Households’ saving pattern and behaviour in East Africa

Abstract This paper aims at examining the influence of households’ demographic characteristics on their savings behavior in the East African region. The findings show that nearly people of all gender and age category in East Africa practice life cycle model of savings behavior. It is concluded from the analysis that the preference of savings motive differs from one country to another. However, it is shown that education is highly ranked in all countries as the most preferred savings motive with old-age savings motive ranking the least. Furthermore, the results from cross-tabulation reveal that male-headed households save more often for business purpose than their counterparts female-headed households, in almost all countries; younger head of households save more frequently for business purpose than older ones; and those heads of households with higher income save less frequently for business purpose compared to households whose heads have lower income. Overall, it is concluded that the households’ savings are mostly used for precautionary motives. This implies inadequate social schemes and insurance services in the region. Subsequently, the governments of the East African region are encouraged to improve the health and insurance systems of their respective countries to enhance the income status and lives of their citizens.

Abstract: This paper aims at examining the influence of households' demographic characteristics on their savings behavior in the East African region. The findings show that nearly people of all gender and age category in East Africa practice life cycle model of savings behavior. It is concluded from the analysis that the preference of savings motive differs from one country to another. However, it is shown that education is highly ranked in all countries as the most preferred savings motive with old-age savings motive ranking the least. Furthermore, the results from cross-tabulation reveal that male-headed households save more often for business purpose than their counterparts female-headed households, in almost all countries; younger head of households save more frequently for business purpose than older ones; and those heads of households with higher income save less frequently for business purpose compared to households whose heads have lower income. Overall, it is concluded that the households' savings are mostly used for precautionary motives. This implies inadequate social schemes and insurance services in the region. Subsequently, the governments of the East African region are encouraged to improve the health and insurance systems of their respective countries to enhance the income status and lives of their citizens. Josephat has a massive experience in several academic work appraisal and review. Apart from publishing extensively in both local and international academic journals he is a peer reviewer of several internationally recognized academic journals indexed by SCOPUS and published by highly reputable publishing houses. Professor Lotto's research work focuses on Corporate Governance, Financial Regulations and Corporate Financial Strategies. He has published over 40 academic work. Josephat's work has also been featured in high-quality international journals indexed in SCOPUS and Web of Science-hosted by the most reputable publishing houses such as

PUBLIC INTEREST STATEMENT
In this paper household saving behavior in East African region is studied, with particular emphasis on why households save, how much heterogeneity in savings motives there is across households in the region, and which demographic factors influence choices of savings motives. This topic is particularly relevant in light of the recent financial crisis in the household sector.
Studying which motives drive households' savings within countries at different stages of their life cycle is fundamental for understanding household saving behavior. A regional view like the one provided in this paper on savings gives insights into how country-specific institutional settings shape saving behavior and how differently formal lending channels are developed.

Introduction
The concept of savings and savings culture dates to over 2000 years ago as highlighted even in the holy bible, in both new and old testaments (see for instance, Genesis chapter 41 and the Gospel of Saint Matthew chapter 25). Intrinsically, almost all people including the poor save for several reasons aiming mostly at income risk management, Dercon (1996) and Ravi (2006).
Empirical and theoretical studies have, however, confirmed that the amount of income-based saving the household currently have is irrelevant in as far as the savings behavior of the household is concerned, (Demirguc-Kunt et al., 2018;Friedman, 1957). According to Friedman (1957) in his theory of Permanent Income Hypothesis (PIH), current income does not determine expected longterm average income of the household but rather the long-term income of the household is the function of household's experience, education and the investment portfolio he is currently holding which is the realistic basis of his consumption and savings. According to this theory household temporary variation in households' income has very small impact on consumption, while long-lasting income changes have a significant impact on spending behavior of households.
Furthermore, households in developing economies are also faced with savings problems related to income fluctuation and climate change. They also face restriction in social coverage and poor credit and insurance markets. Following these challenges developing economies usually suffer problems of savings' allocation and hence difficulties in making decisions on productive investments. A source of income for the households in developing economies is another challenge faced by households in developing economies. According to Schmidt-Hebbel et al. (1996) and Bisat et al. (1997), sources of capital investment are numerous but the most reliable one is the domestic or household savings. According to the authors organizing funds from domestic sources is recognized as the catalyst of economic growth in developing economies. In emerging economies like East African countries, the economic life of households is often jeopardized due to uncertainty surrounding climate change and income fluctuation.
Often time, households may want to save due to fear of losing income in future even when their current income is not that stable, and therefore, savings help them to smooth their continuous future expenditures. Also, other households may want to save to increase their future expenditure power. In this case saving money now creates power to finance other future commitments such as honoring car or house loans obligations. On top of that, households may opt saving to accumulate assets in occupational pension schemes, due to fear surrounding their old age during retirement and their choice to save for future generation in form of bequests.
Understanding household saving motives is imperative, particularly, in developing economies where unlike developed countries a reliable social security system rarely exists, and subsequently households are unlikely to have secured and balanced life in the absence of a proper savings plan. So, savings play a very crucial role to encounter financial crises and reduce risk of having inadequate resources in future. The objectives of this paper are therefore two fold; first to assess the determinants of household savings in East Africa, and second to determine the savings motives of the households in East Africa. East Africa is chosen due to geographical closeness of the countries forming the region may limit cultural differences which are pertinent in determining savings culture of individuals hailing from these countries and the results of the study may be of policy interest towards the strengthening of the East African Community financial inclusion agenda.
The paper is structured such that the second section covers all relevant literature, both theoretical and empirical. While in the third section methodology and data issues are presented, section four covers a descriptive analysis before the analytical evidence is provided in section five. The study is concluded in section six with a concluding remark.

Related literature
The knowledge from Economics and Social Science provide the general understanding of households' savings. According to Livingstone and Lunt (1993) saving is considered as the income remaining after consumption. However, Katona (1975) gives a position of an average individual about the savings. According to Katona (1975), to the average person, saving refers to money put in bank accounts or other assets to protect one from future insecurities or to purchase goods and services. Katona (1975) in his behavioral or psychological approach to saving categorizes average persons' savings motive into three group, namely; contractual saving-where one make frequent payment of installment for an asset, which an obligatory saving; discretionary saving-where one deliberately saves; and residual saving-where one does not spend all of income, and therefore, saves by default.
Several studies on household savings behavior show that the motivations of households' savings are derived from two consumption theories, namely, the permanent income hypothesis and the life cycle hypothesis. According to Schmidt-Hebbel et al. (1996) determinants of households' savings include the future usage due to uncertainty surrounding future, smoothing expenditure pattern, investment purpose, life-cycle considerations, resource accumulation for huge purchases and the inheritance motive. The permanent income hypothesis envisages that an unforeseen increase in the future income compared to the present income slows down current savings contrary to the Keynesian point of view (Hall, 1978;Flavin, 1981).
Authors such as Deaton and Paxson (2005) and Rogg (2006) spell out a gap between investment and savings as the most pressing issue in developing economies, and due to this problem, it becomes very difficult for required investments to be funded via domestic savings. Nevertheless, studies on savings ignore the savings behavior of savers/households and according to Touhami et al. (2009) studies which ignore borrowing behaviors of the savers come up with results which do not take into accounts the real-world environment which reflect a range of saving behaviors. Additionally, it should be clearly understood that borrowing and saving are twin concepts, and they are designed in such a way that the behavior of households towards these two actions are interactive.
Literature proposes several reasons for saving including precautionary motives, future consumption motive and speculative motive (Dardanoni, 1991). Using Bulgaria, Hungary and Poland data Denizer et al. (2002) show that saving and income are directly related although the source of income is not relevant. The authors, further, indicate no relationship between unemployment and saving behaviour of household. According to the authors the insignificant relationship between unemployment and savings in transition economies is not a surprise because those who are unemployed usually use their savings to fund their consumption, and if the rate of unemployment is predicted to increase households save more for precautionary purpose. Savings motives are different across countries. For instance, Kraay (2000) considers precautionary reasons, social safety net, low level of financial development, life-cycle motives, culture, habit, corporate saving, and unintended consequences of social policies as the Chinese households' savings motives.
Empirical studies underline factors affecting households' savings such as changes in the tastes and preferences, social security and capital markets. Stiglitz (1993) provides the explanation for low household' savings. According to the author one of the influential factors which inhibits households from savings is the propagation from people that people live today, and future must take care of itself. The author claims that changes in the households' tastes are among the key factors affecting households' saving in USA.
Stiglitz (1993) also comes up with another factor, social security, insisting that the development of social security benefits contributed to lowered saving rates in the United States of America because social security operated like a pension funds where people contribute into social security fund during their work life and secure it back, with interest, during retirement.
Another study by Carroll and Summers (1991) recognizes improved functioning of capital markets as another key factor which contribute to the lowering level of households' savings. According to the authors, because borrowing is simply the converse of saving, instead of keeping money to be consumed in future, borrowers prefer spending today and repay in future. In another way they substitute current consumption for future consumption in an event when it is cheaper to borrow than to save leading into substitution effect.
Several empirical studies are conducted on the factors affecting households' savings. Guariglia (2001) studied the relationship between savings and households' age and found that age is inversely related to savings. The study finds that younger households save more than their older counterparts. This is inconsistent with the life-cycle theory. This finding is in line with that by Foley and Pyle (2005), in which households save to alleviate temporary income blow. According to Foley and Pyle (2005), households who own assets have lower savings because they already have assets, if the motive of saving was acquiring assets.
Using Pakistan data, Carpenter and Jensen (2002) examined the relationship between household characteristics and saving behavior. The authors found that as households' income increases households tend to increase their savings level, and that there is no savings difference in Pakistan between urban-based households and rural ones. Contrary to Carpenter and Jensen (2002), whose emphasis was on the supply side of savings, Kulikov et al. (2007) focused on the demand side of household savings. Using Estonia household budgetary survey, Kulikov et al. (2007) found that the rate of household savings is more dependent on the temporary income than ordinary income. Kulikov et al. (2007), further, identify other determinants of households' savings such as the status of employment market or the ownership of the non-financial assets. The authors also show that access to finance has a statistically insignificant impact on household savings behavior.
In another study by Klause et al. (1992) income variables are reported to be strongly associated with households' savings. Likewise, Touhami et al. (2009) examined the micro economic factors which influence households saving in Morocco, and they report that income significantly explains the cross-sectional variation of the saving behavior of households. Similarly, Girma et al. (2013) determined factors affecting rural household savings in Ethiopia. Such factors include education level of head of household, households' income and access to finance, among others.

Data
This study adapted data from World Bank's 2017 Global Findex. This is a survey data constructed from survey done by Gallup, Inc. employing comprehensive interviews which involved over 150,000 people around the world nationally representative and respondents randomly selected. A household, which ha civilian aged from 15 years and above, is the unit of analysis in this study. The database categorizes the information by demographic characteristics of the households such as age, gender, income level and education. Furthermore, the database also provides the savings motives of household which include business motive, education motive, future old-age motive and medical motive. The study chose the sample of selected East African countries with about 1000 respondents in each country namely, Tanzania, Kenya, Rwanda, Uganda, Burundi and South Sudan.
The East African region is chosen because the countries forming this region are geographically close, which may limit cultural differences. Culture is a pertinent variable in determining savings behaviors of households, as depicted by Raza Ali (2012) who clearly pointed out that culture is an integral part of every society and shapes the wants and behaviors of individuals, and that the influence of culture on behavior varies from country to country. Therefore, understanding households' savings behavior in East Africa is very crucial, and the results of the study may be of policy interest towards the strengthening of the East African Community financial inclusion agenda.

Analytical framework
Like in Chowa et al. (2012); H and Hailu (2014); Teshome et al. (2013) this study employs descriptive analysis, inferential analysis and econometric models. Descriptive analysis is used to estimate descriptive statistics such as frequencies, percentages and cross tabulations. To examine the association between savings motives and demographic characteristics, the paper employed cross tabulations. This is the statistical process that gives the summary of categorical data to generate contingency tables. In this study a comprehensive contingency table is generated for savings motives and demographic characteristics. The paper also used bar charts to summarize the savings motives across the region. On the other hand, Binary logistic regression model was used to estimate the relationship between major saving motives and household demographic characteristics such as age, sex, education and income. This model is preferred because it allows use of both numeric and categorical data, unlike a usual Ordinary Least Squares (OLS) estimators that allows only continuous. The choice of this model was guided by Gujarati, (2007), and similar model is used by Lotto, (2019). Therefore, the model is specified as follows; is dummy taking a value of 1 for a household whose income lies in low (40%) quintile, zero otherwise and INC 2 is dummy taking value of 1 for household in high income level (60%) quintile, zero otherwise EDU = (EDU 1 and EDU 2 ); EDU 1 is a dummy taking a value of 1 for a household whose education lies in low (40%) quintile, zero otherwise and EDU 2 is a dummy taking a value of 1 for a household whose education lies in high (60%) quintile, zero otherwise.
The 40% and 60% quintiles are adopted from Global Demirguc- Kunt et al. (2018). In this model each of the regression coefficients β, σ, φ and ρ shows the extent to which the independent variables (gender, age, income and education) contribute to the overall influence on dependent variables (savings motive). A positive regression coefficient implies that the independent variable increases the odds of outcome, while a negative regression coefficient means that the predictor decreases the odds of outcome; a large regression coefficient means that the predictor strongly influences the odds of the outcome; while a near zero regression coefficient means that the predictor has little influence on the odds of outcome.

Descriptive analysis
The data from Demirguc-Kunt et al. (2018) allows the analysis of status of household savings behavior across the world. The survey reports that, worldwide, on average around 17% of the adults take loans and make savings for starting or improving their business activities. The survey further shows that those households' members who engage in business are involved in borrowing and savings for business motive than any other households. This finding is in line with that of research conducted in USA by Demirguc-Kunt et al. (2018) reporting that the savings rate of entrepreneurs is higher than general population. However, some literatures such as Okraku and Croffie (1997) argue that households depend primarily on their personal savings, and sometimes business profits, if any, for their financial needs. During the Global Demirguc-Kunt et al. (2018) survey the respondents from East Africa were asked whether they prefer saving their own money to use for business purpose, and about 88% of those who answered this question preferred saving money rather than borrowing when a need for finance arises.
In understanding the behavior of household savings, the survey asked households to tell their savings motives, and their response is presented in Figure 1 below. In general, they identified three major savings motives, namely; old age, medical motive and business motive. Figure 1 show that the savings motive differs from one country to another. The highly ranked savings motive in Burundi, Rwanda and South Sudan is medical while in Tanzania, Kenya and Uganda households save more for business. In general, Figure 1 shows that households save for medical purpose more than any other motives in Burundi, Rwanda and South Sudan. However, when it comes to businessmotivated savings Tanzania, Kenya, and Uganda do rank high in that order.
When it comes to savings for old-age motive, the survey shows that Kenya is ranked high (15%) followed by Uganda (14%) and closely followed by South Sudan (13%); and then Burundi and Tanzania with 3% and 6% respectively of their household's savings for old-age motive. This shows that all countries do not focus so much on savings for old-age motive. The reason may be due to either a presence of good pension systems of the countries, which may cover the life of the households during old-age, or because the business they engage into currently may be used as the security in their old-age. Countries where households save for medical purpose are believed to be highly associated with poor medical services. This has been confirmed by Atlas of African Health Statistics (2017). The Atlas of African Health Statistics (2017) report is consistent with the findings in this study because its finding show that health service availability (a measure of health care access and service readiness which is a proxy indicator for health care quality and safety) is 64% in Tanzania, 77% in Kenya, 61% in Uganda, 50% in Burundi, 49% in South Sudan and 48% in Rwanda. These statistics from Atlas of African Health Statistics (2017) clearly show that, because of relatively poor quality of health services in Burundi, Rwanda and South Sudan households from these countries will tend to precautionarily save more to take care of the health challenges when they occur, as compared to countries such as Tanzania, Kenya and Uganda where health care is relatively good.

Analytical evidence
In this part the association between saving motives with the demographic characteristics of the households, across the region, was established using cross-tabulation. Starting with gender; results presented in contingency Table 1 show that female-headed households save more for medical purpose in Kenya (37%), Burundi (31%), South Sudan (15%) and Rwanda (26%) and those headed by men save more for medical purpose in Uganda (28%) and Tanzania (11%). It is further observed, in Table 1 that, the households headed by men save more for business purpose in all countries (Tanzania (25%), Kenya (44%), Uganda (42%), Rwanda (18%) and South Sudan (15%)) except in Uganda (32%) where women-headed households save more for business purpose compared to their counterparts, male-headed households. Table 1 further shows that Kenyans' households save more often for business purpose than all other countries in the region regardless of the household's gender, age, income level or education followed by Uganda, Rwanda, and then Burundi in that order. The countries whose households save less for business purpose are Tanzania and South Sudan, which are almost at par when compared. Furthermore, Table 1 shows that households headed by women save more often for medical purpose than their male counterparts in Kenya, Rwanda and Burundi while in Tanzania, Uganda and South Sudan men-headed households save for medical purpose more often than women-headed households.
Generally, the contingency Table 1 depicts the following important associations; first, maleheaded households save more often for business purpose than female-headed households in four countries (Tanzania, Kenya, Rwanda, South Sudan) except in Uganda and Burundi. This may echo the level of women entrepreneurship in Burundi and Uganda. Second, the association between savings for business motive and age shows that younger head of households save more frequently for business purpose than younger ones. This is in line with Guariglia (2001) who report that younger households save more than their older counterparts, which is consistent with the life-cycle theory. This finding is also consistent with that by Foley and Pyle (2005), who claim that households who own assets have lower savings because they already have assets, if the motive of saving was acquiring assets. This may be due to the facts that savings may be the only reliable source of financing businesses since borrowing for business needs some larger funds requiring collateral in terms of fixed assets, which younger heads of household may not possess.
The age of the head of household may also be an advantage to him/her because with age his/ her income may be on a higher side due to more experience and probably education, hence, possessing more assets, which can back-up his/her, loan. Third, consistently throughout the region, those heads of households with higher income save less frequently for business purpose compared to households whose heads have lower income. The reason is clear because individuals with higher income will probably own more valuable fixed assets which can be pledged as collateral for loans acquisition compared to individuals whose income status is questionable.
Furthermore, Hosmer and Lemeshow Chi-square was used to test whether, overall, our binary logistic regression model is fit as suggested by Garson (2008). According to Garson (2008), If the goodness of fit test statistic is above 0.05, then the models estimates fit the data at an acceptable level. In this paper the data fed into the model sufficiently fitted the model, as the test statistics is significant at 1% with p = 0.015 which is presented in Table 2 Measuring the impact of households' demographic features; age, gender, education and income on the savings' motives is achieved by looking at the signs of regression coefficients (either positive or negative). According to Garson, (2008), to test the significance of individual logistic regression coefficients for each independent variable, Wald Statistic was used. The Wald statistics illustrates the extent to which each of independent variable contributed to the probability of an individual to choose the saving motives.
A negative β coefficient shows that a variable associated with such a coefficient decreases the logit of the dependent variable meaning that it decreases the probability of the household choosing a particular saving motive while a positive β coefficient indicates an increase in the probability of the household preferring a savings motive. The logistic regression results in Table 3 depict that that education is the only independent variable which is positively related to the choice of the savings motives, and this may imply that education level increases probability of household choosing a savings motive. It should also be understood that a choice of savings requires planning knowledge and the analysis of future uncertain financial situations. The individual with a good level of education may be in a better position to decide whether he/she saves now for either retirement motives or for business motives as opposed to an illiterate individual. Therefore, to choose a better savings motive one may be required to have a certain level of education which may help him to analyze savings motives options. In contrast, the results show that other remaining variables-sex, age, and income have no impact of increasing chances of household choosing saving motives. Generally, the results suggest that education is a significant factor to a decision choosing a savings motive.

A concluding remark
This study explored the influence of households' demographic characteristics on their savings behavior. The descriptive analysis shows that nearly people of all gender and age category in East Africa practice life cycle model of saving behaviour. Therefore, households keep saving for use in future for various key purposes such education, old-age (retirement) and health care. It is concluded from the analysis that the preference of savings motive differs from one country to another. It is further shown that that the highly ranked savings motive in all countries is savings for medical motives except for Tanzania and Uganda where business motives preside. On the other hand, the study shows that the least preferred savings motive by all households across the region is the savings for old-age purpose. This shows that households in all countries do not consider savings for old-age motive as their priority. The reason may be due to, either a presence of good pension systems of the countries, which may cover the life of the households during old-age, or because the business they engage into currently may provide financial security in their old-age.
The study may conclude that countries where households save more for medical purpose are believed to be highly associated with poor medical services as confirmed by Atlas of African Health Statistics (2017).
The results from cross-tabulation reveal the following; first, male-headed households save more often for business purpose than female-headed households in four countries (Tanzania, Kenya, Rwanda, South Sudan) except in Uganda and Burundi. This may echo the high level of women entrepreneurship in Burundi and Uganda. Second, the association between savings for business motive and age shows that younger head of households save more frequently for business purpose than older ones. This is due to the facts that savings may be the only reliable source of financing businesses because borrowing for business needs some larger funds requiring collateral in terms of fixed assets, which younger heads of household may not possess. The age of the head of household may also be an advantage to him/her because with age his/her income may be on a higher side due to more experience and probably education, hence, possessing more assets, which can back-up his/her, loan. Third, consistently throughout the region, those heads of households with higher income save less frequently for business purpose compared to households whose heads have lower income. This may be because individuals with higher income will probably own more valuable fixed assets which can be pledged as collateral for loans acquisition compared to individuals whose income status is questionable.
Finally, logistic regression results show that that education is the only independent variable which is positively related to the choice of the savings motives, and this may imply that education level increases probability of household choosing a savings motive. In contrast, the results show that other remaining variables-sex, age, and income have no impact of increasing chances of household choosing saving motives. Generally, the results suggest that education is a significant factor to a decision of choosing a savings motive because individuals with good education may be in a better position to acquire financial literacy skills which may enable them to analyze choices of savings motives as opposed to their illiterate counterparts.
There are policy implications associated with major findings of this study that-most saving are mostly used by households in East African Region for precautionary motives. This implies inadequate social schemes and insurance services in the region, and this means that the households in the region have no advantage of using social schemes and insurance services which may free savings for use on other livelihood aspects. Therefore, the governments of the East African Region are encouraged to improve the health and insurance systems of their respective countries so as to improve the income status of their citizens.