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Pritchett, Lant

India is an emerging global superpower as its rapid growth has transformed its economy and has maintained itself as the world’s largest democracy. But at the same time India lags in many dimensions—its malnutrition rate is one of the highest in the world, its immunization rates are lower than most African countries, and Bangladesh has a better infant mortality rate. I argue that this is in part because the India state is “flailing”—its very capable head is not longer reliably connected to the arms and legs of implementation. In the four-fold transition of economy, polity, administration, and society the administrative capability of the state is lagging. I use examples from services like health, education, and routine transactions like issuing driver’s licenses to show that the agents of the state routinely do not implement the tasks they are assigned—causing a massive divergence between de jure and de facto reality. The paper concludes with speculations about the causes of flailing and possible future trajectories.

Many reform initiatives in developing countries fail to achieve sustained improvements in performance because they are merely isomorphic mimicry—that is, governments and organizations pretend to reform by changing what policies or organizations look like rather than what they actually do. In addition, the flow of development resources and legitimacy without demonstrated improvements in performance undermines the impetus for effective action to build state capability or improve performance. This dynamic facilitates “capability traps” in which state capability stagnates, or even deteriorates, over long periods of time even though governments remain engaged in developmental rhetoric and continue to receive development resources. How can countries escape capability traps? We propose an approach, Problem-Driven Iterative Adaptation (PDIA), based on four core principles, each of which stands in sharp contrast with the standard approaches. First, PDIA focuses on solving locally nominated and defined problems in performance (as opposed to transplanting preconceived and packaged “best practice” solutions). Second, it seeks to create an authorizing environment for decision-making that encourages positive deviance and experimentation (as opposed to designing projects and programs and then requiring agents to implement them exactly as designed). Third, it embeds this experimentation in tight feedback loops that facilitate rapid experiential learning (as opposed to enduring long lag times in learning from ex post “evaluation”). Fourth, it actively engages broad sets of agents to ensure that reforms are viable, legitimate, relevant, and supportable (as opposed to a narrow set of external experts promoting the top-down diffusion of innovation).

We estimate the “place premium”—the wage gain that accrues to foreign workers who arrive to work in the United States. First, we estimate the predicted, purchasing-power adjusted wages of people inside and outside the United States who are otherwise observably identical—with the same country of birth, country of education, years of education, work experience, sex, and rural or urban residence. We use new and uniquely rich micro-data on the wages and characteristics of over two million individual formal-sector wage-earners in 43 countries (including the US). Second, we examine the extent to which these wage ratios for observably equivalent workers may overstate the gains to a marginal mover because movers may be positively selected on unobservable productivity in their home country. New evidence for nine of the countries, combined with a range of existing evidence, suggests that this overstatement can be significant, but is typically modest in magnitude. Third, we estimate the degree to which policy barriers to labor movement in and of themselves sustain the place premium, by bounding the premium observed under self-selected migration alone. Finally, we show that the policy-induced portion of the place premium in wages represents one of the largest remaining price distortions in any global market; is much larger than wage discrimination in spatially integrated markets; and makes labor mobility capable of reducing households’ poverty at the margin by much more than any known in situ intervention.

Firms in Africa report "regulatory and economic policy uncertainty" as a top constraint to their growth. We argue that often firms in Africa do not cope with policy rules, rather they face deals; firm-specific policy actions that can be influenced by firm actions (e.g. bribes) and characteristics (e.g. political connections). Using Enterprise Survey data we demonstrate huge variability in reported policy actions across firms notionally facing the same policy. The within-country dispersion in firm-specific policy actions is larger than the cross-national differences in average policy. We show that variability in this policy implementation uncertainty within location-sector-size cells is correlated with firm growth rates. These measures of implementation variability are more strongly related to lower firm employment growth than are measures of "average" policy action. Finally, we show that the de jure measures such as Doing Business indicators are virtually uncorrelated with ex-post firm-level responses, further evidence that deals rather than rules prevail in Africa. Strikingly, the gap between de jure and de facto conditions grows with the formal regulatory burden. The evidence also shows more burdensome processes open up more space for making deals; firms may not incur the official costs of compliance, but they still pay to avoid them. Finally, measures of institutional capacity and better governance are closely associated with perceived consistency in implementation.

Learning profiles that track changes in student skills per year of schooling often find shockingly low learning gains. Using data from three recent studies in South Asia and Africa, we show that a majority of students spend years of instruction with no progress on basics. We argue shallow learning profiles are in part the result of curricular paces moving much faster than the pace of learning. To demonstrate the consequences of a gap between the curriculum and student mastery, we construct a simple, formal model, which portrays learning as the result of a match between student skill and instructional levels, rather than the standard (if implicit) assumption that all children learn the same from the same instruction. A simulation shows that two countries with exactly the same potential learning could have massively divergent learning outcomes, just because of a gap between curricular and actual pace—and the country which goes faster has much lower cumulative learning. We also show that our simple simulation model of curricular gaps can replicate existing experimental findings, many of which are otherwise puzzling. Paradoxically, learning could go faster if curricula and teachers were to slow down.

The prevailing aid orthodoxy works well enough in stable environments, but is ill-equipped to navigate contexts of volatility and fragility. The orthodox approach is adept at solving straightforward technical or logistical problems (paving roads, building schools, immunizing children), but often struggles or outright fails when faced with complex, adaptive challenges (fighting corruption, upholding the rule of law, establishing democratic institutions). South Sudan, the world’s newest country, presents a post-conflict environment full of complex, adaptive challenges. Prior to the signing of the Comprehensive Peace Agreement (CPA) in 2005 South Sudan had no formal institutions of self-governance. During the CPA period and after independence in 2011, foreign development agencies have contributed billions of dollars of aid and technical assistance to "build capacity" in the nascent Government of South Sudan (GoSS). The donors utilized approaches and mechanisms of support that at least nominally reflect the prevailing aid orthodoxy. We argue that orthodox state building and capacity building more or less failed in South Sudan, leaving the world’s newest country mired in a "capability trap" (Andrews, et al 2012). Despite countless trainings, workshops, reforms, and a large corps of foreign technical assistants embedded within state ministries, there is an absence of real change, and GoSS now "looks like a state" but performs as anything but. The challenges presented by this new, complicated, post-conflict country demand innovative approaches to building state capability which go beyond importing "best practice" solutions while feigning "client ownership." We explore one such approach to disruptive innovation that has emerged: Problem Driven Iterative Adaptation (PDIA). To escape from the world's newest capability trap, South Sudan’s government and its international donors must challenge themselves to imagine innovative paths to state building, which diverge from "business as usual" and attempt to create something that lasts.

Efforts to build state capability often take the form of commonly used, highly designed and engineered best practice solutions that have worked in many other places and that we suspect (and hope) will work again in many contexts. Such interventions do sometimes work, especially when the treatment actually addresses problems that fester in the context. Where the contextual problems are different, however, the treatment is just isomorphic mimicry—it looks good but will not be a solution to problems that actually matter. Development organizations often cannot see this, however, and offer the same solution again and again—hoping for a different outcome but imposing a capability trap on the policy context, where a new diagnosis and prescription is actually needed. In some countries the treatment has an even worse impact, fostering premature load bearing—where the context cannot actually handle what is prescribed. How can development experts identify in advance where they will have such negative impacts, and how can they identify in advance where they need to do development differently? This paper addresses such questions, and introduces an approach to building state capability in the latter contexts (called 1804 contexts), called problem driven iterative adaptation.

The enthusiasm for the potential of RCTs in development rests in part on the assumption that the use of the rigorous evidence that emerges from an RCT (or from a small set of studies identified as rigorous in a “systematic” review) leads to the adoption of more effective policies, programs or projects. However, the supposed benefits of using rigorous evidence for “evidence based” policy making depend critically on the extent to which there is external validity. If estimates of causal impact or treatment effects that have internal validity (are unbiased) in one context (where the relevant “context” could be country, region, implementing organization, complementary policies, initial conditions, etc.) cannot be applied to another context then applying evidence that is rigorous in one context may actually reduce predictive accuracy in other contexts relative to simple evidence from that context—even if that evidence is biased (Pritchett and Sandefur 2015). Using empirical estimates from a large number of developing countries of the difference in student learning in public and private schools (just as one potential policy application) I show that commonly made assumptions about external validity are, in the face of the actual observed heterogeneity across contexts, both logically incoherent and empirically unhelpful. Logically incoherent, in that it is impossible to reconcile general claims about external validity of rigorous estimates of causal impact and the heterogeneity of the raw facts about differentials. Empirically unhelpful in that using a single (or small set) of rigorous estimates to apply to all other actually leads to a larger root mean square error of prediction of the “true” causal impact across contexts than just using the estimates from non-experimental data from each country. In the data about private and public schools, under plausible assumptions, an exclusive reliance on the rigorous evidence has RMSE three times worse than using the biased OLS result from each context. In making policy decisions one needs to rely on an understanding of the relevant phenomena that encompasses all of the available evidence.

There is an inherent tension between implementing organizations—which have specific objectives and narrow missions and mandates—and executive organizations—which provide resources to multiple implementing organizations. Ministries of finance/planning/budgeting allocate across ministries and projects/programmes within ministries, development organizations allocate across sectors (and countries), foundations or philanthropies allocate across programmes/grantees. Implementing organizations typically try to do the best they can with the funds they have and attract more resources, while executive organizations have to decide what and who to fund. Monitoring and Evaluation (M&E) has always been an element of the accountability of implementing organizations to their funders. There has been a recent trend towards much greater rigor in evaluations to isolate causal impacts of projects and programmes and more ‘evidence base’ approaches to accountability and budget allocations. Here we extend the basic idea of rigorous impact evaluation—the use of a valid counter-factual to make judgments about causality—to emphasize that the techniques of impact evaluation can be directly useful to implementing organizations (as opposed to impact evaluation being seen by implementing organizations as only an external threat to their funding). We introduce structured experiential learning (which we add to M&E to get MeE) which allows implementing agencies to actively and rigorously search across alternative project designs using the monitoring data that provides real time performance information with direct feedback into the decision loops of project design and implementation. Our argument is that within-project variations in design can serve as their own counter-factual and this dramatically reduces the incremental cost of evaluation and increases the direct usefulness of evaluation to implementing agencies. The right combination of M, e, and E provides the right space for innovation and organizational capability building while at the same time providing accountability and an evidence base for funding agencies.

Learning profiles that track changes in student skills per year of schooling often find shockingly low learning gains. Using data from three recent studies in South Asia and Africa, we show that a majority of students spend years of instruction with no progress on basics. We argue shallow learning profiles are in part the result of curricular paces moving much faster than the pace of learning. To demonstrate the consequences of a gap between the curriculum and student mastery, we construct a simple, formal model, which portrays learning as the result of a match between student skill and instructional levels, rather than the standard (if implicit) assumption that all children learn the same from the same instruction. A simulation shows that two countries with exactly the same potential learning could have massively divergent learning outcomes, just because of a gap between curricular and actual pace—and the country which goes faster has much lower cumulative learning. We also show that our simple simulation model of curricular gaps can replicate existing experimental findings, many of which are otherwise puzzling. Paradoxically, learning could go faster if curricula and teachers were to slow down.