RDX. RDX2, RDXF, SAM, QPM, ToTEM, LENS….are names of economic models used by Bank of Canada!

While reading this speech by Stephen Poloz chief of Bank of Canada, for a moment one thinks he/she is reading some scifi stuff. But such has been the state of economic modelling.

Infact the speaker starts with comparing economic forecasting to astronomy:

The Alberta School of Business sits a couple of hundred metres east of the Centennial Centre for Interdisciplinary Science, which houses a number of telescopes. When you look at a star through a telescope, you see it not as it exists today, but as it existed years in the past, when its light started heading toward Earth. In that sense, a telescope is something like a time machine.

If only those telescopes could do the reverse and see into the future! Economic forecasting and policy making would be a snap. But since we do not have a machine that lets us see the future, we have to make do with the next best thing: the economic model.

Having said that, it is one thing to build complex economic models and completely another to explain them. Dr. Poloz does a great job of explaining evolution of economic modelling at the central bank and how these names for these models have come about.

The key issue in building economic models is the trade-off that exists between forecasting ability and theoretical rigour. Forecasting models focus primarily on capturing empirical regularities. They work well when the economy and the shocks that it faces do not change much over time. In contrast, theoretical models built for policy analysis are based on a specific interpretation of how the economy functions. Their specifications may hold true on average, but not for every data point. So models with a strong theoretical base tend to underperform empirical models in normal times. However, they can be very useful in explaining behaviour when large shocks cause data-based models to break down.

The two types of models have tended to be complementary, but that has never stopped economists from pursuing the holy grail of a single model that combines strong theoretical foundations with good empirical performance. Over time, advances in computing capability have made it possible to build more realistic behavioural assumptions into models, improving this trade-off. However, the history of model development at the Bank of Canada reflects both this quest for synthesis as well as the evolving needs of policy-makers. Each new model has drawn on the strengths of its predecessors while addressing their shortcomings. And throughout this history, advances in both economic theory and computer technology have played an important enabling role.

The Bank began modelling in the 1960s, when staff and visiting academics built RDX—which stood for the Research Department Experimental model. The development of the mainframe computer was essential to this work, but not every institution had one. One academic involved in those early efforts at the Bank, John Helliwell of the University of British Columbia, tells of sending boxes of punch cards by bus to a computing centre at the Université de Montréal and of inputting data by modem to a computer in Utah.

Early models used by most central banks were based on Keynesian theory, with the demand side of the economy driving growth. However, the inflationary experience of the late 1960s showed the importance of modelling the supply side, which led to the successor model, RDX2. But after the oil price shock of 1973–74, the Bank wanted to use its model to examine alternative policies. The Bank actually began targeting the money supply as a means of reducing inflation and anchoring inflation expectations in 1975, but RDX2 did not have the ability to compare alternative policy paths.

This led to the development of RDXF, with “F” denoting “forecasting.” This version of RDX2 was more amenable to policy analysis. Acquisition of an in-house mainframe computer greatly facilitated this work. This is the model that was being used for quarterly projections when I arrived at the Bank in 1981.

Supebly told especially the trade off between theory and empirics. Much better than several papers on economic models can tell you. He explains how BoC has responded to changes in thinking on economic models. The journey from a basic macro model RDX to the DSGE based ToTEM model is nicely told.

In the end he says models are fine but we should not get carried away by their powers:

And while our current models continue to perform well, recent experience is pointing to some shortcomings that we need to address. Given how long it can take to develop a new model, investing in the next generation of models is one of the Bank’s top priorities, and I want it to be a top priority for the economics profession as well. Better tools will mean a more stable and predictable rate of inflation, and an even better environment for economic decision making.

It is an exciting time for economics and monetary policy. I can hardly wait to see what comes next. But economists have a tendency to get overly excited about their own issues, so let me leave you with an analogy to help you keep this in perspective.

Today’s macroeconomic models are as different from those of the 1970s as the latest Star Wars film, Rogue One, is from the first of the original trilogy, A New Hope, released in 1977. No matter which film you prefer, it is clear that the tools and the technology available to the director have evolved dramatically. The state of the art today is light years ahead of what was state of the art 40 years ago. But ultimately, storytelling remains what is important. That has not changed.

Our economic models will continue to evolve, becoming better and more sophisticated tools. But it will always be up to central bankers to use these tools, as well as their judgment, to conduct monetary policy, achieve their targets and offer a compelling narrative that everyone can understand.

This blog does not really think much about these macro models as they work fine till things are fine. But then if things are fine, why need a detailed model any whichways?

However, it is always nice to know about the various models and how central banks keep creating hype around their wizardry…


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