Estimation and Projection of Urban Population: Tests of Forecast Accuracy and Bias

The urban population projection is an important tool for planning and policy making. There are so many projection methods available, one of the standard methods is the United Nations method. This article aims to examine the best urban population projection method among different methods viz. Modified Exponential curve, Gompertz curve and Logistic growth curve by using the Mean Absolute Percentage Error (MAPE) and Mean Algebraic Percentage Error (MALPE). The estimation of urban population for sixty years from 1961-2011 is computed and later the urban population is projected for next fifty years by using growth models.
The data collected for this study is from different census reports for India, from www.indexmundi.com for China and from www.worldbank.org for the World. The results revels that there is a strong relationship between the forecast error and the bias with growth rate of urban population during the base period for all the three curves. The Gompertz curve has smaller forecast error compared to other curves and it shows underestimate for India and China. The study also reveals that the logistic growth has the smaller forecast error compared to other growth curves and it shows overestimate for World.