Book Description
ELEMENTARY FORECASTING focuses on the core techniques of widest applicability. The author illustrates all methods with detailed real-world applications, many of them international in flavor, designed to mimic typical forecasting situations.
Customer Reviews:
Not Bad.......2007-01-04
The book starts with talking about forecasting deterministic trends, then seasonalities, later chapters 6,7,8 talk about forecasting cycles. Finally in the end chapters the author puts it all together and talks about multivariable forecasting models. The book is on an introductory level, so if you're looking for indepth discussion of these topics this is not for you. Anoter drawback is that this book does not integrate into its discussion of the topics any examples of code that would show how to forecast with any popular software package (Eviews or SAS).
Third edition is no better.......2004-01-15
I posted the unfavorable review of the second edition. I have recently had an opportunity to see the third edition, and find the same errors are still present.
an embarrassingly slapdash and sloppy book.......2002-09-28
There were a considerable number of errors in the first edition that I pointed out to the author shortly after its publication. The second edition seems to have corrected few if any of them. Let me cite two egregious examples.
In the chapter on ARMA models, the example analyzed is Canadian Employment data. One of the models that is fit is an MA(4) -- see pages 164-6. When I tried to reproduce these results using software other than EVIEWS, using the data disk in the 1st edition, I couldn't. I contacted EVIEWS and they discovered a programming error in the estimation routine. They released a patch to fix EVIEWS. However, the author never re-estimated his model, and the estimates in the second edition are the same as in the first. However, my copy of the 2nd edition has no data disk! Was that thought to be an adequate solution?!
Chapter 9 ("Putting it all together") is a capstone chapter that analyzes liquor sales data using the techniques introduced in earlier chapters. After several pages (pp. 207-19) a model is selected. On pages 220-2, the residuals are examined using the Box-Ljung statistic, and deemed acceptable. However, as a careful examination of table 9.6 makes clear, the p-values for the Box-Ljung statistic were computed as if the input data were a raw series. The model generating the residuals (p. 219) had 3 autoregressive terms! This changes the d.f. in the chi-square distribution of the statistic. If you make the appropriate correction using the data in table 9.6, and compute the p-values correctly, you will see that the model residuals apparently ARE NOT white noise. One reason is a calendar effect in liquor sales: months that contain more than a usual number of Fridays and Saturdays result in more liquor sales; ones with more Sundays result in lower liquor sales. However, the author doesn't discover this, but accepts his inappropriate model on the basis of faulty distribution theory.
Good, but poor examples.......1999-11-27
If the purpose of using this book is to get a brief idea of what certain concepts are then it is a good book. Unfortunately, many people using this book are going to be those who do not have much background with the concepts inside and they will be looking for clearer explanations of what the author is talking about. I think that is the book's weakness: the fact that many times I didn't feel that his definitions and explanations were complete enough.
Excellent introductory guide to forecasting !!!.......1999-01-26
The use of practical examples (using the Eviews software) and the availability of a data disk makes this a very relevant guide for practitioners. There is a good section on graphical analysis and modelling of cycles using AR and MA processes. The mathematics is kept simple and clear, intuitive explanations are given throughout. The treatment of unit roots, cointegration and other advanced materials is quite sketchy but I guess that is to be expected in an introductory text. With the level of clarity evident throughout this book, I certainty hope Diebold follows up with another book on more advanced forecasting techniques.
Book Description
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.
Customer Reviews:
great!.......2007-09-04
It actually presents a good foundation in theory. It is completely unlike most undergrad statistics econometrics texts in that respect. Highly recommended!
Helpful text.......2006-03-13
I actually very much liked this textbook. The examples are both interesting and enlightening, and the explanations clear and easy to follow. As the title suggests, it is tailored to a course with a heavy math component, and the appendix, in particular, provides a good guide to equations, derivations, etc. I have also found it to be extremely useful in later econometrics applications, as its logical organization makes it very easy to find exactly the information you need.
good examples, complicated explanations, too many typos.......2004-02-26
As a student who never has taken econometrics class, I suffered the weakness of this book (which was used as the textbook) more than I benefited from the strengths.
The strength of this book lies in the good examples they use. The book is not dense and mostly the explanation is very
concise. The examples they have is very interesting and might attract students' attention quite well.
However, I found this book's explanation is not very biginner
friendly. The explanation is often unnecessary compliated with too much math, so it might not be good for introductory econometrics class (it could make a good supplemental reading).
Gujarati's, Kennedy, etc has similar coverage but the explanation is much more plain and reader friendly.
The crucial problem which makes this book less than desirable is, amount of typos - I'd say one typo in a few pages on average. Although they have listed erratas on the publisher's web-site, unfortunately they cover relatively low fraction of all the typos this book has (could be inevitable problem with the first edition book). End-of-chapter questions and slides suffer the similar problem, so when my professor did not catch the problem in the end-of-chapter question, I just wasted too much time trying to figure out the answers, which was the worst part of using this book.
Book Description
Both state-space models and Markov switching models have been highly productive paths for empirical research in macroeconomics and finance. This book presents recent advances in econometric methods that make feasible the estimation of models that have both features. One approach, in the classical framework, approximates the likelihood function; the other, in the Bayesian framework, uses Gibbs-sampling to simulate posterior distributions from data.
The authors present numerous applications of these approaches in detail: decomposition of time series into trend and cycle, a new index of coincident economic indicators, approaches to modeling monetary policy uncertainty, Friedman's "plucking" model of recessions, the detection of turning points in the business cycle and the question of whether booms and recessions are duration-dependent, state-space models with heteroskedastic disturbances, fads and crashes in financial markets, long-run real exchange rates, and mean reversion in asset returns.
Customer Reviews:
Amazing treatement for the practitioner and the student.......2007-02-06
This book gives a step-by-step treatement of models with regime changes and time varying coefficients. If you are a student or a practitioner you will find this book very useful to start your applications. The first six chapters are very well developed, and the GAUSS codes provided by the authors let you realize how to do the job. These chapters will let you estimate a model using the classical approach. However, the next chapters that cover exactly the same topics using a bayesian approach are not that well developed. The examples and explanations are not clear, and the few examples do not help you generalize the techniques to your own models. The first six chapters, however, make this book worth 5 stars!
State-Space Models with Regime-Switching:Classical and Gibbs.......2003-12-31
This is basically the only book around on this subject, and they do have useful informations as well. I think explanation is concise enough to clearly understand. I found this book to be useful because of those. The only thing is some typos (which I think is inevitable for this kind of book) and program software on the web which is not very clearly written.
A waste of time........2002-01-29
This book is poorly written. It has numerous typos. The authors never even bothered to explain some of the math notations they used. Apparently, I believe some the examples were copied from other books without a clear explanation of the notations. You'll end up scratching your head on the notations and typos. I wasted a lot of time reading this book. They never mentioned some of shorting comings of using Gibbs Sampling, and ignore some of alternative methods that are far superior in many other respects.
excellent book on regime switching.......2001-03-28
This is really great book for understanding regime switching and state-space models.As far as I know this is the first book that includes both topics together.It is easy to understand and supporting applications at the end of the each chapter make things easier for the reader.Furthermore, it also tells about bayesian econometrics and gibbs-sampling approach.In short,it is a must buy book for a economics graduate student who is interested in nonlinear time series econometrics
Book Description
The techniques of multivariate statistics offer extremely powerful tools for use in solving everyday problems in a wide range of fields. Yet because of their statistical nature they are often out of reach of many of the people who could benefit from them. The rationale behind this book is that it is possible for an interested non-technical reader to gain a working understanding of multivariate analysis. It assumes a general but fairly basic statistical knowledge and concentrates on the statistical techniques specifically relevant to market research.
Book Description
Offering a broad overview of the state-of-the-art developments in the theory and applications of state space modeling, fourteen chapters from twenty-three contributors present a unique synthesis of state space methods and unobserved component models important in a wide range of subjects. They include economics, finance, environmental science, medicine and engineering. A useful reference for all researchers and students who use state space methodology, this accessible volume makes a significant contribution to the advancement of the discipline.
Average customer rating:
|
Simulation-based Inference in Econometrics: Methods and Applications
Manufacturer: Cambridge University Press
ProductGroup: Book
Binding: Hardcover
 Econometrics
| Economics
| Business & Investing
| Subjects
| Books
Statistics
| Economics
| Business & Investing
| Subjects
| Books
General
| Popular Economics
| Business & Investing
| Subjects
| Books
General
| Business & Investing
| Subjects
| Books
Entrepreneurship
| Small Business & Entrepreneurship
| Business & Investing
| Subjects
| Books
All Titles
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Similar Items:
-
Discrete Choice Methods with Simulation
ASIN: 0521591120 |
Book Description
Simulation-based inference (SBI) is the fastest growing area of research in modern econometrics. The techniques of SBI are widespread among scholars and researchers, and have become a staple part of undergraduate and postgraduate research programs. In this volume, Mariano, Schuermann, Weeks and their contributors provide an overview of the applications and techniques at the cutting edge of the subject, as well as a comprehensive survey of the existing literature. The contributions include important new essays by many of the leading figures currently working in econometrics.
Average customer rating:
|
Application of Econophysics: Proceedings of the Second Nikkei Econophysics Symposium - Application of Econophysics
Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover
Econometrics
| Economics
| Business & Investing
| Subjects
| Books
Statistics
| Economics
| Business & Investing
| Subjects
| Books
Theory
| Economics
| Business & Investing
| Subjects
| Books
General
| Popular Economics
| Business & Investing
| Subjects
| Books
General
| Science
| Subjects
| Books
General
| Physics
| Science
| Subjects
| Books
Applied
| Physics
| Science
| Subjects
| Books
General
| Physics
| Professional Science
| Professional & Technical
| Subjects
| Books
ASIN: 443114028X |
Book Description
Econophysics is a newborn field of science bridging economics and physics. A special feature of this new science is the data analysis of high-precision market data. In economics arbitrage opportunity is strictly denied; however, by observing high-precision data we can prove the existence of arbitrage opportunity. Also, financial technology neglects the possibility of market prediction; however, in this book you can find many examples of predicted events. There are other surprising findings.
This volume is the proceedings of a workshop on "application of econophysics" at which leading international researchers discussed their most recent results.
Average customer rating:
|
Income Elasticity and Economic Development: Methods and Applications (Advanced Studies in Theoretical and Applied Econometrics)
M. Ohidul Haque
Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover
Policy & Current Events
| Popular Economics
| Business & Investing
| Subjects
| Books
General
| Popular Economics
| Business & Investing
| Subjects
| Books
Development & Growth
| Economics
| Business & Investing
| Subjects
| Books
Econometrics
| Economics
| Business & Investing
| Subjects
| Books
Economic Policy & Development
| Economics
| Business & Investing
| Subjects
| Books
Macroeconomics
| Economics
| Business & Investing
| Subjects
| Books
Statistics
| Economics
| Business & Investing
| Subjects
| Books
General
| Business & Investing
| Subjects
| Books
All Amazon Upgrade
| Amazon Upgrade
| Stores
| Books
Business & Investing
| Amazon Upgrade
| Stores
| Books
All Titles
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Business & Investing
| Qualifying Textbooks - Fall 2007
| Stores
| Books
ASIN: 0387242929 |
Book Description
Income Elasticity and Economic Development: Methods and Applications is mainly concerned with methods of estimating income elasticity. This field is connected with economic development that can be achieved by reducing income inequality. This is highly relevant in today's world, where the gap between rich and poor is widening with the growth of economic development.
Income Elasticity and Economic Development: Methods and Applications provides a good example in showing how to calculate income elasticity, using a number of methods from widely available grouped data. Some of the techniques presented here can be used in a wide range of policy areas in all developed, developing and under-developed countries. Policy analysts, economists, business analysts and market researchers will find this book very useful.
Average customer rating:
|
Conditional Moment Estimation of Nonlinear Equation Systems: With an Application to an Oligopoly Model of Cooperative R&D (Lecture Notes in Economics and Mathematical Systems)
Joachim Inkmann
Manufacturer: Springer
ProductGroup: Book
Binding: Paperback
Econometrics
| Economics
| Business & Investing
| Subjects
| Books
Labor & Industrial Relations
| Economics
| Business & Investing
| Subjects
| Books
General
| Popular Economics
| Business & Investing
| Subjects
| Books
Statistics
| Social Sciences
| Nonfiction
| Subjects
| Books
General
| Science
| Subjects
| Books
Differential Equations
| Applied
| Mathematics
| Science
| Subjects
| Books
Probability & Statistics
| Applied
| Mathematics
| Science
| Subjects
| Books
General
| Mathematics
| Science
| Subjects
| Books
Statistics
| Applied
| Mathematics
| Professional Science
| Professional & Technical
| Subjects
| Books
All Amazon Upgrade
| Amazon Upgrade
| Stores
| Books
Business & Investing
| Amazon Upgrade
| Stores
| Books
Nonfiction
| Amazon Upgrade
| Stores
| Books
Professional & Technical
| Amazon Upgrade
| Stores
| Books
Science
| Amazon Upgrade
| Stores
| Books
All Titles
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Business & Investing
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Nonfiction
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Professional
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Science
| Qualifying Textbooks - Fall 2007
| Stores
| Books
ASIN: 3540412077 |
Book Description
Generalized method of moments (GMM) estimation of nonlinear systems has two important advantages over conventional maximum likelihood (ML) estimation: GMM estimation usually requires less restrictive distributional assumptions and remains computationally attractive when ML estimation becomes burdensome or even impossible. This book presents an in-depth treatment of the conditional moment approach to GMM estimation of models frequently encountered in applied microeconometrics. It covers both large sample and small sample properties of conditional moment estimators and provides an application to empirical industrial organization. With its comprehensive and up-to-date coverage of the subject which includes topics like bootstrapping and empirical likelihood techniques, the book addresses scientists, graduate students and professionals in applied econometrics.
Book Description
This digital document is a journal article from Journal of Econometrics, published by Elsevier in 2004. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
In this paper we propose a subsampling estimator for the distribution of statistics diverging at either known or unknown rates when the underlying time series is strictly stationary and strong mixing. Based on our results we provide a detailed discussion of how to estimate extreme order statistics with dependent data and present two applications to assessing financial market risk. Our method performs well in estimating Value at Risk and provides a superior alternative to Hill's estimator in operationalizing Safety First portfolio selection.
Books:
- Entrepreneur's Notebook: Practical Advice for Starting a New Business Venture
- Essay On Devel Of Christian Doctrine: Theology (Notre Dame Series in the Great Books, No 4)
- Fair Play: The Moral Dilemmas of Spying
- Foundations of Financial Management (The Mcgraw-Hill/Irwin Series in Finance, Insurance, and Real Estate)
- Foundations of International Macroeconomics
- Founders at Work: Stories of Startups' Early Days
- Friedrich Hayek: A Biography
- Global Cities
- Global Economic Issues and Policies with Economic Applications
- Global Shift, Fifth Edition: Mapping the Changing Contours of the World Economy (Global Shift: Mapping the Changing Contours)
Books Index
Books Home
Recommended Books
- The Frontiersmen: A Narrative
- Roadwork
- Erwin Hauer: Continua--Architectural Screens and Walls
- High-Rise Security and Fire Life Safety, Second Edition
- History: Fiction or Science
- International Financial Management
- L.A. Requiem
- Poolscaping: Gardening and Landscaping Around Your Swimming Pool and Spa
- Frank Lloyd Wright in Pop-up
- How to Connect With Our Living Earth: Telepathic Love from the Dolphins
Time Series Analysis
Applied Econometric Time Series (Wiley Series in Probability and Mathematical Statistics)
Macroeconomics (3rd Edition)
Games of Strategy, Second Edition
Industrial Organization: Contemporary Theory and Practice (with Economic Applications)
![Subsampling the distribution of diverging statistics with applications to finance [An article from: Journal of Econometrics]](http://ec1.images-amazon.com/images/I/11Q2DQ44BZL.jpg)