Quantitative Research Report using STATA Students will write one 3000-word (not including tables, figures, appendices, or works-cited) quantitative research report using cross-sectional or time-series data compiled by the Quality of Government Database (both are available on Keats). Topics will be provided, but students are also free to develop their own topics using alternative databases in consultation with me.
Quantitative Research Report using STATA
Reports should start from an empirical or theoretical puzzle and a clearly formulated research question. It is essential to discuss the empirical and theoretical relevance of the research question.
You must (1) formulate at least two testable hypotheses, (2) include at least two control variables; and (3) carefully explain the operationalization of the relevant theoretical concepts.
You will then test your hypotheses using appropriate statistical techniques learned in this module. This must include a multivariate regression analysis. A complete and detailed template will be provided.
Quantitative Research Report using STATA Options
Why are some countries doing more to protect the environment compared to others? What factors explain variation across countries on the issue of environmental protection? Answer this question using the Environmental Performance Index (epi_epi) as your DV.
In the era of fake news and alternative facts, freedom of the press is facing new and persistent challenges. What factors explain why some countries have more robust provisions for freedom of the press compared to others? Answer this question using the Press Freedom Index (rsf_pfi) as your dependent variable.
From anti-free trade protests to Brexit and Trump, globalization seems to be on the backfoot. What factors explain why some countries remain committed to globalisation while others are turning inward? Answer this question using the Index of Globalisation (dr_ig) as your dependent variable.
Quantitative Research Report using STATA Section II: Theory
Present a minimum of two distinct explanations for your DV
– Each explanation links to two IVs you have selected from the QOG dataset (or another dataset).
– Build your ëtheoryí around the logical ìcausal glueî that links each IV to the DV.
– Be sure to reference relevant literature. However, this is not the focus of this assignment, so you can keep this to a minimum.
– Explanations must be formalized as hypotheses. I.e., you must present two testable hypotheses.
– Hypotheses must state the expected correlation between IV and DV.
Section III: Research Design
– In this section you provide explain the data used to test your hypotheses
– You need to be thorough and precise as the goal is to give enough information so that someone else could replicate your analysis.
– Operationalise your DV, IVs, and 2 control variables. This requires: telling us how each variable was measured giving all the appropriate details. I recommend one (short) paragraph per variable.
Include the following:
o Where did you get your data (original data source)?
o How was it measured? If itís from a survey question, include the original question and answer options. If itís an index, what are its component parts? Be thorough.
o Did you have to transform your data (e.g., create new categories or create an index, etc). Provide exact details
o Discuss any issues of data reliability and validity. Consider the gap between your indicators and your concepts.
– Conclude this section by presenting a Table of Summary Statistics. Be sure to use the correct format.
Section IV: Regression Diagnostics
- Run and report results for regression diagnostics, including: assumption of normal distribution of the DV and residuals, outliers, and multicollinearity. You may want to consider using tables and/or figures. This is up to you.
- Present two (2) two-way scatter plots for each IV and the DV. Be sure to include a fitted regression line. Calculate and consider the ëcorrelation coefficientsí for your main IVs and DV Interpret the results. Is there preliminary evidence for either hypothesis?
Quantitative Research Report using STATA Section V: Regression Analysis
- Explain the regression method used (it will be multivariate OLS regression analysis) and outline what each regression model does.
- You must have a minimum of two regression models. One with the just the control variables, and one with IVs and the control variables.
- Present your regression models in one (1) main regression table. Please refer to the example regression table from Stata Lab 5, page 20.
- Interpret the results of your regression table. It is best to: (1) discuss evidence for your hypotheses; and then (2) discuss results for your control variables.
- Be sure to:
- Discuss the explanatory power of each model and what this means (use the r-squared for each model)
- How has the explanatory power been improved by the addition of your IVs?
- Discuss the magnitude (regression coefficient) and statistical significance (p-value) for each variable on the DV. Be sure to tell us what this means in real-world terms.
- Finally, present and interpret two figures (using ìmarginsplotî) of the marginal effects corresponding to your two hypotheses.
Section VI. Conclusion
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