This year’s Nobel Prize in Economics was awarded to three economists, Prof. Abhijit Banerjee, Prof. Esther Duflo and Prof. Michael Kremer. Their research was groundbreaking due to an “experimental evidence-based approach” to alleviating global poverty that took a nod from practices in medical and scientific research. The typical approach towards development research can be very top-down. Practitioners can unconsciously make biased generalizations when trying to understand how underprivileged communities make economic decisions when designing policy to alleviate poverty.
The trio sought to design an evidence-based approach that would minimize bias and systematically make a complex issue more understandable, and thereby better identify the causal link between policy prescription and economic outcomes. We wondered if this kind of approach could help generate ideas for improving problems India is facing with procurement contracts in its infrastructure projects.
Their approach heavily relies on randomized control trials (RCTs), a type of research common in medicine and science through which the impact of an intervention is isolated by randomly assigning subjects to two groups. A “treatment” group gets the experimental action and a “control” group does not. By comparing the outcomes of the experiment on the two otherwise comparable groups, the difference in the outcome can be attributed to the intervention. This approach is illustrated in following figure.
Government officials and procurement practitioners could benefit from the approach of the Nobel Laureates in better understanding the complex issues in infrastructure projects in India, where there is a great amount of activity but also many difficulties. Government agencies in India—like in many other developing countries—are currently struggling with problems in infrastructure contracts, particularly with delays, cost overruns and disputes. For example, 373 large infrastructure projects in India have reported cost overrun of INR 3.9 Trillion (approximately US$ 56 Billion), while 552 large projects suffer from delays. Addressing these issues is crucial, as the Government of India is expected to embark on a major infrastructure initiative which would invest INR 100 Trillion (approximately US$ 1.4 trillion) to transform India’s infrastructure in every sector over next 5 years. It could have a profound transformation on the country’s economy.
Certain contract conditions, such as those reducing the transfer of risks to contractors, can result in lower bid prices. Others can lead to better overall performance in the project. There is a plethora of reasons why projects get delayed, stalled or fail. However, this list of problems and risks is so long that it is difficult to know exactly how different aspects influence the overall project outcome.
Currently, government agencies often take reactive approach in modifying bidding parameters and contract conditions without enough analysis of the impact of such changes. By adopting a method similar to the one used by the Nobel Laureates, policymakers and procurement practitioners can to isolate the impact of different contract conditions with randomized control trials to aid in the successful completion of their project. Without such review, changes to bidding parameters may bring in more risks and problems.
Applying the RCT approach might help identify the underlying reasons for contract under performance with more certainty and provide much more effective results in public procurement in India. For example, we could apply bonus clause for early completion in one sufficiently large group of road packages. We could omit this feature from another, comparable group of road packages, and then evaluate its effectiveness, assuming that that other variables are controlled. A similar approach could be taken while shifting from one contract model to another (e.g. admeasurement to design-build). Other elements of the procurement process can also be tested if this approach is applied in a systematic way, with embedded experiments to assess impacts.
Although critics may say that this approach oversimplifies complex problems, it is worth trying if other approaches have lacked credible results.
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