Constructing Africa’s Cities: Estimating the value of construction worker jobs

Last registered on December 21, 2022

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Pre-Trial

Trial Information

General Information

Title

Constructing Africa’s Cities: Estimating the value of construction worker jobs

RCT ID

AEARCTR-0006085

Initial registration date

June 29, 2020

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published

June 30, 2020, 12:14 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated

December 21, 2022, 12:11 PM EST

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Country

Senegal

Region

Primary Investigator

Name

Carol Newman

Affiliation

Trinity College Dublin

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Martina Kirchberger

PI Affiliation

Trinity College Dublin

Contact Investigator

PI Name

Sveta Milusheva

PI Affiliation

DIME, World Bank

Contact Investigator

Additional Trial Information

Status

On going

Start date

2020-07-06

End date

2024-09-30

Keywords

Labor

Additional Keywords

Jobs, Construction, Senegal

JEL code(s)

O12, O18, M53, J62

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

Rapid population growth is a key development challenge facing the African continent in the coming decades. Africa’s population, which currently stands at 1.31 billion, is set to grow to 1.68 billion by 2030. This will place huge demands on many sectors of the economy and raises major concerns about how to provide jobs and livelihoods for Africa’s youth. Rapid population growth and urbanization is also placing substantial demands on Africa’s infrastructure with major investments in public infrastructure, including transport, telecommunications and public housing, crucially needed. The labor-intensive nature of such projects provides an opportunity for job creation in the sector, which is one of the main sectors of employment for young men. However, there is no evidence of the effects of jobs created in big infrastructure projects. The central question underlying this project is what the returns from such job opportunities are.

The setting for our project is Dakar, Senegal. The Government of Senegal (GoS) has recognized that improving urban mobility in the Greater Dakar Area (GDA) is of crucial importance for the development of the Senegalese economy, and it has adopted a comprehensive 5-year plan to address some of the challenges that the sector faces. One of the flagship projects of this plan, with strong presidential support, is a modern bus transport system with high level of service (BRT) linking the city center to the north of the city. Construction on the BRT will begin in June 2020 and is estimated to continue for 20 months. It is expected that there will be between 2000 and 3000 workers employed in the construction of the BRT during this period. Given the large scale of this project, in terms of both cost and number of workers, we aim to study the impact of the jobs created on the welfare of the workers that are hired and their medium-term future employment outcomes. With the BRT construction expected to have additional phases and with plans to replicate the project in other west African cities, it is important to understand the costs and benefits incurred by the construction workers in order to understand whether and how, in future phases of this project and in future infrastructure projects more generally, costs can be minimized for workers and benefits can be increased through complementary programs. We will collaborate with CRBC, the contractor selected for the construction of the BRT.

Using a randomized controlled trial, we will test the impact of receiving a job offer to work on this project. We use the fact that there are much fewer jobs than there are eligible workers to randomly assign jobs to applicants thus creating a control group of workers who do not get a job.

Our project will contribute to two key strands of academic literature. First, recent evidence using micro survey data across countries shows that compared to high-income countries, labor markets in low-income countries are characterized by higher turnover rates, steeper tenure profiles, flatter experience profiles and significant matching frictions (Donovan et al 2020, Bicks et al 2018, Abebe et al 2020). Donovan et al (2019) argue that the high turnover rates and steeper tenure profiles are consistent with theories of endogenous separation, proposing the learning model of Jovanovic (1979) and the job ladder model of Burdett and Mortensen (1998). The randomization of the job offer, in combination with detailed data on key variables such as match quality, search intensity and outside offers, allows us to understand the role of endogenous separation for labor market outcomes in low-income countries. This enables us to test, for example, whether match quality leads to a stronger wage-tenure relationship, as well as the role of search intensity and outside offers for labor market outcomes. Second, we contribute to the broader literature examining the impact of transportation investments on welfare since while job creation is cited as a benefit of these projects, there has been no in-depth examination of this claim.

External Link(s)

Registration Citation

Citation

Kirchberger, Martina, Sveta Milusheva and Carol Newman. 2022. "Constructing Africa’s Cities: Estimating the value of construction worker jobs." AEA RCT Registry. December 21. https://doi.org/10.1257/rct.6085-1.1

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

The study will involve an impact evaluation of employment in the construction of the BRT on the welfare of workers

The recruitment of workers for the construction of the BRT is through the local communities. Low skill workers register as interested with their local CIS (Centre d’Information et de Suivi) committee. When construction work begins in a particular area, the construction company will choose workers from that CIS list. By randomizing the order in which the names appear on the list we can randomly select which eligible workers receive a job.

Intervention Start Date

2020-08-10

Intervention End Date

2023-06-30

Primary Outcomes

Primary Outcomes (end points)

We will examine the impact of obtaining a construction worker job and the work experience that this brings on worker outcomes including wage, worker retention, promotion, job satisfaction, and later labor market outcomes including whether the worker finds subsequent employment once the current contract ends, the length of time it takes to find a new job, wage at the time of commencing a new job, job satisfaction at new job. The high-frequency data will allow us to examine the transitional dynamics and help estimate the role match quality, search intensity and outside offers play for labor market outcomes of respondents.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

We will also test the impact of obtaining the job on household welfare.

Secondary Outcomes (explanation)

Experimental Design

The overarching treatment being tested in this impact evaluation is the randomization of the offer of a construction worker contract. We are aiming to get all lists of potential candidates from all communities. While it is impossible to a priori know the number of applicants who come forth, we estimate that our sample size will include a minimum of 1,000 people. ANSD (Statistical office) Senegal predict that there are approximately 28,000 unemployed individuals of working age in the area of study and potentially 115,000 eligible candidates. Randomization will take place at the individual level.

- 500 treatment workers will be offered a job to work on the construction of the BRT
- At minimum 500 control workers, although eligible, will not be offered a contract

The primary instruments for data collection will be a baseline and end-line surveys of all workers in treatment and control groups along with high-frequency phone interviews that will be conducted with all participants on a monthly basis to collect key labor market outcomes.
It is expected that the baseline survey will begin in July 2020. It will take place on a rolling basis as the area under construction expands and new lists are drawn up. All workers will be surveyed before the job offer is made. The high-frequency phone surveys will take place monthly for all participants in the study. The end-line survey will be carried out approximately one year after the start of the contract.

Experimental Design Details

To ensure that all of the potential outcomes are covered by the survey and that information on a wide range of suitable control variables is collected, the baseline and end-line surveys will be similar to a standard long form household survey, intended to understand as much of the socioeconomic picture of each household as possible. This will include modules on household demographic information; income, assets and consumption; travel frequency and travel time. Additionally, the survey will contain individual labor market and health questions for the individual to cover all of our primary and secondary outcomes of interest.

The high-frequency phone interviews will focus on the employment status of the respondents, including hours worked, wages, the type of employment, job search, job offers and satisfaction. Gathering high-frequency data will allow us to closely monitor the dynamics of the labor market in Dakar, not only for those who are employed on the construction project, but also for the control group. This will allow us to track the evolution of those outcomes over the course of the project by studying transitions into and out of the labor market, the arrival of outside offers, and recovering the returns to particular types of labor market experiences. We will also be able to study the role of match quality on transitional dynamics.

Randomization Method

The recruitment of workers for the construction of the BRT is through the local communities. Low skill workers register as interested with their local CIS (Centre d’Information et de Suivi) committee. In some cases, the lists will be compiled by the local townhall or the construction company where there is no CIS. We will use the same approach to randomizing the job offers from these lists. These committees were organized by CETUD, the government agency in charge of overseeing the construction of the BRT with the goal of engaging the local communities and ensuring buy-in from these communities. The CIS board consists of volunteers, usually those that are well-known in the community such as the neighborhood chiefs. Those in the community interested in working on the BRT go to a member of the CIS board and let him or her know, and the board members puts the person on a registry list of interested people. CETUD organizes community sensitization meetings before work is about to start in an area, and these meetings are when those in the local community are told about the potential job opportunities and the process for expressing interest in these jobs through the CIS. Individuals are only allowed to apply to one list and their address is recorded at time of registration to ensure that only those living within the area of the CIS apply for the list.

When construction is underway in a particular area, the construction company will choose workers from that CIS list. Companies do this kind of local recruitment in order to engage the local communities and ensure that work opportunities are somewhat shared among different parts of the city. After an application list has closed and before hiring has begun, we will work with the Community Leaders in each area to draw up a list of eligible workers. From this list, workers will be ordered randomly. We will stratify by age and gender. This is the order in which the names will be given to the construction company and they will give job offers to workers in this order. The fact that the jobs being offered require very basic skills, the construction company have no specific preference on what type of person they hire so long as the age condition is met. Given that there are more workers than there are jobs available, those workers that are not selected will be used as the control group. All eligible workers on the list will be surveyed before the construction starts to gather baseline information.

Randomization Unit

The unit of randomization is the individual.

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

Minimum 1000 individuals

Sample size: planned number of observations

Minimum 1000 individuals

Sample size (or number of clusters) by treatment arms

500 individuals to receive a construction worker job and 500 individuals in the control group.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

To determine the appropriate sample size, we consider two main outcomes: wage income and worker retention. With an average daily wage of 4251.9 FCFA and a standard deviation of 2003.3 FCFA, we can detect an effect size of 5 percent with 80% power. To date, there has been little experimental evidence on the impact of job offers. Blattman and Dercon (2016) find no average treatment effect of the job offer on earnings. Having the power to detect effect sizes of 5 percent thus seems reasonable.

Supporting Documents and Materials

IRB