Aug 2026· Journal of Economic Perspectives· 0 citations· 3 references
Abstract
Most empirical economists have encountered the warning that instrumental variables can be “weak,” but the underlying issues—what makes an instrument weak, why weakness distorts inference, and what to do about it—are less widely understood. This article offers an accessible introduction to the weak instruments problem for the common just-identified case of a single endogenous regressor and a single instrument. We explain why the usual two-stage least squares t-ratio and its “±1.96 times the standard error” confidence interval can yield incorrect inferences, much as homoskedasticity-only standard errors do when errors are not homoskedastic. We then describe practical, robust-to-weak-instrument solutions—including the Anderson-Rubin and tF methods—that deliver valid confidence intervals whatever the instrument's true strength, and we offer some do's and don'ts, notably why the popular “F greater than 10” rule has no theoretical justification in this setting.
Instrumental variable analyses often rely on the assumption that instruments affect the outcome only through the endogenous regressor. In many applications, researchers can defend only a plausible range for direct effects of instruments, while conventional sensitivity analyses may be unreliable when instruments are wea...
Two frequent approaches for identifying structural VARs are external instruments, which carry economic content but are often weak, and non-Gaussianity of the shocks which provides statistical identification but carries no economic meaning. We combine the two strategies in a single generalized method of moments framewor...
In fixed-effect regressions with many groups, fixed effects can absorb most identifying variation, leaving a handful of observations to carry what remains. When variation is this concentrated, conventional $t$-tests can reject a true null more than half the time, and any fixed critical value is either invalid or so con...
We develop a bias-robust causal inference method for observational panel data settings. Such methods typically impute untreated outcomes, so counterfactual error passes straight into the estimated treatment effect while conventional standard errors ignore it. We adapt bias-aware minimax methods, developed for estimatin...
Something is amiss in empirical economics. Despite the advances of the credibility revolution, published estimates tend to be inflated and overconfident. We argue that this stems from a weakness in the dominant econometric framework: treating the researcher like a calculator that mechanically implements the econometric...
M. Stevenson, Joshua B. Fischman· Journal of Economic Literatu...· 3 citations
Claims of the form"we find no evidence that X affects Y"appear throughout the applied finance literature, yet whether such a claim contains evidence of absence or absence of evidence depends entirely on its confidence interval. The term"statistically insignificant"is routinely read to mean zero economic effect. However...
Dai-Yue Tan· 0 citations
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