d. One of the assumptions that needs to hold for the process {yt} to be weakly stationary is that cov(yt,Yt-k is constant over time and depends on both t and k. e. A white noise process is a non-stationary process for which all autocorrelations are equal to zero. f. If our series are non-stationary, it is safe to use OLS as our estimation method.

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d. One of the assumptions that needs to hold for the process {yt} to be weakly stationary is
that cov(yt,yt-k is constant over time and depends on both t and k.
e. A white noise process is a non-stationary process for which all autocorrelations are equal
to zero.
f. If our series are non-stationary, it is safe to use OLS as our estimation method.
Transcribed Image Text:d. One of the assumptions that needs to hold for the process {yt} to be weakly stationary is that cov(yt,yt-k is constant over time and depends on both t and k. e. A white noise process is a non-stationary process for which all autocorrelations are equal to zero. f. If our series are non-stationary, it is safe to use OLS as our estimation method.
d. One of the assumptions that needs to hold for the process {yt} to be weakly stationary is
that cov(yt,yt-k is constant over time and depends on both t and k.
e. A white noise process is a non-stationary process for which all autocorrelations are equal
to zero.
f. If our series are non-stationary, it is safe to use OLS as our estimation method.
Transcribed Image Text:d. One of the assumptions that needs to hold for the process {yt} to be weakly stationary is that cov(yt,yt-k is constant over time and depends on both t and k. e. A white noise process is a non-stationary process for which all autocorrelations are equal to zero. f. If our series are non-stationary, it is safe to use OLS as our estimation method.
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