Basic Regression Analysis with Time Series Data - Finite Sample Properties of OLS under Classical Assumptions
3 important questions on Basic Regression Analysis with Time Series Data - Finite Sample Properties of OLS under Classical Assumptions
What are the classical linear model assumptions in time series regression?
TS2 (No perfect collinearity)
TS3 (Zero conditional mean) E[u|X]=0
TS4 (Homoskedasticity) var(u|X)=o2
TS5 (No serial correlation) correlation(u(t),u(s)|X)
TS6 (Normality) N(0,o2)
Which TS assumptions have to hold to get unbiasedness OLS?
Which variables hold with TS1-TS5 Gauss-Markov assumptions?
The question on the page originate from the summary of the following study material:
- A unique study and practice tool
- Never study anything twice again
- Get the grades you hope for
- 100% sure, 100% understanding
![Trustpilot Logo](/images/design_2020/lp/clp-trustpilot-en.png)