# Econometrics [ISS (Statistical Services) Statistics Paper III]: Questions 1 - 5 of 34

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## Question number: 1

» Econometrics » Heteroscedastic Disturbances

Appeared in Year: 2015

### Describe in Detail

Describe the problem of heteroscedasticity in linear regression model. Outline one method for overcoming this problem.

### Explanation

In the linear regression model, the assumption of variance of the error term is constant for all values of the independent variables does not hold, we face the problem of heteroscedasticity. This leads to unbiased but inefficient estimates that is large than minimum variance. Furthermore, the estimated variances of the parameters are biased, leadin

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## Question number: 2

» Econometrics » Simultaneous Linear Equations Model

Appeared in Year: 2015

### Describe in Detail

Describe the two-stage least squares (2SLS) procedure for structural estimation in a simultaneous equations model. Show that it coincides with indirect least square method when the equation is exactly identified.

### Explanation

Most of the economic theory is built upon system of relationship. We will consider various estimation procedures for the system of simultaneous equation models. One of the estimation is two-stage least squares is to purify the stochastic explanatory variable Y _{1} of the influence of the stochastic disturbance u. This goal is accomplished by performi

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## Question number: 3

» Econometrics » Autoregressive Linear Regression

Appeared in Year: 2015

### Describe in Detail

Write down the auto correlation function of order k. For an AR (1) model X _{t} =0.7X _{t-1} +ϵ _{t}, where {ϵ _{t}} is a white noise process. Show that this model can be expressed as a moving average process of infinite order. Check the model of stationary.

### Explanation

Autocorrelations are measures of dependence between variables in a time series. Suppose that Y _{1}, Y _{2}, …, Y _{n} are square integrable random variables with the property that the covariance

of observations with lag k does not depend on t. Then

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## Question number: 4

» Econometrics » Ordinary Least Squares (OLS)

Appeared in Year: 2015

### Describe in Detail

Describe in detail Indirect Least square method for estimating structural parameters. Is the estimator unbiased and/or consistent?

### Explanation

For a just or exactly identified structural equation, the method of obtaining the estimates of the structural coefficients from the OLS estimates of the reduced-form coefficients is known as the method of indirect least squares (ILS), and the estimates thus obtained are known as the indirect least squares estimates. ILS involves the following three

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## Question number: 5

» Econometrics » Auto-Correlation

Appeared in Year: 2015

### Describe in Detail

Describe exact and near multicollinearity in a regression model. Discuss, along with justification, the effect of these situations on (i) sampling variation and (ii) prediction.

### Explanation

Multicollinearity refers to the existence of a perfect or exact linear relationship among some or all explanatory variables of a regression model. So, there are two types of multicollinearity. They are

1. ** Exact Multicollinearity:** If exist perfect linear relationship among the explanatory variables then it is treated as exact multicollinearity. In c

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