Promoting economic inclusion at scale through self and wage employment support

Last registered on October 31, 2022


Trial Information

General Information

Promoting economic inclusion at scale through self and wage employment support
Initial registration date
October 20, 2022

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
October 31, 2022, 10:38 AM EDT

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


Primary Investigator


Other Primary Investigator(s)

PI Affiliation
PI Affiliation

Additional Trial Information

On going
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
The study aims to evaluate the impacts of a large-scale flagship social protection program in Tanzania, the Productive Social Safety Net (PSSN). The PSSN is based on integrated interventions targeted to the poorest households: conditional cash transfers, a labor-intensive public works (PW) program, and a livelihood program that includes business training and a large business grant. The impact evaluation study is conducted in villages from 17 regions in Mainland and Zanzibar. It uses a multi-arm cluster (villages) RCT design to examine the relative combined impacts of the self-employment support component (i.e., livelihood) and the wage employment component (i.e., public works) as part of a large-scale expansion of these components. It further cross-randomizes the mode of payment (digital vs. manual) to understand the impact of digital e-payment, with particular attention to gender outcomes.
External Link(s)

Registration Citation

COVILLE, AIDAN, DAHYEON JEONG and PATRICK PREMAND. 2022. "Promoting economic inclusion at scale through self and wage employment support." AEA RCT Registry. October 31.
Sponsors & Partners


Experimental Details


This study sits in the context of the first government-led large-scale social protection operation to provide comprehensive livelihood support to poor households. The Government of Tanzania (GoT), with the support of the World Bank and several development partners, has been implementing the Productive Social Safety Nets (PSSN) program since 2012. PSSN’s objective is to support the poorest households in the country to meet their minimum consumption needs, promoting the human capital of their children by incentivizing the utilization of education, health and nutrition services, and promoting income-generating activities. The program is structured around three components: Conditional Cash Transfers (CCTs), Labor-Intensive Public Works (PW), and Productive Inclusion / Livelihoods Enhancement measures. PSSN was massively scaled up in 2015, reaching over one million extremely poor households in about 10,000 villages throughout the country. A further extension of the program – extending coverage to all remaining villages in Tanzania - is currently underway and, to date, PSSN extends CCTs to almost 1.4 million households.

During this second phase of the program (PSSN II – between 2019 and 2025), the GoT committed to massively expanding two economic inclusion components: public works and enhanced livelihood programs to enhance the impact of CCTs and sustainably lift households out of poverty.

First, the main motivation of the PW component is to offer temporary employment opportunities during the agricultural lean season to raise earnings and help them smooth consumption. It provides households with an entitlement of 60 working days per year. The transfer size for PW payment is set in such a way that it is at or below the daily market wage rate for unskilled labor. The daily wage rate will be US$1.3, and one can earn up to approximately US$80 per year.

Second, households will also be offered a “livelihood enhancement” package. After undergoing basic personal finance training, beneficiaries will receive assistance towards the preparation of simple business plans, undergo orientation sessions on how to manage businesses, and be awarded a business grant estimated at US$225), followed by 6 months of mentoring and coaching.

Finally, e-payments will be rolled out throughout the country. Currently, about 19% of beneficiaries receive benefits electronically. By 2025, the option to be paid electronically will be available to all beneficiaries of PSSN, significantly strengthening the financial inclusion aspects of the program.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Data will be collected through baseline and endline household surveys, answered by the female lead on behalf of her and household members.

Main outcomes of interest to be measured, at the household and individual levels are consumption, food security, coping strategies in response to shocks, women empowerment, gender-based violence, savings, credit, enterprises and investments, labor and use time, housing and assets, livestock, farming activities, education, and health.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This study uses a multi-arm cluster randomized controlled trial (RCT) to examine the relative and combined impacts of the enhanced self-employment support component (i.e., enhanced livelihood) and a wage employment component (i.e., public works), and cross-randomizes the mode of payment (digital vs. manual) to understand the impact of digital e-payment.

The study considers villages corresponding to regions in the domains of Mainland and Zanzibar, Tanzania with the following sampling frame:
Mainland - 1553 villages from 41 PAAs in 19 regions
Zanzibar - 190 villages from 11 PAAs in 5 regions

1. In the first stage, 32 PAAs were randomly selected out of 52 PAAs in the sampling frame.
2. In the second stage, one village was randomly selected per ward (if there were multiple villages in each ward in the sampling frame).

The final selected sample was set at 434 villages from 14 regions in Mainland and 3 regions in Zanzibar. These villages were then divided into two groups: a) those that already received some support of switching to e-payment (226 villages); and b) those which haven’t switched e-payments (208 villages). Only those villages that have not been encouraged to use the e-payment cash transfer delivery option by the implementing agency yet, are planned to be part of the cross-randomization to assess the comparison between manual payments versus e-payments.

Villages will be randomly assigned into the following treatment arms (please note that all 434 villages will receive the basic livelihoods package as well as the cash transfer component): a) enhanced livelihoods, b) public works, c) public works and enhanced livelihoods, d) controls. For the e-payment evaluation (208 villages), villages will be further randomized into cash payments and digital payments (e-payments).

For the sampling of households, all households in the selected villages will be defined into the following types:

• Type 1: those nominated by communities AND interviewed by TASAF for PMT AND above the selection threshold (i.e., beneficiaries);
• Type 2: those nominated by communities AND interviewed by TASAF for PMT BUT below the selection threshold;
• Type 3: those NOT nominated by communities AND NOT interviewed by TASAF.

Type 1 households are potential PSSN beneficiaries that can be identified in both control and treatment groups, depending on how their villages will be randomly assigned to the different groups. Type 2 and Type 3 households are not PSSN2 beneficiaries, but we compare the characteristics of households between Type 1, 2, and 3 to assess the accuracy of the TASAF targeting rule. The number of households to interview is 29 households per village (i.e., 17 HHs for Type 1, 8 HHs for Type 2, and 4 HHs for Type 3).

Overall, there are two types of analysis that this study will perform:

- Analysis I - IE analysis of PSSN programs on beneficiaries: For this analysis, the sample of households will be randomly drawn from the households classified as “poor” in the PMT data (type 1). Therefore, there is no need to do a listing of households for this analysis. Since the PMT data is at the village level, the analysis will be done at the village level as well.

- Analysis II - Targeting exercise and spillover analysis: To test the validity of the targeting methods, we will have to compare poverty characteristics of type 1, type 2, and type 3 households. And the sample of households for each type needs to be drawn from a sampling frame that covers the same area. For example, comparing type 1 households that are drawn from the entire village with type 3 households that are drawn from only one sub-village is not valid. Similarly, if we want to measure how the impacts of PSSN programs are different between beneficiaries (i.e., type 1 households) and non-beneficiaries (i.e., type 2 and type 3 households) then type 1-3 households need to be sampled from the same area to ensure comparability. Therefore, for targeting exercise and spillover analysis, we will rely on the listing exercise to create a sampling frame from which we can randomly draw a sample of all three types (i.e., 4 type 1 households, 4 type 2 households, and 4 type 3 households).
Experimental Design Details
Not available
Randomization Method
Randomization was done in office by a computer, using STATA.
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
434 villages.
Sample size: planned number of observations
12,586 households.
Sample size (or number of clusters) by treatment arms
• 226 villages NOT part of the e-payment evaluation
* Enhanced livelihoods (EL) – 57 villages
* Public works (PW) – 56 villages
* PW + EL – 56 villages
* Control – 57 villages

• 208 villages for e-payment evaluation
o Digital/E-payments (104 villages)
* Enhanced livelihoods (EL) – 26 villages
* Public works (PW) – 26 villages
* PW + EL – 26 villages
* Control – 26 villages
o Manual cash payments (104 villages)
* Enhanced livelihoods (EL) – 26 villages
* Public works (PW) – 26 villages
* PW + EL – 26 villages
* Control – 26 villages
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Solutions IRB
IRB Approval Date
IRB Approval Number
#2021/09/24, Promoting economic inclusion at scale through self and wage employment support