Processing and Analyzing Data

Economists are often involved in collecting, processing and analyzing data. You must have the topic in part 1.
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.
Let’s work on Part 2:
Have you established the correlation coefficient determination of the topic?
Is the correlation positive when y tends to increase and negative when y tends to decrease?
Does the preciseness of the shift in y as x increases determine the strength of the linear correlation?
Is the coefficient of linear correlation, r, (the numerical measure of the strength of the linear relationship between two variables) well established?
a) Have you already established linear functional forms (Single/Multiple regression) Single Linear regression: Y = a + bX + u (PLUG IN Y & X VARIABLES & RESIDUALS)
Multiple regression: Y = a + b1X1+ b2X2 + b3X3 + … + btXt + u ( PLUG IN THE REGRESSORS e.g b1 x1, b2, x2, ….)
FOR EXAMPLE: for the topic on ‘Mortgage & Race’
Minorities are more likely to be denied a home mortgage than whites. Is this the result of racism, or are there other plausible explanations? If the financial standing of minorities and whites are different, it is possible that the higher rate of mortgage denial is due to risk, rather than prejudice. The purpose of your paper should be to econometrically estimate the factors that explain the variation in mortgage approval rates.

To complete part 2 of the project you must carry out the following tasks:

1. Formulate a hypothesis regarding the relationship between three or more economic variables. When you formulate your hypothesis, think seriously about what you have learned in your economic theory classes.

2. Plot the data that you will use in your regression and use the graphs to suggest a functional form (e.g., linear, log-linear, or quadratic).

3. Summarize descriptive statistics analysis.

4. Estimate the coefficients.

5. Plot the residuals. Are the residuals consistent with the assumptions of classical regression? If not, can you modify the model so that the residuals are consistent with the assumptions?

6. Conduct hypothesis tests.

7. Write a five to nine page paper. The format of the paper can be either a short paper or a memorandum. The paper should include:
a. A description of the issue that you are analyzing.
b. State the hypothesis that is being tested.
c. Report your estimation results.
d. Report the results from your hypothesis test. Include at least one hypothesis test where you are testing if two or more variables, but not all slope coefficients, are equal to some value (e.g., zero).
e. Discuss the implications of your results. What are the policy implications of your research?
8. Use a grammar utility program to check your sentence structure and spelling.

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