Bihar may be an uphill battle for the BJP

An average of three recent opinion polls (here, here and here) shows that the Bharatiya Janata Party (BJP)- and Janata Dal (United)(JD(U))-led alliances are locked in a statistical dead heat in the 2015 Bihar state election.

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This is a very creditable performance for the BJP. The party was long overshadowed by its partner of two decades, Nitish Kumar’s JD(U), even though it played a crucial supporting role in bringing upper caste votes to the alliance. Today, it appears to have fought Bihar’s two dominant parties to a standstill, and could yet form a government with its political allies. Indeed, the formation of a “grand coalition” (महागठबंधन) by the JD(U), Rashtriya Janata Dal (RJD) and Indian National Congress (INC) could ironically elevate the BJP to political primacy in Bihar, as Yogendra Yadav argued in a recent TV interview.

But it won’t be easy for the BJP to overcome the grand coalition’s raw arithmetic power. At the height of the Modi wave in the 2014 general election, the BJP and its allies outpolled the combined votes of these three parties in only 85 of 243 assembly segments. Most of these lay within 11 Lok Sabha constituencies where heavyweight BJP alliance candidates were contesting. The corollary: the then-hypothetical grand coalition “won” 158 assembly segments.

The big change since then is that the RJD and INC are now in alliance with the JD(U). So why does the race appear to be so tight? One theory is that disaffection with the RJD and Lalu Yadav will encourage many JD(U) supporters who might otherwise have voted for Nitish to switch to the the BJP. Furthermore younger and more educated Yadavs are also said to be weighing support for the BJP, which means that the RJD could also lose votes to the BJP.

Who knows, right? Well, not quite. We have a test of this theory in ten state by-elections fought in August 2014, only three months after the general election. The main difference was that the RJD+INC and JD(U) fought separately in the general election, but presented a unified front in the by-elections. A comparison of vote shares in the two elections gives us an opportunity to gauge the effect of the grand coalition.

So what happened? There was a swing of 2.1% towards the JD(U)-led front and a swing of 6.2% away from the BJP alliance (using simple averages). The BJP and its allies won four assembly seats and the JD(U) alliance took six. This would seem to show that the unification of the RJD, JD(U) and INC had a (weak) positive effect, while the BJP lost substantial vote share compared with the general election, only three months later. If this is a foretaste of how the grand coalition might fare against the BJP, the latter has much to be concerned about.

There are, as usual, caveats. This measure is imperfect because (1) issues and candidates differ between national and state elections and (2) ruling parties tend to win by-elections about two-thirds of the time because voters like their constituencies to receive favourable treatment. This means that any alliance effect — political contradictions that forced some RJD and JD(U) voters into the arms of the BJP — could have been hidden in the by-elections by such an incumbent effect. Furthermore, ten is admittedly a small sample in a state that has 243 assembly constituencies, although as the map below shows they were reasonably diversified in geographical terms (156-Bhagalpur in the southeast seems to not have been properly highlighted).

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Most importantly, of course, there was no chance that the by-elections would result in a change in government, whereas the BJP and its partners present a credible alternative in the state election. So a BJP wave or the move of key swing constituencies towards it (be they Mahadalits or Yadavs) could still produce victory for the BJP. However, the recent historical record and the sheer quantum of votes available to the JD(U) and RJD suggest this won’t be so easy.

Some proof required

There’s been much heated debate about Surjit Bhalla’s August 29 and September 5 Indian Express op-eds in which he argued: “the only explanation for the constancy of the share of the Christian population between 1991 and 2011 (2.32% and 2.3% respectively) is large scale conversion to Christianity”.

The crux of Bhalla’s argument is that because Sikhs and Christians had comparable income and fertility levels in the early 1990s, their respective population growth rates in between 1991 and 2011 should have been similar. Instead, “the Sikh population grew at an average rate of 1.2% per annum, while the population growth rate of Christians was a relatively higher 1.9% per annum… despite [Christians] having the highest per capita consumption, the highest level of female education and the lowest fertility.” The gap is accounted for, says Bhalla, by religious conversions to Christianity, which he quantifies at 1,70,000 per year between 1991 and 2011.

This seems at first like a smart way to isolate the impact of conversion using demographic data. But as the following critique by Rohini Prabha Pande, expert on gender and population dynamics, shows, Bhalla may be too clever by half:

Guest post by Rohini Prabha Pande

Why Bhalla’s argument is half-baked 

The most likely explanation for Bhalla’s “puzzle” might be the simplest one. Even with a slightly lower fertility rate, the Christian population may have grown larger than that of Sikhs because of a larger population base to which this fertility rate is applied, rather than lakhs of conversions. In particular, if the age distribution among Christians favors the reproductive age groups, then even with lower fertility rates the population could grow. This is related to the concept of population momentum and, at minimum, Bhalla needs to examine the age distribution and age-specific fertility rates of Christian versus other groups to rule this out as an alternative explanation.

In another sleight of hand, Bhalla summarily rules out migration – a key component of population growth – as an explanation of why the Sikh population might have grown more slowly than the Christian population. Here too he needs to explain why he is correct, and others – like Aswini Nanda – are wrong.

There are other flaws in his reasoning. I agree with Tony Joseph’s argument that Bhalla’s results depend on which period you pick. To that I would like to add that Bhalla’s focus on 20-year time periods brushes under the rug some key aspects of the relative growth of these two groups’ population, because the more you collapse data, the more information you lose. A quick calculation shows that if you simply parse 1991-2011 into two 10-year census periods (even without going further back in time to 1971, as Joseph does) you get a somewhat different picture: the (compounded) rate of growth of the Christian population across the two periods is slowing faster than the rate of growth of the Sikh population (see Table 1 below).

In other words, while the Christians may have a higher population growth rate than the Sikhs, both groups’ rates are dropping, and the Christians’ growth rate is declining faster than that of the Sikhs. The difference between the Christian and Sikh populations’ growth rates has narrowed from 0.9 percentage points between 1991-2001 to 0.6 percentage points between 2001-2011.

Table 1: Changes in population growth rates of different religious groups in India, 1991-2011
Table 1: Changes in population growth rates of different religious groups in India, 1991-2011

Bhalla then asks “what caused Christian population growth to accelerate from 1.39% (1971-91) to 1.93% a year (1991-2011)?” and concludes that the answer lies in religious conversions. One could equally and legitimately ask what caused Christian population growth to drop from 2% between 1991-2001 to 1.5% between 2001-2011. Framed this way, the question does not – unfortunately for Bhalla – lead to the conclusion that conversions have risen.

So one has to take Bhalla’s assertions with a large pinch of salt, if one were to pay any attention to them at all.

Finally, in his 4 September rebuttal of Joseph, Bhalla asserts that: “The excess Sikh males do not marry; excess Christian women do marry and produce Christian kids.” Aside from the parochialism implicit in this statement, is he assuming that the excess Sikh males don’t marry because there are no Sikh women? His own occasional coauthor, sociologist Ravinder Kaur, is the foremost researcher in India (look here) on the increasing phenomenon of across-region marriage, showing in particular how excess males in Punjab (presumably including Sikhs) import brides from Andhra Pradesh and Assam.

To sum up, Bhalla’s calculations of conversion are at best inconclusive, at worst, disingenuous.