written by Lant Pritchett
The PDIA approach to building state capability grew out of a sense among practitioner/academics (or “pracademics”) that (a) organizational capability for implementation was key to success—as, if not more important the adoption of new policies or the creation of new programs and (b) that the existing models (both in the mainstream academy and in practice) for building capability in the public sector were not working and not up to the task. Our shorthand name for the latter is “the big stuck”: even when people acknowledge the importance of building state capability and are engaged in projects, programs, and policies to try and do so the facts on the ground are that state capability—at least on all of the standard measures—show little or no progress.
The idea for some new, even something pretty radically new as an approach, like PDIA, did not spring from a desire to create the latest new fad, but from a sense that the devil was not in the details of existing approaches. Existing approaches to build capability were not working because of some minor flaw in the way these actions were themselves implemented, they were failing because key ideas about how to build capability—and even, really, what it was—were under-articulated and often just plain wrong.
Given the long lead time between research and publication the “big stuck” tables in our 2017 book were based on country data only through 2012, which now is 8 years ago. So I went back and updated the book’s Table 1, the “big stuck” table with data from two sources: the Quality of Government indicator (adapted from the International Country Risk Group) from the Quality of Government web-site and three of the state capability indices from the Worldwide Governance Indicators. This brings the big stuck up to 2018 (latest available for these data) and, unfortunately the findings are roughly the same.
As Figure 1 shows the typical level of “quality of government” (measured as a combination of Rule of Law, Bureaucratic Effectiveness, and Control of Corruption) is slightly lower in 2018 than in 1996.
This means that developing countries are dealing with a world with greater and greater complexity, more inter-connectedness—and new and unexpected shocks like COVID-19—all with the same, or less, capability as more than two decades ago. The urgency for new approaches to the developing world’s problems is higher today than ever before.
The details on the data, methods, results (updated Table 1)—and graphs that show the available data for each country—are available here.
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