If we presumed that specification of models require creativity. Then, there are some results from our analysis that are already obvious. for few we deny that presumption does not mean exact and exact does not mean disclosure.
What is the purpose of a macro model? Is it to understand or to forecast? If it is to forecast, you don't need sophisticated model to do so. A simple ARIMA model might do the job. If it is to understand, it can be very sophisticated with hundreds of equations and complicated modelling on micro theory. Unfortunately policy changes, human behavior changes and shocks (internal and external) to the system throw out all the carefully calibrated parameters. We start all over again with each shock, cycle, policy and business cycle, which is different.
@Olat-No, I am not defending macro models but laid out the arguments for big models that have strong statistics and small simple models using an aggregated approach. It used to be a big debate in the economics profession in the 1970s and 1980s. Good topic to revisit the past.
Simple macro models are flexible, that they can provide general explanation for many phenomena. These models live long as they may be used over and over again. In contrast, sophisticated and complicated micro model is not flexible, that it can only provide a deeper and stronger explanation for a specific case. Once it is used, it will be forgotten as we may never find an identical case. That is the way of the parametric models. This is a very interesting discussion indeed.
@ Yudhi, flexibility in the face of collapse theories and poor macro modelling prospects.
Despite all the concerns about models whether big or small, they wont go away. Every year/qtr, the IMF, private think tanks and analysts make forecasts of GDP growth, interest rates, inflation and exchange rates. Policy makers, traders and private businesses depend on them for what is happening for the next 3 months and there is monetary value in these forecasts besides understanding them.
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