Finance, savings, and consumption smoothing in rural India

Key Question Being Explored in This Insight:

By how much does banking help poor families save and reduce consumption? Vincent Somville and Lore Vandewalle tackle this fundamental question.

View the page of: Lore Vandewalle

View the page of: Vincent Somville

Institution: Geneva Graduate Institute

Explore more insights in:

Economics Microeconomics Social Sciences

Media Literacy Toolkit

Faculti's Media Literacy Toolkit helps viewers critically engage with academic insights by analyzing the research context, identifying perspectives, and encouraging thoughtful evaluation.

Critical Questions to Consider ▼

What assumptions does the research make?
Are there alternative perspectives not explored?
What are the limitations of the research method?

Bias and Perspective Awareness ▼

This research comes from Geneva Graduate Institute . Reflect on how the institution's academic focus and research partnerships may shape the questions being explored.

Further Reading ▼

Read the Study

By how much does banking help poor families save and reduce consumption? Vincent Somville and Lore Vandewalle tackle this fundamental question.

Image courtesy of interviewee. January 22, 2024

Log-in or Sign-up to Faculti
Currently viewing this subject insight as a guest. You have insight(s) remaining for this month. Login to view 8000+ figures on the platform.

Generating Workspace...

Export as PDF

This video video discusses research on the impact of banking access for low-income populations, particularly focusing on financial inclusion initiatives in India. The research highlights a significant increase in global bank account access, particularly for adults, with figures rising from about 50% in 2011 to 76% in 2020, driven mainly by regions such as Sub-Saharan Africa, Asia, and Latin America.

The study aims to explore how access to bank accounts can influence savings and consumption behavior among low-income households, particularly in rural India. The researchers employed randomized controlled trials (RCTs) to compare individuals who received access to bank accounts with those who did not. They found that while the overall average savings and consumption levels did not see substantial changes, access to banking improved the ability of households to smooth their consumption.

The method involved analyzing the timing of income and expenditures to determine consumption smoothing. The results indicated that those with bank accounts were better able to manage their income flows, allowing them to stabilize their expenditures despite variations in income. This video video was particularly evident in their ability to deposit funds during good income periods and use those savings during lean times.

The study concluded that simplifying access to banking can serve as a crucial development strategy, as it not only opens up savings opportunities but also enables better management of consumption, which is vital for financially vulnerable households. The implications suggest that programs aimed at promoting financial inclusion can significantly benefit low-income populations by enhancing their financial stability and consumption practices.

Language:

Export as PDF

X-TIMESTAMP-MAP:LOCAL=00:00:00.000,MPEGTS=900000

00:00.375 --> 00:01.795
The context for this, for this,

00:01.795 --> 00:05.235
article is the development of, finance for the poor.

00:05.535 --> 00:09.555
So there's been a huge change in the

00:10.215 --> 00:12.475
number of people who have access to bank accounts.

00:12.775 --> 00:16.595
So the, we have numbers from many countries over the world.

00:17.015 --> 00:18.035
Uh, the best survey,

00:18.255 --> 00:20.915
the best database is called the Global FinTech database.

00:21.185 --> 00:22.555
It's published every other year.

00:23.335 --> 00:26.995
And we know from that database that, we used to have

00:27.055 --> 00:30.395
around 50% of adult humans who had access

00:30.395 --> 00:32.155
to a bank account in 2011,

00:32.855 --> 00:36.355
and in 21 in 20 to seven, around 76%.

00:37.365 --> 00:38.745
Uh, and that's all over the world.

00:38.845 --> 00:40.225
And of course, the progress is not

00:40.225 --> 00:41.425
coming from Western countries.

00:41.455 --> 00:43.985
It's Sub-Saharan Africa, Asia, Latin America.

00:44.045 --> 00:46.705
That's where the, the people have got access to,

00:46.725 --> 00:49.305
to bank accounts in India, where we do the work

00:49.305 --> 00:50.625
that we will talk about today.

00:51.045 --> 00:54.905
Uh, this access increase from 35 to 78%.

00:55.485 --> 00:59.945
So massive increase in, the, the number of people

01:00.085 --> 01:02.825
who suddenly have access to a bank account while

01:02.825 --> 01:05.345
before they, they didn't, they had to find other ways

01:05.365 --> 01:06.585
of managing their money.

01:08.105 --> 01:11.085
Uh, so Laura and I were very interested in that change

01:11.465 --> 01:13.405
as economists because they think that, you know,

01:13.405 --> 01:17.245
bank accounts are so fundamental in the way we use money,

01:17.345 --> 01:19.165
the way we save, the way we consume,

01:19.345 --> 01:22.725
how we organize the whole finances of our, of our families.

01:23.065 --> 01:24.765
Uh, that's the main tool that we use.

01:25.505 --> 01:27.285
So what will happen when people

01:27.345 --> 01:30.165
who didn't have access suddenly get access in bank,

01:30.165 --> 01:32.645
these bank accounts, and how will that affect their,

01:32.645 --> 01:34.885
their finances, is what we wanted to find out.

01:35.545 --> 01:37.925
Uh, and it could change the wholesale finance in many ways.

01:37.945 --> 01:40.565
You know, it can, maybe you can suddenly receive digital

01:40.645 --> 01:43.485
payments right before you always have to be paid cash.

01:44.305 --> 01:46.125
Uh, you can get government transfers,

01:46.125 --> 01:47.365
you can receive remittances.

01:47.465 --> 01:50.045
You can start paying bills through your bank accounts.

01:50.065 --> 01:51.365
So there are many things that can change.

01:51.985 --> 01:53.405
The one thing we want

01:53.405 --> 01:56.325
to focus on in this study is the savings aspect.

01:56.835 --> 02:00.865
When people start saving more, because savings are easier

02:01.085 --> 02:04.185
or supposed to be easier once you have a savings account.

02:05.145 --> 02:07.525
And if they start saving more, how does

02:07.525 --> 02:09.965
that affect also their consumption, consumption choices?

02:10.185 --> 02:12.205
How much they consume, when do they consume?

02:12.505 --> 02:15.405
That's, that's what we, we want to, to investigate

02:15.505 --> 02:19.485
before we, we publish this article, there has been a handful

02:19.625 --> 02:23.685
of papers who really focused on how access to banking

02:24.275 --> 02:27.005
affects how much people save and how much people consume.

02:27.545 --> 02:31.925
So those are randomized controlled fires, where people,

02:32.075 --> 02:33.885
some people get access to a bank account

02:34.145 --> 02:35.245
and some people don't.

02:35.305 --> 02:36.645
And then you compare over time

02:36.785 --> 02:38.565
to the save more to the consumer more.

02:39.545 --> 02:42.965
Uh, so one example is, is Deepak Lan Robinson,

02:42.965 --> 02:47.165
and in the, in the American Economic Journal applied,

02:47.285 --> 02:50.685
a few years ago who did this in three different countries,

02:51.065 --> 02:54.205
Uganda, Malan, wi Chile, and,

02:54.785 --> 02:59.605
and, you know, over relatively long time find

02:59.605 --> 03:03.775
that it's not transformative, when people get,

03:03.875 --> 03:05.375
and you know, I cite that article

03:05.375 --> 03:07.335
because it's, you know, similar findings in,

03:07.475 --> 03:09.135
in other related articles.

03:09.635 --> 03:12.215
Uh, when people get access to bank accounts, on average,

03:12.835 --> 03:14.375
we see that they use the bank accounts,

03:14.505 --> 03:16.415
their savings on the account increase,

03:16.835 --> 03:19.215
but their total savings don't really change much,

03:19.435 --> 03:22.215
and their total consumption on average doesn't change much.

03:22.555 --> 03:23.735
So that's where we come in

03:23.735 --> 03:26.015
because we were thinking, okay, maybe,

03:26.105 --> 03:28.415
maybe overall average savings don't change,

03:29.275 --> 03:31.935
but still people could use their savings in very different

03:31.935 --> 03:35.335
ways because they might still be able to smooth consumption,

03:35.525 --> 03:38.135
even if on average the saving level is the same.

03:38.555 --> 03:40.895
It may be that the timing of the saving is different

03:41.245 --> 03:43.495
because a bank account could allow them

03:43.515 --> 03:46.135
to better balance their income flows

03:46.135 --> 03:49.375
and expenditure flows, even if the average is,

03:49.435 --> 03:50.575
is not, is not changing.

03:50.995 --> 03:54.495
So, so in that sense, we relate to that literature.

03:54.515 --> 03:56.095
We try to build on the literature

03:56.095 --> 03:58.375
that's looking at the effect on average savings.

03:59.075 --> 04:01.255
But we want to go a a bit further

04:01.515 --> 04:04.615
by looking at what's the effect on smoothing on some

04:04.615 --> 04:06.535
consumption or the timing of consumption.

04:07.115 --> 04:09.655
So the other big literature we relate on is the,

04:09.655 --> 04:13.455
is this literature that is testing consumption moving,

04:13.635 --> 04:16.015
and that, so that, I want to take a minute to explain

04:16.015 --> 04:18.895
because it's not, it's not easy, but it's really essential.

04:18.955 --> 04:20.855
And then I will, I will pass the microphone

04:20.855 --> 04:21.895
to, to my colleague.

04:21.895 --> 04:24.895
Laura, how do you test whether people

04:25.075 --> 04:26.255
are smoothing consumption?

04:27.595 --> 04:30.365
It's not easy at all. Like the, the, the one, like the,

04:30.385 --> 04:34.125
the intuitive, way people think of doing this is

04:34.125 --> 04:36.045
to look at the volatility of expenditures.

04:36.425 --> 04:39.885
If expenditures are very volatile, people are not smoothing.

04:39.905 --> 04:41.565
And if expenditures are very flat,

04:41.825 --> 04:43.285
people are smoothing consumption,

04:44.465 --> 04:45.805
that's the wrong way of doing it.

04:46.345 --> 04:49.005
Uh, because consumption is not expenditures.

04:49.095 --> 04:50.245
Those are different things.

04:51.285 --> 04:53.145
And what we measure in the data is

04:53.145 --> 04:54.625
expenditures is not consumption.

04:55.725 --> 04:56.825
So I'll give you an example.

04:57.565 --> 04:59.945
Uh, what many people do, at least in our context.

05:00.055 --> 05:02.345
Well, what people like to do when they manage

05:02.345 --> 05:04.905
to accumulate some savings is to buy in bulk.

05:05.285 --> 05:07.465
So, you know, I managed to put money on the side for a week

05:07.465 --> 05:11.265
or two, and then I can bag, I can buy a big bag of rice,

05:11.415 --> 05:13.665
like 10 kilos or 20 kilos of rice,

05:14.005 --> 05:16.545
and then I will consume that little by little over time.

05:17.165 --> 05:20.505
If you look at my expenditures, they're just picking

05:20.965 --> 05:22.745
and then flat, very volatile,

05:23.165 --> 05:25.665
but my consumption will be much more volatile than someone

05:26.005 --> 05:27.905
who is not using the same strategy.

05:28.285 --> 05:30.625
So it's very important that we don't just rely on the

05:30.625 --> 05:31.785
volatility of expenditures,

05:31.785 --> 05:32.985
but that we find another way

05:32.985 --> 05:34.465
to test these consumptions moving.

05:34.925 --> 05:36.745
And the way it's being done in the literature,

05:36.805 --> 05:39.465
and the way we are doing it also in this study, is

05:39.465 --> 05:41.865
to compare the timing of income

05:41.865 --> 05:43.265
with the timing of expenditures.

05:43.285 --> 05:45.905
So we want to know when people receive their income

05:46.445 --> 05:47.865
to the spend it immediately,

05:48.775 --> 05:52.035
or are they able to dissociate the timing

05:52.055 --> 05:54.155
of their expenditures from their timing of income?

05:54.495 --> 05:57.035
Are they able not to spend immediately the money that they,

05:57.120 --> 05:59.645
they get, in which case we'll conclude that they're actually

06:00.285 --> 06:02.205
managing to smooth their, their consumption.

06:02.425 --> 06:03.725
That's what, that's what we'll do.

06:03.725 --> 06:06.565
And then Laura can explain in more detail exactly how we,

06:06.625 --> 06:08.445
how we are going to be able to do that.

06:08.735 --> 06:11.125
First of all, let me give a little bit more background on,

06:11.125 --> 06:13.045
on the institutional setting in which,

06:13.225 --> 06:14.645
in which, we have been working.

06:15.785 --> 06:19.405
So to increase financial inclusion, the, the Reserve Bank

06:19.405 --> 06:20.645
of India, they introduced

06:20.675 --> 06:24.645
what is called the business correspondence model in 2016.

06:24.705 --> 06:26.965
And then in 2014,

06:27.025 --> 06:28.885
the government created a national mission

06:28.945 --> 06:30.005
for financial inclusion.

06:30.425 --> 06:31.965
And it's these programs

06:31.965 --> 06:35.405
that increased bank account penetration in India rapidly.

06:35.905 --> 06:38.005
And it's, while this was happening that,

06:38.005 --> 06:41.445
that we saw an opportunity to start, to start our study.

06:42.225 --> 06:43.405
So how does this work?

06:43.465 --> 06:46.125
So how do people actually get access to bank accounts?

06:46.145 --> 06:49.445
So the program allows, commercial and,

06:49.465 --> 06:53.085
and state banks to appoint financial inclusion companies.

06:53.505 --> 06:55.645
And then these companies, they are the ones

06:55.645 --> 06:56.885
who provide financial

06:56.885 --> 06:59.405
and banking services on behalf on the banks.

07:00.195 --> 07:03.325
Okay? So in the region of our survey, we work

07:03.325 --> 07:04.605
with bank access.

07:04.985 --> 07:07.965
Who appointed the financial inclusion company, basic Sub K,

07:08.105 --> 07:10.805
who is then the main partner on, on on this project?

07:11.395 --> 07:14.565
Okay, so it's finfin, it's it's basic Sub K that is going

07:14.585 --> 07:18.445
to the different villages to start, helping them in, in,

07:18.445 --> 07:20.205
in opening, bank accounts.

07:20.945 --> 07:22.885
So these financial inclusion companies.

07:22.885 --> 07:26.245
So in each of those villages, they are selecting one person

07:26.585 --> 07:27.965
to become the local banker.

07:28.625 --> 07:31.485
So then they train this person, they give them the,

07:31.485 --> 07:33.565
the necessary equipment to be able to,

07:33.585 --> 07:36.605
to provide the service, and they're also providing a

07:36.885 --> 07:39.325
customer service to the clients in case there is a problem

07:39.635 --> 07:43.365
they can always reach out to, to basic, basic sub.

07:43.365 --> 07:47.445
Okay? So to open an account, the local villagers,

07:47.445 --> 07:50.245
they have to fill out a customer application form.

07:50.275 --> 07:51.605
They also have to take a picture,

07:52.185 --> 07:53.845
and they give this to the local banker

07:54.025 --> 07:56.125
who then sends this information to the bank.

07:56.715 --> 07:59.125
Okay? The bank then opens the bank account

07:59.385 --> 08:01.485
and communicates the unique account

08:01.485 --> 08:02.605
number to the bank agent.

08:02.665 --> 08:06.685
And in a final step, the local banker activates this account

08:06.905 --> 08:08.965
by registering the customer's fingerprint.

08:09.275 --> 08:12.605
Okay? So the way that these bank accounts will be protected

08:13.185 --> 08:16.085
is through the fingerprint of, of the customer.

08:16.545 --> 08:19.165
And then it's only once this whole procedure is finalized

08:19.515 --> 08:21.125
that the customer can,

08:21.195 --> 08:23.245
perform standard transactions on the account.

08:23.265 --> 08:25.965
So they can start depositing, they can start withdraw,

08:26.435 --> 08:28.525
they can transfer money to other accounts,

08:28.525 --> 08:31.645
they can do inquiries about the balance at, at any time.

08:32.155 --> 08:34.845
Okay? And important here is that all the transactions

08:34.845 --> 08:36.525
that reduce the account balance

08:37.145 --> 08:39.645
or that provide any information about balance,

08:39.735 --> 08:43.325
those are the transaction that require, the fingerprint.

08:43.585 --> 08:45.165
So depositing is not an issue.

08:45.185 --> 08:46.685
You can basically go to India

08:46.985 --> 08:50.085
and put money in any account, that, that you want.

08:51.105 --> 08:53.565
So that is the setting in, in which we have been working.

08:53.705 --> 08:57.925
So then what we did is we selected 17 villages in,

08:57.985 --> 08:59.285
in rural Chattis card.

08:59.285 --> 09:01.005
That's an east central state of India.

09:01.705 --> 09:03.205
And, and all of those villages,

09:03.295 --> 09:05.725
these local banker is the only person

09:05.945 --> 09:08.765
who offers formal banking services at the doorstep.

09:09.155 --> 09:11.685
Okay? So, and none of these villages you had,

09:11.685 --> 09:13.845
other bank branches being in existence.

09:14.425 --> 09:17.605
The first banking that came so close was through this,

09:17.635 --> 09:20.165
this newly created, created system.

09:20.715 --> 09:22.125
Then in each of those villages,

09:22.185 --> 09:24.645
we randomly selected six men and six women.

09:24.865 --> 09:28.245
So 12 villagers in total who did not yet have an account.

09:29.235 --> 09:31.885
Okay, so how did we do? So?

09:32.025 --> 09:35.085
So we, asked the government to give us the voter list.

09:35.665 --> 09:38.245
We gave each of the people on the voter list a number,

09:38.345 --> 09:40.485
and then we approached them in a sending order

09:40.895 --> 09:42.965
until we had selected six men and,

09:42.985 --> 09:44.525
and six women and six women.

09:45.385 --> 09:47.765
So then out of those 12 people, three men

09:47.765 --> 09:50.245
and three women, they were randomly allocated to

09:50.245 --> 09:51.765
what we will call the treatment group,

09:52.025 --> 09:55.045
and the others are, are allocated to, to the control group.

09:55.465 --> 09:57.845
So the treatment itself is, is twofold.

09:58.345 --> 10:00.045
So first of all, what we did is we

10:00.285 --> 10:01.765
provided help to open the account.

10:02.185 --> 10:04.525
So we helped them with filling out all of the documents.

10:04.525 --> 10:06.805
Some of the people were illiterate, so we literally had

10:06.805 --> 10:08.365
to fill it out, for them.

10:08.385 --> 10:10.685
We also took the picture as to make sure

10:10.685 --> 10:12.965
that the documentation was, was complete.

10:13.465 --> 10:16.165
So then this was sent to the bank, it came back,

10:16.165 --> 10:18.085
and these accounts could, could be opened

10:18.095 --> 10:20.645
after the people registered their, their fingerprint.

10:21.425 --> 10:24.045
So then secondly, what we also did is we organized a

10:24.405 --> 10:26.685
training in how to use these accounts.

10:27.075 --> 10:29.765
Okay? So we showed them how to deposit money, how

10:29.765 --> 10:33.205
to withdraw money, and potentially the most important,

10:33.385 --> 10:34.685
we actually demonstrated

10:34.945 --> 10:36.965
how this fingerprint protects their savings.

10:37.515 --> 10:39.685
Okay? So we would have two neighbors being in

10:39.685 --> 10:40.765
the, in, in the training.

10:41.345 --> 10:43.885
We would, we would deposit some money on, on one

10:43.885 --> 10:45.005
of the person's accounts,

10:45.005 --> 10:47.485
and we would ask the other person to try to withdraw them,

10:47.665 --> 10:49.005
and we would show that it fails.

10:49.235 --> 10:50.605
Okay? Well, if the person tries

10:50.605 --> 10:52.965
to withdraw from their own account, it, it would work.

10:54.105 --> 10:55.685
So these interventions,

10:55.685 --> 10:58.965
they aimed at removing important barriers in particular

10:59.065 --> 11:00.445
for the population under study.

11:00.865 --> 11:02.485
And that indeed seems to be the case

11:02.485 --> 11:04.565
because we still had three men

11:04.565 --> 11:06.885
and three women, so six people in the control group.

11:07.305 --> 11:09.285
And if they wanted, they could open an account.

11:09.385 --> 11:11.485
All they had to do is to fill out these documents,

11:11.485 --> 11:13.885
take the picture and start the whole procedure.

11:14.185 --> 11:15.845
But what we observe is that in,

11:15.845 --> 11:17.805
in the one year we've been in these villages,

11:17.955 --> 11:20.205
only two people in the control group actually did.

11:20.205 --> 11:23.085
So, so there were substantial barriers to,

11:23.265 --> 11:24.805
to opening, an account.

11:25.515 --> 11:28.005
Then over a period of, of six months,

11:28.265 --> 11:31.605
we organized a total of 17 weekly interviews.

11:32.105 --> 11:35.365
So these interviews, they took place on the same day

11:35.365 --> 11:37.325
of the week in a certain village at the

11:37.325 --> 11:38.365
century located room.

11:38.785 --> 11:40.565
So for example, even a certain village,

11:40.565 --> 11:43.405
we were operating on Mondays, then people knew

11:43.405 --> 11:46.245
that on Monday the interview will take place.

11:46.505 --> 11:48.645
So they would travel to this location,

11:48.995 --> 11:51.365
they would wait their turn, do the interview,

11:51.385 --> 11:54.005
and then they would, of course, head back home.

11:54.465 --> 11:57.125
So the total duration is, is about three hours.

11:57.225 --> 11:59.525
So the time to come to do the interview, et cetera,

11:59.735 --> 12:01.765
would take about three hours of their time.

12:02.025 --> 12:05.005
So of course, we had to cap compensate them, for this.

12:05.005 --> 12:07.925
And we did that by paying 150 rupees,

12:07.935 --> 12:09.885
after each of, of the interviews.

12:11.105 --> 12:14.125
And so these weekly interviews is a very important source

12:14.125 --> 12:16.085
of information that we will be using

12:16.505 --> 12:18.125
to get at consumption smoothing.

12:18.125 --> 12:20.285
So as already, explained

12:20.285 --> 12:22.925
before, so what we will do is we'll take a look at

12:22.925 --> 12:25.845
how expenditures and income move over time,

12:26.305 --> 12:29.605
and it's these weekly information that is giving us the data

12:29.635 --> 12:31.685
that is necessary, to do so.

12:32.195 --> 12:36.125
Okay. So we, we created a survey that asks into detail.

12:36.145 --> 12:38.165
We actually asked details about the total

12:38.265 --> 12:41.005
of one hundred and nine ninety five different

12:41.015 --> 12:42.205
goods on a weekly basis.

12:42.885 --> 12:44.205
'cause we realized that if you ask them

12:44.205 --> 12:45.605
how much do you spend on fruits,

12:45.605 --> 12:46.925
how much do you spend on vegetables?

12:47.275 --> 12:48.925
This was too difficult to answer.

12:49.025 --> 12:51.965
We had to ask them about the tomatoes versus the apples

12:51.965 --> 12:55.445
versus the potatoes, versus the types of meat that,

12:55.445 --> 12:57.125
that potentially they, they were buying.

12:57.425 --> 12:59.485
And this is what we're doing on a, on a weekly basis.

12:59.545 --> 13:03.045
So we had a lot of details of what exactly was was going on.

13:03.385 --> 13:06.405
So in addition to that, we have three other sources of data

13:06.515 --> 13:07.925
that, that we used.

13:08.305 --> 13:09.925
So we have the traditional baseline

13:09.925 --> 13:11.285
survey and endline survey.

13:11.865 --> 13:14.605
Um, the baseline survey includes questions on the

13:14.605 --> 13:16.205
characteristics of the participant

13:16.265 --> 13:17.445
of their household members,

13:17.945 --> 13:20.245
but also already some these details on the

13:20.245 --> 13:21.365
household's financial lives.

13:21.545 --> 13:24.045
So what are your current outstanding loans, et cetera,

13:24.255 --> 13:26.845
about which we then ask details on a weekly basis.

13:26.845 --> 13:30.165
That's as well. And we repeated this exercise at the end

13:30.265 --> 13:31.365
of, of the whole study.

13:31.865 --> 13:33.205
And then what's very nice is

13:33.205 --> 13:35.445
that we also obtained administrative data.

13:35.955 --> 13:39.085
Okay? So, through basic sub K, we got access

13:39.665 --> 13:41.485
to the transactions that were made

13:41.485 --> 13:43.965
during the whole survey period by all

13:43.965 --> 13:45.685
of the villagers in our study area.

13:45.825 --> 13:48.565
So not only by the respondents who,

13:48.585 --> 13:50.485
who took place in these weekly interviews,

13:50.865 --> 13:52.325
but also by all their neighbors.

13:52.325 --> 13:55.005
So we could observe if more people were using accounts,

13:55.005 --> 13:57.125
if there were, say, changes in the use

13:57.125 --> 13:58.405
of accounts by other people.

13:58.665 --> 14:01.885
But of course, most importantly, we knew exactly up

14:01.885 --> 14:04.645
to the second precisely when our,

14:04.745 --> 14:07.445
our respondents were making transfers with rolls

14:07.465 --> 14:08.525
and, and deposits.

14:08.905 --> 14:11.165
So these data sets together allowed us

14:11.505 --> 14:13.165
to answer the question that,

14:13.435 --> 14:15.005
Faso can give you some more details about.

14:15.265 --> 14:18.845
The first results are is that's when we test the effect

14:18.845 --> 14:22.925
of getting these bank accounts on the average consumption,

14:23.035 --> 14:25.085
average savings of these households.

14:25.185 --> 14:27.325
And they're very much in line

14:27.325 --> 14:28.725
with the rest of the literature.

14:28.745 --> 14:30.645
We don't find, we find some positive

14:30.645 --> 14:31.925
effects, but not very large.

14:32.025 --> 14:35.365
So people, they do save more on the bank account,

14:35.545 --> 14:38.885
but they don't deserve a bit less in other ways,

14:38.885 --> 14:40.085
like cash for example.

14:40.665 --> 14:42.965
Uh, and then the total savings are not increasing.

14:43.105 --> 14:46.445
The, on the other hand, the new thing

14:46.445 --> 14:48.765
that we are looking at, this consumption small thing, that's

14:48.765 --> 14:50.405
where we find relatively big effects.

14:50.865 --> 14:52.485
So we see that in the control group

14:52.485 --> 14:55.725
that doesn't have those bank accounts, their expenditures

14:56.235 --> 14:58.605
closely, follow their incomes.

14:58.605 --> 15:01.005
So when they have, and those people, they have daily

15:01.105 --> 15:03.925
or weekly incomes, so when they have a good week,

15:04.035 --> 15:05.205
they tend to spend more.

15:05.205 --> 15:07.245
When they have a bad week, they tend to spend less.

15:07.665 --> 15:08.605
So clearly they're not

15:08.675 --> 15:10.325
perfectly smoothing their consumption.

15:10.945 --> 15:13.285
And we don't see that same pattern in the treated group

15:13.285 --> 15:14.285
that got the bank accounts.

15:14.285 --> 15:16.605
What we see in the treated group is

15:16.605 --> 15:19.045
that the expenditures are dissociated from income.

15:19.225 --> 15:20.565
So even if they have a good week,

15:20.875 --> 15:22.325
they don't spend more that week.

15:22.385 --> 15:24.445
If they have a bad week, they don't spend less that week.

15:24.785 --> 15:28.485
So it looks like they're, they're smoothing consumption,

15:28.585 --> 15:29.605
in a much better way.

15:30.025 --> 15:34.585
And in fact, so to respond about the mechanisms, we see

15:34.585 --> 15:37.185
that they're, they're, they're depositing,

15:37.705 --> 15:38.825
actively when they have better weeks.

15:38.925 --> 15:40.625
So if they have a good week, we see

15:40.625 --> 15:41.945
that they put money on the side,

15:42.125 --> 15:44.385
and then when they have, not a good week, they can use

15:44.385 --> 15:47.915
that money to, to, to consume.

15:48.015 --> 15:49.635
So we think that that's what's going on.

15:50.095 --> 15:52.795
Uh, another thing that we see that is going on is that they,

15:52.825 --> 15:56.245
they tend to,

15:57.755 --> 15:58.845
they're, they're,

15:58.845 --> 16:01.005
because we have these weekly interviews where we,

16:01.225 --> 16:05.135
we have questions about how much things they buy

16:05.155 --> 16:06.295
of all different items,

16:06.715 --> 16:09.575
we can look specifically at food expenditures

16:09.875 --> 16:12.015
and make it look specifically at the food

16:12.325 --> 16:13.695
that is, perishable.

16:14.075 --> 16:15.695
So if we see that they buy rice,

16:15.835 --> 16:17.135
we don't know when they consume it.

16:17.635 --> 16:21.775
But if they buy ve vegetable meat fish, given

16:21.775 --> 16:22.775
that they don't have fish

16:22.875 --> 16:25.575
or freezers, we know that these are stuff that they have

16:25.575 --> 16:27.615
to consume within the week or two.

16:28.385 --> 16:30.885
So we, we can look specifically at these type of items

16:31.495 --> 16:33.045
where we know that the expenditures

16:33.045 --> 16:34.485
correspond to the consumption.

16:35.145 --> 16:37.685
And there we, when we do that, we also see the same pattern

16:37.795 --> 16:41.845
that, people seem to be smoothing the consumption,

16:41.955 --> 16:43.485
much more when they have access to the,

16:43.605 --> 16:46.605
these bank accounts compared to, when they don't.

16:46.665 --> 16:48.645
So that's an additional check of, of the,

16:49.345 --> 16:50.405
of the main findings

16:50.865 --> 16:52.125
As just pointed out.

16:52.185 --> 16:54.765
So while most papers that study the impact of,

16:54.825 --> 16:56.565
of providing access to bank account

16:57.155 --> 16:59.205
they observe may be some impacts on savings,

16:59.265 --> 17:01.285
but then there are very limited average effects on

17:01.285 --> 17:03.365
expenditures, on related variables.

17:03.705 --> 17:05.925
And the first contribution that we are making is, is

17:05.925 --> 17:08.565
by showing or confirming that these findings,

17:08.635 --> 17:10.245
also halt in a very different setting.

17:10.805 --> 17:12.805
'cause others had not looked at at India before.

17:13.545 --> 17:16.445
So however, what what the, the additional point

17:16.445 --> 17:19.525
that we're making here is that our study shows that access

17:19.525 --> 17:22.445
to banking can improve consumption smoothing even

17:22.445 --> 17:23.885
without changing mean consumption.

17:24.315 --> 17:26.005
That is kind of the next step that,

17:26.115 --> 17:27.485
that we, we have been taking.

17:27.865 --> 17:30.085
So these results are, are important,

17:30.185 --> 17:33.645
in particular in light of the attention that has been given,

17:33.905 --> 17:36.485
to access to banking by the international community,

17:36.485 --> 17:37.965
but also by several governments.

17:38.285 --> 17:41.165
'cause India is not the only government that started with,

17:41.165 --> 17:45.685
with very, very far going, programs on,

17:45.705 --> 17:46.725
on financial inclusion.

17:46.815 --> 17:49.290
South Africa did it, Bangladesh did it, et cetera.

17:50.025 --> 17:51.885
So given the importance

17:51.885 --> 17:54.405
that we're finding in improving consumption smoothing and,

17:54.425 --> 17:57.085
and consumption smoothing being a, a,

17:57.205 --> 18:00.765
a core important aspect, for, for poor households,

18:01.105 --> 18:03.445
we basically conclude that simplifying access

18:03.465 --> 18:05.605
to a convenience saving tool, in this case

18:05.605 --> 18:07.325
that's bank account counts.

18:07.325 --> 18:09.685
That that is an important development strategy, okay?

18:09.685 --> 18:13.325
Because it can help households in, in, in making sure

18:13.325 --> 18:16.365
that the, the consumption levels are, are similar over time,

18:16.535 --> 18:20.245
which is important, in particular, for them.

18:20.825 --> 18:22.725
So, and if we can make one,

18:22.785 --> 18:24.125
one more additional point to this.

18:24.145 --> 18:27.485
So the, the first aspect is, is making sure

18:27.485 --> 18:28.965
that people open bank accounts.

18:28.965 --> 18:31.365
Here we saw that people actually started using them,

18:31.785 --> 18:33.725
but of course, a natural way of making sure

18:33.725 --> 18:35.205
that people use bank accounts is

18:35.205 --> 18:36.765
that we start paying them into it.

18:37.115 --> 18:39.085
Okay? So the digitization of wages

18:39.085 --> 18:42.245
or wealth schemes that ol also mentioned,

18:42.265 --> 18:45.165
in the introduction, that is a way of making sure

18:45.165 --> 18:47.885
that once people open bank account that there's also an,

18:47.905 --> 18:49.605
an active use, for it.

18:50.025 --> 18:52.405
So, and in the related work, kind of a follow up on,

18:52.405 --> 18:53.445
on this study, which is,

18:53.465 --> 18:55.205
is published in the American Economic Journal,

18:55.205 --> 18:57.285
applied Economics, what we show is

18:57.285 --> 18:59.805
that being paid into the bank account, that

18:59.805 --> 19:01.805
that increases savings into the account

19:01.905 --> 19:04.245
and that this effect is, is long lasting.

19:04.465 --> 19:07.445
And if we combine these two results of, of motivating people

19:07.445 --> 19:10.285
to use the accounts and the accounts helping in improving

19:10.285 --> 19:13.205
consumption smoothing over time, we strongly believe

19:13.205 --> 19:15.725
that this can actually make an an important difference

19:15.725 --> 19:16.565
for poor families.

Impact of Banking Access on Financial Behavior

00:00:00 - The context for this, for this, article is the development of, finance for the poor. So there's been a huge change in the number of people who have access to bank accounts. So the, we have numbers from many countries over the world. the best survey, the best database is called the Global FinTech database. It's published every other year. And we know from that database that, we used to have around 50% of adult humans who had access
00:00:32 - and in 21 in 20 to seven, around 76%. and that's all over the world. And of course, the progress is not coming from Western countries. It's Sub-Saharan Africa, Asia, Latin America. That's where the, the people have got access to, to bank accounts in India, where we do the work that we will talk about today. this access increase from 35 to 78%. So massive increase in, the, the number of people who suddenly have access to a bank account while
00:01:05 - of managing their money. so Laura and I were very interested in that change as economists because they think that, you know, bank accounts are so fundamental in the way we use money, the way we save, the way we consume, how we organize the whole finances of our, of our families. that's the main tool that we use. So what will happen when people who didn't have access suddenly get access in bank, these bank accounts, and how will that affect their, their finances, is what we wanted to find out.
00:01:37 - You know, it can, maybe you can suddenly receive digital payments right before you always have to be paid cash. you can get government transfers, you can receive remittances. You can start paying bills through your bank accounts. So there are many things that can change. The one thing we want to focus on in this study is the savings aspect. When people start saving more, because savings are easier or supposed to be easier once you have a savings account. And if they start saving more, how does
00:02:10 - How much they consume, when do they consume? That's, that's what we, we want to, to investigate before we, we publish this article, there has been a handful of papers who really focused on how access to banking affects how much people save and how much people consume. So those are randomized controlled fires, where people, some people get access to a bank account and some people don't. And then you compare over time to the save more to the consumer more.
00:02:42 - and in the, in the American Economic Journal applied, a few years ago who did this in three different countries, Uganda, Malan, wi Chile, and, and, you know, over relatively long time find that it's not transformative, when people get, and you know, I cite that article because it's, you know, similar findings in, in other related articles.

Savings Utilization and Consumption Smoothing Insights

00:03:12 - we see that they use the bank accounts, their savings on the account increase, but their total savings don't really change much, and their total consumption on average doesn't change much. So that's where we come in because we were thinking, okay, maybe, maybe overall average savings don't change, but still people could use their savings in very different ways because they might still be able to smooth consumption, even if on average the saving level is the same. It may be that the timing of the saving is different
00:03:43 - to better balance their income flows and expenditure flows, even if the average is, is not, is not changing. So, so in that sense, we relate to that literature. We try to build on the literature that's looking at the effect on average savings. But we want to go a a bit further by looking at what's the effect on smoothing on some consumption or the timing of consumption. So the other big literature we relate on is the, is this literature that is testing consumption moving,
00:04:16 - because it's not, it's not easy, but it's really essential. And then I will, I will pass the microphone to, to my colleague. Laura, how do you test whether people are smoothing consumption? It's not easy at all. Like the, the, the one, like the, the intuitive, way people think of doing this is to look at the volatility of expenditures. If expenditures are very volatile, people are not smoothing. And if expenditures are very flat, people are smoothing consumption,
00:04:46 - because consumption is not expenditures. Those are different things. And what we measure in the data is expenditures is not consumption. So I'll give you an example. what many people do, at least in our context. Well, what people like to do when they manage to accumulate some savings is to buy in bulk. So, you know, I managed to put money on the side for a week or two, and then I can bag, I can buy a big bag of rice, like 10 kilos or 20 kilos of rice, and then I will consume that little by little over time.
00:05:20 - and then flat, very volatile, but my consumption will be much more volatile than someone who is not using the same strategy. So it's very important that we don't just rely on the volatility of expenditures, but that we find another way to test these consumptions moving. And the way it's being done in the literature, and the way we are doing it also in this study, is to compare the timing of income with the timing of expenditures. So we want to know when people receive their income to the spend it immediately,
00:05:52 - of their expenditures from their timing of income? Are they able not to spend immediately the money that they, they get, in which case we'll conclude that they're actually managing to smooth their, their consumption. That's what, that's what we'll do. And then Laura can explain in more detail exactly how we, how we are going to be able to do that. First of all, let me give a little bit more background on, on the institutional setting in which, in which, we have been working. So to increase financial inclusion, the, the Reserve Bank

Progress in India’s Financial Inclusion Efforts

00:06:20 - what is called the business correspondence model in 2016. And then in 2014, the government created a national mission for financial inclusion. And it's these programs that increased bank account penetration in India rapidly. And it's, while this was happening that, that we saw an opportunity to start, to start our study. So how does this work? So how do people actually get access to bank accounts? So the program allows, commercial and,
00:06:53 - And then these companies, they are the ones who provide financial and banking services on behalf on the banks. Okay? So in the region of our survey, we work with bank access. Who appointed the financial inclusion company, basic Sub K, who is then the main partner on, on on this project? Okay, so it's finfin, it's it's basic Sub K that is going to the different villages to start, helping them in, in, in opening, bank accounts.
00:07:22 - So in each of those villages, they are selecting one person to become the local banker. So then they train this person, they give them the, the necessary equipment to be able to, to provide the service, and they're also providing a customer service to the clients in case there is a problem they can always reach out to, to basic, basic sub. Okay? So to open an account, the local villagers, they have to fill out a customer application form. They also have to take a picture,
00:07:54 - who then sends this information to the bank. Okay? The bank then opens the bank account and communicates the unique account number to the bank agent. And in a final step, the local banker activates this account by registering the customer's fingerprint. Okay? So the way that these bank accounts will be protected is through the fingerprint of, of the customer. And then it's only once this whole procedure is finalized that the customer can, perform standard transactions on the account.
00:08:26 - they can transfer money to other accounts, they can do inquiries about the balance at, at any time. Okay? And important here is that all the transactions that reduce the account balance or that provide any information about balance, those are the transaction that require, the fingerprint. So depositing is not an issue. You can basically go to India and put money in any account, that, that you want. So that is the setting in, in which we have been working.
00:08:57 - in rural Chattis card. That's an east central state of India. And, and all of those villages, these local banker is the only person who offers formal banking services at the doorstep. Okay? So, and none of these villages you had, other bank branches being in existence. The first banking that came so close was through this, this newly created, created system. Then in each of those villages, we randomly selected six men and six women.

Study Design: Account Access and Data Collection

00:09:29 - Okay, so how did we do? So? So we, asked the government to give us the voter list. We gave each of the people on the voter list a number, and then we approached them in a sending order until we had selected six men and, and six women and six women. So then out of those 12 people, three men and three women, they were randomly allocated to what we will call the treatment group, and the others are, are allocated to, to the control group.
00:09:58 - So first of all, what we did is we provided help to open the account. So we helped them with filling out all of the documents. Some of the people were illiterate, so we literally had to fill it out, for them. We also took the picture as to make sure that the documentation was, was complete. So then this was sent to the bank, it came back, and these accounts could, could be opened after the people registered their, their fingerprint. So then secondly, what we also did is we organized a training in how to use these accounts.
00:10:29 - to withdraw money, and potentially the most important, we actually demonstrated how this fingerprint protects their savings. Okay? So we would have two neighbors being in the, in, in the training. We would, we would deposit some money on, on one of the person's accounts, and we would ask the other person to try to withdraw them, and we would show that it fails. Okay? Well, if the person tries to withdraw from their own account, it, it would work. So these interventions, they aimed at removing important barriers in particular
00:11:00 - And that indeed seems to be the case because we still had three men and three women, so six people in the control group. And if they wanted, they could open an account. All they had to do is to fill out these documents, take the picture and start the whole procedure. But what we observe is that in, in the one year we've been in these villages, only two people in the control group actually did. So, so there were substantial barriers to, to opening, an account. Then over a period of, of six months, we organized a total of 17 weekly interviews.
00:11:35 - of the week in a certain village at the century located room. So for example, even a certain village, we were operating on Mondays, then people knew that on Monday the interview will take place. So they would travel to this location, they would wait their turn, do the interview, and then they would, of course, head back home. So the total duration is, is about three hours. So the time to come to do the interview, et cetera, would take about three hours of their time. So of course, we had to cap compensate them, for this.
00:12:07 - after each of, of the interviews. And so these weekly interviews is a very important source of information that we will be using to get at consumption smoothing. So as already, explained before, so what we will do is we'll take a look at how expenditures and income move over time, and it's these weekly information that is giving us the data that is necessary, to do so. Okay. So we, we created a survey that asks into detail.

Weekly Spending Analysis and Consumption Smoothing

00:12:38 - of one hundred and nine ninety five different goods on a weekly basis. 'cause we realized that if you ask them how much do you spend on fruits, how much do you spend on vegetables? This was too difficult to answer. We had to ask them about the tomatoes versus the apples versus the potatoes, versus the types of meat that, that potentially they, they were buying. And this is what we're doing on a, on a weekly basis. So we had a lot of details of what exactly was was going on. So in addition to that, we have three other sources of data
00:13:08 - So we have the traditional baseline survey and endline survey. the baseline survey includes questions on the characteristics of the participant of their household members, but also already some these details on the household's financial lives. So what are your current outstanding loans, et cetera, about which we then ask details on a weekly basis. That's as well. And we repeated this exercise at the end of, of the whole study. And then what's very nice is that we also obtained administrative data. Okay? So, through basic sub K, we got access
00:13:41 - during the whole survey period by all of the villagers in our study area. So not only by the respondents who, who took place in these weekly interviews, but also by all their neighbors. So we could observe if more people were using accounts, if there were, say, changes in the use of accounts by other people. But of course, most importantly, we knew exactly up to the second precisely when our, our respondents were making transfers with rolls and, and deposits. So these data sets together allowed us
00:14:13 - Faso can give you some more details about. The first results are is that's when we test the effect of getting these bank accounts on the average consumption, average savings of these households. And they're very much in line with the rest of the literature. We don't find, we find some positive effects, but not very large. So people, they do save more on the bank account, but they don't deserve a bit less in other ways, like cash for example. and then the total savings are not increasing.
00:14:46 - that we are looking at, this consumption small thing, that's where we find relatively big effects. So we see that in the control group that doesn't have those bank accounts, their expenditures closely, follow their incomes. So when they have, and those people, they have daily or weekly incomes, so when they have a good week, they tend to spend more. When they have a bad week, they tend to spend less. So clearly they're not perfectly smoothing their consumption. And we don't see that same pattern in the treated group
00:15:14 - What we see in the treated group is that the expenditures are dissociated from income. So even if they have a good week, they don't spend more that week. If they have a bad week, they don't spend less that week. So it looks like they're, they're smoothing consumption, in a much better way. And in fact, so to respond about the mechanisms, we see that they're, they're, they're depositing, actively when they have better weeks. So if they have a good week, we see that they put money on the side, and then when they have, not a good week, they can use

Impact of Bank Accounts on Consumption Patterns

00:15:48 - So we think that that's what's going on. another thing that we see that is going on is that they, they tend to, they're, they're, because we have these weekly interviews where we, we have questions about how much things they buy of all different items, we can look specifically at food expenditures and make it look specifically at the food that is, perishable. So if we see that they buy rice,
00:16:17 - But if they buy ve vegetable meat fish, given that they don't have fish or freezers, we know that these are stuff that they have to consume within the week or two. So we, we can look specifically at these type of items where we know that the expenditures correspond to the consumption. And there we, when we do that, we also see the same pattern that, people seem to be smoothing the consumption, much more when they have access to the, these bank accounts compared to, when they don't.
00:16:49 - of the main findings As just pointed out. So while most papers that study the impact of, of providing access to bank account they observe may be some impacts on savings, but then there are very limited average effects on expenditures, on related variables. And the first contribution that we are making is, is by showing or confirming that these findings, also halt in a very different setting. 'cause others had not looked at at India before. So however, what what the, the additional point that we're making here is that our study shows that access
00:17:22 - without changing mean consumption. That is kind of the next step that, that we, we have been taking. So these results are, are important, in particular in light of the attention that has been given, to access to banking by the international community, but also by several governments. 'cause India is not the only government that started with, with very, very far going, programs on, on financial inclusion. South Africa did it, Bangladesh did it, et cetera.
00:17:51 - that we're finding in improving consumption smoothing and, and consumption smoothing being a, a, a core important aspect, for, for poor households, we basically conclude that simplifying access to a convenience saving tool, in this case that's bank account counts. That that is an important development strategy, okay? Because it can help households in, in, in making sure that the, the consumption levels are, are similar over time, which is important, in particular, for them.
00:18:22 - one more additional point to this. So the, the first aspect is, is making sure that people open bank accounts. Here we saw that people actually started using them, but of course, a natural way of making sure that people use bank accounts is that we start paying them into it. Okay? So the digitization of wages or wealth schemes that ol also mentioned, in the introduction, that is a way of making sure that once people open bank account that there's also an, an active use, for it. So, and in the related work, kind of a follow up on,

Bank Accounts Enhance Savings for Poor Families

00:19:15 - is published in the American Economic Journal, applied Economics, what we show is that being paid into the bank account, that that increases savings into the account and that this effect is, is long lasting. And if we combine these two results of, of motivating people to use the accounts and the accounts helping in improving consumption smoothing over time, we strongly believe that this can actually make an an important difference for poor families.

Faculti AI can make mistakes

Research

Policy

Analysis

Data

Originals

Explainers

Podcasts

Faculti

New on Faculti

Idea Explorer

Definition

News Context

Critical Questions and Answers

Research Summaries

Finance, savings, and consumption smoothing in rural India

Media Literacy Toolkit

Critical Questions to Consider ▼

Bias and Perspective Awareness ▼

Further Reading ▼