I have a project and I need help with the writing. I have the data and the SPSS regression

Econometrics Project

You will choose a research question to address using economic reasoning and multiple linear regression analysis. Remember that your dependent variable must be continuous and you must have two or more independent variables, one of which must be continuous. Your data set must have a minimum of 30 observations. You will present your research both in writing as a formal research paper and as an oral presentation to the class. You may not use problems or examples from statistics or econometrics textbooks or websites as the basis of your project (I will recognize them).

Your research paper must follow this format and use these subheadings:

1. Abstract:

One paragraph summary of project. Must be ≤ 250 words.

2. Introduction:

Explain to the reader what the topic is and why it is interesting and important. Tell reader what this project will do and how it could be useful. This is the time to get the reader interested and convince her/him to read on!

3. Literature Review:

Briefly summarize the academic work related to your topic. What are the basic findings to date and what are the shortcomings or limitations of previous studies? How is your paper different - how does your work fit into the literature? You need at least 3 academic references. In discussing the literature be sure to evaluate the quality of the quantitative argument in each paper cited (strengths and weaknesses). DO NOT organize the literature by article (paragraph about the first article, paragraph about the second article and so on). Instead organize the literature review by a theme such as data used (paragraph about findings based on time series data, paragraph about findings based on cross sectional data) or findings (paragraph about papers that find evidence to support model, paragraph about papers that did not find evidence to support model). The goal is to synthesize the information from the articles you read and explain the patterns and meaning to the reader.

4. Theory:

Present a logical explanation based on economic reasoning of how you think the dependent variable is determined, noting links to the existing literature. What are all the relevant independent variables that could help explain variation in Y and how, specifically, is each expected to be associated with Y (positive or negative)? This is where your understanding of economic theory will be used. Explain your model verbally and illustrate it graphically (e.g., a supply & demand, IS-LM). You may draw theoretical graphs by hand as long as they are neat and clear. After explaining your theory verbally and graphically, summarize your model's implications, i.e. if your model is correct what will be the signs (+/-) of the slopes of your independent variables? Close this section with an equation that represents your theoretical model.

5. Methodology:

Explain how you collected the sample, noting the type of data set (time series or cross sectional) and the sample size. Then explain how each variable in your theoretical model is measured (operational definitions). For example, if one regressor in your theory is money supply, you must explain which measure of money supply (M1, M2, etc.) you use and why. In your operational definitions also make clear the units of each variable (dollars, thousands of dollars) and the type of variable (continuous, discrete, nominal or ordinal).

Present the basic descriptive statistics for each variable in a table and discuss them. The actual data do not belong in the body of the paper; rather they belong in a separate SPSS file to be uploaded along with your paper. Conclude this section with an equation summarizing your econometric model and a summary of the signs your theory predicts for each slope (testable hypotheses).

6. Results:

Report your regression results in tables created by cutting and pasting the relevant SPSS output into your Word document into the body of your paper. If there are regressions run, but not reported in the body of your paper (e.g. Park test regressions), refer the reader to the output appendix to see all the regression results. Be specific where exactly to find the referenced output - page number or appendix A, B, C etc. Carefully examine the regression for signs of CLRM assumption violations. If you find evidence of a violation, take the appropriate remedial action and report and evaluate your revised regression. Once you have addressed all CLRM assumption violations, then use your final regression results to: comment on how well the regression works overall; interpret each of the estimated parameters and test each for statistical significance (2-tailed tests); and test your model's specific implications (1-tailed tests).

7. Summary and Conclusions:

Summarize what your paper has done. Comment on how well your theory works overall. Note the limitations of your model. If your theory didn't work all that well, explain what might have gone wrong (e.g., you couldn't find data on a variable the theory indicated was relevant). Explain what you would do differently in future research on this topic (avenues for future research).

8. Data Appendix:

Present the sources for the data on each variable (use table format). Make sure you cite your sources completely.

9. Regression Output Appendices (A, B, C ....):

Include copies of all the SPSS output referenced in your paper, but not reported in the body of the paper (e.g., regressions used in testing CLRM assumptions). Label them appropriately.

10. References:

Alphabetically (by author's last name) list all sources of material used in the body of your paper (e.g., papers cited in your literature review). Follow MLA or APA style. In the body of the paper cite academic material using the author(s) and date method.

Attachment:- Project Assignment.rar