“Trapped in the ‘Dark Corners'”?: Thoughts on Olivier Blanchard’s “Where Danger Lurks”: The Honest Broker for the Week of September 12, 2014

Olivier Blanchard, inveighing against “ergodicity” and “linearity” as assumptions, sounds like some post-Keynesian from the 1980s. They were right then. He is right now:

Olivier Blanchard: Where Danger Lurks: “One has to go back to the so-called rational expectations revolution…

…What was new was the development of techniques to solve models under the assumption that people and firms did the best they could in assessing the future. (A glimpse into why this was technically hard: current decisions by people and firms depend on their whole expected future. But their whole expected future itself depends in part on current decisions.) These techniques… made sense only… [if] economic fluctuations were regular enough so that, by looking at the past, people and firms (and the econometricians)… could understand their nature and form expectations… and simple enough so that small shocks had small effects…. Thinking about macroeconomics was largely shaped by those assumptions….

The state of the… economic world provided little impetus for… question[ing]…. That small shocks could sometimes have large effects and, as a result, that things could turn really bad, was not completely ignored…. But such an outcome was thought to be a thing of the past that would not happen again, or at least not in advanced economies thanks to their sound economic policies…

That we will assume linearity and ergodicity as convenient to build models we can solve is a not unreasonable modeling strategy to carry you forward.

What is unreasonable is to presume that the place where that modeling strategy stops tells you about the world. Yet that is what a great many economists have done for two generations. Blanchard sees these modeling assumptions as one factor supporting the “Great Moderation” conclusions that:

bank runs… [were of little concern because] the introduction of bank deposit insurance had largely eliminated the problem…. Central banks could quickly provide liquidity…. Sudden stops—episodes when capital flows to a country dry up and all investors try to get out at once—could not be ignored either…. But they were thought to be an issue for emerging markets [only]…

and not for developed economies, in which central banks could print as much of the safe and liquid asset of hard-currency cash as the sudden stoppers desired. Thus, during the “Great Moderation”:

issues of liquidity… were not seen as central…. The probability that central banks would want to decrease nominal interest rates below zero and be unable to do so… was seen as very small…. In short, the notion that small shocks could have large adverse effects, or could result in long and persistent slumps, was not perceived as a major issue. We all knew that there were “dark corners”…. But we thought we were far away from those corners…. Japan sat unhappily in that picture…. But its situation was often interpreted as the result of misguided policies….

As I look back, it still seems to me that in some sense this train of thought ought to be correct.

Regulators understood the moral hazard created by deposit insurance. They also understood the other two moral hazard points of vulnerability: limited liability at the corporate level, and limited liability at the individual level created by richly-funded options-based compensation schemes. From that starting point it ought to have been straightforward to guard against systemic risk. Moreover, even should systemic risk not be properly guarded against, and even should it have macroeconomic consequences, policymakers were far from helpless. Fiscal Policy. Standard monetary policy. Non-standard monetary policy. Banking policy–both to recapitalize the banks and restart the credit channel and via loan guarantees to support a much larger volume of investment spending with the limited risk-bearing capacity the impaired credit channel could mobilize.

With prudent surveillance and proper attention to the hot-money funding sources of the shadow banks, appropriate regulation would have kept us from visiting a “dark corner” in the first place. With appropriate–expansionary–standard and non-standard monetary policy, fiscal policy, and banking-sector lender-of-last-resort and loan-resolution deleveraging and -guarantee policy, we would have quickly exited the “dark corner”. We did not.

Blanchard says:

The main lesson of the crisis is that we were much closer to those dark corners than we thought–and the corners were even darker than we had thought too…. In this environment, economic policy–especially monetary policy–has taken on an element of black magic….

Monetary policy does indeed have an element of black magic to it at the zero lower bound. But fiscal policy–at least for sovereigns possessing exorbitant privilege–does not: one borrows money and buys stuff, and if that causes expected currency depreciation and rising interest rates then monetary-policy loses its black-magic aspect. And loan-resolution deleveraging and loan-guarantee policies to fix and support an impaired credit channel remain available as well.

The most curious question is why these policy levers were not used: who would have thought back in 2007 that the net policy response to the biggest demand shock in the United States since at least the Great Depression would be to cut government spending as a share of GDP, leave housing finance in benign neglect, and keep monetary policy at a gauge that would lead to a 2014 PCE price level 4% lower than had been firmly anticipated back in 2007?

Blanchard says absolutely nothing about this puzzle, and leaves untouched the roles of the economic research, economic policy analysis, and economic policymaking communities in this failure of response.

What does he say? This: He calls for more aggressive prudential regulation and higher capital requirements:

The crisis has one obvious policy implication: Authorities should make it one of the major objectives of policy—macroeconomic, financial regulatory, or macroprudential—to stay further away from the dark corners. We are still too close…. If the financial system had been less opaque, if capital ratios had been higher, there might still have been a housing bust in the United States in 2007–08. But the effects would have been limited…. The reality of financial regulation is that new rules open new avenues for regulatory arbitrage…. Staying away from dark corners will require continuous effort, not one-shot regulation….

And he calls for not the 5%/year inflation target that Larry Summers and I mused about back in 1992 but for a 4%/year inflation target:

If nominal rates had been higher before the crisis, monetary policy’s margin to maneuver would have been larger. If inflation and nominal interest rates had been, say, 2 percentage points higher before the crisis, central banks would have been able to decrease real interest rates by 2 more percentage points before hitting the zero lower bound on nominal interest rates. These additional 2 percentage points are not negligible….

And he calls for an opening up of the economic-research community:

Turning from policy to research, the message should be to let a hundred flowers bloom…. But this answer skirts a harder question: How should we modify our benchmark models—the so-called dynamic stochastic general equilibrium (DSGE) models that we use, for example, at the IMF to think about alternative scenarios and to quantify the effects of policy decisions? The easy and uncontroversial part of the answer is that the DSGE models should be expanded to better recognize the role of the financial system—and this is happening. But should these models be able to describe how the economy behaves in the dark corners?

And then comes a turn in the argument I simply do not understand:

Let me offer a pragmatic answer. If macroeconomic policy and financial regulation are set in such a way as to maintain a healthy distance from dark corners, then our models that portray normal times may still be largely appropriate…

But… but… but… Macroeconomic policy and financial regulation are not set in such a way as to maintain a healthy distance from dark corners. We are still in a dark corner now. There is no sign of the 4% per year inflation target, the commitments to do what it takes via quantitative easing and rate guidance to attain it, or a fiscal policy that recognizes how the rules of the game are different for reserve currency printing sovereigns when r < n+g. Thus not only are we still in a dark corner, but there is every reason to believe that should we get out the sub-2% per year effective inflation targets of North Atlantic central banks and the inappropriate rhetoric and groupthink surrounding fiscal policy makes it highly likely that we will soon get back into yet another dark corner. Blanchard’s pragmatic answer is thus the most unpragmatic thing imaginable: the “if” test fails, and so the “then” part of the argument seems to me to be simply inoperative. Perhaps on another planet in which North Atlantic central banks and governments aggressively pursued 6% per year nominal GDP growth targets Blanchard’s answer would be “pragmatic”. But we are not on that planet, are we?

Moreover, even were we on Planet Pragmatic, it still seems to be wrong. Using current or any visible future DSGE models for forecasting and mainstream scenario planning makes no sense: the DSGE framework imposes restrictions on the allowable emergent properties of the aggregate time series that are routinely rejected at whatever level of frequentist statistical confidence that one cares to specify. The right road is that of Christopher Sims: that of forecasting and scenario planning using relatively instructured time-series methods that use rather than ignore the correlations in the recent historical data. And for policy evaluation? One should take the historical correlations and argue why reverse-causation and errors-in-variables lead them to underestimate or overestimate policy effects, and possibly get it right. One should not impose a structural DSGE model that identifies the effects of policies but certainly gets it wrong. Sims won that argument. Why do so few people recognize his victory?

Blanchard continues:

Another class of economic models, aimed at measuring systemic risk, can be used to give warning signals that we are getting too close to dark corners, and that steps must be taken to reduce risk and increase distance. Trying to create a model that integrates normal times and systemic risks may be beyond the profession’s conceptual and technical reach at this stage…

For the second task, the question is: whose models of tail risk based on what traditions get to count in the tail risks discussion?

And missing is the third task: understanding what Paul Krugman calls the “Dark Age of macroeconomics”, that jahiliyyah that descended on so much of the economic research, economic policy analysis, and economic policymaking communities starting in the fall of 2007, and in which the center of gravity of our economic policymakers still dwell.