Volume 4, No. 1, January 2022
Editor: Rashed Rahman
S M Naseem
There has been a notable shift in the methodological perspective adopted by Development Economics (DE) from a predominantly macroeconomic stance in the postwar period to a prevailing microeconomic focus in the 21st century. In the foundational period of its evolution, for a stretch of about 15 years in the 1940s and 1950s, it was deeply influential among both economists and policymakers. It was characterised by a fascination for high theory and grand generalisations that attempted to explain development as an all-encompassing process. Paul Krugman has aptly described this linked set of ideas as “high development theory”. These included, among others, balanced and unbalanced growth, open and disguised unemployment, low-level equilibrium trap, vicious circle of poverty, export pessimism, centre and periphery, and dependency theories and hybrids thereof.
The heart of the pioneers’ work was theory. Their main preoccupation was to deductively explain different patterns of development emerging over time across different regions of the globe. A major reason for the marginalisation of DE from mainstream economics for many decades was the lazy preference by many early development economists to reject the drive toward mathematical rigour, and adopt instead a loose descriptive style in the name of particularism and exceptionalism. Social sciences generally, but DE in particular, have always tried to emulate physical sciences, both through ever more abstruse mathematical modelling and empirical verification. The need for better statistical work, better data and more systematic evidence, however, received much less attention than the passion for theorising.
However, development planning – which became an operational arm of DE in many developing countries – extensively employed the use of mathematical models and collection and analysis of social and economic data. With the arrival of high-speed computer technology over the past two or three decades there has been an unprecedented flurry of activity in empirical economics, which has played a transformative role in DE. Simple regression analysis, the method of randomisation and the analysis of big data have enabled DE to reach new frontiers . The randomised control trials (RCT) approach, propelled by the concerted efforts of the three Nobel laureates and their associates at PAL has swept development economics in the last two or three decades, eclipsing all other approaches in the field. The approach, moreover, has been enormously influential within governments, international agencies, and non-governmental organisations.
The unassuming Nobel trio of Banerjee, Duflo and Kremer places itself on a much lower pedestal than their predecessors, whose average age at the time of receiving the award would probably have been twice its own. While the latter were treated as high priests of DE and pontificated from their ivory towers, the trio’s conception of what economists should be doing to improve the human condition (especially poverty alleviation) is disarmingly down to earth. They see themselves as society’s “plumbers: we solve problems with a combination of intuition grounded in science, some guesswork aided by experience and a bunch of pure trial and error.” Thus the 2019 Nobel laureates were awarded the Prize in explicit recognition of their efforts to address “smaller, more manageable questions,” rather than big ideas. For example, rather than challenging the cuts to the school systems that are forced by austerity, they focused attention on absenteeism by teachers, the effects of school meals and the number of teachers in the classroom on learning.
The signature experimental approach to poverty alleviation pioneered by the three Nobel laureates relies on so-called RCTs. Inspired by studies in medicine, the approach targets specific interventions (also called “treatments”) to a randomly selected group (schools, classes, mothers, etc), and then compares how specific outcomes change in the recipient group versus those who did not receive the treatment. As the groups are assumed to be otherwise similar, the difference in outcomes can be causally attributed to the intervention.
Despite the generally warm and enthusiastic reception the 2019 Nobel laureates have received from all corners of the globe and all shades of economists, they have been criticised for a number of errors of omission and commission. Firstly, for the absence of any political economy discourse of power and wider social change, which they seem to believe to be beyond their calling. Secondly, their data-centric approach and excessive, if not exclusive, reliance on RCTs stands in sharp contrast to the earlier stress on understanding the deeper, systemic causes of poverty and underdevelopment.
At the core of RCTs is the implicit premise that interventions that work in one place can be expected to work in another. This presumes not only that the results of such ‘micro’ interventions are substantially independent of the ‘macro’ context, but also that a focus on such interventions, as opposed to those which reshape that context, is sufficient to address poverty. These premises of ‘separability’ and ‘sufficiency’ are not easily verifiable in most cases and often require a considerable leap of faith. The implicit claim of protagonists of the randomisation approach (often dubbed as “randomistas”) that DE has heretofore not based its theories on robust empirical evidence is moot. Indeed, DE has pioneered the use of both cross-country and microeconomic statistical exercises to understand the mainsprings of growth and development and the alleviation of poverty. The euphoric claim that RCTs have provided DE with a magic key, the so-called ‘gold standard’, in unravelling poverty alleviation policies seems a bit over the top.
Finally, the critics point out that there are diverse ranges of pressing development policy questions where the method of RCT, by its very nature, cannot be applied at all (for example, in many types of monetary-fiscal policy issues, large infrastructural projects or industrial policy issues), although the protagonists of the experimental approach have diversified its scope beyond the earlier preoccupation with health and education interventions in localised contexts to, for example, larger issues of governance or information networking. A major problem with randomisation is that it is tailored for solving the problems of individuals or households. When a programme is community- or economy-wide or there are pervasive spillover effects from those treated to those not, an RCT will be of little help, and may well be deceptive. The tool is only well suited to a rather narrow range of development policies, and often does not address the questions that policymakers ask.
However, it is undeniable that the RCTs are extremely valuable in providing the knowledge of what ‘works’ at the ground level of policy intervention and what does not. Such knowledge has been greatly helpful in leveraging the effectiveness of public welfare and poverty alleviation programmes, which chronically suffer from underinvestment, often because of insufficient mobilisation and/or elite capture of public resources. An interesting finding of the extensive experiments undertaken by PAL and their associates is that the cost of many pro-poor interventions can be fully paid for by the benefits accrued from them (though it is not clear whether the costs include the overhead costs of running such large and expensive programmes).
Given the enormity of the poverty problem facing the developing countries, DE needs to employ every weapon in its armour to slay the dragon, which stands as the greatest threat to jumpstarting the stalled process of development since the 1970s. The innovative approach pioneered by the 2019 Nobel laureates may not be the panacea that they and their associates claim it to be, but it certainly brings DE to the forefront instead of being left on the backburner for so long. It seems obvious that no single approach can alleviate the problem of poverty or revive the stalled process of development, and only a judicious combination of all available approaches will help solve the predicament of the developing countries in the current phase of the crisis of global capitalism. The “randomistas” and the “developmentistas” will have to work hand in hand to bring back the glory of DE.
To use the 2019 Nobel laureates’ metaphor, the development economist will have to work not only as a plumber, but also as an architect and builder of societies with an egalitarian ethos. Also, in order to make the discipline more relevant and holistic, the scope of dialogue will have to be broadened to include interlocutors from grassroots and civil society organisations, as well as environmentalists, sociologists and other experts. Thankfully, the Nobel duo of Banerjee and Duflo, who are a married couple in real life, have chosen to address some of these larger issues in their book, Good Economics for Hard Times, which was published a few months after the announcement of the Nobel Economics Award for 2019 last October.