Education, Experience and Wage Level [Final 2021] Suppose you have a cross-sectional data set of workers from census data. You want to run a regression of their salaries (Y) on the years of education (X,) and the years of working experience (Z.). Now you want to compare the wage level of workers of the same age, so you have chosen 50 workers who were born in 1986 from your census data. However, years of working experience (Z.) is not available in the data set, so you decided to use
                years of working experience (Z.) = age years of education (X.) - pre-education years. Since all the 50 persons in your observations are 36 years old (and we can assume that pre-education years is 5), this becomes                  Z₁ = 36 X₁ - 5 = 31 - X₂ You have run the GRETL program based on the following regression model                 Y₁ = ₁ + 3₂X₂ + B₂ Z₁ + C₂ ? ): 2,". and you encountered the following result and it showed an error message "Omitted due to ( There were only the values of 31 and 3₂.                 Model 1: OLS, using observations 1-50                 Dependent variable: salaries.                 Omitted due to ( ? ): 2₁                 Coefficient.    Std.        Error   t-ratio   p-value const        -6.71033   1.91416.  -3.506 0.0005     X₁           1.98029   0.136117 14.55  0.0000
(a) Fill in the blank ( ? ). (b) Explain why the program omitted the variable of years of working experience (Z.). If the model maintains Z, in the regression model, what happens?