. What are the important reasons econometricians used lag values of a time series variable?

2. Identify whether the statements from (a)-(c) ate true or false, and explain the reason intensely.

• One of the assumptions that need to hold for the process tyt} to be weakly stationary is that co v(yt, yt-k) is constant over time and depends on both t and k.
• A white noise process is a non-stationary process for which all autocorrelations are equal to zero.
• If our series are non-stationary, it is safe to use OLS as our estimation method.

3. Suppose we have the following model: Y,= a+ flXi+ U,

where the explanatory variable X, is strictly exogenous, and the residual U, is serially correlated.

• Why is serial correlation often present in time series data?
• Why is the presence of serial correlation in the residual a problem?

Suppose we can express serial correlation in U, in the equation above as follows:

U, = PU,•, +e,

State the null hypothesis for testing serial correlation in the equation.