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Intermediate Statistics and Econometrics

Author : Dale J. Poirier
Publisher : MIT Press
Page : 744 pages
File Size : 20,67 MB
Release : 1995
Category : Business & Economics
ISBN : 9780262161497

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The standard introductory texts to mathematical statistics leave the Bayesian approach to be taught later in advanced topics courses-giving students the impression that Bayesian statistics provide but a few techniques appropriate in only special circumstances. Nothing could be further from the truth, argues Dale Poirier, who has developed a course for teaching comparatively both the classical and the Bayesian approaches to econometrics. Poirier's text provides a thoroughly modern, self-contained, comprehensive, and accessible treatment of the probability and statistical foundations of econometrics with special emphasis on the linear regression model. Written primarily for advanced undergraduate and graduate students who are pursuing research careers in economics, Intermediate Statistics and Econometrics offers a broad perspective, bringing together a great deal of diverse material. Its comparative approach, emphasis on regression and prediction, and numerous exercises and references provide a solid foundation for subsequent courses in econometrics and will prove a valuable resource to many nonspecialists who want to update their quantitative skills. The introduction closes with an example of a real-world data set-the Challengerspace shuttle disaster-that motivates much of the text's theoretical discussion. The ten chapters that follow cover basic concepts, special distributions, distributions of functions of random variables, sampling theory, estimation, hypothesis testing, prediction, and the linear regression model. Appendixes contain a review of matrix algebra, computation, and statistical tables.

Economic Statistics and Econometrics

Author : Thad W. Mirer
Publisher : Macmillan College
Page : 424 pages
File Size : 50,95 MB
Release : 1988
Category : Business & Economics
ISBN :

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Combines technique with application using real data sets. The core of the book (Chapters 1-13) covers the basic statistical concepts necessary for econometrics with an emphasis on regression analysis. Part V is a treatment of advanced econometrics theory.

Probability, Statistics and Econometrics

Author : Oliver Linton
Publisher : Academic Press
Page : 390 pages
File Size : 34,98 MB
Release : 2017-03-04
Category : Business & Economics
ISBN : 0128104961

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Probability, Statistics and Econometrics provides a concise, yet rigorous, treatment of the field that is suitable for graduate students studying econometrics, very advanced undergraduate students, and researchers seeking to extend their knowledge of the trinity of fields that use quantitative data in economic decision-making. The book covers much of the groundwork for probability and inference before proceeding to core topics in econometrics. Authored by one of the leading econometricians in the field, it is a unique and valuable addition to the current repertoire of econometrics textbooks and reference books. Synthesizes three substantial areas of research, ensuring success in a subject matter than can be challenging to newcomers Focused and modern coverage that provides relevant examples from economics and finance Contains some modern frontier material, including bootstrap and lasso methods not treated in similar-level books Collects the necessary material for first semester Economics PhD students into a single text

Statistics and Econometrics

Author : Orley Ashenfelter
Publisher :
Page : 328 pages
File Size : 31,18 MB
Release : 2003
Category : Business & Economics
ISBN :

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Every major econometric method is illustrated by a persuasive, real life example applied to real data. * Explores subjects such as sample design, which are critical to practical application econometrics.

Advances in Contemporary Statistics and Econometrics

Author : Abdelaati Daouia
Publisher : Springer Nature
Page : 713 pages
File Size : 10,2 MB
Release : 2021-06-14
Category : Mathematics
ISBN : 3030732495

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This book presents a unique collection of contributions on modern topics in statistics and econometrics, written by leading experts in the respective disciplines and their intersections. It addresses nonparametric statistics and econometrics, quantiles and expectiles, and advanced methods for complex data, including spatial and compositional data, as well as tools for empirical studies in economics and the social sciences. The book was written in honor of Christine Thomas-Agnan on the occasion of her 65th birthday. Given its scope, it will appeal to researchers and PhD students in statistics and econometrics alike who are interested in the latest developments in their field.

Statistical Foundations for Econometric Techniques

Author : Asad Zaman
Publisher : Emerald Group Pub Limited
Page : 570 pages
File Size : 41,6 MB
Release : 1996
Category : Business & Economics
ISBN : 9780127754154

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Statistical Foundations for Econometric Techniques features previously unavailable material in a textbook format for econometrics students, researchers, and practitioners. Taking strong positions for and against standard econometric techniques, the book endorses a single best technique whenever possible. In many cases, the recommended optimal technique differs substantially from current practice. Detailed discussions present many new estimation strategies superior to conventional OLS and ways to use them. Key Features * Evaluates econometric techniques and the procedures commonly used to analyze those techniques * Challenges established concepts * Introduces many techniques that are not available in other texts * Recommends against using the Durbin-Watson and Lagrange Multiplier tests in favor of tests with superior power * Provides many new types of estimation strategies superior to conventional OLS * Forms a judicious mixture of various methodological approaches * Illustrates Empirical Bayes estimators and Robust Regression techniques possessing a 50% breakdown value

Statistics, Econometrics and Forecasting

Author : Arnold Zellner
Publisher : Cambridge University Press
Page : 186 pages
File Size : 49,72 MB
Release : 2004-02-19
Category : Business & Economics
ISBN : 9780521540445

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Based on two lectures presented as part of The Stone Lectures in Economics series, Arnold Zellner describes the structural econometric time series analysis (SEMTSA) approach to statistical and econometric modeling. Developed by Zellner and Franz Palm, the SEMTSA approach produces an understanding of the relationship of univariate and multivariate time series forecasting models and dynamic, time series structural econometric models. As scientists and decision-makers in industry and government world-wide adopt the Bayesian approach to scientific inference, decision-making and forecasting, Zellner offers an in-depth analysis and appreciation of this important paradigm shift. Finally Zellner discusses the alternative approaches to model building and looks at how the use and development of the SEMTSA approach has led to the production of a Marshallian Macroeconomic Model that will prove valuable to many. Written by one of the foremost practitioners of econometrics, this book will have wide academic and professional appeal.

Applied Spatial Statistics and Econometrics

Author : Katarzyna Kopczewska
Publisher : Routledge
Page : 725 pages
File Size : 26,8 MB
Release : 2020-11-25
Category : Business & Economics
ISBN : 1000079783

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This textbook is a comprehensive introduction to applied spatial data analysis using R. Each chapter walks the reader through a different method, explaining how to interpret the results and what conclusions can be drawn. The author team showcases key topics, including unsupervised learning, causal inference, spatial weight matrices, spatial econometrics, heterogeneity and bootstrapping. It is accompanied by a suite of data and R code on Github to help readers practise techniques via replication and exercises. This text will be a valuable resource for advanced students of econometrics, spatial planning and regional science. It will also be suitable for researchers and data scientists working with spatial data.