We propose a new non-linear regression model for rating dependent variables. The rating scale model accounts for the upper and lower bounds of ratings. Parametric and semi-parametric estimation is discussed. An application investigates the relationship between stated health satisfaction and...

This article investigates the statistical and economic implications of adaptive forecasting of exchange rates with panel data and alternative predictors. The candidate exchange rate predictors are drawn from (i) macroeconomic ‘fundamentals’, (ii) return/volatility of asset markets and (iii)...

This paper uses multi-level factor models to characterize within- and between-block variations as well as idiosyncratic noise in large dynamic panels. Block-level shocks are distinguished from genuinely common shocks, and the estimated block-level factors are easy to interpret. The framework...

The paper introduces the appropriate within estimators for the most frequently used three-dimensional fixed effects panel data models. It analyzes the behavior of these estimators in the cases of no self-flow data, unbalanced data, and dynamic autoregressive models. The main results are then...

This paper constructs estimators for panel data regression models with individual specific heterogeneity and two-sided censoring and truncation. Following Powell (1986) the estimation strategy is based on moment conditions constructed from re-censored or re-truncated residuals. While these...

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)....

The paper introduces the appropriate within estimators for the most frequently used three-dimensional fixed effects panel data models. It analyzes the behavior of these estimators in the cases of no self-flow data, unbalanced data, and dynamic autoregressive models. The main results are then...

We provide an axiomatization-based justification for applying the Owen value to decompose R2 in OLS models if prior knowledge can be used to form groups of regressor variables. The assumptions made by the axioms are not only plausible with respect to the variables but also clarify the meaning of...