Posts Tagged Diamond-Dybvig
This is the final part in my series on how the financial crisis is relevant for economics (here are parts 1, 2, 3, 4, 5 & 6). Each part explores an argument economists have made against the charge that the crisis exposed fundamental failings of their discipline, with the quality of the arguments increasing as the series goes on. This post discusses probably the strongest claim that economists can make about the crisis: they do understand it, and any previous failures were simply due to inattention or misapplication, rather than fundamental problems with the theory itself.
Argument #7: “Economists had the tools in place, but we overspecialised and systemic problems caught us off guard.”
Raghuram Rajan was probably the first to take this sort of line, arguing that overspecialisation prevented economists from using the tools they had to foresee and deal with the crisis. But while Rajan’s piece also made a number of other criticisms of economics, over time the discipline seems to have reasserted this argument more strongly: not too long ago, Paul Krugman argued that although “few economists saw the crisis coming…basic textbook macroeconomics has performed very well”. Similarly, Tim Harford claimed at an INET conference last year that the tools necessary to understand the crisis already existed in mainstream economics, and the problem was simply one of knowing when and how to use them. He compared financial crises to engineering disasters, which were understandable using current knowledge but happened nonetheless, due to negligence or oversight on the part of the engineers.
So how true is this claim? Certainly, a number of economic models exist for understanding things like panics, liquidity problems and moral hazard. The most well known of these are the Diamond-Dybvig (DD) model of bank runs – which shows what happens when banks have liquid liabilities (such as demand deposits) which must be available at any time, but have illiquid assets (such as loans) which are not fully convertible to cash on demand – and the Akerlof-Romer (AR) model of financial ‘looting’, which shows that deposit guarantees may create moral hazard as investors gamble other peoples’ money. If you combine tools like these, which help us understand the financial sector, with tools like IS/LM, which tell us how to escape a downturn once it happens, in theory you have a pretty solid set of tools for dealing with the recent crisis.
The first objection I have to these models is that many of their insights could be considered trivial, or at least common sense. The DD model came to the conclusion that deposit insurance might be helpful way to prevent bank runs, which is hardly a revelation considering it came 50 years after FDR and the general public figured out the same thing. The AR model came to the conclusion that deposit insurance and limited liability might create perverse incentives as banks gamble ‘other peoples money’, which again must have been obvious to the policymakers who put Glass-Steagal and other financial regulations in place. Perhaps this point is a little harsh, and I don’t want to overstate it: on the whole, these papers are asking important questions, and in the case of AR they answer them well. Nevertheless, there’s no point in economic theory if it can’t tell us things we didn’t already know. Even the idea that central banks should provide emergency liquidity to banks in trouble is quite obvious, and it predates modern economic theory by a good while.
However, this is not the most important point. The issue I have with these models is that in many of them everything interesting happens outside the model. In Krugman’s favoured IS/LM, a ‘crisis’ is represented by a simple shift in the IS curve, which in English means that a decline in production is cause by…a decline in production. Where this decline came from is presumably a matter for outside the model. Even the most sophisticated macroeconomic models often follow a similar tack, merely describing what happens when the economy suffers from a shock, without exploring possible causes for the shock. Likewise, the DD model suggests bank runs happen because everyone panics, but what causes these panics is not explored: it is assumed depositors’ expectations are exogenous, whether fixed or following a stochastic (random) pattern. Yet studies such as Mishkin (1991) find that bank runs generally follow periods of stress elsewhere in the economy, a fact which DD simply cannot capture.
Economic models are narrowly focused like this because they are generally designed to answer straightforward questions about causality: does the minimum wage cause unemployment; does expansionary fiscal policy cause growth; does a mismatch between illiquid assets and liquid liabilities cause bank runs. But the crisis was an endogenously generated process in which different aspects of the economy – the housing market, the financial sector, government policy – combined to create something bigger than the sum of its parts, and in which it is not possible to isolate a single cause. Consider: the collapse of Lehman Brothers may have triggered the worst of the crisis, but was it really to blame? The economy was already in a fragile place due to systemic trends that can’t necessarily be traced to a single law, institution or actor. Just like the murder of Franz Ferdinand in World War 1, we have to look beyond the immediate and focus on the general if we truly want to understand what happened.
To sum up, the economists above want to argue that they are only culpable insofar as they overspecialised and failed to focus on the right areas in this particular instance. However, the reason for this was not just because of personal myopia; it’s because their chosen methodology means they lack the tools to do so. A model of one aspect of the economy which takes the effect of other areas as exogenous will fail to detect potential positive feedback loops and emergent properties. A model which takes the crisis itself as an exogenous ‘shock’ is even worse, and in many ways is hardly a model of the crisis at all, since it offers no understanding of why crises might happen in the first place. Are there alternatives? I have previously written about how post-Keynesian and Marxist models offer more comprehensive understandings of the financial crisis and antecedent decades; I shan’t repeat myself here. Other promising areas include network theory, evolutionary economics and Agent-Based Modelling. All of these share that they take the system as a whole instead of focusing on isolated mechanics.
I see the crisis in economics as a shock (!!) which hits macroeconomics hard and reverberates throughout the discipline. Regardless of the pleas of some, such events can be seen coming, and they cannot be handwaved away as part of an overall upward trend. And even if individual economists are not in control of policy, key economists have substantial influence, not to mention the theories and ideas in economics as a whole. Recent developments in macroeconomics still leave a lot to be desired, while previously existing tools suffer from similar problems: a lack of holism; a wooden insistence on microfoundations; and attempt to understand everything in terms of simplistic causal links, often relative to a frictionless baseline. Finally, although many areas of economics are not directly indicted by the crisis, many of them share key problems with macroeconomics, and as such the crisis should prompt at least a degree of introspection throughout the discipline.