Abstract
In this paper, we compare the performance of two leading algorithms now regularly used to solve large forward-looking models. In particular we relate traditional Fair-Taylor ‘extended path’ algorithms to the newer breed of stacked Newton Raphson ones.2 As a testing ground for these solution methods we use the IMF’s world econometric model,MULTIMOD (Mason et a1,1990) which may be considered typical of many current forward-looking large macro-models.3
We thank Ralph Bryant, Don Coletti, Peter Hollinger, Andrew Hughes Hallett, Ben Hunt, Tiff Macklem, Guy Meredith, Susanna Mursula, Steve Symansky, Bob Tetlow, Jakob ToftGard and Jan in’t Veld for helpful comments and for prociding simulation analyses on several models.The usual disclaimer applies.
This is not to suggest that they are the only methods of solving forward-looking models only that they would appear to be the most popular — viable alternatives include Penalty function methods (Holly and Zarrop, 1983) and shooting methods (Lipton et al, 1982)
MULTIMOD is an annual estimated econometric model containing the G7 countries as well as distinct other country blocks. Each country incorporates 53 equations (of which 34 are identities) and for which there are roughly 19 exogenous variables including, principally, monetary target, government expenditure, debt target, oil price and population etc. A full description of MULTIMOD’s properties and simulation characteristics is given in Masson et al (1990) and model vintages in Helliwell et al (1990) and Mason et al (1988).Exercises in cross model comparisons may be found in Bryant et al (1988,1933) and Mitchell et al (1995) ,amongst others. Finally note that for these exercises we use the basic production vintage of the MULTIMOD model — MULTAR. With some exceptions — such as the ERM members’ (cubic) monetary reaction function and the obvious case of price deflators and log-linear functional forms — the model is highly linear and so should, in principle, be relatively straight forward to solve.
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Juillard, M., Laxton, D., McAdam, P., Pioro, H. (1999). Solution Methods and Non-Linear Forward-Looking Models. In: Hallett, A.H., McAdam, P. (eds) Analyses in Macroeconomic Modelling. Advances in Computational Economics, vol 12. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5219-2_1
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