Heteroscedasticity, Multicollinearity and Autocorrelation: Basics

Heteroscedasticity, Multicollinearity and Autocorrelation: Basics

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The objective of this series of tutorials is to make the basic concepts related to Heteroscedasticity, Multicollinearity and Autocorrelation easier to understand. The tutorials discuss the theory and application of several concepts related to these topics. For all the details on the tutorials, go to the following link: Heteroscedasticity, Multicollinearity and Autocorrelation: Basics

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Description

The objective of this series of tutorials is to make the basic concepts related to Heteroscedasticity, Multicollinearity and Autocorrelation easier to understand. The tutorials discuss the theory and application of several concepts related to these topics. The tutorials cover the following topics in detail:

  • What is Heteroscedasticity?
  • Causes of Heteroscedasticity
  • Consequences of Heteroscedasticity
  • Detecting Heteroscedasticity
  • White Test for Heteroscedasticity
  • Breusch-Pagan Test for Heteroscedasticity
  • Solutions to Heteroscedasticity
  • Weighted Least Squares
  • Robust Standard Errors
  • Calculation of Robust Standard Errors
  • What is Multicollinearity?
  • Causes and Consequences of Multicollinearity
  • Detecting Multicollinearity
  • Variance Inflation Factor or VIF
  • What is Autocorrelation?
  • Causes and Consequences of Autocorrelation
  • Detecting Autocorrelation
  • Durbin-Watson Test for Autocorrelation
  • Bresuch-Godfrey LM Test for Autocorrelation
  • Solutions to Autocorrelation
  • Newey-West Standard Errors
  • Estimation and Application of Newey-West Standard Errors in R and Stata

For all the details on the tutorials, go to the following link: Heteroscedasticity, Multicollinearity and Autocorrelation: Basics

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