Question

In: Economics

For time series data, where time dependency exists, which of the 5 assumptions under which the Gauss Markov theorem holds is violated. Explain.

For time series data, where time dependency exists, which of the 5 assumptions under which the Gauss Markov theorem holds is violated. Explain.

Solutions

Expert Solution

Gauss Markov model is based on following 5 assumptions :

  • Linearity
  • Random
  • Exogeneity
  • Non collinearity
  • Homoscedasticity

Out of which the time series data doesn't hold true or violates is the "Non Collinearity" assumption as time series regression model is auto correlated and thus based on gauss markov the analysis must be non collinear and regressors should not be perfectly correlated.


Related Solutions

What does the Gauss-Markov theorem claim? Explain the assumptions needed for the Gauss-Markov Theorem.
What does the Gauss-Markov theorem claim? Explain the assumptions needed for the Gauss-Markov Theorem. Are all the assumptions necessary to construct the OLS estimates of the intercept and slope coefficients.
The Gauss Markov Theorem says a) Under the LS assumptions, the OLS estimator has the smallest...
The Gauss Markov Theorem says a) Under the LS assumptions, the OLS estimator has the smallest variance among all linear unbiased estimators b) Under the LS assumptions, the OLS estimator has the smallest variance among all linear estimators c) The OLS estimator has the smallest variance among all linear unbiased estimators d) Under the LS assumptions, the OLS estimator is the most consistent estimator of all linear unbiased estimators
For each of the Gauss-Markov Theorem assumptions (A0-A3), do the following:
For each of the Gauss-Markov Theorem assumptions (A0-A3), do the following: (a) State the assumption in mathematical terms. (b) State the intuitive meaning of the assumption. (c) For bonus points, state what might cause the assumption to be violated.
For each of the Gauss-Markov Theorem assumptions (A0-A3), do the following: (a) State the assumption in...
For each of the Gauss-Markov Theorem assumptions (A0-A3), do the following: (a) State the assumption in mathematical terms. (b) State the intuitive meaning of the assumption. (c) For bonus points, state what might cause the assumption to be violated.
Under what conditions does the Gauss-Markov Theorem guarantee the OLS estimators to be BLUE? State such...
Under what conditions does the Gauss-Markov Theorem guarantee the OLS estimators to be BLUE? State such conditions and explain each of them in your words. What does it mean for the OLS estimators to be BLUE? Explain
. Under the Gauss-Markov assumptions, we know that the Ordinary Least Squares (OLS) estimator βˆ is...
. Under the Gauss-Markov assumptions, we know that the Ordinary Least Squares (OLS) estimator βˆ is unbiased, efficient, and consistent. However, if the assumption that E[ϵ 2 i |X] = σ 2 i = σ 2 is violated while the assumption of E[ϵi , ϵj ] = 0 , ∀i ̸= j holds, that the least squares estimator is unbiased but is no longer efficient. The Generalized Least Squares (GLS) estimator, in this case, may be unbiased, consistent, and efficient...
Q1: Explain what homoscedasticity is. Why is heteroscedasticity a violation of the Gauss-Markov Assumptions. i.e. explain...
Q1: Explain what homoscedasticity is. Why is heteroscedasticity a violation of the Gauss-Markov Assumptions. i.e. explain why MLR.5 is necessary.
Explain the Gauss-Markov assumptions required for unbiasedness and efficiency of the OLS estimator. Distinguish between the...
Explain the Gauss-Markov assumptions required for unbiasedness and efficiency of the OLS estimator. Distinguish between the assumptions for simple and multiple linear regressions. Provide examples of violations of each assumption. Under what circumstances are coefficient estimates from MLR and SLR identical?
(a) Create the correct time series plot. Which type of pattern exists in the data?
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 4 6 7 2 0 1 4 3 3 5 6 4 5 7 8 (a) Create the correct time series plot. Which type of pattern exists in the data? (b) Use a multiple regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data. Qtr1 = 1 if Quarter 1, 0 otherwise; Qtr2 = 1 if Quarter...
Construct a time series plot. What type of pattern exists in the data?
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 4 6 7 2 2 3 6 3 3 5 6 4 5 7 8 Construct a time series plot. What type of pattern exists in the data? The time series plot indicates a linear trend and a seasonal pattern Show the four-quarter and centered moving average values for this time series.   Compute seasonal indexes and adjusted seasonal indexes for the four quarters.
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT