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

Aurélie Lalanne and Martin Zumpe
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Aurélie Lalanne: UMR-CNRS 5113, GREThA, University of Bordeaux

Journal of Quantitative Economics, 2020, vol. 18, issue 4, No 9, 926 pages

Abstract: Abstract 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.

Keywords: Gibrat’s law; Unit-root tests; Cointegration tests; Random urban growth; Low test power (search for similar items in EconPapers)
JEL-codes: C41 R0 R10 R11 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s40953-020-00204-0

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