Abstract
This paper compares the disparities of well-being among sixteen of the most populous states of India in the three years—1991, 2002 and 2012. It finds that while disparity increased between 1991 and 2012 and also between 2002 and 2012, what happened to it between 1991 and 2002 is ambiguous. The major differential contribution of the paper is methodological. By taking a Lorenz dominance approach, we show that, in contrast with the findings in the existing literature, those of this paper—both the definitive and the ambiguous ones—are robust: they do not depend on the use of any specific inequality index as the measure of disparity. Furthermore, the task of reducing well-being matrices to vectors (which is a part of the exercise) has been handled in a way that seems to be logically more satisfactory than the method followed in the literature. Among other distinguishing features of the paper is the fact that economic well-being is measured by asset ownership which, we have argued, is a better indicator of this aspect of well-being than income (which is the measure that is customarily used in this context). Moreover, unlike the existing literature, our time coverage includes the decade of the 2000s.
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Notes
- 1.
The terminology is borrowed from the literature on convergence between countries. There is said to be σ-convergence if the (cross-sectional) dispersion of income levels among countries decreases over time. On the other hand, there is (absolute) β-convergence if countries with lower income levels have higher growth rates of income. It is known that σ-convergence implies β-convergence. If there are just two countries, the converse is also true. In the general case, however, there can be β-convergence without there being σ-convergence (see, for instance, Martin and Sunley 1998 for a discussion of these issues).
- 2.
From 2010, the UNDP started using the geometric (rather than the arithmetic) mean as the aggregator function. It can be checked, however, that the problem noted in the text in connection with the need to ensure that the MLDR satisfies the basic requirements of such a relation would persist even if the arithmetic mean is replaced by the geometric mean as the averaging formula. In fact, it would also persist for some of the other averaging formulas, for instance, the one based on the idea of the (Euclidean) distance of the actual values of achievements of a state from the “ideal” situation in which the state would enjoy maximal possible values of the different achievements (see Noorbakhsh 1998; Banerjee and Kuri 2015). The theoretical literature also contains yet other suggested aggregation procedures (see, for instance, the class of formulas derived axiomatically in Mishra and Nathan 2014 and the other procedures reviewed there). Most of these, however, have not yet been applied to the study of regional disparity in India.
- 3.
Results reached by contributions (such as Roy and Bhattacharjee 2009) that only report the absence of evidence in support of the convergence hypothesis and let the matter rest at that, however, come close in spirit to this part of our finding.
- 4.
Among the contributions in the existing literature, the study by Banerjee and Kuri (2015) covers the longest time span, 1971–2001. Needless to say, we are talking here about the trends of regional disparity of well-being. So far as disparity of income alone is concerned, there are many studies that cover the 2000s.
- 5.
Reflexivity of D means that if A = B, then A DI B; transitivity means that if A D B and B D C, then A D C.
- 6.
In the theory of inequality measurement, one also comes across two other general (i.e. non-equity) conditions. One of these is called scalar multiplication (SM). It requires that if D is a (weak) dominance relation on the set of the well-being matrices in their original (i.e. non-normalised) forms, then for any matrix A and for any positive scalar k, A DI (kA). The other condition is called Population Replication Invariance (PRI) which says that if B is a k-fold replication of the states in A for any positive integer k (i.e. if A is an n × m well-being matrix and if B is the nk × m matrix obtained by writing A k times), then, again, A DI B. However, as stated in the text, under our procedure all well-being matrices are normalised to start with. It is easily seen that SM is, therefore, trivially satisfied by any D. Again, throughout our analysis n is kept fixed. PRI also will, therefore, be trivially satisfied.
- 7.
It also satisfies the conditions of SM and PRI mentioned in Note 6.
- 8.
In our data source (RBI 2016), life expectancy is defined as “the average number of years that is likely to be lived by an infant exposed to the same mortality conditions until they die”. The source gives information on this variable in the form of overlapping 5-yearly moving averages starting from 1991 to 1995. The last 5-year period for which information is available is 2009–2013. For each of the three years of our interest, 1991, 2002 and 2012, we have taken the average value of the 5-year period that is centred on a year which is nearest to it.
- 9.
We mention in passing that even for those who wish to use income as the measure of economic well-being, it may not be a good idea to use PCNSDP as the proxy variable. PCNSDP is a macroeconomic category. Its value is taken from the National Accounts Statistics (NAS). In the Indian economy, it has been known for quite some time now that there is often a large gap between estimates of the rate of change of per capita consumption based on NAS and that based on the household consumer expenditure surveys of the NSSO. Macroeconomic data taken from the NAS do not seem to reflect correctly what is happening at the ground level. While time series data on household income are still not available from these surveys, there are reasons to suspect that there would be a similar problem with respect to the rate of change of per capita income estimated from the NAS. In the present context, this casts doubt on the advisability of comparing between the levels of economic well-being of a state in different years (or between the levels of well-being of different states in a given year) on the basis of macroeconomic categories such as PCNSDP. Using the NSSO figures for average Monthly Per Capita Expenditure (MCPE) of the states may be a better strategy.
- 10.
There was also a change in 2012 in the way in which land and buildings were valued. While in the two earlier surveys, these were valued at prices reported by the interviewees; normative values were used in 2012. We have not found it possible to adjust the figures of the earlier surveys since the normative values for these years do not seem to be available. We believe, however, that since our focus is on the inequality of average asset ownership among the states (rather than on the average values of the assets per se), this omission does not seriously affect the qualitative results of the paper.
References
Anand, I., & Thampi, A. (2016). Recent trends in wealth inequality in India. Economic and Political Weekly, 51, 59–67.
Atkinson, A. B., & Bourguignon, F. (1982). The comparison of multi-dimensioned distributions of economic status. The Review of Economic Studies, 59, 183–201.
Banerjee, A. K. (2014). A multidimensional Lorenz dominance relation. Social Choice and Welfare, 42, 171–191.
Banerjee, A. K. (2016). Multidimensional Lorenz dominance: A definition and an example. Keio Economic Studies, 52, 65–80.
Banerjee, A., & Kuri, P. K. (2015). Development disparities in India: An enquiry into convergence. New Delhi: Springer.
Barro, R. J., & Sala-i-Martin, X. X. (1995). Economic growth. New York: McGraw-Hill.
Boland, P. J., & Proschan, F. (1988). Multivariate arrangement increasing functions with applications in probability and statistics. Journal of Multivariate Analysis, 25, 286–292.
Cowell, F. A. (2000). Measurement of inequality. In A. B. Atkinson, F. Bourguignon (Eds.), Handbook of income distribution (pp. 67–166). North-Holland.
Dholakia, R. H. (2003). Regional disparity in economic and human development in India. Economic and Political Weekly, 38, 4166–4172.
Epstein, L. G., & Tanny, S. M. (1980). Increasing generalized correlation: A definition and some economic consequences. Canadian Journal of Economics, 13, 16–34.
Foster, J. E. (1985). Inequality measurement. In H. P. Young (Ed.), Fair allocation (pp. 31–68). Providence, RI: American Mathematical Society.
Ghosh, M. (2006). Economic development and human development in Indian states. Economic and Political Weekly, 41, 3321–3329.
Hardy, G. H., Littlewood, J. E., & Poliya, G. (1952). Inequalities (2nd ed.). London: Cambridge University Press.
Kolm, S.-C. (1977). Multidimensional egalitarianisms. The Quarterly Journal of Economics, 91, 1–13.
Marshall, A. W., & Olkin, I. (1979). Inequalities: Theory of majorization and its applications. New York: Academic Press.
Martin, R., & Sunley, P. (1998). Slow convergence? The new endogenous growth theory and regional Development. Economic Geography, 74, 201–227.
Mishra, S., & Nathan, H. S. K. (2014). Measuring HDI—The old, the new and the elegant: Implications for multidimensional development and social inclusiveness. LSE Asia Research Centre Working Paper 63.
Noorbakhsh, F. (1998). The human development index: Some technical issues and alternative indices. Journal of International Development, 10, 589–605.
Noorbakhsh, F. (2003). Spatial inequality and polarisation in India. CREDIT Research Paper No. 03/16. http://ssrn.com/abstract=482481.
Reserve Bank of India. (2016). Handbook of statistics on Indian states. Mumbai: RBI.
Roy, H., & Bhattacharjee, K. (2009). Convergence of human development across Indian states. http://www.igidr.ac.in/pdf/publication/PP-062-22.pdf.
Sen, A. (1997). On economic inequality. Oxford: Oxford University Press.
Tsui, K.-Y. (1999). Multidimensional inequality and multidimensional generalized entropy measures: An axiomatic derivation. Journal of Economic Theory, 67, 251–265.
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Banerjee, A.K. (2019). Trend in Inter-state Disparity of Well-Being in India in the Post-Reforms Period. In: Bandyopadhyay, S., Dutta, M. (eds) Opportunities and Challenges in Development. Springer, Singapore. https://doi.org/10.1007/978-981-13-9981-7_25
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