Computable general equilibrium

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Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. A model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations.

The model equations tend to be neo-classical in spirit, often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:

1. non-market clearing, especially for labour (unemployment) or for commodities (inventories)
2. imperfect competition (eg, monopoly pricing)
3. demands not influenced by price (eg, government demands)
4. a range of taxes
5. externalities, such as pollution

A CGE model database consists of:

1. tables of transaction values, showing, for example, the value of coal used by the iron industry. Usually the database is presented as an input-output table or as a social accounting matrix. In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household.
2. elasticities: dimensionless parameters that capture behavioural response. For example, export demand elasticities specify by how much export volumes might fall if export prices went up.

CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands.

CGE models derive too from the models for planning the economies of poorer countries constructed (usually by a foreign expert) from 1960 onwards. Compared to the Leontief model, development planning models focussed more on constraints or shortages -- of skilled labour, capital, or foreign exchange.

CGE modelling of richer economies descends from Leif Johansen's 1960 ^[1] MSG model of Norway, and the model developed by the Cambridge Growth Project in the UK. Both models were pragmatic in flavour, and were dynamic (traced variables through time). The Australian MONASH model ^[2] is a modern representative of this class.

CGE models are useful whenever we wish to estimate the effect of changes in one part of the economy upon the rest. For example, a tax on flour might affect bread prices, the CPI, and hence perhaps wages and employment. They have been used widely to analyse trade policy. More recently, CGE has been a popular way to estimate the economic effects of measures to reduce greenhouse gas emissions.

CGE models always contain more variables than equations -- so some variables must be set outside the model. These variables are termed exogenous; the remainder, determined by the model, are called endogenous. The choice of which variables are to be exogenous is called the model closure, and may give rise to controversy. For example, some modellers hold employment and the trade balance fixed; others allow these to vary. Variables defining technology, consumer tastes, and government instruments (such as tax rates) are usually exogenous.

Today there are many CGE models of different countries. One of the most well-known CGE models is global: the GTAP ^[3] model of world trade.

CGE models are useful to model the economies of countries for which time series data are scarce or not relevant (perhaps because of disturbances such as regime changes). Here, strong, reasonable, assumptions embedded in the model must replace historical evidence. Thus developing economies are often analysed using CGE models, such as those based on the IFPR template model ^[4].

CGE models are also referred to as AGE (applied general equilibrium) models.

[edit] References

1. ^ Johansen, Leif (1960). A Multi-Sectoral Study of Economic Growth, North-Holland (2nd enlarged edition 1974).
2. ^ Dixon, Peter and Maureen Rimmer (2002). Dynamic General Equilibrium Modelling for Forecasting and Policy: a Practical Guide and Documentation of MONASH, North Holland.
3. ^ Hertel, Tom (ed.) (1997). Global Trade Analysis: Modeling and Applications, Cambridge University Press.
4. ^ Löfgren, Hans, Rebecca Lee Harris and Sherman Robinson (2002). A standard Computable General Equilibrium (CGE) in GAMS, Microcomputers in Policy Research, vol.5, International Food Policy Research Institute. [1]

[edit] Further reading

• Adelman, Irma and Sherman Robinson (1978). Income Distribution Policy in Developing Countries: A Case Study of Korea, Stanford University Press
• Dervis, Kemal, Jaime de Melo and Sherman Robinson (1982). General Equilibrium Models for Development Policy. Cambridge University Press.
• Dixon, Peter, Brian Parmenter, John Sutton and Dave Vincent (1982). ORANI: A multisectoral model of the Australian Economy, North-Holland.
• Dixon, Peter, Brian Parmenter and Alan Powell (1992). Notes and Problems in Applied General Equilibrium Economics, North Holland.
• Ginsburgh, Victor and Michiel Keyzer (1997). The Structure of Applied General Equilibrium Models, MIT Press.
• Piermartini, Roberta and Robert Teh (2005). Demystifying Modelling Methods for Trade Policy, Discussion Paper No. 10, World Trade Organization, Geneva. [2]
• Shoven, John and John Whalley (1984). Applied General-Equilibrium Models of Taxation and International Trade: An Introduction and Survey. Journal of Economic Literature, vol.22(3) 1007-51
• Shoven, John and John Whalley (1992). Applying General Equilibrium, Cambridge University Press.

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