  This paper studies the size distributions of urban agglomerations for India
and China. We have estimated the scaling exponent for the Zipf's law with the
Indian census data for the years of 1981-2001 and the Chinese census data for
1990 and 2000. Along with the biased linear fit estimate, the maximum
likelihood estimate for the Pareto and Tsallis q-exponential distribution has
been computed. For India, the scaling exponent is in the range of [1.88, 2.06]
and for China, it is in the interval [1.82, 2.29]. The goodness-of-fit tests of
the estimated distributions are performed using the Kolmogorov-Smirnov
statistic.
