 1986 have the same birth-year cohort effects as those born in December 1986. Second, no constraints are placed on birth-year cohort effects. Trend values of LFPR and E/P (taking on board the CBO's NAIRU) are plotted in the two charts below:




The January 2014 E/P gap with unconstrained cohort effects, as in Kapon and Tracy, is –1.0 percent, well below the –1.7 percent gap in the model with constrained cohort effects. Ultimately, both models are still very consistent with Kapon and Tracy's bottom line:

It is important to control for changing demographic factors when looking at the behavior of the E/P ratio over time. This step is particularly important today when these demographic factors are exerting downward pressure on the actual E/P rate, suggesting that the recent lack of improvement in the E/P ratio does not imply a lack of progress in the labor market. The adjusted E/P rate corroborates the basic picture from the unemployment rate that the labor market has been recovering over the past few years, but that it still has a ways to go to reach a full recovery.

Photo of Pat HigginsBy Pat Higgins, senior economist in the Atlanta Fed's research department

 

 

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Date: Thursday, 06 Feb 2014 20:56

Trying to interpret changes in labor utilization measures such as the employment-to-population ratio is complicated by the fact that they do not refer to the same set of people over time. The age composition of the population is changing, and behavior can vary across and within age cohorts.

This issue is illustrated in a recent New York Fed study of the employment-to-population ratio by Samuel Kapon and Joseph Tracy. This ratio nosedived during the recent recession by about 4 percentage points and has barely budged since.

This measure of labor utilization is the clear laggard on any labor market recovery dashboard. But the authors show that it is not so clear that the employment-to-population ratio is really so far from where it should be, once you control for the fact the employment rates tend to be lower for younger and older people and that the age composition within the population has shifted over time. This idea is similar to the one used to estimate the trend labor force participation rate in this Chicago Fed study by Daniel Aaronson, Jonathan Davis, and Luojia Hu. The issue of controlling for dominant demographic trends is one of the reasons we at the Atlanta Fed decided not to feature either the overall employment-to-population ratio or the overall labor force participation rate in our Labor Market Spider Chart.

A simple, and admittedly crude, alternative to computing the demographically adjusted employment-to-population ratio trend is to look at a segment of the population that is on a relatively flat part of the employment (or participation) rate curve. A common standard for this is the so-called prime-aged population (people aged 25 to 54). These individuals are less likely to be making retirement decisions than older individuals and are less likely to be making schooling decisions than younger people. Of course, this approach doesn't control for within-cohort factors like educational differences.

So what do we find? The prime-aged employment-to-population ratio declined almost 5 percentage points between the end of 2007 and 2009 (versus 4 percentage points overall) and since then has recovered about 25 percent of that decline. Using the end of 2007 as reference, the Kapon and Tracy trend estimate has declined about 1.7 percentage points, which implies the overall employment-to-population ratio, by not continuing to decline, has improved by about 40 percent.

Then what does the analysis say about labor utilization in the wake of the recession? Once demographic factors are controlled for, both aforementioned measures indicate that labor-resource utilization has improved relative to trend. In fact, as Kapon and Tracy note, the relative improvement would be even greater if you believed that employment was above trend before the recession.

Photo of John RobertsonBy John Robertson, a vice president and senior economist in the Atlanta Fed's research department


Author: "macroblog" Tags: "Employment, Labor Markets, Unemployment"
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Date: Tuesday, 28 Jan 2014 12:25

Last month, we at the Atlanta Fed had the great pleasure of hosting Sergio Rebelo for a couple of days. While he was here, we asked Sergio to share his thoughts on a wide range of current economic topics. Here is a snippet of a Q&A we had with him about the state of the euro-area economy:

Sergio, what would you say was the genesis of the problems the euro area has faced in recent years?

The contours of the euro area’s problems are fairly well known. The advent of the euro gave peripheral countries—Ireland, Spain, Portugal, and Greece—the ability to borrow at rates that were similar to Germany's. This convergence of borrowing costs was encouraged through regulation that allowed banks to treat all euro-area sovereign bonds as risk free.

The capital inflows into the peripheral countries were not, for the most part, directed to the tradable sector. Instead, they financed increases in private consumption, large housing booms in Ireland and Spain, and increases in government spending in Greece and Portugal. The credit-driven economic boom led to a rise in labor costs and a loss of competitiveness in the tradable sector.

Was there a connection between the financial crisis in the United States and the sovereign debt crisis in the euro area?

Simply put, after Lehman Brothers went bankrupt, we had a sudden stop of capital flows into the periphery, similar to that experienced in the past by many Latin American countries. The periphery boom quickly turned into a bust.

What do you see as the role for euro area monetary policy in that context?

It seems clear that more expansionary monetary policy would have been helpful. First, it would have reduced real labor costs in the peripheral countries. In those countries, the presence of high unemployment rates moderates nominal wage increases, so higher inflation would have reduced real wages. Second, inflation would have reduced the real value of the debts of governments, banks, households, and firms. There might have been some loss of credibility on the part of the ECB [European Central Bank], resulting in a small inflation premium on euro bonds for some time. But this potential cost would have been worth paying in return for the benefits.

And did this happen?

In my view, the ECB did not follow a sufficiently expansionary monetary policy. In fact, the euro-area inflation rate has been consistently below 2 percent and the euro is relatively strong when compared to a purchasing-power-parity benchmark. The euro area turned to contractionary fiscal policy as a panacea. There are good theoretical reasons to believe that—when the interest rate remains constant that so the central bank does not cushion the fall in government spending—the multiplier effect of government spending cuts can be very large. See, for example, Gauti Eggertsson and Michael Woodford, “The Zero Interest-rate Bound and Optimal Monetary Policy,” and Lawrence Christiano, Martin Eichenbaum, and Sergio Rebelo, "When Is the Government Spending Multiplier Large?

Theory aside, the results of the austerity policies implemented in the euro area are clear. All of the countries that underwent this treatment are now much less solvent than in the beginning of the adjustment programs managed by the European Commission, the International Monetary Fund, and the ECB.

Bank stress testing has become a cornerstone of macroprudential financial oversight. Do you think they helped stabilize the situation in the euro area during the height of the crisis in 2010 and 2011?

No. Quite the opposite. I think the euro-area problems were compounded by the weak stress tests conducted by the European Banking Association in 2011. Almost no banks failed, and almost no capital was raised. Banks largely increased their capital-to-asset ratios by reducing assets, which resulted in a credit crunch that added to the woes of the peripheral countries.

But we’re past the worst now, right? Is the outlook for the euro-area economy improving?

After hitting the bottom, a very modest recovery is under way in Europe. But the risk that a Japanese-style malaise will afflict Europe is very real. One useful step on the horizon is the creation of a banking union. This measure could potentially alleviate the severe credit crunch afflicting the periphery countries.

Thanks, Sergio, for this pretty sobering assessment.

John RobertsonBy John Robertson, a vice president and senior economist in the Atlanta Fed’s research department

Editor’s note: Sergio Rebelo is the Tokai Bank Distinguished Professor of International Finance at Northwestern University’s Kellogg School of Management. He is a fellow of the Econometric Society, the National Bureau of Economic Research, and the Center for Economic Policy Research.


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Date: Saturday, 18 Jan 2014 04:11

Despite the addition of only 74,000 jobs to the economy in December, the unemployment rate dropped significantly—from 7 percent to 6.7 percent. The decline came mostly from a decrease in the labor force.

Since the recession began, the labor force participation rate (LFPR) has dropped from 66 percent to 63 percent. Many people have left the labor force because they are discouraged from applying (U.S. Bureau of Labor Statistics data indicate that a little under 1 million people fall into this category). But the primary drivers appear to be an increase in the number of people who are either retired, disabled/ill, or in school.

Certainly, the aging of the population accounts for much of the increase in the retired and disabled/ill categories. Still, there has been a lot of movement over the past few years in the reasons people cite for not participating in the labor force within age groups. Knowing the reasons why people have left (or delayed entering) the labor force can help us understand how much of the decline will likely halt once the economy picks back up and how much is permanent. (For more on this topic, see here, here, and here.)

The chart below shows the distribution of reasons in the fourth quarter of 2013. (Of the people not in the labor force, 1.6 percent indicate they want a job and give a reason for not being in the labor force. They are categorized here as "want a job" only.) Young people are not in the labor force mostly because they are in school. Individuals 25 to 50 years old who are not in the labor force are mostly taking care of their family or house. After age 50, disability or illness becomes the primary reason people do not want to work—until around age 60, when retirement begins to dominate.


How has this distribution changed over the past seven years? For simplicity, I've grouped people by age to show changes over time in the reasons people give for not being in the labor force. However, you can also see an interactive version of the same data without age buckets—and download the data—here.

Of the 12.6 million increase in individuals not in the labor force, about 2.3 million come from people ages 16 to 24, and of that subset, about 1.9 million can be attributed to an increase in school attendance (see the chart below). In particular, young people aged 19 to 24 are more likely to be in school now than before the recession. Among college-age people, those absent from the labor force because they are in school rose from 57 percent to 60 percent. Among people of high school age, the share not in the labor force because they are in school rose from 87 percent to 88 percent.


The number of middle-aged workers not in the labor force rose by 1.8 million (or 11 percent), with four main factors driving the increase.* "Wants a Job" increased 546,000 (34 percent). The "In School" category increased 438,000 (a 38 percent rise). "Disability/Illness" rose 393,000 (an 8 percent rise), and 302,000 more people said they were retired (a 43 percent rise; see the chart below).


Among individuals aged 51 to 60, those not in the labor force increased by 1.6 million (or 16 percent). This increase came almost entirely from the number of people who are disabled or ill, which rose by 1.3 million (a 33 percent increase). Interestingly, the number of retired individuals actually fell by 305,000 between the fourth quarter of 2007 and the fourth quarter of 2010. Since then, the number of retired people within this age group has risen 183,000 but remains 122,000 lower than fourth-quarter 2007 levels. So it seems more people in this age group were delaying retirement instead of leaving early (see the chart below).


About 6.8 million of the 12.6 million increase in those not in the labor force came from the 61-and-over category. An additional 5.3 million (a 17 percent increase) are retired, and 1 million more (a 34 percent increase) are not in the labor force because they are disabled or ill. The other categories were little changed (see the chart below).


In total, the number of people not in the labor force rose by 12.6 million (16 percent) from the fourth quarter of 2007 to the fourth quarter of 2013. About 5.5 million more people (a 16 percent increase) are retired, 2.9 million (a 23 percent increase) are disabled or ill, and 2.5 million (a 19 percent increase) are in school. An additional 161,000 are taking care of their family or house, and an additional 99,000 are not in the labor force for other reasons. The fraction who say they want a job has risen the most (32 percent) but has contributed only 11 percent to the total change. The chart below shows the overall contributions by reason to the changes in labor force participation for all age groups since the onset of the recession.


What further changes can we anticipate? It's hard to say, as many moving parts are at play. Most people currently in school will be approaching the labor market upon graduation. But increased college and graduate school enrollment could augur a permanent shift in the portion of the population who are in school instead of the labor force. We can also expect continued downward pressure on the LFPR from retiring baby boomers as well as boomers who exit the labor force because of disability or illness.

Last, the portion of people who want a job has increased the most since the recession began, and is currently 1.4 million above its prerecession level. People in this category tend to have greater labor force attachment, making them more likely to shift into the labor force. In fact, the number of people in this category has already started to decrease—and is down 709,000 from the fourth quarter 2012.

My Atlanta Fed colleagues Julie Hotchkiss and Fernando Rios-Avila in their 2013 paper "Identifying Factors behind the Decline in the U.S. Labor Force Participation Rate," looked at a range of LFPR projections for 2015–17 based on different labor market assumptions. Depending on the future strength of the U.S. labor market, the projections are highly varying—ranging between a decline of 2.4 percentage points and an increase of 2 percentage points from the 2010–12 average of 64.1 percent. So far, more factors are pulling down the LFPR than pushing it up; the latest reading for December 2013 is already 1.3 percentage points below the 2010–12 average. At that pace, the Hotchkiss et al. lower-bound estimate will be reached before the end of 2014, unless the dynamics change as the economy further improves.

Photo of Ellyn TerryBy Ellyn Terry, an economic policy analysis specialist in the research department of the Atlanta Fed



* I've chosen to break the "middle-age" grouping at age 50 instead of 54 because the probability of retiring has changed in different ways over the past few years for the 25- to 50-year-old group and the 51- to 60-year-old group. See the chart mentioned earlier for more detail.

 

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Date: Tuesday, 14 Jan 2014 20:23

The December meeting of the Federal Open Market Committee (FOMC), as summarized in the minutes published last week, debated the context for tapering the quantitative easing (QE) program of asset purchases and adjusting the FOMC’s forward guidance on the federal funds rate. One of the issues debated was postrecession progress in the labor market. For example, participants struggled with the reasons for the large drop in labor force participation in recent years:

Some participants cited research that found that demographic and other structural factors, particularly rising retirements by older workers, accounted for much of the recent decline in participation. However, several others continued to see important elements of cyclical weakness in the low labor force participation rate and cited other indicators of considerable slack in the labor market, including the still-high levels of long-duration unemployment and of workers employed part time for economic reasons and the still-depressed ratio of employment to population for workers ages 25 to 54. In addition, although a couple of participants had heard reports of labor shortages, particularly for workers with specialized skills, most measures of wages had not accelerated. A few participants noted the risk that the persistent weakness in labor force participation and low rates of productivity growth might indicate lasting structural economic damage from the financial crisis and ensuing recession.

In a speech on Monday, Atlanta Fed President Dennis Lockhart emphasized similar concerns. He posed the question of whether the improvement in the unemployment rate since the end of the recession, now having recovered about 65 percent of its 2007–09 increase, is overstating the actual progress in the utilization of the nation’s labor resources. President Lockhart observes:

But the unemployment rate is influenced by labor force participation, and there has been a sizable decline in the share of the population in the labor force since 2009. This explains how you could get a big drop in the unemployment rate with anemic job gains, as occurred in December.

The labor force participation rate has fallen from 65.8 percent of the population at the end of 2008 to 62.8 percent in December 2013. On this, President Lockhart notes:

Some of the decline in labor force participation since 2009 is due to the baby boomers retiring, but even among prime-age workers—those aged 25 to 54—the participation rate is down significantly [2.1 percentage points]. This suggests that other factors, such as low prospects of finding a job, are playing a role.

To examine this possibility, we can look at the sum of marginally attached workers. These are people who say they are willing to work and have looked for work recently but are not currently looking.

The marginally attached are not counted in the official labor force statistic. During the recession, the number of marginally attached swelled (from around 1.4 million at the end of 2007 to 2.4 million at the end of 2009). Since the end of 2009, the marginally attached rate (as a share of the labor force including marginally attached) has retraced only 12 percent of the recessionary increase. From this, President Lockhart concludes:

It’s accurate to say the country has a large number of people in the so-called “shadow labor force.”

Because the sharp decline in labor force participation is not fully understood, and because the unemployment rate decline conflates declines in participation with employment gains, President Lockhart suggests it is useful to also look at the share of the prime-age population that is employed. Between the end of 2007 and 2009 the employment-to-population rate for this group declined from 79.7 to 74.8 percent. Since 2009, employment gains for the core of the workforce have advanced only 27 percent toward the prerecession peak (for the entire population over age 16, the recovery is essentially zero). Variations on this theme can be seen here and here.

Usually, the employment to population rate and the unemployment rate move in lock step (because labor force movements are very gradual). But that has not been the case during this recovery.

In addition to unemployment, President Lockhart highlights the issue of underemployment:

Many Americans are working fewer hours than they would prefer because their employers are offering them only part-time work. The share of workers who are involuntarily working part-time doubled during the recession and has moved only about 30 percent lower since the recovery began.

So, on the question of whether the unemployment rate decline has overstated actual progress in labor utilization, Lockhart says yes:

To sum up, these comparisons of employment data suggest that the labor market is not as healthy as the improved unemployment rate might suggest. The unemployment rate drop may overstate progress achieved.

The Atlanta Fed has been featuring the labor market spider chart tool on its website as a way to track relative progress in a number of labor market indicators since the end of the recession. For the purposes of President Lockhart’s speech, the relative improvement in various indicators of the rate of labor utilization was presented graphically in the form of yardage gains from the goal-line of a football field. The changes can be seen here (the data are from the U.S. Bureau of Labor Statistics and Atlanta Fed calculations). The idea is that the labor utilization “team” was driven back to its own goal line from the end of 2007 through the end of 2009, and the graphic shows how many yards (percent) the team has recovered as of the January 10 labor report. (The use of a football field image is perhaps appropriate, given that the recent BCS championship game featured two teams from the Sixth District.)

Labor Utilization Recovery: How Far Have We Come?

President Lockhart also suggests a link between labor market slack and the weak pricing trends we have experienced in recent years:

It’s worth noting that wage and salary income growth remains weak. I hear very little from business contacts about upward wage pressures except in a few specialized job categories. Wage pressures usually accompany growing demand and rising inflation but, although demand appears to be growing, inflation is very soft.

Inflation Y-O-Y Percent Change

In fact, looking at the recent disinflation apparent in virtually all consumer price statistics relative to the FOMC’s longer-run objective, President Lockhart acknowledges the risk of an inflation “safety”:

...I think inflation will stabilize and begin to move back in the direction of the FOMC’s 2 percent objective as the economy gathers momentum. So I’m interpreting the soft inflation numbers as a risk signal. Through the lens of prices, the economy could be weaker than we currently believe.

John RobertsonBy John Robertson, a vice president and senior economist in the Atlanta Fed’s research department


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Date: Wednesday, 08 Jan 2014 22:07

Roughly a year ago, the Federal Open Market committee (FOMC) switched from date-based forward guidance on the federal funds rate path to guidance based on economic conditionality. The idea, as Chairman Bernanke put it in his post-FOMC press conference, is that "[b]y tying future monetary policy more explicitly to economic conditions, this formulation of our policy guidance should also make monetary policy more transparent and predictable to the public."

Now, on the one hand, you can't be any more clear than to say that the policy interest rate will remain near zero until such-and-such a date. But if you really want to know the "reaction function" that guides monetary policy decisions, date-based guidance isn't going to speak very clearly to this question. Rather, you would probably rather know the economic conditions that would warrant the FOMC's decision to adjust the policy rate.

Let me suggest that clear communication is one of the foundations of good monetary policy because it's one of the foundational characteristics of good money.

A textbook description of money is usually just a recitation of its functions—it acts as a store of value, a medium of exchange, and a unit of account. This definition of money is a rather hollow one (as Minneapolis Fed President Narayana Kocherlakota noted back in his academic days) because it tells us only what money does but doesn't speak to the core issue—what is the problem that money solves?

The "unit of account" function, in particular, gets little development in the textbooks and has generally not carried much weight in the academic literature on the theory of money. (There are a few exceptions, like this NBER working paper by Matthias Doepke and Martin Schneider.) But if people are going to communicate with one another about value, those communications are going to be most effective if done using some standardized metric—and that's where money comes in. As a "unit of account," our money is how we communicate about value. It can be a physical thing, like a particular commodity, or it can be an abstract concept, like the broad purchasing power of a medium of exchange.

But this isn't to imply that all things are equally up to the job of being a good unit of account. Many economists, beginning with Adam Smith, have been critical of commodity-based monetary systems in this regard. In Congressional testimony in 1922 about stabilizing the purchasing power of our money, famed economist Irving Fisher argued that while gold may have been chosen as our money because it was a good medium of exchange, it had proven to be a poor choice as a unit of account on which contracts could be negotiated. Indeed, he argued for a system where the value of money was fixed in terms of a statistical index of its broad purchasing power, a system certainly similar in spirit to the one the Federal Reserve pursues today:

Is it not absurd to have a dollar also a unit in weight, when it is not intended to measure weight, but is intended to measure purchasing power. It is used in commerce in buying and selling, by debtor and creditor for lending and repaying; and we propose that the repayment shall be just. What does that mean? It does not mean that you shall return a given weight of gold or a given weight of anything; it means that you shall return to the lender something that is a just equivalent. Value is involved in there, and value is statistically increased by an index number average purchasing power.

In other words, it's essential that the unit of account conveys value so that the units expressed in trade, contracts, and financial accounts are both meaningful and durable. We recently produced a simple four-minute video on the subject. Give it a view and let us know what you think. We're big on getting our communications right.

Photo of Mike BryanBy Mike Bryan, vice president and senior economist in the Atlanta Fed's research department


Author: "macroblog" Tags: "Monetary Policy"
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Date: Friday, 27 Dec 2013 20:01

A few posts back my Atlanta Fed colleagues Tim Dunne and Ellie Terry offered up our latest contribution to the ongoing head-scratching over the rather spectacular decline in U.S. labor force participation (LFP) since the onset of the Great Recession in December 2007. “Rather spectacular” in this case means a fall in the participation rate from 66 percent (of the working age population either working or actively seeking work) to the 63 percent level reported for November. In people terms, that 3 percentage point decline represents a reduction of about 1.4 million participants in the U.S. labor market.

Like many other analysts, Dunne and Terry find that the drop in labor force participation appears to come from a combination of demographic factors—mainly the aging of the population—and other causes not specifically identified but generally interpreted to be associated with the weak economy in one way or another.

Two developing stories suggest the LFP may not be leaving the spotlight just yet. The first is this one, from USA Today:

Some 1.3 million Americans are set to lose their unemployment benefits Saturday...

Federal emergency benefits will end when funds run out for a program created during the recession to supplement the benefits that states provide. The cutoff will initially affect 1.3 million people, but 1.9 million more will lose benefits by mid-2014 when their 26 weeks of state paychecks run out, according to the National Employment Law Project.

What will those 1.3 million Americans do when their benefits run dry? According to a recent study by Princeton University’s Henry Farber and the San Francisco Fed’s Robert Valletta—also presented at a conference hosted here at the Atlanta Fed in October—on balance, the affected individuals are likely to leave the labor force:

We examined the impact of the unprecedented extensions of UI [unemployment insurance] benefits in the United States over the past few years on unemployment dynamics and duration and compared their effects with the extension of UI benefits in the milder recession of the early 2000s. We found small but statistically significant reductions in unemployment exits and small increases in unemployment durations arising from both sets of UI extensions. The magnitude of these overall effects is similar across the two episodes...

We find that the effect on exit from unemployment occurs primarily through a reduction in labor force exits rather than through exit to employment (job finding). This is important because it implies that extended benefits do not delay the time to re-employment substantially and so do not have first-order efficiency effects. The major effect of extended benefits is redistributive, providing income to job losers who would have exited the labor force otherwise (consistent with Card et al. 2007). [link mine]

In other words, if a significant decline in unemployment benefits comes to pass, we may well see another bump downward in the labor force participation rate. Although a decline in LFP associated with the expiration of extended UI benefits would fall in Dunne and Terry’s nondemographic category, the Farber and Valletta results suggest that we should interpret any such decline as structural. And structural in this case means not directly amenable to correction by policies aimed at stimulating spending.

The other important piece of recent news, however, is this one, which you probably heard about:

According to the Bureau of Economic Analysis, real gross domestic product—output produced in the United States—actually grew at a rate of 4.1% in the third quarter, up from BEA’s previous estimate of a 3.6% growth rate. The final results are also a gain over the second quarter’s 2.5% GDP growth.

Furthermore, as noted at Calculated Risk, the good news doesn’t stop there:

A little Christmas cheer...

Via the WSJ:

Macroeconomic Advisers...[raised] its estimate for fourth-quarter growth. It now forecasts gross domestic product to expand at an annualized rate of 2.6% in the final three months of the year, up three-tenths of a percentage point from an earlier estimate.

And Goldman Sachs has increased their Q4 GDP tracking to 2.4% annualized growth.

That all adds up to pretty decent growth in the second half of the year. If it persists, and the long-awaited acceleration in the economic expansion finally arrives, better labor market conditions should follow. And if the six-year fall in LFP has in large measure been driven by weak economic conditions, we should at least see a pause in participation declines as economic activity picks up. Actually, we should probably see an outright increase.

The next several quarters, then, may well provide some clarity as to the persistent question of whether or not the large recent exodus of Americans from the labor force has been the result of a lackluster economy. In this period, we may get some clarity as to whether efforts to stem that exodus were justified by a correct diagnosis of the underlying cause.

Or not.

David Altig By Dave Altig, executive vice president and research director at the Atlanta Fed


Author: "macroblog" Tags: "Employment, Labor Markets, Unemployment"
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Date: Monday, 23 Dec 2013 20:01

By pure coincidence, two interviews with Pennsylvania State University professor Neil Wallace have been published in recent weeks. One is in the December issue of the Federal Reserve Bank of Minneapolis’ excellent Region magazine. The other, conducted by Chicago Fed economist Ed Nosal and yours truly, is slated for the journal Macroeconomic Dynamics and is now available as a Federal Reserve Bank of Chicago working paper.

If you have any interest at all in the history of monetary theory over the past 40 years or so, I highly recommend to you these conversations. As Ed and I note of Professor Wallace in our introductory comments, very few people have such a coherent view of their own intellectual history, and fewer still have lived that history in such a remarkably consequential period for their chosen field.

Perhaps my favorite part of our interview was the following, where Professor Wallace reveals how he thinks about teaching economics, and macroeconomics specifically (link added):

If we were to construct an economics curriculum, independent of where we’ve come from, then what would it look like? The first physics I ever saw was in high school... I can vaguely remember something about frictionless inclined planes, and stuff like that. So that is what a first physics course is; it is Newtonian mechanics. So what do we have in economics that is the analogue of Newtonian mechanics? I would say it is the Arrow-Debreu general competitive model. So that might be a starting point. At the undergraduate level, do we ever actually teach that model?

[Interviewers] That means that you would not talk about money in your first course.

That is right. Suppose we taught the Arrow-Debreu model. Then at the end we’d have to say that this model has certain shortcomings. First of all, the equilibrium concept is a little hokey. It’s not a game, which is to say there are no outcomes associated with other than equilibrium choices. And second, where do the prices come from? You’d want to point out that the prices in the Arrow-Debreu model are not the prices you see in the supermarket because there’s no one in the model writing down the prices. That might take you to strategic models of trade. You would also want to point out that there are a lot of serious things in the world that we think we see that aren’t in the model: unemployment, money, and [an interesting notion of] firms aren’t in the Arrow-Debreu model. What else? Investing in innovation, which is critical to growth, isn’t in that model. Neither is asymmetric information. The curriculum, after this grounding in the analogue of Newtonian mechanics, which is the Arrow-Debreu model, would go into these other things. It would talk about departures from that theory to deal with such things; and it would describe unsolved problems.

So that’s a vision of a curriculum. Where would macro be? One way to think about macro is in terms of substantive issues. From that point of view, most of us would say macro is about business cycles and growth. Viewed in terms of the curriculum I outlined, business cycles and growth would be among the areas that are not in the Arrow-Debreu model. You can talk about attempts to shove them in the model, and why they fall short, and what else you can do.

Of the many things that I have learned from Professor Wallace, this one comes back to me again and again: Talk about how to get the things in the model that are essential to dealing with the unsolved problems, honestly assess why they fall short, and explore what else you can do. To me, this is not only a message of good science. It is one of intellectual generosity, the currency of good citizenship.

I was recently asked whether I align with “freshwater” or “saltwater” economics (roughly, I guess, whether I think of myself as an Arrow-Debreu type or a New Keynesian type). There are many similar questions that come up. Are you a policy “hawk” or a policy “dove”? Do you believe in old monetarism (willing to write papers with reduced-form models of money demand) or new monetarism (requiring, for example, some explicit statement about the frictions, or deviations from Arrow-Debreu, that give rise to money’s existence)?

What I appreciate about the Wallace formulation is that it asks us to avoid thinking in these terms. There are problems to solve. The models that we bring to those problems are not true or false. They are all false, and we—in the academic world and in the policy world—are on a common journey to figure out what we are missing and what else we can do.

It is deeply misguided to treat models as if they are immutable truths. All good economists appreciate this intellectually. And yet there is an awful lot of energy wasted, especially in the blogosphere, on casting aspersions at those who are perceived to be seeking answers within other theoretical tribes.

Some problems are well-suited to Newtonian mechanics, some are not. Some amendments to Arrow-Debreu are useful; some are not. And what is well-suited or useful in some circumstances may well be ill-suited or even harmful in others. Perhaps if we all acknowledge that none of us knows which is which 100 percent of the time, we can make just a little more progress on all those unsolved problems in the coming year. At a minimum, we would air our disagreements with a lot more civility.

Happy holidays.

David Altig By Dave Altig, executive vice president and research director at the Atlanta Fed


Author: "macroblog" Tags: "Economics, Education, Monetary Policy"
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Date: Thursday, 19 Dec 2013 19:47

In an earlier macroblog post, our colleague Julie Hotchkiss examined the decline in labor force participation from the onset of the Great Recession into early 2012, concluding that cyclical factors likely accounted for most of the drop. In this post, we examine how labor force participation has changed since the start of 2012 (and admittedly, we’re much less ambitious in our analysis than Julie). Motivating our analysis, in part, is the observation that much of the recent decline in the labor force participation rate (LFPR) is related to rising retirements (see the November 19 Research Rap by Shigeru Fujita). This is not surprising, as the percentage of individuals aged 65 and older in the population has been increasing sharply over the last half decade. That said, our approach indicates that the LFPR of prime-age workers (ages 25–54) continues to fall, and this is an important source of the overall decline in LFPR in the recent data. Such declines in LFPR in these age categories should be less related to retirement decisions, keeping on the table the possibility that a weak overall labor market remains a key drag on labor force participation.

A straightforward decomposition illustrates that the decline in LFPR among prime-age workers is a major contributor to the overall decline in LFPR. To see this, we separate the change in LFPR into three components: one that measures the change due to shifts in the LFPR within age groups—the within effect; one that measures changes due to population shifts across age groups—the between effect; and one that allows for correlation across the two effects—a covariance term. It works out the covariance term is always very close to zero, so we will omit discussion of that term here. The analysis breaks the data down into five age groups: 16–24, 25–34, 35–44, 45–54, and 55+.

The chart presents the decomposition from Q1 2012 to Q3 2013. Over this period, the overall LFPR declined by half a percentage point, from 63.8 percent to 63.3 percent. The blue areas represent the change due to within-age-group effects, and the green areas represent the change due to between-age-group effects. The sum of the bars is equal to the overall change in labor force participation.

Decomposition of Change in Labor Force Participation (Total Decline from Q1 2012 to Q3 2013 = 0.5)

Three key results emerge. First, increases in labor force participation for the youngest age group boosted overall labor force participation by 0.075 percentage points. Second, the growing population share of the 55+ age group reduced LFPRs over the period by 0.21 percentage points, accounting for roughly 40 percent of the overall decline. Third, labor force participation for prime-age workers continued to fall. The combined within effect for the prime-age individuals (25–34, 35–44, and 45–54) reduced the participation rate by 0.28 percentage points—or a little over half of the overall decline in labor force participation. Additional declines in labor force participation were associated with the reduction in population shares of prime age workers.

From an accounting standpoint, the analysis shows that the fall in the LFPR for prime-age workers is a main contributing factor to the recent decline in labor force participation. Indeed, the LFPR of prime-age workers fell from 81.6 to 81.0 from Q1 2012 to Q3 2013, with similar declines for both men and women. Given that prime-age workers make up more than half of the population, it is not surprising that the drop in the LFPR for these age groups accounts for a substantial fraction of the overall decline.

To put this in perspective, we present the same decomposition from Q1 2010 to Q4 2011, where the decline in the LFPR is 0.8 percentage point. While the magnitude of the overall change is different, the decomposition results are quite similar. The decline in participation rates for prime-age workers accounts for a little over 60 percent of the overall decline, with a substantial drag from the rise in the share of older workers (accounting for a third of the drop). In short, the changes in participation due to within and between effects over the first two years look quite similar to that of the second two years of the labor market recovery.

Decomposition of Change in Labor Force Participation (Total Decline from Q1 2010 to Q4 2011 = 0.8)

A corollary to this analysis is that these sources of decline in labor force participation have allowed the unemployment rate to decline more sharply than expected, given the moderate employment growth observed. We will not take a stand on whether these are “wrong” or “right” reasons for unemployment rate declines. Rather, we note that the patterns observed early in the recovery are still in place (more or less) in the recent data.

Photo of Timothy DunneBy Timothy Dunne, a research economist and policy adviser,

Photo of Ellie Terryand Ellie Terry, an economic policy analysis specialist, both in the research department of the Atlanta Fed


Author: "macroblog" Tags: "Employment, Labor Markets, Unemployment"
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Date: Wednesday, 04 Dec 2013 20:15

The financial system cannot be made completely safe because it exists to allocate funds to inherently risky projects in the real economy. Thus, an important question for policymakers is how best to structure the financial system to absorb these losses while minimizing the risk that financial sector failures will impair the real economy.

Standard theories would predict that one good way of reducing financial sector risk is diversification. For example, the financial system could be structured to facilitate the development of large banks, a point often made by advocates for big banks such as Steve Bartlett. Another, not mutually exclusive, way of enhancing diversification is to create a system that shares risks across banks. An example is the Dodd-Frank Act mandate requiring formerly over-the-counter derivatives transactions to be centrally cleared.
 
However, do these conclusions based on individual bank stability necessarily imply that risk sharing will make the financial system safer? Is it even relevant to the principal risks facing the financial system? Some of the papers presented at the recent Atlanta Fed conference, "Indices of Riskiness: Management and Regulatory Implications," broadly addressed these questions and others. Other papers discuss the impact of bank distress on local economies, methods of predicting bank failure, and various aspects of incentive compensation paid to bankers (which I discuss in a recent Notes from the Vault).

The stability implications of greater risk sharing across banks are explored in "Systemic Risk and Stability in Financial Networks" by Daron Acemoglu, Asuman Ozdaglar, and Alireza Tahbaz-Salehi. They develop a theoretical model of risk sharing in networks of banks. The most relevant comparison they draw is between what they call a "complete financial network" (maximum possible diversification) and a "weakly connected" network in which there is substantial risk sharing between pairs of banks but very little risk sharing outside the individual pairs. Consistent with the standard view of diversification, the complete networks experience few, if any, failures when individual banks are subject to small shocks, but some pairs of banks do fail in the weakly connected networks. However, at some point the losses become so large that the complete network undergoes a phase transition, spreading the losses in a way that causes the failure of more banks than would have occurred with less risk sharing.

Extrapolating from this paper, one could imagine that risk sharing could induce a false sense of security that would ultimately make a financial system substantially less stable. At first a more interconnected system shrugs off smaller shocks with seemingly no adverse impact. This leads bankers and policymakers to believe that the system can handle even more risk because it has become more stable. However, at some point the increased risk taking leads to losses sufficiently large to trigger a phase transition, and the system proves to be even less stable than it was with weaker interconnections.

While interconnections between financial firms are a theoretically important determinant of contagion, how important are these connections in practice? "Financial Firm Bankruptcy and Contagion," by Jean Helwege and Gaiyan Zhang, analyzes the spillovers from distressed and failing financial firms from 1980 to 2010. Looking at the financial firms that failed, they find that counterparty risk exposure (the interconnections) tend to be small, with no single exposure above $2 billion and the average a mere $53.4 million. They note that these small exposures are consistent with regulations that limit banks' exposure to any single counterparty. They then look at information contagion, in which the disclosure of distress at one financial firm may signal adverse information about the quality of a rival's assets. They find that the effect of these signals is comparable to that found for direct credit exposure.

Helwege and Zhang's results suggest that we should be at least as concerned about separate banks' exposure to an adverse shock that hits all of their assets as we should be about losses that are shared through bank networks. One possible common shock is the likely increase in the level and slope of the term structure as the Federal Reserve begins tapering its asset purchases and starts a process ultimately leading to the normalization of short-term interest rate setting. Although historical data cannot directly address banks' current exposure to such shocks, such data can provide evidence on banks' past exposure. William B. English, Skander J. Van den Heuvel, and Egon Zakrajšek presented evidence on this exposure in the paper "Interest Rate Risk and Bank Equity Valuations." They find a significant decrease in bank stock prices in response to an unexpected increase in the level or slope of the term structure. The response to slope increases (likely the primary effect of tapering) is somewhat attenuated at banks with large maturity gaps. One explanation for this finding is that these banks may partially recover their current losses with gains they will accrue when booking new assets (funded by shorter-term liabilities).

Overall, the papers presented in this part of the conference suggest that more risk sharing among financial institutions is not necessarily always better. Even though it may provide the appearance of increased stability in response to small shocks, the system is becoming less robust to larger shocks. However, it also suggests that shared exposures to a common risk are likely to present at least as an important a threat to financial stability as interconnections among financial firms, especially as the term structure and the overall economy respond to the eventual return to normal monetary policy. Along these lines, I recently offered some thoughts on how to reduce the risk of large widespread losses due to exposures to a common (credit) risk factor.

Photo of Larry WallBy Larry Wall, director of the Atlanta Fed's Center for Financial Innovation and Stability

 

Note: The conference "Indices of Riskiness: Management and Regulatory Implications" was organized by Glenn Harrison (Georgia State University's Center for the Economic Analysis of Risk), Jean-Charles Rochet, (University of Zurich), Markus Sticker, Dirk Tasche (Bank of England, Prudential Regulatory Authority), and Larry Wall (the Atlanta Fed's Center for Financial Innovation and Stability).


Author: "macroblog" Tags: "Banking, Financial System"
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Date: Friday, 22 Nov 2013 18:40

In March 2012, the Federal Reserve Bank of Atlanta launched its Jobs Calculator, an application that illustrates the relationship between the unemployment rate, growth in payroll employment, the labor force participation rate, and a few other variables to boot. Most notably, it tells us how many jobs need to be created to achieve a specific unemployment rate within a given period of time. This tool has turned out to be a useful one for anchoring discussions about national employment growth and unemployment among policy makers and the media.

However, the national employment situation masks significant differences in state labor markets. For example, at the trough of the business cycle (June 2009), the national unemployment rate was 9.5 percent, but it ranged from 4.2 percent in North Dakota to 15.2 percent in Michigan. State policy makers, in managing the dynamics of their own employment situation, need to know the data on a state level.

We are pleased to announce that the Atlanta Fed recently unveiled the state-level Jobs Calculator. The same tool that has been used for national discussions is now available for state-level analyses (see the figure below).


Not only does this state tab allow a quick overview of the historical employment growth in each state (see, for example, Alabama's historical employment growth in the figure below), but it also has the same functionality as the national Jobs Calculator. (Because of the recent partial government shutdown, the data are updated only through August; state-level employment data for October will be available November 22.)


Like the national Jobs Calculator, the state-level version allows the user to input a target unemployment rate, choose the number of months desired to hit the target rate, and find out how many new jobs are required per month to get there. But the calculator is flexible enough to allow other interesting experiments as well.

Consider the case of Florida. During the recession, Florida experienced a significant decline in its population growth. It has gone from a high of about 0.2 percent growth per month (roughly 2.4 percent per year) to its current 0.115 percent growth per month (about 1.38 percent per year; see the figure below). Suppose policy makers in Florida want to know how a return to prerecession population growth might affect the number of jobs needed to maintain its current unemployment rate over the next 12 months. (Note that as of August, the unemployment rate in Florida was 7 percent.)


The calculator's default settings always answer the question, “How many jobs per month does it take to maintain today's unemployment rate over the next 12 months?” To answer our hypothetical policy makers' question, all they would have to do is enter a prerecession monthly population growth rate of 0.2 percent into Florida's state Jobs Calculator, leaving everything else the same. Given the current data in hand, we would discover that Florida would need to generate about 6,000 more jobs per month at the higher population growth than at the current—and lower—population growth to stabilize the unemployment rate at 7 percent.

The data behind the state-level Jobs Calculator come from the U.S. Census Bureau's Establishment Survey, the same data used for the national Jobs Calculator, combined with the Local Area Unemployment Statistics (LAUS) programs run by each state. The LAUS contain the regional and state employment statistics that are consistent with data from the Census Bureau's Current Population Survey. State-level population estimates are provided by the U.S. Census Bureau (and are described in more detail here). You'll note that the LAUS data, especially for very small states, look more erratic than national or larger states' numbers—the unfortunate consequence of small sample sizes.

LAUS data are generally issued about the third Friday of each month following the reference month, which means that the state-level Jobs Calculator statistics will be updated about two weeks after the national Jobs Calculator. The schedule of release dates is available from the U.S. Bureau of Labor Statistics.

Photo of Julie HotchkissBy Julie Hotchkiss, a research economist and policy adviser in the Atlanta Fed's research department


Author: "macroblog" Tags: "Employment, Unemployment"
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Date: Thursday, 21 Nov 2013 17:01

The fed funds rate has been at the zero lower bound (ZLB) since the end of 2008. To provide a further boost to the economy, the Federal Open Market Committee (FOMC) has embarked on unconventional forms of monetary policy (a mix of forward guidance and large-scale asset purchases). This situation has created a bit of an issue for economic forecasters, who use models that attempt to summarize historical patterns and relationships.

The fed funds rate, which usually varies with economic conditions, has now been stuck at near zero for 20 quarters, damping its historical correlation with economic variables like real gross domestic product (GDP), the unemployment rate, and inflation. As a result, forecasts that stem from these models may not be useful or meaningful even after policy has normalized.

A related issue for forecasters of the ZLB period is how to characterize unconventional monetary policy in a meaningful way inside their models. Attempts to summarize current policy have led some forecasters to create a "virtual" fed funds rate, as originally proposed by Chung et al. and incorporated by us in this macroblog post. This approach uses a conversion factor to translate changes in the Fed's balance sheet into fed funds rate equivalents. However, it admits no role for forward guidance, which is one of the primary tools the FOMC is currently using.

So what's a forecaster to do? Thankfully, Jim Hamilton over at Econbrowser has pointed to a potential patch. However, this solution carries with it a nefarious-sounding moniker—the shadow ratewhich calls to mind a treacherous journey deep within the hinterlands of financial economics, fraught with pitfalls and danger.

The shadow rate can be negative at the ZLB; it is estimated using Treasury forward rates out to a 10-year horizon. Fortunately we don't need to take a jaunt into the hinterlands, because the paper's authors, Cynthia Wu and Dora Xia, have made their shadow rate publicly available. In fact, they write that all researchers have to do is "...update their favorite [statistical model] using the shadow rate for the ZLB period."

That's just what we did. We took five of our favorite models (Bayesian vector autoregressions, or BVARs) and spliced in the shadow rate starting in 1Q 2009. The shadow rate is currently hovering around minus 2 percent, suggesting a more accommodative environment than what the effective fed funds rate (stuck around 15 basis points) can deliver. Given the extra policy accommodation, we'd expect to see a bit more growth and a lower unemployment rate when using the shadow rate.

Before showing the average forecasts that come out of our models, we want to point out a few things. First, these are merely statistical forecasts and not the forecast that our boss brings with him to FOMC meetings. Second, there are alternative shadow rates out there. In fact, St. Louis Fed President James Bullard mentioned another one about a year ago based on work by Leo Krippner. At the time, that shadow rate was around minus 5 percent, much further below Wu and Xia's shadow rate (which was around minus 1.2 percent at the end of last year). Considering the disagreement between the two rates, we might want to take these forecasts with a grain of salt.

Caveats aside, we get a somewhat stronger path for real GDP growth and a lower unemployment rate path, consistent with what we'd expect additional stimulus to do. However, our core personal consumption expenditures inflation forecast seems to still be suffering from the dreaded price-puzzle. (We Googled it for you.)





Perhaps more important, the fed funds projections that emerge from this model appear to be much more believable. Rather than calling for an immediate liftoff, as the standard approach does, the average forecast of the shadow rate doesn't turn positive until the second half of 2015. This is similar to the most recent Wall Street Journal poll of economic forecasters, and the September New York Fed survey of primary dealers. The median respondent to that survey expects the first fed funds increase to occur in the third quarter of 2015. The shadow rate forecast has the added benefit of not being at odds with the current threshold-based guidance discussed in today's release of the minutes from the FOMC's October meeting.

Moreover, today's FOMC minutes stated, "modifications to the forward guidance for the federal funds rate could be implemented in the future, either to improve clarity or to add to policy accommodation, perhaps in conjunction with a reduction in the pace of asset purchases as part of a rebalancing of the Committee's tools." In this event, the shadow rate might be a useful scorecard for measuring the total effect of these policy actions.

It seems that if you want to summarize the stance of policy right now, just maybe...the shadow knows.

Photo of Pat HigginsBy Pat Higgins, senior economist, and

 

Photo of Brent MeyerBrent Meyer, research economist, both of the Atlanta Fed's research department


Author: "macroblog" Tags: "Fed Funds Futures, Federal Reserve and M..."
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Date: Monday, 18 Nov 2013 18:13

The spigot of credit to small businesses appears to be turning faster. As of June 2013, outstanding amounts of small loans on the balance sheets of banks were 4 percent higher than their September 2012 levels, according to the Federal Deposit Insurance Corporation. While they are still 12 percent off 2007 levels, the recent increase is encouraging.

The turnaround in small loan portfolios is not the only sign of improved credit flows to small businesses. The Fed’s October 2013 senior loan officer survey indicates that credit terms to small firms have gradually eased since the second quarter of 2010. Approval ratings of banks and alternative lenders, as measured by Biz2Credit’s lending index, have also risen steadily over the past two years.

In addition to these positive signs, the Atlanta Fed’s third-quarter 2013 Small Business Survey has revealed signs of improvement among small business borrowers in the Southeast. The survey asked recent borrowers about their requests for credit and how successful they were at each place they applied. We also asked, “Over ALL your applications for credit, to what extent were you total financing needs met?” This measure of overall financing satisfaction showed some signs of improvement in the third quarter.

Chart 1 compares the overall financing satisfaction of small business borrowers in the first and third quarter of 2013. The portion of firms that received the full amount requested rose from 28 percent in the first quarter to 42 percent in the third quarter. Meanwhile, the portion that received none of the credit requested declined from 31 percent of the sample in the first quarter to 22 percent in the third quarter.

Chart 1: Overall Financing Satisfaction

Further, financing satisfaction rose across a variety of dimensions. Chart 2 shows how average financing satisfaction changed for young firms and mature firms, across industries and by recent sales performance. In all cases, there were increases in the average amount of financing received from the first to the third quarter of 2013.

Chart 2: Average Amount of Financing Received Overall

This broad-based increase in overall financing satisfaction is encouraging. Greater financial health of the applicant pool helped fuel the improvement in borrowing conditions. In the October survey, 52 percent of businesses reported that sales increased while 34 percent reported decreases. Sales have improved significantly from a year ago, when about as many firms reported sales increases as reported decreases. Measures of hiring and capital improvements over the year have also improved for the average firm in the survey (see chart 3).

131115c

Lending standards have been improving and small businesses have been slowly gaining momentum, but many obstacles remain. Open-ended questions in our survey revealed that small businesses are still concerned about a number of factors, including the general political and economic uncertainty, the impact of the Affordable Care Act, the higher collateral and personal guarantees required to obtain financing, and regulatory requirements that restrict lending. So while conditions on the ground seem to be improving for small businesses, there still appear to be headwinds that may be holding back a greater pace of improvement.

Read the full survey results.

Photo of Ellie TerryBy Ellie Terry, an economic policy analysis specialist in the Atlanta Fed’s research department


Author: "macroblog" Tags: "Economic conditions, Small Business"
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