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Regression analysis on Unemployment Duration

Layoffs and unemployment have affected a substantial number of workers in recent years. Assume the Bureau of Labor Statistics (BLS) collected data for 50 displaced workers in the Houston area in September 2011. These data are available on the course website within the ââ?¬Å"Case Studyââ?¬Â? icon. The dependent variable (WEEKS) was defined as the number of weeks a worker has been jobless due to a layoff. The data set contains different variables that may be related to the number of weeks a worker has been jobless:

MAN : A dummy variable: 1 if a man, 0 if a woman
AGE :Age, years
EDUC : Completed education, years
MARRIED : A dummy variable: 1 if married, 0 otherwise
HEAD : A dummy variable: 1 if the head of household, 0 otherwise
TENURE : The number of years on the previous job
MGT : A dummy variable: 1 if management occupation, 0 otherwise
SALES :A dummy variable: 1 if sales occupation, 0 otherwise

Suppose that you have been hired by the Bureau of Labor Statistics to analyze the data for a presentation to be made at the BLS annual conference in Houston. Use the methods presented in this course (descriptive statistics, regression analysis, hypothesis testing, etc.) to analyze this data set.
For present purposes, consider a linear regression model, that is, a linear regression of WEEKS on different socio-economic characteristics described above. (A duration model may be a better method to analyze these data, but it is beyond the scope of this course.)
Learning Objective: In attempting the assignment, students are expected to apply concepts, tools and techniques introduced during the course to a real world situation. (Individual case study assessing course Learning Objective 6.)

Present a summary of your analysis, key statistical results, conclusions, and recommendations, in a research report. At the very least, in your report you should:
Provide a clear and concise statement of the problem. The place to start your report is with a summary of the questions you have investigated, why they are important and who should be interested in the results.
Develop numerical and graphical summaries for the data.
Provide descriptive statistics for each variable in the data set.
Make comments and interpretations based on these descriptive statistics.
What new insights do these descriptive statistics provide concerning the duration of unemployment?
Present any additional graphical and numerical summaries that will be beneficial in communicating the data to others.
Use regression analysis to investigate the relationship between the duration of unemployment and different socio-demographic characteristics of the unemployed.
Specify the statistical model that you used, define and discuss the economic variables in the model and the functional form of the model.
Describe the estimation method you used.
Comment on the goodness of fit.
Report the parameter estimates, their interpretation, and values of test statistics. Use the t-test to determine the significance of each independent variable.
Use the F-test to determine the overall significance of the relationship.

Conclude and recommend. What conclusions and recommendations can you derive from your analysis? What are economic implications?