Show that OLS estimator of variance is an unbiased estimator?

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orchestra answered 1 year ago

Show that ?̂??? is an unbiased estimator of minimum variance of parameter ? for a binomial...

Show that ?̂??? is an unbiased estimator of minimum variance of parameter ? for a binomial distribution with parameters ? (known) and ?.

The Gauss-Markov theorem says that the OLS estimator is the best linear unbiased estimator.

The Gauss-Markov theorem says that the OLS estimator is the best linear unbiased estimator. Explain which assumptions are needed in order to verify Gauss-Markov theorem? Consider the Cobb-Douglas production function

Show that ?̅ is an unbiased estimator for ?. ( please show all work completely)

Explain what assumptions are needed in order for the OLS estimator to be unbiased in a crosss sectional environment.

Explain what assumptions are needed in order for the OLS estimator to be unbiased in a crosss sectional environment. Explain what assumptions are needed in order for the OLS estimator to be unbiased in a panel data environment.

Explain what assumptions are needed in order for the OLS estimator to be unbiased in a time series environment.

4. Is OLS estimator unbiased when we use time series data? Why or why not? Are...

4. Is OLS estimator unbiased when we use time series data? Why or why not? Are standard errors still valid if there is serial correlation? Why or why not?

Suppose that Yi=?0+?1Xi+ui and that E[ui|Xi] = 0 and therefore OLS is an unbiased estimator. a)...

Suppose that Yi=?0+?1Xi+ui and that E[ui|Xi] = 0 and therefore OLS is an unbiased estimator. a) Show that Zi=Xi is a valid instrument for Xi , i.e. it is both relevant and exogenous. b) Show that the 2SLS estimator of ?1 using Xi as an instrument for Xi is exactly equal to the OLS estimator of ?1 c) Let Zi=X2i and assume Xi is normally distributed N(?,?²). Is Zi exogenous? Is Zi relevant? Explain how the answer to these questions...

Under assumption MLR.1 - MLR.5, derive the variance of the OLS estimator bj in the multiple...

Under assumption MLR.1 - MLR.5, derive the variance of the OLS estimator bj in the multiple regression model. Express the variance in terms of the R-squared from the regression of xj on the other explanatory variables.

Explain and discuss why engineers usually want the minimum variance unbiased estimator (MVUE). What benefits are...

Explain and discuss why engineers usually want the minimum variance unbiased estimator (MVUE). What benefits are achieved by using the MVUE in making engineering decisions, and what risks or impacts might be seen if another estimator is chosen at times? Try to use hypothetical examples to illustrate your thinking.

explain OLS assumptions and when they are biased and unbiased.

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