


































Advances in Politics and Economics 
ISSN 2576-1382 (Print) ISSN 2576-1390 (Online) 

Vol. 6, No. 2, 2023 

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1 
 

Original Paper 

Shared Prosperity and the Quintile Income in Sudan: 

Preliminary Findings 

Omer Eltayeb Omer
1*

 

1
 Rural Development Department, University of Bakhat Al-Ruda, Eddueim, Sudan 

* 
Omer Eltayeb Omer, Corresponding author 

 

Received: February 14, 2023     Accepted: March 18, 2023     Online Published: March 31, 2023 

doi:10.22158/ape.v6n2p1           URL: http://dx.doi.org/10.22158/ape.v6n2p1 

 

Abstract 

This paper attempted to tackle tow issues: the first issue is the income distribution top income quintiles 

(including some parcels) with bottom 20% and 40% ones. Secondly whether economic growth alone, 

could reduce extreme poverty and mitigate income inequality in Sudan? Different prosperity shared 

indicators applied to data obtained from two Labor Force Migration households’ Surveys collected by 

Ministry of Manpower for years 1996 and 2011. The findings of this study indicated that the income 

share of bottom 40% failed to catch up with shares of top 10%.and overall per capita .Accordingly, all 

the shared prosperity indicators results were associated with idea of polarization in the Sudan society, 

and more importantly CAGR (as one of indicators) empathized that the bottom 20% income have to 

grow by more than 60% annually in order to catch up with overall per capita growth during the period 

of the study. To improve the picture of the income distribution and to reverse the situation of poverty in 

Sudan, the pattern of economic growth has to be restructured and to be associated with high economic 

participation. The paper recommended a deliberate government intervention to improve income 

distribution.  

Keywords 

Shared Prosperity, Quintile Income, Overall per capita, Polarization, Sudan 

 

1. Introduction 

The main objectives of this paper are to answer the following two questions: firstly whether prosperity 

sharing proportionately or not? Secondly would economic growth alone is quite sufficient to reduce 

extreme poverty and to mitigate income inequality? Using data from two Labor Force Migration 

Households’ Surveys (LFMHS) collected by Ministry of Manpower for years 1996 and 2011. Various 

inequality measures such as Gini, Plama ratios and Coefficient of variation, as well as simple Algebra 



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methods of shared Prosperity indicators employed to tackle the above twofold questions using data 

obtained from LFMHS. The growth rates of bottom 40%, top 10% and middle income groups, as well as 

overall per capita income growth from house hold surveys’ data, used by analogy to resemble the Growth 

Domestic Product (GDP) and its associate GDP per capita. On policy side the paper attempt to elaborate 

the question concerning the economic and development policies such as economic growth alone is not 

sufficient to eliminate poverty and inequality, answering such type of question will be helpful for the 

policy makers to design and forge policies and strategies about how to allocate development resources 

between regions and economic sectors in order to reduce poverty and to improve income inequality. 

Though the data isn’t timely due to the fact that government often procrastinated in carrying household 

surveys in regular convergent periods’ basis, it is useful in painting an empirical and quantitative 

documentation picture of bleak economic injustices of long time autocratic government ruled by so 

called National Congress Party (previously National Islamic Front). This paper cover four sections: 

section one is an introduction; section two handling Sudan socioeconomic aspects; section three to 

elaborate data sources and provided under pining theoretical as well as equation formulas for different 

shared prosperity indicators and section four covered the discussion and the results of the study. Finally a 

conclusion to wrap up the proceedings of the paper, and embedded most important results, policy 

implications and further future suggestions. 

 

2. Sudan Socioeconomic Aspects 

Sudan during the period of study achieved higher economic growth rate a 5.8% and sometimes 

exceeded more than 7% per annum, this spectacular growth led to enlargement of its economic size 

from US$ 12 billion to US$ 65 billion and the per capita income grew by 46% per year due the 

exploration and exportation of oil (Nadip, E Alvin, & Lange, S2019). However, Sudan forfeited this 

opportunity to engineer genuine economic transformation and failed to achieve another important 

macroeconomic objective, that to generate sufficient employment opportunities for population growing 

with fast growth rate (2.8%), a population that characterized with young age structure, to mean that an 

army of employment seekers pouring in labor market inactivate to receive new comers. However, the 

employment remunerative is important than employment opportunities for sustainable poverty 

reduction (Fields, 2012, 2018). In addition to these demographic aspects, the inappropriateness and 

non-compliance of the education output to the requirement of the labor market, caused higher youth 

unemployment, in particular the graduates of social sciences suffered higher unemployment compared 

to applied science graduates, Sudanese labor market generally is characterized by low educational 

attainment lack of training and technological development . About 43% of labor force has no education, 

in the urban sector, the workers with no education represent 13.4%, while in the rural sector they are 

about 56%, gender wise employed force 34.9% and 65.9% had no education for males and females, 

respectively (Maglad, 2013; Ali & Elbadawi, 2004).  

The unemployment situation is aggravated further due the application of economic reform policies 



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based on what called Washington consensus namely the privatization of state owned enterprises as one 

of main pillars of the blend of World Bank and international monetary Fund programs, bearing in mind 

the government is main employer particularly in urban sector.  

Also harsh authoritarian measures adopted by the ousted government such as fearing non-trustees in 

different government sectors, and most of the privatized enterprises favored the government affiliates 

and cronies. Also the defunct regime used economic policies to achieve its own political agenda and to 

serve the economic interests of the privileged elite and to consolidate their position on market and 

finance (El-Battahani, 2015). 

The pattern of economic growth, which resulted in more than 7% of economic growth, it isn’t robust 

pattern, this high rate of economic growth is not due: to investment in non- oil sector; investment in 

infrastructure; existence rule of law; existence of virtuous social institutions; prevalence of stable 

macro-economic environment or viable politics. The growth booming probably due to the natural gifts 

such as oil and gold, the traditional composition of the economy remain the same—only industrial 

sector improved due to increased share of oil production—i.e., small enclave modern sector extractive 

colonial built to serve the interest of colonial and domestic few small group of elite, is remained as 

dualistic economy with huge traditional agriculture sector dominated by small modern sector, with 

slight changes if any (Ali & Elbadawi, 2004)  

As far as poverty is concerned, head account, according to the household Survey (2009) carried by the 

National Central Bureau for statistics, it was ranged between 26% as lowest for Khartoum and 69% as 

highest for Darfur the conflict zone, and 47% for the national level, this means only one of two 

Sudanese were able get the minimum food and non-food bundle in 2009. The urban poverty was 

enormously lower than rural areas (Omer, 2018, 2021). 

For human development index as it concerned, prepared by United Nation development program, 

Sudan is classified amongst the poor developing countries in nineties and 2000, while for Millennium 

Development Goals Interim report (MDGs) in 2004, the performance of Sudan in the eight MDGs 

goals were significantly low compared with targeted ones. Moreover, Ali showed that need to sustain a 

growth about 7% per annum to achieve the MDGs on Poverty; otherwise, growing at 2.2 per capita 

income, Sudan would need 28 years to accomplish the MDGs on poverty (Omer, 2018; and Ali, no 

date). While for inequality, latest study findings indicted Sudan is highly unequal in terms of Gini, 

Thiel and Plama Ratios, and the size of middle class size is shrinking for the whole country, at regional 

and mode of living levels (Omer, 2018) 

  

3. Data and Methods 

3.1 Data  

Data obtained from two Labor forces Migration House- hold Surveys collected by the Ministry of 

Manpower for the years 1996 and 2011. The data is very comprehensive encompassing information on 

labor market employment, incomes from wages, agriculture and livestock, non-agriculture activities, 



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real estate, land rent, remittances and subsidies. To eliminate the effects of money value changes during 

the period of the study incomes were deflated using 1990 as baseline year, and the corresponding 

Consumer Price Index (CPI) is used as price deflator in adjusting money values in 1996 and 2011, and 

to eliminate the percussions of the currency changing from Pound to Dinar and gain from Dinar to 

Pound as result of National peace agreement 2005 with Sudan People Liberation Army (SPLA).  

3.2 Prosperity Sharing Indicators 

World Bank group in 2013 agreed on two main goals, firstly on the termination of extreme chronic 

poverty (US$1.25) for poverty line, adjusted with purchasing power parity, in the world 2030 and 

secondly to promote shared prosperity in every society. The second goal behind development of simple 

algebraically and easy calculated quintile income as welfare measure (Rosenbalt & McGavock, 2013; 

Basu, 2013). 

The concept of pro-poor growth (used interchangeably with inclusive growth) is about change of 

poverty incidence and inequality changes in the process of economic growth, and whether growth 

benefits the poor segments in society or not .The world bank defines pro-poor growth only if it reduce 

poverty, and that if poor receive only a tiny fraction of total benefits of growth still the process will be 

called pro—poor (Kakwani & Son, 2006; Weisbrot et al., 2001). 

From various definitions of pro-poor growth this paper used, the slope of the per capita share of bottom 

40%, with respect to overall per capita. Furthermore, shared prosperity indicator will be applied to the 

above mentioned data. 

The specification of whether growth is good for poor people on not, can be expressed in the following 

terms. 

  

This slope of the relationship between average incomes of poorest quintiles and the overall average 

incomes should be very close to and not significantly different from one if growth is good for poorest 

people (Dollar et al., 2013). 

The concept of quintile income, which this study exposed to, emanated from Rawlsian notion which 

emphasize the importance of promoting the welfare of the least fortune members of the society (20% 

bottom), it can be compared to macroeconomic per capita income in developing countries, Basu 

preferred to place the cut-off at bottom 40% since the most poorest people located in bottom 40%, 

Sudan is one of good example the poverty head count 2009 was 47%. Some people criticized the 

bottom 40 % cut-off for it neglecting inequality, but since overall population forced in poorest 40%, the 

mentioned cut-off would not ignore the above altogether, for instance if the poorest 40% incomes 

improved due to the government intervention, the original above cut–off would fall below 

mechanically into public policy focus (Basu, 2013; Omer, 2018). 

Another weakness of the bottom 40% as shared prosperity indicator, if for example two societies have 



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their bottom 40% quintile connected or cross shares, by shared prosperity the two are identical in terms 

of income distribution, but in view of the Lorenz curve dominance the society with dominating Lorenz 

curve has better income distribution, still the shared prosperity is an only goal for the nation to pursue 

if not another problem appear (Basu, 2013).  

Though this paper is not going to engage directly in the discussion of formal derivation and to approach 

the axiomatic of the prosperity share welfare measure, one have briefly to mention the three most 

important traits of the shared measure: (i) SP (x) is complete transitive ordering of set x of all possible 

vector x; (ii) SP(x) meets the criteria of the anonymity, in the sense that two countries with same 

income vector, but income randomly distributed across the people then the two countries have the same 

SP(x) value; (iii) also the Shared Prosperity Indicator (SPI) satisfying weak Pareto principle if every 

individual income rises then society is considered better off. Basu argued that SPI may not meet the 

weak transfer axiom, especially if transfer from rich in bottom 40% of the distribution to poor one 

within bottom 40 % (Rosenblatt & J McGavock, 2013). The shared prosperity Indicator is:- 

 = [(s(x))/0.4)*Y t+1- ((s(x))/0.4)*Y t]/ [((s(x))/0.4)*Y t]            (2) 

The simplified standard way of writing the percentage change is: 

 

Equation (3) represents simple algebraic formula that signalizes the role of economic growth in the 

long run, and its positive effects on the share of the bottom quintiles 40% (Rosenblatt & McGavock, 

2013). 

3.2.1 The Shares within the Shares 

In other words how incomes distributed within top income group, with figures between two brackets to 

show the income shares proportionate to their share of population size. This method covering different 

percentiles, may range for more than the three percentiles, but this study for simplicity will confined to 

the three ones which include 1%, 0.05% and 0.01%. Moreover, this method is meant to detect whether 

income is polarized in the higher income plateau or not (Atkinson, 2011). 

3.2.2 Compound Annual growth Rate (CAGR). 

,  

CAGR is another method to be used to, as an alternative to compare between the bottom quintile 

income (40% 20%) to figure out whether it captured the growth of overall per capita, or top quintile (as 

top 10% as in this paper), another usage of the CAGR as method to predict by how much the bottom 

quintile income has to grow to capture the target, the overall per capita or the top10% income as in this 

study, notably in calculation of warranted quintile income in the end year, then to know by how much 

(percentage) the quintile income has to grow to capture the target.  

Whereas: 



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BV = Beginning Value. 

EV = End Value. 

n = number of years. 

 

4. Results 

This section is intended to demonstrate the empirical findings of the study on extent of the 

disproportionate distribution of economic growth benefits between the top quintile (Top 10% ) and 

bottom quintiles (bottom 20% and 40%) and the degree of inequality in Sudan during the period of 

study, at national, regions and by mode of living, levels. 

Table (1) presents the following findings: at national level in 1996 the share of top 10%is fourteen 

times, more than the tow times of bottom 40% and middle group, respectively; in 2011 the share of top 

10%is six times the share of bottom 40%, and equal to 1.5 times points of the middle income group. 

Furthermore in 2011 the bottom 40% increased by 4.4 point percentage, and middle income group 

increased by 5.3 point percentage, all these increases came at expense of the share of the top 10% 

which decreased by 9.73 point percentages in the same year. The picture will be look different if one 

considered the distribution of shares percentages within bottom 40% and middle income group, for 

more details see (Omer, 2018). 

Urban sector in 1996 resembled the same distribution of national one in the same year, while in 2011 

the share of the top 10% decreased significantly, and the middle income group share increased by more 

than its previous share by more than 20 point percentage. For rural sector the picture is entirely 

different, the share of the top 10% is almost eight times, and more than ten times of bottom 40% in 

1996 and 2011, respectively. The stark observation is the share of middle group is decreased by eight 

point’s percentage in 2011 than its share in1996, while for the top 10% in 2011 increased by more than 

eight points percentages than initial level 1996, this increase came at expense of the share of middle 

income group. Another important observation is that the share of the top 10% at national and by mode 

of living is more than 53% except for urban in 2011 which is 36.10%. 

Another important facets of analysis is reflected by different income inequality measures such as Gini 

coefficient, and Palma ratio to be supported by coefficient of variation –CV-(standard deviation divided 

by the mean) and this last measure reflect whether income distribution is stable or not, in case of high 

CV, i.e., more than three, it means income is highly unequal distributed. Gini coefficient was calculated 

as 0.73and 0.61 for 1996 and 2011, respectively. While the income inequality decreased by 12 points, 

inequality in Sudan still high if compared to regional and international levels, for more details see 

(Omer, 2018).  

As far as mode of living is concerned, the findings revealed that the gini coefficient for the urban is 

higher than rural ones in 1996, but the picture is totally reversed in 2011, theoretically people move 

from rural areas with low wage and low income inequality to the high wage and high income unequal 

urban (Kuznets, 19955). These results bolstered by the values of the CV, that to say income is highly 



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unequally distributed. 

As Palma (2006, 2011) which refers to middle income as 50% income receivers, without indulge in 

income as proper measure of middle class size. The table showed the fact that income share of middle 

income group is less than 50% for all findings except for urban sector in 2011 which is more than 50%, 

one can conclude that the values of Palma ratio is higher by the standard international findings, again 

this revealed that income distribution is highly unequal, for further information see (Omer, 2018; Omer 

& Maglad, 2021).  

 

Table 1. Income Shares of Bottom 40%, Middle Income Group and Inequality Measures for the 

National and Mode of Living by Percentage 

Income groups A 

National  

1996  

B 

National  

2011 

C 

Urban  

1996 2011 

D 

Rural  

1996 2011 

Bottom 40% 4.564 8.93 5.17 10.78 6.17 6.06 

Middle group 31.03 36.43 30.9 53.12 40.27 32.67 

Top 10 % 64.37 54.64 64.74 36.10 53.56 61.27 

CV  3.83 2.7 3.02 1.62 3.4 26.1  

Gini Coefficient 0.71 0.61 0.72 0.46 0.64 0.67 

Palma ratio 14.1 6.12 12.51 3.34 8.72 10.11 

Source: Owen calculation Note; for calculation of Gini coefficient and Palma ratio see (Omer, 2018). 

 

Table 2 presents in columns 2-4 the relative inequality income shares percentages of the poorest 60 % 

and richest 20% and the ratio richest 20% to poorest 60%. The share of the poorest 60% is almost 11% 

in 1996, and then increased almost 20% in 2011. On the other hand the share of the share 20 % was 

76.43% in 1996 and 65.34% in 2011; the ratios of the percentage of richest 20%to poorest 60% are 

7.07 times and 3.3 times for 1996 and 2011, respectively. Though the ratio of richest 20% declined in 

2011 to 65.345 yet it is by any means is very high. By contrast the earrings of top richest 20% in one 

month and half month and four months are equal income earnings of poorest 60% in whole year in 

1996 and 2011, respectively. Columns 5-7 of the table include the shares within shares. In other words, 

the paper question how incomes were distributed within the top income group from 1% to 0.01% 

parcels? The figures between the two brackets are the income shares proportionate to its share of 

population size. The share of the top 1%, top 0.05% and top 0.01% and their share to their 

proportionate population size for 1996 are as following: (6.56%: 65.65 times); (4.9%: 98 times) and 

(2.46%: 246 times) for the three parcel, respectively. While for 2011, the relative share and 

proportionate size came as following: (30.55%; 305.5 times); (29.77%: 5945.4 times) and (18.29%: 

1829 times) for 1%; 0.05% and 0.01, respectively. Looking to the table one can observed upward 



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increase trend of the top income parcels over the period of the study. This suggests a high degree of 

income concentration in the hands of top 10% and particularly the top 0.01% parcel. Moreover, the 

table findings indicated increase of income concentration within top group in 2011 is higher than 1996 

one, put in consideration relative population size of each parcel. 

 

Table 2. Relative Inequality Income Shares % 

Year 

A 

Poorest 60% 

 

B 

Richest 20% 

 

C 

Ratio 

 A/B 

 

D 

Top 

1% 

F 

Top 

0.05% 

 

E 

Top 

0.01 

 

1996 10.854 76.03 7.00 
6.56 

(65.60) 

4.9 

(98) 

2.46 

(246) 

2011 19.567 65.345 3.3 
30.55 

(305.5) 

29.77 

(595.4) 

18.29 

(1829) 

Source: Own calculation, estimates of per capita of household income expressed in constant 1990 terms. 

Calculation. 

 

Table 3, row (1) presents the results of the relationship between averages income of the bottom 40% 

and the average overall income, which is used here instead of GDP as indicator of economic growth, 

for the total sample, regions and rural–urban sectors for the period 2011-1996.  

The slopes of the relationship between growth rates are almost between 0.1 and 0.2 which are different 

significantly from one for the national, regions and mode of living for the entire period of study (for 

regions’ results see annex one), implying that prosperity is not shared by the poorest group, namely the 

bottom 40%. This result is in agreement with Dollar and Kray (2013) observation that say growth may 

not alone be good for the poor if not connected with deliberate income distributional policies such as 

progressive taxes and social spending. 

Moreover, the anti-poor growth is indicated by using equation (3) to calculate percentage change in the 

bottom 40% share (it is not part of the table). The results of percentage change in the bottom 40% for 

the whole sample was -46.9% for 2011-1996. For the same period, the percentage change of bottom 

40% was -35% and -0.71% for urban and rural sectors, respectively. Thus these findings implied that 

the benefits of growth are not favouring the bottom 40%.  

To continue with Table 3, row (2) the prosperity share measure which study how income of bottom 

40% grow from one period to the next, this table showed the following findings, the shared prosperity 

measure is negative and almost 1%. Though the decrease of the per capita is less than 1%, this result 

confirmed the results of the previous two tables the share of poorest 40% is falling behind the rest, or 



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not catch up the incomes, of the middle income group and the top 10%, though the results is not agreed 

with results of Palma regarding the decrease shares of bottom 40%, going the top 10%, yet Plama ratio 

is by all means is higher, internationally wise (Omer, 2018). 

Despite the fact Sudan during twenties of current century achieved economic growth probably 7%, the 

share of the bottom 40% is not concomitant with overall economic growth –implied that, the shared 

prosperity associated with idea of polarization in the Sudan society—one can concluded from this 

result that economic growth alone can’t reduce chronic poverty and alleviated the discreditable 

inequality. In row (3)—A, one can observed that the bottom 40% income appeared higher than overall 

income mean for both national and mode of living, as if symptom of equalitarian or inclusive growth, 

but as in row (3) – B, if inequality of income distribution is considered as shown by previous measures, 

by taken the mean of income top 10 % as alternative to overall mean income, the lacking of quintile 

income of bottom 40% is starkly obvious. Furthermore, if one take Rawlsian bottom 20% - minimum 

percentage principle—for two purposes, the first one to verify the inequality of income distribution 

during the period of the study which founded as overall mean per capita is 1.32 while the income of 

bottom 20% quintile equal to 1.04, i.e., the bottom 20% quintile income failed to catch up with overall 

growth. Secondly, the bottom 20% quintile is easiest for calculation of desired or warranted annual 

compound growth rate, which founded to be equal to 1.61 as calculated in annex (3) section (ii), if one 

subtract 1.61 from one, the result is 61% which means that, if the bottom 20% income had grown by 

61% annually it could have been caught the desired (warranted) income in 2011. 

 

Table 3. Measurements Inclusive Growth, Shared Prosperity and CAGR 

Measures  A 

National  

B 

Urban  

C 

Rural 

Row (1)Slope of relationship between bottom 40% and overall Average 

income 

  

0.09 

 

0.07 

 

0.13 

Row (2)Percentage of shared prosperity -0.94 -0.99 -0.92 

Row (3)* – (A) compound Annual growth rate (CAGR) 

Mean (overall mean) 

Quintile ( income of bottom 40% ) 

Row 3(B) CAGR 

Mean per capita of top 10% 

Quintile income of bottom 40  

 

1.20 

1.30 

 

1.40 

1.02 

 

0.96 

0.04 

 

1.41 

1.01 

 

1.01 

1.11 

 

1.25 

0.81 

 

This table compiled from annexes at the end of the paper. 

 

 



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5. Discussion 

Different methods of prosperity sharing such as; the slope relationship between bottom 40% per capita 

income and overall per capita, as indicator of whether growth is good for poor people or not, the shared 

prosperity indicator formulas (2) and (3) in the text are highlighted the trend of economic growth in the 

long run an its positive effect on the bottom 40% income share; the shares within the shares, namely the 

top parcels of the top 10% income group, compared proportionately to each share population size, to 

detect whether income is polarized / concentrated in the hands on higher income group or not? 

Last not the least, compound annual growth rate used to check whether the poorest income grow by the 

same of overall per capita or not, in addition to that CAGR is employed as forecasting method. All 

these measures are applied to data maintained from two labor force migration households’ surveys 

collected by Ministry of Manpower; with sample size 3288 and 11182 households for years 1996 and 

2011, respectively. The two surveys are similarly designed, comprehensive national data of 

employment, wages and salaries and other sources of incomes, the coverage of the two surveys is 

limited to northern 16 states which regrouped in to six regions, the south before its independence, was 

excluded due to the long persistence civil war. To eliminate the effects of money value changes during 

the period of the study, the prices of 1990 was considered as base line year and the corresponding 

Consumer Price Index (CPI) is used in adjusting money values in 1996 and 2011.  

Though Sudan during the period of the study witnessed unprecedented economic growth rate probably 

about 7%, and led to slight improvement of inequality, as Gini ratio indicated a decrease from 0.71 to 

0.6 yet Sudan is classified is highly income (Omer, 2018). The slight improvement income of the 20% 

and 40% bottom have had not eliminate poverty or mitigate income inequality. The measures employed 

tin this paper the slope relationship (1) and shared prosperity indicator (2), (3) formulas, the share 

within the share, and in conclusion the CARG, all together implied that the benefits of growth is 

enjoyed by the bottom 40%, and these shared prosperity measures associated with idea of polarization 

in the Sudan society.  

In addition, the compound annual economic growth revealed that if the income of the bottom 20% 

income had grown by 61% annually it could have been caught the desired (warranted) income in 2011.  

Moreover, one can make comment on the meagre improvement of the bottom 40 %, it can be attributed 

to the exploration and export of oil and gold, and expansive emergence of informal sector 

predominantly in services sector.  

One can wrap up, that economic growth without government redistribution intervention policies is not 

conducive to eradicate chronic extreme poverty and to improve income inequality in Sudan. As matter 

of policy implications, after empirical evidence of increase of economic growth in terms of growth of 

overall per capita income, and the lack of the bottom 40% per capita behind, the trickle down is myth 

needed to be revised to meet the requirements of reduction of poverty and to mitigate income 

inequality .Trade openness is important but should be in line with needs of most poorest segments of 

society, private sector should be encouraged to be employment friendly. For government should 



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provide investment for infrastructure, enforcement rule of law and viable social institutions, i.e. the 

government have to provide social services- education and health and enhance stable macro-economic 

environment The pattern of economic growth instead of being depend on natural gifts- oil and gold, to 

base on productive one .Other distributive policies such progressive tax may be considered, and rural 

development policy should has to be forged to address poverty and inequality in rural sector.  

In addition to that the household’s surveys must be carried in regular convergent periods to avail for the 

researchers’ up to date information to be used by researchers to lend their immediate findings to policy 

makers.  

 

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Annex (1) 

Table 1. The Relationship between Average Incomes of Bottom 40% and the Overall Average 

Incomes, by Regions and Mode of Living 

 National –Regions 

 2011 –1996 

 A 

Change of overall 

Average Incomes 

  

 B 

Growth Average of Bottom 

40% Income  

 C 

 Slope of the  

 Relationship  

B/ A 

 National   -73493  -6815.1  0.09 

 Eastern   -60411  -6645.21 0.11 

 Northern   -38256  -8449.4  0.22 

 Khartoum   -265420  -31846  0.12 

 Central   -54776  -8960.2  0.16 

 Kordfan   -29427  -3855.5  0.13 

 Darfur   -28584  -2176.9  0.08 

 Urban   -166202  -11077.6  0.07 

 Rural   -30607  -3916.6  0.13 

All estimates of Income Shares in the table expressed in constant terms. 

Source: Own calculations. 

 

Annex (2) 

Table 2. Shared Prosperity Indicator 

National  

And Mode of living  

 A 

Per capita income of  

Bottom 40% 

 B 

Overall per –capita 

Income  

 

Percentage of SP 

National 

1996 

2011 

 

9525 

3575 

 

88418 

14925 

 

- 0.94 

Rural 

1996 

 

7116 

 

45548 

  

- 0.92 



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Published by SCHOLINK INC. 

2011 10766 2298.2 

 

Urban 

1996 

2011 

 

23480 

10723 

 

181083 

3872 

  

- 0.99 

All estimates of Income Shares in the table expressed in constant terms. 

Source: Own calculations. 

 

Annex 3: 

(i)  

Whereas: 

BV = Beginning Value 

EV = End Value. 

n = number of years 

(ii) Y1 = 1996 

Y2 = 2011 

N = population of bottom 20%  

M = overall mean  

 Y = N. M 

 Y1 = 676 × 42290899 = 2900647724 

 Y2 = 2236× 7463613 = 16688638668 

To get the fruit of growth one has to follow the coming steps 

Δ = Y2 – Y1 = 13787990944,  

If fruit of growth proportionately distributed between the five quintiles then, 

 =  = 2757598189, 

The desired quintile income of 2011= the fruit of growth + quintile income of 1996  

2757598189+ 2900647724 = 5658245913 

 Desired  = 

  = 1.61 

 


