Exploring Research Frontiers in Contemporary Statistics and by Abdelaati Daouia, Laurent Gardes (auth.), Ingrid Van

By Abdelaati Daouia, Laurent Gardes (auth.), Ingrid Van Keilegom, Paul W. Wilson (eds.)

This e-book collects contributions written via famous statisticians and econometricians to recognize Léopold Simar’s far-reaching medical impression on information and Econometrics all through his profession. The papers contained herein have been provided at a convention in
Louvain-la-Neuve in may well 2009 in honor of his retirement. The contributions disguise a extensive number of concerns surrounding frontier
estimation, which Léopold Simar has contributed a lot to during the last twenty years, in addition to comparable concerns resembling semiparametric regression and versions for censored data.

This e-book collects contributions written via famous statisticians and econometricians to recognize Léopold Simar’s far-reaching medical impression on information and Econometrics all through his profession. The papers contained herein have been provided at a convention in
Louvain-la-Neuve in could 2009 in honor of his retirement. The contributions disguise a huge number of matters surrounding frontier
estimation, which Léopold Simar has contributed a lot to during the last twenty years, in addition to similar concerns reminiscent of semiparametric regression and types for censored data.

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Extra resources for Exploring Research Frontiers in Contemporary Statistics and Econometrics: A Festschrift for Leopold Simar

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28 A. Shiu and V. 5) in which p is the vector of output prices. , (and the corresponding confidence intervals) to give them meaning in percentage terms. To make statistical inferences based on these group efficiency scores, we use the bootstrap-based approach suggested by Simar and Zelenyuk (2007); readers are referred to the same study for further details of this method. 6) The null hypothesis will be rejected (at certain level of confidence) in favor of H1 W A Z A Z TE > TE if RD A;Z > 1 (or H2 W TE < TE if RD A;Z < 1) and the bootstrapestimated confidence interval of RD A;Z does not overlap with unity.

The performance of public enterprises: concepts and measurements (pp. 243–267). Amsterdam: North-Holland. , & Jacob, P. (2004). Extreme values and kernel estimates of point processes boundaries. ESAIM: Probability and Statistics, 8, 150–168. 22 A. Daouia et al. , & Yao, F. (2008). A smooth nonparametric conditional quantile frontier estimator. Journal of Econometrics, 143, 317–333. Nadaraya, E. A. (1964). Some new estimates for distribution functions. Theory of Probability Applications, 15, 497–500.

3 Truncated Regression Analysis The regression analysis method we employ is not simply a generalization of the above analysis because it imposes a particular structure on the dependency between the efficiency of a DMU and the hypothesized explanatory variables. , size) of the observations. Nevertheless, this analysis complements the methods used above in a number of very important respects. In particular, it allows for inferences to be drawn about different factors that simultaneously influence efficiency scores by focusing on the (marginal) effect of each variable.

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