Instrumental variables estimation can, in principle, avoid biases that ordinary least squares estimation suffers when explanatory variables are correlated with the disturbances. Finding appropriate instruments is a challenge. Ten strategies for avoiding invalid instruments (those correlated with...

We provide a justification for why, and when, endogeneity will not cause bias in the interpretation of the coefficients in a regression model. This technique can be a viable alternative to, or even used alongside, the instrumental variable method. We show that when performing any comparative...

We conduct a simulation study of Local Projection (LP) and Vector Autoregression (VAR) estimators of structural impulse responses across thousands of data generating processes, designed to mimic the properties of the universe of U.S. macroeconomic data. Our analysis considers various...

In this paper we discuss general identification results for Structural Vector Autoregressions (SVARs) with external instruments, considering the case in which r valid instruments are used to identify g ≥ 1 structural shocks, where r ≥ g. We endow the SVAR with an auxiliary statistical model...

When in proxy-SVARs the covariance matrix of VAR disturbances is subject to exogenous, permanent, nonrecurring breaks that generate target impulse response functions (IRFs) that change across volatility regimes, even strong, exogenous external instruments can result in inconsistent estimates of...

The objective of the paper is to draw the theory of endogeneity in dynamic models in discrete and continuous time, in particular for diffusions and counting processes. We first provide an extension of the separable set-up to a separable dynamic framework given in term of semi-martingale...

This paper studies the averaging generalized method of moments (GMM) estimator that combines a conservative GMM estimator based on valid moment conditions and an aggressive GMM estimator based on both valid and possibly misspecified moment conditions, where the weight is the sample analog of an...

The Two-Stage Least squares method for obtaining the estimated structural coefficients of a simultaneous linear equations model is a celebrated method that uses OLS at the first stage for estimating the reduced form coefficients and obtaining the expected values in the arrays of current...

This paper proposes a GMM shrinkage method to efficiently estimate the unknown parameters identified by some moment restrictions, when there is another set of possibly misspecified moment conditions. We show that our method enjoys oracle-like properties, i.e. it consistently selects the correct...

"Statistical adequacy" is an important prerequisite for securing reliable inference in empirical modelling. This paper argues for more emphasis on replication that specifically assesses whether the results reported in empirical studies are based on statistically adequate models, i.e., models...