Purpose: This paper examines the associative and causal relationship between changes in the implied volatility index (VIX) and stock market returns, with data from 15 countries representing both developed and emerging economies.1 We also examine the dynamic variation, if any in the nature of the...

We consider the problem of constructing honest confidence intervals (CIs) for a scalar parameter of interest, such as the regression discontinuity parameter, in nonparametric regression based on kernel or local polynomial estimators. To ensure that our CIs are honest, we use critical values that...

Given a set of baseline assumptions, a breakdown frontier is the boundary between the set of assumptions which lead to a specific conclusion and those which do not. In a potential outcomes model with a binary treatment, we consider two conclusions: First, that ATE is at least a specific value...

We provide a simple distribution regression estimator for treatment effects in the difference-in-differences (DiD) design. Our procedure is particularly useful when the treatment effect differs across the distribution of the outcome variable. Our proposed estimator easily incorporates covariates...

China has been implementing energy efficiency and CO2 emission reduction schemes at the provincial level that have been embedded in the National Five Year Plans of the country. We set out to investigate the relationship between R&D expenditures and CO2 emissions in China at the province level in...

As COVID-19 has spread across the globe, several observers noticed that countries still administering an old vaccine against tuberculosis-the BCG vaccine-have had fewer COVID-19 cases and deaths per capita in the early stages of the outbreak. This paper uses a geographic regression discontinuity...

Did Medicaid expansion under the Affordable Care Act affect the course of the COVID-19 pandemic? We answer this question using a regression discontinuity design for counties near the borders of states that expanded Medicaid with states that did not. Relevant covariates change continuously across...

Binned scatter plots are a powerful statistical tool for empirical work in the social, behavioral, and biomedical sciences. Available methods rely on a quantile-based partitioning estimator of the conditional mean regression function to primarily construct flexible yet interpretable...

Binned scatter plots are a powerful statistical tool for empirical work in the social, behavioral, and biomedical sciences. Available methods rely on a quantile-based partitioning estimator of the conditional mean regression function to primarily construct flexible yet interpretable...

In many set-identified models, it is difficult to obtain a tractable characterization of the identified set. Therefore, researchers often rely on nonsharp identification conditions, and empirical results are often based on an outer set of the identified set. This practice is often viewed as...