During the Republican tantrum over Obamacare that caused the government shutdown and the threat to default on the debt, economists were asked how these events would affect the economy. Unfortunately, as evidenced by their performance during the Great Recession, real-time analysis of the economy is an area where economists do not do very well.
With a few notable exceptions – Paul Krugman comes to mind – most real-time economics analyses have been performed by private sector economists at places like Macroadvisors, or in government agencies such as the Federal Reserve or the Congressional Budget Office.
Unlike academic economists who have little riding on the outcome, real-time analysis of the economy is essential for the bottom line of many businesses and for effective monetary and fiscal policy decisions. Increasingly, however, academic economists are expected to diagnose, analyze, and provide prescriptions for whatever ails the economy in real-time.
This is a new role for academic economists. Most academic economists are engaged in fundamental theoretical research where the goal is to understand how the economy operates rather than the analysis of particular real world events as they are happening. The theoretical models that economists develop are often subjected to econometric tests involving data from past events, but academic economists do not, for the most part, attempt real-time analysis.
The models are not designed with that goal in mind, and the models and empirical techniques that are best for understanding how the economy works are not the best constructs for real time analysis of economy. Even if the tools and techniques academic economists employ were suited for this task, it can take years from the start of a research project to eventual publication in an academic journal.
But digital technology, the Internet, and blogs are changing what academic economists do. Increasingly, academic economists are engaged in real-time analysis and they cannot wait years or even months for answers. If Lehman is failing and the financial sector is going down with it, if Europe is in trouble, or if default on the debt is likely, we need answers right now.
Providing answers months or years from now, and then publishing the findings in a journal article isn’t much help to policymakers and others who need answers right away. That means the discipline has to adjust from being backward looking with plenty of time to determine causes and cures to a mode where we can offer immediate advice on important monetary and fiscal policy questions.
The financial crisis provides a good example. When the crisis hit, economists reached into their bag of models and tried to find the one that would provide the diagnostic and policy prescriptions we needed. This turned out to be much harder than might have been expected. Our models were not designed to be used in this way.
What data should we look at to make an immediate diagnosis? What tests should we conduct to give us data on what is wrong with the economy? If we aren’t sure what the cause is but immediate action is needed to save the economy from getting very sick, what is the equivalent of using broad-spectrum antibiotics and other drugs to attack unknown problems?
The development of digital technology and blogs puts economists in real-time contact with the public, press, and policymakers, and when there are problems in the economy people come looking for answers. There has been some progress in terms of the willingness of academic economists to take on diagnostic and prescriptive roles in real-time, but what is still missing is serious research on the tools and techniques that are needed to perform this role effectively.
We do not have the diagnostic tools we need to identify bubbles and other economic problems in the economy while they are developing – the ability to provide answers while there is still time to take prescriptive measures is missing – and this is a void within the profession that must be addressed.
The Fed does some of this, of course, and the financial crisis has motivated some academic interest in developing early warning systems that would have helped us to identify and do something about stock, housing, and other bubbles before they inflated to dangerous levels. And the new tools and analytical techniques associated with “big data” are promising for this type of use.
But the research hasn’t gone far enough, and my fear is that as we recover from the recession and the need for real-time analysis declines, academic economists will go back to their old, backward looking ways and forget about the need to develop better tools for real-time analysis. Being so unprepared and unaware when the Great Recession hit and having so little to say once the recession was underway did considerable damage to the reputation of economists. We shouldn’t allow ourselves to make that mistake again.