# Econometrics (ISS Statistics Paper III): Questions 12 - 18 of 21

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## Question number: 12

» Econometrics » Autoregressive Linear Regression

Appeared in Year: 2011

Essay Question▾

### Describe in Detail

For the auto-regressive scheme , show that if e is a random variable and the series is long, then

and hence show that, variance of the generated series may be much greater than that of e itself.

### Explanation

Given auto-regressive scheme is a second order Auto-regressive series.

……………. . (i)

Since the series is long and , we have

and Var

Squaring both sides of (i) and taking the expectations, we get

…………. . (i)

Multiplying both sides… (66 more words) …

## Question number: 13

» Econometrics » Ordinary Least Squares (OLS)

Appeared in Year: 2012

Essay Question▾

### Describe in Detail

Discuss the practical consequences of autocorrelation. Show that

### Explanation

Practical consequences of autocorrelation:

1. OLS estimators are still unbiased and consistent.

2. The variance of the estimators are underestimated. In the presence of autocorrelation , but Thus, variance of may be either over estimated or under estimated depending upon the nature of the correlation.

3. Prediction will be… (175 more words) …

## Question number: 14

» Econometrics » Ordinary Least Squares (OLS)

Appeared in Year: 2012

### Write in Short

If the demand curve is of the form , where p is the price and x is the demand, prove that the elasticity of demand is · Hence deduce the elasticity of demand for

## Question number: 15

» Econometrics » Prediction and Simultaneous Confidence Intervals

Appeared in Year: 2012

### Write in Short

Discuss forecasting accuracy and Theil’s U coefficient.

## Question number: 16

» Econometrics » Autoregressive Linear Regression

Appeared in Year: 2012

### Write in Short

Obtain the general solution of first-order auto-regression model.

## Question number: 17

» Econometrics » Autoregressive Linear Regression

Appeared in Year: 2013

Essay Question▾

### Describe in Detail

Obtain the complementary function and particular integral of first order regressive model. Show that is a moving average of random elements with weights,

### Explanation

Let us consider the first order auto regressive model

……. . (i)

this is a linear difference equation of order 1. its complementary function (C. F. ) is the so; ution of

which is a homogeneous linear difference equation of order 1.

if is the trial solution,… (117 more words) …

## Question number: 18

» Econometrics » Ordinary Least Squares (OLS)

Appeared in Year: 2012