Do you agree or disagree with the following statements? Please also provide a br

Question

Do you agree or disagree with the following statements? Please also provide a brief explanation for your decision:

A. Like cross-sectional observations, we can assume that most time series observations are independently distributed

B. The OLS estimator in a time series regression is unbiased under the first three Gauss-Markov assumptions

C. A trending variable cannot be used as the dependent variable in multiple regression analysis

D. Seasonality is not an issue when using annual time series observations

Explanation / Answer

Solution:

A) Disagree. Time series processes are often identically but not independently distributed.
Things that happen in one period tend to influence things that happen in the next —
which is another way of saying that most time series processes are correlated over time,
which is a violation of the independence assumption.

B) Disagree. Time series processes are often identically but not independently distributed.
Things that happen in one period tend to influence things that happen in the next —
which is another way of saying that most time series processes are correlated over time,
which is a violation of the independence assumption.

C) Disagree. We must take care to remove trends that might cause spurious correlation,
but there is no reason why we cannot use a trending variable as a dependent variable.

D) Agree. Mostly, Seasonality usually refers to inter-annual variations, but really, the
phenomenon is simply one of repeated patterns, which could occur over any period of
time. So technically, I think the best answer is “yes,” seasonality is not an issue when
using annual time series observations, but we still need to be aware of regular patterns
that could exist in the data. If you answered “disagree” but gave this as a reason, I give
you full credit.

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