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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 ;
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1. Explain why econometricians must know and understand the classical
linear regression assumptions. (4)
The Importance of Understanding Classical Linear Regression Assumptions in
Econometrics
Econometrics is a critical field that allows economists, statisticians, and social scientists to
analyze and interpret data using quantitative methods. Among these methods, regression
analysis, particularly linear regression, stands as one of the most frequently used tools. Linear
regression enables the estimation of relationships between dependent and independent variables,
helping economists make predictions, test theories, and understand underlying data structures.
However, to ensure the validity of these estimations and conclusions, econometricians must be
familiar with and adhere to a set of underlying assumptions known as the classical linear
regression model (CLRM) assumptions.
The importance of these assumptions lies in the fact that they create the foundation for the
reliability and accuracy of regression models. Without understanding and satisfying these
assumptions, econometric models may yield biased, inconsistent, or inefficient estimates, leading
to misguided inferences and policy recommendations. Therefore, it is essential to explore the
reasons econometricians must understand these assumptions and the potential consequences of
violating them.
Overview of the Classical Linear Regression Model Assumptions
The classical linear regression model consists of several key assumptions that ensure
the estimators derived from ordinary least squares (OLS) are unbiased, efficient, and
consistent. These assumptions are:
1. Linearity in Parameters: The relationship between the dependent and
independent variables is linear in parameters. This does not imply that the
variables themselves must be linear but rather that the equation takes the form
of a linear combination of parameters.
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