Zipf’s exponent and Zipf’s law in the BRICS: A rolling sample regressions approach

Using urban data from the last available census of the five BRICS countries we have tested, by means of a rolling sample regressions approach, whether, as Eeckhout (2004) proposed, the Pareto exponent in a standard Zipf equation is decreasing as more cities are added to the sample. The results are very conclusive: Eeckhout's hypothesis is satisfied for Brazil, Russia and South Africa, but for India and China there are non-negligible parts of the distribution where it is not fulfilled. We also test the fulfilment of Zipf's law: it holds in the upper tail of the five countries (except South Africa) but for the rest of the distribution the predominant outcome is rejection

Urbanization and COVID-19 incidence: A cross-country investigation

This paper investigates the determinants of the diffusion and intensity of the COVID-19 at the country level, focusing on the role played by urban agglomeration, measured using three urban variables: percentage of the urban population, population density, and primacy. We estimate the influence of urban agglomeration on two outcome variables: cumulative number of cases and deaths per 100, 000 inhabitants up to 31 December 2020, using both parametric and semiparametric models. We also explore possible spatial effects. The non-linear effects of the urban variables on the intensity of the disease reveal non-monotonous relationships, suggesting that it is the size of the urban system that is linked to a stronger incidence

Size Distributions for All Cities: Lognormal and q-exponential functions

This paper analyses in detail the features offered by a function which is practically new to Urban Economics, the q-exponential, in describing city size distributions. We highlight two contributions. First, we propose a new and simple procedure for estimating their parameters. Second, and more importantly, we explain the characteristics associated with two traditional graphic methods (Zipf plots and cumulative density functions) for discriminating between functions. We apply them to the lognormal and q-exponential, justifying them as the best functions for explaining the entire distribution, and that the relationship between them is of complementarity. The empirical evidence relies on the analysis of urban data of three countries (USA, Spain and Italy) over all of the 20th century.

Brasil:Estructura urbana y desarrollo

El desarrollo urbano de Brasil en las últimas seis décadas ha sido muy acelerado, pasando de una población predominadamente rural a una mayoritariamente urbana. Prueba de ello son las ciudades de Sao Paulo y Rio de Janeiro. El gran crecimiento poblacional desde 1960 hasta la actualidad ha provocado que se triplice a la población, concentrandose el crecimiento en la población urbana.Este crecimiento se ha relantizado en los últimos años debido a la reducción de la natalidad y el aumento de la esperanza de vida,provocando una inversión en la pirámide poblacional que tendrá consecuencias en la economía. Mediante el análisis estadístico de la población, podemos apreciar un fenómeno matemático denominado ley de Zipf que se produce en la distribución de los municipios más poblados del país. Este fenómeno no es exacto en todas las poblaciones pero se produce en casi todos los países en mayor o menor medida.La distribución de la riqueza en el país es muy desigual, estando muy condicionado los niveles de renta dependiendo del origen étnico del individuo. <br /

The size distribution of employment centers within the US Metropolitan Areas

This study tackles the description of the size distribution of urban employment centers or, in other words, the size of areas within cities with significantly high densities of workers. Certainly, there exists a branch of urban economics that has paid substantial attention to urban employment centers, but the efforts have been focused on identification methodologies. In this paper we build on such body of research and combine it with insights from the latest contributions in the sister subfield of city size distributions to push the agenda forward in terms of the understanding of these phenomena. We consider the 359 Metropolitan Statistical Areas (MSAs) in the United States in the year 2000 and reach three main conclusions: First, employment center sizes are more unevenly distributed than city sizes; second, the two functions that best describe city size distributions, namely the lognormal and the double Pareto-lognormal, also offer a good fit for the case of centers, particularly the latter; and third, several interesting statistically significant relationships (correlations) between variables related to centers and MSAs are deduced. Further experiments with a different technique of center identification suggest that the results are fairly robust to the method of choice. </jats:p

Is there a universal parametric city size distribution? Empirical evidence for 70 countries

We study the parametric description of the city size distribution (CSD) of 70 different countries (developed and developing) using seven models, as follows: the lognormal (LN), the loglogistic (LL), the double Pareto lognormal (dPLN), the two-lognormal (2LN), the two-loglogistic (2LL), the three-lognormal (3LN) and the three-loglogistic (3LL). Our results show that 3LN and 3LL are the best densities in terms of non-rejections out of standard statistical tests. Meanwhile, according to the information criteria AIC and BIC, there is no systematically dominant distribution

US city size distribution revisited: Theory and empirical evidence

We develop a urban economic model in which agents locate in cities of different size so as to maximize the net output of the whole system of cities in a country. From this model two new city size distributions are exactly derived. We call these functions “threshold double Pareto Generalized Beta of the second kind” and “double mixture Pareto Generalized Beta of the second kind”. In order to test empirically the theory, we analyze the US urban system and consider three types of data (incorporated places from 1900 to 2000, all places in 2000 and 2010 and City Cluster Algorithm nuclei in 1991 and 2000). The results are encouraging because the new distributions clearly outperform the lognormal and the double Pareto lognormal for all data samples. We consider a number of different tests and statistical criteria and the results are robust to all of them. Thus, the new distributions describe accurately the US city size distribution and, therefore, support the validity of the theoretical model

US city size distribution revisited: Theory and empirical evidence

We have developed an urban economic model in which a social planner maximizes the net output of the whole system of cities in a country in such a way that agents locate themselves in cities of different sizes. From this model we derive the new “threshold double Pareto Generalized Beta of the second kind”. In order to test the theory empirically, we have analysed the US urban system and have considered two types of data (incorporated places from 1900 to 2000 and all places in 2000 and 2010). The results are encouraging because the new distribution always outperforms the lognormal and the double Pareto lognormal. The results are robust to a number of different criteria. Thus, the new density function describes accurately the US city size distribution and, therefore, tends to support the validity of the theoretical model