The views expressed in this paper are those of the author and do not imply the expression of any opinion on the part of the United Nations Secretariat.

Measurement errors are often correlated, as in surveys where respondent’s biases or tendencies to err affect multiple reported variables. We extend Schennach (2007) to identify moments of the conditional distribution of a true Y given a true X when both are measured with error, the measurement errors in Y and X are correlated, and the true unknown model of Y given X has nonseparable model error...

In a nonparametric setup involving stochastic regressors. regression quantiles relate to the so called conditional quantile functions. Various asymptotic properties of such conditional quantile processes are studied with due emphasis on the underlying design aspects.

We examine local strong rationality (LSR) in multivariate models with both forward-looking expectations and predetermined variables. Given hypothetical common knowledge restrictions that the dynamics will be close to those of a specified minimal state variable solution, we obtain eductive stability conditions for the solution to be LSR. In the saddlepoint stable case the saddle-path solution is...

The purpose of this paper is to provide a construction to model shared-variable systems using higher-dimensional automata which is compositional in the sense that the parallel composition of completely independent systems is modeled by the standard tensor product of HDAs and nondeterministic choice is represented by the coproduct.

Diagnostics for normal errors in regression currently utilize ordinary residuals, despite the failure of assumptions validating their use. Case studies here show that such misuse may be critical even in samples of size exceeding currently accepted guidelines. A remedy is to employ recovered errors having the required properties.

The linear measurement error model is an alternative to the classical regression model, in which we assume that the independent variables are subject to error. This assumption can cause statistical inferences and parameter estimators to di er dramatically from those obtained from the classical regression model. However, inferences may remain unchanged even though the independent variables are a...