The Only Book on Advanced Time Series Data Analysis you'll ever need


  • Author: Statistics Views
  • Date: 12 Apr 2019

I. Gusti Ngurah Agung, PhD, has been an advisor at the Ary Suta Center, Jakarta since 2008. He recently retired from his position as a lecturer at the Graduate School of Management, University of Indonesia. In addition to teaching and being an academic advisor, he has served as independent consultant for various institutions, such as the World Bank, UNFPA, ADB, USAID, and the Rand Corporation. He is the author of several statistical textbooks and research papers in the area of statistics and management. His area of interest is in statistical analysis based on censored data, multiple regression analysis, multivariate statistical analysis, and sociodemographic development.

I. Gusti Ngurah Agung latest book, Advanced Time Series Data Analysis: Forecasting Using EViews, has recently been published. The text itself is said to be the most comprehensive textbook on quantitative data analysis which presents the latest developments in forecasting, including statistical models not yet presented in competitive titles. Agung presents readers with a number of modern, advanced forecast models not featured in any other book. They include various interaction models, models with alternative trends (including the models with heterogeneous trends), and complete heterogeneous models for monthly time series, quarterly time series, and annually time series.

Advanced Time Series Data Analysis: Forecasting Using EViews will appeal to researchers and practitioners in forecasting models, as well as those studying quantitative data analysis. It is suitable for those wishing to obtain a better knowledge and understanding on forecasting, specifically the uncertainty of forecast values.

To purchase the book, please go to to do so now. However, if you want to learn more about the text itself, Fran McMahon sat down with I. Gusti Ngurah Agung to delve deeper into the books creation. Read on to find out more.

thumbnail image: The Only Book on Advanced Time Series Data Analysis you'll ever need

1. Advanced Time Series Data Analysis - Forecasting Using EViews has recently been published. The text is said to provide readers with several modern, advanced forecast models not featured in any other book. What led to the idea to write a book on this area of data analysis?

I would like to share my findings in doing forecasting based on various time series having specific growth patterns, including the time series by states, which I am very sure they have not been presented in such a detailed illustrative examples, either good or bad fit forecasting, in other books on time series.

2. This book presents advanced univariate multiple regressions, which can directly be used to forecast their dependent variables, evaluate their in-sample forecast values, and compute forecast values beyond the sample period. For someone who may not be well versed in this subject area, how would you explain the topic and study to them?

I have tried my best in presenting each chapter starting with the simplest possible model, such as in chapter 1, I present the LV(1) of any time series as the simplest possible forecasting model. So, I advice them to start with this model, then they can continue step-by-step to more advanced models. I am very sure, anyone who has been learning time series should know very well what is the LV(1) time series model, as well as LV(p) model in general. So I am expecting the readers do not have difficulties to study or learn my book in the step-by-step method.

3. What were your main objectives during the writing process? And which topic, that you discuss in your book, would you say was the most interesting studying?

During my writing process, my main objectives are as follows:

(a). to exercise in developing the best possible forecasting model based on various time series having specific alternative growth patterns

(b). to present systematic forecasting models and examples, starting with the simplest model, within each set or group of models, such as starting with alternative dynamic models of single time series, say Yt, then the models based on bivariate (Yt,Xt) up to multivariate variables, with and without the time variable predictor t=@Trend+1.

(c). to present best possible systematic guide book on data analysis in forecasting, with many examples. With special notes and comments.

(d). to present a lot of examples of statistical results data analysis, without the mathematical formulas to the readers. Since I have found most of the students and researchers have difficulties in the mathematical statistics, bases on my experiences as advisors and lecturer in statistics, over 50 years, since 1961.

(e) Hence the most interesting studying in my book is how to do data analysis, derive conclusions based on each statistical results, with their special notes and comments.

4. If there is one piece of information or advice that you would want your audience to take away from your book, what would that be?

I would say there is no piece of information should be taken away by the audience. I would advice them to read the book step by step starting with the simplest possible model within each specific set of models.

For the beginner in doing forecasting, I would advice them to learn only the simplest time series models in each chapter.
On the other hand, whenever someone need additional advice/information, they can contact me by email. I would be very glad to response as soon as possible. As an additional information, in fact, on the behave of the Ary Suta Center (ASC), Jakarta, I provide free consultation for students from any university, in doing data analysis for their theses. So far there are five graduate students of the National University of Malaysia had come to ASC for the consultations, and four have completes their Ph.D degree, in addition doing consultations by email.

5. Who should read the book and why?

The quantitative decision making in business, and the lecturer in Time Series Data analysis, because my book presents alternative models based on time series data having different growth patterns, and various illustrative examples with special notes and comments.

6. Why, do you think, this area of study may be of interest now?

Because, the output of forecasting is one of the best input for the quantitative decision making. In addition, I would say this area of study will be of interest forever.

7. Alongside your own text, what other books would you recommend to students looking to learn more about data analysis?

My book has presented several time series models, which have been presented also in other books, then they are extended to more advanced time series models. So the readers are advice to read the time series books, presented as the references of my books, specifically my previous books, since my previous books present many mores examples of statistical results compare to the other books.

8. What is it about the area of advanced time series data analysis that fascinates you?

I can develop various time series models easily, by using EViews, for the time series having specific growth pattern, either good or bad fit forecasting.

9. What other work are you currently working on or has recently been published?

Now I have been writing a book with the title “Application of Quantile Regression on Experimental and Cross Section Data Using EViews”. I am expecting I can send the New Proposal Book to Wiley, in June 2019. Then I will continue to write an addition book with the “Advanced Time Series Data Analysis: Quantile Regression and Alternatives Using EViews.

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Published features on are checked for statistical accuracy by a panel from the European Network for Business and Industrial Statistics (ENBIS)   to whom Wiley and express their gratitude. This panel are: Ron Kenett, David Steinberg, Shirley Coleman, Irena Ograjenšek, Fabrizio Ruggeri, Rainer Göb, Philippe Castagliola, Xavier Tort-Martorell, Bart De Ketelaere, Antonio Pievatolo, Martina Vandebroek, Lance Mitchell, Gilbert Saporta, Helmut Waldl and Stelios Psarakis.