85:T688,Introduction to Econometrics has been written as a core textbook for a first course in econometrics taken by undergraduate or graduate students. It is intended for students taking a single course in econometrics with a view towards doing practical data work. It will also be highly useful for students interested in understanding the basics of econometric theory with a view towards future study of advanced econometrics. To achieve this end, it has a practical emphasis, showing how a wide variety of models can be used with the types of data sets commonly used by economists. However, it also has enough discussion of the underlying econometric theory to give the student a knowledge of the statistical tools used in advanced econometrics courses. Key Features: * A non-technical summary of the basic tools of econometrics is given in chapters 1 and 2, which allows the reader to quickly start empirical work. * The foundation offered in the first two chapters makes the theoretical econometric material, which begins in chapter 3, more accessible. * Provides a good balance between econometric theory and empirical applications. * Discusses a wide range of models used by applied economists including many variants of the regression model (with extensions for panel data), time series models (including a discussion of unit roots and cointegration) and qualitative choice models (probit and logit). An extensive collection of web-based supplementary materials is provided for this title, including: data sets, problem sheets with worked through answers, empirical projects, sample exercises with answers, and slides for lecturers. URL: www.wileyeurope.com/college/koop86:T7e3,Analysis of Economic Data teaches methods of data analysis to students whose primary interest is not in econometrics, statistics or mathematics. It shows students how to apply econometric techniques in the context of real-world empirical problems. It adopts a largely non-mathematical approach relying on verbal and graphical intuition and covers most of the tools used in modern econometrics research e.g. correlation, regression and extensions for time-series methods. It contains extensive use of real data examples and involves readers in hands-on computer work. The new edition includes new material on the mathematical background required by students and, for those readers unfamiliar with this background, a brief explanation of the relevant mathematics. Topics covered include: the equation of a straight line, the summation operator, and logarithms. The author also includes a much greater discussion of data transformations such as growth rates and index numbers. More material will also be added on data sources, largely focusing on internet data sources.

Gary Koop has a very high international profile in the field of econometrics and is well known for his books and numerous journal publications.
The second edition provides stronger coverage of the relevant introductory mathematics, including: the equation of a straight line, the summation operator, and logarithms. This will make the book more accessible for those students who have limited mathematical skills.
Greater discussion is also provided of data transformations such as growth rate and index numbers. Index numbers are becoming increasingly important and are frequently used in economics courses.
More material will also be provided on data sources, especially internet data sources which are becoming extremely important as a means of gathering data. Some students have difficulty with the collection of data and the inclusion of this material will help those students.

87:T4bb,

"Analysis of Financial Data" teaches the basic methods and techniques of data analysis to finance students, by showing them how to apply such techniques in the context of real world empirical problems. Adopting a largely non mathematical approach, "Analysis of Financial Data" relies more on verbal intuition and graphical methods for understanding. This title includes key features such as: coverage of many of the major tools used by the financial economist e.g. correlation, regression, time series analysis and methods for analyzing financial volatility; extensive use of real data examples, which involves readers in hands on computer work; and, mathematical techniques at a level suited to MBA students and undergraduates taking a first course in the topic. Supplementary material for readers and lecturers are provided on an accompanying website.

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A website containing computer programs and data sets to help the student develop the computational skills of modern Bayesian econometrics can be found at: www.wiley.co.uk/koopbayesian

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