Melanie Schienle

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In this paper, we analyze the properties of nonparametric estimators of a regression function when some covariates are not directly observed, but have only been estimated by some nonparametric procedure. We provide general results that can be used to establish rates of consistency or asymptotic normality in numerous econometric applications, including(More)
Standard fixed symmetric kernel type density estimators are known to encounter problems for positive random variables with a large probability mass close to zero. We show that in such settings, alternatives of asymmetric gamma kernel estimators are superior but also differ in asymptotic and finite sample performance conditional on the shape of the density(More)
In this paper, we prove the existence of a recursive competitive equilibrium (RCE) for an Aiyagari style economy with permanent income shocks and perpetual youth structure. We show that there exist equilibria where borrowing constraints are never binding. This allows us to establish a non-trivial lower bound on the equilibrium interest rate. To solve the(More)
We propose a framework for estimating time-varying systemic risk contributions that is applicable to a high-dimensional and interconnected financial system. Tail risk dependencies and contributions are estimated based on a penalized two-stage fixed-effects quantile approach, which explicitly links time-varying interconnectedness tofonds (WWTF). M.Schienle(More)
This chapter deals with nonparametric estimation of the risk neutral density. We present three different approaches which do not require parametric functional assumptions neither on the underlying asset price dynamics nor on the distri-butional form of the risk neutral density. The first estimator is obtained as a kernel smoother of the second derivative of(More)
We thank Andrew Patton and two anonymous referees for many helpful comments that substantially improved the paper. Abstract In practice, multivariate dependencies between extreme risks are often only assessed in a pairwise way. We propose a test for detecting situations when such pairwise measures are inadequate and give incomplete results. This occurs when(More)
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