Does city structure cause unemployment?

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1 The World Bank Urban Research Symposium, December 15-17, 2003 Does city structure cause unemployment? The case study of Cape Town Presented by Harris Selod (INRA and CREST, France) Co-authored with Sandrine Rospabé (CREREG, France) 1

2 Introduction City structure can deteriorate labor-market outcomes: Mismatch between residences and job opportunities. Residential segregation. South African cities are characterized by: Sprawl. Racial segregation. Objective: A case-study relating unemployment to city-structure. Urban unemployment in South Africa 2

3 This presentation 1. Urban unemployment: some elements of theory. 2. Some stylized facts on Cape Town. 3. The data, sample, and methodology. 4. The empirical analysis. Urban unemployment in South Africa 3

4 1. Elements of theory Distance to job opportunities prevents workers from finding and keeping well-paid jobs (i.e. the spatial mismatch hypothesis, Kain, 1968, Ihlanfeldt and Sjoquist, 1998, Gobillon, Selod, Zenou, 2003): Long and expensive commuting costs (possibly exacerbated by an inefficient public transportation system) might deter some workers from accepting jobs. Job search is less efficient (lack of information about jobs) or less intense (low frequency of search trips, weak incentives to search) at a distance from job opportunities. Urban unemployment in South Africa 4

5 Segregation deteriorates labor-market outcomes (Cutler and Glaeser, 1997): It impedes local investments in human capital (Benabou 1993, Selod and Zenou, 2001, 2003). It fosters socially deviant behaviors that affect employability (Crane, 1991). It deteriorates social networks and information people have about jobs (Holzer, 1988, Ihlanfeldt, 1997, Selod and Zenou, 2003). It facilitates the stigmatization of neighborhoods and territorial discrimination (Zenou and Boccard, 2000). Urban unemployment in South Africa 5

6 2. Stylized facts on Cape Town Urban unemployment in South Africa 6

7 A metropolitan area ( 2.7 million inhabitants) with much inequality Table 1. Social stratification in Cape Town Blacks Coloureds Asians Whites Percentage 26.2% 48.9% 1.4% 23.5% School levels of the labor force (1996) % no schooling % post secondary 6.8% 3.4% 3.1% 5.2% 2.4% 15.9% 0.7% 29.8% Unemployment rates (1996) 37.8% 17.6% 10.6% 4.1% Household disposable income (1996) R 14,156 R 33,658 R 51,381 R 73,572 Proportion of group living below the subsistence level (1999) 48% 27% 20% 4% Urban unemployment in South Africa 7

8 a high level of residential segregation: Table 2. Duncan&Duncan Indices (1996) Blacks/ Blacks/ Blacks/ Whites/ Whites/ Coloureds/ Whites Asians Coloureds Asians Coloureds Asians 92.8% 94.5% 93.5% 76.3% 86.1% 63.3% and a disconnection between places of work and residence: < See following maps > Urban unemployment in South Africa 8

9 Urban unemployment in South Africa 9

10 Urban unemployment in South Africa 10

11 Urban unemployment in South Africa 11

12 Urban unemployment in South Africa 12

13 Urban unemployment in South Africa 13

14 Urban unemployment in South Africa 14

15 Urban unemployment in South Africa 15

16 Urban unemployment in South Africa 16

17 3. The data used (i) Regional Service Council (RSC) Levy database (2000): All firms and establishments paying a local tax. Enables to identify the locations of formal salaried jobs. (ii) Census of the Population (1996): Information on neighborhood composition. Coupled to the RSC Levy database: job densities. Urban unemployment in South Africa 17

18 (iii) Migration and Settlement in the CMA (1998): 990 households (4,299 individuals) living in 25 randomly selected areas in Cape Town. Places of residence and places of work; transportation; Urban unemployment in South Africa 18

19 Approach: Explain the probability of unemployment P i of a worker i, using a logit model: Log (P i /1-P i )=α+βi i +γh i +δn i where I i =personal characteristics H i =household characteristics N i =neighborhood characteristics Sample: All economically active individuals in the migration study aged 15 to 65: 1,877 observations. Urban unemployment in South Africa 19

20 4. The empirical analysis Results obtained so far: The chances of unemployment are exacerbated by spatial factors: Distance to jobs Rural origin (especially for women) Residential inertia Urban unemployment in South Africa 20

21 Table 3. The influence of individual characteristics Model I II III IV Black/African.931 ***.966 ***.930 ***.629 ** Coloured NS NS NS NS Indian/Asian NS NS NS NS Male ***.030 NS *** *** Age *** *** *** *** Age square.002 ***.002 ***.002 ***.002 *** Primary education NS NS NS NS Secondary education *** *** ** * Tertiary education ** ** ** * Couple * * * NS Head of household *** *** *** *** Time spent in present dwelling.017 **.017 **.021 ***.021 *** Rural birth area.434 ***.811 ***.394 **.394 ** Rural birth area*male ***

22 Table 3 (cont d). The influence of household and neighborhood char. Model I II III IV Household characteristics Ownership of the dwelling *** *** Access to electricity *** ** Neighborhood characteristics Median income of the EA ** Average commuting distance for residents in the EA.035 * Job density.267 NS Intercept *** *** *** *** Likelihood ratio % observ. correctly predicted 77% 76.5% Number of observation 1,877 1,877 ***1% significance; ** 5%; * 10%; NS: not significant % 1, % 1,870

23 Conclusion and perspectives Space matters. Perspectives: Strengthen the econometric analysis. Identify the main mechanisms of exclusion and propose adapted policy measures. Replicate this study to other cities in the developing world. Urban unemployment in South Africa 23

Does city structure cause unemployment? The case of Cape Town

7Sandrine Rospabe and Harris Selod Does city structure cause unemployment? The case of Cape Town Introduction In June 1998, the South African newspaper The Star told the story of a 46-year-old single mother