Convergence clubs

Figure 5.17 shows the assessment of convergence clubs by using a graphical plot. In case of LEB, the clubs were comprised of three groups: less than or equal to 50 years, 51-60 years, 61-70 years and more than 70 years. In 1981, Uttar Pradesh was the only state with LEB less than 50 years. At this point, majority of the states fall in between LEB 51-60 years and no state with LEB more than 70 years. However, by 2006 the Uttar Pradesh joined the club of LEB ranging between 51-60 years. Only Kerala has LEB above 70 years and majority of the states were concentrated in the club of LEB levels ranging between 61-70 years.

Convergence clubs in terms of trends in IMR levels of states during 1981-2011 is presented in Figure 5.18. The results showed that in 1981, states like Assam, Bihar, Gujarat, Haryana, Madhya Pradesh, Orissa, Rajasthan and Uttar Pradesh were in the club of IMR above 100. Kerala was the only state in the clubs-III with IMR range of 25-49. However, there was no state with IMR less than 25. By the year 2011, there is no state with IMR above 100. Greater number of states became part of the club with IMR range of 25-49. However, the three states of Kerala and Tamil Nadu in the leading club with IMR of less than 25.

0.05655

0.05155

0.04189

0.020 0.030 0.040 0.050 0.060

1992-93 1998-99 2005-06

Standard Deviation

Period

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122 socioeconomic groups, the trends in convergence clubs by socioeconomic group were not assessed for these indicators. The results presented in figure 5.19 shows intriguing

200-300 Karnataka, Punjab Karnataka Bihar, Madhya Pradesh, Orissa

123 Karnataka (Richest); Kerala (OBC, Others; Hindu, Muslim, Others; Richer, Richest), MP (Muslim; Richest); Maharashtra (SC, ST, OBC]. Overall, the convergence clubs assessment by socioeconomic groups suggests huge variation in mortality transition across the socioeconomic groups and on set of mortality transition across the socioeconomic groups.

124 Figure 5.20. Changing patterns of infant mortality clubs among socioeconomic groups of major states of India, 1992-2006

Period IMR range

Poorer); Orissa (Poorest); Rajasthan (Poorer);

UP (SC, OBC; Poorer) Others; Hindu, Muslim; Middle); Karnataka (SC, ST, OBC, Others; Hindu; Poorer, Middle);

Hindu, Muslim; Poorer);UP (ST, Others; Muslim;

Middle, Richer); WB (SC, ST; Muslim; Poorer)

A.P. (SC, ST, OBC, Others; Hindu, Muslim;

Poorest, Poorer, Middle); Assam (SC, ST, OBC, Others; Hindu, Muslim; Poorest, Poorer, Middle, Richer); Bihar (SC, OBC, Others; Hindu, Muslim; Poorest, Poorer, Middle, Richer, Richest); Gujarat (SC,ST, OBC; Hindu; Poorer, Middle, Richer);

Haryana ( SC, OBC; Muslim; Poorer, Richer); Karnataka (SC, OBC; Hindu;

Poorest, Poorer, Middle); MP (SC, ST, OBC, Others; Poorest, Middle); Maharashtra (Poorest, Middle); Orissa (SC, ST, OBC, Others; Poorest, Poorer, Richer); Punjab (Richer); Rajasthan (SC, ST, OBC, Others;

Hindu, Muslim; Poorest, Poorer, Middle, Richer); TN (Poorest, Poorer); UP (SC, OBC, Others; Hindu, Muslim; Poorest, Poorer, Middle, Richer, Richest); WB (Other Caste;

Muslim; Poorest, Poorer, Middle, Richer)

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Club-III 25-49

A.P. (Muslim); Kerala (Muslim, Others);

Maharashtra (Muslim); Punjab (Others Caste;

Others Religion); Rajasthan (Muslim)

A.P. (Others Caste; Muslim; Richer); Assam (SC, OBC; Richer); Bihar (Richer); Gujarat (Muslim; Richer); Haryana(Religion others;

Richer) Karnataka (Richer); Kerala (Poorer);

Maharashtra (Others Caste; Muslim; Middle, Richer); Orissa (Richer); Punjab (Others Caste;

Poorer); T.N. (SC; Middle, Richer); WB (Others Caste; Middle)

A.P. (Richer, Richest); Gujarat (Others Caste; Muslim; Richest); Haryana(Others Caste; Hindu; Middle, Richest); Karnataka (ST, Others; Muslim; Richer, Middle);

Kerala (Middle); MP (Hindu; Poorest, Poorer, Middle, Richer); Maharashtra (Poorer, Richer, Richest); Orissa (Richest);

Punjab (SC, Others; Hindu, Others; Middle;

Richest); Rajasthan (Richest); T.N. (SC, OBC; Hindu; Middle); WB (SC; Hindu)

Club-IV Less than 25

Kerala (Hindu) Kerala (OBC, Others; Hindu, Muslim, Others;

Middle, Richer); WB (Richer) Assam (Richest); Karnataka (Richest);

Kerala (OBC, Others; Hindu, Muslim, Others; Richer, Richest) , MP (Muslim;

Richest); Maharashtra (SC, ST, OBC, Others; Hindu, Muslim, Others); T.N. (Others Religion; Richer, Richest); WB (Richest) Source: Three rounds of NFHS (1-3)

126

127 5.5. Discussion

This chapter used both standard and inequality based convergence metrics to test the hypothesis of convergence in averages, absolute and relative distribution of mortality rates in India focusing on 15 major states and socioeconomic groups for three key mortality indicators. The results of trend analyses for mortality averages and inequalities of selected indicators suggested varying patterns. The gap across the states in average mortality in terms of IMR and MMR is closing. However, the gap remains the same for LEB and showed a setback in convergence trend in the recent period, 1998-2006. The trends in DMM and Gini coefficient suggested a decline in both absolute and relative dispersion initially, but indicated a reversal for the recent period, 2001-2008. The trends in socioeconomic inequalities in IMR suggested an increase in inequality for 6 out of 15 states.

A range of convergence metrics tested for averages of mortality and inequalities in this study revealed varying patterns of convergence by type of measure and time periods.

The results indicated convergence in averages of mortality indicators, but with decreasing volume and speed of convergence for the recent period. The convergence in averages was principally driven by greater progress in laggard states and resultant catching-up process. However, the results present the evidence of some recent setback in convergence in absolute and relative inequalities in LEB, socioeconomic and relative inequalities in IMR. From the late 1990s, the results suggested progress in converging trend in mortality inequalities was being replaced by diverging trend. These anomalies may arise because of many reasons, but here, I point out few important reasons. First, the divergence in LEB for recent periods is more likely to be the result of unequal rate of progress in reduction of adult mortality across the states. Second, India has adapted globalisation, liberalisation and privatisation policies since 1991, and different states of India benefited differently from these policies. Such differences may have led to increase in the relative income inequality across states and socioeconomic groups in post 1990s and consequently widened the gaps in both child and adult mortality. Third, explanations can also drawn from previous studies, for instance, Wagstaff (2002) provided alternative reasons for such situation: ‘increasing per capita income leads to absolute decline in mortality averages, but increase in relative dispersion of mortality across the different population groups of the developing countries’ as current experience

128 of India suggests. This is mainly due to unequal rate of progress across the population sub groups. Fourth, the difference in both absolute and relative convergence process across the indicators can be attributed to nature of the indicators and factors affecting on them.

Moreover, the data analysed for IMR and MMR belongs to more recent compared to LEB, therefore, the convergence observed in averages of IMR and MMR can also attributed to this. At the same time, one could expect a re-convergence of states in terms of LEB in the last 7-8 years, if the latest data of LEB is available in the near future.

Taken as a whole, from these results, it can be said that improving state average mortality status may not always result in convergence in relative mortality situation of populations. India is a country of huge geographic, socioeconomic and cultural diversity. Therefore, state specific policies play a critical role in explaining the intra-state disparities in mortality.

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CHAPTER 6