Application of CGE modelling

To apply the CGE theoretical framework to empirical policy experiments, modellers need data that display in a comprehensive way all the interdependencies at play within the economy. For this purpose, they make use of social accounting matrices. The typical steps involved in any applied CGE model are depicted in Figure 3-1.

Figure 3-1. Steps in an applied CGE model

Source: Own illustration

The first two steps (SAM development and model specification) are independent and do not necessarily follow a definite order.

The SAM – step 1 in the diagram – is a framework to organise the data on the structure of an economy and display all fundamental interactions taking place in that economy. It provides the essential data required to operationalise a CGE model. For a CGE application, it may be needed to develop a SAM from scratch. Even when a SAM is available, there is often a need to aggregate or disaggregate some sectors of interest or to update the SAM to a reference year that is more suitable for the analysis. The SAM framework has been presented in Chapter 2 and the construction of a SAM is documented in Chapter 5.

The model formulation – step 2 in the diagram – provides the functional form of the behaviour of each agent in the economy. Most applied CGE models allow intra-industry trade by assuming that goods differ by country of origin, which is known as the Armington assumption. Firms are assumed to maximise profits subject to limited production factors

41 and given a certain technology. Households maximise utility subject to a budget constraint. Only representative households are usually considered, assuming that within each household group, preferences and demand functions are the same. The government’s role in CGE models is limited to collecting taxes and making transfers. Therefore, no behavioural function is associated with the government sector. A deeper look into the structure of a CGE model and its behavioural relationships is provided in Section 3.6. In order to fit the functional specifications of the model with the data, the modeller needs the value of exogenous parameters in addition to the value transactions contained in the SAM – step 3 in the diagram. The exogenous parameters capture the behaviour of economic agents and measure their responsiveness to relative prices and income changes. At least three types of parameters need to be estimated. The first type is the elasticities that govern the substitution amongst the primary factors of production (labour, land and capital). The second is the Armington elasticities to differentiate commodities by country of origin. The third type of parameters determines prices and income elasticities. These three types of parameters are often either taken from existing studies or estimated for specific cases. The choice of the closure rules – step 4 in the diagram – is another important step in operationalising a CGE model. The closure rules ensure that the model is closed, meaning that there are enough independent equations to explain the endogenous variables. Moreover, the closure rules capture the macroeconomic environment and define the directions of causality in the model. Depending on the chosen closure rules, the way an economy adjusts to a policy shock differs. The choice of closure rules should be guided by a sound theoretical background, as well as by the specific nature of the problem under investigation. In static CGE models, the closure rules relate predominantly to factor markets, investment, government and current account balances (Gilbert and Tower, 2012). Changes in the capital market usually represent different adjustment timeframes. The Heckscher-Ohlin specification implies mobility of capital across industries. In contrast, the sector-specific factor specification assumes the stock of capital in each industry to be exogenous, i.e. fixed. While the Heckscher-Ohlin specification reflects a long-term perspective, the sector- specific factors specification corresponds to a short-term perspective. In the labour market, the neoclassical standard closure assumes a flexible wage rate and full employment of labour. An alternative is to fix the wage rate and flex the level of employment, hence introducing the possibility for labour to be unemployed.

The choice of closures for the saving-investment balance depends on the characteristics of the economy. The modeller can either fix investment and let the balance identity determine savings (investment-driven closure), or fix savings and let the balance identity determine the level of investment (savings-driven closure).

42 There are different options to close the government account depending on the economic reality the modeller wants to depict. If the government faces a binding budget constraint, the government balance needs to be fixed. Either the government expenditure or income varies to keep the balance. In case the choice is made to let the government’s income vary, a tax rate is chosen to adjust endogenously. Often the income tax is chosen for its income distribution effect, which is absent from other tax instruments.

Finally, to close the current account balance that reflects savings/borrowing from the rest of the world two options are often considered. Either the current account balance is fixed and the exchange rate adjusts, or the exchange rate is fixed and the current account is flexible. When a fixed current account is specified, it represents an economy with limited access to foreign credit. This closure ensures that all the welfare effects are kept in the solution period. By contrast, a flexible current account – by allowing extensive foreign borrowing – increases consumption in the current period but does not account for paying back the debt. Hence, the welfare effects are biased in this closure.

The model calibration – step 5 in the diagram – is the process of estimating all parameters that remain unknown, such that together with the value transactions from the SAM and the values of the behavioural parameters, the model is able to reproduce exactly the data of the reference year. This estimation of the unknown parameters could be done empirically if the required data are available. In most CGE applications, the procedure adopted to estimate those parameters is to use the information contained in the SAM. The model calibration is a mathematical procedure, whereby parameters such as shares and scale parameters are calibrated using the SAM coefficients. Subsequently, the benchmark data contained in the SAM are considered to represent the initial equilibrium. Some consistency checks should be incorporated to help identifying possible errors.

When the model calibration is completed and the consistency checks do not reveal any leakage in the system, the model is ready for policy experiments – step 6 in the diagram. The policy change to be simulated should potentially have economy-wide effects on sectors other than the one where the initial shock is implemented. The parameters whose values need to be changed exogenously to implement the policy change as a shock to the model should be identified. While choosing the variables to be turned into parameters, the researcher needs to keep the equality between the number of equations and the number of variables. After running the policy experiments, the model analysis consists in a pairwise comparison between the counterfactual equilibrium and the benchmark (initial equilibrium). The assessment of welfare changes is usually one of the main outcomes of a CGE model, since the final goal of any policy is to improve people’s livelihoods. Welfare is usually measured in terms of Hicksian compensating or equivalent variation. The net welfare is obtained by summing up welfare gains and losses across individuals and across regions. For

43 a comparison across household groups, the welfare effects measured in monetary units tend to be larger for wealthy households. Subsequently, a better basis for comparison across income groups is to use the ratio of the welfare change to the initial household income.