Final answer:
The components of a regression model where wage is estimated as a function of education, experience, age, and error are the y-intercept, coefficients for each independent variable, and the error term.
Step-by-step explanation:
The regression model where wage is estimated as a function of education, experience, age, and error can be represented as:
wage = a + b1 * education + b2 * experience + b3 * age + error
Here, 'a' represents the y-intercept, which is the baseline wage for workers with zero education, experience, and age. The coefficient 'b1' represents the change in wage for each unit increase in education, 'b2' represents the change in wage for each unit increase in experience, and 'b3' represents the change in wage for each unit increase in age.
Additionally, 'error' represents the random variation or unexplained factors that affect a worker's wage, which cannot be accounted for by the independent variables.