In this paper, I study identification of a nonseparable model with endogeneity arising due to unobserved heterogeneity. Identification relies on the availability of binary proxies that can be used to control for the unobserved heterogeneity. I show that the model is identified in the limit as...

Regression trees are evaluated with respect to mean square error (MSE), mean integrated square error (MISE), and integrated squared error (ISE), as the size of the training sample goes to infinity. The asymptotically MSE- and MISE minimizing (locally adaptive) regression trees are characterized....

The fixed effects (FE) panel model is one of the main econometric tools in empirical economic research. A major practical limitation is that the parameters on time-constant covariates are not identifiable. This paper presents a new approach to grouping FE in the linear panel model to reduce...

This paper unveils a new resource for macroeconomic research: a long-run dataset covering disaggregated bank credit for 17 advanced economies since 1870. The new data show that the share of mortgages on banks' balance sheets doubled in the course of the 20th century, driven by a sharp rise of...

Based on the Lee-Carter (LC) model, the benchmark in population forecasting, a variety of extensions and modifications are proposed in this paper. We investigate one of the extensions, the Hyndman-Ullah (HU) method and apply it to Asian demographic data sets: China, Japan and Taiwan. It combines...

This study investigates the effects of a monetary policy shock on real output and prices, by means of a novel distribution-free nonrecursive identification scheme for structural vector autoregressions. Structural shocks are assumed to be mutually independent. The identification procedure is...

This paper addresses the open debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. Daily covariances are estimated based on HF data of the S&P 500 universe employing a blocked realized kernel estimator. We propose forecasting covariance matrices using a...

To evaluate how occurring critical incidents change customer perceptions of brand personality, this study measures the impact on the basis of an online experiment. For this purpose, 1,132 usable responses are gathered considering the smartphone brands of Apple and Nokia as well as different...

This paper addresses the open debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. We consider the problem of constructing global minimum variance portfolios based on the constituents of the S&P 500 over a four-year period covering the 2008 financial...

To explore how occurring critical incidents affect customer-brand relations, this study measures the impact on the basis of an online experiment. For this purpose, 1,122 usable responses are gathered considering the smartphone brands of Apple and Nokia as well as different scenarios. The...