The Role of Start up Capital in Poverty Alleviation. A Case of Buwama Sub-County Mpigi District

Ben Ssembajjwe¹

Abstract The need to discover the impact of the ‘start up capital’ credit scheme in alleviating poverty among the household of Buwamasub-county laid a foundation for this research. The study tested the hypothesis that accessibility funds from start up capital scheme improved the welfare of beneficiaries. Primary data was collected from 88 respondents and analysed using an econometrics model. Empirical results of the analysis indicated that, access to funds from the credit scheme, expenditure on health and distance from the household to the nearest market significantly increases the probability of a given household being poorat a level of 1%. Other variables considered were insignificant, but they reduce the probability of a household being poor. Occupation of the head of the household and the value of physicalassets owned by the household and the education level of the household head had a negative impact expected outcome. The study recommended comprehensive training of the household heads before advancing credit, efforts should be stepped up to increases the level of education, opening more markets and improving infrastructure in terms of roads. It was also recommended to revisit the scheme to ensure amount given to beneficiaries is sufficient and reduce the interest rate.

Keywords: poverty; buwama-subcounty; startup capital; poor and credit

JEL Classification: M21; I32

1. Introduction

Countries have succeed in achieving rapid economic growth which is narrowing the gap between themselves and the more advanced countries bringing millions of their people out of poverty and raising their GDP/per capitawhile others have actually seen the gap growing and poverty increasing (Sitigltz, 1998).Uganda’s poverty over the past 3 decades largely has been due to the country’s low levels of development (GDP) and some economic prolonged instabilities which destroyed productive assets, infrastructure and depreciated human capital. It should be noted that because may of Ugandans cannot afford basic needs such as water, health, clothing there is urgent need to tackle poverty by directly improving the income the poor people.Chirwa (2002) notes that one of the major causes of poverty in developing countries is a lack of access to productive resources, Using another measure of poverty Hughes etal (2015) revealed that more than 1.2 billion people in the World are striving to survive below $ 1,25 a day which the UN and World Bank described as extreme poverty (UNDP,2008) Further, more it is estimated that in Uganda unemployment rate is 3.6%. It should be noted that the rate left out the students who benefit on services of microfinance. In a study undertaken by Muhumuza (2013), he contended that the proportion of people living absolute poverty is even much worrying in poor countries such as Uganda. Until recently, people living in absolute poverty in Uganda had declined from 56% in 1992 to 44% in 1997 and 34% in 2000 but rose to 38% in 2002. However, 50% of the population could not meet their basic requirements. Poverty in Uganda is a rural phenomenon which is 96 of the poor living in rural area. Poverty continues to be regionally concentrated with north and east having the largest proportion of poor population.The government of Uganda through the Ministry of Finance, Planning and Economic Development instituted a programme of startup capital credit scheme to provide credit to the rural poor. The scheme was meant to operate as a revolving fund, however, it was not the first of its kind many programmes had been implemented earlier ; these included the Rural farmers scheme, which aimed at assisting farmers with short term credit at lower interest rates than what was prevailing in the market, this scheme was mismanaged and failed. Unlike the Rural farmers scheme the startup capital credit scheme targeted the poor who lacked collateral or are prohibited by institutional factors and therefore cannot access credit under the traditional lending system. The broad objective of the scheme was to reduce the level of poverty by creating a revolving fund to support microenterprises among the rural and urban poor especially the youth and women in Uganda.Buwama sub-county is one of the places with the scheme beneficiaries. This sub-county is one of the areas where poverty had worsened with floating of coffee prices and fishing activities were reduced due to poor fishing methods. There has been a considerable effortby the government of Uganda aimed at poverty reduction. One of the programmes that was implemented in that respect is the startup capital credit scheme. Although the scheme was put in place to reduce th3 levels of poverty among the rural and urban poor, through accessing startup capital for development of own micro enterprise, it seems that this objective was not achieved in Buwama sub-county.

2. Statement of the Problem

Since the coming of the National Resistance Movement came into power there has been considerable efforts by the government of Uganda aimed at poverty reduction. One of the programs implemented in this respect is ‘Start up’ capital scheme. Although, the scheme was launched to reduce the levels of poverty among the rural and urban poor through accessing startup capital for development of own micro enterprises, it seems that this objective has not been achieved in Buwama sub-county. Thus the major objective of this study was to investigate the impact of startup capital scheme among other variables on the welfare of it beneficiaries in Buwama sub-county in Mpigi district. will establish the effectiveness of the scheme in improving peoples standards of living, this will have policy implication on how it can be utilized by all stakeholders in poverty redication in the Ministry of finance and economic Planning, Local administrators and Non Governmental organization operating in the area.

3. Literature Review

3.1. Poverty in Uganda

According to statistics Uganda which use a national poverty line of US $ 1 per person per day. 38% of the population live in poverty (Muhumuza, 2013).The birth rate of Ugandans is 5.78 per woman. The enrollment is school is still low where enrollment in primary 8.3million and Secondary school is 1,284,008 and health services are poor. Due to the high rate of unemployment, majority of the population is engaged in informal sector which requires financing through loans. The working population total to 13.9 million people. One of the symbols of poverty in Uganda, are the high levels of income inequality. Income inequality is high and by 2013, the rich were only at 0.395 UBOS (2016) being at the extreme and the poor can hardly afford basic necessities. In a study undertaken by Muhumuza (2013), he contended that the proportion of people living absolute poverty is even much worrying in poor countries such as Uganda. Until recently, people living in absolute poverty in Uganda had declined from 56% in 1992 to 44% in 1997 and 34% in 2000 but rose to 38% in 2002. However, 50% of the population could not meet their basic requirements. Poverty in Uganda is a rural phenomenon which is 96 of the poor living in rural area. Poverty continues to be regionally concentrated with north and east having the largest proportion of poor population. However, income inequality has worsened with gin-coefficient rising from 35% in 1997 to 38 in 2002 (MFPED, 2001). Such a gini-coefficient is an indicator of inequality in income which is thus an indicator that poverty in Uganda is not yet a legend but continues to be the word of mouth in the daily conversations of the citizens. World Bank (2007) also contends that the national poverty line fell by 1.6% in 2006 compared to 1.9% for 2005 and the international poverty line fell by 2.7% per year. The report revealed that in the year 2013, between 30.5% to 30.9% of the people in Uganda were using bicycles as a means of transport, about 36.7% could afford using mobile telephones, only 1.7% to 19.6% could afford electricity and only 0.4% could afford piped water. Uganda National Health Survey (2013) concluded that majority of the people in Uganda fall between the very poor (36.3%) and poor (56.5%). Therefore, whether poor or very poor, it is true that the people are poor in general. The 2014 census indicated that 82% of Uganda’s population lives in rural areas given the higher rates of poverty in rural Uganda compared to urban Uganda.

3.1.1. Approaches to Poverty

There are basically three major approaches to poverty, they include among others; the monetary, capabilities and social exclusion. They are analyzed here under.

3.1.2. Monetary Approach

This approach looks at poverty in monetary terms by asserting that poverty is seen in terms of what level of income one has and the degree at which one can afford their basic needs using their income available as suggested by Lederchi, et al (2003). The approach considers the ability of a person to afford basic needs of life by looking at how much consumption a person can make in a given period of time.

Since the monetary approach basically focuses on the level of income one has and how it can enable them to afford basic needs, there is a need to adopt a more interdisciplinary approach and that is the capability approach below.

3.1.3. Capability Approach

The concept of capability approach looks at the capacity of a human being in terms of development. It focuses on the level at which a human being is able to develop using the available income and the capacity to afford their basic needs. It does not focus on monetary aspects as the monetary approach (Sen 1993). Sen (1993) argues that in this case, income is seen as a secondary item that helps in improving one’s welfare. Therefore, monetary resources are not an end but a means to an end. Thus fulfilling one’s needs goes beyond one’s having money. It is a combination of both monetary and non-monetary resources instead of the sufficiency or adequacy of one of these resources.

It should be the interplay of the two categories. However, Sen (1993) did not foresee the reality that monetary resources remain crucial and critical in as far as achievement of different capabilities is concerned as commented by Olowatomi (2015). It is in most cases by use of money that individuals can afford various basic needs. The challenge with the Monetary and the

Capability approaches is that, they only focus on individuality where they consider a person suffering from poverty alone without minding about how such an individual interacts with others in society. Therefore, there is need to embark on a more socialistic approach to understanding poverty and this is the social exclusion approach presented below;

3.1.4. Social Exclusion Approach

The matter of Social Exclusion (SE) was born in highly industrialized economies to explain the character marginalization that can occur even within wealthy countries with too much welfare pensions. The European Union defines SE as a process through which individuals or groups are fully or partially excluded from full participation in the society or area in which they live (Lederchi, et al (2003). The implication here is that being poor limits someone from participating in productive activities in society. These may range from political, social, religious, cultural, and economic and other forms of social settings in which one may not participate because they are poor and thus seen not to be having meaning in society. On a similar vetting style, Room (1995) presupposes that social exclusion is the denial or non-realization of civil, political and social rights of citizen. Room (1995)’s argument is similar to the capability approach as it goes beyond monetary issues to other aspects of life. On a slightly contrary note, Saunders (2003) contends that social exclusion is an issue that is caused by a linkage of multiple socialization weaknesses which a person may have. These may range from lack of money, inability to afford better health care, inability to afford better means of transport among others all of which interplay to make someone not liked in society or not be excluded from social connections. Just as it sounds social exclusion, a person has less ability to interact easily with others and thus has a high level of inferiority complex. However, Levitas (2000) analyzed that, those prior scholars do not fully explain what really happens when there is social exclusion. Their focus is on simply talking about social exclusion but do not explain what happens if it is there in terms of which impact it has on one’s life. In a deeper understanding, Atkinson (1998) identifies three main characteristics of social exclusion and these are: relativity which is exclusion being relative to a specific society; agency being excluded as result of agents; and dynamic implying that future prospects are just as relevant as current circumstances. The dynamic characteristic emphasizes the process of the causes of deprivation. These are the distinguishing features of this approach from the others are reviewed in this study.

4. Presentation and Analysis of Results

The study looked at the demographic social characteristics of the respondents, specifically the study looked at the education level and occupation of the household’s heads, distance from the household to the nearest market and the value of a given households assets. Education level of the Respondents, 5.7% had no formal education at all while 55.0%had primary level of education, while 33.3%had ordinary level of education while 4.4%had advanced level of education. Only 2.3% had tertiary/university education. Occupation of the households’ head the majority of the household interviewed (59.6%) were headed by people involved in smallholder farming while 40.4% were headed by people in salaried employment. In addition, distance of the household to the nearest market was and the study found that 12.2% of the household interviewed live within less than two kilometers to a market while 50.0%t of the households are located between 4.1kmand 5.0 km to the nearest market. Of the households covered 4.5% were located more than 5.0km to the nearest market. Given the poor state of transport infrastructure in rural areas. It was important to note that households located more than 3.0km to the nearest market would be quite far. This may negatively impact on such household’s capacity to market their produce, thereby increasing their probability of being poor. Monetary worth of the physical assets were also considered by the study. The study covered assets whose monetary vale ranged from Ushs.550,000 and 12,500,000. The majority of households interviewed (49%) were ranging between one and three million value of assets and only 8 percent ranged between eight and twelve million. The study also inquired into the projects undertaken the different household heads using the loan funds. The majority 29.5% of the households heads invested their money in tomato growing projects while brick making projects had the least with 4.5%. Other projects that included, piggery and coffee buying both had 9.1% each fishing 6.8% and others had 22.7%. The study had to examine the amount received by the beneficiaries the majority (54.4 percent) of the household’s head who were interviewed received 200,000 Ugandan shillings. Only 6.8 percent obtained 500,000 Ugandan shillings. Each of the scheme beneficiaries had to pay an interest of 12 percent.

The study establish the effect of individual variable on the probability of a given household being poor Alogit model was estimated using Stata programme. Interpretation of the results of the logit analysis was done in two ways, the sign of the parameters estimation as well as their statistical significance. And the marginal effects of the explanatory variable on the probability of an event. A positive sign of a parameter estimate suggests that the likelihood of a given household being poor increases with increase in the level of the respective other variables being held constant depending on whether the variable is continuous or dichotomous. Conversely a negative sign of a parameter estimate implies that the likelihood of a given household being poor decreases with an increase in the level of the variable. The results of the logit model estimates indicated that access to funds from the scheme, increase in expenditure on health and distance from market increased the probability of a given household being poor, on the other hand increase in year of schooling, value of asset owned family size, and being employed in salaried employment lowers the households’ probability of being poor. The table below indicates the results giving the sign and significance of the coefficient

Table 1. Results of the Logit Model

Source: Primary data, 2018

The dependent variable is the logit which is the ratio of the probability of being poor to the probability of being no-poor. The results from the table indicates that access to funds from the scheme and an increase in house hold expenditure on health significantly increase the probability of a given household being poor. On the other hand a unit increase in family size was found to significantly reduce the probability of a given household being poor. This may be explained by the fact that most households rely on or partially in smallholder farming using own labour. The more household members translate to more labour and thus increased production, thereby reducing the probability of a given household being poor. The other variables failed the significance tests at the conventional of 1%, 5% and 10% levels implying that impact of such variable on the probability of a given household being poor is not stability of a household be statistically different from zero. Besides estimating the signs of the parameter estimates and their statistical significance the study estimated the marginal effects of the explanatory variables on the probability of being poor. This was done by estimating the marginal effects after logit. This is indicated in the table below,

Table 2. The Marginal Effects of the Factors Influencing Poverty on the Probability of the Household Being Poor.

Source primary data, 2018

The results from the table below show that accessibility to funds from the scheme increases the probability of a given household being poor by 0.32. the variable was significant at 1% level. This is contrary to the stated hypothesis that accessibility to funds from the scheme reduces the probability of given household being poor. The alternative hypothesis that accessibility to funds from the scheme increases the probability of a given household being poor, is accepted, this may be explained by the fact that insufficient amounts of money were given out with short repayment period, high interest rates and conditionalites such as one opening up a bank account so that money is channeled through the bank. The conditionalities reduced the money received by the scheme beneficiaries as the necessary costs of satisfying the conditionalities were charged against the loan obtained. This compounded by the fact the interest was charged on the whole amount of credit given including the proportion injected into non-productive activities. Besides the scheme beneficiaries were just given credit without prior training on how to maximize returns from the credit accessed. These factors combined are probable explanation for the un expected findings that accessing funds from the scheme increases the probability of a given household being poor. The study also found that a unit increase in the number of years of schooling for household head reduces the probability of household head being poor. Similarly, a unit increase in the monetary worth of assets owned by a household reduces the probability of a given household being poor by 0.590.A unit increase household being poor by 0.00003. The variable was significant at the 1 percent level of significance. This implied that a unit increase in household expenditure on health significantly increases the probability of the household being poor. This is consistent with economic theory as sickness increases the number of work days lost, a situation that is compounded by increased on health. This reduces the level resources available to the household, and thus increasing the probability of such a household being poor. However, the magnitude by which expenditure on health would increase the probability of a household being poor was very small ie, 0.0003.The probable explanation for this is that household expenditure on health was very low due to several reasons; for example, some people may not go for treatment when there are sick, others use traditional medicine. Further, the high cost of medication in the modern health centers/hospitals prevented a number of people in rural areas from going for treatment in the formal health centers. This limited expenditure on health in rural areas. A unit increase in the size of household reduced the probability of a household being poor by about 0.17 the variable was significant at the 1 % level of significance. This was explained by the fact that in Agrarian economies like Uganda and Buwama sub-county in particular, production is mainly done using family labour. In such instances an increase in family size implies an increase in labour and thus increased production. This eventually transforms to a reduced probability of a given household being poor.

The study also found that household heads located far way from markets are more likely to be poor than their counter parts, who are nearer to the markets. The study established that a unit increase in the distance between households and the nearest market will increase the probability of a given household being poor by 0.62. Household located far way from markets are constrained in marketing their produce, leading to reduced incomes. Consequently this may lead to increased probability of such a household being poor. The study established that the occupation of a household head plays a role in deterring the poverty level of the house household. It was discovered a shift from small holding to salaried employment as major occupation of a household head reduce the probability of a given household being poor by 0.11 the variable was however, not significant at 10% level of significance. One probable explanations for the occupation in salaried employment reducing the probability of a given household being poor may lay in the stable incomes earned. This facilities predictable saving and investment planning decision. In the long run, this impact on incomes earned which lead to reduced probability on a given housed being poor. The reason for this variable being insignificant would lie in the fact that few respondents were employed in the formal sector. And few respondents had education qualification beyond secondary level (2.3%) which would grant them formal salaries employment. Conversely, households mainly depending on small holder farming do not receive regular income, as the sale of their produce is usually irregular. This may further compounded if the household is located far away from the market. In such instance, the probability of the households being poor increases.

5. Policy Recommendations and Areas for Further Research

The study recommended a comprehensive training programme in the relevant areas before extending the credit, interest rates on the credit charged to be reduced and conditionalities of opening accounts be reviewed to reduce operational costs imposed on the beneficiaries, the government should attempt to facilitate the construction of health units to provide free health care. The government should consider starting vocational institute this will give a chance to people to obtain skills and higher training and lastly, the scheme should be revisited to ensure that the amount of credit extended to various beneficiaries insufficient in terms ensuring productivity and profitability. Areas for further research are to carry out similar studies in other districts were poverty is still persistent and study on the efficiency of the start up capital to poverty reduction.

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