Victoria University Regional Model (VURM)

The Victoria University Regional Model (VURM) is a dynamic multi-regional computable general equilibrium (CGE) model.

You will find a brief overview of VURM on this page. For a detailed description of the model, refer to the Adams, et al (2015) in the references section.

Modelling Australia’s regional economies

VURM is a 'bottom-up' regional CGE model, in that it explicitly models economic activity occurring within each region, with national economic outcomes determined as an aggregation of economic outcomes at the regional level.

Depending on the application, VURM identifies up to eight regions, representing each of Australia’s eight states and territories.

The model carries high levels of industrial and commodity disaggregation, with each industry identified as an individual economic actor within each region.

Regional industries

Neoclassical assumptions govern the behaviour of the model’s economic agents. Each of the representative industries operating within each of the model’s regions is assumed to minimise costs subject to constant-returns-to-scale production technologies and given input prices.

Representative household

A representative utility-maximising household resides in each of the model’s regions. Investors allocate new industry-specific capital to each regional industry on the basis of expected rates of return.

Neoclassical economics

Imperfect substitutability between the imported and domestic sources of supply for each commodity are modelled using the constant elasticity (CES) assumption of Armington. In general, markets are assumed to clear and to be competitive.

Purchaser’s prices differ from basic prices by the value of indirect taxes and margin services.

Taxes and margins can differ across commodity, user, region of source and region of destination.

Foreign demands for each commodity from each region are modelled as inversely related to their foreign currency prices.

Taxation & transfers

The model includes details of the taxing, spending and transfer activities of two levels of government: a regional government operating within each region, and a federal government operating Australia-wide.

Inter-governmental transfer payments and personal transfer payments to households are also modelled.

Dynamics, investment, unemployment, sticky wages & migration

Dynamic equations describe stock-flow relationships, such as those between regional industry capital stocks and regional industry investment levels.

Dynamic adjustment equations allow for the gradual movement of a number of variables towards their long-run values. In this regard, VURM allows region-specific unemployment rates to temporarily depart from baseline values under an assumption of short-run regional wage stickiness. Over time, regional wage adjustment gradually returns region-specific unemployment rates to baseline values.

Similarly, we allow regional per capita real disposable income relativities to temporarily depart from baseline values, under an assumption of stickiness in rates of inter-regional migration. Over time, adjustment of rates of inter-regional migration gradually return inter-regional per capita real disposable income relativities back to baseline.

National outcomes & regional linkages

Regional economic linkages arise from inter-regional trade, factor mobility, the taxing and spending activities of the federal government, and long-run economy-wide employment and balance of trade constraints.

The model also evaluates a full set of national and regional income accounts, and associated deflators.

Computation

The model is solved with the GEMPACK economic modelling software (Harrison and Pearson, 1996).

References

  • Adams, P., J. Dixon and M. Horridge (2015), The Victoria Regional Model (VURM): Technical Documentation, 1.0, CoPS Working Paper No. G-254, Centre of Policy Studies, Victoria University, Melbourne. http://www.copsmodels.com/ftp/workpapr/g-254.pdf.
  • Harrison W.J. and K.R. Pearson (1996), “Computing solutions for large general equilibrium models using GEMPACK”. Computational Economics, Vol. 9, pp. 83–127.