Spatial analysis of urban growth in Spain, 1900–2001

The purpose of this paper is to improve the knowledge of the Spanish urban system. We study the evolution of population growth among the group of 722 municipalities included in the Spanish urban areas over the period 1900–2001. A spatial SUR model is estimated for Zipf’s law and shows the existence of two main phases: divergence (1900–1980) and convergence (1980–2001). Then, the cross-sectional distribution of urban population is characterized by means of nonparametric estimations of density functions and the growth process is modeled as a first-order stationary Markov chain. Spatial effects are finally introduced within the Markov chain framework using regional conditioning. This analysis shows a low interclass mobility, i.e., a high-persistence of urban municipalities to stay in their own class from one decade to another over the whole period, and the influence of the geographical environment on urban population dynamism.

[1]  Henry G. Overman,et al.  Cross-sectional evolution of the U.S. city size distribution , 2001 .

[2]  Sergio J. Rey,et al.  Spatial Empirics for Economic Growth and Convergence , 2010 .

[3]  M. Kawagoe.  Regional Dynamics in Japan: A Reexamination of Barro Regressions , 1999 .

[4]  Sandra Bulli.  Distribution Dynamics and Cross-Country Convergence: A New Approach , 2001 .

[5]  Frank Bickenbach,et al.  Evaluating the Markov Property in Studies of Economic Convergence , 2003 .

[6]  James D. Hamilton.  Time Series Analysis , 1994 .

[7]  L. Anselin.  Spatial Econometrics: Methods and Models , 1988 .

[8]  B. Fingleton.  Estimates of Time to Economic Convergence: An Analysis of Regions of the European Union , 1999 .

[9]  A. Zellner.  An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias , 1962 .

[10]  Spain. Dirección General de la Vivienda,et al.  Atlas estadístico de las áreas urbanas en España , 2000 .

[11]  K. Soo.  Zipf's law for cities: a cross-country investigation , 2005 .

[12]  Danny Quah,et al.  Empirics for economic growth and convergence , 1996 .

[13]  Danny Quah,et al.  Empirical cross-section dynamics in economic growth , 1993 .

[14]  X. Gabaix.  Zipf's Law for Cities: An Explanation , 1999 .

[15]  J. Marchal.  Cours d'economie politique , 1950 .

[16]  Danny Quah,et al.  Empirics for Growth and Distribution: Stratification, Polarization, and Convergence Clubs , 1997 .

[17]  Ying Ge,et al.  The size distribution of Chinese cities , 2005 .

[18]  Geoffrey J. D. Hewings,et al.  SPACE‐TIME EMPLOYMENT MODELING: SOME RESULTS USING SEEMINGLY UNRELATED REGRESSION ESTIMATORS* , 1982 .

[19]  P. Cheshire,et al.  Endogenous Processes in European Regional Growth: Convergence and Policy , 2000 .

[20]  Paul A. Johnson,et al.  A nonparametric analysis of income convergence across the US states , 2000 .

[21]  B. Fingleton,et al.  Independence, Stationarity, Categorical Spatial Data and the Chi-Squared Test , 1983 .

[22]  A. Fielding.  Migration and Urbanization in Western Europe Since 1950 , 1989 .

[23]  Urban Structure and Growth , 2005 .

[24]  Duncan Black,et al.  Urban evolution in the USA , 2003 .

[25]  Bernard Fingleton,et al.  Log-Linear Models with Dependent Spatial Data , 1983 .

[26]  Steven Brakman,et al.  The Return of Zipf: Towards a Further Understanding of the Rank‐Size Distribution , 1999 .

[27]  F. Pueyo,et al.  The Evolution of Spanish Urban Structure during the Twentieth Century , 2003 .

[28]  F. Sanz,et al.  LA DISTRIBUCIÓN DEL TAMAÑO DE LAS CIUDADES EN ESPAÑA, 1900-1999 * , 2004 .

[29]  Baris Tan,et al.  Markov chain test for time dependence and homogeneity: An analytical and empirical evaluation , 2002, Eur. J. Oper. Res..

[30]  Bernard Fingleton,et al.  Analyzing Cross‐classified Data with Inherent Spatial Dependence , 2010 .

[31]  Yannis M. Ioannides,et al.  The Evolution of City Size Distributions , 2004 .

[32]  Gilles Duranton,et al.  Some foundations for Zipf's law: Product proliferation and local spillovers , 2006 .

[33]  Jordi Suriñach,et al.  Regional economic dynamics and convergence in the European Union , 1999 .

[34]  X. Gabaix.  Zipf's Law and the Growth of Cities , 1999 .

[35]  Jonathan D. Cryer,et al.  Time Series Analysis , 1986 .

[36]  George Kingsley Zipf,et al.  Human behavior and the principle of least effort , 1949 .

[37]  L. Anselin,et al.  Spatial Panel Econometrics , 2008 .

[38]  X. Gabaix,et al.  Rank − 1 / 2: A Simple Way to Improve the OLS Estimation of Tail Exponents , 2007 .

[39]  J. Córdoba,et al.  On the Distribution of City Sizes , 2003 .

[40]  Zvi Eckstein,et al.  Cities and Growth: Theory and Evidence from France and Japan , 1994 .

[41]  B. Fingleton,et al.  Explaining the Distribution of Manufacturing Productivity in the EU Regions , 2003 .

[42]  Peter Nijkamp,et al.  Dynamic Models of Spatial Autocorrelation , 1977 .

[43]  P. Krugman.  The Self Organizing Economy , 1996 .

[44]  Bernard Fingleton.  Theoretical economic geography and spatial econometrics: dynamic perspectives , 2001 .

[45]  Stefano Magrini,et al.  The evolution of income disparities among the regions of the European Union , 1999 .

[46]  Yannis M. Ioannides,et al.  Dynamic Evolution of the U.S. City Size Distribution , 1999 .

[47]  Duncan Black,et al.  Spatial Evolution of Population and Industry in the United States , 1999 .

[48]  Yannis M. Ioannides,et al.  Zipf’s law for cities : an empirical examination , 2000 .

[49]  John G. Kemeny,et al.  Finite Markov chains , 1960 .

[50]  Julie Le Gallo,et al.  Space-Time Analysis of GDP Disparities among European Regions: A Markov Chains Approach: , 2004 .