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Solar Electricity in Rural Sindh: Role of Flexibility and Planning in Repayment Discipline

Last registered on October 18, 2017

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Pre-Trial

Trial Information

General Information

Title

Solar Electricity in Rural Sindh: Role of Flexibility and Planning in Repayment Discipline

RCT ID

AEARCTR-0002543

Initial registration date

October 18, 2017

Last updated

October 18, 2017 4:52 PM EDT

Location(s)

Country

Pakistan

Region

Sindh

Primary Investigator

Name

Jacopo Bonan

Affiliation

Fondazione Eni Enrico Mattei (FEEM)

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Other Primary Investigator(s)

PI Name

Massimo Tavoni

PI Affiliation

Politecnico di Milano and FEEM

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PI Name

Farah Said

PI Affiliation

Lahore School of Economics

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PI Name

Mahreen Mahmud

PI Affiliation

University of Oxford

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PI Name

Giovanna D'Adda

PI Affiliation

Politecnico di Milano

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Additional Trial Information

Status

On going

Start date

2017-03-01

End date

2018-06-30

Keywords

Environment & Energy

Additional Keywords

JEL code(s)

O13

Secondary IDs

Abstract

Almost 70 million people in Pakistan (35% of the population) do not have access to electricity, as they live in areas, mostly rural,not reached by the grid. Over 75 million (38%), while on-grid, receive low quality energy and experience outages for more than 12 hours per day (IFC 2015). In spite of the significant benefits of access to electricity, the long-run feasibility of grid expansion for the provision of quality electricity to remote areas is often a concern (Greenstone 2014). The development of market solutions to increase access and energy services in underprovided areas using renewables and alternative energy sources is essential to meet SDG 7, reduce poverty and promote growth.
We collaborate with Eco Energy (EE), a for-profit company supplying sustainable and efficient solar energy solutions (e.g. lights, fans, mobile chargers, TV) to households and small business in off-grid areas of rural Pakistan, to evaluate one such market solution. The product is innovative, as it allows to relieve credit constraints to adoption and has strong enforcement feautures: customers access energy through a pay-as-you-go monthly payment scheme and are disconnected when the credit expires.
The research provides contributions both research and policy-wise. First, we investigate key determinants of the sustainability of the business model and of product take-up, by looking at the trade-off between discipline and flexibility in repayment schedule, which is a debated issue in the microfinance literature (Labie et al. 2015 for a review). Second, we push the frontier of the behavioural and microfinance literatures, looking at individual constraints to repayment. We investigate the role of soft behavioural prompts aiming at stimulating the formulation of intentions and mental plans of action in a novel setting as low-cost solutions to lower default rates.

External Link(s)

Registration Citation

Citation

Bonan, Jacopo et al. 2017. "Solar Electricity in Rural Sindh: Role of Flexibility and Planning in Repayment Discipline." AEA RCT Registry. October 18. https://doi.org/10.1257/rct.2543-1.0.

Former Citation

Bonan, Jacopo et al. 2017. "Solar Electricity in Rural Sindh: Role of Flexibility and Planning in Repayment Discipline." AEA RCT Registry. October 18. http://www.socialscienceregistry.org/trials/2543/history/22481.

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Experimental Details

Interventions

Intervention(s)

This study specifically involves a set of products that are relevant to the needs of the poor in rural-off grid areas. These solar products are comparable in cost to what local villagers currently spend on their lighting needs and allow access to lighting, fans, chargers and TV. The system is suitable to serve off-grid areas, as well as on-grid areas as a backup option. This document outlines our experiment and our plan of analyzing the data.

We collaborate with EcoEnergy (EE), a for-profit company supplying sustainable and efficient solar energy solutions (e.g. lights, fans, mobile chargers, TV) to small businesses and households in rural Pakistan, to evaluate an innovative market solution. The product relieves credit constraints to adoption and has strong enforcement features: customers access energy through a pay-as-you-go monthly scheme and are disconnected when their credit expires. Since there is at the moment no financial penalty for late payments, these represent a pure loss for EE. Therefore, timely and quality repayments are crucial for business sustainability. The solar system can be customized to match consumer needs and allows the monthly fee, which can range from USD 8 to 30, to match what they may be currently spending on energy alternatives.

Intervention Start Date

2017-03-01

Intervention End Date

2017-12-31

Primary Outcomes

Primary Outcomes (end points)

The main outcome of the analysis pertain to the sphere of quality of payments to EE and defaults by customers. For each dimension, we will assess both the extensive and intensive margin.

Primary Outcomes (explanation)

See section 4.1 of the document attached

Secondary Outcomes

Secondary Outcomes (end points)

Actual frequency of payments and dropouts.

Secondary Outcomes (explanation)

See section 4.1 of the document attached

Experimental Design

EE conducts product demonstrations at the village or bazar level. Interested individuals and businesses are met individually and applicants that fulfil the eligibility criteria are then offered the product.

The experimental design varies the terms of the product offered to treatment group clients along two dimensions: the flexibility of the repayment schedule, and the presence of tools to reduce inattention and commitment problems in repayment.

Flexibility of payment.
In order to compare the effect of flexibility in the monthly instalment payment, we compare two types of contracts:
- A fixed contract, close to EE’s existing one under which clients will be required to make their entire payments on a monthly basis.
- A flexible contract, under which clients can decide when and at what frequency within each month they want to pay the instalment. Clients in this group will essentially be free to plan how they want to make payments within each month: at take-up, we will inform them of the daily rate and give examples of payments at different frequencies (e.g., weekly, bi-weekly, monthly, bi-monthly).

Implementation Intention Plan (IIP)
The specific screening protocol used by EE makes credit constraints an unlikely explanation for late or non-repayment. We thus focus on inattention and lack of salience as main factors behind default in this setting. To test their role, and assess the effectiveness of cheap and scalable solutions to contrast them, the proposed design randomises the offer of a planning tool to clients based on implementation plans. Drawing from literature in psychology on the use of implementation plans, we ask customers to formulate a plan for his next payments and circle the payment dates on a calendar, delivered by the enumerator, which can then be displayed at his work place or house. This process should help the subject anticipate possible issues in repayment and the strategies to overcome them.

Experimental Design Details

Randomization Method

A random generator number leading to either one or the other contract version has been incorporated in the software used by the salespersons to register new customers. The implementation intention plan intervention is delivered by the enumerator at the time of survey administration, some days after the contract is signed. The treatment is randomised by the research team via the survey software.

Randomization Unit

The level of randomization for both treatments is at the individual level, which results in a 2x2 factorial design.

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

No clusters are involved.

Sample size: planned number of observations

The study sample is expected to be formed by about 650 individuals who signed a contract with EE and installed a solar system. Customers are categorized as small business owners or households, depending on the place where the system is installed.

Sample size (or number of clusters) by treatment arms

We expect to have about 160 individuals per treatment arm.

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

Supporting Documents and Materials

IRB

INSTITUTIONAL REVIEW BOARDS (IRBs)

IRB Name

Blavatnik School of Government’s Departmental Research Ethics Committee (DREC), University of Oxford

IRB Approval Date

2017-05-22

IRB Approval Number

SSD/CUREC1A/BSG_C1A-17-010