Zipf's law for cities: an empirical examination
TLDR
In this paper, a nonparametric procedure was used to calculate local Zipf exponents from the mean and variance of city growth rates to test the validity of Zipf's Law for cities.About:
This article is published in Regional Science and Urban Economics.The article was published on 2003-03-01 and is currently open access. It has received 362 citations till now. The article focuses on the topics: Gibrat's law & Zipf's law.read more
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Journal ArticleDOI
Gibrat's Law for (All) Cities
TL;DR: In this paper, an equilibrium theory of local externalities that can explain the empirical size distribution of cities is proposed, and the driving force is a random productivity process of local economies and the perfect mobility of workers.
ReportDOI
Power Laws in Economics and Finance
TL;DR: In this paper, a review of empirical power laws regarding income and wealth, the size of cities and firms, stock market returns, trading volume, international trade, and executive pay is presented.
Book ChapterDOI
The Evolution of City Size Distributions
TL;DR: In this article, the authors review the accumulated knowledge on city size distributions and determinants of urban growth and offer a novel discussion of the important econometric issues in the characterization of the distribution, emphasizing both bare-bone statistical theories and more developed economic theories.
Journal ArticleDOI
On the Evolution of Firm Size Distributions
Paolo Angelini,Andrea Generale +1 more
TL;DR: In this paper, the impact of financial constraints on firm size distribution (FSD) was studied and it was found that financially constrained firms, identified using various proxies, are smaller than the others (their FSD is more skewed to the right).
Journal ArticleDOI
Zipf's law for cities: a cross-country investigation
TL;DR: The authors assesses the empirical validity of Zipf's Law for cities, using new data on 73 countries and two estimation methods (OLS and the Hill estimator) and conclude that variations in the value of the Pareto exponent are better explained by political economy variables than by economic geography variables.
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BookDOI
Density estimation for statistics and data analysis
TL;DR: The Kernel Method for Multivariate Data: Three Important Methods and Density Estimation in Action.
Book
Applied Nonparametric Regression
TL;DR: This chapter discusses smoothing in high Dimensions, Investigating multiple regression by additive models, and incorporating parametric components and alternatives.
Journal ArticleDOI
Zipf's Law for Cities: An Explanation
TL;DR: In this paper, it was shown that, at least in the upper tail, all cities follow some proportional growth process (this appears to be verified empirically), which automatically leads their distribution to converge to Zipf's law.
Journal ArticleDOI
Applied Nonparametric Regression.
TL;DR: In this paper, the authors propose smoothing with correlated data and with parametric components and alternatives, and investigate multiple regression by additive models, including smoothing in high dimensions, using the kernel method.