Pick one of the following projects. Your written report for this project should be approximately 2-4 typed, double-spaced pages with 1-4 tables and/or graphs. You are tackling issues that could take up many more pages than you are given, so spend time on making your report concise and to the point. Think of your report as being prepared for either the Mayor of Cincinnati (Project A) or the Commissioner of Baseball (Project B), who will have at most 10 minutes to read it. All necessary data/information for each project is available on the blackboard course site.
PROJECT A: You are working for the Mayor of Cincinnati who has received pressure from the African American community to address perceived employer discrimination in the city. The mayor’s office has provided you data collected from surveys of male heads of households living in Cincinnati, including data on earnings, schooling, age, and race. Use this information to get some sense of the extent of wage discrimination against African Americans in community of Cincinnati. In particular, your report should address the following issues:
1) Use descriptive statistics (averages, medians, etc) to show that the wages and attributes of African American men differ from other racial groups. Explain what might account for the observed differences.
2) Discuss how basic descriptive statistics might misrepresent the extent of wage discrimination and how wage regressions might be used to remedy some of these shortcomings.
3) Explain what variables might be included in a wage regression and why.
4) Discuss the results of wage regressions and what the results are consistent with economic expectations. Explain whether these results consistent with wage discrimination and whether any other factors might account for the observed findings.
5) Use the information provided in 1) through 4) to explain whether you believe wage discrimination is present in Cincinnati. Is there any data that are not included in the Census data that might help you distinguish between discrimination and other competing hypotheses for the observed racial wage differential?
Some information regarding some of the variable definitions:
- married = binary variable that equals 1 if person is married.
- no_children = binary variable that equals 1 if person has no children in household.
- african_american = binary variable that equals 1 if person is African American and 0 if white (note: all other minority groups have been dropped from the data).
- blue_collar = binary variable that equals 1 if occupation is blue collar.
- service = binary variable that equals 1 if occupation is in service sector.
- government = binary variable that equals 1 a government worker.
PROJECT B: You are working for Rob Manfred, the Commissioner of Baseball, who is concerned about the lack of African American coaches in baseball. He has provided you data on all position players who began their baseball career over a fifteen year period. The data include information such as the player's: batting statistics, length of career in the majors and minors, and whether the player is African American. He is interested in the role race plays in determining the likelihood a player becomes a coach. In particular, the report must include the following five key elements:
1) Use descriptive statistics (means, medians, etc) to show that the likelihood of coaching and the attributes of African American MLB baseball players differ from other racial groups. Explain what might account for the observed differences.
2) Discuss how basic descriptive statistics might misrepresent the extent of employment discrimination and how a regression might be used to remedy some of these shortcomings.
3) What variables might be included in a coaching regression? Why?
4) Discuss the results of coaching regressions and whether the results are consistent with economic expectations. Explain whether these results consistent with discrimination in the opportunity to become a coach and whether any other factors might account for the observed findings.
5) Use the information provided in 1) through 4) to explain whether you believe discrimination is present in the ranks of major league coaching. Is there any data that are not included in these baseball data that might help you distinguish between discrimination and other competing hypotheses for the observed racial coaching differential? Moreover, is the length of the data period appropriate or should a different period be used?
Most of the data definitions are self-explanatory. All of the variables are continuous except for: 1) the variable "coach" which is a binary variable that equals one if the player coaches; and 2) the position variables (e.g., catcher) that equal one if the player primarily played that position during his career.
Attachment:- project-a-data.xls
Attachment:- project-b-data.xls