Measurement Errors and Instrumental Variables Measurement errors and instrumental variables are two important topics in econometrics that are closely relate...
Measurement Errors and Instrumental Variables
Measurement errors and instrumental variables are two important topics in econometrics that are closely related.
Measurement Errors:
Measurement errors occur when the true value of a variable is unknown and is estimated instead. This can happen for various reasons, such as human error in data collection, sampling bias, or measurement instruments malfunctioning.
Instrumental Variables:
An instrumental variable is a variable that is highly correlated with the dependent variable but is not directly related to the independent variable. This can happen when the dependent variable is influenced by factors that are correlated with both the independent and dependent variables.
Violations of the Classical Assumptions:
Measurement errors and instrumental variables can lead to biased and inefficient estimates of regression coefficients. This is because these errors can bias the estimated coefficients, leading to inconsistent results.
Examples:
Suppose we are estimating the relationship between education and income. However, there is a measurement error in the education variable, which leads to an underestimate of the true relationship.
Consider an instrumental variable such as family wealth. If family wealth is highly correlated with education, it can act as an instrumental variable, leading to an overestimate of the coefficient of education.
Consequences of Measurement Errors and Instrumental Variables:
Biased and inefficient estimates can lead to inaccurate conclusions about the relationship between variables.
This can result in misleading economic policy decisions and inaccurate predictions of future outcomes