Public Policy Conclusions from Urban Growth Models

This paper is intended to be a case study in the use of simulation models to test public policy alternatives. Suggested programs for dealing with urban poverty are tested with the aid of different models which describe the linked growth of housing, population, and industry in an urbanized area. The tested programs are: 1) training, to provide the unskilled with job skills; 2) job provision, to make extra jobs for skilled workers; 3) clearance, to eliminate " excess" housing and thereby free land which may be used by industry. The models used are: the original Forrester [1] model, which treats a single city as a unit in an unchanging national environment; an extension of this model to include all the central cities of the nation and describe the migration between these areas; and finally a complete revision of the Forrester model to obtain a simulation of the national economy including both cities and suburbs. The three different models give very different results. The original model, which focuses upon applying programs to a single city, strongly indicates that clearance is the only one of these programs which is effective in eliminating urban poverty. The second model indicates that when applied throughout the nation, both the clearance and training programs are effective, but job provision is ineffective. However, the third model uses its more complete picture of the national economy to conclude that job provision can indeed be effective in reducing poverty.