Reference Text: Basic Econometrics by Damodar N. Gujarati & Dawn C. Porter Purpose: To outline the fundamental methodology of econometrics, moving from the classical linear regression model (CLRM) to practical issues and modern updates in the field.
# R: OLS
model <- lm(log(income) ~ education + age + experience + female, data = df)
summary(model)
# R: Robust SE
library(sandwich); library(lmtest)
coeftest(model, vcov = vcovHC(model, type="HC1"))
# R: 2SLS (ivreg)
library(AER)
iv_model <- ivreg(log(income) ~ education + age | instrument + age, data=df)
summary(iv_model)
regress ln_income education age experience female
ivregress 2sls ln_income (education = instrument) age experience
xtreg ln_income education age, fe
When searching for an updated (UPD) PPT deck online, you should look for certain hallmarks. A comprehensive set of slides based on Gujarati’s 5th or 6th edition typically includes the following chapters: basic econometrics gujarati ppt upd
When you open a file named Gujarati_Ch12_Hetero_UPD.pptx, check the table of contents slide. A true updated version will have this flow: Reference Text: Basic Econometrics by Damodar N
| Slide Section | Content (Updated features) |
| :--- | :--- |
| Introduction | Real-world example: 2023 Housing price volatility vs. 1990s. |
| Nature of HET | Graphical plot showing "increasing variance" (Brewer's scatter plot). |
| Detection (Old) | Park Test, Glejser Test (Manual calculation). |
| Detection (New/UPD) | Breusch-Pagan-Godfrey Test output from EViews 13 / STATA 18. |
| Consequences | A slide with two side-by-side graphs: Biased SE, T-stat losing power. |
| Remedies | GLS (Generalized Least Squares) vs. Robust Standard Errors (White’s method). |
| Software demo | Screenshot of R code: coeftest(model, vcov = vcovHC(model)). | # R: OLS model <- lm(log(income) ~ education
If your PPT does not have the "Robust Standard Errors" slide, it is likely a very old version (Pre-2010) and may hurt your grade.