A measurement error model is a regression model with (substantial) measurement errors in the variables. Disregarding these measurement errors in estimating the regression parameters results in asymptotically biased estimators. Several methods have been proposed to eliminate, or at least to...

A measurement error model is a regression model with (substantial) measurement errors in the variables. Disregarding these measurement errors in estimating the regression parameters results in asymptotically biased estimators. Several methods have been proposed to eliminate, or at least to...

The least squares estimator is probably the most frequently used estimation method in regression analysis. Unfortunately, it is also quite sensitive to data contamination and model misspecification. Although there are several robust estimators designed for parametric regression models that can...

We argue in this paper that it is more feasible to use binary variables and logistic regression analyses in the assessments of AIDS incidents o or other similar researches in social science. Thus, even in measuring disease persistence we can reach solid and comprehensive results. Statistical...

This paper studies the impact that pre-IPO cash flow volatility has on the initial and long-term value of a publicly traded firm. From the perspective of corporate risk management theory, higher cash flow volatility should reduce value in the form of higher borrowing costs, reduced investment,...

This paper considers identification and estimation of the Quantile Treatment Effect on the Treated (QTT) under a straightforward distributional extension of the most commonly invoked Mean Difference in Differences assumption used for identifying the Average Treatment Effect on the Treated (ATT)....

This paper considers identification and estimation of the Quantile Treatment Effect on the Treated (QTT) under a straightforward distributional extension of the most commonly invoked Mean Difference in Differences Assumption used for identifying the Average Treatment Effect on the Treated (ATT)....

Der Beitrag gibt einen Überblick über neuere Entwicklungen bei Schätzmethoden, Instrumentalvariablenansätzen, Paneldatenmodellen sowie nicht- und semiparametrischen Modellen für Mikrodaten, ergänzt um einige Testverfahren aus diesen Bereichen. Besondere Aufmerksamkeit wird auf Probleme mit...

This paper proposes a nonparametric method for evaluating treatment effects in the presence of both treatment endogeneity and attrition/non-response bias, using two instrumental variables. Making use of a discrete instrument for the treatment and a continuous instrument for...

In the paper is considered identification of coefficients in equations explaining a continuous variable, say the number of sickness absence days of an individual per year, by cohort, time and age, subject to their definitional identity. Extensions of a linear equation to polynomials, including...