Question -

After collecting the data, a forecaster plans on initially estimating the following model

y = β₀ + _i=1∑⁸β_iX_i + β₉(X₅*X₇) +e,

then dropping all of the X variables that are not significant at the 0.05 level, and re-estimating the resulting model to use in forecasting y. Follow this plan and interpret the results from each of the estimated models. Are there potential errors in the model? Assess the models in terms of bias and/or consistency, and efficiency of the estimates. Provide tests and explain the results. Assess the models in terms of forecasting.

Is there a better alternative forecasting model? If so, why would this model be preferred to either of the above models? If not, explain why either or both of the above models are adequate.

Explain the role of non-sample information in specifying and estimating models in this context. How may non-sample information be useful in obtaining unbiased/consistent and efficient estimates? Explain in the context of the above model.

Please use Stata to solve this question.

Attachment:- Data.rar