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Contributed by National Academy of Statistical Administration, India. Demographic Diversity in Districts of India. Background. Decentralised, district-based approach to population and planning. Demographic and development diversity across the districts is well known.
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Contributed by National Academy of Statistical Administration, India Demographic Diversity in Districts of India
Background • Decentralised, district-based approach to population and planning. • Demographic and development diversity across the districts is well known. • exogenous variables and policy and programme interventions affect demographic and development situation differentially across the districts.
Objectives • Analysis of demographic diversity across 640 districts of India on the basis of provisional data of the 2011 population census. • How demographic diversity across districts contributes to demographic diversity across states. • Policy and programme implications of demographic diversity across districts.
Diversity Index • Diversity is measured on a two-dimensional scale • The dimension of intensiveness • The dimension of extensiveness • Intensity is measured in terms of differentials and concentration; differentials are the most basic. • Extensiveness is the ratio of the population of the district to the population of the country.
Diversity Index • The index of the intensity of diversity is defined as Idc(v) = log(Vd/Vc) • The index of extensiveness is defined as Edc = Pd/Pc • The index of diversity is defined as Ddc(v) = Edc*(Idc(v))2
Diversity Index • The Diversity Index is always positive. The limiting value is zero meaning no diversity. • The higher is the index, the larger is the diversity. • It is a fuller measure of diversity as it takes into account the relative size of the population. • It can be decomposed.
Data and Variables • Provisional figures of 2011 population census. • The following 7 variables can be estimated: • Population density • Age composition index (P0-6/P) • Age composition index (P0-6/P7+) • Population sex ratio • Child sex ratio • Fertility index (P0-6/F7+)
Results • All the six variables vary widely across the districts. • The pattern of distribution is different for different variables. • The distribution of population density is highly skewed with a very high value of kurtosis. • In 11 districts, population density is more than 10 thousand persons per sq km.
Results • District Mumbai in Maharashtra has the highest population density in the country – more than 50 thousand per sq km. • In all districts of Delhi, population density is more than 3500 per sq km. • The distribution of the index of age composition and the index of fertility is very similar across districts.
Results • The skewness in the distribution of the two variables across districts is positive but not very large. • The Kurtosis is negative meaning that there is no district with exceptionally high value of these indexes. • The distribution of districts by sex ratio has been found to be negatively skewed.
Results • There are some districts with extremely low proportion of females to males. • In 9 districts, the sex ratio is less than 800 females for every 1000 males. • In Daman and Diu, there are only 533 females for every 1000 males. • In 101 districts, females outnumbered males at the 2011 population census.
Results • The distribution of child sex ratio is more sharply negatively skewed than the population sex ratio. • There are however only 6 districts where the child sex ratio is estimated to be less than 800. Four of these 6 districts are in Haryana. • There are only three districts where female children outnumbered males children.
Results • The distribution of the sex ratio of the population aged 7 years and above is very much similar to the sex ratio of the total population. • In Daman and Diu, there are less than 500 females 7+ for every 1000 males 7+. • In 117 districts, females outnumber males in this age group with Mahe leading the list.
Results • The district level diversity is the highest in case of population density but lowest in case of the sex ratio of the population aged 0-6 years. • The kernel density plots confirm this observation. These plots are always positively skewed because the diversity index used in the present analysis is by definition always positive.
Results • Most of the demographic diversity is the result of extreme situation in only a few districts. • Only 10 per cent of the districts account for • 75 per cent of the diversity in population density. • 52 per cent of the diversity in age structure. • 55 per cent of the diversity in population sex ratio. • 49 per cent of the diversity in child sex ratio. • 66 per cent of the diversity in sex ratio 7+. • 49 per cent of the diversity in fertility index.
Results • In case of population density, within state variation accounts for 52 per cent of the total inter-district diversity in the country. • In case of fertility index more than 71 per cent of the diversity is accounted by between state variations. • Between state component is larger than within state component in five variables.
Conclusions • Most of the demographic diversity is the result of the demographic situation in a few districts of the country. • This observation bears significance in the context of the persistence of social, economic, cultural and ecological diversity of the country. • Despite this diversity, the demographic situation is similar in most of the districts.
Conclusions • In general, the inter-district diversity is largely the result of the diversity across states. Within states, the diversity across the districts is relatively low. • Demographic diversity across states in India is well known. • Provisional results of 2011 population census confirm that this diversity continue to persist.
