Please take note of changes in red concerning Part II made during Reading Week.

• Emphasizes problems in specifying and estimating econometric models, methods available for detecting and handling these problems, and economic applications. Extensive use of matrix algebra. PREREQUISITE ECON 255* and 351*. EXCLUSION ECON 352*. NEW! This course is required for the Major in Applied Economics program

The description above was written many years ago and has not been updated.  Despite this heritage it is surprisingly accurate, but a more precise and detailed discussion of our specific objectives is warranted.:

Part I

In Economics 351, you studied the classical linear regression model. One key assumption of this model was a fixed X (non-stochastic regressors). For time series models, this assumption is untenable. Researchers are now compelled to understand the econometrics of time dependent processes. While the tools of classical econometrics are extremely useful in advancing in this direction, there are many important departures in time series that require additional machinery.

The intention of Part I is to learn and to use the tools of applied time series analysis. This modelling technique is atheoretical.

Our emphasis will be on application; that is, taking the concepts developed in the lectures and employing them in two time series projects. However, there will inevitably be a great deal of theory in the lectures given the nature of the topic.

Notes are bound and sold to you at cost from the AMS Publishing office.These notes are intended to serve as the basis of all the theory. No other book is required.

Part II

As with part one, Economics 351 is our departure point.  The first project gives you the opportunity to learn by doing the first steps in the art and practice of applied micro-econometrics.

• find a topic that can be studied using a survey data set (by reading published papers using similar data)
• making the data set suitable for a linear multiple regression analysis (by following the data handling procedure described in a published paper)
• summarizing your data set for others to understand (by following the example of data summaries in published papers)
• reporting the results of your regression analysis in a clear and complete way (by following the example of published papers)
• making your results available to other researchers through the WWW (the primary medium for disseminating initial research results in economics).

The second project in Part II gives you the opportunity to learn by doing the most important class of statistical model beyond multiple regression for analyzing survey data sets, namely limited dependent variable (LDV) models of various sorts (logit, probit, and tobit).  The same process is required in the second project as the first, but now much more attention is paid to applying techniques appropriately and correctly interpreting the results.
 
 

Part II: the second six weeks of both sections, taught by Professor Ferrall.
 

• Professor Gregory's class notes available at AMS:
• Professor Ferrall's class notes available from this homepage.  You will need a WWW browser and Adobe Acrobat Reader.  Some supporting references will also be listed.  One paper is used as a sample: The Economics of Abuse,  Audra J. Bowlus and Shannon N. Seitz, July, 2000.
• Both parts require use of Stata version 6.0. This version of Stata is available in Dunning 350 and MC B405.  Dunning 350 has a laser printer but you are to supply the paper for your work.