Syllabus Textbook Notes Software Data Homework Examples Other Links Hours |
## Econometrics I## Econ 5243Econometrics I (Econ 5243) is the first course in our Ph.D. level graduate econometrics sequence. This course is appropriate for advanced master's students as well, although those not well versed in linear regression are advised to take Econ 5213 first. There is a much greater emphasis in this course on econometric theory and tools than you'll find in 5213. So, I also advise as a prerequisite a two course sequence in mathematical statistics. In recent years this course has been taught using Davidson and MacKinnon's Econometric Theory and Methods and is suitable only for those who are already reasonably comfortable running regressions and matrix algegra. This page provides links to all important information available on this web site for those enrolled in my Econ 5243 sections this spring. |

- Resources for learning Stata
- Loading web based data into STATA. Unfortuantely, this only works from Internet Explorer (or other web browsers that support Microsoft's .mht format) at this time.
- Introduction to Stata
- Some of you have asked me, "Why aren't we using SPSS?" Although SPSS is particularly adept at analysis of variance, it is not as well suited for the robust kinds of analyses that I think you should be using. Hence, I picked STATA, which is relatively good at this sort of thing and still offers a reasonably powerful engine for doing the things that SPSS does. Version 9 of STATA made some significant strides in this area. For a comparison of SAS, SPSS, and STATA (older version) see UCLA's software comparison.
- This file contains the instructions for computing two-stage least squares in Stata TSLS in Stata.
- The Stata Starter kit from UCLA. This is particularly valuable for those learning to use Stata. There are a number of online tutorials with notes that are available. To get used to using Stata, I suggest looking at the class notes with movies found here.

- Gretl homepage. Gretl. The MS Windows executable that will install Gretl onto your Windows computer is Here. Also listed are some datasets that you may wish to install.
- Using gretl for Principles of Econometrics. This book was prepared to use with another textbook. It gives you a pretty good introduction to using Gretl. Gretl Book.
- Here is a link to the gretl datasets for Davidson and MacKinnon's ETM: Econometric Theory and Methods. Basically, you can click on it to install it. Make sure you install it to the right directory, otherwise gretl won't be able to find it.
- Also, you can consult my gretl page that will contain the links listed above and a few othters.

- The data sets from Davidson and MacKinnon's site here.
- The gretl data sets can be found here.
- The consumption.txt file from Davidson and MacKinnon. Useful for Introduction to Gauss tutorial above.
- Stata datasets from Stock and Watson.
- caschool1.txt for use in ETM 2.16 homework. For the Stata part of this excercise you can use caschool.dta, which is already in Stata format.
- The Wage Data from Jeffrey Wooldridge
- The Stata datasets for dynamic models
- The gasoline consumption data from Greene.
- The ces data (from PoE)
- The Money data from ETM
- Air Quality (Verbeek)
- The Stata data sets from Principles of Econometrics
- The CES_2012.gdt gretl dataset for the CES homework
- mlb1.gdt from Wooldrige.

- Simulation exercise
- Regression exercise. Due March 13. Data.

- Nonlinear least squares and Delta Method

- Nonlinear least squares example using gretl
- Heteroskedasticity program and output.
- Bad Functional Form or autocorrelation?
- Autocorrelation Example from POE
and the .do file

- Jeffrey Wooldridge textbook site
- Latex
and related links. Here you will find some links to sites
that will help you get started with LaTex, if you are so inclined. If
you are just getting started using TeX the go first to Getting Started.
LaTex (pronounced Lay-Tek) is actually a package that makes TeX
(pronounced Tek) much easier to use. According to the Tex User Group
FAQ "TeX ix a typesetting system written by Donald E. Knuth, who says
in the Preface to his book on TeX (see books about TeX) that it is
'intended for the creation of beautiful books - and especially for
books that contain a lot of mathematics'." If you ever plan on writing
professional
papers or books (dissertations) then I highly recommend that you learn to use this system. For example, your textbook was typeset by the authors using TeX.*looking*

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