Data Section and Preliminary Regressions
This assignment includes two separate sections. They can be in the same document. The first section should be labeled “Data” and the second section should be labeled “Preliminary results.”
For the Data section (2-3 pages):
Please submit 2-3 pages discussing the data you are using for your project.
1. I recommend you start your data section with the following (or similar):
a. First paragraph: “To examine the relationship between {ind. var} and {dep var} I need information on…” Then explain where you get that information, or if you can’t get it, what information you use instead.
b. Second paragraph: “I rely on {insert dataset} for information on {var}.” Then go on to discuss.
2. You should spend several pages discussing your data, so be very specific.
a. Describe the specific variables being used, their values, distributions, important info.
b. Describe the datasets, how the data are collected, information in the codebook, and other relevant information.
3. Here are some things should consider discussing:
a. How are the data collected, and by whom?
b. Where is it available?
c. What is the unit of observation (individuals, households, countries, etc.)?
d. How many observations are there? Are there any entities left out?
e. How many individuals/households/counties/states/countries are represented? (Note: this is not the same as N.)
f. Specific information about the variables you are using.
i. Average values, distributions, unexpected values, outliers, top coding, measurement error.
ii. Include histograms of important variables and interpret their results, if relevant.
iii. Are you trimming your data or altering the raw data in any way?
g. Which time periods are covered, and how frequently are data collected?
h. Is it cross-section, time-series, panel, or some other format?
i. Is there any information not included in the data that you might need (or want)?
4. In addition to your primary variables of interest, you should also discuss your control variables, why they are included, and their values. This is an important step to reality-check your data.
5. As you discuss the items above, you should reference a table (Table 1) that you create with summary information about your data. This table should be included at the end of your write-up.
a. Table 1 should include ALL variables that you will use in your study as of now.
b. You should have 8-15 control variables (groups of dummies count as one).
c. Any important missing control variables will be considered an oversight.
d. All information (i.e. numbers) that appear in a Table should be discussed somewhere/somehow in the text, and vice versa.
6. Include a thorough discussion of any of data-related biases that might enter your study. NO JARGON. Examples include:
a. Sample selection
b. Measurement error of any of the relevant variables
c. Limits to the scope (for example, do you want to make a statement for all developing countries, but only have data for Latin America?)
For Preliminary Results section (1-3 pages):
1. Start with a visual representation of the relationship between your two variables of interest, if applicable. An example could be a scatter plot with a best-fit line. Is the relationship intuitive/unexpected/noteworthy/unclear/ambiguous/non-linear? Discuss.
2. Present a table (Table 2) of preliminary regression results. Include at least two regressions, a simple regression with just Y and X and at least one multiple regression with a set of appropriate control variables.
3. As you discuss your results, reference specific numbers in the text.
4. Interpret your results for each regression. This should be thorough. Every single coefficient and its significance should be discussed in some way (sometimes quickly or in groups, sometimes individually in painstaking detail.)
5. Note: Interpreting results does not mean regurgitating numbers. Focus on interpreting the regression. What does it mean? Why? Does it make sense? What does it imply? Is it correct? Why or why not? What nuances exist in the interpretation?
6. Discuss why your preliminary results are biased.
a. Include as many sources of bias as are relevant
b. Give intuitive explanations of those sources of bias in the context of your preliminary analysis.
c. Do these biases cause you to over- or under-estimate the true values?
d. NO JARGON.
7. Example first sentence: “Figure 1 shows the relationship between {ind. var} and {dep var}…”
8. Example second paragraph: “Column 1 of Table 2 shows the results of a simple linear regression of {dep var} on {ind var}…”
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