This exercise aims to gauge your capacity to analyse a dataset and present the findings to essay

dataset and present the findings in a short two-page document

Instructions

This exercise aims to gauge your capacity to analyse a dataset and present the findings to

dataset and present the findings in a short two-page document. To analyse the dataset

please use Stata, R or Python. You may also consult any resources you like, except other

people. Please list any resources that you consulted (you can include these in your

submission).

This task will be assessed on the proficiency, efficiency, clarity and replicability of your

writing, analysis and code.

You are expected to complete this task within 24 hours of receiving it. Submissions

received after this time will not be considered.

Please submit your completed assessment documents using the link found in the email that

was sent to you informing you of the Analytical Assessment.

You should send the following documents when submitting the completed assessment:

• A Microsoft Word document (or other word processing document) of maximum

1,000 words in which you have completed the task below

• All the statistical code that you have used to do the analysis (e.g. Stata do file, R

script, Python script, or Jupyter Notebook).

• any other dataset you might have used.

Please make sure to send us back all the documents in a compressed zip file.

a non-technical audience. To complete this assessment, you will have to perform statistical analysis on a

The Task

services and the experiences of Mobile Money customers in three districts of Rwanda.

The dataset has been provided and you have been asked to write a short summary outlining

key initial findings to be discussed by the Specialist Advisory Board for the study. Members

of this Board include representatives from the National Bank of Rwanda, the Utilities

Regulatory Authority and NGO’s focussing on access to digital financial services and

associated consumer protection issues.

These key initial findings will be used to inform the next stage of the study which includes

focus group discussions with mobile money customers. Correctly identifying and

interpreting issues that negatively affect mobile money customers is very important for

prioritising topics to take forward in the qualitative research.

You are responsible for performing all the statistical analysis required and writing up the

key findings. You should remember that the target audience do not have a statistical

background.

The research manager wants you to address the following points in the key findings

document and working files:

1. During the survey, participants listed all the different types of financial account that

they have registered. The resulting data has a format where there is one observation

per account type. Format the data so that there is now one observation per

participant. (5 marks)

2. Create two dummy variables for whether each participant is: i) financially excluded

and ii) digitally financially included. What are the overall rates of financial exclusion

and digital financial inclusion for the combined population of these three districts?

(10 marks)

a. Financial exclusion is defined as not having registered for any type of

financial account including accounts with: Mobile money operators, banks,

micro-finance institutions (MFI’s), savings and credit cooperative

organisations (SACCO’s) and village savings and loan associations (VSLA’s).

b. Digital financial inclusion is defined as having at least one registered account

with a mobile money operator or an online bank account.

3. Describe in a few short paragraphs how the mobile money market is divided

between the three companies. Include at least one chart or table to illustrate your

findings. (15 marks)

4. Is there a difference in the share of customers who have experienced failed mobile

money transactions in rural and urban villages? If so, is it statistically significant?

Explain your findings including any assumptions and limitations. (15 marks)

You have recently finished the data collection for a project on the use of Mobile Money

5. What variables are good predictors that someone will cancel their mobile money

account? Discuss what causes a customer to stop using their mobile money account

including how strong the evidence is. (20 marks)

Additional marks will be given for:

• The client readiness of your written document (5 marks)

• The quality of your code (5 marks)

TOTAL: 75 marks

Annex 1: Variable description

Variable Description

hhid Household ID

weight Sampling Weight

account_num Account Number

account_type Type of account

district District of household

urban Household location in urban or rural village

gender Gender

age Age

hh_members Number of household members

highest_grade_completed Highest grade completed

mm_account_cancelled Has cancelled a mobile money account in the past

prefer_cash Preference for cash over cashless payment methods

mm_trust Do you trust mobile money?

mm_account_telco Please select the providers for which you have a mobile money account

mm_account_telco_main Which would you consider your main Mobile Money account?

v234 I understood the terms and conditions when I registered for a mobile money account

agent_trust Do you trust mobile money agents?

v236 Have you ever taken a mobile money loan?

v237 Have you ever had issues with the network being unavailable for mobile money transactions?

v238 Before making a transaction are you clear about the fees?

v240 Has a transaction ever failed to go through?

v241 Has an agent you’ve dealt with ever not had enough cash or efloat available?

v242 Do you have a copy of the mobile money terms and conditions?

v243 Do you understand how and where to complain if you have an issue with mobile money?

v244 Have you had an issue successfully resolved after making a complaint?

v245 Do you understand what data mobile money providers collect about you?

v246 Have you been a victim of fraud?

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