What is meant by multicollinearity? What are its consequences on estimates? What remedial measures do you suggest for the problem?

How do you express the multiple regression model in matrix form? Derive OLS estimator for the parameters of the model. Show that the OLS estimators are Best Linear Unbiased Estimators (BLUE).

 Explain the concept of identification in a simultaneous equations model. Why is it called the paradox of identification?

 The relationship between Y and X is given by  where u_i follows classical assumptions. Consider the following set of data and answer the questions.

| Y | 11 | 12 | 13 | 14 | 15 |

|---|----|----|----|----|----|

| X | 18 | 16 | 19 | 22 | 20 |

a) Estimate parameters of the model from the following data by using OLS method.

b) What is the estimate of error variance in the above case?

c) Find the value of R2 for the above data.

. In the case of a two-variable regression model show that TSS = ESS + RSS. Use appropriate diagram to explain your result. In this context, define the concept of R-squared and interpret it.

) Need for Dynamic Panel Data Models

Generalised-ARCH model

Justify the need for Autoregressive Conditional Heteroscedasticity (ARCH) model. Explain how you would carry out a test for ARCH effect in a data set.

 For what purpose is the Box-Jenkins methodology used? Write down the steps of the above method.

What is meant by dynamic model? Explain how the following model can be estimated?
y_t = α + βx_t + γy_{t-1} + u_t
where |γ| < 1 and u_t = ρ u_{t-1} + ε_t. In the above model ε_t is the usual stochastic error term with mean zero and variance σ^2 and |ρ| < 1.

 What is the underlying idea behind the logit model? Explain how the parameters of the logit model can be estimated by maximum likelihood method.

 What is meant by dynamic model? Explain how the following model can be estimated?

What is the underlying idea behind the logit model? Explain how the parameters of the logit model can be estimated by maximum likelihood method.

Distinguish between weak stationarity and strong stationarity. Explain the methods of testing for stationarity in a univariate time series model.

Explain how the first equation in the above model can be estimated.

In the following two-equation system check the identification status of both the equations.

What is meant by identification problem in a simultaneous equation model?

What is meant by identification problem in a simultaneous equation model?

 Derive the conditions of optimality for buying health insurance in cases of absence/presence of free riders.

 Derive the conditions of optimality for buying health insurance in cases of absence/presence of free riders.