metadata: authors: 0: author: Gine,Xavier
1: author: Goldberg,Jessica Ann
count: Malawi
docna: 0: docna: Experience in Financial Decision-Making :
            Field Evidence from Malawi
docty: Policy Research Working Paper
subtopic: International Trade and Trade Rules,Educational Sciences,Urban Governance and Management,Urban Housing and Land Settlements,Urban Housing,Municipal Management and Reform,Transport Services,Banks & Banking Reform
teratopic: International Economics and Trade,Education,Urban Development,Finance and Financial Sector Development,Transport,Communities and Human Settlements,Public Sector Development
abstracts: cdata!: Fifty-three percent of subjects who
            owned a high-fee account with a local bank in Malawi did not
            switch to a new, lower-fee account when given the choice. In
            contrast, holders of high-fee accounts who had been induced
            to make more transactions in the past were significantly
            more likely to adopt the new, cheaper account. Using
            estimates from a structural model, we find that the
            different propensity to switch is better explained by
            differences in the valuation of the new account rather than
            differences in the cost of switching. Experience using
            financial products can thus improve financial decision making.
geo_reg_key: 517195,517191
repnme: repnme: Experience in Financial Decision-Making :
            Field Evidence from Malawi
display_title: Experience in Financial
            Decision-Making : Field Evidence from Malawi
listing_relative_url: /research/2018/09/30400089/experience-financial-decision-making-field-evidence-malawi
topicv3: Commercial Banking m1326069 1236,Transport m1326661 135,Trade m1326924 698,Education m1327048 470,Land and Housing m1327648 817
publishtoextweb_dt: 2018-09-05T00:00:00Z
historic_topic: International Economics and Trade,Education,Urban Development,Finance and Financial Sector Development,Transport,Communities and Human Settlements,Public Sector Development
no_of_pages: 33
author_keys: 0: author_key: 658884
1: author_key: 1037257
model_extractions: Policy Research Working Paper 8576 Experience in Financial Decision-Making Field Evidence from Malawi _Xavier Giné Jessica Goldberg_ Development Economics Development Research Group September 2018
Policy Research Working Paper 8576

# **Abstract**

Fifty-three percent of subjects who owned a high-fee account with a local bank in Malawi did not switch to a new, lower-fee account when given the choice. In contrast, holders of high-fee accounts who had been induced to make more transactions in the past were significantly more likely to adopt the new, cheaper account. Using estimates from a structural model, we ind that the different propensity to switch is better explained by differences in the valuation of the new account rather than differences in the cost of switching. Experience using financial products can thus improve financial decision making.

This paper is a product of the Development Research Group, Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/research. The authors may be contacted at xgine@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# Experience in Financial Decision-Making: Field Evidence from Malawi

Xavier Gine ́ and Jessica Goldberg<sup>_∗_</sup> Originally published in the Policy Research Working Paper Series on _September 2018._ This version is updated on _June 2028._ To obtain the originally published version, please email prwp@worldbank.org.

Keywords: Savings, field experiment, experience. JEL Codes: D14, D91, C93, G21, O16.

> _∗_ Gin ́e: Development Research Group, World Bank, xgine@worldbank.org. Goldberg: University of Maryland, goldberg@econ.umd.edu. We gratefully acknowledge support from the Development Research Group at the World Bank. Ryan Malitz contributed to the design and implementation in the initial stages of the project. We thank Maryumbo Munyenyembe for their outstanding field management; Sai Luo and Bernardo Ribeiro for superb research assistance; and Emily Breza, Francesco Cecchi, Oscar Mitnik, Lore Vandewalle, Bilal Zia, and seminar and conference participants for comments. A previous version of this paper was circulated under the title “Status Quo Bias and Usage of Financial Products: Evidence from Malawi.” This project was reviewed and approved by the Innovations for Poverty Action IRB, protocol numbers 12March-001 and 451.13January-005. The views expressed in this paper are those of the authors and should not be attributed to the World Bank, its executive directors, or the countries they represent.
Over the past two decades, an estimated 1.2 billion adults have gained access to basic financial accounts (World Bank, 2019). While greater financial inclusion has brought significant benefits (see Burgess and Pande, 2005; Batista and Vicente, 2018; Braza and Chandrasekhar, 2019; Callen et al. 2019; Jack and Suri, 2014; Dupas et al., 2018; Kast and Pomeranz, 2014; Schaner, 2018), it has also raised concerns that individuals are acquiring products that do not suit their needs, especially among those with limited financial capabilities (see, e.g., Gross and Souleles, 2002; Choi et al., 2011; Duarte and Hastings, 2012; Hastings et al., 2012; Agarwal et al., 2013, 2015; Gin ́e and Mazer, 2018 and Campbell et al., 2011; DellaVigna, 2009 for reviews).

Policymakers have tried to improve consumer knowledge with financial literacy programs and legislation aimed at increased disclosure and transparency, but these literacy efforts have often proven ineffective (see Cole et al., 2011 and Miller et al., 2014; Hastings et al., 2013 for reviews) and disclosure regulation is typically poorly enforced (Garz et al., 2020).

Before considering the implementation of policies or the enactment of new regulation, it is important to ask whether the simple experience in using financial products can improve financial decision-making. While critical, however, experience obtained through ordinary usage is typically endogenous, making causal inference difficult.

In this paper we combine two field experiments to understand how experience accumulated through usage of a savings account affects the decision to switch to a cheaper alternative when it becomes available. We present a sample of bank account holders from 14 villages in southern Malawi with three choices: to keep their existing account but incur higher monthly fees, to close their existing account and receive the remaining balance, or to switch to a new account with lower fees and transfer the balance from the old account to the new.

In 2012, as part of a previous study, individuals were offered fully subsidized basic savings accounts with a local bank. In 2015, some of those who had opened accounts were randomly chosen to receive MK 25,000 windfall payments (USD 160 using the 2015 purchasing power parity [PPP] exchange rate; see Brune et al., 2017 for details). This transfer did not have persistent effects on saving or spending, but it did increase the number of transactions that subjects made at the bank branch. The random allocation of these transfers thus created exogenous variation in the experience subjects had in using their accounts.

In 2016, the previous research project concluded and subsidies for monthly account maintenance fees were discontinued. Starting in May 2016, account holders had to pay a monthly maintenance fee that had previously been covered by funds raised by the researchers and paid directly to the bank. Concurrently but independently, the bank introduced a new account called the Pafupi account. This account had a different fee structure with withdrawal fees, 2
but no monthly maintenance fees. It also required the purchase of an ATM card. Based on the number of transactions that subjects made between 2012 and May 2016, the Pafupi accounts were less expensive than the original (basic) accounts for everyone in the sample provided their usage patterns persisted and they planned to keep the account open for at least another four months.

In March and April 2016, the research team visited the homes of study subjects who owned savings accounts, and asked them to come to the bank branch to make a decision about their accounts. Subjects could keep their existing basic account and start paying monthly fees; could close their basic account; or could transfer their balances to a Pafupi account with the purchase of an ATM card. Although the Pafupi account was cheaper than the basic account given their past usage, the choice was presented in a neutral way.

The home visits were used to introduce exogenous variation in two dimensions of the account ownership decision. First, we varied the amount of a payment for coming to the branch, which was used to lower switching costs and encourage individuals to actively decide.<sup>1</sup> Second, we varied the timing of when subjects were asked to visit the bank: some were asked to come within the week, while others were asked to come only after a two-week delay. This manipulation assessed whether people would fail to show up at the bank branch due to forgetfulness or inattention.

Using their choices regarding the account disposition and the treatments received in 2015 and 2016, we estimate a structural model of the benefit to each account holder of each type of account and the cost of visiting the bank. In particular, we estimate a generalized extreme value model that does remarkably well at predicting the share of individuals failing to visit the bank, or visiting and either keeping the basic account, switching to a Pafupi account, or closing their account entirely.

Individuals who received transfers in 2015 were more likely to switch to the Pafupi account than those who did not. Our estimates indicate that is explained by differences in how much they value the new Pafupi account, not by differences in the cost of switching. While all subjects appear to value the Pafupi accounts more than the old accounts, those who received transfers in 2015 value the Pafupi accounts more than those who did not receive transfers.

We also find that transfer-induced experience with the basic account increased both trust in the bank and knowledge of the features of the basic account. These results taken together suggest that experience with the basic account helped individuals learn about its features and reliability, enabling subjects to compare new and old accounts and to switch to the cheaper one when given the opportunity to do so.

> 1While the cost of switching items in laboratory experiments is zero, in our setting, there are time and monetary costs associated with visiting the branch. These are however equal regardless of which account is chosen, and randomly offset for most customers.

3
Finally, we provide some evidence against other explanations for the switch of accounts, such as experimenter demand effects or the belief that switching to the Pafupi account may increase the chances of receiving another transfer from the research team.

Our paper contributes to two strands of the literature. First, it adds to the literature on financial decision-making and in particular on the optimal switching of accounts (Samuelson and Zeckhauser, 1988; Madrian and Shea, 2001). When pecuniary and effort costs are large (Burnham et al., 2003; Madrian and Shea, 2001), they can outweigh the benefits from switching. Both lab and field experiments have documented this status quo bias. Samuelson and Zeckhauser (1988) find status quo bias using a wide range of hypothetical questions about job security, the color of cars, financial investments, and policy issues. They also present evidence regarding the selection of medical plans by Harvard employees and report that new employees are more likely to choose a newly introduced medical plan than existing employees even though all have the opportunity to make or update their selection at a minimal cost every year. Similarly, a status quo bias is found in consumer demand for electricity (Hartman et al., 1991) and—more relevant to our context—in retirement savings (Madrian and Shea, 2001) and savings-linked accounts (Blumenstock et al., 2018). Madrian and Shea (2001) study the enrollment of employees of a large firm in 401(k) plans before and after the firm implemented automatic enrollment for new employees. They find that while participation is significantly higher under automatic enrollment, tenure and income (i.e., proxies for financial literacy) also correlate with participation in the 401(k) plan. Since participation requires learning about the plan features and evaluating the various savings options, employees who are financially literate are better able to navigate these complex decisions. Indeed, Samuelson and Zeckhauser (1988), Tversky and Shafir (1992), and Shafir et al. (1993) all suggest that the preference for the status quo may be greater when decisions are more complex (see also Iyengar and Lepper, 2000).

Our paper also relates to a literature underscoring the role of experience with financial products. Most directly related, Breza et al (2022) implement a field experiment with garment factory workers in Bangladesh and show that workers whose income is directly deposited into a bank or mobile money account use the account more and end up paying less per transaction. Factory workers induced to use their accounts by directly depositing their income into them rely initially on agents to make transactions but with experience they learn to make transfers on their own. In contrast, subjects in our study induced to use their account by receiving a large transfer learn to make better financial decisions.

Brown, Cookson and Heimer (2019) show that consumers who are exposed to formal accounts earlier in life have better credit scores and financial outcomes later in life. Finally, Bachas et al. (2019) show that after a period of building trust in the financial provider, the rollout of debit cards to beneficiaries of a cash transfer program in Mexico led beneficiaries 4
to save more in the bank.<sup>2</sup>

# **2 Experimental Design**

In July 2012, we randomly selected and interviewed 872 households from 14 villages surrounding the Mulanje market in southern Malawi.<sup>3</sup> All these villages are located within six kilometers of the local NBS branch.<sup>4</sup> These households were offered assistance in opening a basic savings account at NBS and MK 500 (USD 2.72 using the 2016 PPP exchange rate) was deposited into their account to cover the minimum balance. This minimum balance was enforced in the sense that the bank would deny any withdrawal that would bring the balance below MK 500. In addition, the monthly account maintenance fees of MK 400 per month were paid by the research team directly to the bank and were thus not deducted from subjects’ balances. Because the bank did not charge for transactions, the subsidized basic account offered in the study was free to customers.<sup>5</sup> The take-up rate for these free accounts was 85 percent.

From the 747 households that opened subsidized accounts, 600 were randomly chosen in April 2015 to participate in another field experiment that induced account usage. That experiment varied whether households received a large transfer (MK 25,000 or about USD 160 using the 2015 PPP exchange rate) and whether this transfer was made in cash or directly deposited into subjects’ accounts (see Brune et al., 2017). The transfer increased the number of transactions that participants made at NBS. Account holders who received transfers had the same number of bank transactions in the month preceding the transfer as those who did not receive the transfer. However, transfer recipients made significantly more transactions with their accounts after receiving the transfers, even excluding initial withdrawals of the amount transferred. The increased usage began in the month following the transfers and persisted, with a cumulative average of 1.5 more transactions 12 months after the transfers. Thus, the transfer treatment provides random variation in subjects’ experience using their bank accounts.

> 2A related literature studies how experience can attenuate behavioral anomalies such as the endowment effect, another manifestation of the status quo bias where individuals are reluctant to part with their endowment (Thaler, 1980), and focus on experience acquired by transacting in the market rather than by gaining familiarity with the product (List, 2003, 2004; Feng and Seasholes, 2005; Dhar and Zhu, 2006; G ̈achter et al., 2009; Greenwood and Nagel, 2009; Seru et al., 2010; Engelmann and Hollard, 2010; List, 2011; Anagol et al., ming).

> 3Malawi is a country in eastern Africa with relatively low levels of financial inclusion. According to the 2017 Global Findex database (Demirgu ̧c-Kunt et al., 2018), 34 percent of adults had bank accounts or mobile money but only nine percent had formal savings.

> 4NBS Bank, formerly known as New Building Society is one of the 10 commercial banks operating in Malawi, with a network of 36 branches throughout the country.

> 5Similar to other basic savings accounts in Malawi, the account did not pay interest. Because the inflation rate was above 20 percent throughout the study, the real rate of return was negative.

5
In March and April 2016, we implemented a final experiment that removed the subsidy for the recurring monthly maintenance fees of the basic account. We offered subjects the option to pay the fees themselves, close their accounts, or transfer their balances to the new Pafupi account. Of the 747 households that opened the subsidized accounts in 2012, we were able to contact and visit 594 households in 2016. Unfortunately, we find significantly lower attrition among treated individuals in the 2015 experiment.<sup>6</sup> During the one-on-one home visits, an enumerator explained that after more than three years (since July 2012), the original research about account ownership was ending and the subsidies would stop as of May 2016. The following three options were presented:

1. Keep the existing account. In this case, monthly maintenance fees of MK 400 would be deducted from the balance by NBS beginning in May 2016. If account balances fell below the minimum balance of MK 500, NBS would suspend the accounts. We used examples to show households how their balances would change each month if no additional deposits were made. This was the default option.

2. Close the account and receive the full account balance, including the minimum balance of MK 500 initially deposited by the research team, in cash. Accounts closed by the end of April 2016 would not accrue any monthly charges.

3. Transfer the balance to a Pafupi account without monthly fees but with a withdrawal fee of MK 150. To open a Pafupi account, customers would be required to pay account opening fee of MK 200 and to purchase an ATM card for MK 1,100 (MK 1,300 in total or USD 7 using the 2016 PPP exchange rate).

Enumerators presented these options using a neutral frame. Appendix Table A1 reports the timeline of activities and Appendix Table A2 shows the features of the basic and Pafupi accounts before and after May 2016. Since NBS required households to visit the branch in order to close the account or transfer the balance to a Pafupi account, the field team asked subjects to come to the branch by the end of May 2016 to report their decision and complete the necessary paperwork.

All households received the same information but we experimentally varied two conditions related to this decision. First, we took seriously the concerns about status quo bias (Samuelson and Zeckhauser, 1988) and provided some individuals with cash incentives to visit the

> 6In particular, individuals who received transfers via cash (direct deposit) are 15.2 (15.3) percentage points more likely to be found during the home visits compared to those who did not receive a transfer that had an overall attrition rate of 30.2 percentage points. These percentages are smaller when we consider the sample of 600 individuals that participated in the 2015 experiment. While the control group had an attrition rate of 23.6 percentage points, those that received transfers via cash (direct deposit) were 8.6 (8.8) percentage points more likely to be found. This lower attrition using the sample of the 2015 experiment suggests that more frequent contact with the households reduced attrition.

6
branch within a specified time window. The payment amounts were MK 0 (no payment), MK 500, or MK 1,000. We were explicit that this show-up payment was not conditional on the choice of account disposition and would be paid as long as the account holder came to the branch. The MK 500 payment was calibrated to cover the cost of round-trip bicycle taxi transportation to the branch, although the vast majority of customers in the sample chose to walk rather than pay for transport.

Second, we varied when households were asked to come to the branch. Among those offered a cash payment, half were asked to come within the following week and the remainder were asked to come after a two-week waiting period. Households had to come to the bank within their scheduled window in order to receive their show-up cash incentive (or bonus), and this was framed as a strategy to manage the flow of visitors. By timing the home visits just days before subjects went to the branch, these visits constituted teachable moments, as individuals received information when they needed to make an educated decision. The length of the window for visiting the branch was set at one week regardless of waiting period. The delay was designed to measure the salience of the decision, as forgetful or inattentive customers might not remember to show up after a two-week delay (Bordalo et al., 2012).

This cross-cutting randomization resulted in five treatment groups: a no-bonus or date group, and four groups who could receive cash for coming to the bank within a designated window. This randomization was conducted by computer and stratified by village and previous treatment assignment. Assignment to one of the five conditions was made before household visits began, though it was not visible to the field team until information about the three account disposition options had been delivered.

A final treatment was implemented at the bank branch. Some households were randomly selected to receive MK 1,500 (USD 8 using the 2016 PPP exchange rate), a larger amount than the promised show-up bonus. This amount was enough to pay for the MK 1,300 cost to open the Pafupi account and therefore relaxed a possible liquidity constraint. The offer, however, did not contain any explicit or implicit suggestion about what to do with the savings account. All show-up bonuses were paid in cash before participants were asked about their decisions regarding the accounts. Similar to other treatment conditions, assignment to this extra cash was randomized by computer and stratified by village and original five-group treatment status. Since customers did not learn about the extra cash until they arrived at the branch, it could not have possibly affected their decision to visit the bank.

7
# **3 Data**

We use three sources of data. Baseline data come from the household survey administered to all households in March and April 2016. Outcome data come from records collected by our field team stationed at the NBS branch during the intervention and from NBS administrative data.

Panels A and B of Table 1 use data from the 2016 survey to compare the characteristics and savings-related behaviors of existing account holders who were assigned to the three different treatments in the transfer experiment of 2015. Appendix Table A3 contains the definition of variables. We report the p-value of the joint test of equal means across all three categories in column 5, and we do not expect (and do not observe) differences in time-invariant characteristics such as age and gender of the respondent, that could not have changed as a result of treatment. The p-value of the F-test that all characteristics in panel A are jointly zero is 0.480. Despite the differential attrition, we take comfort in the fact that account holders in the treatment and control group appear to be similar.

In panel B, households that received the transfer did not expect more withdrawals in the next three months than those who did not receive the transfer (p-value is 0.227). Past and predicted usage for both samples is too limited to make the basic account worthwhile given the fee structure. According to their expected use in the three months after the baseline survey, existing account holders would save on average MK 1,067 (USD 5.80 according to the 2016 PPP exchange rate) even after accounting for the cost of the ATM card if they planned to keep it for four months. Panel B of Table 1 also reports account usage six months after the 2015 transfer, using administrative data. We find that individuals who received large transfers (either in cash or via direct deposit) made significantly more transactions (pvalue is 0.022). Although the overall mean is low, individuals who received the large transfer were also more likely to correctly report the fees for the basic account and to trust NBS more. All these variables were expected to be affected by treatment. While other variables in panel B could also have changed with the transfer, we find that they did not: excluding the percentage of individuals who correctly predicted the fees in the basic NBS account, the number of transactions in the six and 12 months after the large transfer, and the percentage who trust NBS, the p-value of the F-test that the remaining characteristics in panel B are jointly zero is 0.419. In particular, while households that received the transfer (particularly in cash) seem to have larger balances in 2016 than those without the transfer, these differences are not statistically significant (p-value is 0.375). The structural model described in the next section uses balance data to explain the decision of account ownership and for this reason it can only be estimated with individuals with available balance data. Although we requested balance data for the full sample of 747 individuals with accounts, the bank only provided 8
data for the sample of 694 that received the home visit. Of those, 596 had valid balance data and this is the sample we use in the structural estimation.

Appendix Table A4 reports balancing tests for the choice environment treatments implemented in 2016 and the same variables in panels A and B of Table 1. Judging by the p-values of the F-tests that all the variables are jointly zero reported in column 6, there are no statistically significant differences, indicating that the randomization of the show-up bonus and timing of the bank visit were balanced.

# **4 Empirical strategy and results**

Consider an account holder deciding what to do with the account. We assume that the utility that account holder _i_ obtains from alternative _j_ (i.e. _Uij_ ), which is fully known to the decision-maker, can be decomposed into a part known to the researcher _Vij_ and an unknown part _eij_ such that _Uij_ = _Vij_ + _eij_ . We assume further that the unobserved part of the utility (to the researcher) for all alternatives is jointly distributed as a generalized extreme value.

In particular, we assume that the set of alternatives can be partitioned into two subsets or nests that depend on whether the account holder decides to visit the bank. If the bank is visited, the account holder can keep the old account, close the account or open a Pafupi account. For any two of these three choices, we assume that the ratio of probabilities is independent of existence of other alternatives. That is, there is no correlation between alternatives and the independence from irrelevant alternatives (IIA) holds. Alternatively, the only option available to account holders that do not visit the bank is to keep the old account. In contrast to the assumption of zero correlation between alternatives when the bank is visited, we allow for some correlation between any of the alternatives when visiting the bank and the choice of keeping the old account when the bank is not visited. We therefore estimate a nested logit model with the tree diagram shown in Appendix Figure A1.

The known part _Vij_ for the different alternatives can be written as the value of the account chosen (or the balance amount if the account is closed) and the net benefit from visiting the bank if a bank visit occurs: 9
According to Table 1, the 2015 transfer induced account usage among recipients which could have led to better knowledge of the terms of the account and higher trust in NBS. As a result, we let the utility that account holder _i_ derives from an account depend on the experimental group in 2015 _g_ and on the balance _m_ in the account. The experimental group in 2015 is _g_ = _C_ if account holder _i_ did not receive a transfer, _g_ = _T_ if account holder _i_ received the transfer in cash and _g_ = _D_ if the transfer received was directly deposited into the account.

In particular, we parameterize the value from the old account as _vg_ 0( _m_ ) = _αg_ 0 + _βg_ 0 _m_ , making explicit that the value of the account can be different depending on the treatment _g_ = _C, T_ or _D_ received in 2015. Similarly, the utility from opening a Pafupi account is _vg_ 1( _m_ ) = _αg_ 1 + _βg_ 1 _m_ . The term _b − ci_ is the net benefit from visiting the bank, as the account holder receives the cash incentive _b_ to visit the bank but must forgo cost _ci_ which also depends on _i_ ’s experimental group _g_ in 2015.<sup>7</sup> The higher account usage induced by the 2015 treatment could have lowered both the monetary cost of visiting the bank if participants discovered a cheaper mode of transportation or a more convenient route, and/or lowered its psychological cost if account holders that received transfers became more familiar with bank procedures or staff. We thus allow the 2015 treatment to affect the valuation of the accounts as well as the cost of going to the bank and we later test whether valuations and costs are the same across experimental arms.

In case of opening a Pafupi account, the individual must pay MK _c_ 1 = 1 _,_ 300. Finally, _δij_ = 1 if the account holder was asked to come to the bank the week following the visit, while it takes value _δij_ = _δj ∈_ (0 _,_ 1] if asked to come to the bank after the two-week delay, where we allow _δ_ to depend on choice _j_ , that is, on whether the account holder keeps the old account ( _j_ = 0), closes the account ( _j_ = _x_ ) or opens a Pafupi account ( _j_ = 1).

Intuitively, the two different treatments implemented during the home visits of the 2016 experiment help identify different parameters of the model: the show-up payment helps identify the cost of visiting the bank _ci_ (along with whether they received the transfer in 2015), while the timing of when they should visit the bank helps identify the discount parameters _δij_ . In addition, the balance data and whether they received the transfer in 2015 identify the parameters governing the value of the two accounts _vi_ 0 ( _m_ ) and _vi_ 1 ( _m_ ).

The probability of each choice can be written as:

> 7We note that _b_ refers to the cash incentive promised during the home visit. While some households were randomly selected to receive an additional amount (up to 1,500 MK) once they visited at the bank, the nested logit model cannot accommodate this surprise incentive in the second stage (choice of accounts). We estimate the model assuming that _b_ includes both the amount promised during the home visit and the additional surprise incentive and we obtain similar results.

10
and The parameter _λ ∈_ [0 _,_ 1] measures the degree of independence in unobserved utility among the choices when visiting the bank. If _λ_ = 1, then this nested logit model reduces to the standard multinomial logit model and suggests that the correlations over alternatives are all zero. Since the cash bonus _b_ (and _c_ 1) enter the utility linearly, the scale parameter _σ_ is identified and interpreted as the standard deviation of the error term. We thus estimate 6 _α_ and 6 _β_ parameters (one for each of the 3 experimental groups in 2015 and the 2 accounts), 3 _δ_ parameters, 3 costs _cg_ of visiting the bank, for _g_ = _C, T_ or _D_ , _λ_ and the scale parameter _σ_ . Column 2 of Table 2 reports the parameter estimate for this full model and column 3 its bootstrapped standard error using 200 samples.

Intuitively, the estimation algorithm tries to find parameters such that the probabilities above match the share of individuals in the data under each choice, reported in the oddnumbered columns of Table 3.

We find that the estimated constant _α_ in the value of the account is higher for the Pafupi account compared to the old account for all account holders, regardless of their treatment status in 2015. In addition, the _α_ -coefficient is higher for individuals who received the transfer in 2015 ( _g_ = _T_ and _g_ = _D_ ) compared to those who did not ( _g_ = _C_ ). We test that there is no difference between the two treated groups in the _α_ -coefficients for each account ( _αT_ 0 = _αD_ 0 and _αT_ 1 = _αD_ 1) and find that we cannot reject the null that they are equal (p-values are 0.826 and 0.819 for the old and Pafupi accounts, respectively). Regarding the other term in the value of the account, that is, the coefficient _β_ multiplying the money balance _m_ , we find little difference between accounts for a given experimental group in 2015, but individuals who did not receive transfers have higher _β_ -parameters compared to those who received transfers, and have similar values of other parameters regardless of whether transfers were received in cash or directly deposited into the account. We test that the _β_ -coefficients are the same across these two groups ( _βT_ 0 = _βD_ 0 and _βT_ 1 = _βD_ 1) and cannot reject the null that they are equal (p-values are 0.978 and 0.798 for the old and Pafupi account, respectively).

We also find that the delay treatment did not have an impact on choices as we cannot reject that _δ_ 0 = _δ_ 1 = _δx_ = 1. In addition, while the estimated cost of going to the bank is different across the three experimental groups in 2015, we cannot reject that it is the same in both treated groups (p-value that _cT_ = _cD_ is 0.272). Finally, we cannot reject the null that _λ_ = 1. In fact, in every one of the 200 bootstrapped samples used, _λ_ was estimated at 1.

The results for the full model suggest that we can estimate a more parsimonious multinomial logit model that pools individuals who received transfers in 2015 ( _g_ = _T_ and _g_ = _D_ ) into a single treatment group, and ignores the delay treatment. The results of this model are 11
reported in columns 3 and 4. We again find that the value of the _α_ -coefficient is higher for the Pafupi account compared to the old account for all individuals. For the Pafupi account, individuals who received transfers in 2015 have a significantly higher _α_ -coefficient compared to individuals who did not receive a transfer (p-value is 0.005). For the old account, the _α_ - coefficient for individuals with a transfer in 2015 is marginally higher compared to individuals without the transfer (p-value is 0.113). The _β_ -coefficients are very similar across accounts for people with the same 2015 transfer treatment. Individuals without a transfer in 2015 had significantly higher _β_ -coefficients compared to those with a transfer for both accounts (p-value is 0.011 for the old account and 0.012 for the Pafupi account).

Finally, while the estimated cost of going to the bank is higher for the group that did not receive the transfer, the difference is not statistically significant (p-value is 0.211).<sup>8</sup> Table 3 considers the goodness of fit of both models, reporting the share of the sample that made each of the different choices (not visiting the bank, visiting the bank and closing the old account, visiting the bank and keeping the old account, and visiting the bank and opening a Pafupi account). Odd-numbered columns report shares from the data, while evennumbered columns report predictions from the full model in Panel A and from the restricted model in Panel B. Table 3 suggests that both models can match remarkably well the share of individuals in each choice when using the full sample in columns 1 and 2, the sample of individuals given a transfer in 2015 (columns 3 and 4) or the sample of individuals without a transfer (columns 9 and 10). Because the restricted model does not use information on which individuals received the transfer in cash or directly deposited into their accounts, this model does poorly in matching the probabilities for these subsamples (columns 5-6 and 7-8 in Panel B) compared to the full model (columns 5-6 and 7-8 in Panel A).

Table 3 reports that 54 percent of the individuals who received the transfer in 2015 switched to the Pafupi account, compared to only 37 percent of individuals without the transfer. To better understand whether differences in the propensity to switch accounts between those with and without the transfer are driven by different costs of visiting the bank or different valuations of the accounts, we estimated the model from columns 3 and 4 restricting (a) the value of each account to be the same for each group (that is, _αCj_ = _αT j_ and _βCj_ = _βT j_ for _j_ = 0 and 1) or (b) restricting the cost of going to the bank to be the same ( _cC_ = _cT_ ). We then construct a likelihood-ratio (LR) test with the unrestricted model in columns 3 and 4 and the one that imposes the same cost of visiting the bank and find

> 8Appendix Table A4 replicates columns 3 and 4 of Table 2 and reports a version of the model where the value of each account is quadratic in money balances _m_ . In particular, _vgj_ ( _m_ ) = _αgj_ + _βgj m_ + _γgj m_<sup>2</sup> for _g_ = _C, T_ and _j_ = 0 _,_ 1. We find that the quadratic terms _γ_ of this extended model are not statistically different from zero. In addition, bootstrapped standard errors for this model tend to be higher than in the model where the value of the accounts is linear in cash balances _m_ . We thus use the parameterization that assumes a linear value of the account as our preferred specification.

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a p-value of 0.247. We cannot reject the null that the restricted model is the same as the unrestricted one which allows the cost of visiting the bank to be different across groups, which suggests that differences across groups in the propensity to switch accounts are not driven by differences in the cost of visiting the bank. In contrast, we can reject the null that the model restricting the same value of the account for each group is similar to the unrestricted model (p-value is 0.040), suggesting that the higher propensity to switch to the Pafupi account among individuals that received the transfer in 2015 is driven by the fact that they value the Pafupi account more than those that did not receive the transfer. This result is consistent with Bachas et al. (2019), who show that the rollout of debit cards to beneficiaries of a cash transfer program in Mexico led beneficiaries to check their account balances more frequently, and consequently built trust in the bank.

Table 4 reports the value of the account for both groups of individuals at different percentiles of money balances _m_ . First, we find that the 2015 control group value the old account more than the treated group for all values of money balances _m_ . Second, while all 2015 treatment groups value the Pafupi account more than the old account, the difference in valuation is largest for the treated group, explaining the differences in the propensity to switch to the cheaper Pafupi account.

One might be concerned that account holders who received the transfer may have switched to the Pafupi account in the belief that doing so would increase the chances of receiving another transfer from the research team. Two arguments oppose this interpretation. First, enumerators told individuals that subsidies were being discontinued because the research project (also responsible for the transfers) was ending and had used all of its funding. It is thus unlikely that they were expecting future transfers. Second, as the choice of accounts was presented in a neutral manner, the probability of a transfer should only depend on keeping an account open, regardless of whether it was the basic or Pafupi account. While only nine percent of existing account holders closed the basic account, those who received the transfer were equally likely to close their accounts compared to those who had not received transfers (the p-value is 0.770).

Alternatively, one could argue that account holders who received transfers may have switched to Pafupi accounts because they expected to make fewer withdrawals and thus correctly identified the Pafupi account as being more suited to their needs. While this explanation aligns with our claim that the transfer induced usage and knowledge about the account, panel B of Table 1 shows that account holders who received the transfer expected to make a similar number of withdrawals in the three months following the survey as those who did not receive the transfer. Moreover, using subjects’ own expectations, the Pafupi account would be less expensive than the ordinary account for all account holders in the sample, as long as they maintained the account for at least four months after the subsidies ended. Thus, 13
even if subjects had different expectations about future account use, expectations could not explain why account holders without the transfer preferred the basic account to the Pafupi account.

# **5 Conclusions**

The conclusion of a previous study of subsidized bank accounts provided a unique opportunity to examine the role of experience in shaping financial decisions. From a sample of subjects who opened and owned subsidized savings accounts beginning in 2012, some were randomly selected to receive a transfer in 2015. Such transfers did not have persistent effects on savings or spending, but they did increase the number of transactions and thus experience with the account. In 2016, all account holders were visited at home and presented with the choice of keeping their existing account but paying previously subsidized maintenance fees, closing their accounts entirely, or switching to a new type of account (Pafupi) with a cheaper fee structure. Importantly, based on the number of transactions individuals had made in the past, the new Pafupi account was cheaper than the original account for everyone in the sample as long as their usage patterns continued and they planned to keep the account for at least four months.

While 54 percent of the individuals who received transfers in 2015 switched to the Pafupi account, only 37 percent of individuals without transfers did so. We estimate a multinomial logit model of account disposition allowing the cost of visiting the bank and the valuation of both the old and new accounts to vary by the experience of the account-holder. We find that differences in the propensity to switch accounts is not driven by differences in the cost of visiting the bank but by the fact that individuals that received transfers in 2015 value the Pafupi account more than those who did not. We conclude that individuals who were induced to use the basic account became familiar with it and subsequently switched to the cheaper Pafupi option when presented with a choice.

While policymakers frequently consider active policies to broaden financial inclusion using financial literacy campaigns, our results suggest that making transfers directly into the accounts of individuals may be beneficial as these deposits induce account holders to transact, and the resulting experience can raise financial awareness and improve financial decision making.

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