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ECS3706 Assignment 2 (COMPLETE ANSWERS) Semester 2 2024 (399706) - DUE September 2024 R50,58   Add to cart

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ECS3706 Assignment 2 (COMPLETE ANSWERS) Semester 2 2024 (399706) - DUE September 2024

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ECS3706 Assignment 2 (COMPLETE ANSWERS) Semester 2 2024 (399706) - DUE September 2024 ; 100% TRUSTED Complete, trusted solutions and explanations. For assistance, Whats-App

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  • September 13, 2024
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ECS3706
ASSIGNMEMT 2 SEMESTER 2
UNIQUE NO . 399706




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, ECS3706 Assignment 2 (COMPLETE ANSWERS)
Semester 2 2024 (399706) - DUE September 2024 ;
100% TRUSTED Complete, trusted solutions and
explanations. For assistance, Whats-App




1. Explain why econometricians must know and understand the classical
linear regression assumptions. (4)



Understanding the Classical Linear Regression Assumptions

Econometrics is a branch of economics that uses statistical methods to quantify
economic theories, test hypotheses, and forecast future trends. One of the most
fundamental tools in econometrics is the linear regression model, particularly the
Ordinary Least Squares (OLS) estimator. The effectiveness of OLS in providing
reliable and unbiased estimates is built on a set of foundational principles called
the Classical Linear Regression (CLR) assumptions. These assumptions are
essential for ensuring that the OLS estimators possess desirable statistical
properties such as unbiasedness, consistency, and efficiency. Understanding and
recognizing the importance of these assumptions is crucial for econometricians for
several reasons, as discussed below.

1. Foundation of OLS Estimator Properties

The OLS estimator is widely used because it has desirable properties when the
CLR assumptions hold. These properties are encapsulated in the Gauss-Markov
theorem, which states that, under the CLR assumptions, OLS estimators are Best
Linear Unbiased Estimators (BLUE). In simple terms, OLS provides the most

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