This chapter reviews the recent developments in the bunching literature, both when
bunching appears in the outcome variable and when it appears in the treatment variable …

A comprehensive and cutting-edge introduction to quantitative methods of causal analysis,
including new trends in machine learning. Reasoning about cause and effect—the …

This paper studies the bunching identification strategy for an elasticity parameter that
summarizes agents' responses to changes in slope (kink) or intercept (notch) of a schedule …

We study the effects of enrichment activities such as reading, homework, and extracurricular
lessons on children's cognitive and non-cognitive skills. We take into consideration the …

The 1938 Fair Labor Standards Act mandates overtime premium pay for most US workers,
but limited variation in the rule has made assessing its labor market impacts difficult. With …

We propose a simple test of the main identification assumption in models where the
treatment variable takes multiple values and has bunching. The test consists of adding an …

As income and wealth inequality have grown in the United States in recent decades, the
large and growing differences in household expenditures on children from advantaged …

Typical censoring models have mass points at the upper or lower tails, or at both tails, of an
otherwise continuous outcome distribution. In contrast, we consider a censoring model with …

We study the effects of enrichment activities such as reading, homework, and extracurricular
lessons on children's cognitive and non-cognitive skills. We take into consideration that …

This paper shows that kinks or discontinuities in economic incentive schemes, such as taxes
or subsidies, simultaneously identify agents' intensive and participation margin responses …