Urban Mobility: Learning from Experiments and Policy Evaluations. Simon Franklin, LSE

Transcription

1 Urban Mobility: Learning from Experiments and Policy Evaluations Simon Franklin, LSE

2 What are the costs of poor transport connections in sprawling cities? Evidence can be hard to come by. Large scale policy evaluations (eg. BRT, Addis LR) 1 Lack of good counterfactuals. 2 Data requirements: baseline data before projects start. 3 Projects have multiple effects: housing, displacement, congestion, commuting.

3 What are the costs of poor transport connections in sprawling cities? Evidence can be hard to come by. Large scale policy evaluations (eg. BRT, Addis LR) 1 Lack of good counterfactuals. 2 Data requirements: baseline data before projects start. 3 Projects have multiple effects: housing, displacement, congestion, commuting. Mechanism experiments are useful to answer key questions. Complement to policy evaluations.

4 How can we use experiments to inform urban transport policy? 1 Provide evidence on specific costs of poor transport infrastructure. Motivate and inform the design of transport projects.

5 How can we use experiments to inform urban transport policy? 1 Provide evidence on specific costs of poor transport infrastructure. Motivate and inform the design of transport projects. 2 Identify populations who particularly high mobility constraints. Who needs particular consideration in the design of projects? 3 Limitations of experimental approaches But can be used at early stages to inform policy evaluation.

6 Example: Transport Subsidies in Addis Ababa We ask the question: Do high transport costs hinder job search? One of many ways that poor mobility can affect cities. We find that transport costs do matter: Reducing transport costs increases job search and improves employment outcomes. Labour market exclusion: Young people, women, the poor, face particularly high barriers to searching for jobs.

7 What we do: Two papers Anonymity or Distance? Job Search and Labour Market Exclusion Girum Abebe, Stefano Caria, Marcel Fafchamps, Paolo Falco, Simon Franklin, Simon Quinn. (NBER Working Paper) & Location, Search Costs, and Youth Unemployment: Experimental Evidence from Transport Subsidies. Simon Franklin (Forthcoming, Economic Journal).

8 What we do: Intervention We offer a monetary reimbursement, available at a central location, 3 times per week, for an average of 16 weeks. Calibrated to cover the cost of a single return trip to the centre. Median = $ 1, Max = $ 1.50, Min = $ The intervention costs 19.8 USD per person.

9 What we do: RCT timeline A randomized trial that reduces search costs for a specific period of time. 1 Representative baseline listing of locations around Addis Ababa. 2 Sampling of unemployed youth, and baseline survey. 3 Randomization assignment. 4 Track labour market outcomes with a high-frequency phone survey. 5 Endline survey 1 year later. Compare people who received transport subsidies to those that did not, to estimate causal effect of reduced transport costs.

10 Context: Labour market in Addis Ababa: 1 A high proportion of insecure, poorly-regulated jobs that are taken disproportionately by the youth. 3 Search is costly. For active job-seekers median expenditure on job search amounts to 16 percent of overall expenditure. Picture

11 Distance and labour market informality

12 Results Overview of Results In both experiments we find: Large and significant average effects of subsidies on the probability of having a good job. Larger experiment allows us to look at subgroups: Impacts are strongly concentrated among young people who lower existing opportunities.

13 Results Impacts for low-education job seekers Mean Post-secondary education Only completed high-school Employed Wage Employed Permanent Job Formal Job Outcome Employed Wage Employed Permanent Job Formal Job Outcome Control Mean Transport Workshop 90% CI for treatment effect

14 Results Impacts for women Mean Male Female Employed Wage Employed Permanent Job Formal Job Outcome Employed Wage Employed Permanent Job Formal Job Outcome Control Mean Transport Workshop 90% CI for treatment effect

15 Results Distance and labour market informality

16 Results Mechanism: increased search effort for formal jobs.

17 Results What do/ don t we learn about the likely effects of urban transport projects? Experiments like this can: 1 Motivate and improve the design of transport projects, 2 Understand the likely winners/losers, 3 And lead to design of better policy evaluations. A form of pre-evaluation. More research required to understand the full effects of projects: Household mobility, Commuting, General equilibrium effects. Role for careful large-scale policy evaluations.

18 Results Moving away from the experimental ideal: How do we generate credible evidence from policy evaluations, that we can can t get from experiments?

19 Results Moving away from the experimental ideal: How do we generate credible evidence from policy evaluations, that we can can t get from experiments? 1 Panels of households and locations before and after the implementation of projects. 2 Spatially representative baseline before the project. Baseline does not need to be detailed. 3 Commuting flows linked to households/wage outcomes. Partition/sieve survey to pin down workers place of employment. 4 High frequency phone surveys (feasible in cities). Key idea: large-scale geo-referenced listing of urban locations in advance of new projects.