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The volumes in Econometric Exercises are intended to be much more than a collection of several hundred solved exercises. Each book has a coherent and well-organized sequence of exercises in a specific field or sub-field of econometrics. Every chapter of a volume begins with a short technical introduction that emphasizes the main ideas and overviews the most relevant theorems and results, including applications and occasionally computer exercises. They are intended for undergraduates in econometrics with an introductory knowledge of statistics, for first and second year graduate students of econometrics, and for students and instructors from neighboring disciplines (e.g., statistics, political science, psychology and communications) with interests in econometric methods.

  • General Editors: Karim M. Abadir, Imperial College of Science, Technology and Medicine, London, Jan R. Magnus, Universiteit van Tilburg, Peter C. B. Phillips, Yale University, Connecticut

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4 results in Econometric Exercises

Bayesian Econometric Methods
  • 2nd edition
  • Joshua Chan, Gary Koop, Dale J. Poirier, Justin L. Tobias
  • Published online:
    14 January 2021
    Print publication:
    15 August 2019
  • Bayesian Econometric Methods examines principles of Bayesian inference by posing a series of theoretical and applied questions and providing detailed solutions to those questions. This second edition adds extensive coverage of models popular in finance and macroeconomics, including state space and unobserved components models, stochastic volatility models, ARCH, GARCH, and vector autoregressive models. The authors have also added many new exercises related to Gibbs sampling and Markov Chain Monte Carlo (MCMC) methods. The text includes regression-based and hierarchical specifications, models based upon latent variable representations, and mixture and time series specifications. MCMC methods are discussed and illustrated in detail - from introductory applications to those at the current research frontier - and MATLAB® computer programs are provided on the website accompanying the text. Suitable for graduate study in economics, the text should also be of interest to students studying statistics, finance, marketing, and agricultural economics.

Statistics
  • Karim M. Abadir, Risto D. H. Heijmans, Jan R. Magnus
  • Published online:
    11 June 2020
    Print publication:
    08 November 2018
  • Building on the success of Abadir and Magnus' Matrix Algebra in the Econometric Exercises Series, Statistics serves as a bridge between elementary and specialized statistics. Professors Abadir, Heijmans, and Magnus freely use matrix algebra to cover intermediate to advanced material. Each chapter contains a general introduction, followed by a series of connected exercises which build up knowledge systematically. The characteristic feature of the book (and indeed the series) is that all exercises are fully solved. The authors present many new proofs of established results, along with new results, often involving shortcuts that resort to statistical conditioning arguments.

Matrix Algebra
  • Karim M. Abadir, Jan R. Magnus
  • Published online:
    05 June 2012
    Print publication:
    22 August 2005
  • Matrix Algebra is the first volume of the Econometric Exercises Series. It contains exercises relating to course material in matrix algebra that students are expected to know while enrolled in an (advanced) undergraduate or a postgraduate course in econometrics or statistics. The book contains a comprehensive collection of exercises, all with full answers. But the book is not just a collection of exercises; in fact, it is a textbook, though one that is organized in a completely different manner than the usual textbook. The volume can be used either as a self-contained course in matrix algebra or as a supplementary text.

Bayesian Econometric Methods
  • Gary Koop, Dale J. Poirier, Justin L. Tobias
  • Published online:
    05 June 2012
    Print publication:
    15 January 2007
  • This volume in the Econometric Exercises series contains questions and answers to provide students with useful practice, as they attempt to master Bayesian econometrics. In addition to many theoretical exercises, this book contains exercises designed to develop the computational tools used in modern Bayesian econometrics. The latter half of the book contains exercises that show how these theoretical and computational skills are combined in practice, to carry out Bayesian inference in a wide variety of models commonly used by econometricians. Aimed primarily at advanced undergraduate and graduate students studying econometrics, this book may also be useful for students studying finance, marketing, agricultural economics, business economics or, more generally, any field which uses statistics. The book also comes equipped with a supporting website containing all the relevant data sets and MATLAB computer programs for solving the computational exercises.