This paper tests the predictive value of subjective labor supply data for adjustments in working hours over time. The idea is that if subjective labor supply data help to predict next year's working hours, such data must contain at least some information on individual labor supply preferences....

Economists sometimes interpret the failure of a significance test to disconfirm a hypothesis as evidence that this hypothesis is valid. Six examples of this are cited from recent journals. But this is a misinterpretation of what significance tests show. While in general it is correct that every...

We consider both a parametric and a semiparametric method to account for classification errors on the dependent variable in an ordered response model. The methods are applied to the analysis of self-reported speaking fluency of male immigrants in Germany. We find that a parametric model which...

In recent years a number of panel estimators have been suggested for sample selection models, where both the selection equation and the equation of interest contain individual effects which are correlated with the explanatory variables. We review and compare some of these estimators, and apply...

Since interventions by the public sector generally commit substantial societal resources, the evaluation of effects and costs of policy interventions is imperative. This paper outlines why program evaluation should follow well-respected scientific standards and why it should be performed by...

As a measure of welfare, the growth of subjective well-being (SWB) is among the most critical aims in human society. However, self-reported well-being is potentially subject to significant misclassification errors. We employ a novel method from the measurement error literature, which relaxes the...

An experiment is performed to assess the prevalence of instability in univariate and bivariate macroeconomic time series relations and to ascertain whether various adaptive forecasting techniques successfully handle any such instability. Formal tests for instability and out-of-sample forecasts...

In statistics, samples are drawn from a population in a data- generating process (DGP). Standard errors measure the uncer- tainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP...