Table of Contents
List of Abbreviations
List of Tables
List of Figures
Chapter 1 Introduction
Chapter 2 Background
People’s Democratic Republic of Algeria
Arab Republic of Egypt
Republic of Iraq
Hashemite Kingdom of Jordan
Kingdom of Morocco
Republic of Yemen
Chapter 3 Literature Review
Chapter 4 Methodology
4.2 Data Gathering Method
4.3 Database of Study
4.4 Validity of Data
4.5 Originality and Limitations
Chapter 5 Correlative Test Hypotheses
Chapter 6 Results
6.1 Qualitative Data Results
6.2 Quantitative Data Results
6.2.1 Hypotheses Results
6.3 Summary of Results
Chapter 7 Conclusion
Appendix I: Tables
Appendix II: Figures
Appendix III: Hypotheses Testing Data
I would like to dedicate the time and effort I have committed to this paper, and my academic journey, to my grandmother – without you, I would not have had the chance to get this far. Your passion in all things has been a guiding light when I needed it most. Thank you.
This paper observes the relationship between multiple variables in order to determine whether Financial Inclusion can be used as a tool for poverty reduction in the Middle East and North Africa. There are many reports that identify this to be function to something very likely as a tool around the world; however, there has been limited work regarding financial inclusion and the Middle East and North Africa. Through qualitative and quantitative research, this paper examines the possibility of this theory working in MENA. Wide income disparities, combined with government corruption, religious dispositions, and an overall lack of money are contributing barriers to the unbanked. These factors greatly limit the use of this tool until other issues are tackled and governments commit to more policies that will be conducive to growth; banks must be more open to lending; and people will have to become more financially literate.
The World Bank, Gallup, the IMF, and various authors, in addition to the World Bank FINDEX dataset are used to reference information conceded by well-respected authors in the financial-, development-, and in the government sector. Although there seems to be a great deal of promise with the concept of Financial Inclusion as a Tool for Poverty Reduction world wide, it seems to be very limited in MENA, in the poverty-stricken nations. Algeria, Egypt, Iraq, Jordan, Lebanon, Morocco, and Yemen are observed in the report. Generally, there are barriers preventing the implementation of inclusiveness, which will prevent the advancement of poverty alleviation. More government commitment is required.
I would like to express my deepest gratitude to Professor Trabold and Professor Mayer, who provided me with an opportunity to further my understanding in a field of research that is very special to me. Professor Trabold’s continuous aid, and persistent guidance and availability helped in the design and execution of this research. Professor’s Mayer’s ability to frequently challenge me contributed, as well, to the hard work put into this paper.
The FINDEX would not be available to me without the efforts from the World Bank, Gallup, and the Bill and Malinda Gates Foundation. The hard work, dedication to objectivity, and overall goal of extreme poverty eradication is a testament to the goodness that this world is capable of. Thanks to those organizations for allowing me to utilize the database.
Dr. Kamal Bhattacharya, Director of the IBM Research Centre in Kenya, gave me the initial idea to work on this subject, and provided me with direction prior to the commencement of this paper. His expertise and consideration is very well appreciated.
In addition to academia and industry, I would like to thank my Grandmother – her never-ending support throughout this two-year process, and especially in the past months, has been unimaginably important to me. I would like to extend my gratitude to her, and the rest of my family and friends – your patience and support have helped me focus on this research.
Finally, I would like to thank two individuals who have been genuine support centres for me – Ben Kuzmaski and Pavel Tikhonov. From day one, despite set backs, they were always there to bounce ideas off of. In our hardest days there was always a way to keep spirits up, and made this academic journey not only insightful, but also positively exciting. Ideas are incubated not by an individual, but by a community. For this reason, I would like to extend my gratitude to all those who have been a part of my life while making something positive of this initially abstract concept.
List of Abbreviations
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List of Tables
Table 1 - GDP Per Capita PPP information gathered from CIA World Fact Book
Table 2 - Questions and Definitions, FINDEX Survey 2011
Table 3 - Chart Analysis - Algeria (Data from World Fact Book 2011)
Table 4 - Chart Analysis - Egypt (Data from World Fact Book 2011)
Table 5 - Chart Analysis - Iraq (Data from World Fact Book 2011)
Table 6 - Chart Analysis - Jordan (Data from World Fact Book 2011)
Table 7 - Chart Analysis - Lebanon (Data from World Fact Book 2011)
Table 8 - Chart Analysis - Morocco (Data from World Fact Book 2011)
Table 9 - Chart Analysis - Yemen (Data from World Fact Book 2011)
Table 10 - Chart Analysis – All Analyzed Nations (Data from World Fact Book 2011)
Table 11 - Hypotheses Testing Legend, Within-Economy Income Levels, as per Global FINDEX (2011)
Table 12 - Hypothesis Test 1 Within-Economy Income Levels and Number of Accounts (Data from Global FINDEX)
Table 13 - Hypothesis Test 2 Within-Economy Income Levels and the use of Financial Institutions for borrowing (Data from Global FINDEX)
Table 14 - Hypothesis Test 3 National GDP per Capita PPP and rate of Account Ownership (Data from Global FINDEX and CIA World Fact Book)
Table 15 - Hypothesis Test 4 National Commercial Lending Rates and frequency of borrowing from a Financial Institution (Data from Global FINDEX and CIA World Fact Book)
Table 16 - Hypothesis Test 5 Respondents who do not have accounts due to religious reasons, who borrow from friends and family (Data from Global FINDEX)
Table 17 - Hypothesis Test 6 Correlation between Within-Economy Income Levels and Religion as a reason for non-participation (Data from Global FINDEX)
List of Figures
Figure 1 - Reasons for Non-Inclusiveness, FINDEX (Data gathered from the World Bank Findex)
Figure 2 - 2011 FINDEX Survey (Page 1 and 2)
Figure 3 - Global FINDEX Methodology
Figure 4 - Religiosity and In-Economy Income Levels, Algeria (Data from Global Findex, 2011)
Figure 5 - Religiosity and In-Economy Income Levels, Egypt, Islamic Republic (Data from Global Findex 2011)
Figure 6 - Religiosity and In-Economy Income Levels, Iraq (Data from Global Findex 2011)
Figure 7 - Religiosity and In-Economy Income Levels, Jordan (Data from Global Findex, 2011)
Figure 8 - Religiosity and In-Economy Income Levels, Lebanon (Data from Global Findex)
Figure 9 - Religiosity and In-Income Levels, Yemen, Republic of (Data from Global Findex, 2011)
Figure 10 - Mean Population with an Account, MENA
Figure 11 - Egypt, Yemen, and Adjusted Mean - Reasons for being unbanked by In-Economy Income
Figure 12 -GINI Indices, 2005 to 2014 (Data from World Bank, 2014)
Figure 13 – Borrowing Mediums, Yemen and Adjusted Mean of total Nations (Data from Global FINDEX)
Figure 14 - Central Bank Discount Rates beside Commercial Bank Lending Rates, MENA (Data Gathered from the CIA World Fact Book 2014)
Figure 15 - Regional Methods of Borrowing MENA (Data from Global FINDEX 2011)
Figure 16 - Hypothesis Test 1 Within-Economy Income to Account Ownership (Data gathered from CIA World Fact Book (2014) and Global FINDEX (2011))
Figure 17 - Hypothesis Test 2 Within-Economy Income Levels and Respondents Borrowing from Financial Institutions (Data from the Global FINDEX 2011)
Figure 18 - Hypothesis Test 3 National GDP per Capita to Account Ownership (Data from CIA World Fact Book 2014 and Global FINDEX 2011)
Figure 19 - Hypothesis Test 4, National Commercial Lending Rates and frequency of borrowing from a Financial Institution (Data from Global FINDEX and CIA World Fact Book)
Figure 20 - Hypothesis Test 5, Respondents who do not have accounts due to religious reasons, who borrow from friends and family (Data from Global FINDEX)
Figure 21- Hypothesis Test 6 Within-Economy Income Levels and Religion as a reason for Non-participation (Data from Global Findex 2011)
The level at which one is deprived of absolute basic needs. This is a non-contextual measure, versus relative poverty. As of recently, the absolute poverty line is between $1.25 and $2.50 PPP
The delivery of financial services at an affordable price to sections of society that are considered disadvantaged and low-income.
The ability to understand how money is earned, how it is used to invest, and how to manage money. In addition, it may be associated with how one donates it.
Formal Financial Institution
A formal financial institution is one that deals primarily with financial transactions, such as investments, deposits and lending. They can extend to insurance companies, trusts, and investment dealers ; however, for the purpose of this report, they will be a synonym for an institution that deals with investments, deposits, and lending.
A statistical measure that represents the distribution of a nation’s income. In this report, it will be used to represent the measure of inequality. A perfect distribution of income is 0.
Database that draws information from 150,000 people worldwide for missions involved with financial inclusion, poverty reduction, gender equality, and various other tasks. The main purpose of it is to index and understand trends in banking around the world.
Highest 10% Earners
The percentage of the gross domestic product (may also in purchasing power parity) that the wealthiest 10% of the population has – a measure that identifies the disparity in income between the top and bottom earners.
A banking system based on Islamic religion, or Shari’a, guided by Islamic economic principals. Two guiding principals of Islamic banking are: sharing of profit and loss, and being disallowed from collecting interest.
This measure is used to identify the total population’s ability to read at the age of 15 and above. There is no way to identify what the standard for each nation is for literacy.
Lowest 10% Earners
The percentage of the gross domestic product (may also be in purchasing power parity) that the poorest 10% of the population has – a measure that identifies the disparity in income between the top and bottom earners
Organizations that provide funding for low-income individuals, usually for MSMEs. These can be commercial banks, but are not always; therefore, they can also be Non-Government Organizations. For this reason, many microfinance institutions cannot accept deposits – they are not always formal banks.
Middle East and North Africa
The Middle East and North Africa is a region that traditionally includes: Algeria, Bahrain, Djibouti, Egypt, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Qatar, Syria, Tunisia, West Bank & Gaza, and Yemen.
A numeric representation of two sets of data, with an attempt to understand the correlation between the two sets. The scale is between -1 and 1
The percentage of the capable labour force that is unemployed4
A non-financial institution providing banking-like solutions to customers. Companies include telecom companies, and retailers
Chapter 1 Introduction
Financial Inclusion (FI), in general terms, is the practice of including individuals into the banking sector. The sector includes, but is not limited to, formal savings institutions, Micro-Financing Institutions (MFI), Credit Institutions, and the finance sector as a whole. Under some definitions, financial inclusion also includes the Agent Banking industry; however, for the purpose of this document, they will be excluded.
The World Bank and the United Nations (UN) have agreed that Financial Inclusion is a means of growth in prosperity within many nations as well as a means to reduce poverty worldwide. In essence, the UN has identified financial inclusion as a conduit for poverty reduction globally. The United Nations Commission on International Trade Law (UNCITRAL), identified that Financial Inclusion is an integral part of reaching individuals in absolute poverty, and helping alleviate that poverty (Kashyap, 2011). At this time, outside of a few regions, this comes as an incredible challenge. This paper aims to identify that Financial Inclusion is not yet a practical Tool for Poverty Reduction in the Middle East and North Africa.
Financial Inclusion is an integral part of economic development worldwide, as it directly enables individuals and nations to develop in various means. The most basic level of inclusion, in theory, allows individuals to save money for future events, including weddings, education and the like. Furthermore, savings can be held for emergencies, including medical bills and sudden events, such as disasters and other situations where mitigation is difficult or impossible.
On a deeper level, micro financing encourages individuals to start ventures or support current business expansions. Business creation helps to develop employment opportunities, which in turn help to alleviate government investments into welfare and human sustainability; instead, government bodies can further invest in infrastructure. In addition to government investments, a growth in labour-force education also encourages Foreign Direct Investment (FDI), where greater infrastructure and development opportunities come to the forefront of the decision (Noorbakhsh, Paloni, & Youssef, 2009).
According to the World Bank’s 2011 Global Financial Inclusion Index (FINDEX), 50% of the world’s population is exposed to the banking industry. This data, however, is not representative of the population outside of developed nations. In fact, according to the data recovered from the World Bank, only 18% of the population is currently formally banked in the Middle East and North Africa (MENA), which is significantly lower than nearly any other region in the world (World Bank, 2011).
An alarming component about MENA is the diversity and overall disparity in the region as a whole. According to the Central Intelligence Agency’s (CIA) World Fact Book, nations range in Gross Domestic Product (GDP) per capita, purchasing power parity (PPP), from a staggering $121,000 per person, to a mere $2,500 in Qatar and the Republic of Yemen respectively. According to the same data from the CIA, it is also a heavily religious region, practicing predominantly Shari’s law in some form or another. (Central Intelligence Agency, 2014)
MENA is quite unique compared to other parts of the world, as there is a vast difference in income across all 19 countries, and even the seven being observed in this report.. One of the principal differences between the western banking system and that commonly found in MENA is that Shari’a law disallows banks from charging interest. This naturally prevents individuals from depositing capital into a savings account to increase wealth.
In the Quran, 3:130, the text condemns Interest, or “riba”, as it is termed. The text states, “O, you who believe! Devour not riba, doubled and redoubled, and careful not of Allah; but fear that you may be successful.” According to Dr. Monzer Kahf, a research Economist at the Islamic Research and Training Institute of the Islamic Development Bank, as states in the Middle East were converting to Islam, revenues from various sources were declining due to the beliefs held. This identifies that there was a time prior to the banking regulation changes, revenues transpired. (Kahf, 2007).
A complementary concern involved with lending in nations where Shari’a is a significant course of law, is the lack of available currency. According to Kahf (2007), there is a heavy influence of available income from the public hand, given without interest. He acknowledged that Sunnah is a type of interest-free public borrowing, and sometimes was considered obligatory lending. This was essentially taking money from the rich and lending to the poor or less wealthy for various types of ventures. This is not possible with a lack of available public currency.
Two of the seven nations being observed – Republic of Yemen, and the Republic of Egypt – have over 80% respondents in each nation that cannot afford an account. The other 20% are of mixed responses, which assert that there are too few people to lend from the upper-echelon within the societies.
Moreover, the total number of respondents that stated lack of money as a reason for non-participation was over 75% in the region as a whole. As was stated, there is a lack of opportunity to open the accounts, as well as a insubstantial ability to borrow from interest-free sources, as there are too few sources for such lending. In addition to the shortage of interest-free lending available to individuals, there is also an issue of non-participation within a formal institution; thus, money is borrowed predominantly from friends and family.
In the 1960’s, India nationalized banks and aggressively attempted to gain greater financial inclusiveness across the nation. In that time, it was discovered that, although many rural areas were reached, people in poorer regions continued to disregard the system due to various reasons. Much like the issues in MENA, India is a country that is split into many different regions, all with differing languages, and some with differing religions, amongst other variables. This provided a crash course in the venture for financial inclusion for under-developed nations.
When the banks became nationalized, the Indian government quickly began to expand to rural areas in order to pull in citizens who had previously not entered the banking sector, assuming that distance was a key reason for non-participation. Expansion was a tall order for the banks, and resources were stretched very thin – motives were not entirely clear, including, but not limited to, the income goals and economic growth goals. In addition, a large expenditure in the employment of new administration for the banks, as well as the purchase of buildings, land and the like caused banks to effectively become fire pits for government funds. (Banerjee, Cole, & Duflo, 2008)
What this example expresses is the fact that it is not as simple as putting banks in places where people can reach them. Furthermore, it indicates that taking banks out of the hands of the private sector is not necessarily the method of growing participation for those in poverty. Banking and inclusiveness require a great deal of social and political plight to encourage the necessity for the banking of people, for the system to work effectively. For this reason, financial inclusion can only be considered a tool, and not means of poverty eradication in itself (Siddiqui, 2006).
Because financial inclusion would be considered a tool, rather than a full mechanism in the alleviation of poverty in the Middle East and North Africa, this paper aims to determine whether this tool can be used to help alleviate poverty; not on it’s own, but as a part of a system. These concepts will lead to the identification of the effectiveness of financial inclusion as a tool presently, based on both qualitative and quantitative data. Because this is as much as financial issue as much as a socio-economic matter, both qualitative and quantitative sources will be observed and used.
Chapter 2 Background
The Middle East and North Africa as a region has been an important point of discussion for the United Nations and various other organizations, as there is a vast potential for development in various contexts. The Middle East holds approximately 60% of the world’s oil and 45% of the world’s total gas reserves (United States Department of Energy, 2009). There is a great deal of opportunity for the region as a whole; however, from country-to-country there is such a vast disparity in wealth that it is difficult to group all nations as being in the same positive position.
Qatar, Saudi Arabia, and the United Arab Emirates have traditionally been “winners” in the region, with a high output of oil and an economic plan that removes the need for domestic oil. Conversely, Iraq and the Republic of Yemen, amongst others, have not traditionally been so prosperous. According to Gal Luft (2003), Iraq has 112 billion barrels (bbl) of proven reserves. There is even more that has yet to be discovered; however, due to political, social, and international issues, Iraq does not maintain a stable economy that can benefit from the natural resources (Luft, 2003).
According to the World Bank, Yemenis have, on average, an income of approximately $2,500 per year – the lowest in the Middle East and North Africa, despite a large reserve of oil (World bank, 2014). The observed reasons for this circumstance have been poor economic management, a declining oil reserve, corruption, and civil war. The USAID annual Corruption Assessment of Yemen states in the opening remarks that the Middle East nation contains all of the attributes of an environment that permits, as USAID eloquently calls it, “the misuse of entrusted authority for private gains” (USAID, 2006). In other words, individuals in power abuse the resources that are given to them.
As of 2005, Yemen’s GINI coefficient was 37.7. In comparison, Germany, in the same year, had a coefficient of 27. This means that there is a large disparity between the wealthy and the poor when compared to OECD nations. Unfortunately, it is difficult to assess the ranking beside other nations within the region, as there is not enough financial data by group. The closest comparison, in this scenario, is Egypt, which had a GINI coefficient in 2008 of 30.8 – significantly lower than Yemen.
The following sub-sections will identify the background of the seven nations observed within this report. Data from the World Bank, the CIA, USAID, International Monetary Fund (IMF) and various other sources will be utilized in order to paint a more comprehensive picture of the region. Of the 11 nations with Data available from the World Bank, seven were chosen, as they were below the median level of income, as per the GDP per capita PPP from the region as a whole, based on CIA figures (2014). The full table, Table 1, of GDP per Capita PPP is available in the Appendix
The median GDP per capita PPP of MENA as a whole – including all 19 countries - is $13,100. The nations identified within the framework outlined – only those at and below the median – include: Egypt, Morocco, Tunisia, Algeria, Iraq, Jordan, Lebanon, and Yemen. Because of data restriction from the World Bank data set, Tunisia will be omitted from this exercise.
People’s Democratic Republic of Algeria
Algeria was a former French colony, and became independent in 1962. It is an area that has suffered from large-scale unemployment (10.3%), and a general shortage in housing, according to the CIA World Fact Book (2014). It is a nation that is predominantly Muslim (99%). The area, in long form called People’s Democratic Republic of Algeria, has a median age of 27.5 years, and a very uneven distribution of household income.
The highest 10% (3,881,372) hold 26.8% of the wealth, while the lowest 10% have a mere 2.8%. This means that the lowest 10% of individuals in the nation have a household income of $2,053.81 per annum, or $171.15 per month, PPP. This also means that the wealthiest 10%, however, hold approximately $19,657.89 PPP. Although the income distribution information is not available for a GINI coefficient calcuation, this information brings forth a suitable sense of the way income is distributed within the nation.
Algeria has a very noteworthy commercial lending rate, which is the same as the Central Bank (CB) discount rate – both at 4%. This is still a relatively high rate by Western standards; however, in the Middle East, it is the lowest rate. These figures make sense of potential reasons why individuals may be using sources other than Financial Institutions to obtain capital. Algeria is one of only two nations that have commercial lending rates that are equal to CB discount rates.
The legal system in Algeria is mixed, combining French law and Islamic religious law, as expected by the predominantly Muslim nation. The age structure is heavily weighted for age groups between 0-14 and 25-54, with a literacy rate of 72.6% of the total population.
Arab Republic of Egypt
With a population of 86,895,099 (2014 figures), Egypt is certainly the largest country in the sample. It is a nation that has undergone a great deal of political change, and was a focus of the 2011 Arab Spring. It is a nation that is 90% Muslim, and as such, has a mixed legal system, similar to Algeria. As it was greatly influenced by the Napoleonic legal system, it is mixed with the Islamic religious law.
Disparity in Egypt is significantly lower than in Algeria; however, there is still a large gap between the rich and the poor in the nation. The lowest 10% of the population lives on approximately $2,538.23; whereas, the highest 10% of earners in the nation have an income of about $16,879.25, or over 600% higher than the lowest. The GINI coefficeint of 30.8 identifies a more evenly distributed income level than Canada in the same time frame (Information gathered from the CIA World Fact Book 2014).
In addition to the disparity in Egypt, the CB discount rate and commercial lending rates are very high. These percentages make it very difficult for individuals to borrow from financial institutions. In fact, Egypt has the second lowest lending rate from Financial Institutions of the seven countries being observed from MENA, where only 39 of the total observed loans were taken from a financial institution. The number of loans from friends and family, as with the rest of MENA, makes up the vast majority.
Republic of Iraq
Iraq has been plagued with a great deal of difficult changes including war, terrorism, extremism, and changing political and social atmosphere. It is not only smaller than most, but it has a generally younger population, where the median age is 21.3 years of age (Central Intelligence Agency, 2014). The literacy rate is fairly normal for the region, with 78.5% of the total population literate.
The disparity between the bottom 10% and the top 10% is quite broad. In fact, it is a wider variance than Egypt, where the poor have an average of $2,740.24 and the wealthy average $19,562.29. This does not seem like a large gap when observing the size of the numbers; however, that is a 614% difference between the two percentiles. This also means that, on average, the poor live with $7.50 per day. This may not constitute as “absolute poverty” by the $2.50/day definition; nonetheless, it does illustrate the difficulty faced when deciding between paying for housing and food, and deciding to invest into a savings account.
Iraq is, like most of the other MENA nations, predominantly Muslim - 97% - according to the CIA World Fact Book (2014). It is not surprising, then, that there is a trace of Islamic law in the legal system, in conjunction with a civil law system. It is also a nation that has similar lending and CB discount rates. Both the CB and Commercial Banks are 6%. The numbers in the World Bank Global FINDEX identify Iraq as the nation with the second highest financial institution borrow rate, with 96 respondents identifying that they have, in the past 12 months, borrowed from a formal financial institution.
Hashemite Kingdom of Jordan
Jordan, second smallest nation in the study with only 7,930,491 inhabitants, also has one of the highest unemployment rates. The nation does have the highest literacy rate. This could be due to the relatively young population, where the largest age group by population is between 0-14, which identifies a potential for future growth with respect to banking.
Disparity in the region exists, and it exists to a very great degree. In fact, the wealthy 10% of the nation averages 881% more than the poorest 10%, where the poorest 10% have a mere $1,644.83 per year ($4.51/day). The figures that are derived from the information gathered from the CIA World Fact Book (2014) identify that the Kingdom of Jordan’s wealthiest 10% have an average income of $14,483.01 per annum.
Jordan has a religious make up where Muslims represent 97.2% of the population, and like Iraq, the nation has a mixed Islamic and Civil law system. Regarding the Discount rate of the Central Bank, it seems as though Jordan’s CB has a very low rate, at only 0.3%, and a commercial lending rate of 8.9% - significantly higher than the CB rate (Central Intelligence Agency, 2014).
Unlike most of the countries in the region of study, the Lebanese Republic’s population of 5,882,562 is only 54% Muslim, and 40.5% Christian; thus, it has a wholly French Civil legal system. In addition, it has a fairly high literacy rate compared to MENA, at 89.6%. This means that the education system is potentially fairly advanced, and primary education is a very important factor in the country.
There is no information available regarding the distribution of income within Lebanon; however, the nation does have a fairly high unemployment rate – 16.8%. The CB discount rate is 3.5%, fairly comparable to the Western central banks. Commercial lending rates are fairly high, at 7.5%, which may deter individuals from borrowing from formal institutions.
This nation has a fairly aged population compared to the rest of the region – 29.3 years old. In addition, the largest age sector is 25-54, which is matched only by Egypt and Algeria, both of which have lower median ages than Lebanon (25 and 27.5 respectively). According to the World Fact Book (2014) the nation is considered quite progressive, relative to MENA. Because the British heavily governed it until the late 1940’s, it has a fairly westernized culture (Central Intelligence Agency, 2014).
Kingdom of Morocco
Of all the nations being examined, it appears that, according to data collected from the CIA, Morocco has the greatest disparity. The highest 10% income earners average $18,116.11 PPP, while the lowest 10% earn $1,473.30 PPP (Central Intelligence Agency, 2014), which amounts to a 1230% difference, a particularly alarming figure. The nation of 32,987,206 is 99% Muslim, which makes it no surprise that the legal body is Islamic law, mixed with French civil law.
Like Lebanon and Jordan, the median age in Morocco is 28.1 years, with an unemployment rate of 18.6% of the total labour force. In addition to the high unemployment rate, the literacy rate is quite low, where 67.1% of individuals over the age of 15 are considered literate. These numbers identify an aged population that are under-employed and under-educated.
The Central Bank discount rate in morocco is 6.5%, surprisingly higher than the lending rate from Commercial Banks, which is 6.3%. These rates, combined with the other factors, may highly deter individuals from utilizing the banking system by any capacity.
Republic of Yemen
Of the countries in MENA being explored, the Republic of Yemen is by far the poorest, both in the highest and lowest quintiles of income. The nation of 26,052,966 has a GDP of $61.63 Billion PPP, which means a GDP per capita of $2,365.57 PPP (Central Intelligence Agency, 2014). This is a staggeringly low number, and it becomes more so when observing the highest and lowest 10% income level averages. On the high end, the 10% earns, on average, $7,285.94 PPP, based on data from the CIA World Fact Book (2014); whereas, the bottom 10% average a mere $686.01 per year. That is less than $2.50 per day – averaged out; some people will make more, many will make less.
In addition to very low incomes, the Republic of Yemen also see a very high commercial lending rate. At 22%, it is far too high for many individuals to take part. It makes very little sense for individuals to participate in the financial institutions. For this reason, there is a greater borrow rate directly from stores (in-store credit and such) as well as from friends and family.
The nation is 99.1% Muslim, and as most others, utilizes a mixed system; however, the Islamic religious law is dampened considerably by a mix of English and Napoleonic Civil law. This means that restrictions are not the same as in other Middle Eastern/North African nations. The literacy rate is the lowest in the region, with only 65.3% of the total population. An identifier for gender inequality in Yemen is that the female rate of literacy, which is remarkably low – only 48.4% of females are considered literate. In addition to the low literacy rate, unemployment is the highest in the region – 35%.
Chapter 3 Literature Review
There is a great deal of research done by the World Bank and the United Nations regarding the use of financial inclusion as a tool for poverty reduction; however, it has become a deeper topic of discussion since the drawing of the Millennium Development Goals (MDG) in 2000 (The United Nations, 2014). The 8 goals included: Eradicate Extreme Poverty and Hunger; Achieve Universal Primary Education; Promote Gender Equality; Reduce Child Mortality; Improve Maternal Health; Combat HIV/AIDS, Malaria and Other Diseases; Ensure Environmental Stability; and, Develop a Global Partnership for Development. (Mohieldin M. , 2013)
A great deal of work has been done in order to identify where financial inclusion can be utilized as a tool in effectively promoting the MDGs; however, as a tool, it can only be utilized as effectively as the end-user can handle it. FI encourages the creation of business; the employment of community members, and an opportunity to grow already established firms. This can alleviate poverty, encourage growth in gender equality, and promote primary education for a greater number of individuals (Mohieldin M. , 2013).
According to Chuhan-Pole (2013), the Millennium Development Goals put the fight against poverty at the forefront of the entire initiative. On a global scale, the reduction of poverty has been phenomenal. Taking China as an example, the poverty rate, over a twenty-year period, dropped from 60% to only 12% (Chuhan-Pole, 2013). This is not only encouraging for the individuals involved directly with the MDGs, but it is equally promising for those in the nations well below the poverty level, looking to utilize financial inclusion as a means for poverty alleviation.
An important note to make, as explained by Marx and Van Den Bosch (How Poverty Differs from Inequality), there is a large difference between inequality and poverty, where they are not necessarily dependant on one-another. An entire nation could be in poverty, and there may be no inequality; whereas, a nation can be entirely out of poverty, and there exists a large inequality, or disparity (Marx & Van Den Bosch). Because of this, identifying top and bottom earners in the given nations is extremely important, as it will illustrate the true poverty and income gaps, which is done using the CIA world Fact Book
According to extensive research done by Demirguc-Kunt and Klapper (2012), much of the world’s poor do not have access to the appropriate financing requirements to fund education or entrepreneurial ventures, and small business owners must reply on their limited earnings to grow, rather than use credit. In their Policy Working Paper, Demirguc-Kunt and Klapper identify that prior to the research done by the World Bank, there was not much data to identify specific correlations and areas of interest for improvement. (Demirguc-Kunt & Klapper, Measuring Financial Inclusion, 2012)
The Bill and Malinda Gates Foundation funded the World Bank’s research into the topic as part of a large-scale developmental initiative. The research reached out to 148 nations, each providing a sample of at least 1000 respondents. The G20 has regarded the advancement of Financial Inclusion research as an area of greater interest than had previously been defined, and this continues to identify the importance of financial inclusion in both Social and Economic development of nations (Pearce, Financial Inclusion in the Middle East and North Africa Analysis and Roadmap Recommendations, 2011). According to the Global Financial Development Report, compiled by the International Bank for Reconstruction and Development and The World Bank, the growing concern for the Financial Inclusion rates around the world are an indicator of the recognition of the necessity for the under-banked to access financial services (International Bank for Reconstruction and Development/World Bank, 2014).
The demographics of individuals on average who do not utilize bank accounts, according to the Global Financial Development Report (2014), are young, unemployed, poor, less well-educated, or out of the workforce. A final reason, which affects much of the world, is that banks do not always reach the rural areas of the world. Although this is discussed in detail in the text, there is potential that this is not necessarily the case in MENA, as was seen in the case of India in the 1960’s (Siddiqui, 2006). There are very few respondents from MENA that identified proximity to be a determinant factor regarding non-participation.
According to the 2008 publication by the World Bank, “Finance for All?”, there are two main categories of non-participants in the banking sector: Voluntary and Involuntary. Voluntary includes no need for an account, and cultural/religious reasons. Involuntary exclusion is defined as insufficient income, discrimination, contractual framework, and price (Demirguc-Kunt, Beck, & Honohan, 2008). By the same authors, there is research supporting that, beyond the voluntary and involuntary reasons for exclusion, there are also potential indicators of higher participation based on the depth of the financial sector, identified by the percentage of the GDP that is contributed by the financial sector (Beck, Demirguc-Kunt, & Peria, 2005).
There is a great deal of literature regarding Shari’a-compliant financial products and instruments, as the World Bank and the International Finance Corporation have identified that 700 million of the world’s poor live in predominantly Muslim nations. According to Mohieldin, the growing interest in the Islamic banking world is certainly helping to raise the number of products and services available, but they are not yet able to function the way that reduces poverty on a large scale (Mohieldin, Iqbal, Rostom, & Fu, 2011). According to Pearce (2011), there is still a gap between financial products available, and those available to the average individual, stating that, although there is depth, financial products are not very far-reaching in MENA
Information discovered by Mohieldin et al (2011) was written prior to the Consultative Group to Assist the Poor (CGAP) releasing the 2012 follow-up report to their 2007 report regarding Islamic microfinance institutions, citing a growth in scale from 130 MFIs in 2007 to 256 in the whole region only 5 years later. Many of these MFIs have been opened in the high-developed Middle East economies, such as Saudi Arabia, UAE, and Qatar; however, not in many of the smaller economies, where financial gains for banks are smaller – there may be promise of growth in the future (Al-Zoghbi & Tarazi, 2013).
The Global Financial Development Report (2014) identifies, as well, the developmental differences between regions such as Sub-Saharan Africa (SSA) to that of MENA, as the number of MFIs to banking institutions varies greatly. In SSA, there are approximately 480 MFIs per 1000 commercial bank outlets; whereas, in MENA, there are a mere 44 MFIs to every 1000 commercial bank outlets (CGAP, 2011). A positive lending normality is occurring in many countries, as there are a number of Cooperatives emerging in MENA, which indicates a growing capital lending potential (Pearce, Financial Inclusion in the Middle East and North Africa Analysis and Roadmap Recommendations, 2011).
Pearce (2011) recognized the need for financial inclusion in MENA in order to secure a safe haven for families to store their earnings, mitigate financial risks, and secure remittance, amongst other important functions, including pension savings, health care and education expenses. The problem at hand, according to Pearce, however, is that there has not yet been a high-level commitment to improve financial inclusiveness across much of the region. Pearce identifies a roadmap that should be taken as a set of checks within the region, which take advantage of opportunities, and prioritize for significantly altering the total financial spectrum of the region (Pearce, Financial Inclusion in the Middle East and North Africa Analysis and Roadmap Recommendations, 2011).
Pearce employs data from the 2010 Financial Access report, compiled by the World Bank, stating a Non-Government Organization (NGO) -led microcredit sector, as well as postal networks dominate MENA heavily. It is material that corroborates the information previously discussed from the CGAP.
Financial Inclusion is an important and highly relevant area of study for the future of the MDGs, and the advancing of multiple aspects of the Post-2015 Goals. There are certainly areas of interest that will come to light, and at this time there does not seem to be a large enough emphasis on the Islamic Banking sector (UNICEF, 2011). There are researchers who are diligently applying time to Financial Inclusion as a concept for the global community, where religion is not a factor in the decision-making criteria for individuals. There are academics that are researching the importance of Islamic Banking to the Organisation of Islamic Cooperation (OIC), but this has not seemed to be a major concern to others.
The research at hand aims to identify how Financial Inclusion may work under certain circumstance. The Global Financial Development Report ascertains that market-based financing, different than those services provided by banks, evolve as the formal traditional banking sector evolves. The formal sector may, in fact, be a step after the informal lending practices that take place in MENA through cooperatives, MFIs, and the like (Schneider, 2002).
According to the data obtained from the World Bank FINDEX, two of the seven selected nations, the Republic of Yemen and the Arab Republic of Egypt, both fall into unique categories, where most of the respondents state that they do not have the money to invest into a bank account (World Bank, 2011). Account penetration in Lebanon is considered quite high compared to the other seven nations, but this does not denote that the numbers are reasonable – there are factors brought forward by the CIA World Fact Book that may provide better understanding of the situation in the region. These factors include religion, population, education rates, and the like.
The paper Financial Development in 205 Economies by Cihak, Demirguc-Kunt, Feyen, and Levine (2013) identifies that the Middle East and North Africa is regionally unique, as it is a territory that scored remarkably low in the access to finance. According to the same text, countries with low incomes tend to show lower degrees of financial development. The paper illustrates that as a financial system is used more frequently, it brings the overall cost of transactions down, which works well for both the customer and the bank, as it draws more individuals into the banking sector, who otherwise would not take part. In addition, it allows for individuals to create a more transparent credit history for lenders. (Cihak, Demirguc-Kunt, Feyen, & Levine, 2013)
Although there is not a great depth of data available through the World Bank in regards to GINI coefficients for the seven select nations involved with this research, gaps can be filled through the CIA World Fact Book, as well as data available in the responses in the World Bank Global Findex. The World Bank is able to provide five of the seven nations’ GINI coefficients. The understanding of the distribution of income in the nations is integral to fully appreciate the reason people decide not to bank, as well as a banking “income”.
Characteristics, such as the gender and age of individuals are a valuable area of interest in determining greater participation feasibility. In addition to personal income, it was identified by the Global Financial Development Report (2014), there are reasons for non-participation beyond solely a lack income. Correlative testing will be completed in order to fully understand the relationship between the sets of data available from the World Bank and the CIA World Fact Book, including income groups, religiosity, reasons for non-participation and methods of borrowing.
The book Making Finance Work for Africa, by the World Bank (2007) contributes a great deal of insight into various barriers of entry into the financial sector for people in each of the countries in MENA, using figures from the IMF’s Financial Access reports (Honohan, 2007). A notable point by Honohan (2007) is that at the time of the publication of the book , there was a fairly close relationship between respondents’ reasons for non-participation due to cost and the access to finance. According to the research, there is a moderate obstacle for both.
Much of the literature has seemed to point towards a correlation between religion and the number of participants. In addition, there has been a very strong argument that the poor are most affected by non-participation, both voluntarily and involuntarily. Not all countries are in a position of absolute poverty; therefore, there may be opportunities in the future to increase the banked demographic. There are many barriers to participation, including lack of money, religion, financial illiteracy, and gender inequality – all of which must be recognized by stakeholders prior to moving forward with initiatives to attempt an increase of financial inclusion.
Chapter 4 Methodology
The following section will address the research and data collection methods, as well as the means in which the information is analyzed. It has been split into six subsections: Approach subsection, Data Gathering Method, Database of Study, Validity of Data, Originality and Limitations, and Summary. The Approach will discuss how the topic was observed. Additionally, it will discuss the method of quantitative research, and the reasons behind the decision for the chosen method.
The Data Gathering Method subsection will discuss the means in which the relevant information was collected from various sources. This subsection will detail where and why information was collected from various primary and secondary sources. The Database of Study subsection will detail the database that was used for analyzing the relevant information within the research paper - the FINDEX.
The Validity of Data subsection will examine the reliability of the information gathered, not only within the dataset, but also within the secondary data that have been recovered for analysis. Originality and Limitations identifies other studies that have been done in prior to this thesis, the outcomes, and the shortcomings.
The research method employed in this paper is a mixed method; that is, it combines both a qualitative and quantitative approach to data examination and analysis. This approach has been chosen due to the subjective nature of this topic. Indeed, an observation of the number of participants in the financial system is very important, and will be analyzed. There is, however, still a great deal of weight put upon expert opinions on the socio-economic situation in the region.
MENA is very heavily influenced by religion, according to many sources, and it affects many parts of the different cultures. Paradoxically, this region of the world has a high rate of corruption in the public sector. Understanding whether or not Financial Inclusion is a tool for poverty reduction in the region depends heavily on the culture, and the reasons individuals participate, or not, in the system.
The initial research stage is to understand, at a deeper level, financial inclusion. After this stage, a great deal of effort will be contributed to dissecting the World Bank Findex Data, and understand the results of the survey. The survey has many variables that will paint a picture of the region, the wealth (or lack thereof), religiosity, saving habits, and borrowing habits, amongst other dynamics. The data has fifty variables, including, but not limited to, the age of the respondents, the gender, the within-economy income class, respondent formal bank account activity, and reasons for non-participation.
The Pearson’s Correlation Coefficient will be the method of hypothesis testing in conjunction with scatter plots of the same data, in addition to other graphical analysis. The six hypotheses to be tested by the data correspond directly by the secondary data gathered. It is commonly accepted by nearly all of the secondary sources that there is a correlation between financial inclusion and decreased poverty levels. These tests are to identify if that is the case in the Middle East and North Africa. Chapter 5 covers the hypotheses in more detail.
In addition to the Datasets, a rigorously selected set of secondary sources was compiled that include experts from the World Bank, CGAP, recognized Universities, United Nations Columnists, and Islamic Economists who both support Islamic Banking, as well as those that see a need for reform in the Islamic banking system. These authors, including Asli Demirguc-Kunt, are very well respected researchers who have worked on Financial Inclusion as a topic for a long period.
The CIA World Fact Book will be considered in order to fill data gaps in the World Bank documents, and to corroborate figures found in the World Bank. CGAP, the International Finance Corporation (IFC) – a World Bank Group – and other prominent organizations that will be utilized as significant sources for information regarding Financial Inclusion as a tool for Poverty Reduction. There are some areas of research where there is not a definite link between financial inclusion, MENA, and the prospect of it as a tool for poverty alleviation as a whole; however, binding these together is done, in part, through the research and knowledge of the Islamic Development Bank, with assistance from World Bank writers.
The Islamic Development Bank will be looked upon in order to develop an accurate regional perspective of the situation, and it’s opportunities and threats in regards to finance. This assessment method will give an overall perspective on the probability of Financial Inclusion being used as a tool for poverty reduction in the region. Furthermore, the Islamic Development Bank represents the thoughts of experts in the region.
A financial indicator put together by the International Monetary Fund (IMF), called the Financial Access Report identifies respondents that report accessibility per 1,000 people in a given nation; however, because the report includes agent-banking as well as formal banking, it serves a purpose different than that of the Global Findex, which aims to indicate reasons for banking non-participation. Indeed, the Financial Access report represents the financial sector landscape; however, it seems to fall short of information that is integral to decision-making for policy makers. For this reason, the Financial Access report will not be observed as a key representing set of research; rather, as a supporting method of measuring general growth in the sector over a period of time.
The quantitative section will use the variables within the FINDEX survey and attempt to understand the correlation between responses that are given, the trend in the answers, and the direction that overall inclusiveness seems to be headed. Based on preliminary research, it is expected that religion will play a strong role in the decision to enter the banking sector. In addition, there is a great deal of poverty in the area, and based on previous readings, a lack of money may become a significant factor in the decision to introduce formal banking as a stronger asset in the reduction of poverty.
4.2 Data Gathering Method
At the beginning of the search for an appropriate method of gathering data, some researchers were contacted in order to make sure that the data that was observed was the most appropriate and accurate to the goal of the research herein. Dr. Kamal Bhattacharya, of IBM Research Kenya identified the necessity to conduct deeper research into the potential for Financial Inclusion to be a method of development. Dr. Bhattacharya acknowledged that there were many by-products to a greater depth of research, such as methods of gaining ground in Africa as a whole.
The databases from the World Bank’s FINDEX were downloaded from the World Bank FINDEX Website for use with the Stata program. Each country was an individual file; seven were downloaded in total – Algeria; Egypt, Arab Republic of; Iraq; Jordan; Lebanon; Morocco; and, Yemen, Republic of. These files were then transferred to Excel for compatibility purposes.
The database was initially split into multiple charts, which cross-reference all of the key information in order to identify potential trends in data. All of the graphics and charts are available in the Appendices. When all information was split, it was isolated, and consolidated with similar data from the other nations. Various spreadsheet study methods were used.
The qualitative data was collected from the World Bank, IMF, and the various other reputable organizations through the respective online library catalogues. Textbooks were not utilized to a great extent in the research, as there was a potential for bias by author. Therefore, working research papers were the most commonly sought after documents, as well as published papers about the current and past banking practices in the nation.
Working research papers are ideal, as the individuals writing are directly connected to the organizations that is being written for. This means there is much more accountability in the writing and research. In addition, there is a greater depth to the information authors can gather. Amongst many other positive factors involved with working research papers, it is accepted that the information therein is to be analyzed and built upon internally and externally.
4.3 Database of Study
The Database of Study is the World Bank Global Financial Inclusion Index. It was chosen as it is not only thorough, but also has data that identifies income levels, reasons for non-participation, methods of borrowing, reasons for borrowing, and the like. Each of the seven nations had a minimum of 1000 respondents, and fifty variables. The survey is labelled as Figure 2 in the appendix, for reference. The fifty variables within the survey data included in the database can be viewed on Table 2.
Table 2 expresses the vastness of the dataset from the World Bank Findex database. Through filtering the variables, an enormous array of trending can be accomplished. Regression trending data over a period of time is not entirely possible from this dataset. In order to compensate for the shortcoming, qualitative research will be used to compensate for the gaps. The dataset is considered quite comprehensive, and ideal for correlative testing, which will be used in this case.
4.4 Validity of Data
The World Bank is technically a part of the United Nations; however, there are separate governing bodies for each institution. By having separate governing bodies, it allows for a greater depth of accountability; however, it does potentially reduce standardized methods for verification, information reporting, and the like. There is no reason, however, to believe that there are differences in reporting methods. When observing the methodology utilized in the gathering of information for the World Bank’s FINDEX, there were well over 150,000 participants in 148 nations around the globe.
These 150,000 respondents represent approximately 97% of the global population (World Bank, 2011). The study in itself was carried out by Gallup throughout the 2011 calendar year, and was funded in large part by the Bill and Malinda Gates Foundation. In email correspondence with a co-author of multiple World Bank reports, a question arose regarding the validity of the FINDEX, as it was partially funded by a charitable organization. In response, Klapper stated, “…I do not perceive any conflict with receiving money from the Bill & Melinda Gates Foundation, which is an independent charitable trust.”
Klapper also identified the problems with using the Gallup World Poll as a source in itself, as it may cause a discrepancy in the data that is being used. This is because the poll looks at the household incomes, and does not contain consumption details. When comparing the FINDEX to the Financial Access report, there was a discrepancy between the definitions of “banked” individuals in each of the research data. For these reasons, as stated previously, the primary data being observed in this report is from the FINDEX.
 (Ravallion, Chen, & Sangraula, Dollar a Day Revisited, 2008)
 (OECD, 2012)
 (Investopedia, 2014)
 (World Bank, 2011)
 (Investopedia, 2014)
 (Central Intelligence Agency, 2014)
 (The World Bank, 2014)
 (Infosys, 2012)
 Because there are not enough segments of income for many of these countries, a Lorenz curve cannot be completed. Only the top and bottom 10% is given.
 According to the to the CIA World Fact Book (2014), Canada’s GINI index was 32.1 in 2005
 In the past 12 months
 Calculated as GDP PPP/Population. CIA rounded up.
 Discrimination based on documentation, income levels, ethnicity, education, and the like
 Too Far Away; Too Expensive; A Lack of Documents; A Lack of Trust; A Lack of Money; Religious Reasons; and, Family Already Has An Account.
 All countries have 1000 respondents except for Egypt, which has 1044 respondents in the survey, and Morocco, which has 1001