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Mathematical statistics --- Quantitative methods (economics) --- Economics --- Graphic methods. --- 519.2 --- 330.115 --- Wiskundige statistiek --- Kwantitatieve methoden (economie)

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This important collection brings together leading econometricians to discuss advances in the areas of the econometrics of panel data. The papers in this collection can be grouped into two categories. The first, which includes chapters by Amemiya, Baltagi, Arellano, Bover and Labeaga, primarily deal with different aspects of limited dependent variables and sample selectivity. The second group of papers, including those by Nerlove, Schmidt and Ahn, Kiviet, Davies and Lahiri, consider issues that arise in the estimation of dyanamic (possibly) heterogeneous panel data models. Overall, the contributors focus on the issues of simplifying complex real-world phenomena into easily generalisable inferences from individual outcomes. As the contributions of G. S. Maddala in the fields of limited dependent variables and panel data were particularly influential, it is a fitting tribute that this volume is dedicated to him.

Quantitative methods (economics) --- Econometrics --- Panel analysis --- Analysis of variance --- Econométrie --- Panel (Psychologie sociale) --- Analyse de variance --- Maddala, G. S. --- Maddala, Gangadharrao Soundalyarao, --- 519.2 --- econometrie --- wiskundige statistiek --- AA / International- internationaal --- 330.3 --- 303.6 --- 330.015195 --- Panel studies --- Social sciences --- Statistics --- Economics, Mathematical --- Probability. Mathematical statistics --- Methode in staathuishoudkunde. Statische, dynamische economie. Modellen. Experimental economics. --- Raming : theorie (wiskundige statistiek). Bayesian analysis and inference. --- Methodology --- Analysis of variance. --- Econometrics. --- Panel analysis. --- Business & Economics --- Economic Theory --- Maddala, G.S. --- Business, Economy and Management --- Economics --- 519.2 Probability. Mathematical statistics --- Econométrie --- Raming : theorie (wiskundige statistiek). Bayesian analysis and inference --- Methode in staathuishoudkunde. Statische, dynamische economie. Modellen. Experimental economics --- Maddala, Gangadharrao Soundalyarao, - 1933-1999

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This is a new edition of a very successful introduction to statistical methods for general insurance practitioners. No prior statistical knowledge is assumed, and the mathematical level required is approximately equivalent to school mathematics. Whilst the book is primarily introductory, the authors discuss some more advanced topics, including simulation, calculation of risk premiums, credibility theory, estimation of outstanding claim provisions and risk theory. All topics are illustrated by examples drawn from general insurance, and references for further reading are given. Solutions to most of the exercises are included. For the new edition the opportunity has been taken to make minor improvements and corrections throughout the text, to rewrite some sections to improve clarity, and to update the examples and references. A new section dealing with estimation has also been added.

Insurance --- Statistics --- 10.01.a --- 10.02.b --- 10.03.a --- KBC9912-IVB --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Actuarial statistics --- Insurance statistics --- Verzekeringswiskunde ; Waarschijnlijkheidsrekening --- Statistieken ; Wiskundige statistiek --- Actuariaat ; Algemeen --- Mathematical Sciences --- Probability --- Statistics. --- Statistical methods.

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The generalized method of moments (GMM) estimation has emerged as providing a ready to use, flexible tool of application to a large number of econometric and economic models by relying on mild, plausible assumptions. The principal objective of this volume is to offer a complete presentation of the theory of GMM estimation as well as insights into the use of these methods in empirical studies. It is also designed to serve as a unified framework for teaching estimation theory in econometrics. Contributors to the volume include well-known authorities in the field based in North America, the UK/Europe, and Australia. The work is likely to become a standard reference for graduate students and professionals in economics, statistics, financial modeling, and applied mathematics.

Quantitative methods (economics) --- Econometric models. --- Moments method (Statistics) --- Estimation theory. --- Modèles économétriques --- Moments, Méthodes de (Statistiques) --- Théorie de l'estimation --- Estimation theory --- 330.115.001.57 --- 519.2 --- Econometrische modellen. Simulatiemodellen --- Probability. Mathematical statistics --- AA / International- internationaal --- 303.2 --- Spreiding en deviatie (wiskundige statistiek). Curtosis. Moments. GMM. --- Moments method (Statistics). --- 519.2 Probability. Mathematical statistics --- 330.115.001.57 Econometrische modellen. Simulatiemodellen --- Modèles économétriques --- Moments, Méthodes de (Statistiques) --- Théorie de l'estimation --- Econometric models --- Method of moments (Statistics) --- Mathematical statistics --- Distribution (Probability theory) --- Estimating techniques --- Least squares --- Stochastic processes --- Econometrics --- Mathematical models --- Spreiding en deviatie (wiskundige statistiek). Curtosis. Moments. GMM --- Business, Economy and Management --- Economics

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This book, like many books, was born in frustration. When in the fall of 1994 I set out to teach a second course in computational statistics to d- toral students at the University of Michigan, none of the existing texts seemed exactly right. On the one hand, the many decent, even inspiring, books on elementary computational statistics stress the nuts and bolts of using packaged programs and emphasize model interpretation more than numerical analysis. On the other hand, the many theoretical texts in - merical analysis almost entirely neglect the issues of most importance to statisticians. TheclosestbooktomyidealwastheclassicaltextofKennedy and Gentle [2]. More than a decade and a half after its publication, this book still has many valuable lessons to teach statisticians. However, upon re?ecting on the rapid evolution of computational statistics, I decided that the time was ripe for an update. The book you see before you represents a biased selection of those topics in theoretical numerical analysis most relevant to statistics. By intent this book is not a compendium of tried and trusted algorithms, is not a c- sumer’s guide to existing statistical software, and is not an exposition of computer graphics or exploratory data analysis. My focus on principles of numerical analysis is intended to equip students to craft their own software and to understand the advantages and disadvantages of di?erent numerical methods. Issues of numerical stability, accurate approximation, compu- tional complexity, and mathematical modeling share the limelight and take precedence over philosophical questions of statistical inference.

AA / International- internationaal --- 304.0 --- 303.0 --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen. --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken). --- Numerical analysis. --- Statistique mathématique --- 519.4 --- Applied Mathematics --- Mathematics. --- Applied mathematics. --- Engineering mathematics. --- Applications of Mathematics. --- Mathematical statistics --- Numerical analysis --- 519.2 --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Mathematical analysis --- 519.2 Probability. Mathematical statistics --- Probability. Mathematical statistics --- Statistical methods --- Mathematical statistics. --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken) --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen --- Engineering --- Engineering analysis