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Department of Economics and Statistics Karlstad University Jari Appelgren Assignment 2 Comparing Qualitative Response Regression Models Applied Econometrics (NEK) & Econometrics B (STAT) For this assignment we will use a subset of a data set, Table 15.27, from the textbook website. NOTE! To make the analyzes more interesting the data has been changed compared to the original on the website. Because of limitations on “Kurstorget” the file is renamed to '.doc' and can be imported into STATA by File > Import > 'ASCII data created by spreadsheet', use Browse to find file, and click OK. The assignment is based on exercise 15.19 from the textbook, and is originally about 2000 women where six variables are used; county, work, age, marital status, number of children, and education. Note that the data set from the website include more variables and more cases than this subset. The assignment is about using the data to estimate three separate models; the linear probability model, the logit model, and the probit model, and to evaluate which of these models you would consider appropriate choice for the data. Part 1 – The Linear Probability Model Estimate a linear probability model and decide on a suitable set of variables that are statistically useful for this model. Explain the parameter estimates and their effect in terms of the probabilities that they estimate. Important that you explain all the problems that are found in the process and how you have solved them. Also finally investigate the final estimated model and comment on any problems that are still evident. Part 2 – The Logit Model Estimate the model according to the Logit form, and find the statistically useful variables. Considering the previous part of the assignment, comment on which variables is significant compared to previous results. Explain the estimates and any problems with the final model. Department of Economics and Statistics Karlstad University Jari Appelgren Part 3 – The Probit Model Same procedure as in parts 1 and 2, but use the Probit form in this case. Explain the difference between Logit and Probit in words and any differences in assumptions and results. Are the results surprising compared to part 2? Optional assignment (only if you are interested) In the Logit model, or more usually logistic regression, the term LD50 is usual (specifically in Medical applications considering the abbreviation LD). Investigate this term and explain it's meaning and how it's related to the estimates in a simple logistic regression with only one independent variable. In our situation there are more than one independent variable, so a bit more difficult to use the same reasoning as for one independent variable. Consider how you might be able to get similar information from this data set. Note that you can either consider all or one at a time, depending on your choice perspective to this problem. Why is the value 50 so interesting in these situations? Please explain. General instructions In each part of the assignment you are required to find a final model. You can consider two ways; by entering or by removing variables from the model based on significance. At least one of Part 1, 2, and 3, should be done by entering or by removing variables. Explain criteria that you use for each method. Please include at least a minimum of output and/or values from the steps used in each part of the assignment, so that is will be simple to follow the choices made along the way. The final models must be included in full from STATA. Also include some diagnostics about the model. The assignment must be turned in at latest the week before the main examination of the course, and place in one (Nationalekonomi / Statistik) of the department postboxes in the begin of the 11C200-corridor. The assignment should be done in groups of up to three students (or alone) and with the name of the assignment and participants' codes clearly on a front page of the assignment. Jari Appelgren 2012-09-10