This web site supports our book, Introductory Econometrics: Using Monte Carlo Simulation with Microsoft Excel, published by Cambridge Humberto Barreto. Read “Introductory Econometrics Using Monte Carlo Simulation with Microsoft Excel” by Humberto Barreto with Rakuten Kobo. This highly accessible and. Introductory Econometrics: Using Monte Carlo Simulation with Microsoft Excel. Front Cover · Humberto Barreto, Frank Howland. Cambridge University Press.

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Thanks for telling us about the problem. Return to Book Page. Preview — Introductory Econometrics by Humberto Barreto. This highly accessible and innovative text with supporting web site uses Excel R to teach the core concepts of econometrics without advanced mathematics. It enables students to use Monte Carlo simulations in order to understand the data generating process and sampling distribution.

Intelligent repetition of concrete examples effectively conveys the properties of the ordi This highly accessible and innovative text ecobometrics supporting web site uses Excel R to teach the sconometrics concepts of econometrics without advanced mathematics. Intelligent repetition of concrete examples effectively conveys the properties of the ordinary least squares OLS estimator and the nature of heteroskedasticity and autocorrelation.

Coverage includes omitted variables, binary response models, basic time series, and simultaneous equations. The authors teach students how to construct their own real-world data sets drawn from the internet, which they can analyze with Excel R or with other econometric software. The accompanying web site with text support can be found at.

Introductory Econometrics : Humberto Barreto :

Hardcoverpages. Published December 26th by Cambridge University Press.

To see what your friends thought of this book, please sign up. To ask other readers questions about Introductory Econometricsplease sign up. Be the first to ask a question about Introductory Econometrics. Lists with This Book. This book is not yet featured on Listopia. Apr 23, Bbarreto added it. When I was a new graduate student I ended up buying several different econometrics texts.

No one text had the best explanation for each topic. The problem remained that for many topics I never did find a book which translated the formal mathematical presentation into a practical worked out example, so that I could understand the procedure and how to implement it. Every topic includes guided Microsoft Excel spreadsheets and add-ins which illustrate the topic being addressed. The economics and the econometrics are presented with such clarity and unity; bridging the two in a way that none of the other texts do.


These are “live” spreadsheets that invite you to experiment. For example; there is an Excel workbook which illustrates the correlation coefficient. Rather than a dry recitation of formula and proof, you can interact with the spreadsheet and see exactly how the same coefficient can apply to data having very different patterns. It is one thing to see an illustration, and quite another to actually be the one creating the diagram, simply by running the macros and changing parameters.

This “hands on” approach is so vital to actually getting an understanding of the material. I have only a basic understanding of Excel, and have had no difficulties in using the workbooks. While the limits of Excel are pointed out by the authors, it is important to note the reason for using Excel. It is widely understood and available; there is no learning curve.

By using Excel there is no software barrier between the student and understanding the principles of econometric modelling. Most of that time was used to extract the data from a. Once I had the data in Excel, it took less than 2 minutes to run the Probit estimation my first time using that add-in! By the way, the results using the authors add-in for solving Probit models with ML estimation were the same as the results from GAUSS code to do the same.

The add-in had a distinct advantage though in that a choice for Probit or Logit model estimation using either Econometrjcs Linear Least Squares or the Maximum Likelihood estimation was just a radio button away! This text can complement any course, regardless of the software used.

Again, the beauty of the book is that you are not just left with Greek formulas that leave you wondering how to do the computations, and you are not left with computer output leaving you to wonder how to interpret that output. The text explains the meaning so powerfully that you are not only armed with an understanding which is useful for success in your course work, but also for applying the quantitative tools in real world analysis and applications.

The text is like going to see your favorite professor who is sitting there with you one on one, giving you insight which only econnometrics from experience.

Introductory Econometrics: Using Monte Carlo Simulation with Microsoft Excel

I’ve been through courses that use Greene, and Judge, as well as introductory texts. This text stands alone in making use of the computing power we have at our disposal today, not to produce more computer printouts, but rather to increase our understanding–providing the sound reasoning for applying that power.


I should add that even after two years of statistics and econometrics I learned quite a lot from the statistics review chapters. Don’t be misled by the “Introductory” title. I had learned and executed Artificial Neural Network models in graduate courses, but still learned a lot from the section on correlation in this book.

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For undergrad students this book will put you on the right path. For hhumberto students it will correct blind spots and misconceptions. The authors have created a product that I wish I had when I was in school, but am glad I found now for applying in my career. Detailed info on contents as well as the Excel files and add-ins are available from the introductorh web site which I found prior to ordering from Amazon.

Once I tried the workbooks, I knew I wanted the book. It’s pages of solid information and inspired teaching.

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