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(a) Describe all tests that you need to undertake prior to working with time series data.
(b) Consider the following regression result:
Standard Errors: (6.7525) (0.8229) (0.0807)
R-squared = 0.9835; R-bar square = 0.9631 df = 7 F-ratio= 102.40
where Y denotes consumption (in rupees); X1t denotes income (in rupees) and X2t denotes income to the square.
(i) What is the problem with this regression? Explain in details.
(ii) With reference to your answer to the above, how would you detect such problem?
(iii) A researcher wants to model the demand for Nokia mobiles in Mauritius. If you were the researcher, clearly provide a model type along with the expected signs for each of the variables you considered.
if there is multicollinearity so why we can not estimate the value of parameters?
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