Standard o f Living.6.5 Inter Relationship among Some Parameters o f Functioning.6 . 6 Analysis o f Variance in G.D.I Index.6.7 Construction o f BORDA Index Covering Various
Functioning Achievements.
CHAPTER 6
Comparative Analysis Of Gender Related Development Index and Related Aspects.
6.1 In tro d u c tio n :
Human Development Report was first published in 1990. Since then UNDP has developed and constructed several composite indices to measure different aspects o f human development. The Human Development Index (HDI) constructed every year since 1990, measures average achievement in basic human development in one simple composite index and produces a ranking o f countries. . In 1995 Human Development Report a Gender Related Development Index (GDI) and a Gender Empowerment Measure (GEM) were introduced. In HDR, 95, attention were dravm to the persistence o f severe gender disparities in human development. The central message o f the report is that human development i f not engendered will be endangered. So the human development paradigm must be fully engendered. Removal o f gender inequality has very little to do with an increase in national income. Every country has made progress in developing women's capabilities, but women and men still live in an unequal world. The revolution towards gender equality must be propelled by a concrete strategy for accelerating progress. The GDI measures achievements in the same dim ensions and using the same variables as the HDI does, but it takes account o f inequality in achievement between m en and women. The GEM measures gender inequality in economic and political opportunities.
The Human Development Report 1997 introduced the concept o f human poverty and formulated a composite measure o f it- the Human Poverty Index (HPI). While
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the HDI measures average achievements in basic dimensions o f human development, the HPI measures deprivations in those dimensions. The HDI, GDI, GEM and HPI all provide summary information about human development in a country. The goals o f gender equality differ from one country to another, depending on the social, cultural and economic contexts. So in the struggle for equality, different countries may set different priorities, ranging from more education for girls, to better maternal health, to equal pay for work, to more seats in parliament, to removal o f discrimination in employment, to protection against violence at hom e, to changes in family law, to having men take more responsibility for family life. Fundamental to all these priorities are the equality of access to means o f developing basic human capabilities, the equality of opportunity to participate in all aspects o f economic, social and political decision making, and the equality o f reward.
6.2 T he H um an D evelopm ent Index:
The HDI is based on three indicators, which are regarded as the reflector o f three basic necessities o f life. Three basic indicators are:
1. Longevity, as measured by life expectancy at birth.
2. Educational attainment, as measured by a combination o f the adult literacy rate (two -thirds weight) and the combined gross primary, secondary and tertiar>' enrolment ratio (one third weight).
3. The standard o f living, as measured by GDP per capita. (PPP. U.S.$)
To construct the index, fixed minimum and maximum values have been established for each o f these indicators:
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1. Life expectancy at birth:Fixed m inim um value is 25 years Fixed m axim um value is 85 years
2. Adult literacy rate(age 15 and above)Fixed minim um value is 0%Fixed maxim um value is 100 %
3. Combined gross enrolment ratio:Fixed m inim um value is 0%Fixed maxim um value is 100%
4. GDP per capita (PPP US$)Fixed minimum value is 100$Fixed maxim um value is 40000 $ (PPP US$)
For computing HDI the individual indices are to be computed at first. In order to compute the individual indices the following general formula is followed.
Index == (Actual value -minimum value)/(Maximum value - minimum value)
For example, if the life expectancy at birth in a country is "a" years, th e n ,Life expectancy index (X) = (a -25)/(85 -25)
Construction o f the income index is a little more complex. Income enters into the HDI, as a surrogate for all the dimensions o f human development not reflected in a long and healthy life and in knowledge- in a nutshell, it is a proxy for a decent standard o f living. The basic approach in the treatment o f income has been driven by the fact that achieving a respectable level o f human development does not require unlimited income. To reflect this, income is discounted in calculating the HDI according to the following formula:
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W (y) = (log y - log ymin )/(log ymax - log ymin)
Let the per capita GDP (PPP US $) for the country be $ A And Y = adjusted GDP per capita (PPP US $) index
Then Y = (log A - log 100)/(log 40000 - log 100)
Let the adult literacy rate (in percentage, age 15 and above) o f the country be "b" and combined gross enrolment ratio (in percentage) be "c".
Then Adult Literacy Index (P) =(b-0)/(100-0)And Combined Gross Enrolment Index (Q)= (c-0)/( 100-0)
Then Educational Attainment Index (Z)= (2.P +1 .Q)/3
Human development index
The HDI is a simple average of the life expectancy index, educational attainment index and adjusted GDP per capita (PPP US $) index; and so is derived by dividing the sum o f these three indices by 3 i.e.
(X + Y + Z ) /3 = HDI o f the country.
6.3 G en d er R elated D evelopm ent Index:
An extremely valuable and innovative contribution o f HDR,1995 is the construction o f Gender Related Development Index, (GDI), which reflects gender disparities in basic human capabilities. The gender related development index owes its origin to its precursor, the Human Development Index. The GDI
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concentrates on the same variables as the HDI but its m ain focus is on both the inequalities between men and women as well as on the average achievement o f all people taken together. In other words, the GDI is basically the HDI adjusted for gender inequality.
The GDI uses the same variables as the HDI. The difference is that the GDI adjusts the average achievement o f each country in life expectancy, educational attainment and income in accordance with the disparity in achievement between men and women. Suppose there are two countries- country A and country B. Country A has achieved a literacy rate say 50 % with no gender inequality in this respect i.e. male and female literacy rates are equal. But country B has achieved a higher literacy rate than country A, say 60% but with severe antifemale bias in this regard - i.e. female literacy rate is lower than male literacy rate. In such a situation we can easily say that country A 's Gender Related Development Index is higher than that o f country B because according to the construction methodology (described later) o f GDI penalty is to be given for inequality in achieving basic human capabilities. GDI falls when the achievement levels of both women and men in a country worsen or when the disparity between their achievements increases.
There fore, the greater the gender disparity in basic capabilities, the lower will be a country's G.D.I compared with its H.D.I.
According to H.D.R.-1995 each society can select a specific value for its 'aversion to gender inequality' (s). The selection o f this value depends upon the initial position (regarding gender inequality) and the time bound goals (regarding elimination o f gender inequality) it sets for itself. If the value o f s is zero then it implies that there is no aversion to inequality and in that case GDI will be equal to the exact value o f HDI. A larger value o f s indicates greater aversion to gender inequality. Actually e indicates the equity preference for society - equity means equality between male and female achievements. For the calculation o f GDI the
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report suggests a moderate value o f e =2 , the harm onic m ean o f female and male achievements and is calculated by taking the reciprocal o f the population weighted A.M o f the female and male achievement levels (which are themselves expressed in reciprocal form). The harmonic m ean value will be less than the arithmetic mean to the degree that there is disparity between female and male achievements. The incremental achievement o f w om en has four tim es the weight o f men if the ratio o f male to female achievement is two and e = 2. If the ratio of male to female achievements is lower than two, the incremental achievement of women is given less weight, although the value o f s remains the same.
Here GDI has been calculated for 16 major Indian states. The calculation is based on the methodology provided by HDR 1995 for computing gender equity sensitive indicators.
The computation o f GDI requires the calculation o f
(i) The equally distributed index o f life expectancy(ii) The equally distributed index o f educational attainment(iii) The equally distributed income index.
The GDI is the average o f these three equally distributed indices, and has a value ranging from 0 to 1 .
6.3(a) Equally D istribu ted Index of Life E xpectancy:
Life expectancy at birth is taken as an indicator o f longevity and for the construction o f GDI we have to find out the equally distributed index o f life expectancy which is an important component o f GDI. Now according to HDR 1995, life expectancy for both male and female are same -60 years; but there are different maximum and minimum values for m ale and female life expectancy. The minimum and maximum values for male life expectancy are 22.5 years and
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82.5 years respectively. The females have a minimum life expectancy - 27.5years and m axim um - 87.5 years. Females enjoy a higher maximum andm inim um values for their greater survival advantage than males.
Let us now suppose that for any country life expectancy at birth for female has been found to be "a" years and that o f male has been found to be "b’’years. Now for any com ponent o f H.D.I individual indices can be computed according to the general formula;
Index ^(A ctual value - Minimum value) / (Maximum value - minimum value)
So in our present case we get two indices - one for male and other for females.
For females; (a- 27.5) / 60 = X]For males; (b - 22.5) / 60 = yi
In order to get G.D.I we have to adjust these indices taking in to account the share o f males and females in total population.
Let for the country under consideration % share o f females in total population be “c”and that o f male be" d".
So the equally distributed index o f life expectancy (with £ = 2) becomes
((c/lOO) (x ,)‘ + (d/100) (y ,)‘ " = 2 ,
Table 6.1 provides the male- female proportion in total population according to states as well as five decades (1961, 1971, 1981, 1991 and 2001) for the calculation o f three equally distributed indices.
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From table 6.1 it is observed that in all states, excepting Kerala, percentage share o f female population (proportion of female population in total population x 1 0 0 ) is less than percentage share o f male population (proportion o f male population in total population x 100) in all the five decades. Moreover if we consider the two terminal periods then we can see that in all states percentage share o f male population has been increased and so that o f female population has been decreased i.e. the gap between the male- female percentage share in total population has been increased continuously which reflects the existence o f anti female bias in various achievements o f life. Kerala is the only state where a completely opposite picture is noticeable.
Table 6.2 provides the indices o f life expectancy in 16 major states in India in five decades-1961, 1971,1981,1991 and 2001.
From the table 6.2 it is clear that in each state, excepting Kerala, female life expectancy index is lower than that o f male in each o f the above mentioned period. This picture is sufficient to conclude that females are discriminated in achieving a long life and this anti female discrimination is so strongly practiced that it completely offsets the established biological norm, which says that females have a greater survival advantage than their male counterparts. It is to be mentioned that Kerala is the only state which has been able to achieve a higher life expectancy index for female than that o f male from 1981.
Table 6.3 presents the values o f the equally distributed index o f life expectancy for 16 Indian states as well as for five decades (1961, 1971, 1981, 1991 2001) based on the methodology already discussed.
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TABLE 6.1
S tate wise, D ecade w ise M ale - Fem ale P ro p o rtio n In T otal Population.
States 1961 1971 1981 1991 2001M F M F M F M F M F
In table 6.3, indices o f life expectancy have been adjusted for gender disparity. From the table it is clear that Kerala has achieved the highest life expectancy index for its people. Punjab ranks next to Kerala. Among the other states performances o f Tamil Nadu, Maharastra, Haryana are also good. Performances o f Madhya Pradesh, Orissa and Assam are very poor in providing a long life to its people. Uttar Pradesh, Rajasthan, also have not been able to provide a satisfactory life expectancy index to their entire people regardless o f male and female population. In the states West Bengal, Karnataka, Gujarat and Andhra Pradesh a moderate equally distributed life expectancy indices have been achieved. One interesting thing is noticeable here that the achievement o f Bihar is not so poor in this regard. Starting from a very low equally distributed index o f life expectancy, 0.2395 in 1961, this state has been able to acquire a moderate index o f life expectancy for all its male and female population. All the states are improving for achieving higher life expectancy index for its people but the rate o f improvement is not even for all states. Again with in the states this improvement rate is not even for all the decades. In Madhya Pradesh this rate o f improvement was very poor between 1961 and 1971, and between 1981 and 1991. But between 1971 and 1981 this improvement rate was very high. Again M adhya Pradesh improves very fast between 1991 and 2001 in acquiring equally distributed index o f life expectancy for its people. Whereas Kerala, starting with a satisfactory equally distributed index o f life expectancy is consistently improving in achieving higher life expectancy index, but its rate o f improvement became slow within the period 1991 to 2001.
6.3(b) E qually D istribu ted Index of E duca tio na l A chievem ent:
According to HDR 1990 adult literacy rate could be taken as a measure o f educational attainment. But this adult literacy rate can hardly reflect the true picture o f educational attainment o f a country. So in 1991, mean years of schooling was included along with the adult literacy rate in the construction o f educational attainment index. But this modification was not sufficient because o f
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the non-availability o f reliable data on mean years o f schooling. So in order to attain educational attainment index HDR 1995 proposed that there should be two com ponents in the so-called index-- Adult literacy with two-third weight and gross com bined primary, secondary and tertiary enrolment with one-third weight. Each o f these sub-components are to be indexed separately using a globally fixed minimum and maxim um values which are 0% and 100% respectively. The two indices are then added together with the aforesaid weights and then the composite index o f educational attainment is formed. In case o f GDI we have to adjust this index for gender disparity by taking into account the share o f male and female in total population.
But in the present study overall literacy rate has been incorporated in place of adult literacy rate (which is meant for population aged fifteen and above). Up to 1981 Census overall literacy rate means literacy rate for population aged 5 and above. It was declared that people below 5 years are illiterate. But in 1991 Census this notion was changed and it was declared that people below the age seven years are illiterate. So in 1991 Census Reports over all literacy means literacy rate for population aged seven and above. So there should not be any ambiguity regarding the overall literacy rate for the four census years if the definition regarding illiterate persons declared in five censuses is considered.
But there are great problems regarding the data on gross enrolment rates published for India and the states. The gross combined primary, secondary and tertiary enrolment rate is defined as percentage o f population in the age group 6 to 23years who are currently enrolled in an educational institution. The number of males and females enrolled at different levels o f education are provided by the M inistry o f Human Resource Development in their annual report. But the data regarding the population in the selected age group are not readily available. More over these enrolment figures are highly unreliable. For example, according to the M inistry o f Human Resource Development (1993), boys' enrolment in primary schooling during 1991-1992 varied between 61% and 148% and was 100% or
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more in 27 out o f 32 states and union territories for which data are available. Again though girls' gross enrolment rates were on the average lower than that o f males, they varied from 59% tol36% and exceeded 100% in 14 out o f the 32 states and union territories. Such misleading picture should not be treated as representative o f either educational attainment. The dismal state of basic education in the country is highlighted most glaringly through this picture. Because o f several reasons gross enrolment rates exceed 100%. Over age pupils and high repetition rates which occur in the final year o f the particular level and the false statem ent o f the principal / teacher regarding the enrolment figures (especially i f their jobs depend upon the numbers enrolled in school) tend to inflate the numerator. So gross enrolment ratios do not give the correct picture o f educational attainment across the country and also it is very difficult to obtain desegregated data on gross enrolment ratio below the state level. Given the problems w ith gross enrolment figures here full weightage has been assigned to overall literacy in the computation o f G.D.I for India and the 16 states.
Let us suppose that for the country under consideration overall literacy rate for female is "p" and that for male is " q ". For the computation o f H.D.I fixed minimum and fixed maximum values are used which are 0 % and 1 0 0 % respectively .So the indices for educational attainment are:
In order to get G.D.I these indices are to be adjusted taking in to account the share of male and females in total population.
So the equally distributed index o f educational attainment (with e = 2) is [(c/1 0 0 ) ( x 2) ‘ -^ + (d /1 0 0 ) (y2) ‘ - ^ ] ‘"-^ .
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Table 6.4 represents the values o f the equally distributed index o f educational attainment for 16 Indian states over the previous five census periods using the above methodology.
From the table 6.4 it is evident that in each year equally distributed index o f educational attainment o f Kerala is highest among other states. Himachal Pradesh, Maharastra, Tamil Nadu rank fair in this respect. Gujarat, Punjab, W est Bengal, Karnataka are the states having moderate index. Perform ances o f Uttar Pradesh, Orissa, Madhya Pradesh, Haryana, Assam, Andhra Pradesh in achieving a higher index o f educational attainment for both male as well as female are not satisfactory. Rajasthan's performance is very poor and performance o f Bihar is worst in this regard. So equally distributed index o f educational attairmient for India, as a whole is 0.635, which is not at all satisfactory. It has to be mentioned that after entering into the decade o f 80's many states, e.g. West Bengal, Kerala, Tamil Nadu, Maharastra, Karnataka, Himachal Pradesh got a boost to leap forward in achieving higher equally distributed index o f educational achievement.
6.3(c) E qually D istributed Index of Incom e:
Along with good health and proper education good income is needed for a decent standard o f living. An adjusted measure o f real GDP per capita expressed in purchasing power parity dollars is used in HDI as a surrogate to measure command over resources needed for a decent standard o f living. The HDI adjusts real income (expressed in PPP dollars) for the dim inishing utility o f higher levels o f income to human development. This is because people do not need an infinite amount o f income to maintain a decent standard o f living.
The HDI uses PPP$ 5120 as a threshold for income which is the average global real GDP per capita in PPP dollars in 1992. The HDI treats income up to this level
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TABLE: 6.4
Equally Distributed Index of Educational Attainment.
at full value, but sharply discounts incomes above this level as having a dim inishing utility by using the following formula w(y) = y* for 0 < y < y*
= y+ 2 [(y -yV ^^] fory* < y < 2 y*
= y* + 2(y*‘^ ) + 3 [ ( y - 2y*)'^^] for 2y* < y < 3y*
India's real GDP per capita for 1992 was estimated at PPP $ 1230, well below the threshold level o f PPP $ 5448 and therefore does not require any adjustment.
In order to arrive at comparable estimates of real income per capita expressed in PPP(purchasing power parity) dollars for Indian states the ratio o f per capita state dom estic product o f each state to per capita national income has been applied to India's real GDP per capita expressed in PPP dollars.
In order to compute the equally distributed index o f income the first step is to calculate the female and male shares o f earned income; this can be done by using
(I) the ratio o f the average female wage to the average male wage, and(II) the female and male percentage shares o f the economically active
population.
In order to do so HDR 1995 uses the male-female wage o f non-agricultural sector. But in the present analysis agricultural wages o f both male and female have been considered since India is basically an agrarian country. Because o f the absence of data on employment by gender the HDR 1995 report makes the simplifying assumption that female employment and male employment are proportional to the female and male participation in the labour force. Census o f India provides data on female and male work participation rates for India and the states. Here in com puting the GDI work participation rates have been used.
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The procedure for calculating the equally distributed index o f income is shown below:
W= share o f econom ically active population for females x ratio o f average wage o f females to m ales + share o f economically active population for males x 1
A = Female wage to average wage = (Ratio o f average wage o f females to males)/ w
B= Male wage to average wage = 1/w
C = Share o f earned income for females = A x share o f economically active population for females.
D = Share o f earned income for males == B x share o f economically active population for males.
E= Females proportional income share = C/ share o f total population for females.
F= Males proportional income share = D/ share o f total population o f males
Equally distributed income index with s = 2 = G
G= [(share o f total population for females) ( E ) ® + (share o f total population for males)
G X average state domestic product = G
(G -1 0 0 )/ All India average -100 - G ^
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Table 6.5 gives the percapita net state domestic product at current price and table6 . 6 gives the equally distributed index o f income.
From the table 6.5 it is clear that for each state percapita net state domestic product has been increased by considerable amount, though this increase o f state domestic product can mostly be attributed to the inflationery price rise rather increase in production as a whole.
A study o f the table reveals the fact that for each state percapita net state domestic product has been increasing consistently. Among the states, achievements of Bihar, Orissa, Assam, Uttar Pradesh are very low com pared with the other states.
Table 6 . 6 depicts a completely random change o f equally distributed index of income achieved by various states over time. In m ost o f the states starting from a high value in 1961, equally distributed index o f incom e falls in the intermediate period - 1971 and then it started reviving; but in some states e.g. W est Bengal , Uttar Pradesh , it failed to gain the initial value up to 1991. After entering in to 2001 the equally distributed index o f income in the states U.P and W.B surpassed the 1961 values. A major cause behind the fall o f the index in 1971 was the deep decline o f female work force participation rate in the year 1971 through out India. Among the states, Andhra Pradesh, Karnataka, Tamil Nadu, Haryana, UP and W.B have been able to achieve a satisfactory equally distributed index o f income. One interesting point is that Kerala, the state which ranked first in achieving equally distributed index o f life expectancy as well as literacy, has poor performance in attaining equally distributed index o f income compared to other states. Bihar, Orissa , Punjab , Maharastra are the states showing random fluctuation in equally distributed income index. 1971. Madhya Pradesh is the state, which show very slow progress in the attainm ent o f equally distributed index o f income.
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TABLE 6.5
P ercap ita Net S ta te Dom estic P rodu ct A t C u rre n t P rice
Table6.7 gives the Gender Related Development Index (G.D.I.) for the major states as well as India as a whole. G.D.I is actually the Arithmetic mean o f Equally Distributed Index o f Life Expectancy, Equally Distributed Index O f Income and Equally Distributed Index O f Educational Achievement.
From the table 6.7 it is clear that if we consider only the two terminal periods then in almost all states value o f G.D.I has increased compared to the initial period - 1961.In many states G.D.I value first falls and then again increases. In Bihar, U ttar Pradesh, M adhya Pradesh, Gujarat, Maharastra, Orissa, Rajasthan, West Bengal G.D.I decreased from 1961 to 1971 and there after it has been increasing consistently. The only cause behind this fall o f G.D.I value in these states is the massive fall o f Equally distributed Index o f Income in 1971 compared to 1961 which completely o ff set the corresponding increase in Equally Distributed Index o f Life Expectancy and Equally Distributed Index o f Educational Attainment in these states. A ndhra Pradesh, Haryana, Karnataka, Kerala, Tamil Nadu are the only states where G.D.I has been increasing consistently. Among the states, performance o f Haryana, Punjab, Kerala, Tamil Nadu, Karnataka, Maharastra are worthy to be mentioned in the field o f achievement o f G.D.I by various states. Maharastra is the leading state in this regard, having the highest value o f G.D.I in almost all years compared to the other states. Haryana ranked second in this field. Kerala's performance in the field o f achievement o f Equally Distributed Index o f Life Expectancy and Equally Distributed Index o f Educational Achievement is best among all the states but in case o f achievement o f Equally Distributed Index o f Income M aharastra, Haryana surpassed Kerala with a considerable margin in each o f the census period and finally in achieving G.D.I M aharastra ranked first. Punjab behaves abnormally; no specific pattern o f change can not be traced regarding its G.D.I achievement in the five previous census years.
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G ender R elated D evelopm ent Index fo r M a jo r S tates in Ind ia in Five Census Periods -1961,1971,1981 and 1991.
Source: Calculated On the Basis o f Data Com piled From Various Census Reports.
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Standard o f living o f an individual is judged by the extent o f capability o f that individual. Capability o f a person means the set o f achieved feasible functionings o f that person. So if the capability set o f a person can be enlarged i.e. if the capability set includes more and more new functioning achievements then it is expected that the standard o f living o f the concerned person has increased. In an exactly analogous marmer it can be said that if on the average the capability set of all persons in a country be enlarged then the average standard o f living o f the people in that country would increase. Now it has already been stressed in the analysis that in order to assess the standard o f living o f common people in a country, both male and female components o f population should be taken into consideration with respect to their functioning achievements. Usually it is observed that in the developing countries average capability set o f females is smaller than that o f males. So compared to males females enjoy less freedom— the freedom o f choice. Attempts at unraveling the root cause o f such discrepancy in functioning achievements o f males and females reveals the truth that there exists gender discrimination — an anti female bias. This explains why females lag behind the males in respect o f functioning achievements. Social and economic opportunities are observed to be less available to the fem ales compared to males in most o f the developing countries, though its m agnitude differs from country to country. So it can be said that average standard o f living o f female population is lower than that o f male population in these countries. Had the females in a country enjoyed the same level o f functioning achievem ents as their male counterparts, average standard o f living o f the com m on people (taking in to consideration o f both males and females) in that country would surely have increased. W ith the growing consciousness in each country, for ensuring a better standard o f living o f both the present and future generations o f human race, the notion o f “Sustainable Development” has been emphasized. Now if the present pattern o f development contains anti female discrimination, sustained development o f the present type would perpetuate this type o f gender
6.4 Inter relationship between Gender Bias and Standard of living:
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discrimination and so standard o f living o f people in general would not be increasing. Human development index has been constructed for several countries to find out the level o f standard o f living o f their people. After the construction of Gender related development index, the very aspect o f gender discrimination received great importance in development plaiming o f many countries, particularly in India. The study o f Gender related development Index o f a country over time provides a clear picture regarding the change in the level o f standard of living o f its people, as well as changes in the magnitude o f gender discriminations.
In India it has been found that G.D.I in 1971 was significantly lower than that of 1961. This was due to drastic fall in female work participation rate in 1971 compared to 1961. After that G.D.I is increasing steadily. So it can be said that in India over time gender discrimination is falling, thereby improving the average standard o f living o f its people. However the fall in anti female bias and improvement in standard o f living are not at the desirable pace. Quicker decline of anti female bias as well as rapid improvement in living condition o f people are the necessary ingredients o f the development. For this rigorous thinking over the matter, appropriate policy, and above all making the people aware o f the evil impact o f anti female bias on their lives are needed on the part o f the Government as well as development planners.
6.5 In te r re lationsh ip am ong some p aram eters of functioning:
In order to have an understanding o f the interrelationship among the different parameters o f functioning achievement considered for constructing the GDI, it is thought proper to run a multiple regression analysis treating life expectancy as dependant variable and education and income as independent variable. It is hypothesised that with the attainment o f higher levels o f education people become conscious about various health hazards and awareness about ways o f achieving
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healthy life pattern increases life expectancy. Similarly with the rise in income opportunities people are likely to have greater access to better means and ways o f eking out their livelihood which is expected to enhance lifespan on the average. On the basis o f this causal hypothesis we consider the equally distributed figures (so that unit free figures can be taken under consideration) o f the three relevant functionings.
Five relevant census years, for which meaningful figures could be computed, were taken into consideration. The census years under consideration are 1960-61, 1970-71,1980-81 ,1990-91 and 2000- 2001.
The multiple regression takes the following form Xi = a + b iX 2 + bzXj
Where,Xi = Equally distributed index o f life expectancy
X 2 = Equally distributed index o f educational attainment
X 3 = Equally distributed index o f income
The relevant results are given in table 6 . 8
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TABLE 6.8
Results O f Regression.
2 0 0 0 - 2 0 0 1
R = 0.729 a =0 .296 O.IOO(SE) 2.943(t value)R^ = 0.531 bi = 0.474 0.169(SE) 2.806(t value)
Adj. R ' = 0.453 b2 =0.046 0.056(SE) 0.826(t value)1990-1991
R a = 0.386 0.053(SE) 7.229(t value)R ' bi = 0.431 0.104(SE) 4.13 l(t value)
R a = 0.345 0.035(SE) 9.826(t value)R ' bi = 0.448 0.083(SE) 5.38(t value)
A dj.R ' b2 = 1.253 E-02 0.037(SE) 0.337(t value)1970-71
R a = 0.278 0.057(SE) 4.883(t value)R ' bi = 0.533 0.193(SE) 2.753(t value)
Adj. R" b 2 = 2.611 E-04 0.082(SE) 0.003(t value)1960-61
R a = 0.227 0.043(SE) 5.236(t value)R ' bi = 0.692 0.179(SE) 3.863(t value)
A dj.R ' b2 = -1.48 E-02 0.057(SE) -0.258(t value)
Source; calculated on the basis o f data compiled from various Census Reports.
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Before explaining the regression results it need to be mentioned that for the year 1990-91 and 1970-71, 16 sets o f data were considered, while for the years 2000 - 2001, 1980-81 and 1960-61 the corresponding num ber was only 15. This is because in 1980-81 no census was held in Assam and for the year 1960-61 and 2000 - 2001 data on life expectancy for Himachal Pradesh was not available.
From the results o f the above table - table 6 . 8 it is found that all the regression equations are good fit as established by the levels o f values o f coefficient of determination i.e. and their significance at 5% level.
The values o f F for years 1990-91 and 1970-71 were respectively F2 , 13 = 9.24 and F2 . 13 =3.49.
W hile that for the years 2000- 2001,1980-81 and 1960-61 were F2 . 12 = 6 .78 , p 2,i2 = 17.53 and F2 . 12 = 7.85 respectively.
The corresponding tabular values at 5% level are F,o5. 2 .i3 = 3.81 and F.o5, 2.12 =3.89.
Here we find that computed values o f F exceed the tabular values for the census years excepting 1970-71. Hence for the remaining census years they are found to be good fit. However the t values for all the years were found to be significant for only the intercept term and the coefficient o f educational level while that for income happen to be insignificant for all the considered years. The simple interpretation is that higher educational attainment gets reflected in better hygienic awareness which also enhances the average years o f life people expect to live.
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Let us now consider the entire G.D.I indices table in order to study and analyse the effects o f two factors in influencing the G.D.I values as they are computed covering the three constituents. In other words we want to conduct ANOVA in the fixed effects model with two way classified data having one observation per cell, so as to analyse whether there is significant variation in G.D.I values across years or across the states.
Lets the states are denoted by symbol A and year by B. For each factor there will be a number o f classes or levels. Here on the left-hand side we have 14 states and on the top we take 5 census years. So there are altogether 5 x 14 = 70 cells. Let the cell G.D.I s be denoted by [ly (i =1,2,3,-----,14; and j =1,2,3,4,5) such that,
Where |i is constant general impact present in all G.D.I values irrespective o f states or census years.
tti = ( lio . |i) = effect on G.D.I due to the ith state factor which is common to all the G.D.I values belonging to this state.
Pj = ( loj - 1 ) = the effect on G.D.I due to the impact o f jth census year which is common to all the G.D.I values belonging to this jth year, and
Yij = ( [ly - [J-io - M-oj + [J-)= the interaction between ith state factor and jth census year fa c to r; It is unique to the G.D.I value in the (i,j)th cell observation.
6.6 Analysis of Variation in G.D.I Index:
1 6 2
Now we carry on the hypothesis testing withHoa : a i = tt2 = --------- = a i 4 0 implying that there exist equality o f theimpact on the G.D.I values due to the different state factor levels.
Similarly we carry on testing o f another hypothesisHob : (3i = P2 = Ps = P4 = Ps = 0 for testing the equality o f the effectso f different census year levels on the values o f G.D.I.
The null hypothesis Hoa will be rejected at ot% level if F= M SA/M SE >Fa_i3.52
And Hqb will be rejected at a % level if F= M SA/MSE >?«, 4,52.
Tio = Total for each o f the 14 A classes.Toj = Total for each o f the 5 B classes.Too = Grand total.
Total SS = 2.315 SS due to states = 0.929 SS due to years = 1.059SSE = Total SS - SS due to states - SS due to years = 0.327
The ANOVA table as obtained from the G.D.I table is given in table 6.9.
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TABLE 6.9
Analysis O f Variance of Two Way Classified Data with One Observation Per
Cell.
Source ofvariation
df SS MS F at level1% 5%
Due to states
13 0.929 .07146 11.378 significant significant
Due to years
1.059 .26475 42.157 significant significant
Error 52 0.327 0.00628Total 69
Source: calculated from various Census Reports
The implication o f the table 6.9 is that different levels o f state factors have significant impact on differences in mean levels o f G.D.Is, Similarly mean levels o f G.D.Is also differ due to different levels o f census years.
6.7 C on stru c tion o f B orda Index C overing V arious Functioning A chievem ent:
In order to project an alternative way of computing the extent of anti female bias, (other than the G.D.I measure) we here propose to take resort to the B orda R ank ing M ethod. For this purpose, it is thought proper to not only confine to the three functioning achievements, i.e. literacy, life expectancy and income levels, but to make it more comprehensive it is proposed to incorporate overall female male ratio, child female male ratio, work force participation rate, agricultural wage earnings e.t.c, for the 14 major states, for the 5 census years- 1961, 1971,
1 64
1981, 199lan d 2001 for which comprehensive data on all the aforesaid categories were available.
In order to construct a meaningful Borda index, male - female differences in work force participation rate, agricultural wage rate, literacy rate and life expectancy figures along w ith female male ratio and children female male ratio for 14 states covering the aforesaid census years have been tabulated in the tables 6.10, 6.11, 6.12, 6.13 and 6.14. Ranking for each category across the states are done in ascending order implying that figures indicating least male-female gap are given lower ranking starting from 1 and gradually increasing as the male-female differences in the corresponding category rises. This is reflective o f the fact that low anti female bias indicating better position o f women vis-a-vis men are put lower ranking values and vice versa. Similarly for the female- male ratios, higher values reflecting relatively better position of women are attached low ranking values and vice versa. The figures in the brackets in each cell for the four tables indicate the rank o f the corresponding item for the corresponding state. All the ranks are summed up covering the seven categories for each state and the aggregate ranks are shown state wise and census year wise in the table 6.15.
From table 6.15 relative positions o f different states in the five census periods - 1961, 1971, 1981, 1991 and 2001 can be studied. It is observed that in 1961, 1971 and in 1981 Andhra Pradesh ranked first and Kerala ranked second . But after entering into 1991 Karnataka marched ahead o f Kerala. So in 1991 A.P again ranked first, Karnataka ranked second and Kerala ranked third. Previously Karnataka was on third position in 1971 and 1981. But in 2001 Kerala ranked first, A.P ranked second and Karnataka ranked third. Tamil Nadu ranked forth in 2001. Performances o f Bihar, Rajasthan, Punjab, Orissa, M.P and even M aharastra are not at all satisfactory. Their rankings have been worsened. W.B has been able to improve their ranking.
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On the basis o f the aggregate Borda ranking it is thought proper to determine the degree o f correlation for successive pair wise census years and also the extent o f correlation between the two terminal periods under consideration i.e. 1961, 2001. The values o f correlation coefficient is supposed to throw light on whether states having on the average lower aggregate Borda ranking in one census year have similar values in another census years and states having on the average higher aggregate values o f Borda ranking in one census year possess higher values in another census year. If strong positive correlation is observed that would indicate that relative position o f states regarding anti female bias have remained same over time on the average.
In the table 6.16 it has been found that for decadal period 1961 to 1971 correlation coefficient o f Borda rank is 0.895, for period 1971 to 1981 the corresponding value is 0.851, for period 1981to 1991the value is 0.913 and for the period covering 1991 to 2001 the value is 0.833. All the values are significant at 1% level. If we take the two terminal years then we see that the correlation coefficient o f Borda ranks between the years 1961 and 2001 is 0.515 - the value is significant at 6% level. The implication is that states having better position regarding the degree o f anti female bias have on the average retained their position while states having relatively bad/worse position regarding anti female bias have over time stayed in the same category. The regional disparity regarding anti female bias has persisted over tim e with little impact being felt during the planning era. Female disadvantages vis a vis males have showed little signs o f redressal in relative sense over the census years.
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Table:6.10
State wise Borda Ranking of Different Levels of Functioning Achievements
Source : Calculated with the help o f various census reports
1 7 2
TABLE: 6.16C orre la tion o f B orda indices across the states fo r pair-w ise census years
1961-71 1971-81 1981-91 1991-2001 1961 -20010.895
Significant At 1% level
0. 851 Significant at 1% level
0 .913 Significant at 1% level
0.833 Significant at 1% level
0.515 Significant at 6% level
Source; Compiled from various Census Reports
The analysis o f gender disparity so far undertaken pertain to mostly conventional indicators and the aspect o f anti female bias is found to be strongly persistent the degree o f which also vary across the states. However the aspect o f non- conventional indicators in explaining gender disparity is relatively little explored. It remains to be analysed whether the extent o f gender disparity as reflected in anti female bias is altered if some o f the relevant quantifiable non-conventional indicators are explicitly taken into consideration.
