[25 points) This question is an introduction to the topic of Instrumental 1vrariable regression. which we will cover in the last few lectures of the course. You will be able to answer this question even if we still haven't talked about this topic in class. In this question we are going to estimate the effect of having more than two children on women's labor supply. We will use a dataset from the Stock and Watson textbook called the \"Fertility\" data. You can find the data on the Brightspace; the \"Fertility STATA\" file can he opened directly in STATA or you can copy and paste the data from the \"Fertility Excel\" file in STATA. The dataset contains information on married women aged 21-35 with two or more children; the data were obtained from the 198i} ILS. lCensus. Check the \"Fertility Description\" file on the Brightspace for a description of the variables [please note that our data only includes a subset of those variables. as I dropped some of those that we are not going to use}. We are interested in studying women who are past the early stages of their career. so we are going to focus only on those who are 3'.) years or older. To drop the women who are younger than 3f] Irom the sample type in STATE: drop if agemicaf}. You can now type in STATA: sum to get some sunnnary statistics about your variables. In all your answers to the questions below1 you can round the results to 3 decimal points. a. (5 points} 1We are interested in studying the impact of having more than two children on the labor supply of women. We decide to consider the following model: meeksnn = :3\" + i'ilrrioreiridsi + i'igcgemi + u!- [1} In this regression+ the variable age-m,- is included to control for the age of the woman. but we are not interested in the parameter :32. Estimate the regression using {lLf-l with heteroskedasticity robust standard errors. Based on yotu' results1 predict the difference in the number of weeks worked by two women of the same age. one with two children and the other one with more than two children. Provide a 95% condence interval for this difference. Show your work.