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R2 Is usually higher in time series econometrics. Why?
Time series data is often in an aggregate form
Trending dependent variables
Stationarity
A stochastic if the probability distribution of the stochastic process does not change over time
Formally the joint distribution of Yt is the same as the joint distriubtion of Yt+h
Covariance Stationarity
A stochastic process, with a finite second moment E(xt) < ∞, is covariance stationary if:
E(xt) is constant
Var(xt) is constant
For any t,h Cov(Xt,Xt+h)
Weak Dependence
A stationary series is weakly dependnet if xt and xt+h are ‘almost’ independent as h increases
Corr(xt,xt+h) tends to zero as h increases
Asymptotic Properties of OLS
TS 1’: Linearity and Weak dependence
No perfect collinearity
Zero conditional mean
Homoskedasticity
No serial Correlation