Econometrics Spring 2020
Economists are often involved in collecting, processing and analyzing data. Perhaps an economist’s greatest contribution to his/her work place is his/her ability to formulate a hypothesis on how markets and/or individuals behave, test the hypothesis, and then discuss the implications of the investigation.
Your assignment is to use the Survey of Consumer Finances to test one or more hypothesis. https://www.federalreserve.gov/econres/scfindex.htm
The following paragraph describes the data set:
“The Survey of Consumer Finances (SCF) is normally a triennial cross-sectional survey of U.S. families. The survey data include information on families’ balance sheets, pensions, income, and demographic characteristics. Information is also included from related surveys of pension providers and the earlier such surveys conducted by the Federal Reserve Board. No other study for the country collects comparable information. Data from the SCF are widely used, from analysis at the Federal Reserve and other branches of government to scholarly work at the major economic research centers.”
Here are some questions that can be addressed using this data source.
Who has a checking account? How is the likelihood of having a checking account a function of income? Age? Wealth? Owning stocks?
Same type of questions for owning a house? A vehicle?
What’s the relationship between education and the number of children that a person has?
What’s the increase likelihood that you read a financial newspaper or magazine if your assets are 10,000? 1,000,000? How do your sources for financial advice affected by income? Wealth?
What percentage of the sample own equity? Bonds? How do you explain the variation? Is it strictly due to total assets? Age? Does race matter?
For a given level of income and age, do homeowners have more or fewer financial assets? Do people who forego owning a home use the freed-up cash to investment more in the market?
Variable definitions can be found at https://www.federalreserve.gov/apps/scfcb/
and the Net Worth Flowchart found at https://www.federalreserve.gov/econres/scfindex.htm
One way of getting a variable definition is to go to https://www.federalreserve.gov/econres/files/bulletin.macro.txt
to obtain the SAS variable name equivalent for the Stata variable name. For example, if you start with the Stata variable educ, you will see in this txt file that its SAS equivalency is X5931. If you go to https://www.federalreserve.gov/apps/scfcb/
you will obtain the following definition of X5931.
RECORD THE HIGHEST LEVEL OF EDUCATION COMPLETED, NOT THE
TIME IT TOOK TO COMPLETE IT. DO NOT INCLUDE TRADE SCHOOLS
-1. Less than 1st grade
1. 1st, 2nd, 3rd, or 4th grade
2. 5th or 6th grade
3. 7th and 8th grade
4. 9th grade
5. 10th grade
6. 11th grade
7. 12th grade, no diploma
8. High school graduate – high school diploma or equivalent
9. Some college but no degree
10. Associate degree in college – occupation/vocation program
11. Associate degree in college – academic program
12. Bachelor’s degree (for example: BA, AB, BS)
13. Master’s degree ( for exmaple: MA, MS, MENG, MED, MSW, MBA)
14. Professional school degree (for example: MD, DDS, DVM, LLB, JD)
15. Doctorate degree (for example: PHD, EDD)
As a second example, https://www.federalreserve.gov/econres/files/bulletin.macro.txt tells me that wageinc is equivalent to SAS X5702. https://www.federalreserve.gov/apps/scfcb/ tells me that this variable is wage income.
If I wanted to present wage income by education, I could do the following:
by educ: sum wageinc [w=wgt]
I can also run a regression of wageinc on educ. I would need to convert educ to separate dummy variables.
reg wageinc i.educ [w=wgt]
results in an error message:
educ: factor variables may not contain negative values
I am going to drop observations where educ = -1 (less than 1st grade education) because the reported mean value from the sum command seems unreasonable.
drop if educ==-1
reg wageinc i.educ [w=wgt]
https://www.stata.com/support/faqs/data-management/creating-dummy-variables/ provides good guidance on creating dummy variables. For example, here’s how I create dummy variables for all of the values of educ:
tabulate educ, generate(educ)
My Stata output is a bit clearer with the educ# values:
reg wageinc educ* [w=wgt]
The data set can tell us how many households have zero or negative assets:
sum networth [w=wgt] if networth <=0
We can use a compound if statement too, such as
sum networth [w=wgt] if networth <=0 & educ==13
The variable race tells us if the person is
1 white non-Hispanic
2 Black or African-American non-Hispanic
3 Hispanic or Latino
5 Other or Multiple race
We could identify the number of Hispanic households with networth <=0
Many of the dummy variables are 1,2 rather than 0,1. This can be rectified with a simple replace command.
Married = 2 if a person is not married nor living with partner
Married = 1 if married or living with partner
replace married =0 if married ==2
reg wageinc educ* age married kids i.race [w=wgt], robust
To complete the project, you must carry out the following tasks:
Your paper must be submitted electronically through Turnitin. Turnitin is a program available through Blackboard (in the content/project folder). I will use Turnitin to check for plagiarism. Plagiarism is a violation of the Queens College academic standards and policy and will not be tolerated.
You should include in the paper a presentation of the descriptive statistics associated with this data set and a discussion of what the values imply.
Your paper is due December 10, 2020.
A student-writing sample is available on Blackboard.
The data for your paper is available on Blackboard. The data is in Stata format.
I have established a discussion board on Blackboard so that you can discuss the paper with your peers. Please post any questions that you may have about the project on Blackboard and let me know that you have posted a question).
Often prospective employers ask for a writing/research sample. You should put considerable effort into this project as you will be able to use the paper to illustrate your analytical and writing skills.
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