The efficient market hypothesis (EMH) in economics states that the price of an asset at a given time reflects all available information. EMH gained credibility and acceptance with the advent of computing power and the work of many economists, most notably Eugene Fama from the University of Chicago, in the 1960s. EMH was built upon earlier work and theories, including the work of French mathematician Louis Bachelier and the random walk hypothesis (RWH), which suggested that prices of assets evolve along a random walk and thus cannot be predicted. One of the critical assumptions underlying EMH is that market participants have rational expectations and as a whole have a normally distributed set of views that then results in a random (unpredictable) pattern of asset prices.

Believers in EMH cite evidence that active money managers in aggregate have not been able to beat stock market indices. Even the legendary Warren Buffett has underperformed the S&P 500 in the most recent decade. Critics point to long price trendlines in certain stocks and market breaks such as the financial crisis of 2008 that demonstrate “herd behaviour". The most promising area of research since the 1980s and 1990s that critiques EMH as incomplete has emerged from the field of behavioural economics.

The study of the impact of cognitive, psychological, emotional and social factors on the economic decision-making of individuals and institutions gave rise to the field of behavioural economics (BE). Behavioural economists believe that individuals do not always behave rationally and that they make decisions that are a result of “rules of thumb". These decisions reflect the cognitive biases of the decision maker. In a way, BE goes back to an earlier era of classical economics that had Adam Smith and Jeremy Bentham as its exponents.

The pioneering giants in the field of behavioural economics are Daniel Kahneman and his long-time collaborator Amos Tversky. While at Stanford University, they intersected with Richard Thaler, now at the University of Chicago. Kahneman, Tversky, Thaler, and Robert Shiller of Yale University (who have won three Nobel Prizes among them) have together contributed a credible challenge to EMH. BE suggests that cognitive biases such as overconfidence, loss aversion, anchoring and hyperbolic discounting impact decision-making, and in so doing impact prices and markets. The beauty of the elements that underly behavioural economics is that they apply to any field where human decisions at an aggregate level across vast numbers matter—in economics, finance and electoral politics.

The use of behavioural science in influencing the choice of voters can take two (opposite) forms. One form is to use the cognitive biases to your advantage by feeding these biases. The other is to “nudge" against these biases so that the polity can make non-intuitive but desirable policy choices. Populist leaders around the world are astute students of group psychology and are exploiting cognitive biases to ensure electoral victory and post-election relevance. US President Donald Trump has demonstrated his mastery of psychology by using (1) identification: make continual disparaging comments about minorities in such a manner that the core base “see themselves" in their candidate; (2) utility: repeatedly communicate the value of the expected campaign results for the core base’s own prospects; and (3) loss aversion: motivate the core base with the idea that this is the last chance to regain lost economic and societal status. Trump used other techniques as well, such as “loss framing" and “reference points".

This year’s Economic Survey claims that the Indian government has used behavioural economics to influence public opinion on policy. In tabular form, it classifies several policies on the influence spectrum from “laissez faire" to “nudge" to “incentivise" to “mandate". The government appears to have a rather confused signalling policy—attempting to use both pro-bias populism and anti-bias encouragement. Numerically, small ideas such as the “super-rich" tax are actual examples of this populist signalling. On the nudge side, Prime Minister Narendra Modi has successfully used his pulpit to build awareness about toilet usage. However, the actual efficacy of these nudges has been shrouded in non-transparency because there have been no credible third-party evaluations done. The Pradhan Mantri Ujjwala Yojana (PMUY) has successfully provided first-time LPG cylinders to 50 million households. However, most independent researchers concur that the behavioural transformation that would lead to sustained use faces many impediments. So, the “nudge" to convert kitchens to a cleaner and more efficient fuel is not really complete.

Being cognizant of behavioural biases is a useful way to set a course for large-scale transformations in a heterogenous country like India. Systematic, independent studies can inform us about the efficacy of the behavioural transformation in question, and should be used to tweak and improve programmes. The lifeblood of these studies is clean, unbiased data. Trapped by the populist urge to signal “all is well", the government has followed a non-rigorous and non-transparent approach to data. This must change if we are indeed serious in our efforts to nudge behaviour and impact people.

PS: “The ideal organizational environment encourages everyone to observe, collect data and speak up," said Richard Thaler.

Narayan Ramachandran is chairman, InKlude Labs. Read Narayan’s Mint columns at www.livemint.com/avisiblehand

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