1. Measuring Democracy: a multidimensional, historical, approach Dinner remarks Michael Coppedge University of Notre Dame

2. Disaggregation Solves some key challenges to measuring democracy Sidesteps need for consensus on a definition of democracy Enables people to create their own customized aggregated index Enables us to pursue both extension and thick intension (if done right)

3. But challenges remain Defining even the loose boundaries of the concept Avoiding concept stretching Choosing a useful level of measurement Securing funding Recruiting, training, and supervising several teams of coders Sustaining commitment to the project

4. Funding The way to secure sufficient funding is to write a persuasive and practical proposal My focus: Realistically, in what ways can we improve on what already exists? A preliminary assessment of today’s discussions

5. Core features of the democratic ideal A set of institutions and processes that approximate political equality, i.e., 1. Every citizen’s preferences receive equal consideration before a binding decision is made 2. The ability of citizens to form and express their preferences is effectively guaranteed 3. Deviations from this principle are likely to be caught and corrected 4. Policies are implemented faithfully and without bias It’s a sequential, evolving process:

6. Agenda-setting Preference formation and expression Social organization Political organization Election of representatives Electoral consequences Post-electoral negotiation Policymaking Checks & balances Administration Direct democracy

7. See handout One way to improve is to measure parts of this process that existing indicators ignore Do we do this? Can we do this?

8. Limitations Feasibility is still the biggest constraint: scarce information, finite personnel, time, and resources We cannot measure every relevant aspect of democracy We should set aside aspects that are tangential or controversial or impossible: Individual autonomy, direct democracy, coalition formation, administration…

9. However We can build on prior efforts We can define explicitly which aspects we are measuring, and which we are not We can thicken the concept in some ways We can extend geographic coverage We can extend historical coverage

10. And We can use better measurement techniques Explicit, concrete coding criteria Qualitative precision without sacrificing quantitative precision Multiple indicators for each concept Multiple coders Estimates of uncertainty

11. We should plan for eventual aggregation So we should have multiple indicators for each likely dimension And we should use the highest level of measurement that we can: ratio or interval whenever possible Consider probabilities as the units of measurement: the probability of censure, of being able to vote, of getting a fair trial, etc.

12. But we have to stay flexible Theoretical dimensions should correspond to empirical dimensions, but often they don’t Empirical dimensions can evolve over the decades

13. Practical questions to discuss How many teams of coders? Undergrads? Grad students? Us? Employees? How would we train them? How would we train after turnover? How much time can we each devote to this project each year? What kind of compensation do we expect? What is the timetable? Do we do everything at once, or a few indicators at a time?