1. Outline for today’s class
How to do research – Sully Schuster
Negotiation practice
How to analyze and graph data

2. Midterm evaluation of teaching feedback
More welcoming response to student answers to questions – my apologies on that.
More in-class discussion
More videos, images, etc.

3. Why States Take Positions They Do in Int’l Negotiations
Ecological
Yes
Vulnerability No
Low
Abatement
Pusher
Bystander
Costs High
Intermediate
Dragger
Sprinz and Vaahtoranta, 1994.

4. Treaty 1 – overarching thoughts
Good strategy: look at analysis of similar treaty in chapters in any of the many books I have put on reserve in the library for the course. Imitate that analysis.
Polar bears
Fisheries
Tropical Timber
Fur Seals

5. Questions in a negotiation
Who to involve – which states, which non-states
What to discuss and how to discuss it (framing)
How ambitious to be
Means of implementation
Response to compliance and noncompliance
Different general strategies of negotiation process

6. Variation in negotiation practice
Agreements reached or not
No forest agreement; no nitrogen-fixing agreement
Many agreements in other issue areas
Marine pollution: 11 treaties, 4 protocols, 74 amendments
Whaling – annual amendments since 1946
LRTAP: 8 protocols; Montreal: 17 amendments/adjusts
Desertification: no additional agreements
Strength of agreements
Montreal vs. climate
Timing of agreements: why in 19xx vs. earlier/later?
Approach to agreements: fisheries v. regional v. global

7. How do choices about what’s in climate change agreement affect whether there is one?
Choice #1: Single or comprehensive - is linkage across issues good or bad?
Choice #2: Few actors or universal
Choice #3: Fixed targets or renegotiable
Choice #4: Binding treaty (hard law) or informal guidelines (soft law)
Choice #5: World Environmental Organization

8. Building a Convincing Causal Argument

9. Building a Convincing Causal Argument
Identify important theoretical question
Develop hypotheses and identify the variables
Select cases to control variables (and thereby exclude rival hypotheses as explanations)
Link data to hypotheses
Examine correlations and causal pathways
Generalize to other cases

10. A Convincing Argument Requires
Evidence
that the ACTUAL value of the Dependent Variable
matches the PREDICTED value of the Dependent Variable for
your theoretical claim
AND FOR
your counterfactual claim

11. Final Paper
Start by identifying good hypotheses from Brown Weiss/Jacobson readings and others on reserve
Compare regulated behavior to otherwise-similar non-regulated behavior to see if they are different
If they do NOT differ, there’s nothing to explain (BUT you may want to explain why you expected them to be different)
If they DO differ, try to exclude other explanations, leaving the treaty as only remaining explanation
Develop counterfactuals to evaluate whether changes were due to treaty or other factors

12. Potential Independent variables

13. Possible Comparison #1: Members/Non-members
Members (regulated actors) to non-members (non-regulated actors),
Members vs. non-members after treaty
Treaty members before/after treaty starts

14. Possible Comparison #2: Regulated/Non-regulated Activity
Members regulated activity to members non-regulated activity
Catch of regulated yellowfin tuna vs. non-regulated bluefin tuna
Sulfur dioxide pollution vs. carbon monoxide pollution

15. Possible Comparison #3: Regulated/Non-regulated Location
Members in regulated location to members in non-regulated location
Catch of yellowfin tuna in regulated area (Indian Ocean) vs. non-regulated area (Western Pacific)
Pollution of regulated river vs. pollution of non-regulated river

16. Pollution Example

17. Pollution Example
Treaty In Force

18. Pollution Example Treaty In Force COUNTERFACTUAL 1:
Predicted Emissions if Treaty Wasn’t Signed (using Members)

19. Pollution Example Treaty In Force COUNTERFACTUAL 1:
Predicted Emissions if Treaty Wasn’t Signed (using Members)

20. Pollution Example Treaty In Force COUNTERFACTUAL 2:
Predicted Emissions if Treaty Wasn’t Signed (using Non-Members)

21. Problems of graphing data and how to resolve them

22. Data Analysis Strategies, aka: “How to Drink from a Firehose”
Determine ideal DV before looking at data
Draw expected graph by hand: years, lines included, success example
Identify best indicators you have available
Compare regulated/non-regulated behavior
Actors: Member/non-member
Regulated countries vs. non-regulated countries
Activity: Regulated/non-regulated activity
E.g., regulated chemical/species vs. unregulated chemical/species
Location: Regulated/non-regulated geographic area
E.g., catch in North Pacific vs. South Pacific

23. Simplify your data!! DON’T USE ALL THE DATA YOU HAVE!
Focus on most important indicators
Focus on 15 years before / 15 years after
Focus on countries most responsible
Create columns for regulated/non-regulated
Compare average of country groups
No more than 6 lines on one graph
Think about normalizing data across countries:
Index // percent change // per GDP // per person
Graph alternative explanations, e.g., price

24. Graphing without thinking: don’t know what you’re seeing
Goal:
See if treaties change country behavior over time
Draw what you want by hand, then graph
Country-groups, X-axis, Y-axis, expected lines
Practice makes perfect – do it by hand again!

25. Graphing everything creates spaghetti
Large countries swamp small
Too much to understand
Graph all; then delete one-by-one to learn about your data: major polluters, missing data, etc.
Create groups of different type states
Members vs. Non-members
Developed vs. Developing members
Green vs. Brown members
Other categories theory suggests
Make sure data isn’t messing you up

26. Graphing the raw data doesn’t make countries similar enough
Solution 1: Indexing
Concept: view each country’s behavior as % of its behavior in year treaty entered into force (EIF year)
Doing it: copy of rectangle, but with formula that divides each country’s data in each year by that country’s data in the EIF year
Solution 2: Normalizing
Concept: view each country’s behavior after adjusting for population, GDP, or other variables
Doing it: copy of rectangle, but with formula that divides each country’s DV by IV in each year