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December 27, 2013
Is the Labor Force Participation Rate about to Fall Again?
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...
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.
By Dave Altig, executive vice president and research director at the Atlanta Fed
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December 23, 2013
Goodwill to Man
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.
By Dave Altig, executive vice president and research director at the Atlanta Fed
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December 19, 2013
Labor Force Participation Rates Revisited
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.
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.
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.
By Timothy Dunne, a research economist and policy adviser,
and Ellie Terry, an economic policy analysis specialist, both in the research department of the Atlanta Fed
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December 04, 2013
Is (Risk) Sharing Always a Virtue?
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.
By 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).
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