Empirical Research Proposal Guideline:

Empirical Research Proposal Guideline:

Throughout the semester, you learn a wider range of topics including validity and reliability, levels of measurement, hypothesis formation, and requirements of establishing causality, descriptive statistics, statistical inference, and linear regression analysis.

You are expected to have a better acquaintance with quantitative data and methods conducive to conducting empirical political science research and the ability to comprehend and critique the techniques employed in a paper. Now you will practice applying these skills to write an empirical research proposal and later on in the next assignment you will implement the proposal by writing a fulllength academic paper to empirically examine the causal theory of your interest.

Your empirical research proposal1 will ask a precise research question, briefly review existing literature, formulate a theoretically informed testable hypothesis and propose a research design that you will employ to empirically test the hypothesis. More precisely, the proposal should address the following five sections 2 : 1. Research question and (causal) theory: What is a political science-related research question that you are interested in to empirically examine? How is your research question situated in relevant political science literature? Why is it important to study the research question that you pose? What is your theory? What are the key concepts in your theory? How is your causal theory, if confirmed, expected to help us better understand politics and/or contribute in political science scholarship? (25 out of 100)

1. The proposal should be within 6 pages (double-spaced, 12 font). If you use references for literature review, you may use an additional page just for citing the references. You will submit the proposal electronically on Quercus.
2. Hypothesis: What is your research and null hypothesis? What is the key independent/causal variable that is likely to explain your dependent variable? How do you expect the independent variable to be related to your dependent variable? (e.g., do you expect that as X increases (decreases), Y increases (decreases)? What is the causal mechanism? (e.g., why does your independent variable affect your dependent variable? (20 out of 100)
3. Measurement: How will you operationalize the concepts into measureable variables? (e.g., from the Pollock and Edwards’ book, which variable will you use as X and Y?). What is the name of the dataset that you will be using from the Pollock and Edwards’ book to test your hypothesis? What do these variables measure? What is the unit of analysis and the level(s) of measurement? (20 out of 100)
4. Research design: What is your research design? What method(s) will you employ to statistically test the hypothesis? More precisely, how will you proceed with/complete your research and why the approaches and methods you are taking is appropriate to address the question you raise? (20 out of 100)
5. Confounding variables (z) and reverse causality: You expect that X causally affects
6. However, what are the other variables that you think could also be a cause of the Y

while being correlated with X. Identify multiple (up to 2) causal variables. Are they confounding variables? Why? Is there any possibility of reverse causality? (e.g., we expect that our X will affect Y, but is there any chance that Y will rather affect X?) (15 out of 100).