On 26 October, a 19th-century bridge over the Machchu river in Gujarat’s Morbi city was opened to the public in a grand show, built with money from local people. five days later, the the bridge collapsed, An estimated 135 people were killed and injured 180 others. It was clear that mischief and dubious bargaining had taken place in awarding the contract for the restoration of the bridge to an inexperienced private firm. The Bharatiya Janata Party (BJP) was (and is) in power in state and local administration; The local MLA was also from BJP.
fall into the trap
A little more than a month later, state elections were held in December where the electorate of Morbi voted. Around 50,000 people in Morbi voted for the BJP in either the 2017 or 2020 bypolls. That is, immediately after the bridge collapse and where many lives were lost, the people of Morbi rewarded the BJP by voting for the party in higher numbers than before. BJP’s vote share in Morbi is 60% in 2022, compared to just 45% in 2017. In fact, even in polling areas near the collapsed bridge, more voters voted for the BJP in 2022. 2017. Can we infer that the BJP won the Morbi constituency only because a bridge collapsed and many lives were lost?
This is clearly a silly and facetious, but intentionally provocative question. Such stupid questions insult our basic intelligence and attack our moral senses. If any, the real question is: Why didn’t the voters of Morbi punish the BJP for this tragedy, especially when it happened weeks before the election?
Yet, if one looks at it objectively and in an abstract way, an event x happened (i.e., the bridge collapsed) and then a seemingly related event y happened (BJP’s victory). It is tempting and intuitive for the human mind to correlate the two and conclude that x led to y.
This happens all the time in our public remarks.
In the rush to interpret election results, media commentators and even so-called experts such as pollsters and political scientists constantly fall into this trap. If a political party makes an election promise or carries out a specific campaign (x) and then that party wins the election (y), commentators immediately conclude that the party won the election because of its promise (x to y). Went. Why is it that the “x to y” argument seems so absurd in the case of a bridge collapse, but completely plausible in the case of an election promise or campaign, even though the underlying logic is exactly the same? Because, context matters.
Just as it is illogical to claim that two events – the collapse of a bridge due to BJP’s misrule and the BJP’s subsequent victory in that constituency – show a causal relationship, it is equally illogical to claim so without hard evidence that a particular campaign or a promise or an event led to an electoral victory or defeat.
simplified correlation
Pollsters often ask people what their top issues are, and then how they plan to vote, to determine what influences people’s voting choices. They then simply correlate the two to draw strong conclusions. For example, a survey may show that people want lower taxes. If a political party promises lower taxes and wins an election, it does not mean that the party won because it promised lower taxes, although that sounds counterintuitive. A more rigorous way of analyzing this is to ask: Would that party not have won the election if it had not promised lower taxes?
Philosopher Karl Popper famously argued that unless a theory can pass the test of ‘falsifiability’, it cannot be considered absolute truth. To put it simply, he said that claiming that all swans are white must also conclusively mean that there is not a single black swan. economist Abhijit Banerjee, Esther Duflo and Michael Kremer won the Nobel Prize (2019) to develop a method called randomized control trial (RCT) experiments designed to conclusively predict whether x leads to y in policy experiments such as whether providing mid-day meals in schools would improve educational outcomes. A simplified version of such RCTs can be adapted to electoral surveys to draw more robust conclusions.
In our example, two sets of survey questions can be designed, one set explicitly telling voters that a political party has promised lower taxes and the other set in which the party makes no such promise. Voters can be randomly given one of these two questionnaires for a survey of equal sample size. If there is no difference in the party’s vote share in these two survey sets, then it would be clear that the promise of lower taxes has no effect on people’s intention to vote, and if there is a significant difference, it is in favor of the party. It is understandable for Party will promise less tax
This is a more rigorous way of establishing a causal relationship between the two than the current simplistic and widely misleading way of imputing causality, called ‘cross-tab’ analysis by pollsters. This is a major reason why the same election promise or strategy works for just one party or one state or one region or one section of people, while not in others, confusing political parties and leaders.
For example, the Aam Aadmi Party promised many similar things to what the Congress party did in Himachal Pradesh in the run-up to the November elections, but it didn’t seem to be working for them; Nor did a few similar promises work for the Congress party in all the districts of Himachal Pradesh. Misrepresenting causal links to election results through simplistic and non-rigorous narratives and developing a misleading narrative for election results is often more dangerous than no explanation at all.
the last word
It’s easy to dismiss this as some useless academic discussion of scientific methods (by intellectuals far from the ground) that are irrelevant to the real world. Learning from electoral victory or failure is extremely important for a democracy as they shape and influence political and policy thought for the nation. One might erroneously speculate that religious polarization or the promise of zero taxes, for example, wins elections, prompting all political parties to join in their quest for electoral victory, leaving the nation irreparable. damage occurs. Attributing causes to electoral outcomes in a democracy is a serious exercise that must be done with utmost rigor and care by experts. It is too important and dangerous to reduce it to dramatization for television or lazy research.
Praveen Chakraborty is a political economist and head of the data analytics department of the Congress party.
Election results and the danger of misinterpretation
Placards with portraits of some of the victims of the Morbi tragedy are placed near the site of the bridge collapse on November 10, 2022. Photo credit: The Hindu
On 26 October, a 19th-century bridge over the Machchu river in Gujarat’s Morbi city was opened to the public in a grand show, built with money from local people. five days later, the the bridge collapsed, An estimated 135 people were killed and injured 180 others. It was clear that mischief and dubious bargaining had taken place in awarding the contract for the restoration of the bridge to an inexperienced private firm. The Bharatiya Janata Party (BJP) was (and is) in power in state and local administration; The local MLA was also from BJP.
fall into the trap
A little more than a month later, state elections were held in December where the electorate of Morbi voted. Around 50,000 people in Morbi voted for the BJP in either the 2017 or 2020 bypolls. That is, immediately after the bridge collapse and where many lives were lost, the people of Morbi rewarded the BJP by voting for the party in higher numbers than before. BJP’s vote share in Morbi is 60% in 2022, compared to just 45% in 2017. In fact, even in polling areas near the collapsed bridge, more voters voted for the BJP in 2022. 2017. Can we infer that the BJP won the Morbi constituency only because a bridge collapsed and many lives were lost?
This is clearly a silly and facetious, but intentionally provocative question. Such stupid questions insult our basic intelligence and attack our moral senses. If any, the real question is: Why didn’t the voters of Morbi punish the BJP for this tragedy, especially when it happened weeks before the election?
Yet, if one looks at it objectively and in an abstract way, an event x happened (i.e., the bridge collapsed) and then a seemingly related event y happened (BJP’s victory). It is tempting and intuitive for the human mind to correlate the two and conclude that x led to y.
This happens all the time in our public remarks.
In the rush to interpret election results, media commentators and even so-called experts such as pollsters and political scientists constantly fall into this trap. If a political party makes an election promise or carries out a specific campaign (x) and then that party wins the election (y), commentators immediately conclude that the party won the election because of its promise (x to y). Went. Why is it that the “x to y” argument seems so absurd in the case of a bridge collapse, but completely plausible in the case of an election promise or campaign, even though the underlying logic is exactly the same? Because, context matters.
Just as it is illogical to claim that two events – the collapse of a bridge due to BJP’s misrule and the BJP’s subsequent victory in that constituency – show a causal relationship, it is equally illogical to claim so without hard evidence that a particular campaign or a promise or an event led to an electoral victory or defeat.
simplified correlation
Pollsters often ask people what their top issues are, and then how they plan to vote, to determine what influences people’s voting choices. They then simply correlate the two to draw strong conclusions. For example, a survey may show that people want lower taxes. If a political party promises lower taxes and wins an election, it does not mean that the party won because it promised lower taxes, although that sounds counterintuitive. A more rigorous way of analyzing this is to ask: Would that party not have won the election if it had not promised lower taxes?
Philosopher Karl Popper famously argued that unless a theory can pass the test of ‘falsifiability’, it cannot be considered absolute truth. To put it simply, he said that claiming that all swans are white must also conclusively mean that there is not a single black swan. economist Abhijit Banerjee, Esther Duflo and Michael Kremer won the Nobel Prize (2019) to develop a method called randomized control trial (RCT) experiments designed to conclusively predict whether x leads to y in policy experiments such as whether providing mid-day meals in schools would improve educational outcomes. A simplified version of such RCTs can be adapted to electoral surveys to draw more robust conclusions.
In our example, two sets of survey questions can be designed, one set explicitly telling voters that a political party has promised lower taxes and the other set in which the party makes no such promise. Voters can be randomly given one of these two questionnaires for a survey of equal sample size. If there is no difference in the party’s vote share in these two survey sets, then it would be clear that the promise of lower taxes has no effect on people’s intention to vote, and if there is a significant difference, it is in favor of the party. It is understandable for Party will promise less tax
This is a more rigorous way of establishing a causal relationship between the two than the current simplistic and widely misleading way of imputing causality, called ‘cross-tab’ analysis by pollsters. This is a major reason why the same election promise or strategy works for just one party or one state or one region or one section of people, while not in others, confusing political parties and leaders.
For example, the Aam Aadmi Party promised many similar things to what the Congress party did in Himachal Pradesh in the run-up to the November elections, but it didn’t seem to be working for them; Nor did a few similar promises work for the Congress party in all the districts of Himachal Pradesh. Misrepresenting causal links to election results through simplistic and non-rigorous narratives and developing a misleading narrative for election results is often more dangerous than no explanation at all.
the last word
It’s easy to dismiss this as some useless academic discussion of scientific methods (by intellectuals far from the ground) that are irrelevant to the real world. Learning from electoral victory or failure is extremely important for a democracy as they shape and influence political and policy thought for the nation. One might erroneously speculate that religious polarization or the promise of zero taxes, for example, wins elections, prompting all political parties to join in their quest for electoral victory, leaving the nation irreparable. damage occurs. Attributing causes to electoral outcomes in a democracy is a serious exercise that must be done with utmost rigor and care by experts. It is too important and dangerous to reduce it to dramatization for television or lazy research.
Praveen Chakraborty is a political economist and head of the data analytics department of the Congress party.