■ Methodological issues
Generally, the Macroeconometric modelling aims at the empirical behavior of an actual economic system.
That kind of models will be regarded as the subsystems of the interlinked equations estimated from time series data using statistical or econometric techniques.
Bardsen et al. ( 2005) states that a conceptual starting point is the idea of general stochastic process that as generated all data that one observes for the economy and this process can be summarized in terms of the joint probability distribution of random observable variabls in the stochastic equation system.
They further assert that, for a modern economy, the complexity of such a system and of the joint probability distribution is evident. Nonetheless, it is always possible to take the high aggregated approach in order to represent the behavior of a few headline variables such as inflation, GDP growth, unemployment in a small scale model.
If those are small enough, the estimation of such econometric moded can be based on the formally established statistical theory (as with low dimensional vector autoregressive models the VARS, where the statistical theory has been extended to co integrated variables.
The operational procedures of Macroeconometric modelling can be summarized below:
♢ Choosing the relavant variables the subsectors of the economy can be analysed (marginalisation).
♢ Distinguishing between the exogenous and endogenous variables the relavant partial models are constructed which will be called as the type A models.
♢ At last, the submodels built are combined in order to obtain model B for the entire economy.
Thank You
To be contd ...
Aditya Pokhrel
MBA, MA Economics, MPA
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