Parametric, semiparametric and nonparametric models of urban growth

This paper discusses parametric, nonparametric, and semiparametric models of urban growth. To illustrate differences across approaches, we test Gibrat's law in the long run, using the three methods and three different datasets: Spanish capital cities and regions (1900-2011, annual data) and US MSAs (1900-2000, decennial data). Our results reveal that the estimation of the relationship between growth and initial size can significantly vary across methods. We suggest and encourage the use of semiparametric methods in future research of urban growth.

Automated summary

This paper discusses different models (parametric, nonparametric, and semiparametric) of urban growth and compares their results using three different datasets. The findings suggest that the estimation of the relationship between growth and initial size varies significantly across methods. The use of semiparametric methods is recommended for future research in this field.