Despite the widespread use of graphs in empirical research, little is known about readers' ability to process the statistical information they are meant to convey ("visual inference"). We study visual inference within the context of regression discontinuity (RD) designs by measuring how...

Different episodes of economic growth display widely varying distributional characteristics, both across countries and over time. Growth is sometimes accompanied by rising and sometimes by falling inequality. Applied economists have come to rely on the Growth Incidence Curve, which gives the...

This paper has two main parts. In the first, we describe a method that smooths the objective function in a general class of indirect inference models. Our smoothing procedure makes use of importance sampling weights in estimation of the auxiliary model on simulated data. The importance sampling...

The economics 'credibility revolution' has promoted the identification of causal relationships using difference-in-differences (DID), instrumental variables (IV), randomized control trials (RCT) and regression discontinuity design (RDD) methods. The extent to which a reader should trust claims...

Time-use researchers are typically interested in the time use of individuals, but time use data are samples of person-days. Given day-to-day variation in how people spend their time, this distinction is analytically important. We examine the conditions necessary to make inferences about the time...

Shared-frailty survival models specify that systematic unobserved determinants of duration outcomes are identical within groups of individuals. We consider random-effects likelihood-based statistical inference if the duration data are subject to left-truncation. Such inference with...

We examine a new general class of hazard rate models for survival data, containing a parametric and a nonparametric component. Both can be a mix of a time effect and (possibly time-dependent) marker or covariate effects. A number of well-known models are special cases. In a counting process...

A growing literature on inference in difference-in-differences (DiD) designs with grouped errors has been pessimistic about obtaining hypothesis tests of the correct size, particularly with few groups. We provide Monte Carlo evidence for three points: (i) it is possible to obtain tests of the...

We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. This design arises in many institutional settings where a policy variable (such as weekly...