“Simple” is the opposite of both “complex” and “complicated”. But, as political economist Yuen Yuen Ang has eloquently shown, the two words mean very different things.

She illustrates this with an example. A toaster is complicated. It has many different parts, all of which must work for it to deliver toast. A tree is complex. It has many different parts and processes, which enable it to exist and reproduce. When these are impaired, then all or some of its parts respond to try and keep the tree functional and reproductive. This involves adaptation and evolution. If the response is malignant, the tree ceases to exist.

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The “scientific approach” used by economists, engineers, and the like views problems as more or less complicated. It seeks to simplify them or to empirically understand the contours of complicatedness (called being “data driven”) to derive policy solutions. In contrast, scientists and philosophers attempt to understand the workings of complexity to arrive at solutions that are progressive and avoid malignancy. Data is used to draw inferences to understand complexity, not to prove or disprove complicated propositions.

This distinction is especially vital at the present juncture. Economists have, finally, abandoned simplistic approaches such as rational expectations and the efficient markets hypothesis to address economic challenges. There is growing interest in studying how sociology, political institutions, and human behaviour impact economic decision-making.

But the lens continues to be that of complicatedness, not complexity. Economics continues to treat the problem as one in which the complications introduced by such things as human behaviour need to be addressed, leading to the rise of behavioural economics as a discipline. This posited three ways to solve the problem of complicatedness. First, asserting that people behaved not as individuals but as herds. This amazing vulgarisation of societal dynamics was then added to by positing that people could be “nudged” into the right kinds of behaviours to make better choices. Both these approaches captivated policymakers, leading to facile advertising agency-type recommendations becoming the stuff of policy initiatives. This included predicting herd behaviour to estimate the trajectory of economic growth, and setting up “nudge” units in government, aided by a cohort of intellectually questionable consulting firms quick to jump on to this bandwagon.  On the empirical “data-driven” side, randomised control trials (RCTs) entered economics from medicine to generalise from the particular about things as diverse as education policy and social protection.

These approaches utterly and completely failed for they sought to address phenomena that were perceived as complicating a simple theoretical approach — the rational self-interested maximisation of economic utility by all economic participants. There was no attempt to understand that the policy canvas was, in fact, a complex one and it was the failure to create a framework to understand and address this complexity that led to the problem in the first place. They were trying to fix a tree as if it were a toaster.

Today, despite Nobel prizes to the economists who propounded these approaches, behavioural economics stands discredited, RCTs are no longer used anywhere except in development economics, (typically the dustbin where failed experiments are consigned) and nudge units have quietly been wound up.

But the problem has not gone away. There continues to be little understanding of perhaps the two most important phenomena of our times: The sharp rise in inequality that has accompanied an unprecedented rise in human prosperity, and the increasing and genuine popularity of bigoted political platforms that clearly and obviously detract from prosperity.

Both are global phenomena. Bigotry and populism are central features of the Indian, Brazilian, American, Italian and Swedish landscapes, even as all these countries face an unprecedented challenge in addressing inequality. So, positing simplistic binary relationships between democracy/autocracy/ bigotry and economic prosperity will not help. Nor will explanations that seek to establish populism as somehow a consequence of chicanery and misinformation or an “insider-outsider” problem — the pro-Brexit British Prime Minister, a rich prig married to a billionaire heiress but ethnically of Indian-origin, is, like Donald Trump, radically different from the support base that voted his party in. India’s second-poorest state is steadfast in its endorsement of authoritarian populism. Jair Bolsonaro’s support in Brazil came, like Mr Trump’s, from the losers in the inequality stakes. The prosperous winners, whether in South India, or coastal Brazil, or the United States continue to opt for less regressive alternatives. Women, despite significant gender oppression, continue to be enthusiastic voters and leaders of bigoted parties and movements, as do people from ethnic minorities and many disadvantaged castes and tribes.

To give just one example, those who propagate a universal basic income (UBI) to address inequality do not see that if economic development and prosperity were more inclusive, a UBI would not be necessary in the first place. But all of progressive economics has argued for a welfare state to compensate those excluded from economic prosperity. They have ignored things like industrial and income policies to enable their participation in creating economic prosperity. The people impacted see this, and vote and support what they can get out of the zero-sum game of bigotry and the compensatory game of subsidies and “freebies”.

An analytical approach that unpacks and makes sense of this complexity is urgently needed, to build a progressive alternative to the inequality-accepting, bigotry-promoting, political majority that is now in the ascendant. 

rathinroy@outlook.com. The writer is a macro-fiscal and political economist, and former member of the Economic Advisory Council to the Prime Minister