Joining the dots in India: a ‘thicker’ base for policy reform

Photo of low-income homes on the hillside in India

The central challenge for economic policy in a developing country is to sustain or raise rates of economic growth.


Just as a doctor might gather information of different sorts in order to understand the causes of a patient’s symptoms, a 'thicker' diagnostic approach can also be used by public authorities to determine the causes of systemic issues to inform policy choices. The process of diagnosing a policy issue is an essential first step in tackling it through reform measures and as such, diagnostic approaches are increasingly being employed by decision makers in low- and middle-income countries.

In India – a country with strong growth in recent years, but also wide disparities and unique features and problems – and other countries, there are two distinct types of academic approach to diagnostics. The first more traditional approach starts ‘downstream’, listing the economic or outcome-level problems (symptoms) evident in the country, looking at how serious different problems are and their possible causes without necessarily delving too deeply into the wider interactions of politics, institutions and society. Whereas a second set of approaches start ‘upstream’ with those very features. The latter ‘upstream’ approach may successfully describe the politics and social dynamics within a country, but it’s hard to be precise about the main impacts of politics and social foundations however well they are described.

A ‘thicker’ diagnostic can be conducted if we focus on the similarities between these approaches – namely, how different sets of features impact others. Information of different types can then be assembled in “layers” of these features. At the very least there are “upstream” and “downstream” layers including environmental, political and social foundations; institutions; public and private sector production; and outcomes.

Sifting through this evidence and considering the interactions and feedback loops between the layers allows long ‘chains of causality’ to emerge, which help describe not just causes of growth, but also the underlying causes of these causes. In the case of India it’s possible to pull out two long chains of causality impacting growth: the ‘missing middle’ and the ‘low-human-capital-rural-trap’.

The former describes a situation in which the formal marketplace within the country consists of a small number of old, large and highly capitalised firms and very few younger, smaller firms – the absence of small and medium-sized enterprises being the ‘missing middle’. Operating around this formal sector, there exists a huge informal market with far less capital and much lower labour productivity. These can be considered downstream symptoms of an historical ‘elite bargain’ which sees barriers to market entry with regulation enforced in an asymmetric way to protect the interests of those connected to power. Recent India Government policies to promote innovation, start-ups, manufacturing, skills and financial inclusion seek to deal with parts of this problem.

The second chain describes a situation that sees constraints on investment in human capital founded in deep social disempowerment along gender, caste and tribal lines – with women, girls and low status groups strongly disadvantaged. This disadvantage is reinforced by social discrimination in both service delivery – particularly in rural areas – and in the labour market, where women and other disadvantaged groups, even those who have been educated, face insurmountable barriers to work. These biases are further compounded by social norms that see women and girls discriminated against at the household level.

Moreover, Indian politics has historically been a high stakes game because of the profits of being an insider. Historically, the strategy for winning elections was clientelism: direct rewards for votes. The modern version of this strategy still seems to produce a distinct bias towards the public provision of private goods, handouts and subsidies, rather than public goods like education and health. Public provision of healthcare in India is particularly low by international standards. A combination of handouts which are easy to access in rural areas and the bias against public goods is another reinforcement of the low-human-capital-rural-trap.

These few “long chains” don’t cover the full complexity of growth in India and merely link together parts of understanding that are already well established, but in describing the deeper causes of immediate problems and some key interactions, they make it possible to think differently about what might be done about the problems.

The greater the evidence base and the more developed the chains, the deeper the understanding of these interactions and the more tailored the conclusions around the impact of different policy options can become. For example, increased funding for public services is unlikely to be enough to break through the low human capital trap because there would still be social bias against investing in women and girls and against providing services to low status groups. Instead, a more focused, proactive approach that sees education, nutrition and health services targeted solely at disempowered groups – potentially with rewards for enrolment and with special service providers – might lead to more meaningful outcomes in the Indian context.

Any sort of diagnostic requires evidence – policy diagnostics are no different. Whereas a doctor may prescribe medical solutions based on evidence of symptoms alone, to be truly committed to evidence-based policymaking we need to consider a ‘thicker’ approach that brings together and assesses all the available evidence and the interactions therein. This is analogous to a doctor considering “what sort of patient am I dealing with” as well as looking at the primary symptoms. With this in mind, the role of the diagnostic becomes not so much to provide policy solutions, but rather to highlight winners and losers from different reform options, revealing the unintended impacts of different policies and providing policymakers with the information they need to start – or stop – actions that will influence growth in their unique contexts.

Stevan Lee is a Principal Economist at Oxford Policy Management. He has extensive in-country advisory experience, including a nine-year residency in African countries and in the Middle East. He has spent a large part of his career working with academics – getting academic work into a useful form for policy advice with the UK Department for International Development and the World Bank. 

Stevan was part of an OPM panel event discussing 'Thicker Diagnostics: Expanding development diagnostics'. He presented a practical application of how to do a thicker diagnostic, building on the work presented in this In Focus piece. Watch the event recording on OPM's YouTube channel.

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