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General

Study Overview

Title:

Competition Constrains Adaptation to Climate Shocks

Study is 3ie funded:

No

Study ID:

RIDIE-STUDY-ID-662be9f821fd1

Initial Registration Date:

04/26/2024

Last Update Date:

12/12/2023

Study Status:

Ongoing

Location(s):

Ghana

Abstract:

How does market structure affect climate adaptation decisions? Using detailed weather and financial transaction records at small retail vendors from Ghana’s leading mobile money provider, we document evidence of adaptation and the effects of competition. To estimate the impacts of competition on adaptation, we exploit exogenous variation linked to the feasibility of the network infrastructure and a competition policy that made transactions interoperable. Unexpected temperature reduces sales revenue (-1.40%), seller’s presence, and the number of customers. Accurate forecasts reduce this adverse effect by 50%, highlighting the value of forecast information for adaptation. Firm adaptation is, however, limited in more competitive markets, which we show is due to increased coordination failures and costs. The results point to an unintended negative climate adaptation effect of policies that increase competition in retail markets.

Registration Citation:

Categories:

Environment and Disaster Management
Other

Additional Keywords:

Climate Adaptation, Mobile Money Retailing, Household Finance, Weather Forecasts, Market Competition

Secondary ID Number(s):

Principal Investigator(s)

Name of First PI:

Francis Annan

Affiliation:

University of California, Berkeley

Name of Second PI:

Edem Klobodu

Affiliation:

Queen's University

Study Sponsor

Name:

N/a

Study Sponsor Location:

Ghana

Research Partner

Name of Partner Institution:

n/a

Type of Organization:

Other

Location:

Ghana

Intervention

Intervention Overview

Intervention:

We examine how adaptation varies under different competition intensity (i.e., high vs. low). Since competition is not randomly assigned, we capture its effects in three ways: (1) by using exogenous variation linked to the feasibility and reliability of the retail network infrastructure; (2) by using a baseline measure of competition that is not directly affected by weather conditions in estimating equation; and (3) by exploiting random variation in competition policy that enabled interoperable transactions to estimate the impact of competition on adaptation.

 

Theory of Change:

Our study explores how competition impacts retail vendors' adaptation to weather shocks, using exogenous variations related to retail network infrastructure and interoperable transaction policies. We find that weather shocks decrease sales, with more agent absence and fewer customer visits. Forecast provision, however, mitigates this sales decline by 50%. We hypothesize that competition impedes adaptation due to coordination failures, evidenced by customer switching and communication barriers. In competitive markets, customers often switch to closer vendors in poor weather, disrupting regular buying patterns. Moreover, competitive markets may face higher communication barriers, as agents vie for the same customers, contrasting with monopolistic markets where stable customer bases allow for consistent communication. This results in varying service quality during adverse weather conditions.

Multiple Treatment Arms Evaluated?

No

Implementing Agency

Name of Organization:

n/a

Type of Organization:

Other

Program Funder

Name of Organization:

n/a

Type of Organization:

Other

Intervention Timing

Intervention or Program Started at time of Registration?

Yes

Start Date:

01/01/2017

End Date:

Evaluation Method

Evaluation Method Overview

Primary (or First) Evaluation Method:

Difference in difference/fixed effects

Other (not Listed) Method:

Additional Evaluation Method (If Any):

Instrumental variables

Other (not Listed) Method:

Method Details

Details of Evaluation Approach:

Outcomes (Endpoints):

The outcome variables are sales revenue, number of customers and labor supply or agent presence

Unit of Analysis:

Mobile money agents or vendors

Hypotheses:

We hypothesize that:

Hypothesis 1: The provision of forecast information significantly mitigates the adverse effects of weather shocks.

Hypothesis 2: The ability of retail firms to adapt to weather shocks is negatively impacted by the presence of competition.

Unit of Intervention or Assignment:

Number of Clusters in Sample:

n/a

Number of Individuals in Sample:

15031

Size of Treatment, Control, or Comparison Subsamples:

15031

Supplementary Files

Analysis Plan:

Other Documents:

Data

Outcomes Data

Description:

The first dataset is an administrative one that comprises 15,031 sellers in the data, and the dataset covers the period from January 1, 2017, until March 31, 2019. In total, there are 12,325,420 observations of seller labor supply and 8,770, 895 observations of buyer visits and transaction amount. We obtain weather realizations and forecast data from the European Centre for Medium-Range Weather Forecasts (ECMWF). For realizations, we use the ERA5 reanalysis data.

Data Already Collected?

Yes

Data Previously Used?

No

Data Access:

Restricted -- Access requires a formal approval process

Data Obtained by the Study Researchers?

Data Approval Process:

We signed an NDA with the largest mobile money provider in Ghana to obtain the data.

Approval Status:

Yes-obtained approval and have received the data

Treatment Assignment Data

Participation or Assignment Information:

Yes

Description:

Data Obtained by the Study Researchers?

Data Previously Used?

Data Access:

Data Obtained by the Study Researchers?

Data Approval Process:

Approval Status:

Data Analysis

Data Analysis Status:

Yes

Study Materials

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Registration Category

Registration Category:

Non-Prospective, Category 4: Data for measuring impacts have been obtained/collected by the research team and analysis for this evaluation has started

Completion

Completion Overview

Intervention Completion Date:

Data Collection Completion Date:

Unit of Analysis:

Clusters in Final Sample:

Total Observations in Final Sample:

Size of Treatment, Control, or Comparison Subsamples:

Findings

Preliminary Report:

Preliminary Report URL:

Summary of Findings:

Paper:

Paper Summary:

Paper Citation:

Data Availability

Data Availability (Primary Data):

Date of Data Availability:

Data URL or Contact:

Access procedure:

Other Materials

Survey:

Survey Instrument Links or Contact:

Program Files:

Program Files Links or Contact:

External Link:

External Link Description:

Description of Changes:

Study Stopped

Date:

Reason: