Labour Supply

CANDIDE 2.0 and TIM both contain detailed demographic blocks and disaggregated participation rate equations. This may be a real advantage in modelling labour supply. The CANDIDE part rate equations are plausible enough by themselves, but there are reasons to be skeptical about the strength of the labour supply response to tax changes, which in simulation can almost counteract the impact of labour demand on the unemployment rate.

RDX2 also only had a single participation rate equation. It included the capacity utilization rate, population in secondary school, and net immigration as explanatory variables.

The CHASE model has six age-sex groups. Its part rate equations, which depend on a trend and the percentage change in employment, appear to be misspecified. The trend is the only influence captured substantially by the equations.

The DRI model does not explicitly model labour supply. Instead it sums employment and unemployment. The key relationship is an Okun's law equation relating the gap between the actual and natural unemployment rate to capacity utilization and the ratio of the prime age male labour force to the total working population. Such an equation does not directly reflect many of the important factors behind decisions to participate in the labour force affecting various age and sex groups, and is a questionable basis for determing labour supply.

The FOCUS model has an age-sex breakdown and structural participation rate equations incorporating age and sex specific factors as well as general trends and employment rates. The only problem with the sector is that it is getting out of date and may not reflect recent movements in part rates that may reflect structural changes.

MTFM also has an age-sex breakdown and structural participation equations that appear reasonable.

RDXF only has a single participation rate. This may not be adequate to capture the complex age and sex specific factors determining the participation rate. The lag structure of the

equation has also grown increasingly complex since the original version of RDXF. This could reflect an attempt to pick up with lags what are really shifts in fundamental determinants.

The MACE part rate equation is interesting in that it suggests that the AIB raised part rates and that an increase in real wages lowers the part rate. This latter result is opposite from that found in CANDIDE.

In SAM labour supply is based on the same intertemporal utility maximization decision as

consumption. As a result, the specification is very complicated involving the ratio of per capita real wealth to the returns from labour market participation and adjustments for the difference between steady state and actual valuations.

Such a specification is unlikely to track in the short- to medium-term because of its lack of labour market slack variables and trends related to demographics. It would not be suitable for a quarterly forecasting model.

4.9 Trade

An important issue in the trade sector is the extent of disaggregation that is desirable. The large annual models, CANDIDE and TIM, are able to take advantage of the extensive detail available in the annual data. CANDIDE has 208 trade volume and value equations and 89 trade price equations and TIM has 730 trade equations and 234 trade price (including identities). It would not be possible for a quarterly model to have such a high level of disaggregation.

The quarterly models range in size from MTFM with 117 trade equations and 131 trade price equations and QFS with 81 trade equations and 86 trade price equations to FOCUS with 37 trade equations and 19 trade price equations. In the middle fall CHASE (63 trade and 32 trade price equations), DRI (49 trade and 33 trade price equations), and RDXF (44 trade and 28 trade price equations). Somewhere in this range is probably about the right size trade sector for a quarterly forecasting model.

The two small annual models have very small trade sectors. MACE has 6 trade equations and 2 trade price equations and SAM 2 trade equations and 4 trade price equations. This would clearly not be enough for a quarterly forecasting model because quite often the short-term growth of exports and imports are associated with particular developments affecting certain categories of trade flows.

A minimum level of disaggregation for forecasting the trade sector would include separate treatment of exports of wheat, automobiles, forest products, minerals, and energy and of imports of automobiles, energy, and interest and dividends. Further disaggregation could be helpful provided sufficient attention were paid to getting the detail right.

Among the quarterly models the approach to modelling trade flows is very similar. This is particularly the case for import equations where the general specification is as a function of domestic activity, relative prices, and capacity utilization. For export equations there are some differences in the extent to which supply variables play a role, but there is general agreement on the importance of trade weighted foreign activity variables and some measure of export prices relative to foreign prices. Concerning import prices, all of the models exhibit price taking behaviour. But for export prices there is disagreement. Export prices in RDXF and CHASE primarily reflect price taking behaviour, whereas in DRI and QFS export prices are set in Canada.

FOCUS, MTFM, and RDX2 display both price setting and taking behaviour to varying degrees.

In this case the middle road would seem to be the most reasonable course. For some categories of

exports, including particularly, primary products and raw materials, price-taking behaviour is probably dominant; for others such as manufacturing where there is more product differentiation, price-making behaviour may be more characteristic.

The SAM export equation is quite different from the other export equations. In the long-run exports are determined by supply. This assumption might be useful for ensuring that the trade balance does not become a source of instability in longer-run simulations but it does not give enough emphasis to foreign demand for short- to medium-run forecasting.

The exchange rate equations in those models that have them are essentially renormalized short-term capital flow equations. Since this theoretical approach to the exchange rate suggests that the appropriate form for such an equation is as an adjustment of desired to actual stock of outstanding short-term liabilities, a well specified equation should have the lagged stock of outstanding short-term liabilities as an explanatory variable. This was the case in RDX2 and is the case in DRI and CHASE, which followed RDX2.

Other models, particularly, RDXF and QFS, take a purchasing-parity view of longer-term exchange rate determination, although there are capital flow influences in the short-term. One question in such models is what index should be used to measure PPP.

FOCUS takes another approach to determining the exchange rate. It is set as the price which equilibrates the balance of payments. This is possible because of the high degree of sensitivity of capital flows to exchange rate variations. The FOCUS approach certainly represents an

interesting alternative. However, the high degree of sensitivity of capital flows does cause FOCUS to

respond too strongly to changes in interest rates. So it is not clear that a market clearing exchange rate is a viable approach for a quarterly model.

MACE has a large array of options for exchange rate determination implemented through simulation rules. This is useful for policy analysis.

SAM determines the exchange rate as clearing the market for foreign assets. This is a consistent and theoretically rigourous approach which integrates well with its treatment of other

financial assets.

4.10 Government

There is relatively little that the Department of Finance can learn from the government sectors of the macro-models. As a general rule the models do not incorporate the degree of detail

required, nor is sufficient attention always paid to institutional details and the specification of individual equations. This is understandable given that the primary objective of the models is to explain aggregate economic activity and not to prepare the government's fiscal plan.

A feature of two of the models, RDX2 and CANDIDE, that may be of some interest is their personal income tax models. An up-to-date version of such a model could be of some use in producing medium- and long-term fiscal forecasts.

5 SOME OBSERVATIONS ON CANADIAN MACROECONOMIC MODELLING