Appendix C: Excluded municipalities

Dans le document Essays on location choice: agglomeration, amenities and housing (Page 134-142)

I exclude from the sample 24 excluded municipalities with a total stock of housing that does not exceed 50 dwellings. These are small jurisdictions with an average population of 77 inhabitants and an average size of 5 square kilometers. On average, these municipalities are located 52 kilometers away from Paris (with a standard deviation of 21 kilometers).

These jurisdictions have been excluded as they are often characterized by extreme vacancy rates. The latter indeed take values between 0 and 58% in these locations. The following map represents the location of these excluded municipalities. The results are similar when including these outliers in the analysis (results not reported).

Figure 3.12: Location of excluded municipalities (with fewer than 50 dwellings)

App endix D: Correlations b et w een indicators of comm uting cost

Table3.11:Cross-correlationtable Variables1DistancetotheCBD2345678 1DistancetotheCBD1.000 2Directconnection(dummyvar.)-0.355*1.000 3Commutingtime0.836*.1.000 4Nb.oftrainstations-0.266*.-0.273*1.000 5Nb.oftrains-0.480*.-0.522*0.173*1.000 6Commutingcost0.127.0.227*-0.062-0.1171.000 7Dist.tocloseststation0.642*-0.547*0.025-0.060-0.024-0.0011.000 8Totalcommutingtime0.761*-0.532*0.999*-0.270*-0.522*0.227*0.970*1.000 *Significantat1%significancelevel

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This collection of essays explores the determinants and effects of location choices faced by economic agents. It addresses the three following questions: firstly, what are the determinants of a location choice across cities? Secondly, what are the consequences of these individual decisions and the effect of the spatial concentration of workers? Thirdly, once working in a large city, how do individuals allocate themselves within that urban area? This thesis answers these questions by looking at three specific dimensions of these location choices: the role of consumption amenities, the effect on the entry into the working life, and the influence of distance and transport to the center of a city.

Each essay is concerned with the interaction between urban economics and other strands of research. The first essay follows on from Richard Florida’s analysis that de-scribes the emergence of a new socioeconomic class, the so-called creative class. This research has been influential in very different fields, including economics, sociology, re-gional sciences, political sciences and socio-economics. Existing analyses from these vari-ous strands of research have been influential to formulate the research question addressed in this chapter, and to identify the main issues faced by previous empirical works. Besides, this essay indirectly questions the ambition and efficacy of economic policies oriented to-ward the arts. In that respect, it completes other analyses performed in the fields of urban planning and political sciences.

The second chapter is also multidisciplinary as it directly combines two types of anal-yses. Evaluating the sources of agglomeration economies is one of the main questions handled by researchers in the field of urban economics. To approach this question, this chapter uses tools and concepts proposed by researchers in the fields of labor and educa-tions economics. It also directly contributes to these fields but exploring the influence of a new variable that affects young workers’ ability to find jobs related to their field.

To finish, the last essay combines elements from the fields of labor economics, real estate and transportation economics. By asking questions related to affordability and accessibility of housing in big cities as well as workers’ commuting behaviors, it also indirectly contributes to recent policy debates. Striking examples include the design of the Grand Paris and the extension of existing transport infrastructures in that area, or recent debates about the requisition of vacant homes in large cities. Both have attracted much attention over the last years.

1.1 Analysis of the wage and rent equations . . . 15

1.2 Wages and rents according to the relative specialization of cities in 2010 . . 19

1.3 Rent regressions . . . 21

1.4 Wages regressions . . . 22

1.5 Alternative measure: access to cultural goods and services . . . 27

1.6 Alternative measure: access to cultural goods and services (with fixed-effects) 28 1.7 Seemingly Unrelated Regressions - cultural employment . . . 30

1.8 Concentration index and location quotients - Rent equation . . . 31

1.9 Concentration index and location quotients - Wage equation . . . 32

1.10 Employment and population growth . . . 35

2.1 Summary statistics . . . 47

2.2 Baseline regressions . . . 54

2.3 Matching: Neutralizing the influence of Paris and the biggest areas . . . . 56

2.4 Robustness check: Highest degrees and agglomeration . . . 58

2.5 Alternative methods of estimation . . . 60

2.6 Instrumental variables . . . 65

2.7 Spatial Sorting: ability . . . 67

2.8 Spatial Sorting: mobility . . . 68

2.9 Spatial Sorting: mobility . . . 69

2.10 Spatial Sorting: mobility . . . 70

2.11 Spatial Sorting: mobility . . . 71

2.12 Wage regressions . . . 73

2.13 Wage regressions - Robustness checks . . . 77

2.14 Wage regressions - Instrumental variables . . . 79

3.1 Stock of housing by occupancy status . . . 92

3.2 Between and within variations of vacancies in Parisian municipalities . . . 94

3.3 Growth rates of housing supply in the Paris metropolitan area (1968 - 2011) 95 3.4 Characteristics of housing units (in %) . . . 95

3.5 Baseline regressions . . . 107

3.6 OLS estimations . . . 110

3.7 Robusteness checks . . . 112

3.8 Neighborhood and Sensitive urban zones . . . 113

3.9 Regression with commuting . . . 117

3.10 Summary statistics . . . 120

3.11 Cross-correlation table . . . 122

1 Rents and population . . . 2

2 Crime rates and population . . . 2

3 Wages and population . . . 3

4 Amenities and population . . . 4

1.1 Local amenities in a spatial equilibrium . . . 14

1.2 Wages, rents and culture (average over 2005-2011) . . . 19

2.1 Employment density in French employment areas . . . 48

2.2 Historical provinces and capitals . . . 61

2.3 Historical remoteness and current employment density . . . 63

2.4 Correlation between employment density and historical population density 63 2.5 Average wage by employment area . . . 72

2.6 Marginal effect of employment density (in log) on wages, conditional on skill match. . . 75

2.7 Marginal effect of skill match on wages, conditional on employment density. 75 3.1 Evolution of housing vacancy rates (1968-2011) . . . 91

3.2 Housing vacancy rates in the Paris area . . . 93

3.3 Evolution of housing vacancy rates in the Paris area (1968-2011) . . . 94

3.4 Equilibrium rent and perceived market tightness in c . . . 100

3.5 Beveridge curve and equilibrium u and v inc. . . 101

3.6 Beveridge curve and equilibrium u and v inc and c0 . . . 102

3.7 Equilibrium rent and market tightness with commuting costs . . . 103

3.8 Commuting patterns in the Paris area . . . 105

3.9 Location of train stations in the Paris area . . . 114

3.10 Commuting modes . . . 115

3.11 Effect of a rise in κ . . . 119

3.12 Location of excluded municipalities (with fewer than 50 dwellings) . . . 121

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