The predominance of female deficiency has been a

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1 a case study International Journal of Commerce and Business Management ; Vol. 4 Issue 1 (April, 2011) : A critical analysis of sex ratio in n scenario with special reference to Orissa Received : October, 2010; Accepted : January, 2011 ABSTRACT In, the demographic imbalances are growing at a faster rate than the other country. The declining trend in the juvenile sex ratio raise questions about the presumed interlink between development and women s empowerment. Improvement in health, education and higher work force participation of women has no impact in translating into a higher value for girl children and women. This simply raises a finger towards gender distribution of prosperity and the gender balance in empowerment flowing from prosperity. In this attempt has been made to answer the question raised above by analyzing the various factors responsible for this problem separately. Das, Manjula, Jha, Dilip Kumar and Mohanty, Anouja (2011). A critical analysis of sex ratio in n scenario with special reference to Orissa. Internat. J. Com. & Bus. Manage, 4(1): Key words : Sex ratio, Declining trend, Factors responsible The predominance of female deficiency has been a striking feature of our population throughout the whole of the regular census history. The census figures indicate that there has been a steady fall in the proportion of females in the entire successive census except a small rise in 1951, 1971 and 2001 census. Further it also indicates that while the females outnumber males in Kerala, in the states like Haryana, Himachal Pradesh, Jammu & Kashmir and Delhi, it has been constantly low. The states like Orissa, Manipur, Tamil Nadu and Mizoram have much lower sex ratio after The higher sex ratio in southern states and lower in case of northern states has been an enduring feature of the social life of our people for an indefinitely long time. The recent demographic trend (2001 census) while shows slight increase in sex ratio from 927 to 933 at the same time it also highlights the worrisome decline in the juvenile sex ratio(0-6 years) in several states. The overall juvenile sex ratio dropped from 945 to 933 in between 1991 and Urban areas, which tend to be characterized by higher per capita income and higher literacy rates revealed the worst sex ratios. At the all- level there has been continuous declining of sex ratio (FMR) i.e. number of females per Correspondence to: DILIP KUMAR JHA, Department of Economics, Guru Ghasidas Vishwavidyalaya,BILASPUR (C.G.) INDIA Authors affiliations: MANJULA DAS, ITER, S O A University, BHUBNESHWAR (ORISSA) INDIA ANOUJA MOHANTY, Department of Management, F.M. University, BALASORE (ORISSA). INDIA thousand males since 1901, except some marginal increase in 1951 and 1981.In 2001 the FMR has slightly improved to the extent of 933. The reasons put forward for the declining sex ratios are Differential mortality rates, Discrimination against female children leading to female mortality, Sex selective abortions and infanticides, Unequal access for women to life sustaining inputs like food, nutrition and health, leading again to differential mortality, Depleting and degrading status of women in some societies because of social and cultural factors and violation of human rights. Declining trend in sex ratio (FMR) in as well as in Orissa has been a matter of serious concern for the last few decades, although the state s figure is better than that of. Juvenile sex ratio also shows a similar trend as already studied by Agnihotri (2000 and 2002). For the improvement of sex ratio, various rules and steps are being taken by the Governments both at the state and national levels. In this context, the present paper makes an attempt to find out possible association of sex ratio (over all) with factors such as child sex ratio, work participation rate, literacy rate, differential mortality rate and human development index. Further, a longitudinal study of sex ratio of the State of Orissa and also the country as a whole has been undertaken. In the study of sex ratios in the country, it is sometimes hypothesized that there is a link between HIND INSTITUTE OF COMMERCE AND BUSINESS MANAGEMENT

2 156 female work and female worth. Higher participation in economic activities enhances the status of women ensuring their more equitable access to basic survival inputs. Low participation affects this access adversely resulting in more masculine sex ratio than usual. Longitudinal study of sex ratio: The sex ratio at birth (Table 1) and in the age group (0-4) years (Table 2) showed that number of males significantly increased with respect to time ( p<0.01). The linear trend line for sex ratio at birth was computed as: Table 1 : Proportion of males to females at birth of Sr. No. Period (t) Males per hundred females (U t ) Source: Office of Registrar General, Population Census Reports (SRS). Table 2 : Proportion of males to females in the age group (0-4) years for Period (t) Males per hundred females (U t) U t = x t; R 2 =0.644 ( highly significant, P < 0.01). Similarly for the age group of (0-4) years, U t = x t, R 2 =0.729 (P=.031) At all- level it was observed that the sex ratio at birth for the period between to showed that male children outnumber the females, justifying perhaps biological propensity of n women to give birth to more male children (Fig. 1). This masculinization of sex ratio is also revealed in sex ratio of 0 4 years of aged children in the country during (Table 2 and Fig. 2). MALES PER 100 FEMALES Fig. 1 : Males per 100 females at birth of ( to ) Fig. 2 : Males per 100 females (0-4) years age group Orissa/ Factors affecting sex ratio: It is hypothesized that over all sex ratio is likely to be affected by factors such as child sex ratio, differential mortality rate (DMR), literacy rate (LR), female labour participation rate (FLPR) and human development index (HDI). Taking into account, different indicators of 15 major states of the country, we find FMR(Y) = x LR (X 1 ); with R 2 = ; FMR(Y) = x DMR(X 2 ); with

3 R 2 = 0.338; (P=0.023) FMR(Y) = x 10-2 FLPR(X 3 ); with R 2 = ; FMR(Y) = x FMR (0 6) (X 4 ); with R 2 = 0.515; (P=0.003) FMR (Y) = x HDI (X 5 ); with R 2 = ( Significant at 5% level, - Highly significant (P<0.01)) The linear correlation coefficient between sex ratio (FMR) and female FLPR and between FMR and HDI were found to be low and not significant where as the regression coefficient of FMR with differential mortality rate (DMR) and with FMR (0-6) were found to be significant. The correlation between sex ratio and literacy rate was also not significant although positive. Thus, the plausible argument put forward in support of literacy and female labour participation may be that it takes relatively longer period till the level of literacy and female labour participation favourably affects the FMRs (Table 3). Note: The FMR (0 6) years of age group is also not significantly associated with literacy rate and FLPR as evident from the following regression equations. FMR 0 6 = x LR; R 2 = 0.002; (not significant) FMR 0 6 = x FLPR; R 2 = 0.001; AN ANALYSIS OF SEX RATIO IN INDIAN SCENARIO Table 3 : Different indicators of some major States of, 2001 FMR Death rate Sr. Literacy States (Sex No. rate Male Female Diff. ratio) Female labour participation (FLP) Sex ratio (0 6 years) 157 Comparison between rural and urban sex ratio: A comparison between rural and urban FMR of Orissa and ( ) showed that rural FMR has always been higher than urban FMR in the State as well as in (Table 4 and Fig. 3). However, urban Orissa has lower FMR than urban during The linear trend in sex ratios over the years ( ) is shown by the following regression equations: Orissa : ) = x t;r 2 = ; (P=0.001) ) = x t; R 2 = ; (P=0.009) : ) = x t; R 2 = 0.904; (P=0.000) ) = x t; R 2 = On considering the sex ratio of above data (Table 4) from 1961 to 2001 (i.e. after independence) the following linear trends equation were found. Orissa : ) = x t; R 2 = ; (P=0.012) Human development index (HDI) 1. Andhra Pradesh Assam Bihar Gujarat Haryana Karnataka Kerala Madhya Pradesh Maharashtra Orissa Punjab Rajasthan Tamil Nadu Uttar Pradesh West Bengal Economic Survey of, 2001

4 158 Table 4 : Rural- urban sex ratio of Orissa/ Orissa Year Rural Urban Rural Urban Source: Census, 2001 SEX RATIO ) = x t; R 2 = ; (P=0.008) ) = x t; R 2 = ; (P=0.007) : ) = x t R 2 = Orissa(Rural) Orissa(Urban) (Rural) (Urban) Fig. 3 : Rural urban sex ratio of Orissa/ ) = x t; R 2 =0.615 ) = x t. R 2 =0.973 (P=0.002) ( Significant at 1% level) The linear trends of sex ratios of Orissa were statistically significant during The increasing trend of sex ratios in urban is supposed to be affected by migration or urban awareness. Residence-wise sex ratio for different castle grousp: Scheduled castes (Orissa) (Table 5 and Fig. 4): ) = x t; R 2 = 0.823; (P=.033) ) = x t; R 2 = ; (P=.036) ) = x t; R 2 = 0.042; SEX RATIO Rural Orissa Orissa Urban Orissa Orissa Rural Urban india Fig. 4 : SC sex ratio rural-urban of Orissa/ Table 5 : Sex ratio of scheduled castes Orissa Census Year Rural Urban Total Rural Urban Total Source: Census of, 2001

5 Scheduled castes () : (Table 5 and Fig. 4) ) = x t; R 2 =0.463; ) = x t; R 2 =0.598; ) = x t; R 2 = 0.895; (P=.015) ( Significant at 5% level) Scheduled tribes (Orissa): (Table 6 and Fig. 5) ) = x t; R 2 =0.677; ) = x t; R 2 = 0.614; ) = x t; R 2 = 0.142; Table 6 : Sex ratio of scheduled tribes Census Orissa Year Rural Urban Total Rural Urban Total Source: Census of, 2001 SEX RATIO Rural Orissa Urban Orissa Rural Urban Fig. 5 : ST sex ratio for rural-urban of Orissa/ AN ANALYSIS OF SEX RATIO IN INDIAN SCENARIO ) = x t; R 2 =0.544 ) = x t; R 2 = (significant) (P=.015) 159 Other caste (Orissa): (Table 7 and Fig. 6) ) = x t ; R 2 = ; (P=0.01) ) = x t ; R 2 = ; (P=0.003) ) = x t ; R 2 = ; (P=0.004) Other caste (): (Table 7 and Fig. 6) ) = x t ; R 2 = 0.219; ) = x t ;R 2 = 0.326; ) = x t ; R 2 = 0.365;. Table 7 : Sex ratio for other castes Orissa Year Rural Urban Total Rural Urban Total Source: Census of, 2001 SEX RATIO Scheduled Tribes (): (Table 6 and Fig. 5) ) = x t; R 2 = Orissa(Rural) Orissa(Urban) (Rural) (Urban) Fig. 6 : Sex ratio for other caste (rural/urban) of Orissa/

6 160 As found from the regression equations, the sex ratio of the state of Orissa in case of ST community, the linear correlation coefficient was not significant, where as for SC community, it was negative and significant and in case of other castes, it was negative and highly significant. Urban sex ratio showed deviation from it, may be due to migration or urban awareness. Effect of literacy rate on sex ratio in Orissa: It is sometimes hypothesized that higher literacy rate encourages favourable sex ratio (FMR). The data for 30 districts (Table 8) show that FMR was inversely related to literacy rate as per 2001 census, which seems to be a disturbing sex ratio scenario in the state. The linear regression equations for the age group 0 6 years as well as the entire population were obtained as: For (0 6) years age group, sex ratio: FMR 2001 = x LR; R 2 = ; (P=.000) For all age group, sex ratio: FMR 2001 = x LR; R 2 = ; (P=.000). After independence, in 1951 census the male literacy rate in Orissa was as low as and female literacy ratio was extremely low to the extent of The difference in the literacy rate between males and females increased steadily till 1991 census and the gap reduced to during 2001 census. Figure shows the slope of male literacy was higher than that of female implying a slower growth in case of female literacy. The increase in literacy rate has not helped the improvement in sex ratio and surprisingly declining sex ratio was observed. A Table 8 : District-wise sex ratio in rural and urban areas of Orissa according to census Sr District No. Rural Urban Total Rural Urban Total Literacy rate 1. Angul Balasore Bargarh Bhadrak Bolangir Boudh Cuttack Deogarh Dhenkanal Gajapati Ganjam Jagatsinghpur Jajpur Jharsuguda Kalahandi Kandhamal Kendrapara Keonjhar Khurda Koraput Malkangiri Mayurbhanj Nabarangpur Nayagarh Nuapada Puri Rayagada Sambalpur Sonepur Sundergarh Source: Census of, 2001

7 disturbing feature arised due to the fact that FMR was negatively correlated with literacy rate, which was highly significant as shown by the regression equations. In all contexts, FMR was positively correlated with literacy rate (LR) although, the regression was not significant. Human development index and sex ratio in Orissa: It may be of interest to study whether the level of human development is associated with the level of sex ratio across 30 districts of Orissa (Table 9). Simple linear regression analysis with FMR (2001) as the dependant variable and HDI/GDI as independent variable gave the following regression equations: For age group 0 6 years: FMR 0 6 = x HDI; R 2 = 0.307; AN ANALYSIS OF SEX RATIO IN INDIAN SCENARIO (P=0.002) FMR 0 6 = x GDI; R 2 = 0.057; (Not significant) 161 For all age groups: FMR = x HDI, R 2 = ; (P=0.000) FMR = x GDI, R 2 = ; (P=0.002) ( - Highly Significant, p< 0.01) Following the criteria of UNDP for categorization of districts into high, medium and low human development, as per HDI 0.79 and above, HDI was observed between 0.50 to 0.78 and HDI between 0 to 0.499, respectively it was found that no district has HDI equal to 0.79 or above. The districts having low HDI are given in Table 10. Table 9 : Human development index and gender development index for district of Orissa Sr. Health Income index Overall HDI value HDI rank GDI value RDI rank District No. index literacy index 1. Angul Balasore Bargarh Bhadrak Bolangir Boudh Cuttack Deogarh Dhenkanal Gajapati Ganjam Jagatsinghpur Jajpur Jharsuguda Kalahandi Kandhamal Kendrapara Keonjhar Khurda Koraput Malkangiri Mayurbhanj Nabarangpur Nayagarh Nuapada Puri Rayagada Sambalpur Sonepur Sundergarh Orissa Source : Orissa Human Development Report, 2004.

8 162 Table 10 : Districts of Orissa with low HDI and GDI, as per 2001 Sr. Sex ratio, District HDI GDI No Rayagada Nabarangpur Koraput Gajapati Kandhamal Malkangiri Source : Orissa Human Development Report, The difference between HDI and GDI values is a sensitive indicator of basic gender inequality. The difference was relatively more pronounced in case of coastal districts compared to the districts known to be backward in terms of conventional indicators of development. However, the square of the rank correlation coefficient between HDI and GDI was (0.8483) 2 = , showing thereby moderate gender disparity among the districts of the state. It was important to note here that the six tribal dominated and least developed districts like Rayagada, Koraput, Nabarangpur, Gajapati, Kandhamal and Malkangiri with less gender inequality have favourable sex ratio. This lead to empirically confirming the disturbing hypothesis that the prosperity leads to decrease in sex ratio. Conclusion: The longitudinal study of the data of showed Agnihotri, S.B. (2000). Sex ratio patterns in, Sage Publication, New Delhi. REFERENCES increasing trend in favour of male child in case of both sex ratios at birth and in the age group (0-4) years. The data relating to 15 major states of revealed that child sex ratio (0-6 years) and DMR was positively correlated to the overall sex ratio, which was significant where as literacy rate, FLPR and HDI having positive correlation with FMR and were not significant. Taking into consideration the data from 1961 to 2001, it was found that while the total FMR and rural FMR showed a significantly declining trend for the state of Orissa and a declining trend in context, the urban FMR has an increasing trend. This might be due to urban awareness or migration. The FMR for ST community was higher than that for SC people and in turn SC FMR was higher than that for other caste s people. The longitudinal analysis of sex ratios of Orissa according to SC, ST and other castes revealed a declining trend but it was not significant in case of ST community, whereas, it was significant in case of SC community and highly significant in case of other castes, who are supposed to be more educated and developed. The most shocking fact was that in Orissa context the literacy rate was negatively correlated to FMR which was significant, where as it was positive in case of although not significant. This contradicts the assumption that education and awareness balances the FMR. The factors such as HDI and GDI both were found to be negatively correlated to FMR which was significant. Agnihotri, S.B., Changes in Sex Ratio Patterns in Orissa (2002). Is there an Epi-centre of female deficit, Demography, 31 (2) :