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Working Paper
Minimum Distance Estimation of Dynamic Models with Errors-In-Variables
Empirical analysis often involves using inexact measures of desired predictors. The bias created by the correlation between the problematic regressors and the error term motivates the need for instrumental variables estimation. This paper considers a class of estimators that can be used when external instruments may not be available or are weak. The idea is to exploit the relation between the parameters of the model and the least squares biases. In cases when this mapping is not analytically tractable, a special algorithm is designed to simulate the latent predictors without completely ...
Working Paper
Tail Sensitivity of US Bank Net Interest Margins: A Bayesian Penalized Quantile Regression Approach
Bank net interest margins (NIM) have been historically stable in the US on average, but this stability deteriorated in the post-2020 period, particularly in the tails of the distribution. Recent literature disagrees on the extent to which banks hedge interest rate risk, and past literature shows that credit risk and persistence are also important considerations for bank NIM. I use a novel approach to Bayesian dynamic panel quantile regression to document heterogeneity in US bank NIM estimated sensitivities to interest rates, credit risk, and own persistence. I find increased sensitivity to ...