**Sargodha University MA Economics Paper-VIII Econometrics Theory and Application Past Papers 2017**

Here you can download Past Papers of Paper-VIII Econometrics Theory and Application, MA Economics Part Two, 1st & 2nd Annual Examination, 2017 University of Sargodha.

**Econometrics Theory and Application UOS Past Papers 2017**

**M.A. Economics Part – II**

**Paper-VIII(Econometrics)**

**1 ^{st} Annual Exams.2017**

**Time: 3 Hours Marks:100**

**Note: Objective part is compulsory. Attempt any four questions from subjective parts**

__Objective Part__

**Q.1:Write short answers of the following on your answer sheet in two lines only. (2*10)**

- What are ingredients of econometric model?
- Differentiate between mathematical economics and econometrics.
- Why we estimate standardized coefficients.
- What is the format of ANOVA TABLE?
- How can you define the problem of perfect multicollinearity?
- What are the consequences of heteroskedasticity for OLS estimation?
- How can you evaluate the forecasting power of a model?
- List out the causes of coefficient variation.
- Which tests can be used for identifying restrictions?
- What is cointegration?

__ ____Subjective Part__

**Q.2:** (a) Define econometrics and discuss its scope in detail.

(b) Explain methodology of econometric research by discussing the stages of specification, estimation, evaluation and forecasting.

**Q.3:** By using the following data, estimate appropriate model and test individual significance of parameters at 5% level of significance. Do the data support the existence of Phillips-Curve relationship (negative relationship between % change in wage rate and unemployment rate)

% Change in wage rate |
5.0 |
3.2 |
2.7 |
2.1 |
4.1 |
2.7 |
2.9 |
4.6 |
3.5 |
4.4 |
4.0 |
7.7 |
5.7 |
9.5 |

Unemployment % |
1.6 |
2.2 |
2.3 |
1.7 |
1.6 |
2.1 |
2.6 |
1.7 |
1.5 |
1.6 |
2.5 |
2.5 |
2.5 |
2.7 |

**Q.4:** (a) What are the major causes of autocorrelation in a time series data.

b. Following residuals are estimated for a certain relationship. Apply an appropriate test to detect autocorrelation at 1% level of significance.

Sr. No. |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
10 |

Residual |
1 |
-1.5 |
-0.7 |
-1.3 |
-4.65 |
-0.3 |
-3.1 |
-5.5 |
-4.7 |
-1.3 |

Sr. No. |
11 |
12 |
13 |
14 |
15 |
16 |
17 |
18 |
19 |
20 |

Residual |
4.6 |
4.3 |
1.9 |
1.9 |
2.9 |
2.6 |
-2.3 |
0.9 |
1.4 |
3.7 |

**Q.5:** By considering the following model:

W_{1} = *a*_{1} + *K*_{t} + U_{1}

K_{t} = *β*_{1} *w*_{t} + *β*_{2}X_{t} + U_{2}

Prove that α_{1}(ILS) = α_{1}(2SLS)

**Q.6:** By considering the repression model:

Y_{t+1} = *a* + *β*X_{t+1} + et+_{1}

Find mean and variance for un-conditional forecasts when

*a*is estimated, β is known*a*is known and β is unknown

**Q.7: **Write note on the following

- Detection on the following.
- Recursive equation system.

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