Over the last decade the functional relationship between income and gender development has become one of the most debated issues in policy making areas and in the social sciences. International agencies such as the International Labour Organization (ILO), the United Nations (UN) and the World Bank are attempting to better understand the growth impact on alternative gender development strategies. A crucial concern of this effort is to gain proper knowledge about economic growth impact on gender inequalities.1) In this paper we focus on the link between a country’s degree of gender disparity in different dimension and its income level. Gender development gap may have adverse impacts on a number of valuable development goals.2) This paper envisages analyzing the validity of existing literatures on gender equality and the objective is to establish a casual relationship between the income component of the index to the gender related development and how far income level of the country can influence the existing gender gap of the country.
1. INTRODUCTION The United Nation Development Program (UNDP)
brought people to the centre of development by emphasizing human
development as a process of enlarging peoples choices. People are
both agents and beneficiaries of change. This notion has totally
dethroned GNP maximization and reliance on per capita income as the
only yardstick for measuring development. Thus GNP maximization
becomes a necessary but not sufficient element for human
development.Human Development Index (HDI) - HDI was introduced in
UNDP to measure human development for 174 developed and developing
countries. It focuses on 3 critical dimensions to human
development: longevity, knowledge and a decent standard of living.
This index is now widely used in the analysis of socioeconomic
development. Although the use of composite indexes has been
criticized HDI does simplify a complex reality and offers important
policy insights.
Gender related Development index (GDI) - Women represent half or
more of the population of any given country. How do they fare in
human development? In 1995 UNDP introduced a second measure of
human development that takes into account differences in
achievements between men and women.GDI comprises the same 3 HDI
variables adjusted for gender differences. In no country,
industrial or developing, do women enjoy the same opportunities as
men.
According to World Bank, investing in woman is the most
beneficial investment a developing country can undertake. Gender
equality is recognized as a highly desirable developmental goal. In
the developing world, woman lags behind men in every aspect of
economic life. Womens lower shares in education, labour force and
income define their low status, inflecting high opportunity costs
on their economies in terms of forgone growth and development.
The report constructed a gender- related development index for
130 countries which has spurred efforts to construct a similar
index for Indian states[Prabhu et al,1995;Shiva Kumar 1996]these
attempts, however, must be considered preliminary in view of the
several problems associated with (a)the GDI as a measure of gender
disparities and (b)its calculation.
Inequality between man and woman can be of various kinds. As far
as economic aspects are considered, biases in life expectancy,
education, jurisdiction and professional life are among the suspect
that might deserve closer investigation. However, in every general,
it seems necessary to clarify that inequality in itself does not
necessarily need to be something to be considered as negative.
Nonetheless, it may not be forgotten that gender inequality itself
can well be considered bad and required political counteraction,
regardless of the existence of a link with economic growth. 1.1.
Background of studyThe UNDPs Human Development Report for 1995
focused on gender disparities in development. Education is an
important component of opportunities and empowerment. A number of
empirical studies find that increases in womens education boost
their wages and that returns to education for women are frequently
larger than the returns to education for men. Empirical evidence
also shows that increases in female education improve human
development outcomes such as child survival, health and schooling;
the impacts on these outcomes are larger for a given increase in
womens education than for an equal increase in mens education
(World Bank 2001, Schultz 2002, Strauss and Thomas 1995, King and
Hill, 1993).
Over the last several decades, gender issues have attained
increased prominence in the debates over development policy. There
is a growing body of evidence and experience linking gender
awareness in policy and projects to equitable, efficient and
sustainable outcomes in development. However, these links are still
not widely understood nor have these lessons been fully integrated
by donors or national policy makers.
Day by day each and every nation is growing. Some of them are
growing very fast and some are not. With this growing factor the
inequality between man and woman is also changing. This change can
be indicated by an indicator, known as Gender Development Index
(GDI).
The Gender Development Index (GDI) is a composite indicator that
measures the development of states according to the standard of
living in a country. Although standard of living mainly reflected
by high level of per capita income, but whether the link works
strongly or not is a question of debate. 1.2. ObjectivesOver the
last decade the functional relationship between income and gender
development has become one of the most debated issues in policy
making areas and in the social sciences. International agencies
such as the International Labour Organization (ILO), the United
Nations (UN) and the World Bank are attempting to better understand
the growth impact on alternative gender development strategies. A
crucial concern of this effort is to gain proper knowledge about
economic growth impact on gender inequalities.
1) In this paper we focus on the link between a countrys degree
of gender disparity in different dimension and its income level.
Gender development gap may have adverse impacts on a number of
valuable development goals.
2) This paper envisages analyzing the validity of existing
literatures on gender equality and the objective is to establish a
casual relationship between the income component of the index to
the gender related development and how far income level of the
country can influence the existing gender gap of the country.
2. SURVEY OF LITERATURE1) It is a fair generalization to say
that the relative status of women is poor in the developing world,
compared to developed countries. We treat gender inequality as an
endogenous variable and show that it can be explained to a
considerable extent by religious preference, regional factors, and
civil freedom. For some of these variables, the direction of the
effect depends on the particular measure of inequality (POLICY
RESEARCH REPORT ON GENDER AND DEVELOPMENT, David Dollar, Roberta
Gatti, 1999).2) The opportunity cost of women's time as well as the
bargaining power of women to be important determinants of the
fertility rate. Greater female education, and particularly lower
gender inequality in education, is thus likely to lead to reduced
fertility. (POLICY RESEARCH REPORT ON GENDER AND DEVELOPMENT,
Stephan Klasen, 1999)
3) From the regressions applied in this paper, the hypothesis
that a high per capita income is associated with less gender
inequality can be supported Similar to Dollar & Gatti, it was
found that inequality in education is strongly and negatively
associated with high GNP per capita. However, the factor of
inequality in education did not turn out to be the most influential
one when predicting per-capita income levels (The Influence of
Gender Inequality on Economic Growth, David Gumbel, 2004).4) The
effect on growth of increased gender equality of opportunity has
received far more attention than either equality of voice or
equality under the law. Equality of opportunity in education has
received particular attention, for two simple reasons. First,
educationand, more broadly human capitalis easily incorporated into
two frequently-used econometric models of economic growth: the
augmented Solow model and endogenous growth models.28 Second,
educational inequalities are both easily measurable and these
measures are widely available (Gender Equality, Poverty and
Economic Growth, BY: Andrew Morrison, Dhushyanth Raju, Nistha
Sinha, The World Bank Gender and Development Group Poverty
Reduction and Economic Management Network September 2007)5) Closing
the gap between male and female employment rates would boost GDP
significantly. Were Italian female employment to rise to the level
of male employment, then the level of GDP (assuming everything else
equal) would be boosted by 21%. For Spain, GDP would be 19% higher,
Japan 16%, the Eurozone 13%, Germany 9%, France 9%, the US 9%, the
UK 8%, Denmark 5% and Sweden 3% (Gender Inequality, Growth and
Global ageing, Kevin Daly, 2007).6) In recent years gender has
become a significant part of the mainstream discourse on economic
growth and development. Gender perspective has been adopted by the
international organisations such as, World Bank, WTO and IMF in the
formulation of Millennium Development Goals, trade policies and
macroeconomic structural Programmes (GENDER INEQUALITY, ECONOMIC
DEVELOPMENT, AND GLOBALIZATION: A STATE LEVEL ANALYSIS OF INDIA,
Rashmi Umesh Arora, 2012) 3. SECTIONTo measure Gender Development
Index we need to understand the computation of HDI. We have to
collect the basic knowledge about the relationship between HDI and
GDI. Gender related HDI is known as GDI. In other words the GDI is
the HDI discounted for gender inequality. Gender-related
Development Index (GDI), is not only measure the achievement in the
same basic capabilities as the HDI does, but takes note of
inequality in achievement between men and women. In early days HDI
was the main ingredient to measure the income proportion of the
economy but it was not clear concept of gender biasness with
respect to their income. To measure gender wise contribution of the
economy economist introduced a new component called GDI. 3.1.
METHODOLOGYIn Gender related development Index we have to calculate
three major component i.e. life expectancy, educational attainment,
and income. These three component are separately calculated and
then combined in an equal-sensitive way.The value of is the size of
the penalty for gender inequality. The larger the value, the more
heavily a society is penalized for having inequalities. If = 0,
gender inequality is not penalized (in this case the GDI would have
the same value as the HDI). As increases towards infinity, more and
more weight is given to the lesser achieving group. The value 2 is
used in calculating the GDI. This value places a moderate penalty
on gender inequality in achievement. When = 0, the above formula
becomes the arithmetic mean weighted by female and male populations
shares, and the resulting index should be equal to the component
index for the whole population as used in HDI. When, as in the
calculations for the GDI, = 2, the above formula becomes the
harmonic mean weighted by the population shares (UNDP 1995: 73)1.
Any difference between the female index and the male index
regardless of its direction is penalized in the ED Index. This is
to say that for all three components the Equally Distributed
formula can only impose a penalty, not award a bonus.
We assume , as the parameter of inequality aversion, which is
equal to 2. Let N be the total population. NM is the total number
of male and NF is the total number of female in the whole
population.Equally distributed Life Expectancy index:
[{(NM/N)LEIM}^(1-)+{(NF/N)LEIF}^(1-)]^1/(1-)=A (say)
LEIM = Life Expectancy Index of male
LEIF= Life Expectancy of female
Equally distributed Educational Attainment Index:
[{(NM/N)EAIM}^(1-)+{(NF/N)EAIF}^(1-)]^1/(1-)=B (say)
EAIM=Educational Attainment Index of male
EAIF= Educational Attainment Index of female
Equally distributed proportional income
[{(NM/N)PYM}^(1-)+{(NF/N)PYF}^(1-)]^1/(1-)=K (say)
PYM=Proportional Income of male
PYF= Proportional Income of female
Adjusted real GDP per capita (discounted for gender
inequality):
K x Average Real GDP per capita= $KEquality distributed Income
Index:
($K-$100)/($5448-$100)=C
$100 is the minimum value and $5448 is the maximum value of
adjusted real GDP.
Gender-Related Development Index (GDI):
(A+B+C)/3
GDI is the average of Equally Distributed Life Expectancy Index,
Equally Distributed Educational Attainment Index and Equally
Distributed Income Index. 3.2. DATA ANALYSISMajor finding
Transition of position in terms of HUMAN and GENDER RELATED
INDEX
Diagram 1: Position of countries with respect to their Income
Index and HDI in the year 1980
Source: UNDP Report 2014
i) In the beginning of 20th century, India was standing in
relatively lower position in comparison with China & Kenya,
Kenya has a higher value of income index and HDI than other two.
From 1980 to 1990 we get a better picture of India where both
income index and HDI values increases but still India is lagging
behind the other two, but distances have narrowed down.Diagram 2:
Position of countries with respect to their Income Index and HDI in
the year 1990
Source: UNDP Report 2014
ii) Interestingly, another feature can be found by analyzing the
above diagrams that initially countries all over the world are
scattered in a more arbitrary way. But after one decade the
scatterness among the countries has been reduced to a larger extent
that signifies that countries are started to converge in terms of
HDI.
iii) In the year 2000, it can be seen from the diagram below
that India has progressed in account of HDI and surpassed Kenya.
Kenya is almost in a static position and its value of income index
is almost stagnant since 1980s while China registered a significant
improvement in HDI.Diagram 3: Position of countries with respect to
their Income Index and HDI in the year 2000
Source: UNDP Report 2014
iv) In 2010, India and China both improved in HDI as well as in
terms of income index but China moves faster in the race of human
development than India which translated into higher gap between
India and China position. 0ne point should be noted that Kenya has
shown a marginal increment in the value of HDI, but income index
remains more or less same. That means Kenya is lagging behind than
other two due to less improvement in income sphere.Diagram 4:
Position of countries with respect to their Income Index and HDI in
the year 2010
Source: UNDP Report 2014
Diagram 5: Position of countries with respect to their Income
Index and HDI in the year 2013
Source: UNDP Report 2014
v) From the early years, it can be viewed that countries are
coming closer to each other i.e. the arbitrariness of the scatter
plot has been reduced significantly. Positive concern for human
development all over the world is depicting in this above diagrams.
Almost every country has shown positive change in terms of human
development. vi) Another natural causal relationship is evident
from the diagrams that increase in per capita income of a country
i.e. rise in income index and increase in HDI value of that country
has a clear positive relation.
vii) In the recent year, India has improved its position but
Chinas progress towards human development is praiseworthy whereas
Kenya is far lagged behind than other two due to almost stagnant
income index. In spite of the fact that in the beginning Kenya was
the 1st rank holder among these three countries. After discussing
about human development, a decent picture of improvement can be
found. Now, lets shift the focus towards gender development. Does
income play such significant role in GDI as in HDI? Does human
development necessarily translated into gender development? The
answer is not that satisfactory
Diagram 6: Position of countries with respect to their income
Index and GDI in the year 2013
Source: UNDP Report 2014
viii) In the above diagram, it is evident that countries all
over the world have extreme difference in terms of gender
development. Arbitrariness in scatter plot is quite high than that
of initial state of HDI calculation. Here, Kenya having much lesser
value of income index has done well in GDI compared to India. China
is in win-win state both in terms of HDI & GDI. Some countries
with high value of income index have higher value of GDI. Although
it cannot be generalized that income index and GDI share a direct
relationship as in the case of HDI. So now I want to investigate
whether there lies any positive relation between a countrys level
of national income and its value of GDI. The diagram below depicts
relationship between GNI per capita in PPP (Constant 2011
International $) .i.e. Aggregate income of an economy generated by
its production and its ownership of factors of production, less the
incomes paid for the use of factors of production owned by the rest
of the world, converted to international dollars using PPP rates,
divided by midyear population.
Diagram 7: Position of countries with respect to their GNI per
capita and GDI in the year 2013
Source: UNDP Report 2014
ix) Above figure shows no such direct relation between level of
NI and GDI value as in the case of HDI that conclude the very fact
that higher per capita do not reflect in GDI value . There must be
some added efforts instead of growth that would implicate better
gender development. Moreover, India has to go a long way to achieve
high GDI value; in spite of having a decent growth rate its
performance towards gender development is not satisfactory at
all.
Diagram8: Position of countries with respect to their GNI per
capita and HDI in the year 2013
Source: UNDP Report 2014
Here, relation between level of national income and HDI value
have been plotted for the purpose of comparison. Figure shows vivid
difference in relation. In case of HDI countries are close or to
each other showing a clear positive relation.
From the above discussion it is clear that high level of GNI
trigger better performance In HDI, but high value income index do
not necessarily translate into better performance in GDI because
bad performance in other two indices other than income index may
discount the good effect of income index alone, as a result no
direct relation between GDI and income level is found. In this
sphere we need policy prescription for supplementing income growth
that would be more viable in future towards the progress of
development in our country. Although many steps are taken in this
context, but recent data reveals that much has to be done in
future.After analysing the global scenario the paper focus on
Gender Inequality and the level of development of the countries. I
have chosen China as a representative of developed countries and
Kenya as a representative of under developed counterpart of the
world. Now India has been taken to compare with these two countries
to access the position of India with others. Being a developing
country India has surpassed the takeoff stage of growth. Now this
growth how influenced the level of Human Development as well as
Gender Development that need to be addressed.
Table 1: Human Development Index (HDI) Trends, 1980-2013
YEARCHINAINDIA
KENYA
19800.4230.3690.446
19900.5020.4310.471
20000.5910.4830.455
20050.6450.5270.479
20080.6820.5540.508
20100.7010.5700.522
20110.7100.5810.527
20120.7150.5830.531
20130.7190.5860.535
SOURCE: UNDP Report 2014
According to UNDP report 2014 on the basis of these HDI trends
all countries are ranked. China is ranked 91, India is ranked 135
and Kenya is ranked 147.
From the development studies we know there are some ranges of
HDI which helps us to make some groups among the countries of the
world with respect to their estimated HDI. The countries whose
estimated HDI is greater than 0.8 (HDI>0.799) belongs to very
high HDI group. The countries whose HDI is in between 0.699 to
0.799 (0.799-0.699) belongs to high HDI group and countries whose
HDI is in between 0.699 to 0.549 (0.699-0.549) belongs to medium
HDI group and lastly HDI value less than 0.549 are belongs to low
GDI group. From the above table we can observe till 2000 China was
belong to medium HDI group but after that it took off its situation
and came into the high HDI group. Now in case of India till 2000 it
was belong to lowest HDI group but there after it developed itself
and became medium HDI group. Lastly about Kenya till 2005 it was in
lowest HDI group but after the year it took off its HDI position.
Diagram 9: Human Development Index (HDI) TrendsAfter analysing the
growth rate of these three countries, now the trend of HDI can be
analysed. Three countries have done much better since 1980 to the
current period. India was the lowest among these three during 1980
but achieved 2nd rank in 2013. It means India has developed much
faster than Kenya. Kenyas HDI value almost stagnated at around 0.5.
china is obviously done a great job in the course of human
development. It has been shown in the figure that China has
followed upward rising trend in HDI value and ranked 1st among
these three with a high value of HDI around 0.7 in the year
2013.Table 2: GDP growth rate, 1991-2013YEARCHINAINDIAKENYA
19913.841.061.44
19929.185.48-0.80
199314.244.750.35
199413.966.662.63
199513.087.574.41
199610.927.554.15
199710.014.050.47
19989.306.183.29
19997.838.852.31
20007.623.840.60
20018.304.821.00
20029.084.301.10
200310.038.301.50
200410.097.925.10
200511.318.405.80
200611.609.706.40
200713.009.007.00
20089.606.201.60
20099.206.802.60
201010.4010.105.80
20119.206.804.40
20127.703.204.60
20137.703.205.10
SOURCE: Compile from multiple sources
CIA- The world fact bookEuropean commission statisticsTable 3:
Average rate of growth (1991-2003)
CHINAINDIA KENYA
average growth rate9.8778260876.2926093.080435
Interestingly if we want to compare these countries in terms of
their average rate of growth between 1991-2013.The relative ranking
positions of these countries is exactly identical with their
ranking position in terms of HDI. The result also provides an
important insight that income growth contributes much to hold
relatively better position in HDI ranking among the countries of
the world.Diagram10: GDP growth rate, 1991-2013
From the above graph diagram we see that India and Kenya share
almost the same growth rate in the year 1991 where as China is
better off with around 4% of GDP growth rate. After that Kenya and
India has an almost similar trend of growth rates till 2010.
Although India is doing better that Kenya, While China has
experienced high growth rate of 14% in the year 1993 followed by
decrease in growth rate till 2000. After that China recovers
herself and follows moderate growth rate at around 10% on an
average. In the year 2010, India and China experience a slump till
2012. In the current year China has the highest growth rate around
8% followed by Kenya around 5% and India around 3%. Table 4:
Comparison between Human Development Index (HDI) and Gender
development index (GDI)
Country HDI RankGDI Rank
China9149
India135132
Kenya147107
SOURCE: UNDP Report 2014From the above table we can see the
position of these three countries according to their ranking with
respect to HDI & GDI in the basis of world rank. Here is an
interesting situation can be observed i.e. India is above Kenya
according to HDI rank but in case of GDI Kenya is better than
India. At the same time China is better in the both cases.
After talking about the cross country study, the paper wants to
address the global scenario regarding the relationship of income
level and HDI, GDI ranking among the countries i.e. whether higher
level of income really play a vital role for attaining higher value
in HDI & GDI or not. For this purpose Karl Pearsons Correlation
index has been constructed. For that data has been collected for
countries are about their Gross National Product (GNI) per capita
at PPP$(2011) and HDI, GDI values. The following table shows the
value of correlation between HDI, GDI index and GNI per capita
income. These figures vividly represent the significant
differential effect of income on HDI and GDI values which is
earlier proved in cross country comparison. The findings are
suggesting that a country with higher per capita income is more
likely to hold a better position in HDI ranking but in case of GDI
the chance of that particular country to hold a higher index value
is relatively lower as the value of correlation is quite low. The
outcome is very useful in case of policy implication. Table 5:
CorrelationKarl Pearson's correlation index
GNI P.C.I
HDI0.725
GDI 0.449
In this table a glance of job segregation is provided.
Table 6: Gender segregation in field of study: In most
countries, women dominate health and education studies and men
dominate engineering and sciences.
Fraction of countries where
Number of
the field of study is countries
Field of studyFemale dominated %Male dominated %Neutral %Number
of countries
Agriculture3742289
Education8461097
Engineering, manufacturing and construction0100097
Health and welfare8241397
Arts and humanities5563996
Science13682096
Services21592187
Social sciences; business and law23166197
SOURCE: WDR 2012 team estimates based on data from UNESCO
Institute for statiscs.
Diagram 11: Gender segregation
Although this paper is primarily meant to search the
differential impact of income component on HDI and GDI. But as this
difference is already shown and it is also backed up by statistical
measure in the above sections, some possible reasons for this
underlying difference are cited:
In GDI the method used to estimate female and male earned
incomes ignores the existence of self-employment; biases in women
and mens access to full-time paid work; and the complex nature of
intrahousehold distribution of money, goods, and labour. (Stanton
2007) which is not posses any problem in case of HDI as per capita
income of the countries is quite accessible. A general critique of
GDIs data availability and reliability has been provided by Bardhan
and Klasen (1999).The data used by the UNDP to estimate
gender-specific incomes are not in fact available for many
countries. HDR 2005 (UNDP 2005: 346) This types of criticisms are
not provided for HDI. As a result this could be a possible
explanation for the differential impact of income. Unlike the other
components in GDI, gendered income is a rough estimate. Several
critiques have questioned the appropriateness of using
non-agricultural wages together with labour force participation as
gender weights for GDP per capita.2All these reasons reflect the
same idea that unlike HDI in the case of GDI income component does
not serve as an appropriate measure to take into account women and
mens standard of living. As a result income component is having
lesser command over GDI as in case of HDI. 4. ConclusionFrom the
above analysis, we can conclude that although the countries have
progressed in terms of human development till they need to go long
in the way of gender development. As we find that income
sensitivity of GDI is lower than that of HDI. So income growth
alone cannot play a significant role to improve the situation of
existing gender disparity.
Moreover, from the last figure we can easily remark that women
are skewed in some economic activities and their proportion in
comparison to male counterpart is negligible mainly in case of
engineering and manufacturing. Thus there are segregation of work
i.e. some are womens job and mens job.
When we compare the three countries which is India, China and
Kenya an interesting point to be noted that Kenya and India both
started from a similar level of development but Kenya in recent
times lagged behind the other two. China has secured praise worthy
position both in context of HDI and GDI.
Whereas India is the least performing country among there three
in terms GDI. So it is a matter of grave concern that India should
emphasised on human participation in economic activity and
empowerment so as to move forward in the path of gender
development. China can be a good example to follow. India has taken
some steps to reduce the gender gap. The calculation of correlation
index and large difference in their values statistically
established the fact that income component has greater contribution
towards HDI than GDI. Higher level of per capita income leads a
country towards higher rank in HDI with much larger probability
than that of in case of GDI.
Therefore here arises crucial need of policy prescription to
promote gender parity and development.4.1. Policy PrescriptionThe
Human Development Index (HDI) introduced by UNDP in 1990 is a
simple average of three dimension indices that measure average
achievements in a country with regard to A long and healthy life.
But Gender gaps are pervasive in all walks of economic life. The
goals of human development cannot be achieved without the
development and empowerment of women. However, the reality that
woman faces disparities in access to and control over resources.
Thus there is need to include gender sensitive measures of human
development. Therefore, in 1995, the UNDP introduced a
Gender-related Development Index (GDI). The Gender-related
Development Index adjusts the average achievements in the same
three dimensions that are captured in the HDI, to account for the
inequalities between men and women. The construction of index is
not enough to create proper environment for gender development
unless some policies are framed by the central authorities of the
countries.
The paper finding reveals that a nation does not have to be
affluent to treat women and men equally. Thus promoting more women
to leadership roles and creating environments more conducive to
womens input makes good sense from the perspective of business,
politics and ethics. Many nation are following some important
guidelines (such as MDG)3 to narrow down the gender gap. An OECD
country focuses on how to close these gender gaps under four broad
headings: 1) Gender equality, social norms and public policies; and
gender equality in 2) education; 3) employment and 4)
entrepreneurship. In USA some positive action has been taken in the
same line by raising child care support, minimum wage, breaking
occupational segregation etc.
India also started to walk in the path of gender equality but
the efforts are not creating good results rather the gap is
widening and all the indicators have been deteriorating over a
period of time [Swarna S. Vepa(2007)]. Thus gender discrimination
continues to be an enormous problem within Indian society. Women
receive little schooling, strong "son preference" and suffer from
unfair and biased inheritance and divorce laws. These laws prevent
women from accumulating substantial financial assets, making it
difficult for women to establish their own security and
autonomy.
To reduce the existing gender gap by 2015 as an objective of
MDG, the task force has identified seven strategic policies to be
followed by nations of the world.
1. Strengthen opportunities for post-primary education for girls
while simultaneously meeting commitments to universal primary
education.
2. Guarantee sexual and reproductive health and rights.
3. Invest in infrastructure to reduce womens and girls time
burdens.
4. Guarantee womens and girls property and inheritance
rights.
5. Eliminate gender inequality in employment by decreasing
womens reliance on informal employment, closing gender gaps in
earnings, and reducing occupational segregation.
6. Increase womens share of seats in national parliaments and
local governmental bodies.
7. Combat violence against girls and women.
These guidelines need to translate into development policy and
practice at the scale required to bring about fundamental
transformation in the distribution of power, opportunity, and
outcomes for both women and men. The policy recommendations made in
the above can pave the way toward an equal world.
4.2. LimitationThe paper mainly indicated towards the fact that
income level or its growth has differential treatment on HDI and
GDI. The states of relationships are presented by the value of
correlation index. Many researches [Dollar, Gatti et al,] have
pointed out that growth and HDI has close and significant relation
by applying regression analysis. Although the paper has not applied
regression but the relationship is also evident from correlation
index.The paper only concentrated on single component of HDI and
GDI. But other factors like education have also a lot of say in
determining HDI and GDI which is not checked in this paper. The
role of other determinants of development is not stated
properly.
Moreover in case of cross country comparison the countries have
been chosen a bit arbitrarily for the sake of convenience and for
fulfilling the objective of the paper.
In spite of having afforded said limitations; the paper searched
out the impact income component on HDI and GDI and its preferential
effect on each index which is the ultimate objective of this paper.
The limitations can be avoided in future. 5. REFERENCES:1) A
critical analysis of World Bank policy prescription of Gender
mainstreaming. 28 June 2008.
Peter Wall Institute for Advanced Studies at the University of
British Columbia, Vancouver,
Canada
2) A.P.Thirlwall, Economics of development 9th edition, page-
52.
3) Andrew Morrison, Dhushyanth raju, Nistha Sinha, The World
Bank Gender and Development Group Poverty Reduction and Economic
Management Network September 2007, Gender Equality, Poverty and
Economic Growth.
4) D. Hosni, M.Sandberg and A. Chanmala, Inequality among women
and its impact on economic growth: The case of MENA.5) David
dollar, Roberta gatti, 1999, page 20, Policy research report on
gender and development.
6) David Gumbel, 2004 The Influence of Gender Inequality on
Economic Growth.7) Kevin Daly, 2007 , Gender Inequality, Growth and
Global Ageing. 8) Michael P. Todaro , Stethen C. Smith, Economic
development 10th edition, page- 49-50 .9) N.G.DAS, combined Edition
(volume I & II), Statistical Methods, page- 304-308. 10) Nancy
Forsythe, Roberto Patricio Korzeniewicz, Nomaan Majid, Gwyndolyn
weathers, Valeria Durrant,2003,Gender inequalities and economic
growth and economic reform: A preliminary longitudinal evalution11)
Rashmi Umesh Arora, 2012 , Gender inequality, economic development,
and globalization: a state level analysis of India,12) Stephan
Kalsen, 1999, page 9 Policy research report on gender and
development.13) Swarna S.Vapa, 2007, Gender Equality and Human
Development.
14) World Development report 2012 on Gender equality and
Development15) hdr.undp.org/ TIME: 11:45a.m DATE: 22.12.201416)
mecometer.com/ TIME: 8:30p.m DATE: 8.1.201517)Engendering Human
Development:
A Critique of the UNDPs Gender-Related
Development Index
Elizabeth A. Stanton
March 2007
POLITICAL ECONOMY RESEARCH INSTITUTE 6. APPENDIXList of tables
Page No.1) Human Development Index (HDI) Trends, 1980-2013 122) GDP
growth rate 143) Average rate of growth (1991-2003) 144) Comparison
between Human Development Index (HDI)
and Gender development index (GDI) 15
5) Correlation 166) Gender segregation 16List of diagrams Page
No.
1) Position of countries with respect to their Income index and
HDI in the year 1980 62) Position of countries with respect to
their Income Index and HDI in the year 1990 73) Position of
countries with respect to
their Income index and HDI in the year 2000 84) Position of
countries with respect to
their Income Index and HDI in the year 2010 85) Position of
countries with respect to
their Income Index and HDI in the year 2013 96) Position of
countries with respect to
their Income Index and GDI in the year 2013 107) Position of
countries with respect to
their GNI per capita and GDI in the year 2013 118) Position of
countries with respect to
their GNI per capita and HDI in the year 2013 119) Human
Development Index (HDI) Trends 13
10) GDP growth rate,1991-2013 15
11) Gender segregation 17
1 A harmonic mean is equal to n/(1/x1 + 1/x2 ++ 1/xn), where n
is the number of terms.
3TheMillennium Development Goalsare a UN initiative.
TheMillennium Development Goals(MDGs) are eight international
development goals that were established following the Millennium
Summit of the United Nations in 2000
2 Bardhan and Klasen (1999, 2000)
(2000); Klasen (2006); and Prabhu et al. (1996).
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CHINA
INDIA
KENYA
Sheet1
CHINAINDIAKENYA
19913.841.061.44
19929.185.48-0.8
199314.244.750.35
199413.966.662.63
199513.087.574.41
199610.927.554.15
199710.014.050.47
19989.36.183.29
19997.838.852.31
20007.623.840.6
20018.34.821
20029.084.31.1
200310.038.31.5
200410.097.925.1
200511.318.45.8
200611.69.76.4
20071397
20089.66.21.6
20099.26.82.6
201010.410.15.8
20119.26.84.4
20127.73.24.6
20137.73.25.1
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0.5020.4310.471
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CHINA
INDIA
KENYA
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CHINAINDIAKENYA
19800.4230.3690.446
19900.5020.4310.471
20000.5910.4830.455
20100.7010.570.522
Sheet1
CHINA
INDIA
KENYA
_1486580213.xlsChart1
37422
84610
01000
82413
55639
136820
215921
231661
Female dominated %
Male dominated %
Neutral %
Sheet1
Field of studyFemale dominated %Male dominated %Neutral %
Agriculture37422
Education84610
Engineering, manufacturing and construction01000
Health and welfare82413
To resize chart data range, drag lower right corner of
range.
Field of studyFemale dominated %Male dominated %Neutral %
Agriculture37422
Education84610
Engineering, manufacturing and construction01000
Health and welfare82413
Arts and humanities55639
Science136820
Services215921
Social sciences; business and law231661
