Robust Confidence Sets in the Presence of Weak Instruments

This paper considers instrumental variable regression with a single endogenous variable and the potential presence of weak instruments. I construct confidence sets for the coefficient on the single endogenous regressor by inverting tests robust to weak instruments. I suggest a numerically simple algorithm for finding the Conditional Likelihood Ratio (CLR) confidence sets. The full descriptions of possible forms of the CLR, Anderson-Rubin (AR) and Lagrange Multiplier (LM) confidence sets are given. I show that the CLR confidence sets have nearly shortest expected arc length among similar symmetric invariant confidence sets in a circular model. I also prove that the CLR confidence set is asymptotically valid in a model with non-normal errors