Description
MECE-101: INTRODUCTORY ECONOMETRIC METHODS
Assignment Course Code: MECE-101
Asst. Code: MECE-101/AST/2025-26
MASTER OF ARTS
(ECONOMICS)
ASSIGNMENTS 2025-26
Fourth Semester Courses
(For learners appearing in term-end exams in June
2026 and December 2026 Sessions)
Maximum Marks: 100
Note: Answer all the questions. While questions in Section A carry 20 marks each, those in Section B carry 12 marks each.
Section A
- 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.
2.The relationship between Y and X is given by 𝑦𝑖 =∝ +𝛽𝑥𝑖 + 𝑢𝑖 where 𝑢𝑖 follows classical assumptions. Consider the following set of data and answer the questions. Y 11 12 13 X 18 16 14 15 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.
Section B
- Explain the concept of identification in a simultaneous equations model. Why is it called the paradox of identification?
4.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).
5.What is meant by multicollinearity? What are its consequences on estimates? What remedial measures do you suggest for the problem?
6.Why is the OLS method inappropriate when a dataset is having heteroscedasticity problem? Explain the White’s Test to detect heteroscedasticity in a data set.
- Write short notes on the following:
- a) Lagrange-Multiplier (LM) Test
- b) Likelihood Ratio Test
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