Dris proposal for national licensing of the electrical occupations

What is a CGE model?

A CGE model is a mathematical model of an economy that is capable of capturing economy-wide impacts and intersectoral reallocation of resources that may result from a shock to the economy. CGE models are generally designed for quantitative analysis of:

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  resource allocation issues
  
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  changes in technical efficiency
  
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  government tax or issues related to expenditure policy
  
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  external events that can be represented as price or activity shocks.
  

The core data of a CGE model is an input–output (I–O) table. An I–O table is a system of accounts that shows, in value terms, the supply and disposal of goods and services within the economy in a particular year. An I–O table captures sales of products to other industries for further processing (intermediate usage), together with sales of products to final users. It also captures the inputs used in an industry’s production, whether they be intermediate or primary inputs (such as labour and capital). The table is balanced such that total of the inputs to each industry is equal to total of the outputs from each industry. Essentially, an I–O table is a snapshot of an economy (whether it is a region, state or country) in a particular year.⁷³ Figure H.24 provides a representation of a CGE model.

Figure H.24: Diagrammatic representation of the core of a CGE model

A CGE model pushes forward the base I–O table through time by utilising a set of equations that capture neoclassical microeconomic theory⁷⁴ to determine behaviour of economic agents when they are faced with changes in key economic variables (especially relative prices). The equations are solved simultaneously, where some variables are determined by the model (endogenous variables) and some are determined outside the model (exogenous variables). The classification of endogenous and exogenous variables is determined by the user based on the set of assumptions derived for the specific modelling exercise.

The CGE model used for this modelling exercise is the Monash Multi-Region Forecasting Model (MMRF). MMRF is a multi-sector CGE model of the Australian economy that encompasses all states and territories. It was developed by the Centre of Policy Studies at Monash University.

CGE modelling exercises are often undertaken alongside cost–benefit analysis because a CGE model can provide economy-wide metrics that cannot otherwise be provided by a cost–benefit analysis. CGE modelling provides a deeper analysis that contributes to the strength of the argument for policy makers. It is a common tool used by the Productivity Commission when undertaking inquiries; in addition, it is used by the Department of the Treasury when assessing policy decision such as the carbon price mechanism.

It is important to recognise key limitations to this modelling when assessing the results. The results are not intended to be definitive forecasts or precise point estimates of key economic indicators resulting from the proposed reforms. Rather, the results of the modelling should be viewed as a projection of economic variables under a series of plausible assumptions that have informed a ‘scenario analysis’.

While the modelling exercise has been informed by the impact analysis results, not all individual costs and benefits have been modelled explicitly in the CGE model. Hence, it is not possible to directly compare the results of the impact analysis with those of the scenario modelled in MMRF (i.e. an increase in efficiency).

The key limitations to this modelling approach include:

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  The model has an inadequate occupation dimension. The model has been run as an efficiency shock to the construction industry, as opposed to targeting the electrical profession directly. This is largely due to the lack of occupational detail in MMRF. In addition this modelling exercise does not allow for movement between occupations.
  
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  While the efficiency gain has been scaled down to account for the proportion of electrical employment for total employment in the construction industry, this approach assumes that the penetration of electrical services into other industries has the same composition as that of the construction industry as a whole.
  

Additional limitations are discussed below.

Time dimension

CGE models can be set up as either ‘comparative static’ or ‘recursive dynamic’, depending on the treatment of time in the modelling exercise. This modelling exercise has been run as comparative static.

While recursive dynamic modelling can account for how the economy changes over time to move from one equilibrium position to another, comparative static modelling presents a static viewpoint, comparing the economy at a point in time to the economy once the impact of the shock has been absorbed.

Due to the comparative static nature of this modelling, there is no allowance for, for example:

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  underlying changes in the economy over time
  
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  the way that the shock might be disaggregated over a number of time periods and how it might play out through the directly affected industry, interrelated industries and the wider economy over time
  
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  a lagged adjustment process in the labour market.
  

Ideally, a recursive dynamic approach to the modelling would be employed to more appropriately address the economy-wide impacts of national occupational licensing restrictions as, for example, a lagged adjustment process in the labour market is fundamental to the movement of the impact through the wider economy.

However, the comparative static results provide a high-level illustrative story of how industry and macroeconomic variables may respond to a change in efficiency as a result of the policy change.

A recursive dynamic exercise would be far more advanced but requires significantly more time to undertake.⁷⁵

The shock to the model