We propose a nonparametric method to test which characteristics provide independent information for the cross section of expected returns. We use the adaptive group LASSO to select characteristics and to estimate how they affect expected returns nonparametrically. Our method can handle a large...

This paper proposes new, simple, and more accurate statistical tests in a cointegrated system that allows for endogenous regressors and serially dependent errors. The approach involves first transforming the time series using some orthonormal basis functions in L2[0,1], which has energy...

This paper addresses the problem of estimation of a nonparametric regression function from selectively observed data when selection is endogenous. Our approach relies on independence between covariates and selection conditionally on potential outcomes. Endogeneity of regressors is also allowed...

This paper discusses nonparametric kernel regression with the regressor being a d-dimensional ß-null recurrent process in presence of conditional heteroscedasticity. We show that the mean function estimator is consistent with convergence rate p n(T)hd, where n(T) is the number of regenerations...

We introduce econometric methods to perform estimation and inference on the permanent and transitory components of the stochastic discount factor (SDF) in dynamic Markov environments. The approach is nonparametric in that it does not impose parametric restrictions on the law of motion of the...

Why do some economies grow faster than others? Do economies in the middle-income range face especially difficult challenges producing consistent growth? Using a transition matrix analysis on decade-level growth rates, we find that the data clearly reject the idea that middle-income economies...

We consider nonparametric identification and estimation of pricing kernels, or equivalently of marginal utility functions up to scale, in consumption based asset pricing Euler equations. Ours is the first paper to prove nonparametric identification of Euler equations under low level conditions...

Previous studies have shown that both height and weight are associated with wages. However, by focusing on interpreting the partial effects of either height or weight on wages while holding all else constant, some gaps in our understanding of the complex relationship between body size and wages...

In this paper a semiparametric stochastic metafrontier approach is used to obtain insight into firmlevel competitiveness in Europe. We differ from standard TFP studies at the firm level as we simultaneously allow for inefficiency, noise and do not impose a functional form on the input-output...

The aim of this paper is to provide simple nonparametric methods to estimate finitemixture models from data with repeated measurements. Three measurements suffice for the mixture to be fully identified and so our approach can be used even with very short panel data. We provide distribution...

We propose a simple model selection test for choosing among two parametric likelihoods which can be applied in the most general setting without any assumptions on the relation between the candidate models and the true distribution. That is, both, one or neither is allowed to be correctly...

In this paper we explore the possibility of the application of GAMLSS regression techniques for the analysis of income distributions in Germany following the reunification. We find that conditional income distributions can generally be modelled using the three parameter Dagum distribution and...

Der Value at Risk ist die am stärksten verbreitete Kennzahl zur Bestimmung des Risikos bei Finanzinstituten. Für diese gibt es bezüglich Theorie, Simulation und empirischer Anwendung bereits ein breites Spektrum an Literatur. Im Rahmen dieser Arbeit werden verschiedene Methoden zur Schätzung...

In this paper we explore the application of structured additive distributional regression for the analysis of conditional income distributions in Germany following the reunification. Using a bootstrapped Kolmogorov-Smirnov test we find that conditional personal income distributions can generally...

Die Dissertation behandelt Heterogenität in Paneldatensätzen auf Firmenebene. Es wird aufgezeigt, dass eine Berücksichtigung von Heterogenität unerlässlich ist, um Produktivität und technische Effizienz in parametrischen Frontiermodellen unverzerrt messen zu können. Verschiedene gängige...