In an interesting and highly readable recent Bloomberg blogpost Noah Smith distinguishes 4 kinds of macro: coffee-house macro, financial macro, academic macro and Fed macro. I like to add ’empirical macro’, i.e. the National Accounts, but that’s for another occasion as I just ran into a blogpost by Olivier Blanchard and a speech by Mario Draghi which nicely illustrate the differences between two of Noah’s macro’s, i.e. academic macro and what I want to rename ‘central bank’ macro (sorry, Noah!). Academic macro is defined by Noah as: “This traditionally involves professors making toy models of the economy — since the early ’80s, these have almost exclusively been DSGE models (if you must ask, DSGE stands for dynamic stochastic general equilibrium). Though academics soberly insist that the models describe the deep structure of the economy, based on the behavior of individual consumers and businesses, most people outside the discipline who take one look at these models immediately think they’re kind of a joke. They contain so many unrealistic assumptions that they probably have little chance of capturing reality. Their forecasting performance is abysmal. Some of their core elements are clearly broken. Any rigorous statistical tests tend to reject these models instantly, because they always include a hefty dose of fantasy.
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In an interesting and highly readable recent Bloomberg blogpost Noah Smith distinguishes 4 kinds of macro: coffee-house macro, financial macro, academic macro and Fed macro. I like to add ’empirical macro’, i.e. the National Accounts, but that’s for another occasion as I just ran into a blogpost by Olivier Blanchard and a speech by Mario Draghi which nicely illustrate the differences between two of Noah’s macro’s, i.e. academic macro and what I want to rename ‘central bank’ macro (sorry, Noah!).
Academic macro is defined by Noah as:
“This traditionally involves professors making toy models of the economy — since the early ’80s, these have almost exclusively been DSGE models (if you must ask, DSGE stands for dynamic stochastic general equilibrium). Though academics soberly insist that the models describe the deep structure of the economy, based on the behavior of individual consumers and businesses, most people outside the discipline who take one look at these models immediately think they’re kind of a joke. They contain so many unrealistic assumptions that they probably have little chance of capturing reality. Their forecasting performance is abysmal. Some of their core elements are clearly broken. Any rigorous statistical tests tend to reject these models instantly, because they always include a hefty dose of fantasy.”
And Central Bank macro as:
“The Federal Reserve uses an eclectic approach, involving both data and models. Sometimes the models are of the DSGE type, sometimes not. Fed macro involves taking data from many different sources, instead of the few familiar numbers like unemployment and inflation, and analyzing the information in a bunch of different ways. And it inevitably contains a hefty dose of judgment, because the Fed is responsible for making policy.”
Comes in Olivier Blanchard, a former chief economist of the IMF and academic who struggles with the question:”How should we teach macroeconomics to undergraduates after the crisis?”. In a blogpost in which he in facts scuttles a core element of the DSGE models, i.e. ‘General Equilibrium’, he states about financial markets:
“The teaching solution, in my view, is to introduce two interest rates, the policy rate set by the central bank in the LM equation and the rate at which people and firms can borrow, which enters the IS equation, and then to discuss how the financial system determines the spread between the two. I see this as the required extension of the traditional IS-LM model. A simple model of banks showing the role of capital, on the one hand, and the role of liquidity, on the other, can do the trick. Many of the issues that dominated the crisis, from losses and low capital to liquidity runs can be discussed and integrated into the IS-LM model. With this extension, one can show both the effects of shocks on the financial system and the way in which the financial system modifies the effects of other shocks on the economy.
Hmmm… not much about the causes of the crisis (like securitized sub-prime mortgages). But it is nevertheless interesting to compare this idea of two interest rates (the central bank rate for banks, the higher bank rate for ordinary ‘agents’) with the statements of Mario Draghi
“…in reality, there is not just one interest rate which determines saving and investment in the whole economy. There is in fact a constellation of rates, which apply to different maturities, to different types of financial instruments, to different borrowers and lenders. So even without policy rates moving much, it is still possible for the central bank to stimulate the economy by lowering the level of all those interest rates. This can be effective in any circumstances, but particularly so when risk premia have risen due to market fragmentation or unwarranted uncertainties.”
Hmmm… not much about different countries. But indeed: a trade credit is not the same thing as a securitized mortgage or a car loan. Car loans provided by car companies can serve as collateral at the ECB, by the way. Other ‘payables’, to my knowledge, not. And Draghi is right, the ECB can change this, therewith influencing financial markets. So, what should we teach our students? The Blanchard idea that mortgages and trade credits are fundamentally the same thing, or the Draghi idea that there are, seen from a policy angle, differences? Noah Smith clearly has a point.