Using Econometrics A Practical Guide Problems
In most economics courses it is never the intention to use or require advanced econometrics skills. However, a certain level of basic knowledge and basic standards is required when reading academic journals and making empirical assignments. Econometrics is the discipline involved in empirical measurement and testing of economic relationships and the techniques to solve the associated problems.
Estimation and measurement has a large theoretical basis. Different estimators and hypothesis tests depend on a clear understanding of their statistical (distributional) properties. Courses in econometrics provide these theoretical aspects in the form of mathematical/statistical derivations, proofs, and algebra. Practical econometrics is not involved with derivations, proofs and matrix algebra.
Practical econometrics relies on standard estimation techniques and tests, as they are implemented in commercial econometrics computer software. However, practical econometrics still requires the practitioner to have an adequate understanding of the issues involved in selecting the appropriate techniques and tests. In other words, computer software generates output but this has to be understood and evaluated. Garbage in - garbage out. What we generally DO NOT need. An adequate understanding of the use of ordinary least squares estimation (OLS) is almost always sufficient, at least to start with. However, if you intend do some serious empirical research (for example, an empirical thesis) it is worthwhile to invest the additional effort and look into the uses of the more advanced techniques.
For example, unit root tests, cointegration methods, instrumental variables (IV, TSLS), GMM, FIML, SUR, VAR/VECM, estimation with panel data, etc. Again, do not spend much time on proofs and algebra, but focus on the arguments for choosing between alternative estimation techniques, and find out how to do the work using your statistical computer package. The following internet references provide useful online help with collecting additional insight into regression analysis and econometrics. The presentation and level of difficulty varies. My search for better websites continues and suggestions are welcome. Carefully select your desired topics. Focus on the practical implications and not on the algebra.
Always try to make the link with the practical use of the computer software package EViews. Search for the appropriate commands used in EViews in any given situation. I do not regularly work with panel data methods.
The following references provide some useful further explanation and discussions of various problems. Yaffee (2003), A primer for panel data analysis,.
Petersen (2009), 'Estimating standard errors in finance panel data sets: Comparing approaches,' Review of Financial Studies, vol.22 (1) January 2009: 435-80. Programming Advice - Finance Panel Data Sets: based on STATA. Arellano (2003) Panel Data Econometrics, Oxford University Press. Frees (2004) Longitudinal and Panel Data, Cambridge University Press. Kling, University Tuebingen: Short introduction, panel data analysis. Greene, Stern - New York Univ.: B55.9912 Econometric analysis of panel data.
ISER - EC968 Panel data methods. Edgerton, Lund University: Panel data course (2004).
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