Especially for the purposes of policy analysis, we often want to force the result of an equation towards a particular value over time (e.g. to achieve the elimination of indoor use of solid fuels). Target variables are generally paired, one for the target level and one for the number of years to reach the target (from the initial year of the model forecast). Targets have different types:
In this case, the target value and year define to what absolute value the variable should move and in how many years after the first model year. Together they determine a path in which the value for the variable moves linearly from the value in first year to the target value in the target year. (In some cases, the model uses non-linear convergence, e.g. to accelerate movement in early years and then to slow it as the target is approached.) Trgtval and trgtyr are the parameter suffixes used for this parameter type. The first of these changes the target itself and the second of these alters the number of years to the target.
Relative (standard error) targets
In this case, the target value and year def ine to what relative value the variable should move and in how many years after the first. The relative value is defined as the number of standard errors above or below the “expected” value of the variable of interest. (An expectation is usually based on the country's GDP per capita and a cross-sectional analysis of country values.) As with the absolute targets the value calculated using the targeting is compared to the value forecast in the model without targeting and the final forecast value gradually moves from that pre-targeting forecast value to the target value. Two different parameter suffixes are used in standard-error targeting: setar and seyrtar. The first of these changes the target itself and the second of these alters the number of years to the target.