This month marks the centennial of the birth of mathematician Alan Turing, the “father” of modern computing and artificial intelligence. To celebrate the occasion, we’ll be publishing a series of articles on modelling and economics. In today’s article, Dave Turner, Head of the Macroeconomic Analysis Division in the OECD’s Economics Department, gives a personal view of the models we use here.
Macroeconomics and, more specifically, economic models have come in for widespread criticism for their failure to predict the financial crisis. Informed criticism often focuses on so-called “Dynamic Stochastic General Equilibrium” models (mercifully abbreviated to DSGE models), which had become the dominant approach to macroeconomic modelling in both academic and policy circles. Such models based on assumptions of “efficient markets” and “optimising agents” with “rational expectations”, seemed to rule out the possibility of financial crises by the very nature of their assumptions.
The approach to economic modelling within the OECD is, however, much more eclectic with a large number and wide variety of different models used for different purposes. This can be illustrated by a few examples of the models which are currently used within the Economics Department at the OECD to generate the twice-yearly projections published in the OECD Economic Outlook.
The projections produced for the OECD Economic Outlook place a high weight on the judgment of country specialists rather than relying on numbers mechanically generated by a single econometric model. On the other hand, these country specialists increasingly have the option to compare their projections with what econometrically estimated equations would produce. Additionally, simulations from a conventional large-scale macro model provide further information on the effect of changes since the previous forecasting round n variables including oil and other commodity prices, and fiscal and monetary policy settings. Moreover, importance is attached to ensuring that the set of country projections are globally consistent, in particular that growth in world exports is in line with growth in world imports (so avoiding implicit exports to the Moon) and estimated trade equations often play a role in ensuring this global consistency.
With the onset of financial turmoil, further guidance for the Economic Outlook projections has been provided through the development of financial conditions indices for the major OECD countries. These capture the effect of broadly defined financial conditions on economic activity and include not only standard text-book measures of policy interest rates and exchange rates, but also survey measures of bank lending conditions and interest rate spreads (the difference between government interest rates and the rates at which companies can borrow). The latter, less conventional, components have been crucial in tracking the adverse effects of the financial crisis. In addition to providing input to the main projections, these financial conditions indices have also been used as the basis for constructing upside and downside scenarios in relation to the ongoing financial and sovereign debt crisis.
Other models are used in the Economic Outlook projections to situate the current state of the main OECD economies, by using high frequency data. Thus “Indicator models” use estimated combinations of monthly data on hard indicators, such as industrial production and retail sales, as well as soft indicators such as consumer and business surveys to make forecasts of GDP over the current and following quarter. Even here, treating the model predictions with caution is often warranted, especially, for example, if recent indicators have been affected by unusually unseasonal weather.
At the other extreme of the projection horizon, a model has recently been developed to extend the Economic Outlook projections over a further 50 years. While such projections are inevitably “heroic” and subject to many qualifications, such a long-term horizon is needed to address a number of important policy issues that will only play out over a period of decades. Such issues include the implications for government debt of current high fiscal deficits; the impact of ageing populations on growth and government budgets; the impact of structural policy changes on how economies catch-up with the technological leaders; and the growing importance of China and India in the global economy.
Beyond the Economic Outlook projections, much of the other empirical work undertaken in the OECD Economics Department can be described as using economic models, if “economic models” are defined more loosely to include any quantitative (usually estimated) relationship between economic outcomes and variables which are readily amenable to policy influence. Such models are often characterised by the construction of summary indicators which try to capture and contrast some salient features of member country economies and relate them to policy levers and/or economic outcomes.
Examples of such approaches include quantifying the effect of product market regulation on productivity, tax policy on R&D spending, or the design of pension systems on retirement decisions. Such specialised “models” are usually small, and do not pretend to provide a universal approach to economics or provide answers to questions across many different policy fields.
Moreover, work is ongoing to evaluate the impact of structural policies on macroeconomic performance, an area the OECD has been pioneering and in which it has already contributed significantly to the G20 process. In exploiting its access to a rich cross-country information set made available by its member countries, it is this type of modelling where the OECD is uniquely well placed to play a role in providing policy advice to its member countries, rather than attempting to develop the next generation of all-encompassing whole economy models with a fancy new acronym.