What’s Easy & What’s Not?

Universe
Published

May 3, 2026

Universe problem-definition design

Those who can’t perform addition will not be able to compute square-roots either. State capacity constraints determine which interventions are feasible before any policy design begins.

Origin

This framework builds on Vijay Kelkar and Ajay Shah’s argument in In Service of the Republic, which draws on a landmark paper by Lant Pritchett and Michael Woolcock on state capability.

What it says

Before selecting a policy intervention, the first diagnostic is whether the required state capacity exists, can be built, or is out of reach. A state that cannot collect taxes reliably should not attempt industrial policy. A bureaucracy that cannot process permits efficiently should not design complex subsidy schemes.

The framework is a hierarchy of feasibility. Low-capacity states should choose simple, rules-based interventions that do not demand fine-grained discretion. As capacity accumulates, more sophisticated tools become available. The error is to copy high-capacity policies into low-capacity contexts and expect them to work.

In the Indian context, this explains why some states successfully implement land reforms while others cannot, and why digitisation of welfare delivery works better where administrative backbone already exists.

Applied

  • When prioritising reforms in a resource-scarce environment: start with what the state can actually deliver.
  • When sequencing institutional development: build basic capacity before attempting advanced regulatory design.
  • When evaluating why a well-designed policy failed on the ground.

When it falls short

“State capacity” is often vague and difficult to measure precisely. The framework does not tell you how to build capacity, only what not to attempt without it. Political will and bureaucratic capacity are distinct, and the framework can conflate them.

Further reading

Originally explored in A Framework a Week: What’s Easy & What’s Not? on Anticipating the Unintended.