ONE-STAGE STRUCTURAL MODELS TO EXPLAIN CITY SIZE

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. © 1990.