I worry about the predictive accuracy of many common growth models in the current economic circumstances. Questions about their performance are important, as their predictions are useful in helping countries to adopt policies and change their characteristics in order to promote rising incomes, and are also helpful in anticipating the global changes that a country's enrichment brings. Different approaches to growth models are an active area of economic research.
The problem with many growth models is that their foundations are prefabricated. A major strand of analysis assumes that changes in an economy's output is determined solely by changes in productive factors, and those factors obey rigid rules of change themselves. Another major strand is exclusively empirical, which allows the inclusion of a very large number of determinant variables, but ignores how those determinants are themselves determined or how they influence growth. Sophisticated estimation methods allow the models to produce reasonable fits to past data despite the relative ignorance of fundamentals.
It seems fairly clear that if a major change occurs in the underlying interaction between growth and its determinants, then the models may not be such a good fit to future data. In particular, if a major structural change occurs which has no precedent in past data, the model predictions may be weak. This vulnerability of models without foundations has been observed in the past, when high inflation and unemployment coincided in the 1970s leading to a rejection of a hypothesised trade-off between them in all circumstances. Consequently, a major break in the analytical tradition occurred with a shift towards macromodels with detailed foundations. The modelling approach continues today, although it has not been applied so extensively to growth models, with exceptions who have also attempted empirical estimation. The approach is brave, in view of the uncertainty and probable early failure. One recent paper takes several macroeconomic equations derived from microfoundations and estimates them as a separate system away from the rest of the derived equations.
The micro to macro approach might seem to be the best possible, but is far more demanding in the modelling, and it is uncertain whether the resulting analysis will contribute more than the cruder macroeconomic approach. The economy, after all, cannot stand still while economists find a perfect model to describe it. Critics in the 1960s were probably correct in many of their analytical qualifications of the neo-classical synthesis school of economics, but the neo-classical synthesis works reasonably well, can easily be understood, and became dominant. Interestingly, many of the universities which were the targets of criticism back then have pioneered the more sophisticated microfounded models of today, while other universities have championed the cruder macromodels, if not inventing them.
The current economic turmoil, and the global imbalances which produced it, seem to have no precedent in the last fifty years of data which is generally used for estimating growth models. It thus provides a stress test for macromodels to see whether they are up to the job, or whether they will have to be jettisoned in favour of microfounded growth models.