Econometrics cheat sheets created using
- Econometrics Cheat Sheet: Basic econometrics concepts, OLS assumptions and properties, coefficient interpretatation, error measures, R-squared, hypothesis testing and confidence intervals, dummy variables and structural change, summary of popular OLS problems and more!
- Time Series Cheat Sheet: Components of a time series, trends and seasonality, auto-correlation, stationarity, weak and strong dependence, cointegration and heterocedasticity on time series.
- Additional Cheat Sheet: Matrix notation of OLS, variable omission problem, proxy variables, instrumental variables, Two Stage Least Squares, information criteria, non-restricted hypothesis test, incorrect functional form, logistic regression, statistical definitions, VAR models, VECM.
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Econometrics Cheat Sheet. Current version: CS-24.2
PDF file | TeX file | |
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English 🇬🇧 | en.pdf | en.tex |
Spanish 🇪🇸 | es.pdf | es.tex |
Time Series Cheat Sheet. Current version: TS-24.2
PDF file | TeX file | |
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English 🇬🇧 | en.pdf | en.tex |
Spanish 🇪🇸 | es.pdf | es.tex |
Additional Cheat Sheet. Current version: ADD-24.2
PDF file | TeX file | |
---|---|---|
English 🇬🇧 | en.pdf | en.tex |
Spanish 🇪🇸 | es.pdf | es.tex |
Those are the residuals from a OLS regression between
Why is $\beta_0$ the constant term? My reference manual / professor's definition of the econometric model is different.
There is some debate about the correct way to name the coefficients, their sub-index and the sub-index of the variables of a model. The naming could have an impact on how some statistics like the adjusted R-squared or some tests like the F test are written.
For example, while some econometricians write the multiple regression model with a constant term like this:
There are others that refer to that same econometric model as:
And others refer as:
All the above are equally valid representations of the multiple regression model. In the specification
In this project, the main specification used is the first
The specification
For specification
For space reasons, the version included in the cheatsheet is the matricial one. It is perfectly valid and equal to the non matrix version.
The non matrix version:
In addition to the notes taken from the Degree in Economics and Master in Modern Economic Analysis by Universidad Rey Juan Carlos, and the Master in Applied Statistics by Máxima Formación and Universidad Nebrija, the books used:
[1] Baltagi, B. H. (2011). Econometrics. New York: springer.
[2] Gujarati, D. N., Porter, D. C., & Gunasekar, S. (2012). Basic econometrics. Tata McGraw-Hill Education.
[3] James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning. New York: springer.
[4] Lütkepohl, H., & Krätzig, M. (Eds.). (2004). Applied Time Series Econometrics. Cambridge: Cambridge University Press.
[5] Ruiz-Maya, L., & Pliego, F. J. M. (2004). Fundamentos de inferencia estadística. AC.
[6] Stock, J. H., & Watson, M. W. (2012). Introduction to econometrics. New York: Pearson.
[7] Wooldridge, J. M. (2015). Introductory econometrics: A modern approach. Cengage learning.
- Reddit user _bheg_ - Pointed out about the importance of including strong and weak exogeneity and their consequences on bias and consistency properties of OLS.
The first (and I think, the best) way to help the project is to directly support the authors of the manuals that are included in the resources section (for example, by buying their works). Each and every one of the authors of the manuals are wonderful minds who have contributed a lot to econometrics and statistics.
Another great way to support the project is by sharing it and ⭐ it!