Of
late, there has been a lot of discussion about the relative performance of
the states in India. A spate of analyses has been devoted to considering
the growth performance of the different states, and many of the
traditional prejudices regarding the ‘dynamic’ and ‘stagnant’ regions seem
to be confirmed by such analyses. These patterns are then explained by the
usual arguments with respect to backward and forward states. During the
1990s, it has further been argued that those states that have been more
open to economic liberalization have shown faster rates of growth in
general.
However, much of such analysis has been in terms of aggregate growth
rates, whereas obviously what is more significant is the change in per
capita income. It is well known that regional inequalities are large in
India, and there is widespread perception that they have increased in the
recent past. Chart 1 indicates the relative position of states with
respect to aggregate net State Domestic Product (SDP) and per capita net
SDP in 2000–01 (at constant 1993–94 prices). The importance of considering
per capita patterns becomes immediately obvious from this chart. Among the
largest economies in terms of aggregate SDP, only Maharashtra is among the
top in terms of per capita income. Uttar Pradesh, the second largest state
economy in aggregate terms, is among the lowest in per capita terms.
Meanwhile, Punjab and Haryana, which have relatively small total SDP, have
the highest and third highest per capita incomes.
Chart 1 >>
Of course, all this says nothing about intra-state inequalities, which
also cannot be assumed to be similar across states. The NSS estimates show
that some of the states with highest per capita income have also the
highest internal inequalities in terms of per capita consumption
expenditure. Thus, the two states with the highest Gini coefficients for
per capita consumption (indicating the greatest inequality) are Tamil Nadu
(with a Gini ratio of 0.398 in 1999–2000) and Maharashtra (with a Gini
ratio of 0.345). These two states are among the highest in per capita SDP.
However, other states with high per capita SDP show relatively less
inequality in consumption expenditure. Thus Punjab showed a Gini
coefficient of 0.29, while Haryana had a Gini ratio of 0.285 in the same
period, for per capita consumption expenditure. Conversely, some states
with low per capita SDP such as Uttar Pradesh and Bihar had relatively
high inequality with a Gini ratio of 0.327 and 0.318 respectively.
In what follows, we will ignore intra-state income inequalities, and focus
on patterns across states, in terms of per capita income and growth. We
will also ignore rural–urban differentials within states, which are also
estimated to have increased over time and especially in the last decade.
Charts 2 to 5 show the per capita SDP of each state as per cent of the
highest (which in all of the years happens to be Punjab) and the rank of
the various states in the four years 1970–71, 1980–81, 1990–91 and
2000–01. A comparative look at these charts reveals a number of
interesting trends.
Chart 2 >>
Chart 3 >>
Chart 4 >>
Chart 5 >>
First, it emerges that over time the basic hierarchy has broadly remained
the same, with Punjab, Haryana and Maharashtra at the top in per capita
terms, and Bihar and Orissa at the bottom. Within this, however, a number
of the states with relatively higher per capita income have been improving
their position vis-ŕ-vis the state with the highest, which is
Punjab. This was especially true for the period 2000–01, when there were
four states (Haryana, Maharashtra, Tamil Nadu and Gujarat) with per capita
incomes of more than 80 per cent of that of Punjab, compared to 1970–71,
when only the state of Haryana could cross that mark. In other words, as
compared to the earlier years, at present there is less difference among
states at the top in terms of per capita incomes.
Another feature that emerges is the variation in the relative position of
the ‘middle income’ states vis-ŕ-vis the highest, not only in terms
of ranking, but as proportions of the highest per capita SDP. States such
as Tamil Nadu, Karnataka and Kerala show significant increases over the
longer period, with some fluctuations in 1990–91. Andhra Pradesh shows
wide fluctuations with an increase in 2000–01, while West Bengal shows no
clear trend, despite a dip in 1990–91 and a recovery thereafter.
Finally, the deterioration of the relative position of the lowest per
capita income states, is worth noting. In the 1970s and 1980s, Orissa and
Bihar (the two states with the lowest per capita SDP) had per capita
incomes between 40 to 50 per cent of that of Punjab; by 2000–01, the
figures had fallen to 34 per cent for Orissa and only 22 per cent for
Bihar. In other words, in some of the more backward states, the
disadvantages of the low base combined with other factors create relative
stagnation in per capita incomes, thus increasing gaps with the richer
states.
This phenomenon of increasing gaps between richest and poorest states is
shown very clearly in Chart 6 that describes the per capita SDP of the
richest state (Punjab) as a multiple of the poorest (Bihar). It shows that
the divergence increased even in the period 1970–90, but not very
substantially, and in 1990–91, the ratio was just above 3 times. But over
the 1990s there was an explosive increase in such inequality that caused
the gap to increase dramatically to more than 4.5 times by 2000–01.
Chart 6 >>
Clearly, the causes for such increasing divergence over the most recent
period require further investigation. Some possible causes and factors are
discussed below. But before that, it may be worth looking into the
patterns of growth of aggregate SDP, to see if there are any trends that
emerge from such overall performance.
Chart 7 indicates that there has been no such thing as a common pattern
across states in terms of SDP growth rates, and also that the trends have
varied widely across decades. While it is true that some of the more
‘backward’ states exhibit lower rates of growth, this has not been
consistently true over all three decades. Thus, in the 1980s, several of
the supposedly ‘BIMARU’ states (Bihar, Madhya Pradesh, Rajasthan and Uttar
Pradesh) grew faster than the national average in terms of aggregate SDP,
thereby providing challenges to the more common perception. By the 1990s,
however, growth had decelerated in these states (except Rajasthan), but so
also did it slow down in a number of the higher income states such as
Maharashtra, Punjab and Haryana.
Chart 7 >>
Interestingly, in the 1990s, West Bengal showed the highest rate of
aggregate SDP growth after Karnataka, even though it has not been
generally recognized as a fast growing state. Indeed, its aggregate rate
of growth appears to have been faster than that of Gujarat and Tamil Nadu,
both of which are described as dynamic states. This comes out even more
sharply in terms of per capita incomes. Chart 8 gives some indication of
the aggregate rates of growth and per capita SDP in the second half of the
1990s, for the six largest state economies. Karnataka clearly grew at the
fastest rate, in both aggregate and per capita terms, followed by West
Bengal and Tamil Nadu.
Chart 8 >>
The gap
between West Bengal and Tamil Nadu, on the one hand, and Gujarat and
Andhra Pradesh on the other hand, was significantly greater in terms of
per capita growth, than in aggregate SDP growth. This is possibly
reflective of the greater success of West Bengal and Tamil Nadu in
controlling fertility and therefore also population growth. But once
again, these patterns are not generally recognized.
