2. In Table 2 you find estimation results of wage regressions using data from Austria from the years 2004 until 2006.Five specifications are estimated. The dependent variable is the logarithm of the hourly wage. The first specification includes a dummy that is one for females and zero for males as well as year dummies, then years of education, years of experience and years of experience squared, dummy variables for occupations, and dummy variables for industries are sequentially added.

i)Write down the regression model for the fifth specification. Explain why we add the various variables to the regression model. Describe and explain the estimated coefficients of female in all specifications. Are the coefficients significantly different from zero? Why? What does the estimated coefficient of female mean? Why does the estimated coefficient of female change when adding additional explanatory variables? What are the reasons why the coefficient becomes smaller in absolute terms when adding additional explanatory variables? Comment on the estimated coefficients for education and experience in specification (5). Are the coefficients significantly different from zero? Why? What do the estimated coefficients of education and experience mean? Comment on the R-squared in all specifications.