The use of observational methods remains common in program evaluation. How much should we trust these studies, which lack clear identifying variation? We propose adjusting confidence intervals to incorporate the uncertainty due to observational bias. Using data from 44 development RCTs with...

The use of observational methods remains common in program evaluation. How much should we trust these studies, which lack clear identifying variation? We propose adjusting confidence intervals to incorporate the uncertainty due to observational bias. Using data from 44 development RCTs with...

Evidence suggests that productivity would be much higher and unemployment much lower if the supply of and demand for skills were better matched. As a result, skills mismatch between workers (supply) and jobs (demand) commands the ongoing attention of policymakers in many countries. Policies...

We use a randomized experiment to evaluate the impact of providing richer information about prospective jobs to vocational trainees on their employment outcomes. The setting of the study is the vocational training program DDU-GKY in India. We find that including in the training two information...

Evidence suggests that productivity would be much higher and unemployment much lower if the supply of and demand for skills were better matched. As a result, skills mismatch between workers (supply) and jobs (demand) commands the ongoing attention of policymakers in many countries. Policies...

Do tax systems distort firm-to-firm trade? This paper considers the effect of tax policy on supply chains in a large developing economy, the state of West Bengal in India. Using administrative panel data on firms, including transaction data for 4.8 million supplier-client pairs, we first...

Do tax systems distort firm-to-firm trade? This paper considers the effect of tax policy on supply chains in a large developing economy, the state of West Bengal in India. Using administrative panel data on firms, including transaction data for 4.8 million supplier-client pairs, we first...