An investigation on the determinants of opening a bank account in Zimbabwe

ABSTRACT

The promotion of an inclusive financial system has become important to many countries in policy crafting. The study seeks to explore the determinants of opening an account with a bank in Zimbabwe. Data from Finscope Survey 2014 was used to estimate probit models and for robustness check Linear Probability Models. Using these data, the socioeconomic factors influencing individuals in deciding whether or not to open an account with a bank in Zimbabwe is analysed. According to our analysis, the decision to open a bank account by individuals is influenced by Location, Age, Gender, Marital status, Proof of residence, Employment history and Level of Education. There is need to build inclusive financial systems through different policies by governments and central banks. Financial literacy education and financial inclusion campaigns are paramount in improving levels of people opening bank accounts.

KEYWORDS:

• Financial inclusion
• Zimbabwe
• bank account
• economic growth

JEL CODE:

• E5

1. Introduction

The purpose of this study is to investigate the determinants of opening an account which is an important element of financial inclusion (FI) in Zimbabwe. Financial Inclusion (FI) can be defined as the access and use of formal financial services in an appropriate way. Financial services play a pivotal role in development as it facilitates economic growth and improves livelihoods. FI helps in reducing poverty and the entire economy is also set to grow. Inclusive financial systems permit poor people to prudently manage their consumption and guarantee themselves against unforeseen economic vulnerabilities. Financial inclusion facilitates the efficient allocation of productive resources. Financially inclusive systems make it possible for poor people to save, borrow, venture into business and possibly seek financial advice. This then gives them the urge to build assets or portfolios, invest in education and business ventures to develop better standards of living. Inclusive finance also benefits disadvantaged groups of the society such as youth, women, disabled and rural folks. In a study at global level, Allen et al. (2012) find a direct relationship between higher income and financial inclusion. For this cause financial inclusion has been on the agenda for organisations such as G20, IMF, World Bank and other regional blocs gaining prominence recently to improve quality of lives around the globe.

There are a number of studies done on FI issues in many countries but there is none that have considered the determinants of bank account opening in Zimbabwe using cross-sectional data. Having an access to a transaction account is the starting point toward broader FI since people are able to receive, store and send money (World Bank, 2016). A bank transaction account serves as a doorway to other financial services and ensuring that people across the globe have access to these services is the main goal of the World Bank Group’s Universal Financial Access 2020 initiative. Opening a bank account is regarded as the entry point of the broad aspect FI and the crafting of policies is centred on it. A bank account ushers in many benefits to an individual, community and the entire economy (Ellison et al., 2010; Dermigüç-Kunt et al., 2013; Ghatak, 2013; Clamara et al., 2014). The use of financial services empowers the poorest and vulnerable in the society to be emancipated from poverty and reduces inequality. The use of formal bank accounts enables individuals and families to save resulting in economic growth. People are able to manage and save money and by consulting experts they acquire knowledge and skills that enable them to make informed financial decisions. Formal financial system participants (financially included) get the opportunity to start and grow businesses through access to credit. Bank account users are able to borrow to finance their education that develops generations of educated and informed citizens. Being financially included helps cushion one in periods of financial shocks. The use of bank accounts promotes investments within the community, providing job opportunities that in turn boosts Gross Domestic Product (GDP), income and status.

The world today has more than 50% of its adult population financially excluded, in other words they do not have accounts with banks (World Bank, 2014). According to the World Bank, the world has approximately 7 billion people of which 4.2 billion are adults. Out of approximately 4.2 billion adults, only 1.9 billion have accounts with banks. In Africa, there are 230 million (75%) households unbanked (World Bank, 2014). International forums such as the Bretton Woods institutions, the Group of Twenty (G-20) and European Union(EU) have moved up the reform agenda, reflecting the transformative power of financial inclusion and its implications for reducing poverty and fostering shared prosperity. There are a number of studies revealing a correlation between financial inclusion and economic growth or stability in a country. Unfortunately, real-world financial systems are far from inclusive, with more than half of the world’s adult population having no bank accounts (World Bank, 2013, 2015). Globally, it is reported that only 44% of the world’s youth today have an account with formal financial institutions and 1.3 billion of women are still outside the financial system (Global Findex, 2017).

Zimbabwe may boast of more than 90% adult literacy rate (UNDP, 2015) in the country but has 69% of the population living below the poverty datum line which was USD500 as at 31 December 2016 (ZIMSTAT, 2017). In Zimbabwe, about 83% of the population have no accounts with banks, whilst 17% benefit from inclusive financial systems (FinScope, 2014). Basic financial services such as bank accounts and credit facilities are not available or accessible to many in almost all classes of the society. This implies that those who are financially excluded are being hindered from economic and social integration. There are financial services gaps that exist within certain segments of the population that the Central Bank, government and financial players have to ensure that they are filled for high financial inclusion levels to be achieved.

The majority of the population in Zimbabwe has no accounts with banks (Finscope, 2014) despite the fact that there are 13 commercial banks, 1 merchant bank, 4 building societies and 1 savings bank in the country (RBZ, 2018). It is also estimated that there is USD3 billion (RBZ, 2015) circulating in the informal sector whereas the yearly budget of the country is approximately USD4 billion (Ministry of Finance, 2017). There is need to address this problem by promoting opening of bank accounts by individuals.

There are barriers that need to be eliminated for people to be financially and socially included. The problem of low FI may be difficult to address without identifying the determinants of opening bank accounts. A coordinated cross-governmental approach is essential in addressing financial inclusion issues and such initiatives need to mirror the language used by service users. There is need to build inclusive financial sectors that help people improve their lives.

Although FI has become a topical issue on the global policy agenda, literature on financial inclusion remains scarce. Several researchers have focused their efforts on investigating factors that influence FI in various countries but no study on what influences account opening in Zimbabwe. It is worth noting that bank accounts have been used as a proxy for FI by many researchers (see Allen et al., 2012; Martinez et al., 2013) and this has been driven mainly by lack of data. Other studies have focused on varying levels of financial inclusion in both emerging and advanced economies (Martinez et al., 2013; Potrich et al., 2015; Tuesta et al., 2015). Zimbabwe among other developing countries has the financial inclusion situation not significantly improved (World Bank, 2016). Majority of the people are financially excluded and high levels of poverty still prevail. In comparison to other developing and developed countries, Zimbabwe’s FI levels are too low though with great potential. This study contributes to the existing literature by finding the determinants of opening bank accounts using a detailed and wide covering survey done in Zimbabwe. This shall be achieved by investigating the factors influencing bank account opening in the country using data from Finscope Household Survey (2014). This study asks the following question: what are the factors that influence the decision to open a bank account in Zimbabwe?

The rest of the paper is arranged as follows: Section 2 presents Literature Review; Section 3 describes the data used; Section 4 outlines the research methods used; Section 5 reports, analyses and discusses the results; and Section 6 concludes.

2. Literature review

The major theory to be surveyed in the literature is based on the premise that financial inclusion or access to and use of formal financial services improve the livelihoods of people (ADB, 2013; World Bank, 2014). In other words, financial inclusion reduces poverty. One is financially excluded when there is difficulty of access to basic financial services (Ardic et al., 2011). Financial exclusion can be voluntary (self-exclusion) and involuntary. Self-exclusion may be due to lack of trust on the banking system, ethnic or religious reasons and involuntary exclusion is mainly due to various unfavourable conditions. A number of studies concur that formal financial services such as microcredit and savings can produce a progressive impact on a variety of microeconomic indicators, including self-employment, business activities, household consumption, and well-being (Kedi, 2003). Benefits of inclusive financial systems are not limited to the microeconomic level. As individuals benefit, non-experimental evidence shows that broader financial inclusion also corresponds with greater local economic movement and reduced economic inequality at the macroeconomic level.

Low financial inclusion in a society acts as a retardation to development as it slows economic growth, giving rise to poverty and inequality (Nava et al., 2011; World Bank, 2013). In other words, if the Gini Coefficient is high close to one or one (representing perfect inequality), there is need for models that bring the coefficient down. There are a number of theoretical models that confirm that the presence of financial exclusion is the root of persistent income disparities or poverty traps (Basu & Mallick, 2007; Beck et al., 2007; World Bank, 2015). A number of studies and wide-ranging empirical literature has found a strong relationship between economic development and financial inclusion. Reforms that promote broad access to financial services should be at the centre of the development programme (Reyes et al. 2011).

Until up to the 1970s, the Kuznets hypothesis appeared to be applicable especially in the developed world. There appeared to be a virtuous circle, with more disparity resulting in greater growth, which lead to reduced inequality. The downward movement in equality reversed significantly in recent years. The position that inequality enhances development was contested more by several cross-country regressions showing a negative correlation between the average rate of economic growth and inequality measures (World Bank, 2006). A case study of South Korea and the Philippines development trends appeared similar in the early 1960s, except for the extent of income inequality. Over the next 30-year period, production in the Philippines that had more inequality barely doubled, and the fast economic growth in South Korea resulted in fivefold increase of output level.

Financial development may pass down to the underprivileged through its impact on economic growth and production. This comes as a result of the understood positive link between financial inclusion and economic development. Several studies have supported the trickle-down theory and these include Ravallion & Datt (2002), Mellor (1999), Dollar & Kraay (2002), Fan et al. (2000) and the World Bank (1995). On the contrary, Fishlow (1995), in a study on the connection between inequality, poverty and economic growth using data from Latin America, no support for this theory was found. The author found that the economic growth in that region was not accompanied by a decline in poverty. The findings were attributed to the prevailing great levels of inequality in Latin America. On the same note, Basu & Mallick (2007), in examination of the significance of the trickle-down outcome in rural India, little evidence suggests that the effect had been experienced. The little evidence was attributed to the occurrence of capital-labour replacement in India, which hindered growth from poverty reduction. Dreze & Sen (1990) argue that financial inclusion generates little or no benefits in terms of a number of non-pecuniary methods of well-being. As a matter of fact, some development economists argue that economic improvement that emanates from greater financial sector growth does not essentially advance the lives of the poor. It is also argued that instead growth developments typically trickle up to the middle and rich class. Generally, the direct relationship between financial development and poverty alleviation springs from the availability or accessibility of formal financial institutions, instruments and services to poor households (Holden & Prokopenko, 2001). Therefore, it is necessary to grow an inclusive financial system in Zimbabwe.

The rise of poverty in the United Kingdom in the 1980s and 1990s was attributed as one of the boosters of financial exclusion, connected to the rise of inequity in income redistribution, and to the decline of real income of the poorest segments of British society, but the average income of the country kept growing (Olit, 2012). Kenya implemented various innovative finance solutions that transformed economic, financial and social landscape of the country (Musau et al., 2017). Through these initiatives, there was a great improvement of formal account holders. The initiatives included the mobile-phone financial services drive, shariah compliant services and the agency banking model among other services launched in 2010. The developments have ushered in immense opportunities for achieving sustainable development, inclusive economic growth and poverty reduction (Mugo & Kilonzo, 2017).

Many researchers have found that inclusive growth can be achieved through financial inclusion (Bhandari, 2008:479; Ellison et al., 2010:71; Ardic et al., 2011:270). There is need to make formal financial services available to all segments of the population as there is an anecdotal evidence suggesting that informal financial services are at least 5–10 times more costly and also less reliable than formal ones. Therefore, availing formal and affordable financial services to the unbanked would definitely have positive consequences on the lives of these people, and economic growth (Klein & Mayer, 2011:179).

Several studies have focused on the determinants of FI which is broad and few studies have focused specifically on opening of bank accounts although it is the gateway to financial inclusion.

There are a host of factors that have been found to contribute to high levels of financial exclusion in an economy that include proof of residence, proof of identity, distance, employment history and remoteness of place are some of the factors affecting financial inclusion (Rani, 2010:775).

In a study that used a sample of 500 respondents looking at demand-side factors affecting financial inclusion in India, in Ghatak (2013:3) the following independent variables were identified: Inflation, Occupation, Literacy, Resistance to change, Physical Assets, Accessibility, Transaction Costs, Technology, Fear, Dominance of a group, Saving, accessibility, culture, income, Cost of Living. In Zimbabwe, inflation may not be significant in determining opening of bank accounts since inflation levels are low and relatively stable since the adoption of the multicurrency regime in 2009. Resistance to change and fear variables are one and the same thing, fear of change is one of the most common reasons for resistance to change and measurement of thereof is subjective (Demirgüç-Kunt & Klapper, 2012). In some countries the variable of dominance of a group and physical assets are insignificant as there may not be different groupings and opening bank accounts not influenced by possession of physical assets (Bhatnagar & Gupta, 2013).

In a study focusing on factors influencing the intentions to use banking Services in Yemen, Al-Qasa, Isa and Othman (2013) found the following determinants to be significant: bank advertisement; service quality; Legal framework; and cultural belief. However, the study did not consider determinants such as Location, Age, Gender, Marital status, Proof of residence, Employment history and Level of Education. Being there no study that also focused on determinants of opening a bank account using rich data set and probit model estimations, this study seeks to fill the gap by investigating factors influencing account opening in Zimbabwe.

In a study to investigate the factors influencing FI in rural Kenya, Kimutai (2015) found that network access, financial education, infrastructure and agent quality determined FI in Kenya. The study used a sample size of 113 commercial bank agents situated in different parts of Kenya. In an investigation of factors influencing FI in Peru, Clamara et al. (2014) found the following as determinants of FI: age, income level, education and gender. The study used a household survey but Peru and Zimbabwe differ in many aspects such that determinants of opening accounts may be different. Prabhakar et al. (2016) found the following as the determinants of FI in India: products, frequency of need of banks services and physical distance. Although products is an important factor to consider given the availability of data other factors such as age, gender, marital status and education were ignored in this study. Also Prabhakar et al. (2016) focused on the determinants of financial services usage not on account opening determinants.

The existing literature has the following weaknesses: (1) non considered Location, Age, Gender, Marital status, Proof of residence, Employment history and Level of Education in a single study focusing on opening bank accounts; and (2) no study on determinants of bank account opening was done in Zimbabwe. There is need for identification of all factors contributing to accessibility, affordability and appropriateness of financial products and services to all segments of the population ((Rani, 2010:775). If factors, reasons or barriers to opening of bank accounts are identified, solutions to financial exclusion problems can easily be solved. The aim of developing inclusive financial systems requires an understanding of factors causing exclusion and social difference (World Bank, 2008).

3. Methodology

The Finscope Survey uses a random selection of eligible members in each household by Kish Grid. The survey carried out 4000 face to face interviews across all provinces in Zimbabwe covering both rural and urban areas. The survey provides very valuable information that allows us to analyse elements of financial inclusion that have not been studied before, due to lack of appropriate information at the national level (Table 1). The survey generates information about the characteristics and statistics of users and non-users of formal and informal financial services. Finscope Survey 2014 was carried out by Finmark Trust, ZIMSTAT and Ministry of Finance in 2014. The survey provides very valuable information that allows us to analyse elements of financial inclusion that have not been studied before, due to lack of appropriate information at the national level. The survey generates information about the characteristics and statistics of users and non-users of formal and informal financial services.

Table 1. Descriptive statistics.

Characteristics of Individuals	Frequency	%	Mean
Total number of respondents	4000	100
Location			0.346
Urban	1384	35
Rural	2616	65
Gender			0.42475
Male	1699	42
Female	2301	58
Marital status			0.65075
Married	2603	65
Not married	1597	35
Level of Education			2.94825
None to Early Child Development	178	4
Grade 1–7	1375	35
Form 1–6	2087	52
Dip/Cert after Primary	37	1
Dip/Cert after secondary	214	5
Graduate/Post Graduate	109	3
Average (years)			40.1025
18–25	785	20
26–35	1092	27
36–45	860	21.5
46–55	512	12.8
56–65	400	10
66–75	227	5.6
76–85	124	3.1
Proof of residence			0.07875
With proof of residence	315	8
No proof of residence	3685	92
Employment history			0.94075
With history of employment	3763	94
No history of employment	237	6
Level of income($)			0.051231
No income	262	6.55
1–100	2211	55.28
101–200	480	12
201–300	285	7.15
301–400	158	3.95
401–500	153	4
501–1000	110	3
1001–2000	30	0.75
2001–3000	5	0.12
3001–4000	4	0.1
4001 and above	2	0.05
Refused/Don’t know	282	7.05

Source: Finscope Household Survey (2014).

To address the research objective that seeks to determine factors influencing the opening of bank accounts in Zimbabwe an econometric model was created. We have estimated probit models to investigate the determinants of opening bank accounts by an individual. The methodology used is similar to that used in Martinez et al. (2013).

In this analysis the probit models take as the dependent variable, BA, whether an individual has an account with a bank or not (1 if the person has an account and 0 if not). In a binary response model, interest lies primarily in the response probability$P(\text{BA}=1|x)=P(\text{BA}=1|x_1,x_2,\dots ,x_{\mathrm{k}}),$where BA is a financial inclusion indicator and x is the full set of explanatory variables.

The Linear Probability Model (LPM) is used largely to enable us to directly obtain coefficient estimates rather than the estimation of scaled coefficients that are obtained with the probit model, which then need to be transformed. Since the focus of this study is on factors affecting the decision to be financially included, this should not be a problem, as both the LPM and the probit model generally produce similar coefficient estimates at the mean (Wooldridge, 2009). To address a potential challenge with the LPM, which is heteroskedasticity (which invalidates statistical inference), the standard errors in our models are robust to heteroskedasticity. To avoid the LPM limitations we then consider a class of binary response models of the form$P(\text{BA}=1|x)=G(b_0+{\beta }_1{x}_1+\cdots +{\beta }_{\mathrm{k}}{x}_{\mathrm{k}})$where G is a function taking on values strictly between zero and one: 0 < G(z)< 1 for all real numbers z. The logit and probit models are used in the vast majority of studies and it is a matter of preference (Wooldridge, 2009:575). In this study, probit models are estimated alongside LPM for robustness check. In the probit model, G is the standard normal cumulative distribution function (cdf), which is expressed as an integral:$G\left(z\right)=\mathrm{\Phi }\left(z\right)=\underset{-\mathrm{\infty }}{\overset{z}{\int }}\mathrm{\Phi }\left(v\right)\text{d}v,$where ɸ(z) is the standard normal density and ɸ(z)= $\left(2\pi \right)$^−1/2exp(−z² /2).

We then conduct maximum likelihood estimation as a series of probit models. The binary choice model was created from Q8.4 in the questionnaire that asks the following question: ‘Do you currently have a bank account(s) in your name? It could be a joint/group account on which your name appears.’

The dependent variable, the decision to open an account (BA) with a formal financial institution depends on many explanatory variables. Having a bank account or not, is a measure that is widely used as a proxy for financial inclusion (World Bank, 2014). We then need to estimate the following model:$Pr\left(\text{B}{\text{A}}_{\mathrm{i}}\right)={\beta }_0+{\beta }_1\text{Ag}{\text{e}}_{\mathrm{i}}{+}_2\text{Ge}{\text{n}}_{\mathrm{i}}+{\beta }_3\text{Ma}{\text{r}}_{\mathrm{i}}+{\beta }_4\text{Proof}\mathrm{\_}\mathrm{R}\mathrm{e}{\text{s}}_{\mathrm{i}}+{\beta }_5\text{Lo}{\text{c}}_{\mathrm{i}}+{\beta }_6\text{Ed}{\text{u}}_{\mathrm{i}}+{\beta }_7\text{Em}{\text{p}}_{\mathrm{i}}+e_{\mathrm{i}}.$

3.1. Variables included in the model

Variables considered are those in accordance with the literature and availability of Finscope data may influence financial inclusion. Below is a brief description of the variables included in the probit models and the reasons for using them.

3.1.2. Proof of residence (Proof_res)

When opening an account with a bank, one is asked to provide evidence of identity and confirmation of a physical address (World Bank, 2011). This can be a harrowing experience for those who have no required documents in their name. In the UK, having no proof of address is a massive hurdle to jump before you can set up a current account which enables an employer to pay wages directly into one’s bank account (European Commission, 2010). Some required documents, usually all documents must be original. Utility bills, local authority bills, tenancy agreement, current council rent book and mortgage statements are some of the documents that are generally accepted as proof of residence in many countries (World Bank, 2011). For the model estimated proof of residence is included as a dummy variable for those with required documents (See Table 2).

Table 2 Description of variables.

Variable	Question	Definition	Label
Location	Q109 Is the respondent from rural or urban?	Dummy: 1 if urban and 0 if from rural.	Loc
Age	Q10.7 How old are you in complete years?	Ranging from 18 to 85 years	Age
Gender	Q10.6 Is the respondent male or female?	Dummy: 1 if male and 0 if male.	Gen
Marital status	Q1.9 What is your marital status?	Dummy: 1 if married and 0 otherwise.	Mar
Proof of residence	Q1.381/2/4 Which of the following documents do you have? Read out response and multiple responses possible. Item 1. Electricity/water bill Item 2. Telephone i.e TelOne bill. Item 4. Lease or rental agreement (e.g vehicle or house)	Dummy: 1 if yes for item 1, 2 and 4; and 0 if not.	Proof_res
Level of education	Q1.10 What is the highest level of education you have completed?	With 6 categories ranging from none/ECD to Graduate/Postgraduate.	Edu
Employment history	Q1.11 Have you ever been employed?	Dummy: 1 if yes to Q1.11 and 0 if no.	Emp
Bank account/no bank account	Q8.4 Do you currently have account(s) in your name? It could also be a joint/group account on which your name appears.	Dummy: 1 if yes and 0 if otherwise.	BA

Source: Finscope Consumer Survey Zimbabwe (2014).

3.1.3. Employment history (Emp)

The nature of employment also matters as there is a higher probability of one having a bank account if formally employed unlike a situation where one has no formal employment (Clamara et al., 2014). In case of a household with nobody formally employed the chances of it being financially included are very small compared to the one with someone employed. In Spain, among the financially excluded population the unemployed or those with no history of formal employment were most likely to be financially excluded. On the contrary, some studies reveal that in Spain, unemployment does not seem to be a factor of significance in defining financial exclusion in rural areas. In the model, these variables are taken as dummy variables for those who have been employed before.

Educational level (Edu)

As the level of education rises, levels of financial inclusion tend to increase (Lewis and Messy, 2012). Research has found that financial exclusion is prevalent in mostly disadvantaged communities with lower education standards and resulting in much bigger problems of social exclusion. Some studies have shown that individuals with only primary education are more likely not to own financial services or products compared to tertiary graduates (Messy & Monticone, 2012).

Levels of education impact not just the possession of a financial product but also the use of channels to access the products. From a study done in Australia, in terms of product ownership, education level was found to be a significant indicator for financial exclusion in all essential services identified. In this model education variable is a series of dummy variables depending on the age of the respondent. There are 6 categories ranging from None/early child development to Graduate/post graduate.

3.1.4. Marital status (Mar)

Marital status is a basic variable related to access and use of financial services (Martinez et al., 2013). When someone is in marriage there is a high probability of financial inclusion and in many cases a joint account. It has been found that for a single person one is less bothered by the need to have an account as living from hand to mouth is common. Cano et al. (2013) argue that for Columbia marriage reduces the probability of being in the financial system. The same study in Columbia asserts that married men are more likely to be financially included. In the model, the variable is taken as a dummy variable for married individuals.

3.1.5. Location (Loc)

Geographical area is one influential factor determining financial accessibility of people living in remote, rural and marginalised areas. Some studies find different effects of location of individuals to financial inclusion (Murcia, 2007; Kedir, 2003). Studies in the UK have shown that financial inclusion or exclusion is geographically concentrated (European Commission, 2010). Location is a dummy in the estimated model based on whether one is staying in rural or urban area.

3.1.6. Gender (Gen)

Accessibility of financial services is different for men and women. In a survey done in Mexico, results show that 42% of men use formal saving and only 30% of women do so. A number of studies have also shown (Johnson, 2004; Allen et al., 2012) that women have fewer possibilities of accessing formal financial services, so most public policy interventions are focused on promoting financial inclusion among women (Samaniego & Tejerina, 2010; De los Ríos & Trivelli, 2011). For the model estimated, gender is included as a dummy variable.

3.1.7. Age

In any population, age is a factor that can influence the level of financial inclusion or exclusion. The public tend to consume and use less with age according to Modigliani’s life-cycle theory. In reference to this theory, people gather savings during their adult life and de-accumulate later in old age (Deaton, 2005). This means that the level of financial inclusion is higher among the economically active people and that of financial exclusion is higher in old age and the minors (Barnet & Solow, 2000:246). A research done in Mexico confirmed and supports this finding, while in Spain, it was revealed that the elderly (retired), and the young people under 25 years have common features in terms of financial exclusion or inclusion patterns. In line with the life-cycle theory, as age increases the probability of no interest in financial services falls though up to a certain stage. Therefore, it is interesting to find out the behaviour of this variable in the Zimbabwean context. For the model estimated age is taken as a series of dummy variables depending on the age of the respondent ranging from 18 to 85 years.

Physical access: The greater the distance from a bank branch the less the chances of FI. This this is still an influential factor as branchless banking (sophistication) is still in its infancy in the country. The growth in the use of internet banking, debit cards, credit cards and so on may reduce the influence of branch use in the country, hence growth in FI. Distance from financial services provider is quickly losing its importance (Brevoort & Wolken, 2008:1) but this remains influential in service provision in Zimbabwe. This is an important factor influencing financial inclusion but in this study it was left out as the aspect of distance or time to the nearest bank was not covered in the questionnaire.

4. Results and discussions

Table 3 presents results estimated from LPM and probit model. Both estimated results of LPM and probit show that all variables are significant in influencing the decision to open a bank account in Zimbabwe. But in this study, Probit results shall be reported. The estimated coefficients reveal which factors influence respondents to open or not to open an account with a bank. A statistically significant coefficient suggests the likelihood of holding an account with a formal financial institution, will increase/decrease as the response of the explanatory variable increases/decreases. All variables are statistically significant at 1%, 5% and 10% levels.

Table 3. Linear probability model (LPM) and probit models on factors determining financial inclusion.

	LPM	Probit
VARIABLES	BA	BA
Location	0.161***	0.692***
	(0.0125)	(0.0553)
Age	0.00194***	0.00901***
	(0.000366)	(0.00168)
Gender	0.0928***	0.391***
	(0.0114)	(0.0520)
Marital status	0.0269**	0.0988*
	(0.0118)	(0.0543)
Proof of residence	0.182***	0.510***
	(0.0217)	(0.0835)
Education	0.0654***	0.241***
	(0.00482)	(0.0193)
Employment	0.0856***	0.492***
	(0.0238)	(0.133)
Constant	−0.304***	−3.120***
	(0.0308)	(0.166)
Observations	4000	4000
R-squared	0.1470	0.1503

Standard errors in parentheses.

Source: Author computation using Stata.

***p < .01, **p < .05, *p < .1.

According to the probit model results, an individual in an urban area is more likely to be having an account than the one from rural areas. Location of an individual has a great influence on decision making of whether to open an account or not. One living in town is more likely to have an account with a bank than the one in the rural areas. This is in line with the studies of Murcia (2007) and Allen et al. (2012) that report differential effects on financial decision making according to one’s location. It is important for the central bank and other stakeholders to push for the agent banking model to deliver banking and financial services to the rural since the branch model (teller/cashier) may not be viable. Atandi (2013:408) found that there was a growing need to promote institutional and technological innovation to expand financial system usage and access. In the same study, Atandi reports that Kenya had made strides in addressing these financial system infrastructure weaknesses by promoting agency banking.

On gender variable, results show that males are more likely to have an account than their female counterparts. This confirms findings in a number of studies in developing countries, where man are likely to be financially included than women (Demirgüç-Kunt et al., 2013). There is, therefore, need to empower women economically and encourage them to open bank accounts. Projects and business training focusing on women empowerment will go a long way in increasing FI levels in Zimbabwe. Different women pressure groups can join with commercial banks and other stakeholders to encourage women to engage in small projects by the provision of credit facilities and promote bank savings (see Muhammed, 1998).

The more one is educated the greater the probability of financial inclusion of that individual. There are many studies (Mitton, 2008; Kempson et al., 2013) that have shown the similar results where education has a positive influence on financial inclusion. In addition to academic knowledge, the population can be encouraged to open accounts by pushing for financial education as suggested in Lewis & Messy (2012). The argument is that when one is educated s/he may still need financial education or knowledge to make informed financial decisions.

Age is significant in determining whether one has an account or not. The results show that getting older increases the likelihood of having a bank account. The results are in line with Martinez et al. (2013) who found the same in Mexico. The main reason is that in Zimbabwe due to economic hardships youth (18–25years) unemployment is high and there are little opportunities for other sources of income. One is likely to be financially independent at a later stage in life. There are many young people (18–35 years) who are still under the care of their parents or rely on others for basics of life. In such cases, the head of the household is likely to be having a bank account. The solution lies on the economic opportunities growing as people access loans and other financial services benefits that improve their welfare. Opening bank accounts and taking advantage of governments subsidised credit facilities (Ozili, 2018) will go a long way in addressing the high financial exclusion levels in Zimbabwe.

History of formal employment has a positive influence on financial inclusion according to the results. Once one was or is currently formally employed it is more likely that the individual has an account than one who has not. In many cases, the account would have been opened mainly for the purpose of salary or wage receipting. The findings are in line with that of Olit (2012) in a study in Europe, stating that statistically it is proven that unemployment is the most meaningful circumstance pushing to be at risk of financial exclusion. In Zimbabwe, the majority of those who earn salaries are paid through the bank and pay tax. In this regard, the government and its agencies have to work on formalising the economy that is largely informal for better FI levels to be attained.

On proof of residence, if one has the required papers such as telephone bills (Telone), electricity/water bill, and lease/rental agreement, chances are high of finding one with an account. Results show a positive correlation between financial inclusion and proof of residence in Zimbabwe. Proof of residence has caused many to go without bank accounts. Globally, lack of documentation has hindered many from opening accounts (Demirgüç-Kunt & Kappler, 2012) with formal financial institutions. However, a formal letter from the employer to a permanent employee has become popular in Zimbabwe. Without proof of residence, it is almost impossible to open an account with a bank in Zimbabwe. There is need to relax the requirements for documents and perhaps make use of affidavits where one can swear before a commission of oaths and identity cards. This will remove the barriers that currently hinder many from opening accounts with banks.

The results also reveal the significance of the marital status variable to influencing financial inclusion in Zimbabwe. In Zimbabwe, when one is married/living together/cohabiting, the individual is more likely to be financially included. The reason may be that if one member of a household opens an account others tend to rely or use the same account (joint accounts). Also the question that was asked in the questionnaire also includes having a joint account. In a household, it is easier to maintain one account being used by both parties. The finding contradicts that of Martinez et al. (2013) on a study done in Mexico, where they conclude that the variable of being married or living as a couple is not significant in that country. However, more bank accounts can be opened if monthly service and other transaction charges are reduced, as joint accounts are a way to avoid prohibitive bank charges. There are a number of success stories across the world where special accounts are opened for the unbanked that attract no charges (see Garg & Agarwal, 2014).

5. Conclusions and recommendations

The analysis reveals that in Zimbabwe important factors influencing opening of bank accounts include age, gender, proof of residence, marital status, education, employment history and location. These factors can also be of influence in a number of developing countries.

There is need for the government through the central bank to encourage or motivate the public in rural areas to open bank accounts through various ways. This can be done by massive FI campaigns in rural areas starting with the remote ones and a financial education drive. Financial institutions can also be encouraged to open branches or establish agents in rural and remote areas as physical access (distance) remains an important factor. Regulations must be put in place to motivate universal access and financial innovation for provision of the best supply of financial services and products for the population. There must be a law that prohibits a bank from denying a national identity card carrying citizen from opening a basic account (transaction/savings) as proof or residence and other documents required have hindered many from accessing formal financial services. An identity card must suffice for a savings or transaction account and no one must be turned away because of failure to produce too many documents required by banks.

On the aspect of education, Zimbabwe’s high literacy levels have failed to yield high financial inclusion levels according to statistics and regression results. It is important to highlight a serious gap of knowledge of the banking sector in Zimbabwe that includes financial markets and financial products. It is not a problem unique to Zimbabwe as in Europe it has been reported as one of the main factors aggravating the consequences of the financial crisis for many families. Improvement of financial education (financial literacy) levels must be a target for the Zimbabwean banking industry and this must also target avoiding over-indebtness and financial exclusion of families and individuals. Also through proper financial literacy education to women especially through existing women pressure groups more women may be encouraged to utilise bank accounts. Through financial inclusion awareness programmes, whether one is on a formal job or not, opening of bank accounts may also be encouraged.

The results with respect to the factors influencing the decision to open a bank account enable the Zimbabwean population to enjoy the benefits of financial inclusion. Financial inclusion remains important for the people to be capacitated to deal with financial shocks by using banking services. The use of informal financial services or markets may be viewed as lack of knowledge or financial illiteracy regarding formal financial services. A number of studies have demonstrated that financial capabilities allow individuals to develop skills, understanding and knowledge on financial services operations so that there is adequate personal finance management. The ultimate goal is to see income levels and standard of living improving in the country through financial inclusion.

For this research, however, more objective indicators of account use would have been ownership of an account, frequent use of account and use of the account to save. Also the variable of distance or time taken to the nearest bank was missing which would have been very informative. Income is also a crucial factor but the variable was not provided for in the data. The aspect of social media is increasingly becoming important to financial services delivery across the globe since it brings convenience and cheaper ways of doing business. Subject to availability of data these variables can be considered in future studies. These were not provided for in the survey used and future studies can consider them.

Acknowledgements

The author is grateful to Finmark Trust for the permission to use their Finscope Survey 2014 data. The author is also indebted to colleagues who assisted with valuable comments.

Disclosure statement

No potential conflict of interest was reported by the author.