THE INFLUENCE OF FINANCIAL PLANNING ON THE RELATIONSHIP BETWEEN HOUSEHOLD INCOME AND LEVEL OF SAVING IN TANZANIA

There are many studies on the relationship between household income and saving though very little is known about the influence of financial planning on the relationship between household income and saving.This paper examined the moderating effect of financial planning on the relationship between household income and saving in Tanzania.Based on cross-sectional secondary data (Finscope data,2017) that was collected using multistage sampling from 9457 respondents, descriptive, correlation, regression and moderation effect were performed to analyze the data.The findings indicate that household income and interaction effects have a positive relationship with level of saving. Finally, regression results show that household income and financial planning have a positive significant effect on household saving levels and that financial planning has a positive moderating effect on the relationship between household income and level of saving. From these study results,it is recommended et al. (2013) in their study consider the fact that the increase in household savings has contributed to a risingnational saving rate, which they regard in the case of China to be among the highest in the world. The authors reiterated that an increase in transitory income variance causes younger people (between 20 and 30years) to savemore in order to adjust their buffer stock to the riskier environment thereafter the rate will start declining over time.AlsoAlvarez-Cuadrado et al. (2012) in their study on income inequality and saving indicated a presence of positive relationship between level of income and saving. All these studies show the presence of direct positive relationship between the level of income and the levels of saving. (financial planning) and XM is the product of Household Income and financial planning.The model results show Y = 212570+ 0.135X + 568404M + 1.579XM as the optimal regression model for the variables in this study.

There are many studies on the relationship between household income and saving though very little is known about the influence of financial planning on the relationship between household income and saving.This paper examined the moderating effect of financial planning on the relationship between household income and saving in Tanzania.Based on cross-sectional secondary data (Finscope data,2017) that was collected using multistage sampling from 9457 respondents, descriptive, correlation, regression and moderation effect were performed to analyze the data.The findings indicate that household income and interaction effects have a positive relationship with level of saving. Finally, regression results show that household income and financial planning have a positive significant effect on household saving levels and that financial planning has a positive moderating effect on the relationship between household income and level of saving. From these study results,it is recommended that the government of Tanzania through the ministry of community development, gender and children in should introduce financial awareness programs to the communities in order for the people to realize the need of financial planning and hence improve their saving.Further more the government throughthe ministry of education and vocational training should introduce financial awareness in the school curriculum so that citizens learn how to plan for financial matters at early stages.

ISSN: 2320-5407
Int. J. Adv. Res. 8(12), 622-634 623 According to Asare et al (2018) in a study done on the Africa's economies, saving has a positive impact on the economic growth of a country hence it is a very important aspect that economies need to take into serious account if they want to compete globally. The importance of saving is further highlighted by Brunie (2017) in his research entitled Economic benefits of savings groups in rural Mozambique which found out that saving through saving groups (SGs) allowed households to bridge seasonal food consumption gaps and meet cash needs during crises and accumulated savings supported asset purchases. Jagadeesh (2015) in his study on the existence of a long run relationship between Gross Domestic Product and Gross Domestic savings in Botswana found out that there is significant relationship between Savings and Economic growth.
There is a wide range of Saving rates around the world, for instance on average, East Asia saves more than 30 percent of gross national disposable income (GNDI), while Sub-Saharan Africa saves less than 15 percent (Loayza et al 2000).The authors further reiterate that, regional differences have been rising and over the past three decades saving rates have doubled in East Asia and stagnated in Sub-Saharan Africa and in Latin America and the Caribbean. According to Grigoli et al (2018), Gross domestic savings in Africa averaged only 8 percent of GDP in the 1980s, compared to 23percent for Southeast Asia and 35 percent in the Newly Industrialized Economies. The authors also highlighted that apart from being generally low, saving rates in most of Africa have shown consistent decline over the last thirty years.Domestic savings in many developing countries in Africa for example Kenya have remained low despite the fact that household savings contribute a sizeable share of domestic and national savings in both industrial and developing countries (Njenga et al, 2018).A study carried out by Lubawa et al (2018) showed that there are low savingscapability in Tanzania for most households arising from low incomes due to over reliance on subsistence agriculture. However, Heckman and Hanna (2015) affirms that there are considerable number of researches that disapprove the commonly believed view that many rural households in less developed countries are too poor to save. Saving by rural households has been confirmed beyond doubt (Steinert et al ,2018) Furthermore, Mariyah et al (2018)argues that the level and power to save depends on various factors such as income, interest rates, fiscal factors as well as psychological, cultural and social factors. These social and psychological factors contribute to the motivationof individuals to judge and plan for their incomes in relation to their expenditure patterns and savings. In this case financial planning is reflected interms of financing ability for social events, alternative financing for financial obligations, financing ability in old age and financing for future purchase.Hence planning has an influence on the relationship between household income and the saving. This study will therefore aim at testing the moderation effect of the planning on the relationship between household income and saving.

ISSN: 2320-5407
Int. J. Adv. Res. 8(12), 622-634 624 characteristics and attitudinal variables affect saving and asset accumulation Marshal (1961). Generally, the economic theory creates a belief that a person who is good planner will consume less in the current period and save a portion of the current income for future consumption since there is uncertainty associated with future income. The theory explains the role of financial planning to saving levels of the household in the saving model.

Empirical Literature: Level of saving:
In economics saving is defined as the difference between disposable income and consumption expenditures whether at household or business level (Antwi and Chagwiza, 2018). Beckmann et al. (2013) considers saving as a key macroeconomic variable to economic growth since it is a potential source of investment.Saving is essential to the health of economies and households, yet relatively little studies investigated saving levels among the urban working class in the nineteenth century (Bodenhorn, 2018). Bodenhorn in his study used survey technique in data collection and the analysis which revealed sophisticated saving levels in consistence with life-cycle and precautionary theories. This justifies the saving levels as being influenced by the precautionary motives and old age financial security. The author further highlight that younger households saved less than older households giving a clue of the need for old age income sustenance.

House Hold Income:
According to Mamun et al. (2018) household income refers to "the average monthly income acquired by all members of thehousehold from all possible sources in the last 12 months." Al-Mamun and Mazumder (2015) Considered household income as one of the indicators of household overall economic security which in this case is also a subset of planning on the levels of saving. The authors are also of the view that income is difficult to measure accurately and reliably because it is in a continuous flow and it tends to differ within or between time periods. However, most of the impact studies and for the purpose of this study household income is measured based on respondents' recall of relevant data to solve this problem.
Level of Income and Saving: Antwi and Chagwiza (2018) in their study revealed that organization or household with a health income have a higher propensity of saving. Chamo et al. (2013) in their study consider the fact that the increase in household savings has contributed to a risingnational saving rate, which they regard in the case of China to be among the highest in the world. The authors reiterated that an increase in transitory income variance causes younger people (between 20 and 30years) to savemore in order to adjust their buffer stock to the riskier environment thereafter the rate will start declining over time. AlsoAlvarez-Cuadrado et al. (2012) in their study on income inequality and saving indicated a presence of positive relationship between level of income and saving. All these studies show the presence of direct positive relationship between the level of income and the levels of saving.
Number of Income Sources: Senadza (2014) in his studyclassified Household income sources into six categories, namely, on-farm income(income earned by household from its own farm), farm wage income, non-farm selfemployment income, non-farm wage employment income, remittance income and other income. Data also used in this study identifies household income of the households to be in one or more of these categories. In line with this, Antwi and Chagwiza (2018) comment that when employment opportunities are created, it leads to higher income generation which could translate to higher savings within households and hence the indication of the positive relationship between number of sources of income and the levels of saving.It can therefore be hypothesized that household incomes generally influence the level of household savings in Tanzania.

H 1 :
There is a significant effect of household incomes on the level of household savings Financial Planning: Individual's decision to save is affected by the temptation to consume in the present (Gigerenzer, 2004). This finding indicates that individuals with no planning culture are likely to spend their income haphazardly hence remaining with little or no money left for saving. Paule-Paludkiewicz et al. (2016) on the other hand have identified the significant effect of culture on the saving behavior of households which is a concept deviant from the main theories adopted for the purpose of this study.
Planning for Ability to meet Future Expenses/Purchases:Antwi and Chagwiza (2018) considered savings as an important element for hedging against shocks and emergencies. These scholars associate the concept with the future 625 purchasing power of the farming which is one of the major considerations for saving to carter for future purchase. Karlan et al. (2014) in their study have highlighted some of the important welfare consequences of under saving such as variable consumption, low resilience to shocks and foregone profitable investments. Gjertson (2016)in their study consider saving to be acting as buffer in case of emergencies eventually complementing to the motives for saving. The focus of most of these studies was on project level consisting of several groups therefore it is of paramount importance to shift the focus to the household level.
The fact of future uncertainties has compelled numerous governments to gradually pushing individuals to save for future events through the introduction of supplemental contributory pension schemes for the purpose of facilitating retirement savings (Salleh, 2015). Salleh (2015) further highlighted some of the reasons for saving as the initiation and the maintenance of the children/grandchildren's education. This motive partly gives a clear picture about the concept of financing for future obligations Isaga (2018). This signifies that planning for future uncertainties play a greater role in the motive to saving by individuals and the households.
Planning for Ability to Pay for social Events: Chamon et al. (2013) calibrated a buffer-stock savings modelto obtain quantitative estimates of the impact of rising household-specific income uncertainty as well as another shock to household income. The authors' calibrations suggest that rising income uncertainty and pension reforms lead younger and older households, respectively, to raise their saving rates significantly. The low saving rate presents potential problems in terms of long-term financial insecurity which also influences short term concerns over the ability of households to meet unexpected expenses like social events related to their present needs (Babiarz and Robb 2014).From Chamon et al. (2013) point of view, the same argument can be extended to justify on the consequences of income uncertainties and shocks when it comes to financing for social events. Therefore, this is clear indication that planning for ability to finance social events has a positive influence on the amount of money that can be saved.
Planning for Financial Ability in Old age:Adami et al (2018)also conducted a study on long-term savings accumulation in the UK. The authors used cross-sectional information to compare long-term saving amongst different ethnic groups with the control group, the native population. The authors further applied the life-cycle framework theoretical model to explain saving profiles. The model was specifically used to examine changes in income and saving patterns over the life-course. The theory advocates that individuals make savings decisions to smoothen consumption over different phases of their life-cycle. The findings further indicate that socio-economic factors are key elements in determining whether individuals plan for retirement if factors are controlled for the differences in saving behaviors between ethnic minorities and the control population decrease considerably. Tavor et al (2016) in their study examined the decision-making process involved in saving for retirement in comparison with decision-making processes regarding other financial products (such as loans and savings plans) and the real products (such as a car or a home). In their study, out of the 107 respondents, 95 per cent save for retirement indicating high sensitivity to old age income sustenance in US. Hanna et al (2016) revealed the fact that the household should set its spending in each future period so that it will have enough wealth when it reaches retirement to meet its goal. John (2017) also recapitulates on the fact that a commitment to fixed regular savings deposits can help individuals to achieve the welfare-maximizing level of savings. These arguments giveevidence that planningfor welfare of the future and old age financing has a positive effect on saving levels of the households.
Therefore it can be hypothesized that planning for finances generally influences the level of savings of an individual and a household.

Type of Data and Sampling:
This study is a cross-sectional research aimed at establishing the effect of financial planning on the relationship between household income and savings of the people of Tanzania. The population of the study covers all the regions in the country. Secondary data (FinScope data for Tanzania,2017) was used in this study. FinScope is a nationally representative survey that provides an overview of the financial behavior of Tanzanian adults (i.e. individuals 16 years or older) in terms of how they generate income and how they manage their money.
A multi-stage stratified sampling approach was used to achieve a representative sampleof individuals aged 16 years and older(stratified sampling to obtain EAs-Enumeration Areas followed by simple random sampling to obtain the households and the members to respond to the questionnaires). The sample frame was based on the 2012 Tanzania Population and Housing Census. The sampling design was done byNational Bureau of Statistics in consultation with the Technical Committee and this enhanced the credibility and reliability of the data that was collected. A representative sample of 9459 was used to collect data about the financial inclusion in Tanzania.
This data was collected from April to July 2017 and this shows how recent and dependable it is about the financial inclusion in Tanzania. The data was collected by the use of the face to face structured questionnaire as a data collection tool.

Variables used in this study:
Household level of saving was used as the depended variablein this study. This refers to the level of saving or the total amount of money that the household is able to put aside for future use from the incomes that they earn. This variable captures the amount of money saved monthly by the households which was eventually measured on a continuous scale.The independent variable was household income. This variable refers to the aggregate amount and level of income that has been capturedmonthly. The household income was used an indicator of household saving and was measured on a continuous scale. Financial planning on the other hand has been used as a moderating factor of the relationship between household income and saving. Financial planning variable has been considered to be measured by the ability to pay for the old age obligations, ability to pay for futureexpenses and ability to pay for social events. The planning variable was measured on a binary scale where "1" represented high planning and "0" represented low planning. The study also considered other variables such as gender, marital status, age, education which are supposed to affect household's income and theirlevel of saving (Belkeet al., 2015). In this study cross tabulation of these variables with the variable saving was done to ascertain their influence on the saving.

Age:
This is a variable was used to refer to age of the head of the household. This variable has been measured as a continuous variable in terms of years of the household head. The age of the person has been thought to also influence the amount of savings that the person is able to save. Young people are always thought to saveless that the older ones (Bodenhorn, 2018) because most of their incomes are diverted to leisureand also have less experience on their jobs and hence their salary scales are low. Furthermore, the young people have to establish themselves which explains their low ability to save.

Gender:
This is variable that has been used in this study to refer to the sex of the household head. This variable has been measured as a binary variable with 1 representing Male and 2 representing Female. Gender has been thought to influence the amount of saving that the individual household head is able to save in a sense that the level of saving of females are significantly different from that of males.

Level of Education:
This variable has been used in this study to mean the range of education level that the household head have attained. This variable was measured also a binary variable with 1 representing those below secondary and 2 representing those who completed secondary and above. This variable has been used because it is always thought that highly educated people save more than those who have less education levels because the highly educated know the impact of future financial crisis and also have better financial planning skills.

Estimation Methods:
A number of methods have been employed to analyze the relationships and underlying characteristics of the study variables.

Cross tabulation:
Has been used to obtain the underlying characteristics of the variables and the within group variations across or between any two variables.For example, this has been used to check if the differences in gender has got a corresponding difference in the amount of money that is saved. It has also been used to check if different planning levels have an impact on the amount of money saved.

Correlation analysis:
Has been used to check for the correlation of the variables under study.The correlation coefficients and their significance have been used to ensure that there is no multicollinearity among independent variables and ensure that independent variables are significantly correlated to the dependent variables if they are to be possible predictors.

Regression:
Was used to check for the exitance of the linear relationship between the dependent variable and the set of independent variables used in the study.This was checked use of F-statistic and its significance. It has also been used to check the percentage variation in the dependent variable (savings) that is explained by the independent variables in the study by observing the R 2 of the regression model. Furthermore, this method has been used to check the magnitude of the direction of the effect of the independent variables on the dependent variable by observing the regression model coefficients and the corresponding significances.

Interaction effect testing for moderation:
Was used to check for the moderation effect of financial planning on the relationship between income and saving.This has been done by checking the significance of the effect of the product of household income and financial planning on the level of saving.

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Presentation and Discussion of the Results:-Descriptive statistics:  Table 1 shows the households' number of income sources. Most households (69.9%) rely only on one source of income while about 3% rely on more than three sources which could be one of the reasons for their low savingsas depicted in Table 2 which shows that household savings are positively skewed. This is in line withSenadza (2014) and Antwi&Chagwiza (2018) who found out that the number of income sources are positively related to the level of saving.  This therefore shows that household income and level of saving of the largest portion of the population is low with few people having reasonablyhigh saving and incomes.These results suggest that the low levels of savingsof the household in Tanzania are due to their low household incomes which concurs with the studies of Senadza (2014), Antwi and Chagwiza (2018) and Alvarez-Cuadrado et al. (2012). Therefore, household incomes positively influence the level of household savings in Tanzania. It is paramount to check the influence of level of education on the level of saving of households because sometimes the education level of an individual can have an influence on their perception of saving. For instance, table 3 representing the crosstabulations of the different levels of education and the saving levels shows that the biggest percent ofpeople in Tanzania (88%) are below secondary level of education while those who have education level above secondary account for only 12%.The results concur with the general characteristics of levels of education just like most African countries. It is also evident that almost all the people (98%) have very low saving with only 2% of the population showing some evidence of high saving which could be because the biggest category of lowly educated people are the ones who take up low category jobs and some of them are not employed at all. Therefore, low savings are attributed to the low education levels of the majority of the people in Tanzania which implies that the government needs to invest a lot in education of its people if it's to address the problem of low levels of savings. Gender is one of the personal characteristics that are thought to influence the level of saving of an individual and household. In most African household settings men are thought to have positive attitude towards saving than females because they have an obligation to provide and cater for their families. Results in table 4 show that most households in Tanzania (56%) are headed by females and also 98% of the households have very low savings. This shows a significant effect of gender on the level of saving of the households in Tanzania. Most households that are headed by males have got a higher saving than those headed by females as also illustrated by table 3. This could be because of the cultural beliefs in Tanzania that saving and working is always a responsibility of the males.  Table 5 shows that household heads who are below 30 years of age have very low savings which is in line with (Bodenhorn, 2018). This could be because young people have low experience in jobs and therefore their incomes are low in relation to their low pay category. Also, the people in this group mostly have a high affinity for leisure activities that consume most of their incomes hence making them to have low savings. However, this contradicts with Chagwiza (2018) who in his study asserted that younger people save more. Furthermore, Table 6 shows that actually the people below 30 years have low planning levels and this could also be explaining their low savings. High savings are evidenced in age category (between 30 and 50) in line with Chamo et al. (2013) and this could be because people have enough experience to enhance their incomes but also are in relatively higher pay categories hence saving more. Furthermore, this age category is likely to contain people who have settled families and hence the gross household incomes from all the sources increases and hence allowing people to save more.  Table 6 shows that planning is highest for household heads who are between 30 to 50 years of age.This is because most of these people have families and they need to account for most of their incomes. Therefore, the savings in this category also increase as seen in table 5. Accordingly, the government needs to introduce financial planning culture through trainings to people of different categories in order to improve their saving habits and hence improve level of saving.

Cross tabulation results:
The analysis of the cross tabulation of the control variables with savings has given an inner understanding of someone of the underlying factors that could explain the variation in the level of savings of the Tanzanian households. A more clear explanation for the variation of the saving levels is given by the hypothesis testing of the existence of significant relationships between the dependent and independent variables in the following section.

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Correlation results in table 7 show that there is a significantlow correlation among the independent variables (Gender, Education level, Age, Household Incomes and Planning) because the pairwise correlation of these variables are all less than 0.50 which is very much below the cutoff of very strong correlation of 80% as stated by Hair et al. (2014). This therefore show that theindependent variables are actually independent and hence no multicollinearity. Furthermore, there is evidence of a strong significant positive correlation (r=.278**, p=0.000) between household income and saving which makes sense because the actual practice of saving relies largely on a person's disposable income. This finding is also in line with the studies by Senadza (2014), Antwi and Chagwiza (2018) and Alvarez-Cuadrado et al. (2012). Table 7also shows a significant positive correlation (r=.023*,p=.024) between planning and saving among the people of Tanzania which could be due to the fact that planning enables people to rationally allocate resources. The evidence of the impact of financial planning on saving is also highlighted by Gigerenzer, (2004). From the evidence given by the finding, empirical studies and Neoclassical EconomicsTheory,increase in household income and planning increases the level of saving. Gender is the only control variable that shows a significant correlation with savings according to table 6 and table3. From cross tabulation results in table 4, men save more than women and hence men headed households are more likely to have more savings than other household headed by women in Tanzania. Multiple regression analysis was done for the significant control variable (gender), the independent variables (household income and planning), the interaction term(Planning*Household Income) and the dependent variable (Level of saving) and the model results are shown in table8.The regression model yielded a significantF -statistic (F=1012.6, p=0.000) which confirms the existence of linear relationship between household income, planning, interaction term, gender andLevel of Saving. Furthermore, the model indicated the coefficient of determination(R 2 =0.244) which shows that 24.4% of the variation in the level of saving is explained by gender, household income, planning andinteraction term and the remaining 75.6% is due to other dynamic factors that are not yet considered for example environmental changes, political climates etc which all can affect income and saving of people in Tanzania. From table 8, Standardized beta coefficients show that the most important predictor of Level of saving is household income (beta=0.232) and then followed by planning(beta=0.020) because the larger the beta coefficient the more important the explanatory variable (Hair et al, 2014). These results show that household income positively and significantly affects level of saving because p value is lessthan 0.05 therefore we accept H 1 : household income significantly affects the level of saving and this is in line with the findings ofAntwi and Chagwiza (2018).Furthermore, financial planning positively and significantly affects the level of saving because of itsbeta=0.232 and p=0.00 and this is in line with the findings ofGigerenzer, (2004) hence the hypothesis H 2 is accepted. Table 8 also shows that planning positively affects the relationship between household income and level of saving because the beta value of the interaction term is positive and significant and this confirms the acceptance of hypothesis H 3 hence planning positively influences the relationship between household income and level of saving in Tanzania.
The regression model used in this study is of the form Y = β 0 + β 1 X + β 2 M + β 3 XM(Pokhariyal, 2019)where Y is the Level of saving, X is the Household Income, M is the moderator (financial planning) and XM is the product of Household Income and financial planning.The model results show Y = 212570+ 0.135X + 568404M + 1.579XMas the optimal regression model for the variables in this study.
Results from table 8 identified thatβ 3 the coefficient of XM is positive and significant confirming the acceptance of the hypothesis H 3 hence planning moderates the relationship between Household Income and Level of saving. These results were also confirmed by the scatter plot in figure2 which presents the relationship between levels of savings and household incomes at both high and low planning levels.The use of scatter plots to show moderation is in line with Tang et al., (2009) who identify a more analytic framework for moderation analysis beyond analytic interactions. The figure 2 shows that in presence of financial planning, the coefficient of determination is 0.177 which gives Pearson correlation coefficient of 0.42. Therefore, if the household heads usetheirfinancialplanning skills, the household incomes will positively correlate to their saving by 0.42. In the presence of low or no planning, the incomes are less correlated to savings by 0.077. The results indicated in figure 2 concur with the findings of (Gigerenzer, 2004) who found out that individuals with no financial planning culture are likely to spend their income haphazardly hence remaining with little or no money left for saving. Therefore, financial planning positively moderates the relationship between household incomes and the level of savings in Tanzania.

Conclusion and Recommendations:-
This study sought to investigate the influence of financial planning on the relationship between household income and savings of the households in Tanzania. Keynesian Theory and Life-Cycle Hypothesis theory were used to provide evidence of the relationship between household income and level of saving whereas Neoclassical Economics Theory was used to give the planning-saving relationship. Based on cross-sectional secondary data, descriptive, correlation, regression and moderation effect were performed to analyze the data. Results have shown both household income and financial planning are positive predictors of savings which is also in line with most of the literature reviewed. Findings also show positive relationship between future uncertainties and the motive to household savingwhich agrees with the postulates of Neoclassic Economic Theory. Furthermore, results have indicated that financial planning positively influence the relationship between household income and saving which was the main gap that has been bridged in this study.

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The data collected on all the households in Tanzania was holistically analyzed without demarcations for rural or urban households assuming that they share common characteristics. However, saving levels and planning cultures in rural and urban households may likely bedifferent which is one of the limitations of this study. Furthermore, a longitudinal study could be conducted in the future to show the presence of dynamics between the relationship of household income and saving.This is because there is a likelihood of changes in saving pattern with time hence over reliance on particular period may render inconclusive results.
Finally, the government of Tanzania should involve the citizen in financial planning and management training through the ministry of community development, gender and children by introducing both rural and urban financial literacy training opportunities in order for the people to realize the need of planning. This will help the individuals up to household and national level to improve their saving.Furthermore, the government through the ministry of education and vocational training should introduce financial awareness in the school curriculums so that citizens learn how to plan for financial matters at early stages.

Research limitations:
The data was collected on all the households in Tanzania without demarcating whether it was for rural household or urban household. Saving cultures and financial planning levels in rural households and urban householdsare likely to be different.Analysing saving levels without taking into consideration the two social strata was a limitation of this research.