Is the Modi Effect waning? (What Jammu and Jharkhand tell us)

The recent state elections in Jammu & Kashmir and Jharkhand went well for the Bharatiya Janata Party (BJP), but the results have also sparked speculation as to whether the Narendra Modi effect is beginning to wane. Congress Party MP Rajeev Satav seems to think so (and was retweeted by Aam Aadmi Party leader Arvind Kejriwal):

If only things were so simple.

Take Jharkhand. As Satav says the BJP’s vote share dropped about 9 percentage points between the general election in April-May 2014 and the state assembly election in November-December 2014. But that’s not unexpected: the chart below shows the BJP has lost 7-9 percentage points in vote share between national and state elections held in close succession since 2004.

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This is also true of state assembly constituencies won (see chart below). In both 2009 and 2014, the BJP in Jharkhand won 19-20 more state assembly segments in national elections than it did in the state elections that followed a few months later. Note that 2004/05 is an exception partly because the BJP stood alone in the 2004 parliamentary election but allied with the Janata Dal-United in 2005 for the state election.

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This pattern occurs presumably because many Jharkand voters chose to vote for the BJP in national elections but switched to a regional party such as the Jharkhand Mukti Morcha that seemed a more viable option in state politics.

The BJP’s position in Jammu appears unchanged between the national and state elections. While it’s true that the party’s overall vote tally in Jammu and Kashmir has fallen, its grip on Jammu hasn’t really weakened. The BJP won 24 assembly segments (in the Jammu and Udhampur parliamentary constituencies) in the general election, and won 25 assembly seats in Jammu in the subsequent state election.

There is therefore no real evidence to suggest that the Modi effect (or anti-Congress sentiment) has waned either in Jammu or Jharkhand.

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An aggressive Indian border stance would play into the Pakistan Army’s hands

It’s no surprise that the escalation of cross-border tensions in the midst of two important state elections has led Prime Minister Narendra Modi and other officials to issue tough statements to Pakistan. However there is also some evidence that the government is actually considering a change in its current stance of letting officers on the ground respond to ceasefire violations as they see fit, more or less proportionately, to one in which it escalates violence more readily.

Business Standard Consulting Editor Ajai Shukla describes army thinking thus:

With Indian posts on the LoC better constructed and more heavily armed than Pakistan’s, an escalation of firing imposes disproportionate costs on the Pakistan Army. The BSF too has been instructed to retaliate strongly. New Delhi’s decision not to call for a flag meeting underlines its conviction that the military cost will soon become too high for Pakistan.

The Economic Times reports that:

…the Pakistan Army has now given India a chance to do what it wanted to do for a long time – target and destroy permanent defences that were aiding in infiltration.

This sort of talk is understandable if meant as a warning to Pakistan, but any strategy aimed at stopping cross-border militant infiltration is essentially trying to solve a problem that doesn’t exist.

On the face of it, it does seem that the border had been steadily heating up:

The data I located are similar, and show a discernible spike in 2013, but the casualty figures are much lower, with an average of one Indian fatality and eight Indian wounded per year between 2010 and 2013. Also note that the available data appear to exclude Indian ceasefire violations, if any:

Chart 1: Pakistani ceasefire violations along the Line-of-Control

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There does seem to be a discernible increase. Even so, ceasefire violations at this level are strategically meaningless unless they are married to a specific objective. The most likely such goal would be to give cover to cross-border militant infiltration aimed at stirring up trouble in Jammu and Kashmir (J&K).

The former commander of the Srinagar-based XV Corps Lt Gen Syed Ata Hasnain believes that Pakistani troops have targeted the international border, rather than the Line-of-Control, this time round because “this is the best ground for infiltration and immediate targeting of suitable objectives in a very short time frame”.

But what do the data tell us?

Chart 2: Insurgent infiltration attempts in Jammu and Kashmir

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It’s pretty clear that infiltration attempts into J&K by armed insurgents have sharply declined over the past decade, judging from Home Ministry data (sourced from here and here). One dip occurred following the 9/11 attacks in the US as a result of which Pakistan was forced to reduce support to armed groups in Kashmir. The second dip occurred in 2004 after the November 2003 ceasefire with Pakistan which made it harder to infiltrate fighters across the border using covering fire. Furthermore, the rise in ceasefire violations since 2011 has led to no increase in crossborder incursions.

This fall in insurgent infiltration attempts has also contributed to an unambiguous decline in militant violence in the state (data from South Asia Terrorism Portal):

Chart 3: Fatalities from insurgent violence in Jammu and Kashmir 

The reduction in violence in J&K undoubtedly has many causes, but a decline in Pakistan-aided infiltration is clearly an important contributor. Consequently, a more aggressive posture on the border might play well to domestic audiences and TV channels, but would do nothing for political stability in J&K. On the contrary, if Pakistan does in fact intend for its border provocations to facilitate the movement of armed fighters into J&K, a “tougher” Indian policy would simply play into its hands (look here for a different argument that reaches the same conclusion).

An alternative explanation of Pakistan’s border behaviour draws on Pakistani domestic politics and on the power tussle between the military and civilian leadership in that country. But that’s for another time.

Manmohan years still most peaceful despite riots uptick in 2012/13

In a pointed analysis on Scroll.in using data from the National Crime Records Bureau (NCRB), Shivam Vij shows that the rate of rioting in India (per 100,000 population) has fallen continuously since 1992, reaching a plateau around 2003 and remaining pretty much constant since then. Vij is correct that the Manmohan Singh years have been the most peaceful on average since 1963, but it is also true that this level was first reached in Atal Bihari Vajpayee’s final year in office.

The Scroll report excludes data for 2012 and 2013, but these are available in the NCRB’s annual Crime in India 2012 (PDF) and Crime in India 2013 (PDF) publications. Incorporating data from those years shows an uptick in riots in 2012, taking the number above the 6 riots per 100,000 population mark, before it drops back down below this level in 2013. This doesn’t amount to anything more than statistical noise, particularly in the context of the larger trends the report highlights.

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A couple of points are worth mentioning. One is that riots here are defined as incidents that are in violation of sections 143-145, 147-151, 153, 153A, 153B, 157, 158, or 160 of the Indian Penal Code. This is different from the Home Ministry’s definition of “communal incidents” that I used in BJP-ruled states more communally violent. To take one example, the NCRB lists 72,126 riots in India in 2013, while the Home Ministry offers a figure of 823 communal incidents for the same year. It is possible that the smaller number is a subset of the larger one (not all riots have a “communal” angle), but we don’t know that for sure.

More importantly, it is also possible that the number of riots is being undercounted. As Rukmini Shrivinasan points out, NCRB data only record the “principal offence” reported in a police first information report i.e. the offence that attracts the maximum punishment. This means that a riot that resulted in a death could be counted as a murder or attempted murder instead. This is common international practice (as NCRB deputy director R Rajasekaran has written), and even in the US only a quarter of all incidents are disaggregated by types of offence (under the National Incident Based Reporting System). There is a programme underway to automate and network crime data collection co-ordinated by the NCRB but when this will happen is anybody’s guess.

The Rajya Sabha will remain a headache for the NDA

With the Lok Sabha, the lower house of Parliament, securely in the hands of the Bharatiya Janata Party (BJP) and its allies, the locus of political opposition is set to move to the Rajya Sabha, the upper house, where the BJP remains in a minority. Most bills need to be passed by both houses to become law, and this has sparked speculation as to how the BJP might push through its legislative agenda without a Rajya Sabha majority.

It is evident from the chart below that the the United Progressive Alliance (UPA) controls many more seats in the Rajya Sabha than does the BJP-led National Democratic Alliance (NDA).

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There are two obvious paths before the BJP:

  1. Regional parties. The ruling party could make deals with unaligned regional parties (such as the Biju Janata Dal and the AIADMK) to win support for specific bills. Since the NDA is 59 seats short of a majority it will have to convince six or seven of the largest regional parties to support it in the Rajya Sabha.
  2. Joint sittings. The BJP could arrange for joint sittings of the two houses under Article 118 of the constitution. The NDA is slightly over the halfway mark of the two houses’ 777 combined seats. However this is a rare step, carried out only thrice in Indian parliamentary history, and would require the consent of the President of India.

With two ordinances passed in its first two days, the Modi government has signalled that it may not be overly concerned about precedent. Even so, frequent joint sittings of the two houses could anger opposition parties that have become quite efficient at disrupting parliament in recent years.

The desirability of each strategy depends in part on how the number of seats controlled by the NDA grows over the next five years. If the NDA can woo new allies easily then it is less likely to take recourse to the more drastic step of calling joint parliamentary sessions. Recall that the Rajya Sabha reflects the balance of power in India’s states, and that a third of its members are elected every two years.

How then might the balance in the Rajya Sabha shift in the coming years? Let us assume that the NDA’s strong 2014 Lok Sabha performance translates into state election victories in 2014 (Delhi, Haryana and Maharashtra), 2015 (Bihar) and 2016 (Assam) in roughly the same proportion. This is a contestable assumption because the national level “Modi wave” will have less relevance in a state election in which local factors gain prominence.

Still, maintaining that assumption, here is what the Rajya Sabha might look like in 2016 (excluding the 11 current vacancies in the upper house):

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This is quite clearly not enough to tilt the scales in the NDA’s favour. Even after the 2016 Rajya Sabha elections, the ruling alliance will be 47 seats short of a majority and will need the support of regional parties such as the Samajwadi Party and the All India Trinamool Congress.

The NDA’s prospects begin to sharply improve in its fourth year if the 2014 election results are mapped on to state elections in 2017. Keep in mind that this is a very optimistic scenario for the alliance: the BJP’s popularity could well have ebbed by then and the local factors mentioned above will again be in play in a state election. We are also assuming that party state assembly seat shares translate quite simply into Rajya Sabha votes; in practice there is often voting across party lines and strategic voting in favour of third candidates that can make the outcome less predictable.

But assuming that the broad patterns of the general election apply to the 2017 state elections in Goa, Gujarat, Himachal Pradesh, Manipur, Punjab, Uttar Pradesh and Uttarakhand, this is what the Rajya Sabha could look like in 2018:

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The NDA is still 30 seats short of the halfway mark in the Rajya Sabha, and the ruling alliance will need to win over at least one of the three biggest regional parties (Samajwadi, Trinamool and AIADMK) plus an assortment of smaller players. The NDA is well over the halfway mark of a joint sitting at this point, so its preferred strategy will depend on how easily it can woo those parties.

Either way, the NDA will remain short of a majority in the Rajya Sabha, although its rising tally will require it to attract fewer allies by 2018. But 2018 is close to the end of the its term, which means that for most of its tenure the NDA will be forced to reach out to a large number of regional parties to pass bills in parliament.

And the winner is…

Never mind the general election, real geeks want to know who won the battle of the exit polls. The contestants, as many will recall, were:

And judging from the result and the accolades that followed, Today’s Chanakya was the clear winner.

But not so fast. To make election predictions under India’s first-past-the-post system, polling agencies must first estimate party vote shares and then use this data to make seat share predictions. As we discussed in Why you should ignore opinion poll seat predictions, the primary task of a survey is to collect data on vote shares. This is subsequently translated into seat share predictions based on mathematical models that try to guess how these votes will be distributed among different states and regions.

The ideal scenario is one in which you accurately capture the vote share of different parties and convert these into the correct number of seats. But you can also get the right answer if you make two opposite errors that cancel each other out. This is what occurred with CSDS’ 2012 Uttar Pradesh post-election poll, in which CSDS was the only pollster to correctly predict the number of seats that the Samajwadi Party and the Bahujan Samaj Party would win in that complex four-cornered contest. As Yogendra Yadav later wrote:

Sukumar is absolutely right in saying that we over-estimated the lead in terms of votes and under-estimated its impact on seats. These two compensating errors cancelled each other and our final forecast was closer to the outcome than others.

The first step in evaluating the success of an exit poll (or a post-election poll taken some days after voting) is therefore to check how close it came to estimating the correct vote share. There are various ways to do so (e.g. here), but here we rely on two common techniques:

  1. Comparing the ratio of the votes of the winner and the runner up (the “Mosteller 2” method)
  2. Comparing the margin in percentage points between the winner and the runner up (the “Mosteller 5” method–preferred by Nate Silver)

In the recently concluded election, the BJP-led National Democratic Alliance (NDA) won 38.3% of the vote while the United Progressive Alliance (UPA) won 22.8%. This is a ratio of 1.68 in favour of the NDA and a vote share gap of 15.5 percentage points.

Under the Mosteller 2 method, we rank the exit polls based on how far they deviated from the vote share ratio in their own estimates. And we find that the NDTV Hansa poll performed the best, while the India Today Cicero poll did the poorest.

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Using the Mosteller 5 method, we find that NDTV Hansa did the best again with a deviation of only 0.8 percentage points from the actual vote share gap between the NDA and the UPA. CNN IBN CSDS came second, and India Today Cicero were last once again.

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What is interesting is that Today’s Chanakya’s performance was middling according to both measures, even though its seat share estimate came closest to the actual. Certainly the agency is a winner from a marketing point of view, but in this case a subpar vote estimation appears to have been overcompensated for by an aggressive seat conversion formula (as others also noticed with its Uttar Pradesh prediction).

Today’s Chanakya may be doing best in the box office, but the award for best survey goes to NDTV Hansa.

Research note

Only NDTV, CNN IBN and India Today were kind enough to make their national vote share estimates easily available online. I had to endure considerable time watching YouTube videos to locate the vote shares of the India TV Cvoter and ABP News Nielsen exit polls and — even less forgivably — failed to locate the Times Now ORG data in spite of being forced to watch Times Now for a memorable length of time. Equally painful was having to manually calculate Today’s Chanakya’s national vote share estimate from its state vote share data, since the agency inexplicably chose not to disclose its national numbers.

The return of the gender gap

If women alone were to vote in the current elections, the Bharatiya Janata Party (BJP) would win 88 more Lok Sabha seats than the Indian National Congress (INC) (using CSDS data — see Table 3a). If only men voted, the BJP would get 126 more seats than the INC (if we stubbornly assume a constant ratio of voteshare-to-seats conversion). This hypothetical example highlights how gendered voting choices can have a big effect on election outcomes.

As Rajeshwari Deshpande wrote in September 2009:

The Congress has enjoyed an advantage among women voters since the 1996 general election. The party’s popularity among women reached a high point in 1999 when the gender gap in favour of the Congress was 5 percentage points. Since then, the gap has been closing. In the 2009 election, the Congress enjoyed a slight tilt in women’s votes towards it.

That no longer seems to be the case. According to the latest available CSDS data, the gender gap between the INC and BJP has reemerged with a vengeance (we define the gender gap as the difference between women and men voting for the BJP subtracted from the difference between women and men voting for the INC — note that the 2014 gap emerges from less reliable pre-poll data while the rest are from post-poll data):

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So why might such a gap exist? The United States has experienced a gender gap in favour of the Democratic Party since 1980, and in 2000 and 2012 Democratic presidential candidates had a 20 percentage point gap in their favour (that dwarfs the Congress Party’s record eight-point gap in 1998 and 1999). Explanations of the gender gap in the United States and other industrial societies fall into three general (and partly overlapping) categories:

  • Economic. Higher female participation in the labour force, and the fact that female workers face wage discrimination at the workplace, have pushed women to the left of the political spectrum in favour of parties that emphasise redistributive politics.
  • Family. In a similar vein, rising marriage ages, the widespread use of contraception, more out-of-wedlock childbearing and increased divorce rates have driven women voters to the political left, since they are no longer in a position to benefit from the incomes of male partners.
  • Values. The belief that a woman is entitled to reproductive autonomy (particularly salient in the United States) and the spread of feminist ideas have pushed women voters in the direction of political parties that share those values.

To what extent might these factors apply in the India case? At first blush, it would appear unlikely. India’s female labour force participation rate has fallen in recent years (from 44% in 2005 to 36% in 2012), which would undermine the case for an economic explanation. The mean effective age of marriage for Indian women has risen from 19.5 years in 1991 to 21.2 years in 2011 (a 9% increase), and contraception usage has increased between 1992-93 and 2005-06, but the divorce rate remains low and out-of-wedlock childbearing appears rare. So far as values go, abortion is not a partisan political issue in India, and there is no evidence that women’s rights issues shape voting behaviour.

Indeed that India even has a voting gender gap should be surprising: political scientists Ronald Inglehart and Pippa Norris found (using 1990s data) that only “postindustrial” societies have a gender gap that favours left parties; the gap favours ideologically conservative parties in post-Communist and developing societies. (Let’s leave aside the question of how generalisable categories such as “left” and “right” can be.)

But things get interesting when you look at the following chart (drawn from Table 2 in Deshpande’s article):

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The gender gap in favour of the INC in 2009 — when it was small by historical standards — was highest in precisely those groups that you would expect to be most influenced by the same economic and cultural trends that have created the gender gap in Western societies. If this holds up to further scrutiny (beyond the scope of this blog), then it could provide one answer to the puzzle that Deshpande posed about women and the INC: “There is no evidence that women find its policies more attractive than [do] men”.

There are other views. Deshpande argues that it makes more sense to look instead at regional variations, and sure enough, the INC’s gender advantage varies from state to state. She suggests that the INC’s gender gap is really the reflection of caste and class factors, and that there is no independent gender tilt in favour of the INC (although there probably is one against the BJP). Furthermore regional parties matter a great deal, and women in the latest CSDS surveys appear to be leaning towards Mamata Banerjee in West Bengal, Jayalalitha in Tamil Nadu and Mayawati in Uttar Pradesh.

That said, women’s issues are more salient in the 2014 national campaign than ever before (as Supriya Nair pursuasively points out), which has forced political parties to craft more specific appeals to women. An Association for Democratic Reforms-Daksh survey found that women’s safety is the third most important election issue (of ten) for urban voters. And Narendra Modi’s aggressive, patriarchal campaign clearly contrasts with Rahul Gandhi’s persistent outreach to women voters.

Paint by numbers

We observed what can go wrong when journalists who lack an understanding of statistical inference make claims about data in How Mail Today got its analysis of communal violence exactly wrong. This tendency became clear once again from an Apr 26 article in The Hindu titled Gujarat behind West Bengal in new factory jobs, as the following analysis shows:

Guest post by Philip K. Oldenburg, Research Scholar, South Asia Institute, Columbia University 

Perhaps the most common error the media make when presenting data is to use the “absolute” numbers on their own, rather than adjusting them appropriately. For example, growth in income should always be “real,” adjusted to eliminate the effect of inflation. In a piece headlined “Gujarat behind West Bengal in new factory jobs; National Sample Survey data poses a challenge to ‘Gujarat growth model’,” published in The Hindu recently (April 26, 2014), we find a graph showing that there were 24 lakh jobs created in the manufacturing sector between 2004 and 2011 in West Bengal, versus 14.9 lakh jobs in Gujarat — some 60% more, making the state a “distant second.”

If one adjusts the figures to take into account the differing populations of the various states, the graph would be much less dramatic, and the ranking changes (excluding states with negative job creation):

Jobs created per 10,000 population

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West Bengal is now only 8.5% “better” than Gujarat. (Ideally, one would “normalize” the absolute numbers in this case by using some other denominator that would adjust for size of the state: perhaps its adult worker population, or something else.) That adjustment makes the analysis in the rest of the report irrelevant, in my opinion.

In the best of all possible worlds, any reporter assigned to do a story that rests on quantitative data should have had at least a course in elementary statistics, and every editor (equipped similarly) would catch errors in data presentation and analysis with about the same failure rate as now exists for typographical errors.

Deflating expectations

Every time the price of onions rises, pundits remind us (here and here) of what happened in Delhi in 1998, when a spike in the price of onions is believed to have contributed to the state election defeat of the Bharatiya Janata Party (BJP). Inflation does appear to matter greatly to Indian voters: “price rise” was the single most important issue for voters in the February 2014 CSDS tracker poll (PDF), followed by “development”, “corruption” and “economic growth”.

Some blame the United Progressive Alliance (UPA) for feeding food inflation via frequent increases in the minimum support prices (MSP) for cereals like rice and wheat in its quest for rural votes. This may therefore have come as a bit of a surprise:

Modi’s declaration is a timely reminder of just how far we are from India’s “Thatcher moment“. India’s political realities do not permit a mass party like the BJP to ignore key constituencies, and this will continue to shape the economic policies of a future BJP-led government.

That said, inflation is a hot political issue and the BJP’s election manifesto claims that the National Democratic Alliance (NDA) did much more to control inflation than did the UPA:

The BJP-led NDA Government’s record of holding the prices is a demonstration of our commitment to break the vicious cycle of high inflation and high interest rates.

Tellingly, the Indian National Congress manifesto has no mention of either inflation or “price rise”.

How to judge? Just as India’s economic growth is linked to the global economy through trade and investment flows (see How bad is the UPA’s economic record?), the prices of Indian goods and services — particularly those that are tradable — are tied to global prices. I therefore compare India’s annual GDP deflator since 1998 with that of developing countries (using World Bank data). The GDP deflator is a better measure than an inflation index (like the Consumer Price Index) because it does not limit its measurements to a fixed basket of goods and services but one that evolves with the economy.

And this is what we find: the NDA clearly was more successful at controlling prices than the UPA. In absolute terms, inflation rose from 4.5% during the NDA period (1998-2004) to 6.2% during UPA1 (2005-09), and further to 8.2% during UPA2 (2010-12).

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But how much of this can be blamed on poor economic management? That’s where the global comparison becomes relevant, and the UPA2 in particular performs poorly here. Under the NDA and UPA1, India’s inflation rate stayed below that of the developing world (although the differential decreased during UPA1). But under UPA2, Indian inflation soared to 2.5 percentage points above the developing country average. This can’t simply be explained away by high oil prices and inflation in food commodities (e.g. wheat and rice) because developing countries were also affected by those.

This World Bank chart shows how India’s inflation rate (in %) diverged quite sharply from other countries from 2009 onwards:

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So why did this separation occur? Plausible reasons include:

  • Fiscal deficit. The UPA sharply increased government spending in 2008-09, in the run up to the 2009 elections as well as to stave off the effects of the global crisis, but found it hard to reverse course and reduce the deficit subsequently for political reasons. Finance Minister P Chidambaram even blamed his predecessor, now President Pranab Mukherjee, last year for this inflationary surge.
  • Food prices. Food inflation has been a big driver of overall inflation in recent years. As their incomes have risen, Indians have consumed greater quantities of proteins such as milk, eggs, meat and fish, and the prices of these commodities have accordingly spiralled.
  • Minimum support prices. Government policies to ensure that farmers receive higher prices for cereals (e.g, rice and wheat) and pulses have also contributed to food inflation.
  • Subsidy reform. Ironically, price increases in petrol, diesel, non-nitrogen fertilisers and electricity aimed at reducing the deficit have helped increase inflation directly, as well as indirectly by making it more expensive to grow agricultural produce.
  • Rural wage increases. The wages of agricultural labourers have gone up rapidly, both because of the rural employment guarantee act and because of higher wages in sectors like construction that provide alternative employment for this section of workers.

Not everyone agrees that persistent inflation is a completely bad thing. Harish Damodaran argues that inflation in India is a consequence of the economic empowerment of lower-income groups.

For now, though, it’s the UPA that seems to be paying a political price for elevated inflation and slow economic growth.

Postscript

Some analysts like Yogendra Yadav do not think that the concept of “price rise” as presented in opinion polls is reducible to inflation. As he wrote in 2009:

In India ‘price rise’ is a way of talking about the lack of purchasing power or insufficient income rather than what economists call ‘inflation.’

If so, then real wage growth might better capture how the state of the economy will affect voting behaviour. But that’s a different study.

Is AAP India’s most criminal party?

With candidates declared for six of the nine rounds of voting in this never-ending general election, a partial analysis can now be done of how many stand accused of criminal activity and in what proportion parties are awarding tickets to such folks (data from National Election Watch, also see preliminary analysis here).

The chart below ranks parties by the proportion of candidates that have serious criminal charges against them:

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As before, parties from Bihar and Maharashtra have the highest percentage of Lok Sabha candidates that face serious criminal charges. In 2009, the Indian National Congress (INC) and Bharatiya Janata Party (BJP) were comparable; the BJP is doing a little worse so far in the 2014 election with 17% of its candidates facing serious charges compared with 13% of the INC’s.  The Bahujan Samaj Party (BSP) is performing better this time round: it has fewer accused candidates than the BJP, INC or the Samajwadi Party (SP). The Aam Aadmi Party (AAP), as might be expected, looks pretty good here.

What about levels of criminality? To calculate the intensity of the alleged criminality of each party’s candidates, we count the number of candidates with more than one serious charge, add up the number of charges and calculate the total as a percentage of the total candidates per party. And here is what we find:

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Shock and horror! AAP turns out, by far, to have the highest levels of alleged criminality of all of India’s parties. The Shiv Sena and Nationalist Congress Party come a poor second and third respectively.

As it happens, AAP’s ranking is driven by two statistical outliers: Anti-nuclear activists SP Udayakumar and M Pushparayan respectively account for 382 and 380 of the 829 serious charges that AAP candidates face. The next such candidate is Trinamool’s Kameshwar Baitha with “only” 48 charges, suggesting that the numbers for Udayakumar and Pushparayan are unusual. After all, is Udayakumar really 48 times more “criminal” than Sri Ram Sene leader Pramod Mutalik who faces eight serious charges?

To limit the effect of such outliers, let’s give a score of 10 to all candidates who were had more than nine serious criminal charges. The result is:

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The AAP now drops in the rankings and ends up with about the same intensity of criminal charges as the Congress Party, although it still does worse than the BSP and Biju Janata Dal. The “criminality” of the BJP slate of candidates is more than double that of the INC and AAP, up from being 28% greater than the INC in 2009. The Congress score in 2014 is about the same as it was in 2009, but the BJP’s is sharply higher this time.

As before, the BSP does well in this ranking, although its score is not strictly comparable with the SP’s because the latter is focused much more on Uttar Pradesh and has only two-fifth as many candidates. Communist Party of India (Marxist) supporters can breathe a sigh of relief: it moves from the top of the list in 2009 to somewhere in the middle.

Finally the overall incidence of serious criminal charges is higher (so far) in 2014: 302 of the 533 candidates facing serious criminal charges (the 57th percentile) have more than one charge against them compared with 355 of 1,114 (the 32nd percentile) in 2009.

Remember however that this is still an incomplete list: we await candidate data for the final rounds of voting.