Econometrics in Theory and Practice: Festschrift for Hans Schneeweiß
Hans SchneeweiB is- one of the best-known German econometricians and statisticians. He was born in Glatz, Silesia, on March 13, 1933. Hans SchneeweiB studied mathematics and physics and received his Ph. D. degree from the Johann-Wolfgang-Goethe University, Frankfurt, in 1960. He was member of the academic staff of the Faculty of Law and Economics of the Saar University between 1959 and 1965. Following his Habilitation in 1964, he was appointed to the chair of Statistics and Econometrics at the same university. As a visiting professor he worked at the Institute for Aca demic Studies in Vienna in 1967 and at the Department of Statistics of the University of Waterloo, Canada, in 1970/71. He has been a full professor of Econometrics and Statistics at the Ludwig-Maximilians-University in Mu nich since 1973. His extensive research activities abroad included important projects in Waterloo, Vienna, Dundee (Scotland), Sidney, China, Kiev. During the more than 40 years of his academic work he has published outstanding, original articles on econometrics and statistics. To give an ex ample, it is his research on decision theory which has marked developments in this field. His book Entscheidungskriterien bei Risiko, published in 1967, is an excellent starting for anyone looking for an introduction to the complex iSsues involved.
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algorithm approach assume assumptions asymptotic autoregression bandwidth behaviour bias calculated coefficients cointegration cointegration rank conditional conditional distribution consider consistent estimator covariance matrix criteria criterion decision rules decision theory denotes econometric models economic equation error correction error variances errors-in-variables model example F-test Germany given heteroscedastic income Institut für Statistik instrumental variable interest rate Journal kernel knowledge latent variable least squares estimator likelihood estimator linear model long-run Ludwig-Maximilians-Universität München market segment maximum likelihood mean method monetary money demand Monte Carlo München nonlinear nonparametric nonparametric regression normal distribution observed obtain optimal orthogonal parameters planned segment predictor probability problem production random variable real exchange rate regression model regressors sample Schneeweiß shocks simulation spline Stefanski stochastic stochastic volatility Theorem theory trend Universität values variance function vector volatility function weighted least squares zero