BECC-110 Introductory Econometrics Solved Assignment 2024-2025
Course Code: BECC-110
Assignment Code: ASST/BECC 110/ 2024-25
Total Marks: 100
Title Name | BECC-110 Solved Assignment 2024-2025 |
University | IGNOU |
Service Type | Solved Assignment (Soft copy/PDF) |
Course | BAG(Economic HONOURS) |
Language | ENGLISH |
Semester | 2024-2025 Course: BA(Economic HONOURS) |
Session | July 2024 and January 2025 Admission cycle |
Short Name | BECC-110 |
Assignment Code | ASST/BECC 110/ 2024-25 |
Product | Assignment of BAG(Economic HONOURS) 2024-2025 (IGNOU) |
Submission Date | July Cycle: 30 April January Cycle: 31 October |
Assignment I
Answer the following Descriptive Category Questions in about 500 words each. Each question
carries 20 marks. Word limit does not apply in the case of numerical questions. 20 x 2 = 40
1) Specify a multiple regression model. Point out the assumptions about the error term. Describe
how the parameters of the model can be estimated by maximum likelihood method.
2) What is meant by autocorrelation? Describe the reasons for the presence of
autocorrelation in regression model. What are the consequences of autocorrelation?
Assignment II
Answer the following Middle Category Questions in about 250 words each. Each question
carries 10 marks. Word limit does not apply in the case of numerical questions. 10 x 3 = 30
3) Explain why an error variable is added to the regression model. Distinguish between
the error term (u) and the residual ( ).
4) Which assumption is violated when there is heteroscedasticity in dataset? Describe
any three methods of detection of heteroscedasticity.
5) Explain the impact of measurement error in independent variable of a regression
model.
Assignment III
Answer the following Short Category Questions in about 100 words each. Each question carries
6 marks. 5 x 6 = 30
6) What are properties that a good estimator should satisfy?
7) Distinguish between
and adjusted-
.
8) Describe the remedial measures for the presence of multicollinearity in a multiple
regression model.
9) Interpret the parameters in a log-linear regression model.
10) Write a short note on regression through the origin.
BECC-110, BECC 110 BECC110,
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