Misspecified models and noisy covariate measurements are two common sources of bias in statistical inferences. While there is considerable literature on the consequences of each problem in isolation, this article investigates the effect of both problems in tandem. In the context of linear models, the large-sample error in estimating the regression function is partitioned into two terms, one res...

We empirically analyze the impact of transaction costs on the performance of essentially affine interest rate models. We test the implied Euler restrictions and calculate the specification error bound of Hansen and Jagannathan to measure model misspecification. Using both short-maturity and long-maturity bond return data we find, under the assumption of frictionless markets, strong evidence of ...

In a structural error model the structural quasi score (SQS) estimator is based on the distribution of the latent regressor variable. If this distribution is misspecified the SQS estimator is (asymptotically) biased. Two types of misspecification are considered. Both assume that the statistician erroneously adopts a normal distribution as his model for the regressor distribution. In the first t...

We introduce the concept of a Misspecification Equilibrium to dynamic macroeconomics. A Misspecification Equilibrium occurs in a stochastic process when agents forecast optimally given that they must choose from a list of misspecified econometric models. With appropriate restrictions on the asymptotic properties of the exogeneous process and on the feedback of expectations, the Misspecification...

I propose a nonparametric iid bootstrap that achieves asymptotic refinements for t tests and confidence intervals based on the generalized method of moments (GMM) estimators even when the model is misspecified. In addition, my bootstrap does not require recentering the bootstrap moment function, which has been considered as a critical procedure for bootstrapping GMM. The elimination of the rece...

We propose a framework to handle lack of fit problems in structural equation models by analyzing misspecified moments. This framework allows to relate misspecification of the moment equations to biases of parameter estimates and non-centrality of the model. Misspecification of a single moment is shown to lead to misfit of all moments as well as biases in most parameter estimates in full informa...

We explore methods for confronting model misspecification in macroeconomics. We construct dynamic equilibria in which private agents and policy makers recognize that models are approximations. We explore two generalizations of rational expectations equilibria. In one of these equilibria, decision makers use dynamic evolution equations that are imperfect statistical approximations, and in the ot...