Rural voters make elections a close call in Haryana even as the ruling combine romps home with a diminished majority in Maharashtra

Far from an easy ride in the first assembly polls following the Lok Sabha elections where the Bharatiya Janata Party and its allies in the National Democratic Alliance secured a massive victory, the polls have revealed that the opposition is not altogether done and dusted in the country as it is being made out to be.

Counting in Haryana and Maharashtra is still on as this article is being written (2:45 pm). In fact, around 83% and 76% of the total estimated votes had been counted and tallied in the Election Commission website at the time of writing. So, even if this is an initial analysis, there are substantive vote counts to base it on.

Here’s a look at the respective vote shares in the 2014 and 2019 assembly elections besides the 2019 Lok Sabha elections.

Maharashtra

In Maharashtra, ruling combine’s vote share has fallen somewhat relative to the 2014 assembly and 2019 Lok Sabha elections (the Shiv Sena’s in particular). Among the opposition, the NCP has done marginally better than the previous elections while the Congress has barely managed to retain its vote share. The accrual to the opposition’s tally in terms of votes has come from smaller parties in the alliance which have done relatively better.

Haryana

Unlike Maharashtra, where the ruling BJP-Shiv Sena combine is headed towards a clear majority with 57% of the seats (and 42.3% of the vote share), the situation in Haryana reflects a neck-to-neck election. The net negative swing away from the BJP since the Lok Sabha elections has been around 22 percentage points, largely garnered by the Jannayak Janata Party led by Dushyant Chautala.

Looking at Haryana, first, the fact that the BJP and the Congress are nearly tied in leads despite an eight percentage point vote share difference seems incongruent. But a break-down of the region-wise vote shares and leads brings some clarity.

The Congress party trails the BJP in most regions except East Haryana, where it has taken a marginal lead over the BJP in vote shares. Also, its votes-to-leads conversion ratio is higher.

Here’s another break-up that tries to explain this. This relies upon assembly constituencies classified as rural and urban areas.

Urban-rural breakup

There is a very clear rural-urban divide in the vote shares of the three main parties in Haryana, with the BJP doing much better in the urban and semi-urban areas while the JJP doing much better in the rural areas, even as the Congress vote share is largely uniform. It is clear that the JJP has eaten into the BJP’s vote share in the rural areas and has allowed the Congress to be competitive in such seats.

In Maharashtra too, the victory of the ruling combine was a foregone conclusion according to most observers, but the leads thus far show much lesser vote shares than what was expected. A region-wise and urban-rural wise break-up of the vote shares and leads are as below:

The takeaway from these two assembly elections is that despite a lackadaisical campaign by the opposition and an incumbency advantage (this close to the Lok Sabha elections), the ruling BJP has not had it too easy. In Haryana, voters - especially in the rural areas have moved away from the BJP and have favoured the opposition. The State has a high rate of unemployment (20.3% according to the CMIE unemployment survey index), and a degree of rural distress, which has enabled the opposition to garner some support despite the high pitch campaign by the BJP based on nationalism and Kashmir’s status.

In Maharashtra, the ruling combine had it better, but still suffered a relative drop in vote share compared to both the 2014 Assembly elections and the 2019 Lok Sabha elections. Even here, there was a rural-urban break-up visible. This is a wake-up call to the opposition to get its act together and give a semblance of a fight both politically and electorally to a dominant BJP at the centre.

(With inputs from Varun B. Krishnan and Vignesh Radhakrishnan. Regional classifications are based on CSDS data. Urban-rural classification is based on night-light data made available by SHRUG development data lab)