Studies on population dynamic have revealed that as thetrends and patterns cf demographic variables have changed thedistribution shapes may also change. In fertility. for example, thedecline in total fertility rates (TFR) may be followed by the shiftingin the age of childbearing which in turn distorting the shape offertility rates. Despite these facts, however, most forecastingdone in developing countries has traditionally assumed the constantpatterns of demographic variables, whereas the levels have changed(e.g. TFR and IMR). This study attempts to _fill this gap bycontributing an alternative scenario in forecasting demographicvariables. Using multiple data sources (census and surveys),assumptions for forecasting was constructed by incorporatingvariation in the age profile as well as in the level of demographiccomponents. Demographic models, which include the models ofdemographic schedules and Heighman-Pollard were applied. Thisstudy demonstrated how it is possible, using limited data thatavailable in Indonesia and in many developing countries, toconstruct alternative 'dynamic? scenarios. It has been done so byapplying some advanced demographic methods to indonesia data,and draw evidence from other, similar countries. An alternative'dynamic ' scenario was implemented by using the changes of levelsand patterns of demographic parameters over the forecastingperiod. |