We discuss a method to estimate the confidence bounds for average economic growth, which is robust to misspecification of the unit root property of a given time series. We derive asymptotic theory for the consequences of such misspecification. Our empirical method amounts to an implementation of the bootstrapping procedure advocated in Romano and Wolf (2001). Simulation evidence supports the th...

Rare variant association studies are gaining importance in human genetic research with the increasing availability of exome/genome sequence data. One important test of association between a target set of rare variants (RVs) and a given phenotype is the sequence kernel association test (SKAT). Assignment of weights reflecting the hypothesized contribution of the RVs to the trait variance is embe...

This paper studies the design of mechanisms that are robust to misspecification. We introduce a novel notion robustness connects a variety disparate approaches and study its implications in wide class of mechanism problems. is quantifiable, allowing us to formalize answer comparative statics questions relating nature and degree misspecification to sharp predictions regarding features of f...

This paper studies the forms of model misspecification that are more likely to persist when an agent compares her subjective with competing models. The learns about action-dependent outcome distribution and makes decisions repeatedly. Aware potential misspecification, she uses a threshold rule switch between models according how well they fit data. A is globally robust if it can against every l...

Summary In observational causal inference, exact covariate matching plays two statistical roles: (i) it effectively controls for bias due to measured confounding; (ii) justifies assumption-free inference based on randomization tests. this paper we show that inexact does not always play these same roles. We find often leaves behind statistically meaningful bias, and renders standard tests asympt...