This article reviews recent significant progress made in develo** estimation and inference
methods for nonlinear models in the presence of mismeasured data that may or may not …

Publisher Summary This chapter discusses latent variable models in econometrics. The
essential characteristic of a latent variable is revealed by the fact that the system of linear …

We introduce a factor approach to performance measurement of global ESG equity
investments. We construct ESG pure factor portfolios (PFP) following Fama-MacBeth; then …

Economists have devoted increasing attention to the magnitude and consequences of
measurement error in their data. Most discussions of measurement error are based on the …

GIVEN A LINEAR REGRESSION MODEL with measurement errors in variables, this paper
shows how simple functions of the model data can be used as instruments for two staged …

Current practice in structural modeling of observed continuous random variables is limited to
representation systems for first and second moments (eg, means and covariances), and to …

We consider a multiple mismeasured regressor errors-in-variables model where the
measurement and equation errors are independent and have moments of every order but …

Causal modeling is an informal name attached to a class of methods of multivariate analysis
concerned with testing structural theories of a phenomenon. In most cases, these structural …

ESG factors are becoming mainstream in portfolio investment strategies, attracting
increasing fund inflows from investors who are aligning their investment values to …

Traditionally, an assumption underlying econometric models is that the regressors are
observed without measurement error. In practice, however, economic observations, micro …