| Abstract: | Several papers have estimated the parameters of Pareto distributions for city sizes in different countries, but only one has attempted to explain the differing magnitudes of these parameters with a set of country-specific explanatory variables. While it is reassuring that there has been some research which advances beyond simple “curve-fitting” to explore the determinants of city size distributions, the existing research uses a two-stage OLS method which yields invalid second-stage standard errors (and, consequently, questionable hypothesis tests). In this paper, we develop candidate one-stage structural models with normal and non-normal errors which accommodate truncated size distributions, potentially Pareto-like shapes, and city-level variables. In general, these new models are nonlinear in parameters. We illustrate with data on U.S. urban areas. |
