Political connections, political favoritism and political competition: evidence from the granting of building permits by French mayors


This article discusses the influence of political connections on public policies implemented at the local level. Using a sample of more than 189,000 local politicians in French cities with more than 3500 inhabitants, I examine whether families of candidates who supported the mayors elected in 2008 obtain more building permits than the families of their political opponents. I find that the former obtain 35% more building permits than the latter between 2008 and 2014. Then, I show that the previous difference declines with political competition and disappears after close elections. My interpretation of those findings underlines two mechanisms. First, political competition disciplines mayors: in cities with weak political competition, mayors may favor their supporters when these supporters or one of their family members wants to obtain building permits, but they refrain from doing so after close elections. Second, in these cities, individuals who want to obtain something in exchange for their support (such as facilitating the acquisition of building permits) may easily forecast who is likely to become the mayor and whom they should support.

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  1. 1.

    I follow Curto-Grau et al. (2018) and borrow the definition of political favoritism from Golden and Min (2013). It is defined as situations in which “politicians allocate [goods or resources] disproportionately to population subgroups, variably identifiable by race, ethnicity, or partisanship” (Golden and Min 2013, p.74).

  2. 2.

    The literature includes Fisman 2001; Khwaja and Mian 2005; Faccio 2006; Li et al. 2008; Ling et al. 2016. Scholars do not always detect a positive effect and sometimes find a negative effect of political connections for business firms (Fisman et al. 2012; Bertrand et al. 2018).

  3. 3.

    The phenomenon is particularly relevant because local politicians and candidates during municipal elections may benefit from urban growth (Logan and Molotch 1987), even though the conjecture does not imply that local politicians run for election because they own land (Poulos 2019).

  4. 4.

    Other studies nuance this finding (for instance: Samson Kimenyi and Shughart 2008), ethnic favoritism may not disappear with democracy, but its prevalence is based on constitutional choices.

  5. 5.

    That mechanism requires that voters somehow observe favors that have been granted to supporters of the politician and that they dislike observing such favors.

  6. 6.

    That group includes those who know they cannot obtain a building permit unless a politician helps them.

  7. 7.

    In the electronic appendix (A.1), I present a conceptual framework that seeks to highlight such exchanges of favors and the likely effect of political competition.

  8. 8.

    The sample covers 2561 cities, which represents 94% of cities with more than 3500 inhabitants. In the other cities, the electoral system does not allow for identifying the supporters of mayors.

  9. 9.

    That scenario is authorized by electoral laws even if it is a rare. In the electronic appendix A.2.1, I discuss that point in greater depth and detail the identification of political supporters.

  10. 10.

    “Article L. 422-1 of the Code de l’urbanisme.” Préfets, the representatives of the state at the département level (an administrative unit larger than cities) might also be involved, and in very rare cases, the emission of building permits is delegated to the “établissement public coopération intercommunale” (EPCI).

  11. 11.

    Changing zoning laws is a long process, but it is possible during a 6-year term. For instance, it appears that for cities that decided to write new zoning documents in 2009, 45% of them entered into application before 2014 (author computation).

  12. 12.

    I was not able to detect the surnames of applicants in approximately 1.3% of applications. In addition, surnames sometimes appeared to be misspelled or truncated.

  13. 13.

    The main sample adopts exact surname matching. However, I also test matching based on a Levenshtein distance that allows for small differences in the spelling of surnames. Results of such an exercise are available upon request.

  14. 14.

    In the electronic appendix (A.3.2), I detail the steps required to build the sample and provide further descriptive statistics on the cities included in the sample.

  15. 15.

    July 2008 and January 2013 are, respectively, 3.5 months after the 2008 elections and 3.5 months before those in 2014.

  16. 16.

    I employ a linear probability model because of the large number of dummies and fixed effects entered into the regressions.

  17. 17.

    As discussed above, the event is rare.

  18. 18.

    See the electronic appendix (A.3.2) for more detail.

  19. 19.

    The information comes from data collected by the National Institute of Statistics and Economic Studies (INSEE).

  20. 20.

    The variables become significant when I do not control for “rank on lists”, suggesting that “political involvement” plays a role.

  21. 21.

    Two explanations for the finding are possible. Either those individuals are not connected strongly to mayors or mergers between lists occur only when political competition is important enough.

  22. 22.

    Those variables are constructed from local statistics collected by the National Institute of Statistics and Economic Studies.

  23. 23.

    Artificial lands are defined as all non-natural lands, that is, streets, buildings, developed areas, and so on. In computing that percentage, I removed all water zones (e.g. lakes, sea, rivers). The data are 2006 observations from the Corine Land Cover European projects.

  24. 24.

    Descriptive statistics for the variables may be found in the electronic appendix (A.3.2).

  25. 25.

    In this table, I focus on the main variables. The full table can be found in the electronic appendix (A.4)

  26. 26.

    The differences in the average effect are explained by small differences in the samples used in the two analyses as a result of missing data and the fact that the sample now is restricted to the two main lists in each city.

  27. 27.

    When “victory margin” is not centered around its mean, “majority” is not statistically significant, providing an alternative means for concluding that when political competition is intense, political connections have little effect.

  28. 28.

    The other results are reported in the electronic appendix (A.4).

  29. 29.

    As detailed in the electronic appendix (A 5.2), the quality of these data is low, and results should be interpreted with caution.


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I benefited from discussions with Carles Boix, Philippe de Donder and Karine Van der Straten. Emmannuelle Auriole, Filip Kostelka, Julie Lassébie, Justin Leduc, Thierry Madiès, Mohamed Saleh, Albert Solé-Ollé and Emmannuel Thibault also provided me with useful comments. Two anonymous reviewers provided extremely useful advice and helped me improve the manuscript. I also thank Benjamin Vignolles, Benoit Petinat and the SOeS team from the Ministère du Développement Durable, who provided me with data and information. All errors are mine.

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Lévêque, C. Political connections, political favoritism and political competition: evidence from the granting of building permits by French mayors. Public Choice 184, 135–155 (2020). https://doi.org/10.1007/s11127-019-00718-z

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  • Political favoritism
  • Local elections
  • Building permits
  • Mayors
  • Housing supply

JEL Classification

  • R31
  • R50
  • D73