Our research-policy engagements form the core of EPoD's activities. The impetus comes from proactive and collaborative interactions, initiated by either the policy or academic side, that focus on a particular policy problem. Our policy partners include state and national government agencies, banks, and civil society organizations. Research-policy engagements can develop over a period of years and typically involve several researchers, our in-country policy partner(s), as well as one of our partnering research organizations.
EPoD uses the term policymaker to refer to actors who are engaged in setting policies and practices that are intended to benefit the public in the areas of economic development, social advancement or governance. This includes politicians and bureaucrats at the local, state and national level, as well as practitioners in nongovernmental organizations and decision-makers in the private, public and civil sectors invested in defining policies and best practices for the public good.
Policy Research Engagements:
Evidence for Policy Design's policy research engagements seek to answer critical questions for policy counterparts, while producing new knowledge on effective policy design, governance, and human behavior that can be published in top economic and policy journals. Below you can explore dozens of studies that fall under our main areas of research:
Across all of these areas, EPoD affiliates work with policy actors to identify barriers that keep rigorous evidence from affecting policy. Based on the results, they build policymaker demand and local capacity for the use of evidence through policy outreach and training efforts. This institutionalizes ongoing learning processes and ensures that policy redesign happens as and when needed.
Our Methodology - Smart Policy Design
Effective policymakers have a deep understanding of policy priorities and the know-how that comes from experience, while applied economists have insights firmly rooted in economic theory and rigorous evidence. Click on each of the steps below to read how Smart Policy Design capitalizes on synergies and prevents wasted efforts by involving policymakers and researchers from the start.
Step One - Identify
The first step is to identify the policy problem. While this may occur in many ways, a successful model is when the involved stakeholders – public, private and academic – come together to combine information on policy priorities and opportunities with economic insights in order to identify a question that can be feasibly approached.
Step Two - Diagnose
Researchers work closely with policy partners, again using insights from economic theory and empirical evidence, to diagnose the market or policy failures that underlie the identified problem. Descriptive data and existing research can often help distinguish between potential explanations and screen for underlying causal factors.
Step Three - Design
The joint policy-research team applies its collective expertise to design policy innovations that are financially, administratively, and politically feasible in addition to being justified by economic principles and well-supported by evidence. Monitoring and feedback mechanisms are built into every design, often including new tech-based platforms for collecting and learning from implementation data.
Step Four - Implement and Test
The Smart Policy Design approach emphasizes rigorous testing at relevant scale, with scientific methods of evaluation used to measure impact – often comparing several designs via large-scale field studies that draw on tools such as randomized controlled trails. Testing the design provides key information on how best to improve and refine the policy (Step 5) and may open up the next frontier of policy questions with new evidence on the nature of the problem.
Step Five - Refine
Smart Policy Design is an iterative approach, where the lessons learned at each stage are used to refine existing designs and identify the next set of objectives and challenges. The aim is to generate a cycle of continuous policy improvement. New knowledge on policy design and impact is shared through academic research, training, policy dialogues and public dissemination.
In Practice - A Case Study
Starting in 2001, we collaborated with government partners and researchers from other institutions on the Learning and Educational Achievement in Pakistan Schools (LEAPS) project to investigate the poor educational outcomes in Pakistan.
Together, we captured the educational universe and its evolution over a ten-year period in more than a 100 villages by testing and tracking over 12,000 children and collecting five rounds of detailed information on over 800 schools, 6000 teachers, and 1800 households.
Learn more about our LEAPS Initiative here.
Using the first round of data, we observed that test scores were low, but that a rising number of small private schools, run out of people’s homes often with female teachers, were outperforming public schools – academically and in terms of instilling civic values – at lower cost.
Yet despite a competitive market and variation in quality across schools, the average quality levels were still low and parents relatively poorly informed about quality differentials.
We evaluated both the supply side of the educational market, where we found that schools were constrained in how best to offer and signal their quality.
On the demand side, we found that while parents were highly invested in children’s education, they often faced limited information in terms of selecting the best school given their resources.
We designed a randomized controlled trial whereby parents and schools would receive child-level and school-level information on learning outcomes in the form of report cards for all schools in the village.
The report cards included test scores on English, Math and Urdu (the vernacular).
The team ran this intervention in over 800 public and private schools across 112 villages, with half of the villages receiving the report card treatment.
In response to treatment, average test scores improved, enrollment increased, and average private school fees decreased. Interestingly, initially low-performing private schools improved quality while initially high-performing private schools decreased fees.
There was also evidence that public schools increased quality. Given the relatively low cost of the intervention, the benefits were substantially higher than program price.
Our results were presented at numerous conferences, and have been successful in changing the educational debates in the country.
New efforts have sprung up by independent NGOs and the Punjab government through the Punjab Examination Commission (PEC) to test children regularly and disseminate the results to help parents make better decisions and schools compete on quality. However, the intervention also revealed real financial and educational innovation constraints schools face in enhancing quality.
As a result the team has now started work with micro-finance and educational service providers on introducing innovative financial products and educational support services tailored to the needs of the low-cost educational sector.