Poverty Elimination Through Potential Zakat Collection in the OIC-member Countries: Revisited.
Shirazi, Nasim Shah ; Amin, Fouad Bin
This paper is the extended and updated version of Shirazi (2006),
which covers 38 OIC-member countries. The paper estimates the resource
required and potential zakat collection for poverty elimination. The
paper employed the poverty gap index based on US $ 1.25 a day and US$
2.0 a day estimated by the World Bank (2009). Zakat potential has been
estimated by employing Kahf (1989) method of estimation with some
modifications. The paper finds that half of the sample countries not
only meet their resource shortfall by potential zakat collection but
also generate surplus funds which are sufficient for the resource
deficit countries. The paper suggests pooling of zakat funds from the
zakat surplus countries and providing for the resource deficit countries
to eliminate the poverty.
Keywords: Poverty Alleviation, Resource Shortfall, Zakat
Collection. OIC-Member Countries
1. INTRODUCTION
The World Bank has been reporting poverty estimates for a number of
years which are helpful in assessing the progress towards poverty
alleviation across the countries. The World Bank (2009) estimates show
that poverty level has been decreasing over last two and half decades.
The number of absolute poor (in terms of $1.25 a day) has decreased from
about 1.9 billion in 1981 to about 1.8 billion in 1990, and it further
dropped to about 1.4 billion in 2005. The share of people living on less
than $ 1.25 a day decreased by 10 percentage points from 52.2 to 42.0
percent during 1981 to 1990 and ir further went down by about 17
percentage point (from 42.0 percent to 25.3 percent) during 1990 and
2005. Similarly, we can find variations on the poverty alleviation front
across the regions. East Asia and pacific, Middle East and North Africa
witnessed a decline in poverty both in terms of number of absolute poor
and the share of people in poverty during 1981 to 2005. Although the
share of South Asia's poor people in Global poverty declined from
59.4 percent to 40.3 percent during 1981 to 2005, yet absolute number of
poor people increased from 548 million to 596 million during the same
period. SubSahara Africa witnessed a slight decreased (53.4 percent to
50.9 percent) in its share of poor people, while the number of poor
people increased from 211 million to 388 million during 1981 to 2005.
This shows that poverty has been the serious problem and a great
challenge for Developing Countries. In Europe and central Asia, both the
number of poor people and the share of people in poverty increased
during the same period. [See World Bank (2009), Table 2.8]. The World
Bank believe that about 46 million more people will come under the
income level of $1.25 a day due to the recent global economic meltdown
and the slow economic growth rates.
Different policies and strategies, both at the micro and macro
level including safety-nets programmes, have been adopted in different
countries in the past to reduce the poverty, but the fact remains that
poverty still persists especially in developing countries. The Muslim
countries have a very strong institution--Zakat and Sadaqat--which has
never been practiced in its true spirit. We firmly believe that if this
institution is revived and fully implemented then absolute poverty can
be eliminated from these countries.
This paper is written in the said spirit. The paper attempts to
estimate resource shortfall and potential Zakat collection for poverty
elimination in 38 OIC-member countries. (1) The rest of the paper is
organised as follows. Section 2 gives a brief summary of the literature
review and Section 3 discusses the data and methodology employed for the
estimation of results. Section 4 highlights the poverty incidence in the
OIC member countries from which data are available, Section 5 provides
the estimates of resource required for poverty elimination, the
estimates of potential Zakat collection and compares both the resource
required and resource needed that can be made available through
potential Zakat collection. Section 6 sets forth the summary and
conclusion.
2. LITERATURE REVIEW
An extensive review of literature has been covered by [Shirazi
(2004, 2006)]. However, this section focuses on a few studies only,
which discuss the subject matter of the paper. Ahmed (2004) estimates
the potential of Zakat collection and resource required for poverty
alleviation for a sample of 24 IDB member countries by using a $1/day
(group1) and $2/day (group 2) international poverty lines. To determine
the amount needed per annum for poverty alleviation, the author
multiplied the number of poor of each country under his study by 365 and
converted the amount into percentage of GDP of the respective country.
Similarly he estimated the resource required under $2.00 a day. He found
that, at one extreme, Tunisia required only 0.3 percent (for group 1)
and 1.4 percent (for group 2) of its GDP for the alleviation of extreme
poverty while at other extreme, Nigeria required huge amount that is
107.7 percent (for group1) and 149.6 percent (for group 2) of GDP
respectively for poverty alleviation. The author employed Kahf (1989)
estimates to measure the potential of Zakat in the respective countries.
Author compares the percentages of GDP required under $1 and $2 for
poverty alleviation with potential Zakat collection under three
different opinions for Zakatable items. With the Zakat rate of 1.8
percent, only eight countries namely Tunisia, Turkey, Kazakhstan,
Jordan, Algeria, Morocco, Egypt and Azerbaijan are capable of lifting
the poor from poverty line in a year (group 1), but other 16 countries
are failing to do so. At 4.3 percent Zakat rate half of the sample
countries are able to move their hard core poor people (Group 1) out of
poverty [for further detail see Ahmad (2004)].
In our view, study has two shortcomings. Firstly, study multiplies
the total number of poor of the respective country by 365 to estimates
total funds needed per annum for poverty alleviation. Thus the study
assumes that every poor has zero income. This may not be true. Some may
be having zero income while other more than zero but less than $1 a day.
Therefore, precise estimates for obtaining absolute resource required
can be obtained by using the poverty gap index. Secondly, the author has
not adjusted the Muslim and non-Muslim population for the estimation of
potential Zakat.
Yaumidin (2009) estimates the resource needed for poverty
alleviation and potential Zakat collection for Malaysia and Indonesia.
She concludes that Malaysia performs better than Indonesia. She
replicates the methodology employed by Ahmad (2004) which suffers the
same shortcoming as discussed above.
Although macroeconomic policies play pivotal role in alleviating
poverty, yet it cannot be eliminated without the use of Zakat in an
effective way [Ahmad (2008)]. Ahmad is of the view that Zakat can make
an impact on poverty ir (i) it is complemented by robust macroeconomic
policies that increase growth and redistribute income, and (ii) when
larger portion of Zakat is used for productive purposes.
Hassan and Khan (2007) find that Zakat fund can largely facilitate
the government budgetary expenditure and support the poor through
transfer of payment in Bangladesh. By allocating funds into eight groups
of Zakat recipient, it is possible to increase the income and employment
with the improvement of safety net programmes. Zakat funds can increase
the tax potential of the government through the improvement of
productivity, employment and output. They conclude that Zakat funds can
replace the government budgetary expenditures ranging flora 21 percent
of ADP (annual development me) in 1983-84 to 43 percent of ADP in
2004-2005. These funds can be used for other developmental and social
expenditures. They suggested that Zakat should be included, for
Bangladesh and rest of the Muslim countries, as a poverty alleviation
instrument in their PRSP.
Sadeq (1996) finds that RM 293 million (which is about 73 percent
of estimated potential Zakat collection) will be needed annually to
change the status of hard-core households to a status of non-poor
households in Malaysia. The test of the amount (23 percent), as the
study suggests, could be used for uplifting their economic condition.
While discussing the distributive effect of Zakat, Awad (1989)
estimates that in Sudan about 3 to 4 percent of GNP is collected as
Zakat revenue which implies that one third of GNP can be redistributed
form the rich to the poor in a decade. However, some studies find that
the proceeds of Zakat will not exceed 1 to 2 percent of GNP, when all
the existing Fiche rules are followed, especially in Sudan and Saudi
Arabia [Khan (1989) and Salama (1990)].
The studies made, so far, are either limited in scope or lack the
proper methodology for estimation of the resource needed and potential
Zakat collection. Therefore the present study is devoted for the
purpose.
3. METHODOLOGY AND DATA SET
As we have noted earlier that this paper is the updated and
extended version of Shirazi (2004, 2006), so we have followed the same
estimation method for the current paper. However, we have corrected the
error which we made in our earlier paper, which resulted under
estimation of the resource required for poverty elimination.
3.1. Estimation of Resource Shortfall
The resource gap has been estimated by using the poverty gap index,
which is defined as the mean shortfall below the poverty line, expressed
as a percentage of the poverty line. The World Bank has used the recent
updated poverty lines of US $1.25 a day in 2005 PPP terms for hard core
poor and US $2.0 a day for the poor respectively which represents the
mean of poverty lines found in the poorest countries ranked by per
capita consumption. (2) This reflects the depth of poverty as well as
its incidence. The poverty gap index does not provide the total income
(consumption) shortfall explicitly. For this purpose we will use the
estimated poverty gap based on international poverty line, and convert
it into absolute figures for each country under study.
[P.sub.1] = 1/N [[summation].sup.q.sub.i=1] (z-[Y.sup.i]/z), Where,
N is total population, Z is poverty line and Yi is
the income (consumption) of the ith household. The poverty gap
index has been rearranged to get the absolute resource shortfall of the
country concerned.
[[summation].sup.q.sub.i=1] (Z - Yi) = [P.sub.1]NZ
Similarly average resource shortfall under $2 a day is calculated.
This will give us, on average, the total amount required for poverty
elimination for each country under study.
3.2. Estimation of Potential Zakat Collection
Different studies have been made for the estimation of potential
Zakat collection in the past. All such studies have used different
methodology and employed diverse opinions of scholars regarding the
coverage of Zakat and consequently their results are not comparable [see
Salama (1982); Chowdhry (1991); Kahf (1989, 1999); Hussain and Shirazi
(1994); al-Tahir (1997)]. (3) Since there is no agreement among the
scholars on the new wealth that may be brought under Zakat net, hence
there is urgent need for the general agreement on the definition of the
items, which may be taken as Zakatable items. This requires Ijmah of the
ullama and other contemporary scholars on the issue.
Kahf (1989) estimated Zakat potential for eight Muslim countries by
using National Income Accounts. His estimates of potential Zakat were
based on three different opinions of jurists regarding Zakatable items.
Those three definitions were named as Z1, Z2 and Z3. Z1 was estimated in
accordance with the majority traditional view according to which Zakat
was levied on agriculture, livestock, stock in trade, gold, silver and
money. Z2 was based in accordance with the views of contemporary Muslim
scholars where Zakat can be deducted from net returns of manufacturing
concerns and building rents and from net savings out of salaries. Z3 was
based on Malikite views, where Zakat base includes buildings and other
fixed assets except those assigned for personal and family use.
According to these definitions, under Z1, Zakat can be collected in the
range of 1.0 percent to 2.0 percent, under Z2 from 3.1 percent to 4.9
percent and under Z3 from 3.2 percent to 7.5 percent of the GDP for the
eight Muslim countries (for detail see Table 1).
The different potential Zakat collection is due to different
economic structure of the countries. Kahf's (1989) estimates
covered eight Muslim countries having different economic structure,
therefore, we have opted his definitions for potential Zakat estimation
with some changes.
It may be noted that Zakat is collected from the rich Muslims only
and nonMuslims (4) citizens are exempt from the payment of Zakat.
Kahf's study for the abovementioned eight countries, perhaps, did
not take into account this factor while estimating Zakat potential under
different definitions of Zakatable items. Consequently, we have adjusted
GDP of each Muslim country by taking into account the proportion of
Muslim Population in each of the Muslim country. We have used the per
capita concept of GDP for the adjustment of GDP. For example, GDP of
Bangladesh was US$ 163,728 million (at PPP) in 2005, and the Muslim
population was 88 percent, therefore, adjusted GDP for the purpose of
Zakat estimation will be [(163,728)*(0.88)] US$ 14408 1 million.
Similarly, we have adjusted the GDP of all other countries with respect
to their proportion of Muslim population. After adjusting GDP, we have
used the Kahf's definition of potential Zakat collection for Egypt,
Pakistan and Turkey as reported in the above Table 1. On the other hand,
for the rest of the Islamic countries, where such estimates are not
available, we have taken the average of Zs of the above eight countries
(see Table 1) and used this average to estimate the potential Zakat
collection.
3.3. Data Sets
We have used Poverty gap index under US $ 1.25 a day and US $ 2.0 a
day as reported in World Bank (2009). Total Number of Population is
taken from World Development Indicators (2007), while GDP (at PPP) from
2005-2007 are taken from the CIA World Fact books (5) and Development
Data Group, the World Bank. 2008. 2008 World Development Indicators
Online. (6)
4. POVERTY INCIDENCE IN MUSLIM COUNTRIES
This section gives an overview of poverty condition in OIC-member
states. The poverty in the majority of the OIC-member countries are
sever and housing more than 50 percent of their population as extremely
poor. Among these countries are Burkina Faso (56.5 percent), Chad (61.9
percent), Guinea (70.1 percent), Mali (51.4 percent), Mozambique (74.7
percent), Niger (65.9 percent), Nigeria (64.4 percent), Sierra Leone
(53.4 percent), and Uganda (51.5 percent). The incidence of poverty in
Bangladesh (49.6 percent), Benin (47.3 percent), Comoros (46.1 percent),
guinea-Bissau (48.8 percent) and Uzbekistan (46.3 percent) is also very
high.
The World Bank (2009) report overestimates the percentage of poor
population (under $1.25 a day) in case of Benin, Burkina Faso,
Guinea-Bissau and Uganda compared to their national poverty lines. In
contrast, countries like Albania, Azerbaijan, Egypt, Iran, Jordan, and
Malaysia have the lowest rate of poverty (less than 2 percent of their
total population) while Kazakhstan, Morocco, Tunisia, Turkey and Gabon
also having less than 5 percent of their total population as poor.
Interestingly, the report underestimates the percentage of poverty in
case of all these countries compared with their national poverty line,
which indicates the real picture of poverty in the respective countries.
However incidence of poverty reported in the countries like Bangladesh,
Mozambique, Niger, Nigeria and Togo is approximately comparable under
both the national and international poverty lines. Under international
poverty line of US $ 2 a day the incidence of poverty, in most of the
countries, is found to be more than 70 percent of their total population
(for detail see Appendix Table 1).
Since the international poverty measurements provide a uniform
standard for comparing poverty rates and the number of people in poverty
across countries, therefore results based on national and international
poverty lines cannot be compared. However, as we have noted elsewhere,
for precise measure micro data of each country is required.
5. RESULTS
In this section we have reported the estimates of resource required
and potential Zakat collection for poverty elimination in the OIC member
countries.
5.1. Resource Shortfall for Poverty Elimination
The column 7 and column 8 of the Table 2 depicts the resource
required for poverty elimination under US $1.25 a day and US $ 2.0 a day
respectively. Fifteen countries of the sample including Albania (0.03
percent), Algeria (0.16 percent), Azerbaijan (0.04 percent), Gabon (0.03
percent), Egypt (0.04 percent), Guyana (0.66 percent), Iran (0.02
percent), Jordan (0.04 percent), Kazakhstan (0.03 percent) Malaysia
(0.02 percent), Morocco (0.06 percent), Suriname (0.54 percent), Tunisia
(0.04 percent), Turkey (0.05 percent) and Yemen (0.88 percent) require
small amount of resources for poverty elimination. These countries
constitute about 37 percent of a total of 38 OIC-member countries that
need less than 1 percent of their GDP per annum for reducing poverty.
For some countries the resource requirement for poverty elimination
ranges from 1 percent to about 3 percent of their GDP. This group of
countries consists of Cameroon (2.69 percent), Cote d'Ivoire (2.01
percent), Djibouti (1.48 percent), Mauritania (1.84 percent), Pakistan
(1 percent), Senegal (3.20 percent), and Tajikistan (1.55 percent).
Resources shortfall for some countries is quite high. These countries
are Mozambique (29.81 percent), Niger (21.29 percent), Sierra Leone
(19.03 percent), and Guinea-Bissau (17.26 percent).
Column 8 of the Table 2 presents the resource shortfall under US
$2. The resource short fall as a percentage of GDP is very high in the
case of Guinea-Bissau (58.24 percent), Mozambique (72.09 percent), Niger
(56.49 percent), Sierra Leone (56.26 percent), Chad (35.06 percent),
Guinea (36.46 percent) and Uganda (31.35 percent). The total resource
shortfall for all the sample countries under US $1.25 a day and US $ 2.0
a day is estimated to be 1.53 percent and 5.20 percent respectively of
their total GDP.
5.2. Potential Zakat Collection
The Table 3 presents the potential amount of Zakat that can be
collected under three different opinions of scholars regarding the items
and assets that can be brought under Zakat net. Column 4 of the Table
shows Muslim population in the respective country, which is used for the
calculation of column 5 of the Table. Potential Zakat collection in
absolute terms is reported in columns 6 through 8, while columns 9
through 11 depict potential Zakat collection as percentage of GDP for
the respective country. On average ZI (7) for 8 OIC members'
countries ranges from 0.02 percent to 0.40 percent of their GDP. This is
due to very low share of Muslim population in these countries.
Similarly, for these countries, Z2 and Z3 vary from 0.04 percent to 0.85
percent and 0.04 percent to 0.85 percent of their GDP respectively. For
rest of the 30 OIC member countries, Z1 ranges from 0.68 percent to 1.88
percent, Z2 varies from 1.46 to 4.85 percent, while Z3 varies from 1.65
percent to 7.43 percent of the GDP of the respective country. The
potential Zakat collection from Z1, Z2 and Z3, for all the countries
under study, comes out to be 1.55 percent, 3.44 percent and 4.31 percent
of their total GDP respectively. Although we have used 1.8 percent as Z1
for all other countries except Egypt, Pakistan and Turkey (for which we
have used 2.0 percent, 1.6 percent and 1.9 percent respectively) still
we get different potential Zakat collection as a share of GDP due to
adjustment of GDP with Muslim population share.
5.3. Resource Shortfall and Potential Zakat Collection
Resource shortfall and potential Zakat collection have been put
together in Table 4. Columns 3 and 4 shows the resources shortfall under
US $ 1.25 and 2 respectively whereas columns 5 through 7 represents the
potential Zakat collection under three definitions of Zakatable items.
The resource requirement, under US $1.25 a day, of some of the countries
for poverty elimination is too high, which cannot be met by their
potential Zakat collection. For example, the resource shortfall of
Burkina Faso (9.73 percent), Chad (12.78 percent), Guinea (14.62
percent), Guinea-Bissau (17.26 percent), Mozambique (29.81 percent),
Niger (21.29 percent), Ni geria (10.19 percent), Sierra Leone (19.03
percent) and Uganda (10.28 percent) are very high and corresponding
Zakat collection even under Z3 is very low. However, resource shortfall
of the countries like Albania, Algeria, Azerbaijan, Djibouti, Egypt,
Iran, Jordan, Kazakhstan, Malaysia, Morocco, Pakistan, Tajikistan,
Tunisia, Turkey, Yemen can be covered from collection of Z1 (see Table).
If we take into account the administrative cost of Zakat collection
(assuming 10 to 20 percent of the potential Zakat collection), even then
Z2 and Z3 collection is enough for fulfilling both the amount of
resource shortfall and administrative cost. The countries, like Gabon
(0.03 percent) Mauritania (1.84), Senegal (3.20 percent) and Suriname
(0.54 percent) cannot meet their resource shortfall by Z1 but these can
meet it by utilising Z2. The nineteen OIC member countries can easily
eliminate poverty form generating their own Zakat resources, whereas the
rest of the sample countries cannot meet their resource shortfall from
their own resources.
Resource shortfall, under US $1.25 a day and US $ 2.0 a day, on
average, is 1.53 percent and 5.20 percent of the GDP for all the
countries under study. The corresponding amount, which can be collected
under Z1, Z2 and Z3, estimated to be 1.55 percent, 3.44 percent and 4.31
percent of their total GDP, respectively. These resources are not only
sufficient to provide for the shortfall and eliminate the extreme
poverty but also can generate surplus.
Resource shortfall under US $ 2.0 a day is high. Countries, which
could meet their resource shortfall under US $ 1.25 a day from Zakat
proceeds, are notable to meet their resource shortfall under US $ 2.0 a
day. The countries which added to such list ate Djibouti, Pakistan,
Tajikistan and Yemen (see Table 4). As noted above that resource
shortfall under US $ 2.0 a day cannot be met by resources raised through
potential Zakat collection. The maximum that can be collected is
estimated to be 4.31 percent of the GDP of all countries under study,
whereas corresponding resource required are estimated to be 5.20 percent
of the GDP of these countries. However, some resource rich countries are
not included in the sample due to non-availability of the data., If
these countries also collect Zakat to its potential and transfer their
surplus to the common pool and if these funds could be provided for the
resource deficit countries then we hope that the deficit in resource can
be met and poverty under US $ 2 a day can easily be eliminated.
6. SUMMARY AND CONCLUSION
The poverty has been the serious problem and challenge for the
Developing countries. Since majority of the OIC countries fall in the
same category, therefore, these countries also face the same problems
and challenges. Different policies and strategies, in addition to
safety-nets programme have been adopted in the past to alleviate
poverty, but poverty still persists. Some of the Muslim countries have
implemented the system of Zakat officially and while in other it is
unofficial matter and they have ignored the collection and distribution.
But the fact is that none of the Muslim country has enforced Zakat in
letter and spirit. It is believed that if the system is enforced in
letter and spirit then extreme poverty can be eliminated. The paper has
been written in this spirit.
The paper has estimated the resource required by 38 OIC member
countries and potential Zakat collection for poverty elimination. We
have employed the poverty gap index based on US $ 1.25 and US $ 2.0 as
reported in World Bank Indicators (2009) for measuring resource
shortfall. Our results show that fifteen countries of the sample
including Albania (0.03 percent), Algeria (0.16 percent), Azerbaijan
(0.04 percent), Gabon (0.03 percent), Egypt (0.04 percent), Guyana (0.66
percent), Iran (0.02 percent), Jordan (0.04 percent), Kazakhstan (0.03
percent) Malaysia (0.02 percent), Morocco (0.06 percent), Suriname (0.54
percent), Tunisia (0.04 percent), Turkey (0.05 percent) and Yemen (0.88
percent) require small amount of resources for poverty elimination. Some
countries, like Cameroon, Cote d'Ivoire, Djibouti, Mauritania,
Pakistan, Senegal and Tajikistan resource requirement for poverty
elimination ranges from 1 percent to about 3 percent of their GDP.
Resources shortfall for some countries is quite high. These countries
are Mozambique (29.81 percent), Niger (21.29 percent), Sierra Leone
(19.03 percent), and Guinea-Bissau (17.26 percent). Similarly resource
shortfall, under US $2 a day, for countries like Guinea-Bissau (58.24
percent), Mozambique (72.09 percent), Niger (56.49 percent), Sierra
Leone (56.26 percent), Chad (35.06 percent), Guinea (36.46 percent) and
Uganda (31.35 percent) is quite high. The total resource shortfall for
all the sample countries under US $ 1.25 a day and US $ 2.0 a day is
estimated to be 1.53 percent and 5.20 percent of their total GDP
respectively.
We have used Kahf (1989) for the estimation of potential Zakat
collection with some modifications. On average, Z1 for 8 OIC member
countries ranges from 0.02 percent to 0.40 percent of their GDP. This is
due to very low share of Muslim Population. Similarly, for these
countries, Z2 and Z3 vary from 0.04 percent to 0.85 percent and 0.04
percent to 0.85 percent of their GDP respectively. For rest of the 30
OIC member countries, Z1 ranges from 0.68 percent to 1.88 percent, Z2
varies from 1.46 to 4.85 percent, while Z3 varies from 1.65 percent to
7.43 percent of the GDP of the respective country. The potential Zakat
collection from Z1, Z2 and Z3, for all the countries under study, comes
out to be 1.55 percent, 3.44 percent and 4.31 percent of their total GDP
respectively.
Keeping in view the resource required and resource available
through potential Zakat collection, the general picture that emerges is
as follow. Most of the African OIC member countries cannot meet their
resource requirement by their own potential Zakat collection. However,
countries like Albania, Algeria, Azerbaijan, Djibouti, Egypt, Iran,
Jordan, Kazakhstan, Malaysia, Morocco, Pakistan, Tajikistan, Tunisia,
Turkey, Yemen resource shortfall can be covered from collection of Z1.
If we take into account the administrative cost of Zakat collection
(assuming 10 to 20 percent of the potential Zakat collection), even then
Z2 and Z3 collection is enough for fulfilling both the amount of
resource shortfall and administrative cost. The countries, like Gabon
(0.03 percent) Mauritania (1.84), Senegal (3.20 percent) and Suriname
(0.54 percent) cannot meet their resource shortfall by Z1 but these can
meet it by utilising Z2. The nineteen OIC member countries can easily
eliminate poverty form generating their own Zakat resources, whereas the
rest of the sample countries cannot meet their resource shortfall from
their own resources.
Resource shortfall, under US $1.25 a day and US $ 2.0 a day, on
average, is 1.53 percent and 5.20 percent of the GDP for all the
countries under study. The corresponding amount, which can be collected
under Z1, Z2 and Z3, estimated to be 1.55 percent, 3.44 percent and 4.31
percent of the total GDP, respectively. These resources are not only
sufficient to provide for the shortfall and eliminate the extreme
poverty but also can generate surplus.
Resource shortfall under US $ 2.0 a day is high. Countries, which
could meet their resource shortfall under US $ 1.25 a day from Zakat
proceeds, are notable to meet their resource shortfall under US $ 2.0 a
day. The countries which added to such list are Djibouti, Pakistan,
Tajikistan and Yemen. The maximum Zakat that can be collected is
estimated to be 4.31 percent of the GDP of all countries under study,
whereas corresponding resource required are estimated to be 5.20 percent
of the GDP of these countries. However, some resource rich countries are
not included in the sample due to non-availability of the data. If these
countries also collect Zakat to its potential and transfer their surplus
to the common pool which could be provided for the resource deficit
countries, then we hope that the deficit in resource can be met and
poverty under US $ 2 a day can easily be eliminated. However, this
requires globalisation of Zakat and serious efforts on the part of the
OIC-member countries.
Appendix Table 1
Poverty in the Selected Muslim Countries
1 2 3 4
OIC--Member Population Below Survey Population
Countries National Poverty Year Below $ 1.25
Line (%) a Day (%)
Albania 25 2005 <2
Algeria NA 1995 6.8
Azerbaijan 49 2005 <2
Bangladesh 45 2005 49.6
Benin 37 2003 47.3
Burkina Faso 45 2003 56.5
Cameroon 48 2001 32.8
Chad 80 2002 61.9
Comoros 60 2004 46.1
Coted1voire NA 2002 23.3
Djibouti 50 2002 18.8
Egypt 16.7 2004 <2
Gabon NA 2005 4.8
Gambia NA 2003 34.3
Guinea 40 2002 70.1
Guinea-Bissau NA 2002 48.8
Guyana NA 1998 7.7
Iran 40 2005 <2
Jordan 30 2006 <2
Kazakhstan 26 2003 3.1
Malaysia 8 2004 <2
Mali 64 2006 51.4
Mauritania 57 2000 21.2
Morocco 17 2007 2.5
Mozambique 70 2002 74.7
Niger 63 2005 65.9
Nigeria 60 2003 64.4
Pakistan 35 2004 '22.6
Senegal 54 2005 33.5
Sierra Leone 68 2002 53.4
Suriname NA 1999 15.5
Tajikistan 60 2004 21.5
Togo 32 2006 38.7
Tunisia 14.1 2000 2.6
Turkey 20 2005 2.7
Uganda 35 2005 51.5
Uzbekistan NA 2003 46.3
Yemen 45.2 2005 17.5
1 5 6 7
OIC--Member Poverty gap at Population Poverty Gap
Countries $ 1.25 a day Below $ 2 a at $ 2 a Day
(%) Day (%) (%)
Albania <0.5 7.8 1.4
Algeria 1.4 23.6 6.4
Azerbaijan <0.5 <2 <0.5
Bangladesh 13.1 81.3 33.8
Benin 15.7 75.3 33.5
Burkina Faso 20.3 81.2 39.2
Cameroon 10.2 57.7 23.6
Chad 25.6 83.3 43.9
Comoros 20.8 65 34.2
Coted1voire 6.8 46.8 17.6
Djibouti 5.3 41.2 14.6
Egypt <0.5 18.4 3.5
Gabon 0.9 19.6 5
Gambia 12.1 56.7 24.9
Guinea 32.2 87.2 50.2
Guinea-Bissau 16.5 77.9 34.8
Guyana 3.9 16.8 6.9
Iran <0.5 8 1.8
Jordan <0.5 3.5 0.6
Kazakhstan <0.5 17.2 3.9
Malaysia <0.5 7.8 1.4
Mali 18.8 77.1 36.5
Mauritania 5.7 44.1 15.9
Morocco 0.5 14 3.1
Mozambique 35.4 90 53.5
Niger 28.1 85.6 46.6
Nigeria 29.6 83.9 46.9
Pakistan 4.4 60.3 18.7
Senegal 10.8 60.3 24.6
Sierra Leone 20.3 76.1 37.5
Suriname 5.9 27.2 11.7
Tajikistan 5.1 50.8 16.8
Togo 11.4 69.3 27.9
Tunisia <0.5 12.8 3
Turkey 0.9 9 2.6
Uganda 19.1 75.6 36.4
Uzbekistan 15 76.7 33.2
Yemen 4.2 46.6 14.8
Source: World Bank (2009).
Comments
As the title suggest, this is an important area in poverty
alleviation through potential Zakat Collection in OIC-member Countries.
First of all, apart from the technical comments, I would like to say
that it is difficult to comment on the text as a through editing of the
paper is needed for the benefit of the reader.
Secondly, authors claims at page 5 that earlier studies were either
limited in scope or lack the proper methodology for estimation of the
resources needed and potential zakat collection. But what constitutes a
proper methodology is not explained in the paper clearly. Thirdly, the
authors have used poverty gap index based on $ 1 a day poverty or $ 2 a
day estimated by the World Bank to compute the resource shortfall for
poverty alleviation but have not mentioned with clarity that how they
have converted into absolute number.
Thirdly, authors reviewed that Kahf (1989) using National Income
Accounts estimated zakat potential for eight Muslim countries which is
based on three different opinions of jurists regarding zakatable items
namely Z1, Z2 and Z3.
* Z1 was estimated in accordance with the majority traditional view
according to which Zakat was levied on agriculture, livestock, stock in
trade, go|d, silver and money.
* Z2 was based in accordance with the views of contemporary Muslim
scholars where Zakat can be deducted from net returns of manufacturing
concerns and building rents and from net savings out of salaries.
* Z3 was based on Malikite views, where Zakat base includes
buildings and other fixed assets except those assigned for personal and
family use. According to these definitions, under Z1, Zakat can be
collected in the range of 1-2 percent of GDP, under Z2 from 3.1- 4.95
and under Z3 from 3.25 to 7.5 percent of the GDP for the eight Muslim
countries.
The authors claim that Kahf (1989) estimates has a shortcoming of
not taking into account of non-Muslims population and claim that their
estimates are better than Khaf (1989). While authors have not applied
the above method using national accounts as done by Kahf, the authors
should not claim that these are their estimates and are better than
Kahf. In my opinion, authors have simply adjusted Kahf estimates by
multiplying it to non-Muslim population ratios with Kahf's
estimates. The authors' estimates can be regarded as Kahf's
non-Muslim population adjusted estimates.
Finally, it is also important to discuss the existing extent of
Zakat collection in Pakistan and in other Muslims countries and how
Zakat collection can be enhanced to fill the gap in order to reduce
poverty. Currently, few hundred billion of rupees have been collected in
Pakistan as people are not willing to pay Zakat through government
system due to lack of creditability of the government. Similar is the
case with other Muslim countries. Hence, its scope for poverty
alleviation will remain limited.
Talat Anwar
Canadian International Development Agency, Programme Support Unit,
Islamabad.
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the Institution of Zakat: A Case of OIC Member Countries. International
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Indicators Online. Washington, DC: The World Bank. Available at:
http://go.worldbank.org/UOFSM7AQ40
(1) Data are available for 38 OIC-member countries only.
(2) For precise estimates, national poverty lines and micro data of
each country are required, which are not available to us. Therefore we
have to rely on the International poverty line and the poverty gap index
measured in terms of international poverty line. The World Bank has
updated the previous international poverty line which was in terms of$ I
a day for the extreme poor and $ 2 a day for the relative poor. However,
this poverty line remained controversial among the researchers [see
Pogge and Reddy (2003)]. The recent updated poverty lines in terms of
$1.25 a day and $2.0 a day is also questioned by the same author [see
Reddy (2009)].
(4) Although non-Muslims are exempt from the payment of zakat but
controversy still exists regarding the payment of zakat to the poor
non-Muslims. Maududi (1988, pp. 63-64), wrote that non-Muslims should be
helped from other social welfare funds as they are not eligible for
taking zakat. His views were based on Hadith "...To be taken from
your rich people (Muslims) and to be distributed to your poor
people". Shaikh (1980) was of the view that zakat money may be paid
to non-Muslims after meeting the need of the Muslims. He said that there
is nothing-pertinent indication in the Qur'an or Hadith that zakat
is to be used for Muslims only. Abu Saud (1988) expressed the same view.
He further reported that zakat could be paid to non-Muslims as long they
do not fight against IsLam and Muslims. However, non-Muslims are not
excluded from the poor people of the countries under study.
(5) Available at (http://www.nationmaster.com/graph/eco_gdp
pur_pow_par-economy- gdp-purchasingpower-parity) Economy Statistics >
GDP (purchasing power parity) (most recent) by country.
(6) GDP, PPP, current international dollars, :
http://earthtrends.wri.org/text/economics-business/variable222.html
(7) Z1 = [{(0.018) (Adjusted GDP/GDP)}* 100]. Similarly Z2 and Z3
are calculated by using average of eight Muslim countries, which is 3.85
percent and 4.34 percent of the GDP respectively. For Egypt, Pakistan
and Turkey Z2 is 3.9 percent, 3.5 percent and 4.9 percent and Z3 is 4.9
percent, 4.4 percent and 7.5 percent respectively.
Yaumidin, Karomah U. (2009) Islamic Alternative: Comparative Study
between Indonesia and Malaysia. Paper presented in The International
Conference on Islamic Economics and Economics of the OIC Countries,
Kuala Lumpur, 28-29 April.
Nasim Shah Shirazi <
[email protected]> is Professor, and Md.
Fouad Bin Amin is PhD Student, Department of Economics, Faculty of
Economics and Management Sciences, International Islamic University
Malaysia (IIUM).
Table 1
Percentage of Estimated Zakat Proceeds to GDP in
Selected Muslim Countries
Countries Z1 Z2 Z3
Egypt 2.0 3.9 4.9
Indonesia 1.0 1.7 2.0
Pakistan 1.6 3.5 4.4
Qatar 0.9 3.7 3.2
Saudi Arabia 1.2 3.7 3.4
Sudan 4.3 6.3 6.2
Syria 1.5 3.1 3.1
Turkey 1.9 4.9 7.5
Average 1.80 3.85 4.34
Source. Kahl (1989).
Table 2
Resource Shortfall for Poverty Elimination under US $1.25& US $ 2
Poverty Lines
1 2 3 4 5
OIC--Member Survey Total GDP (PPP) Resource
Countries Year Population Millions Shortfall
under $
1.25 per
Annum
(Million)
Albania 2005 3153731 17,234 5.76
Algeria 1995 28265291 109,616 180.54
Azerbaijan 2005 8391850 38,389 15.32
Bangladesh 2005 153281120 163,728 9161.42
Benin 2003 7961594 9,163 570.30
Burkina Faso 2003 13081911 12,450 1211.63
Cameroon 2001 16240110 28,129 755.77
Chad 2002 9118887 8,335 1065.09
Comoros 2004 587944 630 55.80
Cote d'Ivoire 2002 17691452 27,333 548.88
Djibouti 2002 762775 1,244 18.44
Egypt 2004 71550018 309,733 130.58
Gabon 2005 1290693 17,839 5.30
Gambia 2003 1524061 1,491 84.14
Guinea 2002 8513599 8,556 1250.75
Guinea-Bissau 2002 1455881 635 109.60
Guyana 1998 736291 1,977 13.10
Iran 2005 69087070 643,503 126.08
Jordan 2006 5537600 25,628 10.11
Kazakhstan 2003 14909000 103,441 27.21
Malaysia 2004 25191441 276,939 45.97
Mali 2006 11968376 12,664 1026.59
Mauritania 2000 2566152 3,634 66.74
Morocco 2007 30860595 125,392 70.40
Mozambique 2002 19134153 10,366 3090.40
Niger 2005 13264190 7,988 1700.55
Nigeria 2003 134659379 178,435 18185.75
Pakistan 2004 152061263 306,752 3052.63
Senegal 2005 11770340 18,133 579.98
Sierra Leone 2002 4924199 2,396 456.07
Suriname 1999 432413 2,159 11.64
Tajikistan 2004 6467377 9,682 150.49
Togo 2006 6410428 4,971 333.42
Tunisia 2000 9563500 45,617 17.45
Turkey 2005 72065000 561,075 295.92
Uganda 2005 28947181 24,534 2522.57
Uzbekistan 2003 25567700 43,028 1749.79
Yemen 2005 21095679 46,150 404.25
For all Countries 101009024 3208969 49106.43
1 6 7 8
OIC--Member Resource Resource Resource
Countries Shortfall Shortfall Shortfall
under $ 2 under $ under $ 2
per Annum 1.25 per per Annum
(Million) Annum as as % of
% of GDP GDP
Albania 32.23 0.03 0.19
Algeria 1320.55 0.16 1.20
Azerbaijan 30.63 0.04 0.08
Bangladesh 37820.58 5.60 23.10
Benin 1947.01 6.22 21.25
Burkina Faso 3743.52 9.73 30.07
Cameroon 2797.85 2.69 9.95
Chad 2922.33 12.78 35.06
Comoros 146.79 8.86 23.30
Cote d'Ivoire 2273.00 2.01 8.32
Djibouti 81.30 1.48 6.54
Egypt 1828.10 0.04 0.59
Gabon 47.11 0.03 0.26
Gambia 277.03 5.64 18.58
Guinea 3119.89 14.62 36.46
Guinea-Bissau 369.85 17.26 58.24
Guyana 37.09 0.66 1.88
Iran 907.80 0.02 0.14
Jordan 24.25 0.04 0.09
Kazakhstan 424.46 0.03 0.41
Malaysia 257.46 0.02 0.09
Mali 3188.97 8.11 25.18
Mauritania 297.85 1.84 8.20
Morocco 698.38 0.06 0.56
Mozambique 7472.84 29.81 72.09
Niger 4512.21 21.29 56.49
Nigeria 46103.33 10.19 25.84
Pakistan 20757.88 1.00 6.77
Senegal 2113.72 3.20 11.66
Sierra Leone 1348.00 19.03 56.26
Suriname 36.93 0.54 1.71
Tajikistan 793.16 1.55 8.19
Togo 1305.61 6.71 26.26
Tunisia 209.44 0.04 0.46
Turkey 1367.79 0.05 0.24
Uganda 7691.84 10.28 31.35
Uzbekistan 6196.59 4.07 14.40
Yemen 2279.18 0.88 4.94
For all Countries 166782.55 1.53 5.20
Source:
(1.) Total Number of Population is taken from WDI, 2007, Online
Database, 2007 The World Bank Group,
(2.) GDP (at PPP) from 2005-2007 are taken from the web.
(http://www-nationmaster-com-graph-
eco_gdp_pur_pow_par-economy-gdp-purchasing power-parity) Economy
Statistics > GDP (purchasing power parity) (most recent) by
country.
(3.) GDP, PPP, current international dollars, Web: http://
earthtrends.wri.org-text-economics-business-variable-222.html.
(4.) All the web pages accessed on 20-08-09 to 29-09-2009.
Table 3
Potential Zakat Collection
1 2 3 4 5
OIC-Member Survey GDP Muslim Adjusted
Countries Year (PPP) [Popu.sup.n] GDP (PPP)
Millions (%) in Million
USD
Albania 2005 17,234 58 9995.72
Algeria 1995 109,616 99 108519.84
Azerbaijan 2005 38,389 93.4 35855.33
Bangladesh 2005 163,728 88 144080.64
Benin 2003 9,163 20 1832.60
Burkina Faso 2003 12,450 52 6474.00
Cameroon 2001 28,129 20 5625.80
Chad 2002 8,335 54 4500.90
Comoros 2004 630 99 623.70
Cote d'Ivoire 2002 27,333 38.6 10550.54
Djibouti 2002 1,244 99 1231.56
Egypt 2004 309,733 90 278759.70
Gabon 2005 17,839 1 178.39
Gambia 2003 1,491 95 1416.45
Guinea 2002 8,556 85 7272.60
Guinea-Bissau 2002 635 38 241.30
Guyana 1998 1,977 10 197.70
Iran 2005 643,503 98 630632.94
Jordan 2006 25,628 95 24346.60
Kazakhstan 2003 103,441 47 48617.27
Malaysia 2004 276,939 60.4 167271.16
Mali 2006 12,664 90 11397.60
Mauritania 2000 3,634 99 3597.66
Morocco 2007 125,392 99 124138.08
Mozambique 2002 10,366 20 2073.20
Niger 2005 7,988 90 7189.20
Nigeria 2003 178,435 50 89217.50
Pakistan 2004 306,752 98 300616.96
Senegal 2005 18,133 94 17045.02
Sierra Leone 2002 2,396 60 1437.60
Suriname 1999 2,159 22 474.98
Tajikistan 2004 9,682 95 9197.90
Togo 2006 4,971 13.7 681.03
Tunisia 2000 45,617 99 45160.83
Turkey 2005 561,075 99 555464.25
Uganda 2005 24,534 15 3680.10
Uzbekistan 2003 43,028 89 38294.92
Yemen 2005 46,150 99 45688.50
For all Countries 3208969
1 6 7 8
OIC-Member Z1 Z2 Z3
Countries (Million (Million (Million
USD) USD) USD)
Albania 179.92 384.84 433.81
Algeria 1953.36 4178.01 4709.76
Azerbaijan 645.40 1380.43 1556.12
Bangladesh 2593.45 5547.10 6253.10
Benin 32.99 70.56 79.53
Burkina Faso 116.53 249.25 280.97
Cameroon 101.26 216.59 244.16
Chad 81.02 173.28 195.34
Comoros 11.23 24.01 27.07
Cote d'Ivoire 189.91 406.20 457.89
Djibouti 22.17 47.42 53.45
Egypt 5575.19 10871.63 13659.23
Gabon 3.21 6.87 7.74
Gambia 25.50 54.53 61.47
Guinea 130.91 280.00 315.63
Guinea-Bissau 4.34 9.29 10.47
Guyana 3.56 7.61 8.58
Iran 11351.39 24279.37 27369.47
Jordan 438.24 937.34 1056.64
Kazakhstan 875.11 1871.76 2109.99
Malaysia 3010.88 6439.94 7259.57
Mali 205.16 438.81 494.66
Mauritania 64.76 138.51 156.14
Morocco 2234.49 4779.32 5387.59
Mozambique 37.32 79.82 89.98
Niger 129.41 276.78 312.01
Nigeria 1605.92 3434.87 3872.04
Pakistan 4809.87 10521.59 13227.15
Senegal 306.81 656.23 739.75
Sierra Leone 25.88 55.35 62.39
Suriname 8.55 18.29 20.61
Tajikistan 165.56 354.12 399.19
Togo 12.26 26.22 29.56
Tunisia 812.89 1738.69 1959.98
Turkey 10553.82 27217.75 41659.82
Uganda 66.24 141.68 159.72
Uzbekistan 689.31 1474.35 1662.00
Yemen 822.39 1759.01 1982.88
For all Countries 49896.21 110547.42 138365.46
1 9 10 11
OIC-Member Z1 Z2 Z3
Countries (% of (% of (% of
GDP) GDP) GDP)
Albania 1.04 2.23 2.52
Algeria 1.78 3.81 4.30
Azerbaijan 1.68 3.60 4.05
Bangladesh 1.58 3.39 3.82
Benin 0.36 0.77 0.87
Burkina Faso 0.94 2.00 2.26
Cameroon 0.36 0.77 0.87
Chad 0.97 2.08 2.34
Comoros 1.78 3.81 4.30
Cote d'Ivoire 0.69 1.49 1.68
Djibouti 1.78 3.81 4.30
Egypt 1.80 3.51 4.41
Gabon 0.02 0.04 0.04
Gambia 1.71 3.66 4.12
Guinea 1.53 3.27 3.69
Guinea-Bissau 0.68 1.46 1.65
Guyana 0.18 0.39 0.43
Iran 1.76 3.77 4.25
Jordan 1.71 3.66 4.12
Kazakhstan 0.85 1.81 2.04
Malaysia 1.09 2.33 2.62
Mali 1.62 3.47 3.91
Mauritania 1.78 3.81 4.30
Morocco 1.78 3.81 4.30
Mozambique 0.36 0.77 0.87
Niger 1.62 3.47 3.91
Nigeria 0.90 1.93 2.17
Pakistan 1.57 3.43 4.31
Senegal 1.69 3.62 4.08
Sierra Leone 1.08 2.31 2.60
Suriname 0.40 0.85 0.95
Tajikistan 1.71 3.66 4.12
Togo 0.25 0.53 0.59
Tunisia 1.78 3.81 4.30
Turkey 1.88 4.85 7.43
Uganda 0.27 0.58 0.65
Uzbekistan 1.60 3.43 3.86
Yemen 1.78 3.81 4.30
For all Countries 1.55 3.44 4.31
Source: Percentage of Muslim Population is taken from:
http://en.wikipedia.org-wiki-Islam by-country.
Table 4
Resource Shortfall and Potential Zakat Collection
1 2 3 4
OIC--Member Survey Resource Shortfall Resource Shortfall
Countries Year % of GDP (US $ % of GDP (US $ 2)
1.25)
Albania 2005 0.03 0.19
Algeria 1995 0.16 1.20
Azerbaijan 2005 0.04 0.08
Bangladesh 2005 5.60 23.10
Benin 2003 6.22 21.25
Burkina Faso 2003 9.73 30.07
Cameroon 2001 2.69 9.95
Chad 2002 12.78 35.06
Comoros 2004 8.86 23.30
Cote d'Ivoire 2002 2.01 8.32
Djibouti 2002 1.48 6.54
Egypt 2004 0.04 0.59
Gabon 2005 0.03 0.26
Gambia 2003 5.64 18.58
Guinea 2002 14.62 36.46
Guinea-Bissau 2002 17.26 58.24
Guyana 1998 0.66 1.88
Iran 2005 0.02 0.14
Jordan 2006 0.04 0.09
Kazakhstan 2003 0.03 0.41
Malaysia 2004 0.02 0.09
Mali 2006 8.11 25.18
Mauritania 2000 1.84 8.20
Morocco 2007 0.06 0.56
Mozambique 2002 29.81 72.09
Niger 2005 21.29 56.49
Nigeria 2003 10.19 25.84
Pakistan 2004 1.00 6.77
Senegal 2005 3.20 11.66
Sierra Leone 2002 19.03 56.26
Suriname 1999 0.54 1.71
Tajikistan 2004 1.55 8.19
Togo 2006 6.71 26.26
Tunisia 2000 0.04 0.46
Turkey 2005 0.05 0.24
Uganda 2005 10.28 31.35
Uzbekistan 2003 4.07 14.40
Yemen 2005 0.88 4.94
On Average 1.53 5.20
1 5 6 7
OIC--Member Z1 Z2 Z3
Countries (% of GDP) (% of GDP) (% of GDP)
Albania 1.04 2.23 2.52
Algeria 1.78 3.81 4.30
Azerbaijan 1.68 3.60 4.05
Bangladesh 1.58 3.39 3.82
Benin 0.36 0.77 0.87
Burkina Faso 0.94 2.00 2.26
Cameroon 0.36 0.77 0.87
Chad 0.97 2.08 2.34
Comoros 1.78 3.81 4.30
Cote d'Ivoire 0.69 1.49 1.68
Djibouti 1.78 3.81 4.30
Egypt 1.80 3.51 4.41
Gabon 0.02 0.04 0.04
Gambia 1.71 3.66 4.12
Guinea 1.53 3.27 3.69
Guinea-Bissau 0.68 1.46 1.65
Guyana 0.18 0.39 0.43
Iran 1.76 3.77 4.25
Jordan 1.71 3.66 4.12
Kazakhstan 0.85 1.81 2.04
Malaysia 1.09 2.33 2.62
Mali 1.62 3.47 3.91
Mauritania 1.78 3.81 4.30
Morocco 1.78 3.81 4.30
Mozambique 0.36 0.77 0.87
Niger 1.62 3.47 3.91
Nigeria 0.90 1.93 2.17
Pakistan 1.57 3.43 4.31
Senegal 1.69 3.62 4.08
Sierra Leone 1.08 2.31 2.60
Suriname 0.40 0.85 0.95
Tajikistan 1.71 3.66 4.12
Togo 0.25 0.53 0.59
Tunisia 1.78 3.81 4.30
Turkey 1.88 4.85 7.43
Uganda 0.27 0.58 0.65
Uzbekistan 1.60 3.43 3.86
Yemen 1.78 3.81 4.30
On Average 1.55 3.44 4.31
Source: Based on Tables 2 and 3.
