ECONOMIC DEVELOPMENT AND POVERTY IN INDIA: AN INTER STATE ANALYSIS

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1 International Journal of Economic Issues, Vol. 4, No. 2 (July-December, 2011): International Science Press ECONOMIC DEVELOPMENT AND POVERTY IN INDIA: AN INTER STATE ANALYSIS MANJIT SINGH Lecturer of Economics, Royal College of Business and Technology, Surrey, BC, Canada. SIMANPREET KAUR Lecturer of Economics, D.A.V. College, Amritsar (Punjab) India Economic development is the primary objective of the majority of the world s nations. This truth is accepted almost without controversy. Economic development is necessary for underdeveloped countries because it helps them in solving the problems of general poverty, unemployment, backwardness and low standard of living. On the other hand, economic growth is equally significant to developed countries as it helps them to maintain their existing growth rate (Todaro, 1977). The general belief is that development trickles down and spreads and everybody gains from development. Thus, the poor are also expected to gain and poverty is expected to decline. Poverty can be defined in many different ways. Some attempted to define it in numbers, while others have given a more ambiguous definition. According to Scottish Poverty Information Unit, Poverty is defined relative to the standards of living in a society at a specific time. People live in poverty when they are denied an income sufficient for their material needs and when these circumstances exclude them from taking part in activities which are an accepted part of daily life in that society ( scotland/ education/ int/ ms/ health / wealth/ poverty/ definitions.html). According to the House of Commons Scottish Affairs Committee ( scotland/ education/ int/ ms/ health/ wealth/ def of poverty/ definitions.shtml), There are basically three current definitions of poverty in common usage: absolute poverty, relative poverty and social exclusion. Absolute poverty is defined as the lack of sufficient resources with which to keep body and soul together. Relative poverty defines income or resources in relation to the average. It is concerned with the absence of the material needs to participate fully in accepted daily life. Social exclusion is a new term used by the government. The Prime Minister of UK ( scotland/ education/ int/ ms/ health/ wealth/ def of poverty/ definitions.shtml), described social exclusion as a shorthand label for what can happen when individuals or areas suffer from a combination of linked problems such as unemployment, poor skills, low incomes, poor housing, high crime environments, bad health and family breakdown.

2 344 / INTERNATIONAL JOURNAL OF ECONOMIC ISSUES In the new system, poverty would be measured with reference to basic facilities like quality education, good health and clean drinking water availability, said Montek Singh Ahluwalia, Deputy Chairman of the Planning Commission ( southasia.oneworld.net/ todaysheadlines/ India-alters-its-definition-of-poverty21/02/2009). In the context of economic growth and poverty, some issues arise whether the reduction of poverty and acceleration of growth conflict? Or are they compliments? Traditionally, it was opined that rapid growth was bad for poor, because they would be bypassed and marginalized by the structural changes in the modern growth. Beyond this, there had been considerable concern in policy circles that public expenditures required for reduction of poverty would entail a reduction in rate of growth. However, there are following reasons why policies aimed towards reducing poverty level have not lead to slower rate of growth: First, widespread poverty creates conditions in which the poor have no access to credit, are unable to finance their children s education and in the absence of physical or monetary investment opportunities, have many children as a source of old age financial security. Together these factors cause per capita growth to be less than what it would be if there were growth equality (Todaro and Smith, 2003). Second, the low incomes and low levels of living for poor, which are manifested in poor health, nutrition and education, can lower their economic productivity and thereby lead directly and indirectly to slower growing economy. Strategies to raise the incomes and levels of living of the poor would therefore contribute not only to their material well being but also to the productivity and income of the economy as a whole (Dasgupta and Ray, 1987). Third, raising the income levels of the poor would stimulate an overall increase in the demand for locally produced necessary products like food and clothing, whereas the rich tend to spend more of their additional incomes on imported luxury goods. Rising demand for local goods provides a greater stimulus to local production, local employment and local investment. Such demand thus creates the conditions for rapid economic growth and a broader participation in that growth (World Bank, 1979). Last, a reduction of mass poverty can stimulate healthy economic expansion by acting as a powerful material and psychological incentives to economic progress. Poverty imposes an oppressive weight on India, especially in rural areas where close to 80 per cent of Indian poor live. Despite decades of efforts at poverty alleviation, the absolute number of poor has doubled since independence i.e. in India today has the largest number of poor people on the planet. India also has the greatest concentration of rural households that are totally landless, i.e. 60 million households. Landless and rural poverty are closely linked ( news/ India/definition-of-poverty-poor-cpas/106704/). In early 1950s, it was widely believed that eradication of poverty was dependent on economic growth for which increase in the level of domestic savings and investment were considered essential requirements. Some economists believed that there is trade off between growth and equity while others viewed the process as sequential one. Poverty has multiple effects on economic growth. These include the effects of levels and standards of consumption inadequate for nutritional and physical health, safe and healthy living, accumulation of knowledge and skills, child care and protection

3 ECONOMIC DEVELOPMENT AND POVERTY IN INDIA: AN INTER-STATE ANALYSIS / 345 and advancement of the welfare of future generations (Pritchett and Summers, 1996). Furthermore, when poverty causes health problems and energy deficiency, it may contribute to irregular work and limited capacity for extended periods of work. Deficiencies in levels of education and training directly constrain productivity. In these various ways, human poverty may cause under-achievement of productivity and economic growth. There is thus a causal link running from poverty to economic growth (Bourne, 2008). There is also a causal connection from economic growth to poverty. Employment and incomes are lower during recessions than during growth periods. Economic volatility causes fluctuations in employment and incomes, with particularly stronger influence on the employment and incomes of lower skilled workers. The poverty effects are magnified because poor people have weaker and less effective mechanisms for coping with loss of employment and income. The absence of personal coping mechanisms would not be so problematic if government financed safety nets were adequate. This generally is not the case and the capacity to finance what exists is usually vitiated by slow economic growth or recessions (Bourne, 2008). Growth trickles down and spreads was the wide belief among many developing countries when they treaded on the path of development. As a consequence of this belief no need was felt for undertaking special programs to create employment opportunities, alleviate poverty and reduce income inequalities. But the hopes of solving problems with growth got belied with failure of trickle down effect (Thirwall, 1972). Thus, reducing poverty and providing for minimum needs is the ultimate yardstick against which development may be measured. These have been major concerns of the developing countries. Experience suggests that reducing poverty requires coordinated macroeconomic and sectoral efforts and reforms. High rates of economic growth, especially in agriculture, have contributed to rapid decreases in poverty incidence in India and elsewhere. Good infrastructure, a well-educated and mobile labour force, effective institutions, and a stable political and social environment are enabling conditions. Conversely, low levels of education and ill-health, exacerbated by social and structural barriers, reduce opportunities for escaping poverty and improving quality of life. What factors are behind slowdown in poverty reduction? First, the slowing of poverty reduction may partly be a statistical artifact the National Accounts Statistics (NAS) reported a faster growth of consumption and cereal availability than the household surveys. The differences between the surveys and the NAS suggest a need for better statistics. Second and a worrisome possibility is that growth, including agricultural growth, which was previously identified as a major factor in reducing poverty, has become less efficient in reducing poverty in the 1990s. Third, while some of the better off states have exhibited rapid growth and reduced poverty, most of the poorer states have increasingly lagged behind. As a result of economic growth, poverty has reduced to a great extent but it has not reduced in states like Bihar, Orissa. Thus, there arises need to examine the determinants of poverty and poverty-development linkage in India. The present study has been undertaken in this context. The overall objective of the study is to examine the deprivations and poverty in the light of experience of Indian states.

4 346 / INTERNATIONAL JOURNAL OF ECONOMIC ISSUES An attempt was made to analyze the trends in poverty in 17 major states of India. The analysis of trends in poverty has been made at three points of time depending upon the availability of data i.e , and In India, the estimates of poverty have been basically made by NSS through its different consumption rounds. The Planning Commission has also been estimating incidence of poverty. On the basis of recommendations of Task Force on Projections of Minimum Needs and Effective Consumption Demand in September 1989, Planning Commission constituted an Expert Group on Estimation of Proportion and Number of Poor under the chairmanship of Prof. D.T. Lakhadawala, in order to look into the methodology for estimation of poverty at national and state levels, and also to go into the question of re-defining the poverty line, if necessary. 1. VARIABILITY IN POVERTY AMONG THE STATES To examine the variability of poverty among the states, coefficients of variation were worked out (Tables 1, 2 and 3). In , the coefficient of variation in poverty level among the 17 major states was per cent. In , the coefficient of variation reduced to per cent but again in , the C.V. increased to per cent. This indicates that during to , there was decrease in poverty in both developed and less developed states but during to , while the poverty in the developed states decreased more, in the less developed states, the reduction in poverty was relatively small. This led to increase in variability of poverty among the states in In case of indicators of economic development, the inter-states disparities in literary rate ( ) decreased throughout the period , and In case of variable value of industrial output per worker ( ), the inter state disparities increased during to but decreased in In case of variables like per capita income (X 1 ), % percentage of rural population ( ) percentage of labour force in agricultural sector ( ) and annual per capita food production ( ), the inter-state disparities increased during , and In case of variables like share of primary sector in NSDP ( ), share of secondary sector in NSDP ( ), share of tertiary sector in NSDP ( ), percentage of urban population ( ), per capita power consumption ( ), number of registered motor vehicle per lakh of population ( ), annual per capita milk production ( ) and number of doctors per lakh of population ( ) the inter state disparities decreased during to but increased in CORRELATION MATRIX ( ) Correlation coefficients between different pairs of the indicators of economic development and also between poverty and indicators of economic development were worked out for , and The correlation matrix for , given in Table 4, shows that the correlation coefficients for majority of pairs of the indicators were significant. Further, the correlation coefficients between poverty (Y) and per capita income (X 1 ); poverty and

5 ECONOMIC DEVELOPMENT AND POVERTY IN INDIA: AN INTER-STATE ANALYSIS / 347 Table 1 (Year ) % of Per % of % of % of % of % of Per No. of Annual Literacy % of % of Value of Annual No. of Popula- Capita Primary Secondary Tertiary Urban Rural Capita Registered Per Rate Labour Labour Industrial Per Doctors tion Income Sector in Sector Sector Popula- Popula- Power Motor Capita (%) Force Force in Output Capita Per Below (Rs.) NSDP in in tion tion Consump- Vehicles Milk in Non- Agri- Per Food Lakh Poverty NSDP NSDP tion (kwh) Per Lakh Produc- Agri- culture Worker Produc- of Line of Popula- tion culture Sector (Rs. tion Population (Rs. Lakh) Sector Thousand) (Rs. Lakh) tion States Y X 1 Andhra Pradesh Assam Bihar Gujarat Haryana Himachal Pradesh Jammu and Kashmir Karnataka Kerala Madhya Pradesh Maharashtra Orissa Punjab Rajasthan Tamilnadu Uttar Pradesh West Bengal Cofficient of Variation

6 348 / INTERNATIONAL JOURNAL OF ECONOMIC ISSUES Table 2 (Year ) % of Per % of % of % of % of % of Per No. of Annual Literacy % of % of Value of Annual No. of Popula- Capita Primary Secondary Tertiary Urban Rural Capita Registered Per Rate Labour Labour Industrial Per Doctors tion Income Sector in Sector Sector Popula- Popula- Power Motor Capita (%) Force Force in Output Capita Per Below (Rs.) NSDP in in tion tion Consump- Vehicles Milk in Non- Agri- Per Food Lakh Poverty NSDP NSDP tion (kwh) Per Lakh Produc- Agri- culture Worker Produc- of Line of Popula- tion culture Sector (Rs. tion Population (Rs. Lakh) Sector Thousand) (Rs. Lakh) tion Y X 1 Andhra Pradesh Assam Bihar Gujarat Haryana Himachal Pradesh Jammu and Kashmir Karnataka Kerala Madhya Pradesh Maharashtra Orissa Punjab Rajasthan Tamilnadu Uttar Pradesh West Bengal Coefficient of Variation

7 ECONOMIC DEVELOPMENT AND POVERTY IN INDIA: AN INTER-STATE ANALYSIS / 349 Table 3 (Year ) % of Per % of % of % of % of % of Per No. of Annual Literacy % of % of Value of Annual No. of Popula- Capita Primary Secondary Tertiary Urban Rural Capita Registered Per Rate Labour Labour Industrial Per Doctors tion Income Sector in Sector Sector Popula- Popula- Power Motor Capita (%) Force Force in Output Capita Per Below (Rs.) NSDP in in tion tion Consump- Vehicles Milk in Non- Agri- Per Food Lakh Poverty NSDP NSDP tion Per Lakh Produc- Agri- culture Worker Produc- of Line (kwh) of Popula- tion culture Sector (Rs. tion Population (Rs. Lakh) Sector Thousand) (Rs. Lakh) tion Y X 1 Andhra Pradesh Assam Bihar Gujarat Haryana Himachal Pradesh Jammu and Kashmir Karnataka Kerala Madhya Pradesh Maharashtra Orissa Punjab Rajasthan Tamilnadu Uttar Pradesh West Bengal Coefficient of Variation

8 350 / INTERNATIONAL JOURNAL OF ECONOMIC ISSUES X 1 1 Table 4 Correlation Matrix ( ) X 1 Y Y annual per capita milk production ( ); poverty and registered motor vehicles per lakh of population ( ); poverty and annual per capita food production ( ) and poverty and per capita power consumption ( ) were negative and significant at one per cent level. 3. STEP-WISE MULTIPLE REGRESSION ANALYSIS ( ) In order to examine the set of determinant of poverty, step-wise multiple regression analysis was applied. The explanatory variables were added on the basis of correlation coefficient with the dependent variable (Poverty = Y), after checking multi collinearity with the previously included variables. The results given in Table 5 show that regression coefficient of per capita income was negative and significant and this variable explained 54.5 per cent variations in poverty. In the second step, when per capita milk production ( ) was added, regression coefficient of per capita income (X 1 ) was negative and significant, while of annual per capita milk production ( ) was negative but non-significant. Both there variables explained 56.8 per cent variations in poverty. In the third step, when the variable number of registered motor vehicles ( ) was added, the regression coefficient of ( ) was negative and significant, while of X 1 and were negative but non-significant. There three variables together explained 69.3 per cent variations in poverty. In the next step, when the variable annual per capita food production ( ) was included, then the regression coefficients of all the explanatory variables except of per capita food production ( ) were negative but non-significant. These four variables together explained 71.9 per cent variations in poverty.

9 ECONOMIC DEVELOPMENT AND POVERTY IN INDIA: AN INTER-STATE ANALYSIS / 351 Y = X 1 (7.235) (-4.242) r 2 = 0.545, F = Y = X (5.745) (-2.211) (-0862) R 2 =.568, R 2 =.507 F = Table 5 Results of Step-wise Regression Analysis ( ) Y = X (5.195) (-1.145) (-1.678) (-2.294) R 2 =.693, R 2 =.622 F = Y = X (5.117) (-1.537) (-1.862) (-1.374) (1.062) R 2 =.719, R 2 =.625 F = Y = X (5.465) (-2.047) (-1.538) (-1.816) (.682) (1.368) R 2 =.760, R 2 =.651 F = Further, when per capita power consumption ( ) was added, the regression coefficients of X 1, and were negative and non-significant; of and were positive and non significant. The five explanatory variables explained 76 per cent variations in poverty. 4. CORRELATION MATRIX ( ) The correlation matrix for , given in Table 6, shows that again correlation coefficients for majority of the pairs of the indicators were significant. Further, the correlation coefficients between poverty (Y) and annual per capita milk production; poverty and annual per capita food production ( ); poverty and percentage of labour force in non-agricultural sector ( ) and poverty and per capita income (X 1 ) were negative and significant at one per cent level. But the correlation coefficient between poverty and percentage of labour force in agricultural sector (X 12 ) was positive and non-significant. 5. STEP-WISE MULTIPLE REGRESSION ANALYSIS ( ) In order to examine the determinants of poverty, step-wise multiple regression analysis was applied.

10 352 / INTERNATIONAL JOURNAL OF ECONOMIC ISSUES X 1 1 Table 6 Correlation Matrix ( ) X 1 Y Y The results given Table 7 show that regression coefficients of annual per capita milk production ( ) was negative and significant and this variable explained 47.5 per cent variations in poverty. In the second step, when the annual per capita food production ( ) was added, regression coefficient of both and were negative and non-significant. Both these variables explained 47.6 per cent variations in poverty. In the third step, the variable percentage of labour force in non -agricultural sector ( ) was added, the regression coefficient of was negative and significant, while of and were negative and non-significant. These three variables together explained 65.6 per cent variations in poverty. In the next step, the variable percentage of labour force in agricultural sector ( ) was included, then the regression coefficients of, and was negative and non significant and of was positive and non-significant. These four variables together explained 65.7 per cent variations in poverty. Further, when per capita income (X 1 ) was added, the regression coefficients of,, and X 1 were negative and non-significant and of positive and non significant. These five variables together explained 68.8 per cent variation in poverty. 6. CORRELATION MATRIX ( ) The correlation matrix for ; given in Table 8, shows that correlation coefficients for majority of the pairs of the indicators were significant. Further, the correlation coefficients between poverty (Y) and percentage of labour from in non agricultural sector ( ); poverty (Y) and per capita income (X 1 ); poverty and annual per capita food production ( ) and poverty (Y) and no. of registered motor vehicles per lakh of population ( ) were negative and significant at the one per cent level.

11 ECONOMIC DEVELOPMENT AND POVERTY IN INDIA: AN INTER-STATE ANALYSIS / 353 Y = (12.821) (-3.684) r 2 =.475 F = Y = (7.193) (-.612) (-.0161) R 2 =.476, R 2 =.401 F = Table 7 Results of Step-wise Regression Analysis ( ) Y = (7.360) (-1.032) (.344) (-2.612) R 2 =.656, R 2 =.577 F = Y = X (.127) (-.996) (.338) (-.126) (-.112) R 2 =.657, R 2 =.543 F = Y = X 1 (.199) (-.608) (.010) (-.193) (-.183) (-1.043) R 2 =.688, R 2 =.546 F = Table 8 Correlation Matrix ( ) X 1 Y X Y

12 354 / INTERNATIONAL JOURNAL OF ECONOMIC ISSUES But the correlation coefficient between poverty (Y) and percentage of labour force in agricultural sector ( ) was positive and non-significant. 7. STEP-WISE MULTIPLE REGRESSION ANALYSIS ( ) The results of step-wise regression analysis given Table 9 show that regression coefficient of percentage of labour force in non-agricultural sector was negative and significant and this variable explained 33.6 per cent variations in poverty. In the second step, when percentage of labour force in agriculture sector ( ) was added, regression coefficient of percentage of labour force in non-agricultural sector ( ) was negative and significant. The regression coefficient of percentage of labour force in agricultural sector ( ) was also negative and significant. Both these variables explained 50.5 per cent variations in poverty. Y = (5.170) (-2.754) r 2 =.336 F = Table 9 Results of Step-wise Regression Analysis ( ) Y = (2.794) (-2.795) (2.789) R 2 =.505 R F = Y = X 1 (2.830) (-2.828) (-2.822) (-1.773) R 2 =.625, R 2 =.538 F = Y = X (3.451) (-3.446) (-3.441) (-2.809) (-2.875) R 2 =.778, R 2 =.704 F = Y = (3.337) (-3.333) (-3.328) R 2 =.783, R 2 =.684 F = In the third step, the variable per capita income (X 1 ) was added, the regression coefficient of and was negative and significant while of X 1 was negative but non significant. These three variables together explained 62.5 per cent variations in poverty.

13 ECONOMIC DEVELOPMENT AND POVERTY IN INDIA: AN INTER-STATE ANALYSIS / 355 In the next step, the variable value of industrial output per worker ( ) was included, then the regression coefficients of all the variables were negative and significant. These four variables together explained 77.8 per cent variations in poverty. Further, when no. of registered motor vehicles per lakh of population ( ) was added, the regression coefficients of X 1,, were negative and significant; of positive and non-significant and of was negative and non-significant. The five explanatory variables explained 78.3 per cent variation in poverty. The results indicate that the variables per capita income, number of registered motor vehicles, milk production and power consumption, labour force in nonagricultural sector and per capita food production were significant variables in affecting poverty. The significance of variables changed from per capita income to other variables during to CONCLUSIONS To examine the variability of poverty among the states, coefficients of variation were worked out. In , the coefficient of variation in poverty level among the 17 major states were per cent. In , the coefficient of variation reduced to per cent but again in , the C.V. increased to per cent. This indicates that during to , there was decrease in poverty in both developed and less developed states but during to , while the poverty in the developed states decreased more, in the less developed states, the reduction in poverty was relatively small. As a result, the variability increased. The results of step-wise multiple regression indicate that the variables per capita income, number of registered motor vehicles, milk production and power consumption, labour force in non-agricultural sector and per capita food production were significant variables in affecting poverty. The significance of variables changed from per capita income to other variables during to IMPLICATIONS Following implications are derived from the present study: First, no doubt the incidence of poverty has reduced in almost all the states, but the relatively developed states have been more successful in reducing poverty than the backward states. Therefore, Central Government should concentrate more on alleviating poverty in states like Bihar, Orissa and Madhya Pradesh. Second, the poverty reducing impact of per capita income has reduced during to Therefore, targeted programs for helping the poor should be started for reducing poverty. Third, rather than transferring income to the poor, employment should be provided to them so that they also contribute to the national development. In this context, the programs like National Employment Guarantee Scheme are to be welcomed. Last, more infrastructural facilities and public utilities be provided in the backward states so that they experience rapid development and are able to reduce poverty.

14 356 / INTERNATIONAL JOURNAL OF ECONOMIC ISSUES References Bhalla, Surjit S. (2000), FAQs on Poverty in India, Seminar at the Delhi School of Economics, July 20, Bourne, O. E. (2008), Economic Growth, Poverty and Income Inequality, University of West Indies, St. Augustine Campus, Trinidad and Tobago. Dasgupta, Partha and Debraj Ray (1987), Inequality as a Determinant of Malnutrition and Unemployment, Economic Journal, Vol. 97(1), pp Pritchett, L. and Summers, L. H. (1996), Wealthier is Healthier, Journal of Human Resources, Vol. 31, pp Thirlwall, A. P. (1972), A Cross Section Study of Population Growth and the Growth of Output and Per Capita Income in a Production Function Framework, The Manchester School of Economics and Social Studies, Vol. 40, (4). Todaro, M. P. (1977), Economic Development, Pearson Education, Delhi. Todaro, M. P. and Stephen C. Smith (2003), Economic Development (Eighth Edition), Pearson Education, Delhi. World Bank, World Development Report, Various Issues, Oxford Press, New York.

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