When categorical data are misplaced into the wrong category, we say the data is affected by misclassification. This is … that ignore misclassification can be biased. In this dissertation, we develop methods to provide improved estimators and … misclassification/reclassification model. These correction methods use the score function approach, regression calibration and a mixture …

misclassification in register data. The analysis of the determinants for job separation with transition to unemployment illustrates the …

models to adjust for misclassification will be proposed to address four related questions of interest.The first question … inferences. As a methodological transition into our next motivating example, we address this general misclassification problem as … correct for misclassification in this setting utilizing external or internal validation data.Our fourth question aims to …

created by polling the respondents on their expectations versus intentions. Expectation-based forecasts are more efficient … statically significant positive relationship between confidence and the accuracy of individual-level expectations. This positive …

In modeling expectation formation, economic agents are usually viewed as forming expectations adaptively or in …, we show that this kind of model performs well in simulation experiments. Focusing upon producers' expectations in the …