The correlation approach is considered for the model-following problem using closed-loop noisy data. The idea is to tune the controller parameters such that the output error between the real closed-loop system and the designed one be uncorrelated with the reference signal. This way, the controller parameters will not be influenced by noise. Since perfect decorrelation is not always possible, th...

Abstract Instrumental variables are often associated with low estimator precision. This paper explores efficiency gains which might be achievable using moment conditions which are nonlinear in the disturbances and are based on flexible parametric families for error distributions. We show that these estimators can achieve the semiparametric efficiency bound when the true error distribution is a ...

We use Monte Carlo simulations and real data to assess the performance of methods dealing with measurement error in investment equations. Our experiments show that fixed effects, error heteroscedasticity, and data skewness severely affect the performance and reliability of methods found in the literature. Estimators that use higher-order moments return biased coefficients for (both) mismeasured...

This study investigated various uncertainties in colour matching, including matching stimulus and measuring instruments (such as random fluctuation, drift over time, spatial uniformity, temperature), calibration (photometric, wavelength and additivity) and observer (intraand inter agreements). From the research results, it was found that the observer error was the major source of errors in colo...

We propose a computationally efficient approximation for the double bootstrap bias adjustment factor without using the inner bootstrap loop. The approximation converges in probability to the population bias correction factor. We study the finite sample properties of the approximation in the context of a linear instrumental variable model. In identified versions of the model considered in our Mo...

The impact of endogeneity and measurement error on the estimated effect of household economic resources on child height is demonstrated. These econometric problems contribute to uncertainty in the literature about the significance of income effects on child health and nutrition. Results are based on a household survey from Papua New Guinea, where repeated within-year observations on households ...

We consider the nonparametric regression model with an additive error that is correlated with the explanatory variables. We suppose the existence of instrumental variables that are considered in this model for the identification and the estimation of the regression function. The nonparametric estimation by instrumental variables is an ill-posed linear inverse problem with an unknown but estimab...