Now consider again following regression results (t ratios are in parentheses) (10) Yi = 0 + 1 X1i +2X2i + 3X3i + 4X4i +5X5i + 6X6i +7X7i +8X8i + 9(X4*X6) +Ui where Y is dummy variable if female want to do job, then value of Y is 01 otherwise zero. X1 after-tax real average hourly earnings of wife X2 Family head after-tax real income annual X3 age in year X4 years of schooling completed X5 is an attitude variable, 1 = if respondent feel ok, 0 = otherwise X6 is again an attitude variable, 1 = if the respondents head of family favored his wifes working, 0 = otherwise X7 size of household X8 number of female members in household Suggest a technique to estimate the model and explain with a sound logic(s). and Also suggest hypothetical signs of all coefficients of regressors make economic sense? Explain one by one. and Suggest at least three methods for model diagnostics and Suggest any two or three econometric problems that you are expecting in this model with reasons. and I am very euthanistic to learn from you the role of 9 in above model. What is definition, estimation procedure, and interpretation of this parameter?