Friday, August 13, 2010

Nudging to solve the "last-mile" problems

In a provocative recent op-ed in the New York Times, George Loewenstein, one of the founding fathers of behavioural economics, struck a note of caution on the euphoria surrounding the use of nudge-based solutions to addressing major public policy problems.

"Behavioral economics should complement, not substitute for, more substantive economic interventions. If traditional economics suggests that we should have a larger price difference between sugar-free and sugared drinks, behavioral economics could suggest whether consumers would respond better to a subsidy on unsweetened drinks or a tax on sugary drinks. But that’s the most it can do. For all of its insights, behavioral economics alone is not a viable alternative to the kinds of far-reaching policies we need to tackle our nation’s challenges."

There is no denying the fact that the recent interest in behavioral economics is increasingly showing signs of "irrational exuberance", with a claim for explanation and solution for every problem. But without being a magic-pill for those problems, as I shall attempt to show, behavioral economics has a specific and critical last-mile role in achieving the desired objectives.

The great development challenges of the past half-century have involved putting in place the infrastructure - physical and manpower - to deliver the basic welfare functions of the government. Accordingly, the big challenge was to construct schools and hospitals and recruit adequate numbers of teachers, doctors and nurses. In agriculture, it was to make massive investments in irrigation, encourage use of fertilizers, and enable access to credit and extension services. Similarly, provision of civic services involved massive investments in water, sewerage, electricity, and garbage collection and disposal services.

Government programs were designed with the specific objective of ensuring adequate availability of these basic requirements, and it was presumed that once put in place, the objectives would be automatically achieved. The qualitative side of the problem, the one that focuses on the outcomes, was never the object of much attention.

This approach was understandable since it was time when the basic ingredients were themselves deficient. How do we talk about learning outcomes when there were no adequate teachers and schools; control child mortality and maternal deaths without adequate hospitals and doctors to provide even primary health care; or talk about sanitation and personal hygiene when the majority of households do not have water, sewerage and toilets?

Today, though considerable amount of work still needs to be done, there have been significant advances to meet these infrastructure deficiencies. There is now ample evidence to prove that while all these inputs are necessary, they are not sufficient to achieving the objectives in education, health care, nutritional support, agriculture, and so on.

A different set of challenges have emerged in the achievement of these desired objectives. These include as diverse challenges as getting people to avoid open-defecation and use toilets, parents to send children to school and then college, patients to adhere to a medication schedule, poor people to save more, citizens to keep surroundings clean, and so on.

Harvard economist, Sendhil Mullainathan classifies these as daunting "last-mile" problems. He advocates marrying scientific method with art, psychology, and marketing to address the "frustrating" last mile problem in obtaining successful outcomes using various technological and other innovations.

It is therefore time to reach beyond the inputs-driven paradigm and explore what it takes to get a teacher to teach, a doctor to treat, people to exhibit civic responsibility, and farmers to improve productivity. In view of the complex nature of human interactions, micro-founded public policy approaches that take into account the behavioral biases of individuals may be more effective at addressing these issues.

The regulatory approach to addressing such last-mile problems have failed to yield the desired results, leaving us with only incentives and nudges. While incentives can help to design the most effective decision-making environment, carefully structured nudges can enable actors overcome cognitive biases and take appropriate decisions.

As recent research in behavioral economics has shown, even when incentives are put in place, people often tend to take the sub-optimal decisions. This arises either due to various cognitive biases like decision making inertia (paradox of choice or decision paralysis), complexity with the decision making environment, short term biases etc.

Let us take the example of nurses involved in ante-natal and immunization activities. She would need to record and maintain reports of the various indicators relating to the mother and child over nearly two years, and then take specific time-bound or remedial actions based on those. Even with the best of regulatory architecture and incentive structures, it is well nigh impossible to ensure effective implementation. However, a technology-based solution that uses mobile phones to both collect information and then remind the nurses about their specific actions at the appropriate times, can be an effective nudge in overcoming the last mile-challenge.

Similarly, many other critical modern-day public policy problems involving the last-mile challenges like water and energy conservation, littering and segregation of garbage at homes, promotion of safe-sex, controlling crime and obesity and so on may be more effectively tackled with a careful mixture of incentive structuring and facilitative nudges.

None of this is to ignore the importance interventionist, hard-choices like taxes and mandatory choice requirements. It is surely facile to assume that such complex issues can be resolved with simple regulatory and/or technological fixes.

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