Question

While estimating a regression model you found that the explanatory variable is measured with certain error. Specify the model. What are its consequences on the parameters?

20 Feb 2025
Answer :
Word Count : 596

In econometrics, when an explanatory variable in a regression model is measured with error, it leads to what is known as measurement error or errors-in-variables (EIV) problem. This issue arises when the observed independent variable does not perfectly reflect the true variable, leading to biased and inconsistent parameter estimates.

Specification of the Model

Consider the standard simple linear regression model:

Yi=β0+β1Xi+uiY_i = \beta_0 + \beta_1 X_i + u_i

where:

  • YiY_i is the dependent variable,
  • XiX_i is the true (but unobserved) explanatory variable,
  • uiu_i is the error term, and
  • β0\beta_0 and β1\beta_1 are the parameters to be estimated.

However, suppose XiX_i is not observed directly. Instead, an error-ridden version of it, Xi∗X_i^*, is observed:

Xi∗=Xi+νiX_i^* = X_i + ____ _________ __________ _____ ___ ______ ___ ____ _________ _______ ______ _____.
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