In empirical work in economics it is common to report standard errors that account for clustering of units. Typically, the motivation given for the clustering adjustments is that unobserved components in outcomes for units within clusters are correlated. However, because correlation may occur...

Regardless of the field, forecasts are widely used and yet assessments of the embedded uncertainty—the magnitude of the downside and upside risks of the prediction itself—are often missing. Particularly in policy-making and investment, accounting for these risks around baseline predictions...

Three recent rounds (2003, 2006, and 2009) of the Family Income and Expenditure Survey are matched to rainfall data from 43 rainfall stations in the Philippines to quantify the extent to which unusual weather has any negative effects on the consumption of Filipino households. It is found that...

In empirical work in economics it is common to report standard errors that account for clustering of units. Typically, the motivation given for the clustering adjustments is that unobserved components in outcomes for units within clusters are correlated. However, because correlation may occur...

Inference using large datasets is not nearly as straightforward as conventional econometric theory suggests when the disturbances are clustered, even with very small intra-cluster correlations. The information contained in such a dataset grows much more slowly with the sample size than it would...

We consider inference in regression discontinuity designs when the running variable only takes a moderate number of distinct values. In particular, we study the common practice of using confidence intervals (CIs) based on standard errors that are clustered by the running variable. We derive...