Redirect


This site has moved to http://economistsview.typepad.com/
The posts below are backup copies from the new site.

September 30, 2007

Economist's View - 5 new articles

Alan Blinder: Who Caused the Mortgage Mess?

Alan Blinder says it's time to start pointing fingers. All six of them:

Six Fingers of Blame in the Mortgage Mess, by Alan S. Blinder, Economic View, NY Times: Something went badly wrong in the subprime mortgage market. In fact, several things did. And now quite a few homeowners, investors and financial institutions are feeling the pain. ...

Finger-pointing is often decried both as mean-spirited and as a distraction from the more important task of finding remedies. I beg to differ. Until we diagnose what went wrong with subprime, we cannot even begin to devise policy changes that might protect us from a repeat performance. ... Because so much went wrong, the fingers on one hand will not be enough.

The first finger points at households who borrowed recklessly to buy homes... They should have known better. But what can we do to guard against it happening again? Not much, I'm afraid. Gullible consumers have been around since Adam consumed that apple. ...

It seems more promising to point a finger directly at lenders. Some lenders sold mortgage products that were plainly inappropriate for customers, and that they did not understand. ...

Here, something can be done. For openers, we need to think about devising a "suitability standard" for everyone who sells mortgage products. Under current law, a stockbroker who persuades Granny to use her last $5,000 to buy a speculative stock on margin is in legal peril because the investment is "unsuitable" for her (though perfectly suitable for Warren Buffett). ...

But who will create and enforce such a standard for mortgages? Roughly half of recent subprime mortgages originated in mortgage companies that were ... outside the federal regulatory system. ... We should place all mortgage lenders under federal regulation.

That said, bank regulators deserve the next finger of blame for not doing a better job of protecting consumers and ensuring that banks followed sound lending practices. ...

Regulators also need to start thinking about how to deal with a serious incentive problem. In old-fashioned finance, a bank that originated a mortgage also held it for years..., giving it a clear incentive to lend carefully. But in newfangled finance, banks and mortgage brokers originate loans and sell them quickly to a big financial firm that "securitizes" them...

Securitization ... has ... made mortgages more affordable. ... But securitization sharply reduces the originator's incentive to scrutinize the creditworthiness of borrowers. After all, if the loan goes sour, someone else will be holding the bag. We need to find ways to restore that incentive, perhaps by requiring loan originators to retain a share of each mortgage.

But wait. Don't the ultimate investors have every incentive to scrutinize the credits? ... The answer is yes — which leads me to point a fourth finger of blame. By now, it is abundantly clear that many investors, swept up in the euphoria of the moment, failed to pay close attention to what they were buying.

Why did they behave so foolishly? Part of the answer is that the securities ... were probably too complex for anyone's good — which points a fifth finger, this one at the investment bankers who dreamed them up and marketed them aggressively.

Another part of the answer merits a sixth finger of blame. Investors placed too much faith in the rating agencies — which, to put it mildly, failed to get it right. It is tempting to take the rating agencies out for a public whipping. But it is more constructive to ask how the rating system might be improved. That's a tough question because of another serious incentive problem.

Under the current system, the rating agencies are hired and paid by the issuers of the very securities they rate — which creates an obvious potential conflict of interest. ... This needs to change, but precisely how is not clear.

So that's my list... But as we point all these fingers, let's remember the sage advice of the late and dearly missed Ned Gramlich, the former Fed governor who saw the emerging subprime problems sooner and clearer than anyone. Yes, the subprime market failed us. But before it blew up, it placed a few million families of modest means in homes they otherwise could not have financed. That accomplishment is worth ... quite a lot.

We don't have to destroy the subprime market in order to save it.

Working their Way to the Bottom

knzn peers into "the duffle bag of economists":

Conflicting Opinions, by knzn: I know I should have been done with this last year, but after coming across this piece of Fedspeak..., I couldn't resist.

You'd have to dig pretty far down in the duffle bag of economists to find one who actually believes in the Philips Curve...

--Arthur Laffer, Founder and Chairman, Laffer Associates, Wall Street Journal, August 24, 2006

The Phillips curve is a core component of every realistic macroeconomic model.

--Janet L. Yellen, President and CEO, Federal Reserve Bank of San Francisco, speech, Boston Fed Conference on Behavioral Economics, September 28, 2007 (Perhaps they keep the realists at the bottom of the duffle bag?)

My theory is that as the bag is jostled about, natural sorting causes heavyweight economists to drift to the bottom. Thus, one does have to dig down pretty far to find the most informed views.

The Economics of Time Travel

Ever wonder how much it would cost to build a time machine? No? Well, if you ever do, here's the answer:

Time machine possible says professor, Gold Coast News: Building a time machine that travels into the future is not science fiction - if you are a multi-trillionaire, a physics expert says.

Dr Craig Savage, who lectures in relativity and quantum mechanics at the Australian National University, says it is possible for people to travel forward in time but the costs involved are too great.

''If you could build a spaceship that could go three quarters of the speed of light you would time travel one hour into the future for every hour of your time,'' he said.

''People have designed such spacecrafts at various times but they would just be unimaginably expensive to create. ''It's not an issue of technology, it's one of economics.''

The cost of operating a time travelling machine, in relation to the cost of electricity, would be ten trillion dollars, Dr Savage estimates.

"Trust Us"

"Wartime economist" and libertarian David Henderson:

War and the Constitution, by David R. Henderson: ...The U.S. Constitution is there to protect our rights, to tell the government the only things it can do. If the federal government does not have a specific power granted to it within the Constitution, then it does not have that power. Period. ...

[O]ur rights... [are also protected by] the carefully thought-out division of powers within the U.S. Constitution. Why such a division of powers? Because no one is to be trusted with too much power. Incidentally, when Alberto Gonzales gave a talk at the Naval Postgraduate School in 2002 defending many of President Bush's unconstitutional actions, a colleague and I challenged him afterward. He tried to reassure us, saying, "Condi and others and I are looking out for how the president will play in history. We don't want him to look like some monster who destroyed our freedom. Trust us." I answered, "The Constitution is not based on trust, but on distrust."

One of the most important things the government does is engage in war. For that reason, the Constitution gives the power to declare war solely to Congress. ...

Consider why this matters. Think back to all the discussion before the U.S. government invaded Iraq in March 2003. One of the biggest issues was whether, and to what extent, Saddam Hussein had weapons of mass destruction. We now know that he didn't have such weapons – even many of Bush's defenders will admit his error. We don't even need to get into the issue of whether Bush was lying. Even if we assume the best – that Bush was saying what he thought to be true – the point is that we could have had a much better discussion of the issue if Bush had followed the Constitution. If Congress had actually decided to vote on whether or not to declare war on Iraq, they would have had a debate. If they had had a debate, there would have been multiple sources of information about the weapons of mass destruction. But by violating his oath to uphold the Constitution, Bush made sure that there wasn't an extensive debate. ...

links for 2007-09-29

September 29, 2007

Economist's View - 7 new articles

The Implications of Behavioral Research for the Phillips Curve

San Francisco Fed President Janet Yellen discusses the use of behaviorally based macroeconomic models incorporating features such as money illusion, rules of thumb, and concern for issues such as fairness and equity to improve the ability of the New Keynesian Phillips curve to explain macroeconomic data:

Implications of Behavioral Economics for Monetary Policy [1], Janet Yellen, SF Fed: I want to congratulate the Federal Reserve Bank of Boston for organizing a fascinating and thought-provoking conference. I applaud the Bank's decision to establish a center to promote and support research in behavioral economics and concur wholeheartedly with the judgment that motivates these initiatives—that research in behavioral economics is broadening and enriching our understanding of decisionmaking. This research has the potential to strengthen the conceptual and empirical underpinnings of macroeconomic policy.

The Federal Reserve is one of a growing number of organizations that have already taken some implications of behavioral research to heart. This year, we began to automatically enroll new employees into our System's savings plan, defaulting them into an asset allocation fund that includes fixed income, domestic, and international equity investments. Employees who do not want to participate can, of course, easily opt out. But our early experience mirrors well-known research findings: so far, an overwhelming fraction of employees who were defaulted in remain in. Of course, this choice reflects the Federal Reserve System's appreciation of the striking findings of behavioral economics concerning the sensitivity of saving decisions to default enrollments.

In terms of the Federal Reserve's public policy responsibilities, I can easily envision other ways in which explorations in behavioral economics could be of practical use. For example, one of the Federal Reserve's responsibilities is to design consumer disclosures, including the information that borrowers receive from lenders when they take out a mortgage, apply for a credit card, or lease a new vehicle. As we have unfortunately seen recently, such disclosures have not always been effective in conveying the key information that is relevant to such decisions in a salient, understandable, and timely way. Indeed, recent research by the Federal Trade Commission[2] documents that a large fraction of mortgage borrowers fail to understand the financial implications of prepayment penalties and other complex loan features. To improve the effectiveness of such disclosures, the Federal Reserve has begun to use consumer testing techniques,[3] but there remains substantial scope for behavioral research to contribute to the design of more effective practices in the consumer disclosure area.

Today, however, I would like to focus on some implications of behavioral economics for the conduct of monetary policy. I will concentrate on implications of behavioral research for the Phillips curve, although the papers at this conference demonstrate that behavioral economics has implications for many other aspects of macroeconomic modeling, including the behavior of housing and other asset prices, and the specification of crucial components of aggregate demand, such as the consumption function.

The Phillips curve is a core component of every realistic macroeconomic model. It plays a critical role in policy determination, because its characteristics importantly influence the short- and long-run tradeoffs that central banks face as they strive to achieve price stability and, in the Federal Reserve's case, maximum sustainable employment—our second, congressionally mandated goal. I will argue that behavioral economics can enhance our understanding of the Phillips curve, and this is important for two reasons: First, better models of the inflation process help improve our forecasts and clarify limitations on what monetary policy can do. Second, the theoretical underpinnings of the Phillips curve are important in understanding what central banks should do. In other words, beyond determining the "constraints" governing what is feasible, models underpinning the Phillips curve have implications for the way in which central banks should interpret their price stability mandate and for assessing the welfare costs of fluctuations in output and inflation.

The New Keynesian model provides theoretical microfoundations for a Phillips curve that relates actual inflation to expected inflation one period ahead as well as to marginal cost.[4] This model has become a standard workhorse for policy analysis, and provides loose justification for empirical implementations of the Phillips curve, which typically relate actual inflation to lags of inflation (as a proxy for expected inflation), a measure of the output or unemployment gap (which proxies for cyclical fluctuations in marginal cost), and other variables reflecting "supply shocks" such as the prices of energy and imported goods. The coefficient on the unemployment gap in the Phillips curve determines the slope of the "short-run" Phillips curve relationship between unemployment and inflation and is a crucial parameter for monetary policy because it influences the sacrifice ratio—the cost in terms of unemployment or lost output to lower inflation. Virtually all empirical research on the inflationary process finds that the "short-run" Phillips curve is flat enough to generate a significant short-run tradeoff.

Of course, the existence of this empirical short-run tradeoff between inflation and unemployment also helped motivate the development of the New Keynesian model in the first place. In particular, with no frictions and with fully maximizing agents, markets should always clear, and the labor market should be no exception. Thus, the short-run Phillips curve "should be" vertical.[5] This divergence between theory and reality was the original motivation for Keynesian economics. But in contrast to the ad hoc behavioral assumptions underlying old-style Keynesian theory, modern researchers have "amended" the neoclassical model with well-specified assumptions concerning the nature of preferences, the process of decisionmaking, the frictions characterizing markets, and the details of expectation formation. The objective has been to build models on sound microfoundations that are not only rigorous but also realistic.

Viewed in this light, the now standard New Keynesian approach explains the short-run Phillips curve tradeoff by introducing a key "friction" into neoclassical theory, namely, price-stickiness; such a friction is often justified as a menu cost of changing nominal prices. The consequence is that firms change the prices they charge only periodically, not continuously. With staggered decisionmaking across price setters, the aggregate price level exhibits inertia, rationalizing the short-run Phillips curve tradeoff. Other frictions, such as wage rigidity and habit persistence in consumption, are typically added to improve the fit of the model.

Behavioral macroeconomic models have extended this agenda, both by providing new justifications for wage and price rigidity and by incorporating additional departures from the frictionless benchmark. Of course, the jury is still out on which modifications are most important empirically for understanding the macroeconomy. Nevertheless, the evidence presented throughout this conference regarding how people behave is too compelling to simply ignore. Let me discuss a few examples of behavioral macroeconomics.

Some behavioral models assume that people follow simple heuristics or rules of thumb that require relatively little cognitive effort or time (such as focusing on only a few salient details of a problem). Indeed, the psychology and economics literature that builds on the work of Kahneman, Tversky, and others generally concludes that people do not make decisions in the fully rational way commonly envisioned in standard macroeconomic models. As Benjamin and Laibson (2003) summarize the findings of this literature: "Economic agents make good decisions but not perfectly rational ones."

Other behavioral models, including those surveyed by Fehr, Goette, and Zehnder (2007) and by Rotemberg (2007) at this conference, go much further, arguing that individual behavior is affected by a reliance on nominal frames of reference and by considerations such as fairness, envy, social status, and social norms. As Rotemberg makes clear, such assumptions can also rationalize the phenomenon of "price-stickiness" embodied in the Phillips curve.

Of course a logical question is why such additional complexities are worth incorporating into macro models if the New Keynesian approach, based on costly price adjustment, is empirically satisfactory. The problem is that the New Keynesian Phillips curve is not fully satisfactory. For example, it is not consistent with contractionary disinflations or with the inflation persistence observed in the postwar period. It also is not consistent with empirical estimates of the joint responses of unemployment and inflation to monetary shocks.[6]

Behaviorally based macroeconomic models help address these concerns about the New Keynesian Phillips curve, notably by modifying the process of expectations formation, the feedback between expected future inflation and current inflation, the link between labor market conditions and firms' marginal cost, and the impact of "supply shocks" on the inflation process. They also offer new insights. For example, Mankiw and Reis (2002) assume that decision makers form expectations using "sticky" or stale information, an assumption they justify on behavioral grounds. To keep their model more tractable, they assume that all agents act as if they had rational expectations, but most use outdated information. With this amendment of the standard New Keynesian model, the Mankiw-Reis version generates a short-run Phillips curve that is downward-sloping and that is consistent with inflation persistence and costly disinflation.

Of course, the assumption of rational expectations, which Mankiw and Reis maintain, is a clear, but probably unrealistic, benchmark. Ball (2000) suggests, on near-rationality grounds, that perhaps people forecast with optimal univariate estimation rather than acting as if they knew the entire model.[7] For the postwar period, this approach makes expected inflation close to being last period's inflation—so expectations depend heavily on recent experience. Inflation is thus persistent, but this persistence is not structural. An important implication for policy is that, if policymakers change their behavior, the empirical dynamics of inflation could change markedly.

Let me next turn to the long-run properties of the Phillips curve. Most macroeconomists accept that the long-run Phillips curve is vertical, so that steady-state unemployment is unaffected by the average level of inflation. Intriguingly, some behavioral models raise the possibility that steady-state unemployment might depend on the inflation rate.[8] For example, Akerlof, Dickens, and Perry (2000) explore the implications of a model with money illusion, a phenomenon which, according to surveys and other empirical evidence, appears to be both widespread and significant in decisionmaking. In their model, when inflation is sufficiently low, most agents don't focus on the difference between real and nominal variables, so inflation is relatively unimportant for nominal wage bargains and for prices. As inflation rises, however, it becomes salient to a growing fraction of agents who take it fully into account. This hypothesis gives rise to a long-run Phillips curve that is bowed in at very low inflation rates, backward bending at slightly higher rates, and ultimately vertical at the "natural rate" when inflation is sufficiently high. The implication is that a very small amount of inflation may lower equilibrium unemployment. Beyond a point, however, higher inflation raises equilibrium unemployment, since inflation becomes an increasingly salient factor in decisionmaking. Akerlof et al. argue that, in the late 1990s, as inflation fell to low levels, it became less salient to wage bargains, reducing the effective natural rate of unemployment.

Closely related to the idea of money illusion is downward nominal wage rigidity which, as Fehr et al. discuss, may reflect considerations of fairness. Pervasive evidence of such nominal rigidity was identified, for example, by the International Wage Flexibility project (see Dickens et al., 2007). As Tobin (1972) originally showed, such downward nominal wage rigidity means that, at sufficiently low inflation rates, a significant fraction of firms would optimally cut nominal wages. This possibility is explored in another paper by Akerlof, Dickens, and Perry (1996). In their model, if productivity growth and steady-state inflation are low, then long-run unemployment might be relatively high. The reason is that some firms might need to cut real wages which, at very low inflation, requires nominal wage cuts. If they're unwilling or unable to implement such cuts, then they may lay off workers instead. This reduction in labor demand leads to an increase in unemployment. Of course, if productivity growth is high, as it has been on average since the mid-1990s, then downward nominal wage rigidity becomes a less important issue.[9] Behavioral considerations thus point to the possibility of a long-run tradeoff between inflation and unemployment at very low inflation rates.

Downward nominal wage rigidity, as well as downward real wage rigidity, may also affect the linkages in the Phillips curve among unemployment, marginal cost, and inflation. In particular, norms governing the pay increases that are deemed fair may result in a short-run Phillips curve that is convex rather than linear. The nonlinearity is due to the fact that, even with high unemployment rates, firms are unwilling to treat workers in ways they consider unfair—either cutting nominal wages or raising nominal wages by less than workers think they should receive, causing inflation to "bottom out" as unemployment rises. For the United States, Clark, Laxton, and Rose (1996) find evidence of nonlinearity, although tests to discriminate among alternative functional forms of the Phillips curve suffer from extremely low power, making a reliable assessment of the degree of convexity impossible. The degree of convexity of the short-run Phillips curve is potentially important, however, because the volatility of unemployment and mean unemployment are inversely related along paths with constant expected inflation. This means that policies to stabilize unemployment produce the payoff of lowering it on average.

Another implication of behavioral economics for the Phillips curve relates to the impact of productivity growth on equilibrium unemployment when real wages exhibit some rigidity, a phenomenon found by the International Wage Project to be prevalent in many countries. Ball and Moffitt (2001), for example, have shown that shifts in productivity growth, like other supply shocks, can shift the Phillips curve and thereby change, at least for a time, the equilibrium unemployment rate, or NAIRU. Behavioral economics suggests that norms may govern the real wage increases that workers consider fair, and these norms or aspirations may be historically rooted. Shifts in productivity growth make it easier or more difficult for firms to meet these norms, altering, at least for a time, the unemployment rate that is consistent with growth in real wages that is in line with productivity. During the 1990s, faster productivity growth enabled firms to more easily meet norms for real wage growth that were depressed by the post-1973 productivity decline. In this view, the sluggish upward adjustment of norms enabled unemployment to fall to 40-year lows without igniting inflation. In essence, the short-run NAIRU was below its long-run level. By contrast, the poor experience of the 1970s reflected the collision of inherited norms for rapid real wage growth with the unpleasant reality of a sharp productivity slowdown.

Let me wrap up these remarks on the implications of behavioral research for the properties of the Phillips curve by noting that at least some of the behaviorally based insights have already crept into our internal analysis and forecasts. For example, Federal Reserve policymakers often attributed favorable inflation performance in the late 1990s to fast productivity growth and its effect on the short-run NAIRU. And policy simulations with FRB/US, the Board of Governors' main model, sometimes assume that agents form expectations by estimating reduced-form vector autoregressions rather than using model-consistent expectations. Moreover, issues related to communications and credibility figure prominently in FOMC discussions, because members recognize that well-anchored inflation expectations, as we have had in the United States since the mid-1980s, can reduce the sacrifice ratio and the sensitivity of inflation to supply shocks. More generally, the Federal Reserve recognizes that public understanding of its reaction function can help people form expectations in ways that are likely to enhance the stability of the economy. Given the importance that expectations formation plays in all aspects of modern macroeconomic models, I see a high payoff to further behavioral research on how people actually form expectations. Moreover, behavioral research could be very useful in helping us understand how best to communicate our views on the economy and on policy.

So far, I have discussed how behavioral research affects our understanding of what policy can do. I now want to draw on some of this discussion to address the question of what policy should do—namely, what we can learn about the appropriate objectives of monetary policy.

I'll start with inflation. In the long run, everyone agrees that inflation primarily reflects the actions of the central bank. But what inflation rate should we strive for as a long-run objective? Existing theoretical work, grounded in neoclassical models, provides surprisingly little guidance. It points to the importance of "shoe-leather" costs, since individuals tend to economize on their use of cash as inflation rises. However, these costs are probably small at low to moderate inflation. More important, in all likelihood, is the impact on the incentive to save and invest stemming from the interaction of inflation with the tax code. But behavioral economics brings other considerations into play. Empirically, the evidence from surveys performed by Shiller (1997) and those discussed by Di Tella and McCulloch (2007) at this conference, reveal that individuals strongly dislike inflation. It appears to reduce reported happiness. Such evidence, along with evidence suggesting that individuals heavily rely on nominal frames of reference in decisionmaking, reinforce the desirability of keeping inflation quite low. After all, zero inflation, correctly measured, means that the distinction between real and nominal variables is unimportant; indeed, targeting a constant price level would make it easier for people to plan for the future. However, some considerations highlighted by behavioral research point in the opposite direction. For example, the tendency of workers to ignore inflation in wage bargaining until it becomes salient and the prevalence of downward nominal wage rigidity suggest that there may be potential benefits from choosing an inflation target that is low but positive. These arguments reinforce a case for some small inflation cushion to guard against deflationary risks due to the "zero nominal bound" on interest rates. Although empirical work suggests that downward nominal wage rigidity is prevalent in the United States, its importance diminishes when productivity growth is high, as it has been since the mid-1990s.

Let me next turn to some implications of behavioral economics for the Fed's role in stabilizing the real economy. Along with price stability, output stabilization has been an important policy objective during the postwar period, and fluctuations in both output and unemployment have diminished. The questions for policymakers are how large are the welfare losses that result from such output volatility and how beneficial would further reductions be?

Perhaps surprisingly, standard economic theory suggests that the losses associated with output volatility of the magnitude experienced during the postwar period are quite small. Lucas (1987, 2003) spawned a large literature by arguing that the welfare gains from additional stabilization of the economy are tiny. Given standard preferences and the observed variance of consumption around a linear trend since 1947, he calculates that the representative American consumer would be willing to reduce his average consumption by a trivial amount, only ½ of 1/10th of a percent, to eliminate all remaining consumption volatility. Lucas concluded that stabilization of output, even if possible, should not be a[10] macroeconomic priority.

If Lucas's calculation were correct, then the average person in the United States would value consumption stabilization (complete insurance) by only around $16 a year.[11] Compared with the premiums we pay for very partial insurance (e.g., for collision coverage on our cars), this seems implausibly low. The New Keynesian model offers one basis to conclude that the costs may be larger. For example, Galí, Gertler, and López-Salido (2007) argue that, because of wage and price markups, steady-state employment and output are inefficiently low. In their model, the welfare effects of booms and recessions are asymmetric because marginal increases in employment result in diminishing welfare gains. In good times, with low unemployment, the marginal gain from additional job creation may be low, because marginal employees may be close to indifferent between work and leisure. In contrast, job creation in bad times may yield a sizeable welfare surplus. As a result, recessions are particularly costly—welfare falls by more during a business-cycle downturn than it rises during a symmetric expansion. If good policy reduces the frequency and severity of recessions, then the analysis of Galí et al. suggests that the resulting welfare gains may be substantial.

Behavioral considerations suggest some additional reasons why output stabilization may raise welfare. In particular, some of the behavioral phenomena discussed previously create the tantalizing prospect that a more stable economy may benefit from higher average levels of employment, output, and consumption. As DeLong and Summers (1988, p. 434) once put it, stabilization might "…fill in troughs without shaving off peaks."[12] Or, as in Barlevy (2004), stabilization might increase the economy's long-run growth rate. In contrast, both the neoclassical model, analyzed by Lucas, and the New Keynesian model, analyzed by Galí et al. predict that mean consumption, output, and unemployment are unaffected by the volatility of these variables.

One behavioral reason that a more stable economy might enjoy lower average unemployment relates to the convexity of the short-run Phillips curve. If this relationship is convex, rather than linear, higher volatility in unemployment is associated with a higher mean. Recall that such convexity could reflect the influence of downward rigidity in either nominal or real wages. Interestingly, using U.S. data for the period 1971 to 1995, Debelle and Laxton (1997) estimate that the increase in mean unemployment associated with the volatility in unemployment over this period amounted to a nontrivial 0.33%.[13] Yellen and Akerlof (2004) show that a similar argument applies if the long-run Phillips curve is not vertical at low inflation rates.

For policymakers, the bottom line of such research is that behavioral economic models tend to reinforce the priority that policymakers should attach to the goal of stabilizing output. But the magnitude of the possible gains are difficult to infer from existing empirical estimates of the Phillips curve. In principle, the happiness literature might give us some more direct evidence on these benefits. As Di Tella and McCulloch emphasize in their paper, there is persuasive evidence that happiness is inversely correlated with both unemployment and inflation. The finding that lower unemployment raises satisfaction even when it is fairly low to start with is consistent with the New Keynesian assumption that equilibrium unemployment is inefficiently high. But this finding sheds little light on how policymakers should assess the welfare consequences of fluctuations. This hinges on the more subtle issue of how volatility in unemployment affects well-being for a given mean. On this point Wolfers (2003), using subjective measures of satisfaction, found evidence of nonlinearity in the relationship between life satisfaction and unemployment, implying that unemployment volatility does undermine well-being. Even so, Wolfers found that the welfare benefits of reducing volatility are subject to rapidly diminishing returns, so that further reductions in the volatility of unemployment would raise welfare by only a relatively small amount, albeit by more than Lucas's estimate.

There's a lot more work to be done here to validate and confirm that happiness responses correspond to well-being.[14] In addition, we care about more than just whether people are happy; we'd like to understand why. There is considerable scope for more refined survey evidence that focuses more precisely on what it is that people dislike about unemployment and inflation, and why.[15]

Let me conclude by summarizing what I think policymakers can learn from behavioral research bearing on the Phillips curve. This research provides clear-cut evidence that people often deviate from the way that benchmark neoclassical theories assume. People have money illusion, follow rules of thumb, and care about issues like fairness and equity. As I've discussed, there's a growing body of literature that shows that macroeconomic theories built on behavioral foundations have strikingly different implications from more standard theories. Behavioral research thus offers the promise of unified theories that can explain microeconomic behavior as well as the movements of macroeconomic aggregates.

With respect to the Federal Reserve's dual mandate, behavioral research supports the view that inflation is costly, although very modest inflation might help protect against downward nominal wage rigidity. Behavioral macroeconomic models also provide theoretical underpinnings for the view held by most policymakers that, in the short run, monetary policy can and should strive to stabilize the real economy.

In sum, research on behavioral economics is as exciting for policymakers as it is for academics. It helps policymakers understand what they should care about and improves the quality of our economic models. The work at this conference highlights some of the progress that has been made, but also suggests that the marginal product of further research in behavioral economics is still likely to be very high.

Endnotes

1 I am deeply indebted to staff in the Economic Research Department of the Federal Reserve Bank of San Francisco, and most particularly to John Fernald, for their help in preparing these remarks.

2 See Lacko and Pappalardo (2007).

3 See Kroszner (2007).

4 The New Keynesian intuition for such a relationship is that firms that are readjusting their prices today will want higher prices if the marginal cost of production is relatively high; but they are also concerned that they might be unable to change their price in the future. Hence, if they expect inflation to be high in the future, they will want to raise their price by more today in order to keep from being stuck with a price that is too low.

5 In a simple version of the New Keynesian Phillips curve, Mankiw (2001) shows that the slope of the curve is αλ2/1-λ, where λ is the fraction of agents that adjust their prices each period and α is the response of the desired real price to movements in the unemployment gap with a small value of α reflecting greater real rigidity. With perfectly flexible wages and prices, λ = 1 and the curve is vertical.

6 Mankiw (2001) highlights these critiques.

7 A key motivation for Ball (2000) is that inflation appears very persistent in the postwar period but not persistent under the gold standard, which was a very different monetary regime. Common features of New Keynesian models, such as backward-looking agents or price indexing, can yield more persistence but not its apparent regime-specific nature.

8 Technically, in standard Phillips curve models, this relates to whether the coefficient on expected inflation is one.

9 Recent productivity data have been, on balance, weaker than the average since the mid-1990s. But most, if not all, estimates of trend productivity growth remain above the average growth rate from 1973-1995.

10 As Lucas (2003) makes clear, even taking his estimates at face value, such a calculation does not imply that the Federal Reserve should ignore fluctuations. Very long, very deep downturns, such as the Great Depression, are costly, and policy has avoided such episodes during the postwar period, presumably averting sizeable welfare costs.

11 Reis (2007) suggests this way of framing the benefits of stabilization.

12 Yellen and Akerlof (2004) survey this literature.

13 0.33% is the estimated difference between the average historical rate of unemployment and the deterministic NAIRU, defined as the unemployment rate consistent with nonaccelerating inflation in the absence of shocks.

14 Responses do appear correlated with things like income, employment status, education, marital status, and so forth. And there is some evidence that these measures are, in turn, mirrored in suicide data (see Daly, Wilson, and Johnson, 2007), which is clearly of a very objective nature.

15 Shiller (1997) took this approach in asking people about inflation.

References

Akerlof, George A., William T. Dickens, and George L. Perry. 1996. "The Macroeconomics of Low Inflation." Brookings Papers on Economic Activity 1996(1), pp. 1-59.

Akerlof, George A., William T. Dickens, and George L. Perry. 2000. "Near-Rational Wage and Price Setting and the Long-Run Phillips Curve." Brookings Papers on Economic Activity 2000(1).

Ball, Laurence. 2000. "Near-Rationality and Inflation in Two Monetary Regimes." NBER Working Paper 7988.

Ball, Laurence, and Robert Moffitt. 2001. "Productivity Growth and the Phillips Curve." In The Roaring Nineties: Can Full Employment Be Sustained? edited byAlan B. Krueger and Robert Solow. New York: Russell Sage Foundation and Century Foundation.

Barlevy, Gadi. 2004. "The Cost of Business Cycles under Endogenous Growth." American Economic Review 94(4), pp. 964-990.

Benjamin, Daniel J., and David I. Laibson. 2003. "Good Policies for Bad Governments: Behavioral Political Economy." Manuscript prepared for Federal Reserve Bank of Boston Behavioral Economics Conference, June.

Clark, Peter, Douglas Laxton, and David Rose. 1996. "Asymmetry in the U.S. Output-Inflation Nexus: Issues and Evidence." IMF Staff Papers 43(1) (March), pp. 216-250.

Daly, Mary C., Daniel J. Wilson, and Norman J. Johnson. 2007. "Relative Status and Well-Being: Evidence from U.S. Suicide Deaths." Working Paper Series 2007-12, Federal Reserve Bank of San Francisco.

Debelle, Guy, and Douglas Laxton. 1997. "Is the Phillips Curve Really a Curve? Some Evidence for Canada, the United Kingdom, and the United States." IMF Staff Papers 44(2) (June), pp. 249-282.

DeLong, J. Bradford, and Lawrence H. Summers. 1988. "How Does Macroeconomic Policy Affect Output?" Brookings Papers on Economic Activity 1988(2), pp. 433-480.

Dickens, William T. , Lorenz Goette, Erica L. Groshen, Steinar Holden, Julian Messina, Mark E. Schweitzer, Jarkko Turunen, and Melanie E. Ward. 2007. "How Wages Change: Micro Evidence from the International Wage Flexibility Project." Journal of Economic Perspectives 21(2) pp. 195-214.

Di Tella, Rafael, and Robert MacCulloch. 2007. "Happiness for Central Banks." Paper prepared for the Federal Reserve Bank of Boston Behavioral Policy Conference, September.

Fehr, Ernst, Lorenz Goette, and Christian Zehnder. 2007. "The Behavioral Economics of the Labor Market: Central Findings and Their Policy Implications." Manuscript (September).

Galí, Jordi, Mark Gertler and J. David López-Salido. 2007. "Markups, Gaps, and the Welfare Costs of Business Fluctuations." The Review of Economics and Statistics 89(1) (November), pp. 44-59.

Kroszner, Randall S. 2007. "Creating More Effective Consumer Disclosures." Speech delivered May 23 at the George Washington University School of Business, Financial Services Research Program Policy Forum, Washington, D.C.

Lacko, James J., and Janis K. Pappalardo. 2007. "Improving Consumer Mortgage Disclosures." Federal Trade Commission, Bureau of Economics Staff Report (June). http://www.ftc.gov/os/2007/06/P025505MortgageDisclosureReport.pdf

Lucas, Robert E., Jr. 1987. Models of Business Cycles. Oxford: Basil Blackwell Ltd.

Lucas, Robert E., Jr. 2003. "Macroeconomic Priorities." American Economic Review 93(1) (March), pp. 1-14.

Mankiw, N. Gregory. 2001. "The Inexorable and Mysterious Tradeoff between Inflation and Unemployment." The Economic Journal 111(471) (May) pp. 45-61.

Mankiw, N. Gregory, and Ricardo Reis. 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve." Quarterly Journal of Economics 117(4) (November), pp. 1295-1328.

Reis, Ricardo. 2007. "The Time-Series Properties of Aggregate Consumption: Implications for the Costs of Fluctuations." Manuscript, Princeton University. Shiller, Robert. 1997. "Why Do People Dislike Inflation?" In Reducing Inflation: Motivation and Strategy, edited by Christina D. Romer and David H. Romer. Chicago: University of Chicago Press.

Rotemberg, Julio J. 2007. "Behavioral Aspects of Price Setting, and Their Policy Implications." Manuscript (September).

Tobin, James. 1972. "Inflation and Unemployment." American Economic Review 62(1-2) (March), pp. 1-18.

Wolfers, Justin. 2003. "Is Business Cycle Volatility Costly? Evidence from Surveys of Subjective Well-Being." International Finance 6(1) (March), pp. 1–26.

Yellen, Janet, and George Akerlof. 2006. "Stabilization Policy: A Reconsideration." 2004 Presidential Address to the Western Economic Association, Economic Inquiry 44(1), pp. 1-22.

"I Really Believe That Economics Can Make the World a Better Place"

Frederic Mishkin is interviewed by Gary Stern of the Minneapolis Fed. The interview was conducted last May, but it wasn't posted until recently. The initial discussion on the health of the financial system is interesting given recent troubles in mortgage markets:

Interview with Frederic Mishkin, The Region, FRB Minneapolis, May 8, 2007: "Now I have a seat at the table," said Frederic Mishkin in conversation with Minneapolis Fed President Gary Stern. "Now I'm able to bring my academic experience to actual policymaking, and that is a very exciting enterprise for me."...

In September 2006, Mishkin was appointed to the Fed's Board of Governors, thereby gaining his "seat at the table": the opportunity-and responsibility-to shape monetary policy for the nation. Given his academic background, it's difficult to imagine anyone better prepared for the job, but as Region readers are well aware (2006 Annual Report) the transformation of economic theory into effective policy is not a simple task. ...

Mishkin brings an almost tangible enthusiasm to the task of translating theory into policy. A conversation with him is a fast-paced journey through macro theory and international history, filled with anecdote, humor and a passion for the field. His zeal is contagious, fueled by the conviction that the work of economists can improve our well-being. "I believe that ideas really do matter," he says in the interview that follows. "I really believe that economics can make the world a better place."

BANK SUPERVISION Stern: Let's begin with a fairly general question. One of the rationales offered in the past for why banks are special and thus have an important role to play in the financial system is the opaqueness of their assets, their complexities and so forth. But, today, with improvements in technology, reduction in cost of information and a growing variety of financial market innovations, banks may be less special and so play a less important role in the financial system. Does this mean that banking is less important?

Mishkin: Changes in the ability to process information more effectively have allowed a lot of lending to be moved out of the opaque into the more transparent. That has meant that the importance of banks in the overall financial system in terms of lending has decreased.

One of the huge impediments to the effective functioning of securities markets is that if there's not a lot of transparency in assets, then there cannot be a widespread set of holders. They're not going to buy an asset unless it's transparent because they can't do the individual monitoring themselves. In that context, if something has to be monitored very carefully internally, you have to have institutions making private opaque loans like banks.

With better information you now can make some assets much more transparent. For example, credit scoring enables loans that used to be very opaque to be far more transparent. Now you can actually provide the credit scores as part of the information about loans, and you can securitize those assets. What that means is that we actually have a more efficient financial system with a lot of assets moving out of bank balance sheets and out of private lending into public securities markets. That's a big positive for the economy. It means, however, that banks are not going to have the same dominance they used to have.

Nonetheless, banks are still very important in the system. If you look at bank lending as a percentage of total lending, it has declined, but it's still a very significant percentage of the total. So the importance of banks in terms of this private information that they collect with opaque assets is still there, but it's not as dominant as it used to be.

It should be mentioned that countries with lower quality of information, such as developing countries, are much more bank-dominated than the United States is. Although banks are not as dominant as they used to be in the United States, we still have to worry about the possibility that banks may get into trouble if they're no longer able to make these private loans and no longer able to collect the information that nobody else can collect. That is, if they can no longer perform their special role, the result would be a severe hit to the economy and to the efficiency of the capital markets. So the fact that we have an improvement in the overall financial system with banks playing a less dominant role doesn't mean that they and bank supervision are still not important.

TOO BIG TO FAIL Stern: If banks are, overall, less important, does that mean that the too-big-to-fail [TBTF] issue has diminished in importance as well?

Mishkin: Well, there's one sense in which the overall financial system is a little bit more secure. This is the spare tire that Alan Greenspan used to talk about because securitization makes for a more extensive financial system so that-all else equal-if problems were to arise in the banking sector, they would not be quite as serious overall. But it nonetheless is true that if you have systemic problems in the banking system, it's still going to create serious damage to the economy.

Stern: So if we're concerned about too big to fail, what would you recommend we do about it?

Mishkin: I think actually that a lot of things we have done are moving us in the right direction. One thing the Federal Reserve System has done is to create an LCBO [large complex banking organization] program where we do special monitoring of the largest financial institutions, because there is a recognition that if one of these [institutions] fails, it can have much more systemic implications for the economy. We've also put into place elements to reduce secondary, knock-on effects when a large institution fails, making the failure less costly to the financial system. We clearly want to keep on moving in exactly that kind of direction.

Very important, too, is that prudential supervision now focuses on risk management in a forward-looking manner, which is extremely important in terms of these large institutions. So the way that I would view this is that the Federal Reserve is in fact aware of the TBTF problem, and it's trying to make steps in the right direction. Clearly one of the reasons you wrote your book was to help keep pushing this process forward.

We also want to make clear that there are cases where we think the systemic problems are not severe and therefore that institutions can fail. Again, that has a benefit in terms of making market discipline more powerful.

A second issue that is extremely important is the question of punishment. Even if there is some kind of support for an institution, the fact that managers, stockholders, bondholders in fact take a big "haircut" is actually very important in terms of creating the right incentives for people not to take on excessive risk. We've made progress in this regard.

In emerging-market countries, however, the TBTF problem is greatly amplified because it's not just depositors who are protected but bondholders and equity holders. That means the incentives for markets to punish people for taking on excessive risk are decreased very substantially.

We can get one reading of the market's view on TBTF from the rating agencies. The rating agencies have long considered the likelihood of bailouts when they rate banks. Ratings for certain banks benefit significantly from the expectation that the home-country government will step in and provide support to prevent failure. The rating agencies rank the United States as a low-support country overall. That doesn't mean that there isn't an issue of potential support for the largest banks, and in fact the rating agencies indicate that there is. But we have made progress, particularly since the FDICIA [Federal Deposit Insurance Corporation Improvement Act] made it clear that we are going to make sure that people actually take haircuts. Even if institutions are so large that there is a perception that the government will not stand by completely and let them fail, there's still an issue about what kind of punishment is going to be meted out on the people who actually caused the problems in the first place. So there is a gradation here, and on that basis the United States has made progress. And, in fact, it's made progress relative to many other countries in the world.

HEALTH OF THE BANKING SYSTEM Stern: You touched earlier on the fact that banks are less important overall in the financial system than they were, and that reminded me that one of the explanations, or at least a partial explanation, for the Great Depression was that bank credit dried up and, in particular, small and middle-size firms couldn't get financed. I take it you would assess that risk as somewhat lower today because the range of alternatives has increased.

Mishkin: I would, but it would still be a problem. If we were to end up killing a lot of banks, we would still have a huge hit to the economy. So, for example, we've seen financial crises in emerging market countries, and because they're so bank-dominated, it freezes up the whole financial system. Well, in our case, if we have a banking crisis, it would not freeze up the whole financial system, but it would close up a good part of the system. And that would mean very severe costs for many, many people. That's one of the reasons why, as bank regulators and supervisors, we want to make sure that the financial system is safe and sound.

We've seen cases where this makes a difference. Let me give you an example. Leading up to the last recession that we had in 2001, we had a lot of very nasty shocks to the economy. We had the collapse of the stock market; we had September 11th; we had the Enron affair, which basically indicated that information in financial markets was not as good as people thought. All of those were very contractionary, yet we had a very mild recession. I was teaching at the time, and while I'm not an economic forecaster, this was one of the times I felt really good about my prognostications on the economy. Students were asking about the recession, and I said to them, "This is going to be a mild recession because the banks are in such good shape." And I got it right. So having the banking system work well is an extremely important part of keeping the economy stable. This is one of the reasons we do have to worry about too big to fail. I don't think it's quite as serious a problem as you make out in your book, but nonetheless I feel that it is a problem we do have to worry about.

FINANCIAL GLOBALIZATION Stern: Let's shift gears, because you talked a little bit earlier about foreign economies and some of the hindrances to their success. I've been struck for a while that although almost all professional economists and many economic policymakers agree about the benefits of trading goods and services for all countries that participate voluntarily, that same consensus doesn't seem to hold for financial globalization or integration. Why is that, in your view?

Mishkin: This is an area where I've done a lot of research in recent years and is of great interest to me. And it started really because I went to the Federal Reserve Bank of New York in 1994. Previously, I'd done all my work on the domestic U.S. economy; I hadn't really thought very much about emerging-market countries. And then, of course, the Mexican crisis occurred, and the president of the Bank kept asking me questions. I didn't have answers, so I figured I'd better think about it.

The reason financial globalization is much more controversial, I think, is severalfold. One is that economists have always been trained in terms of thinking about comparative advantage and the benefits of trade. It's one of the first things you learn in your Economics 101 course and is an idea that has been around for over a hundred years. On the other hand, the new literature on the importance of finance to economic growth has been around only 15 years or so. It's remarkable that so many people, including economists, don't understand how important finance is to economic growth. For example, the best selling undergraduate textbook in economic growth, which I actually think is a terrific book, doesn't discuss the link between financial and economic development. That to me is remarkable.

We have even had high-level government officials who've said, "Why is finance important? All these finance people get paid huge amounts of money and what do they do? They don't make anything real." Many people just don't understand the importance of finance. And yet when you start looking at why some countries are rich and others aren't, one of the things you realize is that finance is crucial. A good financial system allocates capital to its most productive uses, and this turns out to be absolutely essential to economic development.

When we look at developing countries, one thing we have learned is that throwing money at a country doesn't work. The most extreme example, of course, is that many countries that have oil wealth actually have not developed well. In fact, frequently countries with fewer resources are the ones that have done much better. Why is that the case? Because if you have money just pouring in, the government may not feel that it needs to actually develop institutions to make the capital markets work well. The government doesn't have trouble getting tax revenue, and it doesn't need to set up institutions that make it easy for people to do business. So we find that just throwing a lot of money at a country doesn't actually help.

What really is important to a country's growing rich is TFP [total factor productivity] growth. The countries that have done well are the ones that are able to allocate capital to productive uses. That increases productivity, and that's the source of growth in these countries. And so the question is, How do you get them to make that happen? Well, one view is that we can just open our capital markets to the world. In textbook versions that has the advantage of lowering the cost of capital by having it coming from outside. And it will be beneficial if you have the right institutional framework in place. But if the right framework isn't in place, opening up your capital markets can lead to a financial crisis and blow up your economy.

The benefits of financial globalization are clear cut. It lowers the cost of capital and therefore makes it easier to finance. It also increases competition in the banking system, which encourages domestic financial institutions to support institutional reform, because now that they have foreigners competing with them, they will lose business unless their country has the institutional framework that allows them to make good loans. So there are those benefits. But there's also the potential cost of opening up in the wrong way. So, does globalizing financially help a country? The evidence is mixed.

We take for granted the ease with which our institutions work. For example, at one point, because of my textbook, I decided to open a corporation called Mishkin Economics, Inc. It turned out it wasn't a great idea, so I eventually got rid of it. But it only took me an hour and $300 to set it up initially. But if you want to open up a small business in many developing countries, it's an extremely costly and difficult enterprise that only rich people can do.

If you ask yourself, Why does this happen? Why are legal businesses so hard to set up? Why is there corruption in these countries? Why aren't there enough judges and a good legal system to enforce contracts? The answer is that the elites in these countries do better if there's no competition. How do you keep competition from occurring? Make sure that you don't have an institutional framework that allows financial systems to allocate capital to your competitors. So financial repression-the fact that the financial system is not developing-is something that elites have frequently promoted. But then at some point they may have to open up the economy. The same elites may try to do that in a way that's very attractive to themselves, but which hugely increases risk-taking that can lead to a financial crisis and government bailouts that cost the public dearly. In my research, I have described how financial crises evolved in places such as Mexico in 1994 and in East Asia, especially South Korea in 1997.

The issue here is not, Is financial globalization inherently a good or a bad thing? If it's done right, it's extremely important to success in these countries. But if you do it wrong, it's going to create huge problems. So the issue is, How do you get it right? And one of the big problems in many of these countries is the too-big-to-fail problem. TBTF is much more pernicious than it is in advanced countries like the United States.

INTERNATIONAL CAPITAL FLOWS Stern: If you look at capital flows around the world in the last decade or more, despite what you might predict, capital seems to flow more toward the developed economies. And what flows into the developing economies seems to be small, at least compared to what some people predicted and hoped for. Are these infrastructure flaws a factor in that?

Mishkin: Absolutely. We're actually in an extraordinary period where money is flowing uphill. If you think about it, you should be able to make a lot of money by taking a factory that you could build in Europe or the United States and, instead of putting it in a country with high-cost labor, you could put it in a developing country where labor costs 10 cents on the dollar. So the standard view is that the returns should be very high in developing countries and much lower in rich countries. We should then expect to see large amounts of capital flow from rich to poor countries. We don't. This phenomenon is called the Lucas paradox because Bob Lucas first brought attention to it. But when Lucas raised this paradox in 1990, he was just commenting on how little capital flows from rich to poor countries.

What's even more extraordinary since Lucas wrote his paper is that the flow has actually gone the other way. Why is this happening? Because some of these countries with very high savings rates-China, for example-know that if they put the money into their economy, it will be misallocated. A much better deal is for them to take the money, send it to a rich country like the United States and get very low interest rates on it. So they're basically sending us cheap goods and helping us finance their purchase with extremely low interest rates. But they're still getting a better deal than putting it into their own financial system, because it's so undeveloped.

Is it a bad situation if this money is flowing to rich countries? It's a plus from the standpoint of where developing countries currently are. But it's a bad situation because they haven't developed the institutional framework to allow them to allocate capital well. For them to be successful and to remove some of these global economic imbalances, the solution is for them to develop their financial systems, making it more advantageous to keep their funds in country. That way they can earn higher returns in their country and develop. Also, it will mean that these huge capital flows that are coming to the rich countries and the coincident current account deficits that we have in countries like the United States will no longer occur.

Stern: Let me take that a step further. This would suggest a fair amount of risk aversion on the part of global investors-that they're willing to give up a fair amount of potential return for the safety of investing in, say, dollar- or euro-denominated assets. On the other hand, if you look at quality spreads in financial markets or even between developing- and developed-country bonds, you would often reach the opposite conclusion, that you're not very well-compensated for taking risks. How do you reconcile that discrepancy?

Mishkin: The reason you're unwilling to invest more in these countries is that they don't have the absorptive capacity to allocate capital well. For example, in many of these countries, if you put money in, it won't be put to good use. Underdevelopment of their property rights and legal systems, high levels of corruption-all these things are impediments to financial development. These are exactly the reasons that returns are not very high.

So in a sense, the answer to the Lucas paradox, the reason money is not flowing from rich to poor countries is that returns are not as high as they should be in these poor countries because of poor institutional development. If the world had good markets in all places, then money would be flowing from rich to poor. But when the markets are very undeveloped in poor countries and developed in rich countries, then the returns are not high in the poor countries. There are actually better returns in the rich countries, and money's going to flow uphill. That, of course, is not a great situation for world welfare because it is one of the reasons that these countries stay poor. It's not in our interest that these countries stay poor.

FINANCIAL CONTAGION Stern: Let me explore one other aspect of this. You were talking about Korea back in 1997. That brought to mind the contagion of financial problems, especially among developing countries. And 1997, 1998 was illustrative of that. This is another concern people raise about global financial integration: You might be enhancing vulnerability by allowing global financial integration to progress.

Mishkin: There is one sense in which you are enhancing vulnerability. If flows of capital can move very quickly from one place to another-they can move in and they can move out quickly-in that sense you can have some vulnerability. But there are two views of contagions; people typically emphasize just one and not the other. One view is that if something happens at the center of the world financial system, in terms of its views about a particular asset class, then investors will lump a set of emerging-market countries together and might pull out money from many of them at the same time; in this way contagion can actually come from the advanced countries.

However, another very important view that I think is not emphasized enough is that contagion occurs when one country gets into trouble and investors start to look at whether other countries are like it in terms of bad policies. When the Asian crisis started, for example, it started with Thailand. Government policies to liberalize the capital account along with lack of appropriate supervision and regulation resulted in excessive borrowing from abroad and risky lending by Thailand's finance companies. When the crisis erupted after the failure of Thailand's largest finance company, it exposed the underlying weaknesses of financial institutions' balance sheets. Nonperforming loans were so large that attempts by the government to bail them out and defend its currency at the same time failed, leading to a currency and financial crisis in Thailand.

At that point investors started to say, Well, what other countries might be like Thailand? There was new information from the problems in Thailand that suggested that some East Asian countries that we thought couldn't have any problems actually may have had some deep-seated problems. So investors took a look at South Korea. Has South Korea got a problem? Oh, yeah, Korea has a similar problem. Indonesia, oh, my God, even worse problems in Indonesia.

In addition, there were speculative attacks on Taiwan, Hong Kong and Singapore. Those countries had better bank supervision, and investors soon realized that the financial system problems that existed in Korea, Indonesia and Thailand were not a problem in this other set of East Asian countries. The speculative attacks stopped, and they didn't have financial crises. So when you look at this issue of contagion, one of the issues is that contagions can occur because there are bad policies in a set of countries, and once this fact gets revealed, you start looking elsewhere for the same bad policies.

It's no different in the United States. When Enron went belly up, people started to realize that maybe there were other companies that weren't providing reliable information. So the view here is that if there are similar bad policies in a number of countries or companies, there can be contagion when that fact is revealed.

The opposite is true too. For example, the crisis in Argentina in late 2001 and early 2002 did not spread elsewhere-with the exception of Uruguay, which was closely tied to the Argentine economy-because it was clear Argentina had been on a path of bad policies that were not being reproduced in other countries in Latin America. As a result, what happened to Argentina pretty much stayed in Argentina.

So, to sum up, although there is an element of truth in the view that these financial crises occur because of what happens in advanced countries, I think the ultimate responsibility when things go really wrong resides in the countries that have blown up. That is very important because it tells you that they have to improve their own policies with regard to how to get to a financial system that is well-supervised and well-regulated, just as we have in advanced countries. And how do you deal with the too-big-to-fail issue? As I said, TBTF is even a more severe problem in these countries because their banks are more dominant in the economy and the information flows are not as good. But it's not just too big to fail, it's also that many financial institutions are too politically connected to fail. The issues that we worry about here in the United States are actually a whole order of magnitude worse in these countries and emerging-market countries, and this is why it's very important to focus on encouraging them to get their fundamentals right.

DUAL MANDATES AND THE GREAT MODERATION Stern: Unlike a number of other central banks around the world, the Federal Reserve has a very explicit dual mandate, and frequently it's portrayed as if there's a conflict between the objectives of price stability and maximum employment. What's your view of that?

Mishkin: When any monetary economist writes down how a central bank should operate, we write down that it should have a dual mandate. I've done it in my papers, as have almost all monetary economists, because we always write down that a central bank should try to minimize not just fluctuations in the inflation gap [actual minus the optimal level of inflation] but also fluctuations in the output gap [actual minus potential output]. But then you have to ask yourself, What's the best way to minimize this loss function that includes both output gaps and inflation gaps?

Well, one thing that we've learned over the years is how important it is to have a strong nominal anchor in terms of not only producing less fluctuation in inflation but also less fluctuation in output gaps. By strong nominal anchor, I don't necessarily mean a nominal inflation target or objective, more broadly I mean a concerted effort by the central bank to control-and also make it clear that it will control-inflation. By doing so, the bank anchors both inflation and inflation expectations. That's important because it gets you a much more efficient monetary policy.

It is possible to think about the dual mandate as a trade-off between inflation gap fluctuations and output gap fluctuations. In fact this is described by the Taylor curve, a standard indifference curve that shows the trade-off between these two things. And we've found that if inflation expectations and inflation are not anchored, which was the situation we had in most advanced countries, including the United States, in the 1970s and early 1980s, then you're in the interior of the curve-you're in an inefficient position in terms of monetary policy.

It's remarkable that central banks throughout the world, including the U.S., have now focused much more on promoting a strong nominal anchor. If you're focused on price stability as a major concern, there is the worry that maybe you're going to focus less on the output fluctuation part of the dual mandate, and the result will be that you might get lower volatility of inflation, but you'll get more volatility in terms of output fluctuation.

But that's not what's happened. Throughout the world we're seeing much lower inflation fluctuations: In fact, nobody, myself included, would have predicted 15 or 20 years ago that so many countries in the world would have such low and very stable inflation. But what's even more remarkable is that we actually have more stable output fluctuations.

Stern: Is that your explanation for the Great Moderation [the widespread decline of macroeconomic volatility in recent decades]?

Mishkin: It's one of the explanations. I think there are a lot of other things that may be going on. I take the view that monetary policy becoming more efficient is one of the important sources of the Great Moderation. But I also think that, as my mother always said, "It's better to be lucky than good." Although I always like to modify her dictum to, "It's better to be lucky and good." And I think that's also part of the explanation. Monetary policy in the United States especially, but also elsewhere in the world, has been much better than it was before. That's part of the Great Moderation. But we've also been lucky. There seem to be fewer shocks to the economy than we've had in previous periods.

Monetary policy is not a unicausal explanation for the Great Moderation, but I think it's actually a very important part of the picture. And this is one of the great monetary policy successes. As I said, it's an extraordinary period in terms of where we are relative to 15 to 20 years ago. In most cases central banks did not have somebody like "the maestro," Alan Greenspan, yet they also id very well.

Indeed, as an economist I believe that ideas really do matter. I am proud as an economist that our better understanding of monetary theory has improved monetary policy and has actually contributed to economic world welfare. Indeed, I didn't become an economist because I just wanted to get tenure at a good university. I really believe that economics can make the world a better place.

PERFORMANCE OF THE U.S. ECONOMY Stern: Let me ask you a question about the U.S. economy. Since the early 1990s, the United States has done, I would say, appreciably better economically than most of the other advanced industrial countries. What's your explanation for that?

Mishkin: I think it gets back to this issue of finance. The United States has been blessed with a financial system that has in many ways worked better than other countries' financial systems. The common law legal system that we inherited from the British is very good at dealing with financial contracts. Countries that have a common law system have bigger, better-functioning securities markets because the quality of enforcement and the improvement of information have actually made the securities market more important.

That helped us in terms of the so-called new economy. We have a better venture capital system than most other countries have. That has allowed nerdy guys with great ideas to get access to capital. Our legal system has meant that venture capitalists are willing to give money to these nerdy guys because of two things: First, venture capitalists can put in governance to make sure that if a guy has a good idea but doesn't know how to manage, venture capitalists can put in a CEO or put people on the board of directors to make sure their money is used properly.

Second, we have a very deep securities market, so when the company does well, venture capitalists can issue an IPO [initial public offering] and basically cash out. So our financial system is a tremendous advantage for the U.S. economy; it has allowed us to be more dynamic than other countries. We have an extremely competitive economy, and as an economist, I think competition is key to having an economy that does well.

You can see this in our university system, which I have seen firsthand as a professor over the past 30 years. The American university system is the most dominant in the world. Why? Because it's not this ivory tower that everybody pictures; it's actually very dog-eat-dog. Competition in the U.S. university system is what drives the system, and it has made it one of the dominant export sectors that we have in the United States.

And, in general, we are a very, very dynamic economy. The financial system has helped in that regard. Monetary policy has also helped in the following sense: Monetary policy did not create the new economy, but if monetary policy keeps the economy on an even keel and keeps inflation low, that also contributes to an environment that enables the new economy to blossom.

IS THE BUSINESS CYCLE DEAD? Stern: You brought up the term new economy. That term became popular sometime in the second half of the 1990s, and I always took it to mean that productivity was on a new and more-favorable path. I think some people took it to mean that the business cycle was now dead, and we would see sustained economic growth forever. I'd like to get your take on that.

Mishkin: My view is that there are a few things we're always going to have: There's death, there's taxes and there's the business cycle. Good policy can certainly minimize the propagation of shocks. But there are always going to be surprises to the economy. And, as I said, if you look at the most recent recession, there were several surprises. Who could have anticipated September 11? A terrible thing. The Enron episode. Who could have anticipated it? You could have energy shocks. You could have a terrorist incident. You can have a war. So there are always shocks to the economy. You can't always anticipate those shocks, and those shocks frequently produce business cycle movements.

Good policy, however, makes it less likely that shocks will be propagated. One of the reasons I think monetary policy has contributed to the Great Moderation is that monetary policy has propagated adverse shocks much less than it did in the past. Think about oil price shocks in the '70s. There we had monetary policy that did not have a strong nominal anchor. Inflation and inflation expectations were not anchored. In that context, when we had an oil price shock, people thought, "Gee, inflation's going to spin out of control. This means that interest rates are going to rise for two reasons. One, higher expected inflation drives interest rates up; and two, the central bank, in order to restore credibility, has to raise interest rates." What was the result of that? Not only high and variable inflation, but also much larger business cycle swings. We had a very severe recession in 1974-75, and we also had very severe recessions in 1980 and 1981-82.

It's a huge benefit to have credible monetary policy with a strong nominal anchor. Think of the recent very strong energy price shock. It led to a temporary rise in inflation, but only temporary, because the central bank had convinced people with its past, present and continuing actions that it was not going to let inflation get out of control. The Fed would do what it had to do.

This is a very important part of central banking. It's not just what you do now but also people's expectations of what you're going to do in the future. It's extremely important that people understand that the Federal Reserve is monitoring inflation very carefully and that we will make sure that if inflation starts to rise, we will do something about it. If inflation doesn't moderate to levels that we think are appropriate, or if inflation falls too low so that we have the potential for deflation-we will do the right things about it. That creates exactly this kind of stabilization of not only inflation but also of output fluctuations.

CENTRAL BANK MANDATES Stern: The European Central Bank arguably doesn't have a dual mandate. At the end of the day, do you think that's going to matter to economic performance in Europe?

Mishkin: The Congress has given us a dual mandate; that is, the Federal Reserve seeks to promote the two equal objectives of maximum employment and price stability, so that's what we have to execute. Even if the Congress hadn't given us such a mandate, the basic structure of the dual mandate is what I would feel is appropriate, and so we should be aiming to pursue such an objective anyway.

A hierarchical mandate says that first we focus on price stability and if we're successful then we'll focus on other concerns, particularly output fluctuations. If you interpret a hierarchical mandate as focusing on price stability in the long run, making sure that long-run inflation expectations are grounded-and we've seen tremendous success not just in the United States but in Europe in terms of grounding inflation expectations-then the dual mandate and the hierarchical mandate are identical.

Some people have said to me that the dual mandate versus hierarchical mandate dichotomy is a red herring. I don't agree, because I think it is an important issue in communications strategy. It's important to make it clear that you care about output fluctuations, but you're going to look at this from a long-run context and never take your eye off the inflation ball. That's the right way to do the dual mandate.

Similarly, with the hierarchical mandate, you should not be an "inflation-nutter," as Bank of England Governor Mervyn King has expressed it. That is, you shouldn't be focused solely on inflation control. You must also worry about the fact that if you act too quickly to get inflation down to your long-run objective, you might have excessive, unnecessary fluctuations in output. So I think modern monetary theory, in writing down a hierarchical mandate or a dual mandate, will write exactly the same loss function, exactly the same kind of optimization theory for a central bank.

In some contexts it may be better to discuss monetary policy in terms of the hierarchical mandate. I think the reason it's been done in Europe is because they have had so much worse monetary policy in many countries. To make sure that people understood that they would really control inflation, they had to do it by talking about it as a hierarchical mandate. While in the United States, which has actually never had a hyperinflation and has had much more successful monetary policy, it's more appropriate to talk about it in terms of a dual mandate.

Stern: Maybe we're less prone to the time consistency problem.

Mishkin: Exactly. The time consistency problem is a central issue in thinking about how to do central banking-and also in terms of bank supervision. It's really the same issue. You want to make sure that you're doing the right thing in the long run and not pursuing short-run strategies that end up with very bad long-run outcomes. It's extremely important-in order to deal with the time consistency problem-to say that in the long run, price stability is absolutely going to happen. And that means that you can actually exercise "constrained discretion," the phrase Ben Bernanke and I coined in our earlier work. The idea is that you do need some discretion to deal with the shocks in the economy, but you want to make sure that that discretion is constrained in the sense that you don't ever get into the time consistency problem of allowing the nominal anchor to be weakened. And that's really what the whole concept of constrained discretion is.

This also relates to bank supervision. In my research on this, I felt that the distinction between rules and discretion is too stark. We know with discretion you can get into the time consistency problem. The way I think about this is, suppose it's New Year's Eve and I say I'm going to go on a diet. Then, of course, at the next meal I see a beautiful piece of cake and I can't resist: I've got to eat it. But I say to myself, It's no problem because I won't eat it tomorrow. Well, the next day comes and I can't resist again and keep on eating that cake, and I end up being obese. So we know that one of the ways to solve that problem is to set yourself a rule: Thou shalt not eat cake.

The problem is that there are always going to be unforeseen circumstances where actually you may need to use discretion. It's something you couldn't predict beforehand. If you have a rigid rule, you may find the rule no longer applies, and if you stick to it you will get very bad outcomes.

In terms of bank supervision, in my initial work on this I looked at prompt corrective action strategies. Originally, the idea was that PCA should be a hard and fast rule. No matter what, it has to be done. When you hit particular triggers, you automatically have to do X, Y and Z. What the Congress did in the FDICIA legislation of 1991, which I thought was very smart, was to say, "Look, there is a norm, and that's what should usually be done. But there could be unforeseen circumstances where we need to allow for deviation from that rule." They did this by saying that there would be a presumption that the rule should be followed but did give the supervisory agencies some discretion to deviate from the rule.

Why then aren't we back in a time inconsistency view of the world? Because Congress constrained the discretion. How? Through transparency. FDICIA requires a mandatory review of any bank failure that imposes a cost on the FDIC. The result report on what actions the supervisory agencies took must then be made available to any member of Congress and to the general public upon request, and the Government Accountability Office must do an annual review of these reports. Opening up the actions of the supervisors to public scrutiny will make it far more likely that they will follow PCA unless they have a very good reason for doing otherwise.

So it's exactly this constrained discretion kind of idea. Constrained discretion says that for most cases you want to operate according to a rule. On the other hand, there are going to be circumstances we can't predict where you may have to deviate from the rule. But in that case we don't want to let you do whatever you want. We want to have some check-and-balance on the system. In fact, my view is that this is also what our Constitution is all about. Having an institutional framework to deal with some of these time consistency problems is something that we see in the political sphere as well.

SYSTEMIC RISK EXCEPTIONS Stern: I would agree that having some discretion to deviate from a rule, such as the systemic risk exception to using least-cost resolution of a banking failure, is probably a good idea. But as you know, my Too Big to Fail coauthor and I are more concerned than you are that that exception will be invoked in circumstances where it's not really appropriate.

Mishkin: Right. We have a disagreement. Where we disagree on this is that I think transparency actually has a huge benefit in this regard. And so I view FDICIA as having been more effective than you and Ron Feldman do, as I indicated in my review essay on your book. The reason I take this view is that when you actually expose things to the light of day, then you change behavior. And there is a big difference in terms of the way things were done before, where of course there could always be an agreement between the three agencies, but it was not as transparent.

Stern: And there was, in the Continental Illinois National Bank and Trust Company case in 1984, for instance.

Mishkin: Yes, there was a bailout in the Continental case, but there was no transparency about how the bailout would be done. Now everybody's on notice that a rule has been put in place, that everybody expects you to follow that rule under normal circumstances, and if you deviate from it you'd better explain why. Now, this kind of transparency may not solve the problem 100 percent, and this is always the tension about constrained discretion. What's the optimal level of constraint? You're always afraid, when you say there's discretion, that when push comes to shove, the constraint won't be there. My view is that one of the things that helps this process tremendously is the kind of transparency that actually would produce a constraint on behavior. And, in fact, what we've seen is really a sea change in the way bank supervisors and regulators operate from pre-1991 to post-1991.

The element of transparency also comes up in the implementation of prompt corrective action, where there is a presumption that the rule will be followed, but prudential supervisors can deviate from the rule. But whenever there's a bank failure, whatever the supervisors have done has to be reported publicly, making it hard for them to deviate from the rule. They don't have to pursue prompt corrective action exactly, but clearly the presumption is there, and if they don't, they'd better explain themselves. They have to send a report to the GAO explaining why they didn't do what the standard rule told them they were supposed to do. The result we've seen is prompt corrective action has been working very well.

Stern: Thank you very much.

Video Lectures

I will probably regret doing this, but for anyone interested in videotaping their classes, here is one example of how the videos turn out from a class I taught yesterday afternoon. The camera is on a tripod between the second and third rows, and a student worker from Media Services sits in a chair and operates it (which is mostly just tracking back and forth).

This is the Google video version, so the resolution isn't quite as good as the other version I'll post for the class, but I think it's good enough (and uses Google's bandwidth, I also use TypePad to store and serve class videos).

This isn't an exciting lecture or anything, in fact it appears to be pretty boring (and the camera made me surprisingly nervous at the start, so my explanations about Greenspan , etc., aren't as clear as I'd like), but I have the impression from this post that people seem to be interested in trying this, and it does illustrate how you might expect the videos to turn out. So, setting aside my reluctance to expose my teaching, here's what you might expect. The picture gets a bit better once the overhead projector is turned off a few minutes into the video (scrolling works):

Paul Krugman: Hired Gun Fetish

Paul Krugman on the (mis)use of private security contractors in Iraq:

Hired Gun Fetish, by Paul Krugman, Commentary, NY Times: ...As far as I can tell, America has never fought a war in which mercenaries made up a large part of the armed force. But in Iraq, they are ... central to the effort...

And, yes, the so-called private security contractors are mercenaries. They're heavily armed. They carry out military missions, but ... don't answer to military discipline. On the other hand, they don't seem to be accountable to Iraqi or U.S. law, either. And they behave accordingly.

We may never know what really happened in a crowded Baghdad square two weeks ago. Employees of Blackwater USA claim that they were attacked by gunmen. Iraqi police and witnesses say that the contractors began firing randomly at a car that didn't get out of their way.

What we do know is that more than 20 civilians were killed, including the couple and child in the car. And the Iraqi version of events is entirely consistent with many other documented incidents involving security contractors.

For example, Mr. Singer reminds us that in 2005 "armed contractors from the Zapata firm were detained by U.S. forces, who claimed they saw the private soldiers indiscriminately firing not only at Iraqi civilians, but also U.S. Marines." The contractors were not charged. In 2006, employees of Aegis, another security firm, posted a "trophy video" on the Internet that showed them shooting civilians, and employees of Triple Canopy, yet another contractor, were fired after alleging that a supervisor engaged in "joy-ride shooting" of Iraqi civilians.

Yet..., Blackwater has the worst reputation. On Christmas Eve 2006, a drunken Blackwater employee reportedly shot and killed a guard of the Iraqi vice president. (The employee was flown out of the country, and has not been charged.) In May 2007, Blackwater employees reportedly shot an employee of Iraq's Interior Ministry...

Iraqis aren't the only victims of this behavior. Of the nearly 4,000 American service members who have died in Iraq, scores if not hundreds would surely still be alive if it weren't for the hatred such incidents engender.

Which raises the question, why are Blackwater and other mercenary outfits still playing such a big role in Iraq?

Don't tell me that they are irreplaceable. The Iraq war has now gone on for four and a half years — longer than American participation in World War II. There has been plenty of time ... to find a way to do without mercenaries...

And the danger ... to American forces has been obvious at least since March 2004, when four armed Blackwater employees blundered into Fallujah in the middle of a delicate military operation, getting themselves killed and precipitating a crisis that probably ended any chance of an acceptable outcome in Iraq. Yet ... last year the State Department gave Blackwater the lead role in diplomatic security in Iraq.

Mr. Singer argues that reliance on private military contractors has let the administration avoid making hard political choices, such as admitting that it didn't send enough troops... Contractors..., "offered ... additional forces, but with no one having to lose any political capital." That's undoubtedly part of the story.

But it's also worth noting that the Bush administration has tried to privatize every aspect of the U.S. government it can, using taxpayers' money to give lucrative contracts to its friends — people like Erik Prince, the owner of Blackwater, who has strong Republican connections. You might think that national security would take precedence over the fetish for privatization...

"Does Lack of Liquidity Impair Entrepreneurs?"

Who's right, Smith or Plato?:

Does lack of liquidity impair entrepreneurs?, by Hans K. Hvide, Vox EU: One of the oldest ideas in the study of entrepreneurship is that entrepreneurs may be unable to establish a venture at an efficient scale due to liquidity-constraints arising from capital market imperfections. This idea can be traced back to Adam Smith, who in the Wealth of Nations stated that entrepreneurs: "have all the knowledge, in short, that is necessary for a great merchant, which nothing hinders him from becoming but the want of sufficient capital."

Business people and venture capitalists, on the other hand, caution that excess liquidity can facilitate overspending or adversely affect the entrepreneur's motivation to perform. The idea that more liquidity can have a negative effect on performance can be traced back to Plato, who in the Republic wrote: "wealth is the parent of luxury and indolence". Who should we place our bets on, Adam Smith or Plato?

Previous work tends to focus on whether lack of liquidity stops nascent entrepreneurs from starting up a company. The findings here are mixed. While early research such as Evans and Jovanovic (1989) tends to find that start-up propensity is correlated with wealth, recent work on US data by Hurst and Lusardi (2004) finds practically no relation. The question then is whether lack of liquidity can have effects on other, perhaps more important, aspects of entrepreneurship, such as size and profitability.

Using a unique dataset from Norway, our research investigates the effect of liquidity, as measured by founder's prior wealth, on start-up size and start-up profitability. To avoid capturing effects that go via more wealthy founders having higher human capital, we control for human capital via age, education, and prior wage variables. We also control for business cycle and industry effects.

The following figure uses the estimated coefficients to plot predicted start-up size and predicted profitability for varying wealth levels.

Liq

The dashed line depicts the predicted start-up size as a function of the founder's prior wealth. Size is measured in log Norwegian kroner (NOK) value of assets at the end of the first year of operations (1EUR=8NOK). Liquidity has a rather strong effect on size. For example, the predicted start-up size for an entrepreneur with wealth around NOK 5,000,000 is about twice the predicted start-up size for a founder that has wealth of just NOK 500,000. The positive relation between founder wealth and start-up size suggests that, consistent with Smith's view, liquidity constraints are important in determining venture size.

The solid line depicts the relationship between wealth and profitability, as measured by operating return on assets. Profitability increases by about 8 percentage points from the 10th to the 75th wealth percentile. This suggests an entrepreneurial production function with a region of increasing returns, and that liquidity constraints could stop entrepreneurs from being able to exploit a "hump" in marginal productivity.

At the top of the wealth distribution, profitability drops by about 11 percentage points from the 75th to the 99th percentile. That profitability decreases on some interval of the wealth distribution is what one would expect if marginal profitability decreases as start-ups reach their efficient scale, as in Evans and Jovanovic (1989). It is puzzling, however, that profitability on assets falls sharply in the region where entrepreneurs are least likely to be liquidity-constrained.

One explanation for why the relation between wealth and profitability decreases sharply at the top could be that richer founders are more indolent and less dedicated to their venture. We find evidence consistent with this view. While 85% of the entrepreneurs in the bottom 95% of the wealth distribution work for the start-up at the end of the second year of operations, the corresponding figure for the entrepreneurs in the top 5% is only 68%.

We also investigate the relation between founder prior wealth and other measures of performance such as entrepreneurial wage and survival. Our results here are broadly consistent with the results obtained on profitability.

Overall, our findings thus give support to both Adam Smith and Plato. A moderate amount of liquidity may propel entrepreneurial performance, consistent with Smith's view, but an abundance of it may do more harm than good, consistent with Plato's view.

Borrow and moral hazard As an alternative explanation to increasing returns, the upward-sloping part of the dashed curve could be because more wealthy entrepreneurs borrow less than less wealthy entrepreneurs and are thus less exposed to moral hazard, as in Aghion and Bolton (1997) thus ensuing better performance. We investigated this possibility by analysing the relationship between founder prior wealth and the level of debt of the start-up at the end of the first year. As argued by Paulson et al. (2006), one would expect this relationship to be negative if the underlying reason for liquidity constraints is moral hazard, while if the underlying reason for liquidity constraints is limited liability, as in Evans and Jovanovic (1989), one would expect it to be positive. The estimates we obtained suggested a strong positive relation between wealth and the level of debt in all wealth groups, with an elasticity of debt to wealth of about 0.3. Thus the role of moral hazard in explaining the upward-sloping part of the solid line in the figure seems limited, and increasing returns to scale seems the more likely explanation.

Policy implications We see two main policy implications. For a main bulk of the wealth distribution, liquidity constraints incur a large negative effect on start-up size and profitability. This suggests a possible role for policy in alleviating financial constraints of young businesses. Obviously, such policies may have pitfalls of their own. For example, policies aimed towards improving the liquidity of start-ups could have a detrimental effect on the selection into entrepreneurship, a question our study does not address. Second, we find a sharply negative relation between liquidity and profitability at the top of the wealth distribution. This suggests that policies aimed at alleviating liquidity constraints should carefully target those entrepreneurs that are indeed likely to be liquidity-constrained.

The Great Moderation in Output

This work finds that The Great Moderation in output - the decline in the volatility of output in the mid 1980s - is due to declining variability in investment and consumer durables purchases, a result that suggests that better inventory management and financial innovation are at least part of the declining volatility story. It also finds that for understanding swings in GDP growth, "Tracking shifts in investment spending remains critical, but changes in household spending on nondurable goods are now more important than movements in consumer durables. Meanwhile, the fraction of jobs growth volatility attributable to firms in professional and business services has risen to the point where this sector has become the largest contributor to short-run swings in aggregate jobs growth.":

The 'Great Moderation' in Output and Employment Volatility: An Update, by Evan F. Koenig and Nicole Ball , Economic Letter, FRB Dallas: Volatility can wreak havoc on economies. Sudden, sharp ups and downs in business activity can make it difficult for consumers to plan their spending, workers to feel secure in their jobs and companies to determine their future investments. Because of their impact on expectations and business and consumer confidence, swings in the economy can become self-reinforcing. Volatility can also spill over into real and financial asset markets, where severe price movements can produce seemingly arbitrary redistributions of wealth.

It's good news, then, that the U.S. economy has become much more stable. On average, the five recessions from 1959 to 1983 were 47 months apart, lingered 12 months and were associated with a 2.17 percent peak-to-trough decline in real gross domestic product. By contrast, the 1990 downturn came after 92 months of expansion, lasted eight months and involved a 1.26 percent decline in GDP. The 2001 slump ended a record 120 months of uninterrupted growth, lasted eight months and entailed a GDP decline of only 0.35 percent. More generally, quarterly growth in both real GDP and jobs became markedly less volatile after 1983.[1]

Explanations for this "Great Moderation," as it's called, include structural changes in the economy, improved monetary policy and simple good luck.

Potentially important structural changes include the elimination of ceilings on deposit interest rates, broader access to credit markets through financial innovations like home equity loans, tighter inventory controls facilitated by technology, and the globalization of output and labor markets.

By improved monetary policy, analysts typically have in mind central bank actions that respond more quickly and forcefully to emerging inflation pressures, so that medium- to long-term price expectations remain contained.

As for good luck, analysts cite the reduced frequency of economic shocks comparable to the 1973 Arab oil embargo and 1979 oil price spike.[2]

We've accumulated eight years of additional data since completion of the early work on the Great Moderation, and the U.S. economy has experienced another recession and recovery. The new data allow us to examine whether the moderation has continued and detect changes in different sectors' contributions to volatility.

Our results are interesting because of the light they shed on the debate over the causes of the Great Moderation, but they're also useful in their own right. Breaking volatility down by sector, for example, can pinpoint which industries and expenditure categories are currently the most important sources of fluctuations in GDP and employment. It's in these areas that monitoring efforts ought to be focused.

What we've found in studying the new data is that the reduced aggregate volatility that began in 1984 has continued into the new millennium. The economy's volatility hasn't, however, dropped much further. In the case of GDP growth, most of the initial volatility decline can be attributed to greater stability in investment and consumer durables expenditures. Volatility from consumer spending has fallen further in recent years, but this decline has been completely offset by increased volatility from international trade.

In the case of jobs growth, most of the 1984 volatility decline can be attributed to manufacturing. The sector's volatility contribution has held steady since then, even though its employment share has continued to shrink. Meanwhile, jobs growth volatility originating in professional and business services has increased sharply.

Sector Volatility How much any sector contributes to the U.S. economy's ups and downs depends on three factors: the sector's own volatility, its share of business activity, and its tendency to move with or against the overall economy. This cataloging is analogous to the familiar notion that any given stock contributes more to a portfolio's riskiness the more volatile its returns, the larger its portfolio share, and the greater the correlation between its return and returns on the portfolio's other stocks.[3]

We traced various sectors' contributions to the volatility of quarterly growth in GDP and jobs over three periods: the 25 years starting in 1959 and running through 1983, the 12 years from 1984 through 1995 and the nearly 12 years from 1996 through the second quarter of 2007. Each of these intervals includes at least one economic expansion, recession and recovery.

The most recent period is interesting because it was marked by rapid growth in international trade and financial flows and the spread of new, more flexible labor market arrangements. These are the kinds of structural changes that might be expected to affect the stability of economic growth. This period was also marked by large swings in the real price of oil.[4] Insofar as oil price shocks were responsible for some of the economy's pre-1984 instability, we might expect a return of some of that volatility.

GDP Growth Volatility We can measure GDP growth's volatility by looking at the range within which growth has fallen 95 percent of the time. Between 1959 and 1983, for example, annualized GDP growth averaged 3.6 percent and strayed outside a –5.3 to 12.5 percent range only 5 percent of the time. The margin of error for GDP growth over this period was plus or minus 8.9 percentage points (Chart 1).

Chart 1: GDP growth volatility dropped off sharply in the mid 1980s

Between 1984 and 1995, growth was 3.2 percent, plus or minus 4.3 points—a margin of error less than half of what it had been. Finally, from 1996 to 2007, GDP growth averaged 3.1 percent, plus or minus 4.1 points.

By convention, analysts measure a series' volatility by its standard deviation, which is one-half the margin of error. In percentage points, the standard deviations for GDP growth are 4.47 for 1959–83, 2.14 for 1984–95 and 2.04 for 1996–2007.

The big decline in GDP growth volatility occurred during the mid-1980s. Since then, it has stayed relatively constant. Sustaining this low volatility over the past 12 years is impressive, however, given the large swings in oil prices and business investment during that period. This suggests the economy's increased stability is due to more than good luck.

So, if not purely good luck, then what? A sector-by-sector breakdown reveals expenditure categories whose volatility contributions fell most sharply from 1959–83 to 1984–95 (Table 1). Inventory investment's contribution declined from 1.82 to 0.69 percentage points, consumer durables' from 0.83 to 0.44 points, residential investment's from 0.57 to 0.25 points and nonresidential fixed investment's from 0.71 to 0.42 points.

Table 1
Contributions to Volatility in GDP Growth (Percentage points)
1959–83
1984–95
1996–2007
Consumption
1.42
.82
.41
Durables
.83
.44
.12
Nondurables
.39
.24
.18
Services
.20
.14
.11
Investment
3.10
1.36
1.34
Nonresidential fixed
.71
.42
.51
Residential
.57
.25
.17
Inventory
1.82
.69
.66
Government
.22
.24
.17
Net exports
–.26
–.28
.12
Total
4.47
2.14
2.04
NOTES: The total is the standard deviation of GDP growth. 2007 data are through the second quarter. Numbers may not add up due to rounding.
SOURCE: Bureau of Economic Analysis.

These results suggest—but don't prove—that tighter inventory controls, consumers' improved access to credit and financial deregulation played important roles in the economy's greater stability.

Although the decline in overall GDP growth volatility has been small since 1995, some shifts in sector contributions are significant. For example, consumption's contribution over the most recent 12 years is half what it was over the previous 12. Most of this decline can be attributed to consumer durables, but nondurables also show a drop.

The recent reduction in consumption's volatility contribution is, however, offset by net exports' increased contribution. In 1959–83 and 1984–95, the trade sector subtracted about 0.3 percentage points from GDP volatility. This reflects net exports' historical tendency to act as an automatic stabilizer, rising when the U.S. economy is weak and falling when it's strong. Since 1995, though, the correlation between quarterly changes in net exports and GDP has turned slightly positive, and the category has added 0.1 point to aggregate volatility.

Let's take a closer look at investment and consumer durables, which are primarily responsible for output's increased post-1983 stability. Changes in these sectors' relative size didn't contribute much to the decline in overall GDP volatility. Most of the impact came from reductions in their volatility and their correlation with the overall economy.

For investment, the standard deviation of sector growth fell from 22.6 to 14.2 to 11.4 percentage points over the sample periods, and the correlation between sector and GDP growth declined from 0.85 to 0.64 before bouncing back up to 0.73 (Chart 2A).

Chart 2: investment, consumer spending on durables key to post-1983 GDP stability

Meanwhile, investment's share of GDP held steady at about 0.16 (16 percent). The net result was a sharp decline in the sector's contribution to GDP growth volatility from 1959–83 to 1984–95 and very little change from 1984–95 to 1996–2007.

For consumer durables, the standard deviation of sector growth fell from 15.0 to 12.1 to 9.4 percentage points, and the correlation between sector and GDP growth dropped from 0.66 to 0.44 to 0.15.

At the same time, the sector share held steady at about 0.084 (8.4 percent). Consequently, consumer durables' contribution to the volatility of GDP growth fell substantially from sample period to sample period, up to and including 1996–2007 (Chart 2B).

Before 1984, the key categories to watch in tracking GDP fluctuations were inventory investment, consumer durables spending and nonresidential fixed investment. Inventory and nonresidential fixed investment remain important sources of volatility today, but consumer durables ranks as an also-ran. Now tied for third in importance are consumer expenditures on nondurable goods, residential investment and government expenditures.[5]

Jobs Growth Volatility When it comes to overall volatility, jobs growth exhibits a decline that's similar to the one we saw for GDP growth but smaller in magnitude (Chart 3). The margin of error needed to encompass 95 percent of jobs growth's variation narrows from 5.1 percentage points for 1959–83, to 3 points for 1984–95, to 2.7 points for 1996–2007. The standard deviation of jobs growth drops from 2.53 to 1.52 to 1.33 points in those periods.

Chart 3: job growth volatility declined markedly in the mid-1980s

Average annual jobs growth has declined, too, going from 2.3 percent in 1959–83 to 2.1 percent in 1984–95 and 1.4 percent in 1996–2007.

Manufacturing was mainly responsible for the sharp fall in jobs growth volatility after 1983. Its contribution dropped from 1.25 percentage points in 1959–83 to 0.32 points in 1984–95 and 0.34 in 1996–2007 (Table 2). Construction has caused less volatility in the past 12 years, but it's doubtful this decline will survive the current slowdown in residential building.

Contributions to Volatility in Jobs Growth (Percentage points)
Table 2
1959–83
1984–95
1996–2007
Goods
1.54
.56
.46
Resources
.04
.01
.00
Construction
.25
.23
.12
Manufacturing
1.25
.32
.34
Private services
.88
.89
.86
Trade, transportation and utilities
.40
.40
.29
Information
.10
.04
.10
Financial
.04
.06
.03
Professional and business
.13
.19
.37
Education and health
.07
.01
–.03
Leisure
.12
.13
.08
Other
.03
.06
.01
Government
.11
.07
.01
Total
2.53
1.52
1.33
NOTES: The total is the standard deviation of jobs growth. 2007 data are through the second quarter.
SOURCE: Bureau of Labor Statistics.

Overall, private services' contribution to the economy's volatility hasn't changed much. Within services, however, we see a marked tendency for the volatility from the professional and business services sector to rise over the three periods—from 0.13 percentage points to 0.19 points to 0.37 points. The contribution from trade, transportation and utilities, on the other hand, has declined.

What's going on in manufacturing and professional and business services, the two sectors with the most notable change in their contributions to overall volatility?

Part of the story in manufacturing is foreign competition and productivity-enhancing technologies, which have combined to reduce the sector's share of total employment from 25 percent to 17 percent to 12 percent (Chart 4).

Chart 4: manufacturing much less important as source of jobs growth volatility

The standard deviation of manufacturing's volatility growth rate is generally lower now, too. It fell sharply from 5.4 percentage points in 1959–83 to 2.2 points in 1984–95, before rising slightly—to 3 points—over the past 12 years. This lower jobs growth volatility probably reflects the more stable growth in investment and consumer goods expenditures we've already discussed.

Finally, it's interesting that the correlation between total and manufacturing jobs growth has changed so little over the years, fluctuating from 0.95 to 0.86 to 0.91. Perhaps more flexible labor market practices have offset the weaker links between investment expenditures and GDP and between consumer goods expenditures and GDP.

Manufacturing has traditionally been a source of economic instability, but volatility from a segment of the usually stable services sector may be something of a surprise. Professional and business services' increasing contribution to overall volatility has been driven mainly by two factors: the sector's growing relative size—its share of total jobs has gone from 8 to 10 to over 12 percent—and rising internal volatility—the standard deviation of its growth is up from 1.9 to 2.3 to 3.2 percentage points (Chart 5). The sector's correlation with aggregate jobs growth has held fairly steady.

Chart 5: professional and business services more important source of jobs growth volatility

The expansion of professional and business services has been well documented. This sector includes business managers and knowledge-based employees like lawyers, accountants and computer-system designers, whose jobs are in increasing demand and relatively difficult to send overseas. The sector's rising volatility reflects the high-tech boom and bust of the late 1990s and early 2000s. The 2001 downturn was widely considered a white-collar recession. Unfortunately, the detailed subsector data we need to be able to say more are simply not available for before 1990.

Factoring in all these changes, which were the most important sources of jobs growth variation before the Great Moderation and which are the most important now? Between 1959 and 1983, manufacturing; trade, transportation and utilities; and construction—in that order—were the main drivers of aggregate jobs growth fluctuations. Today, the big three are professional and business services; manufacturing; and trade, transportation and utilities. Given that service-sector developments increasingly drive the U.S. economy today, it's no surprise that two of the three most important sectors to monitor fall into the services category.[6]

Summary and Conclusions GDP and jobs growth became more stable about 24 years ago. Most of the decline in output growth volatility is attributable to smaller swings in investment and consumer durables purchases, swings that are also less synchronized with fluctuations in the overall economy. The reduction in jobs growth volatility is due almost entirely to a shrunken and less variable manufacturing sector.

Changes in GDP and jobs growth volatility since 1984 have been relatively modest. Beneath the surface, however, sector contributions have shifted. Consumer spending—especially on durable goods—accounts for an ever-smaller fraction of short-run variability in GDP growth. On the other hand, net exports have become less of a stabilizing influence.

Two decades ago, keeping tabs on shifts in investment spending and consumer durables purchases was crucial for understanding swings in GDP growth. Tracking shifts in investment spending remains critical, but changes in household spending on nondurable goods are now more important than movements in consumer durables. Meanwhile, the fraction of jobs growth volatility attributable to firms in professional and business services has risen to the point where this sector has become the largest contributor to short-run swings in aggregate jobs growth.

While the underlying causes of the economy's increased stability remain the subject of debate, the stability's persistence suggests that it's unlikely to be entirely the result of good luck. Improved monetary policy may well have played a role, but the timing of the volatility reduction and its sectoral composition also suggest other factors have been at work. They include improved inventory management, changes in the financial system that have made it easier for households to smooth out their spending over time, and the elimination of ceilings on bank deposit interest rates, which has helped reduce the construction sector's cyclicality.

Notes

The authors thank Christine Rowlette and Jessica Renier for research assistance.

  1. Among the earliest articles documenting the reduction in GDP volatility are "Has the U.S. Economy Become More Stable? A Bayesian Approach Based on a Markov-Switching Model of the Business Cycle," by Chang-Jin Kim and Charles Nelson, Review of Economics and Statistics, vol. 81, November 1999, pp. 608–16; "Output Fluctuations in the United States: What Has Changed Since the Early 1980's?" by Margaret M. McConnell and Gabriel Perez- Quiros, American Economic Review, vol. 90, December 2000, pp. 1464–76; and "The Long and Large Decline in U.S. Output Volatility," by Olivier Blanchard and John Simon, Brookings Papers on Economic Activity, no. 1, 2001, pp. 135–64. (Blanchard and Simon see the 1984 volatility reduction as part of a longer-term trend.) For evidence on jobs growth volatility, see "The Declining Volatility of U.S. Employment: Was Arthur Burns Right?" by M. V. Cacdac Warnock and Francis E. Warnock, Federal Reserve Board of Governors, International Finance Discussion Paper no. 677, August 2000. Inflation has been lower and more stable, too. However, we focus on real activity.
  2. Good summaries of the Great Moderation literature include "The Great Moderation," a speech by Federal Reserve Chairman Ben S. Bernanke at the meetings of the Eastern Economic Association, Feb. 20, 2004, and "Has the Business Cycle Changed? Evidence and Explanations," by James H. Stock and Mark W. Watson, a paper presented at the Federal Reserve Bank of Kansas City symposium "Monetary Policy and Uncertainty," Jackson Hole, Wyo., Aug. 28–30, 2003. Also, see "On the Causes of the Increased Stability of the U.S. Economy," by James A. Kahn, Margaret M. McConnell and Gabriel Perez-Quiros, Federal Reserve Bank of New York Economic Policy Review, May 2002, pp. 183–202; "New Economy, New Recession?" by Evan F. Koenig, Thomas F. Siems and Mark A. Wynne, Federal Reserve Bank of Dallas Southwest Economy, March/April 2002, pp. 11–16; and "Has Monetary Policy Become More Effective?" by Jean Boivin and Marc P. Giannoni, Review of Economics and Statistics, vol. 88, August 2006, pp. 445–62.
  3. Suppose that the random variable X is the weighted sum of n other random variables, Xi, for i = 1, 2, ...n: X = ΣαiXi, where the weights, αi, are fixed. From the definition of the correlation coefficient, ρXXi , we know that Cov(X, Xi ) = ρXXi σX σXi , where σX and σXi are the standard deviations of X and Xi , respectively. Hence, σ²X = Cov(X, Σαi Xi ) = Σαi Cov(X, Xi ) = Σαi ρXXi σX σXi , and σX = Σαi ρXXi σXi. In practice, there is often small period-to-period variation in the αi. Consequently, this formula is only approximately valid.
  4. The standard deviation of the four-quarter change in real oil prices was 36.3 percentage points over the 24 years from 1960 through 1983, 22.7 points over 1984–95 and 32.7 points over 1996–2007. Looking only at the standard deviation of oil price increases (some claim increases have a much bigger economic impact than decreases), the standard deviations are 52.5, 15.1 and 25.9 points over the three periods.
  5. An alternative ranking, based solely on correlations between sector and GDP growth, has consumer durables expenditures, nonresidential fixed investment and inventory investment in a virtual dead heat over 1959–83, with correlations of 0.66, 0.65 and 0.64. In today's economy, the top-ranking sectors by this criterion are nonresidential investment (0.56), inventory investment (0.46) and consumer expenditures on nondurable goods (0.46).
  6. A ranking based entirely on the correlation between sector and aggregate jobs growth puts manufacturing in first place over 1959–83, with a correlation of 0.95, followed by the professional and business services and trade, transportation and utilities sectors in a virtual tie, with correlations of 0.92 and 0.91, respectively. In today's economy, the tables are turned. Professional and business services and trade, transportation and utilities both have correlation coefficients of 0.95, while manufacturing has slipped to third, with a correlation coefficient of 0.91.

links for 2007-09-28