ubermore notes by Mike Williams
RSSA simple example of a relationship in econometrics from the field of labor economics is: \ln(\text{wage}) = \beta_0 + \beta_1 (\text{years of education}) + \varepsilon. Economic theory says that the natural logarithm of a person’s wage is a linear function of (among other things) the number of years of education that person has acquired. The parameter β1 measures the increase in the natural log of the wage attributable to one more year of education. The term ε is a random variable representing all other factors that may have direct influence on wage. The econometric goal is to estimate the parameters, β0 and β1 under specific assumptions about the random variable ε. For example, if ε is uncorrelated with years of education, then the equation can be estimated with ordinary least squares.
About ubermore notes by Mike Williams
