Abstract
Gibrat’s law and Zipf’s law describe two very well-known empirical regularities on the distribution of settlements. Many studies have focused on the analysis of both these regularities, stimulated by the idea that an accurate description of the distribution of people in space is important for both policy-relevant purposes and for specifying more appropriate theoretical models. However, the existing literature provides an analysis of Gibrat’s and Zipf’s law without taking into account the demographic characteristics of the population under analysis. Given the fact that many countries, and especially those in Europe, will become ageing societies in the decades to come, the aim of this chapter is to provide a more accurate description of the distribution of people, taking into account the demographic differences between people. In this analysis, we focus on both municipal population (place of residence) and employment (place of work) data for Germany between the years 2001 and 2011. Here, we provide evidence of different behaviour in the cohorts of older people. Theoretical models of urban growth that aim to be more fit-for-purpose need to take this different behaviour into consideration.
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Notes
- 1.
A first attempt trying to add age into Gibrat/Zipf’s literature has been proposed by Giesen and Suedekum (2014). Even though this approach has not considered the age structure of the population/labour force but the age of the city, it might be considered as one of the first works that goes beyond the simple city size spatial distribution.
- 2.
Note that the huge increase in employment in the older cohorts can also be due to the reform of the labour market that took place in Germany between 2003 and 2005, also known as the Hartz package (Hartz I–IV). In brief, the first three stages of the reforms sought to improve job search efficiency and employment flexibility. They included deregulation of the temporary work sector to give individual employers more flexibility to vary employment levels without incurring hiring or firing costs, as well as a restructuring of the federal labour agency in order to improve the training and matching efficiency of job searchers. The final set of reforms entailed a major restructuring of the unemployment and social assistance system that considerably reduced the size and duration of the unemployment benefits and made them conditional on tighter rules for job search and acceptance.
- 3.
In that paper, the authors show that the estimator obtained by means of the usual regression is biased. They also show that this bias could be minimised if we subtract 0.5 from the rank value.
- 4.
Even the test of the equality of the two estimated parameters is not significant. Pairwise tests are available upon request.
- 5.
We refer readers to their papers for a more detailed description.
- 6.
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Modica, M., Reggiani, A., De Vivo, N., Nijkamp, P. (2018). Ageing and Labour Market Development: Testing Gibrat’s and Zipf’s Law for Germany. In: R. Stough, R., Kourtit, K., Nijkamp, P., Blien, U. (eds) Modelling Aging and Migration Effects on Spatial Labor Markets. Advances in Spatial Science. Springer, Cham. https://doi.org/10.1007/978-3-319-68563-2_14
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