Description
It is an effort to find out the extent to which income inequity is being affected by various macroeconomic factors.
ANALYSIS OF WEALTH DISPARITY IN INDIA
INTRODUCTION
INDIA SHINING
• Among the fastest growing economies at annual GDP rate of 5.8% for last two decades. • Foreign exchange reserves are at over $103 billion & the stock market is going through the roof. • Check out the mushrooming malls, improving telecom connectivity, booming industry.
• The government has ambitious plans to link rivers, to build superhighways both concrete and wireless, crisscrossing the nation.
INTRODUCTION
INDIA SHINING ???
? Indians still constitute 17 percent of the world population where we account for 35 percent of the poor and 40 percent of the illiterates. ? Despite sustained high economic growth rate, approximately ? 80% of its population lives on less than $2 a day ? 40% of children under the age of three are underweight ? a third of all men and women suffer from chronic energy deficiency. ? With economic reforms the wealth disparity has been on an increase, while metros and medium cities have experienced matchless growth, the rural areas are suffering from economic stagnation.
INTRODUCTION
ABOUT THE PROJECT : ? It is an effort to find out the extent to which income inequity is being affected by various macroeconomic factors.
? Our study is based on secondary data from various sources of government of India & survey conducted by National Sample Survey Organization(NSSO).
MACROECONOMIC INDICES
LORENZ CURVE ? Lorenz curve plots the cumulative percentage of total income received against the cumulative number of recipients.
? Graph showing the proportion of
the distribution assumed by the bottom y% of the values.
? It is often used to represent income distribution, where it shows for the bottom x% of households, what percentage y% of the total income they have.
MACROECONOMIC INDICES
? Gini Coefficient – measure of statistical dispersion developed
by the Italian statistician Corrado Gini. ? Measure of inequality of income or wealth. ? Range from 0 to 1. ? A value of 0 represents perfect equality, a value of 100 perfect inequalities. ? G=A/(A+B).
MACROECONOMIC INDICES
Figure 1: Gini's index (1950-2004)
45.00 40.00 35.00
30.00
25.00 20.00 15.00 10.00 5.00 0.00 1940
1950
1960
1970
1980
1990
2000
2010
OBSERVATIONS AND ANALYSIS
MEASURES OF WEALTH ? TOTAL HOUSEHOLD ASSETS -The NSS defines total household assets as comprising physical assets like land, buildings, livestock etc. ? NET WORTH : Net worth is defined as the total household assets net of the indebtedness of households (also provided in the surveys).
OBSERVATIONS AND ANALYSIS
PROBLEMS WITH THE DATA
? This methodology does not over sample the wealthy & since a large concentration of wealth is at the top end of the population; this is
problematic since a few large values can impact the summary
measures like the mean and the median. ? Generally all the respondents under-report their wealth holdings. So, inequality in asset holding is underestimated in the survey. ? Difficulty in obtaining the market prices for various kinds of assets. ? To counter these problems : consumption based deflators were used. Consumer Price Index (CPI) - for agricultural workers in order to deflate wealth data and for urban workers to deflate urban data.
OBSERVATION & ANALYSIS
GROSS DOMESTIC PRODUCT ? GDP has been steadily increasing from the year 1951-2004. ? The growth has been very sharp in the 1990’s during the post-
liberalization period.
? Gini’s Coefficient = 59.8581 + -2.16938 loge(GDP)
1400000 1200000 1000000 800000 600000 400000 200000 0 1940 -200000
GDP
1960
1980
2000
2020
OBSERVATIONS AND ANALYSIS
SUMMARY MEASURES
OBSERVATIONS AND ANALYSIS
The following observations can be made: ? Overall Per Capita assets have increased by 35%. ? Overall net worth has increased by 39%. ? Ratio of average per capita assets in urban areas to average per capita assets in rural areas is relatively constant at 1.5. ? If we analyze per capita net worth in the same segment i.e. rural and urban, we find that growth is faster in urban areas.
OBSERVATIONS AND ANALYSIS
INEQUALITY MEASURES
? The observations that can be made Gini coefficient has seen an increase of about 2 percent
for per capita net worth as well
as about 1 percent for per capita assets. ? From the values of per capita shares and per capita loans we
see that tremendous focus is given to the health of stock
market and the movement of corporate asset.
OBSERVATIONS AND ANALYSIS
OBSERVATIONS AND ANALYSIS
? So as to answer the wealth concentration levels, examination
of shares and cumulative shares by decile for both total per capita assets and per capita net worth. From the table below we find that 10 percent of the individuals possess a little over half of the total country’s wealth. ? Bottom 10 per cent possess a mere 0.4 per cent of the total wealth.
ANALYSIS
ANALYSIS
• The cumulative share of net worth per capita in 1991 is higher than (although close to) the corresponding figure for 2002. • This would indicate that if we construct Lorenz curves based on deciles, the Lorenz curve for 1991 would be close to but lie above the Lorenz curve for 2002. • We can observe that the absolute Lorenz curve for 1991 lies above the same for 2002. This indicates an unambiguous increase in inequality from 1991 to 2002 according to all standard absolute inequality measures.
• We can also note that the difference across these two points in time
between the absolute Lorenz curves is much more pronounced compared to the difference between the standard Lorenz curves.
ANALYSIS
• It is interesting to note too that growth in asset holdings has been fastest in the urban areas of the middle income
states, regions which include
dynamic urban centers such as Hyderabad and Bangalore.
CONCLUSIONS
• Two patterns in Indian wealth distribution:
? Majority of the population, witnessed increase in its absolute wealth levels during the period of liberalization.
? Impressive increases in wealth levels have been unequal across
different groups.
• Reason behind the increase in inequality probably is due to a
number of factors:
? notably includes technological change. ? In addition, increased international trade and the declining role of labour unions as other, probably lesser contributing factors.
CONCLUSIONS
• Effects of wealth inequality :
? It may itself limit the growth potential of economies by not allowing all economic agents to fully exploit the new opportunities. ? Greater inequality makes a greater proportion of the population
vulnerable to poverty.
? if not addressed can also lead to a backlash against economic liberalization, limiting the ability of economies to benefit from the globalization.
CONCLUSIONS
• Increasing trade and financial globalization have had
separately identifiable and opposite effects on income
distribution.
? Trade liberalization and export growth are found to be
associated with lower income inequality.
? Increased financial openness is associated with higher
inequality.
CONCLUSIONS
• The unbalancing impact of financial openness mainly felt
through foreign direct investment (FDI) and technological
progress appear to be working through similar channels
by increasing the premium on higher skills, rather than
limiting opportunities for economic advancement.
• There is also large differences in wealth holdings among
religious groups.
CONCLUSIONS
• For a given level of technology, greater access to
education would be expected to reduce income
inequality by allowing a greater share of the population
to be engaged in high-skill activities.
CONCLUSIONS
• Wealth levels rise with the educational level of the head of the
household.
? Individuals from the households with a graduate head have about twice the average wealth as those from one with a head who has a secondary school certificate. ? They also earn nearly five times that of individuals from a household with an illiterate head.
CONCLUSIONS
• Increase in the relative productivity of agriculture is expected to reduce income disparities by increasing the income of those employed in this sector. • In many developing countries a lot of the poor are still employed in the agricultural sector, so that an improvement in the export prospects of this sector tends to reduce inequality. • The share of agriculture employment tends to increase inequality, while the share of industry employment reduces it. • This is consistent with the idea that labour shifts from agriculture to industry raise the productivity of the agricultural sector where most poor are employed and decrease productivity in industry.
Thank You !!!
doc_207444003.pptx
It is an effort to find out the extent to which income inequity is being affected by various macroeconomic factors.
ANALYSIS OF WEALTH DISPARITY IN INDIA
INTRODUCTION
INDIA SHINING
• Among the fastest growing economies at annual GDP rate of 5.8% for last two decades. • Foreign exchange reserves are at over $103 billion & the stock market is going through the roof. • Check out the mushrooming malls, improving telecom connectivity, booming industry.
• The government has ambitious plans to link rivers, to build superhighways both concrete and wireless, crisscrossing the nation.
INTRODUCTION
INDIA SHINING ???
? Indians still constitute 17 percent of the world population where we account for 35 percent of the poor and 40 percent of the illiterates. ? Despite sustained high economic growth rate, approximately ? 80% of its population lives on less than $2 a day ? 40% of children under the age of three are underweight ? a third of all men and women suffer from chronic energy deficiency. ? With economic reforms the wealth disparity has been on an increase, while metros and medium cities have experienced matchless growth, the rural areas are suffering from economic stagnation.
INTRODUCTION
ABOUT THE PROJECT : ? It is an effort to find out the extent to which income inequity is being affected by various macroeconomic factors.
? Our study is based on secondary data from various sources of government of India & survey conducted by National Sample Survey Organization(NSSO).
MACROECONOMIC INDICES
LORENZ CURVE ? Lorenz curve plots the cumulative percentage of total income received against the cumulative number of recipients.
? Graph showing the proportion of
the distribution assumed by the bottom y% of the values.
? It is often used to represent income distribution, where it shows for the bottom x% of households, what percentage y% of the total income they have.
MACROECONOMIC INDICES
? Gini Coefficient – measure of statistical dispersion developed
by the Italian statistician Corrado Gini. ? Measure of inequality of income or wealth. ? Range from 0 to 1. ? A value of 0 represents perfect equality, a value of 100 perfect inequalities. ? G=A/(A+B).
MACROECONOMIC INDICES
Figure 1: Gini's index (1950-2004)
45.00 40.00 35.00
30.00
25.00 20.00 15.00 10.00 5.00 0.00 1940
1950
1960
1970
1980
1990
2000
2010
OBSERVATIONS AND ANALYSIS
MEASURES OF WEALTH ? TOTAL HOUSEHOLD ASSETS -The NSS defines total household assets as comprising physical assets like land, buildings, livestock etc. ? NET WORTH : Net worth is defined as the total household assets net of the indebtedness of households (also provided in the surveys).
OBSERVATIONS AND ANALYSIS
PROBLEMS WITH THE DATA
? This methodology does not over sample the wealthy & since a large concentration of wealth is at the top end of the population; this is
problematic since a few large values can impact the summary
measures like the mean and the median. ? Generally all the respondents under-report their wealth holdings. So, inequality in asset holding is underestimated in the survey. ? Difficulty in obtaining the market prices for various kinds of assets. ? To counter these problems : consumption based deflators were used. Consumer Price Index (CPI) - for agricultural workers in order to deflate wealth data and for urban workers to deflate urban data.
OBSERVATION & ANALYSIS
GROSS DOMESTIC PRODUCT ? GDP has been steadily increasing from the year 1951-2004. ? The growth has been very sharp in the 1990’s during the post-
liberalization period.
? Gini’s Coefficient = 59.8581 + -2.16938 loge(GDP)
1400000 1200000 1000000 800000 600000 400000 200000 0 1940 -200000
GDP
1960
1980
2000
2020
OBSERVATIONS AND ANALYSIS
SUMMARY MEASURES
OBSERVATIONS AND ANALYSIS
The following observations can be made: ? Overall Per Capita assets have increased by 35%. ? Overall net worth has increased by 39%. ? Ratio of average per capita assets in urban areas to average per capita assets in rural areas is relatively constant at 1.5. ? If we analyze per capita net worth in the same segment i.e. rural and urban, we find that growth is faster in urban areas.
OBSERVATIONS AND ANALYSIS
INEQUALITY MEASURES
? The observations that can be made Gini coefficient has seen an increase of about 2 percent
for per capita net worth as well
as about 1 percent for per capita assets. ? From the values of per capita shares and per capita loans we
see that tremendous focus is given to the health of stock
market and the movement of corporate asset.
OBSERVATIONS AND ANALYSIS
OBSERVATIONS AND ANALYSIS
? So as to answer the wealth concentration levels, examination
of shares and cumulative shares by decile for both total per capita assets and per capita net worth. From the table below we find that 10 percent of the individuals possess a little over half of the total country’s wealth. ? Bottom 10 per cent possess a mere 0.4 per cent of the total wealth.
ANALYSIS
ANALYSIS
• The cumulative share of net worth per capita in 1991 is higher than (although close to) the corresponding figure for 2002. • This would indicate that if we construct Lorenz curves based on deciles, the Lorenz curve for 1991 would be close to but lie above the Lorenz curve for 2002. • We can observe that the absolute Lorenz curve for 1991 lies above the same for 2002. This indicates an unambiguous increase in inequality from 1991 to 2002 according to all standard absolute inequality measures.
• We can also note that the difference across these two points in time
between the absolute Lorenz curves is much more pronounced compared to the difference between the standard Lorenz curves.
ANALYSIS
• It is interesting to note too that growth in asset holdings has been fastest in the urban areas of the middle income
states, regions which include
dynamic urban centers such as Hyderabad and Bangalore.
CONCLUSIONS
• Two patterns in Indian wealth distribution:
? Majority of the population, witnessed increase in its absolute wealth levels during the period of liberalization.
? Impressive increases in wealth levels have been unequal across
different groups.
• Reason behind the increase in inequality probably is due to a
number of factors:
? notably includes technological change. ? In addition, increased international trade and the declining role of labour unions as other, probably lesser contributing factors.
CONCLUSIONS
• Effects of wealth inequality :
? It may itself limit the growth potential of economies by not allowing all economic agents to fully exploit the new opportunities. ? Greater inequality makes a greater proportion of the population
vulnerable to poverty.
? if not addressed can also lead to a backlash against economic liberalization, limiting the ability of economies to benefit from the globalization.
CONCLUSIONS
• Increasing trade and financial globalization have had
separately identifiable and opposite effects on income
distribution.
? Trade liberalization and export growth are found to be
associated with lower income inequality.
? Increased financial openness is associated with higher
inequality.
CONCLUSIONS
• The unbalancing impact of financial openness mainly felt
through foreign direct investment (FDI) and technological
progress appear to be working through similar channels
by increasing the premium on higher skills, rather than
limiting opportunities for economic advancement.
• There is also large differences in wealth holdings among
religious groups.
CONCLUSIONS
• For a given level of technology, greater access to
education would be expected to reduce income
inequality by allowing a greater share of the population
to be engaged in high-skill activities.
CONCLUSIONS
• Wealth levels rise with the educational level of the head of the
household.
? Individuals from the households with a graduate head have about twice the average wealth as those from one with a head who has a secondary school certificate. ? They also earn nearly five times that of individuals from a household with an illiterate head.
CONCLUSIONS
• Increase in the relative productivity of agriculture is expected to reduce income disparities by increasing the income of those employed in this sector. • In many developing countries a lot of the poor are still employed in the agricultural sector, so that an improvement in the export prospects of this sector tends to reduce inequality. • The share of agriculture employment tends to increase inequality, while the share of industry employment reduces it. • This is consistent with the idea that labour shifts from agriculture to industry raise the productivity of the agricultural sector where most poor are employed and decrease productivity in industry.
Thank You !!!
doc_207444003.pptx