In the continuation of a series of posts about the CGE model, this post will describe its main processes and features. We would like to thank the CGE model followers for their valuable comments on the introductory post, based on which we have made important notes for future work. We hope for further feedback exchange.

How does the CGE model work?

The process of calculating effects in the model depends on a number of inputs: data (input-output tables (IOT), elasticity coefficients), the model itself (in the form of a system of equations and conditions), the choice of exogenous variables, and the choice of shocks.

Figure 1 clearly shows the relationship of these elements in the work of the model. Thus, the process begins with calibration to match the equations and conditions of the model. Before calculating any equilibrium, it is necessary to determine which variables of the model will be exogenous, i.e. independent of it. The choice depends on the purpose of the analysis and expert preferences (for example, the choice between a long-term and short-term scenario).

The basic equilibrium is the first result of the model and describes the state of the economy without any external shocks/policies, but in which all markets are at equilibrium. It is formed on the basis of data on the economy from the IOT and elasticity coefficients (covering the inherent behavior of agents in the country, their reaction to price changes).

After determining the model's shocks, an alternative equilibrium is formed, indicating how hypothetically economic indicators are adjusted in response to an external shock (or shocks).

The results for the analysis of policies and external factors are the incremental effect on the economy or the difference between indicators in the basic equilibrium and in the alternative (C-B in Figure 2).

Features of the Kazakhstan model

Kazakhstan's KAZORANI model covers 68 sectors of the economy and has a regional expansion (at the level of macro indicators).

Among its features, we can note the choice of various exogenous variables, depending on the purpose of the analysis (as was previously noted in the comments).

There may also be several shocks. In other words, it is possible to assess the simultaneous effect of a double shock on the export demand for non–ferrous metals from the Republic of Kazakhstan - both from the price side and from the volume side (which forms two separate shocks).

A convenient function for policy analysis is also grouping sectors by any criteria: locality/tradability, technology, etc. For example, it is possible to highlight the effects of shocks on high-tech manufacturing sectors, the Advanced Manufacturing group, and so on.

In general, despite some methodological assumptions of the model, inherent in most quantitative tools in the economy, its flexibility and ease of use for determining hypothetically approximate scenarios remains a definite advantage.