Time-Series Based Empirical Assessment of Random Urban Growth: New Evidence from France

LALANNE, Aurelie; ZUMPE, Martin

doi:10.1007/s40953-020-00204-0

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LALANNE, Aurelie

Groupe de Recherche en Economie Théorique et Appliquée [GREThA]

ZUMPE, Martin

Groupe de Recherche en Economie Théorique et Appliquée [GREThA]

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Ce document a été publié dans

Journal of Quantitative Economics. 2020-05-09

Résumé en anglais

Modern urban growth literature frequently uses unit-root tests in order to check the empirical relevance of Gibrat’s law of random growth. The contradictory nature of the test results provided by this literature is most likely linked to the low power of unit-root tests. To address this problem, we apply unit-root testing to a large-sized sample of high-quality French census data covering an exceptionally long time span of more than two centuries. We add subsequent cointegration tests in order to detect the possible presence of cointegrated random growth, which may reflect the fact that cities with a similar economic structure react fairly similarly to exogenous growth shocks. According to the test results, the random growth hypothesis cannot be rejected for a very large majority of the tested French cities; on the other hand, the null hypothesis of absence of cointegration cannot be rejected in more than 95% of the cases. Our findings therefore provide empirical support for non-cointegrated random growth.< Réduire

Mots clés en anglais

Gibrat’s law

Unit-root tests

Cointegration tests

Random urban growth

Low test power

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