Flashcards in Term 2 Deck (69)
Discuss Simple and Multiple Regressions
A ~ represents a simple
A ^ represents multiple
What is the simple relationship between B~1 which does not control for X2 and B^1 which does (Bias)
What are the two cases of B~ and B^?
If x2's effect on Y is positive, x1 and x2 are positive correlated
If x1 and x2 are negatively correlated
What is bias equal to for B~1?
What is asymptotic theory?
As N gets larger, the probability that Z is different from its mean falls
What is the CLT?
As a sample size increases, the sample becomes normally distributed
What is the consistency of OLS?
As sample size increases, a coefficient tends to its true value
What is the normality of OLS?
As the sample size increases, the distribution becomes normal
What are the consequences of heteroskedasticity?
OLS is unbiased,
Incorrect estimators therefore cannot use T and F tests
OLS no longer BLUE
How do you estimate variance of a coefficient under heteroskedasticity?
Why is it not a good idea to only compute robust SE?
They are worse than usual SE
How can we detect heteroskedasticity?
The Breusch-Pagan Test
How do you perform the Breusch-Pagan Test?
Estimate the Regression, Square the residuals
Regress U^2 using explanatory variables, F test for joint significance
How do you perform the white test?
Same as BP but with indicators
How do you calculate the WLS?
Replace every coefficent by RootX
What is the difference between CS and TS data?
TS data is ordered, thus is not randomlyy sampled
There is therefore correlation
What are the types of TS data models?
Static: Same time period
Finite Distributed Lag (FDL): Y can be affected by upto Q periods in the past
What is lag distribution and how is it calculated
Plots the coefficents of each lagged variable on a graph
What is the impact propensity? What occurs if log form?
The coefficent of Z in the current time period - immediate change
Short run instantaneous elasticity
What is the long run propensity? What occurs if log form?
The sum of all lag coefficents
Tells us what happens if Z permanently increases
Called long run elasticity
What is an autoregressive model? What does its order determine?
A model where past Y's influence current Y's
Order is number of lags
What assumptions are required for finite sample OLS to be unbiased? (1-3)
TS1 - Linear in Paramaters
TS2 - No perfect collinearity
TS3 - Errors conditional mean is zero
These assumptions allow OLS to be unbiased
What assumptions are required for finite sample OLS to be unbiased? (4-6)
TS4- Homoscedaticity (Variance does not depend on X or change over time
TS5- No serial correlation (errors are not correlated)
TS6 - Normality
What is contemporaneous exogenity?
A weaker assumption of TS3, that assumes no conditional mean for only variables within the same time period
What are the three types of correlaton?
Explanatory variables over time
Explanatory variables and errors
Violates TS3 and bais
Errors over time
How do you calculate variance of a coefficent in a TS model?
Variance(B) = Var/SST(1-R2)
What is the problem associated with TS data and R2
If their is a high trend within the data, R2 will be higher than it should be
What is weakly dependant data?
The condition that we impose on TS data to ensure CLT and LLN holds
Correlation between observations gets smaller as time between grows
How do you calculate the corr for weakly dependant data?
Coefficent of Yt-1 raised to time period in advance