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«Development, Security, and Cooperation Policy and Global Affairs THE NATIONAL ACADEMIES PRESS 500 Fifth Street, N.W. Washington, DC 20001 NOTICE: The ...»

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• Research design

• Pilot field studies

• Future research 3:00 Break



–  –  –

12:30 Working Lunch/Continued Discussion with Democracy and Governance Practitioners Kenneth Wollack, President, National Democratic Institute Christopher Fomunyoh, Senior Associate for Africa and Regional Director for Central and West Africa, NDI 3:30–3:45 Break



–  –  –

Thursday, November 9


8:30 Continental breakfast available in the meeting room 9:00 Meeting begins

• Opening remarks by committee chair

• Plan for the meeting 9:15 Session #1: Rule of Law 10:15 Break 10:30 Session #2: Governance 11:30 Session #3: Civil Society 12:30 Working Lunch 1:15 Session #4: Elections and Processes 2:15 Break 2:30 General discussion 4:30 Summary 5:00 Adjourn 6:00 Committee Working Dinner

–  –  –

May 3rd




10:45 Update from USAID on Field Visits

• Field visit schedules

• Mission issues and updates

• Continued discussion of the revised field plan 11:15 Public Workshop Issues 11:30 Voices from the Field 12:30 Working Lunch (NAS Cafeteria) 1:30 Review of Project Statement and Deliverables 1:45 NRC Report Review Process 2:30 Break


2:45–5:00 Meeting Adjourns May 4th


8:30–5:00 Meeting Adjourns

–  –  –

July 20th


8:30 Continental breakfast available in the meeting room 9:00 Updates and conversation with USAID

• Issues and questions from yesterday’s discussion



–  –  –

This appendix contains three sections to support and expand the material in Chapter 3. The statistical analysis presented in the first section was carried out by Ramziya Shakirova, a graduate student at George Mason University, on behalf of the committee. The second section contains the agenda and participants list for a committee workshop, “Democracy Indicators for Democracy Assistance,” held at Boston University in January 2007. The last section is an “Outline for a Disaggregated Meso-level Democracy Index” by John Gerring, which contains additional material related to the index proposed in Chapter 3.


Spearman vs. Pearson Coefficients The comparison of Spearman and Pearson correlation coefficients shows that on the whole, they are quite similar. However, in some cases the Spearman correlation coefficients are not significant (probably, the Pearson coefficients are too, but Stata does not display a significance level for the Pearson coefficients), which means that the Freedom House (FH) and Polity scores are in fact independent. The countries in “Partially Free

Group” with insignificant correlations are:

Cambodia: Pearson is 0.3281; Spearman is 0.3453, not significant Armenia: Pearson is 0.1632; Spearman is 0.1615, not significant

–  –  –

Azerbaijan: Pearson is -0.0808; Spearman is 0.2864, but not significant Moldova: Pearson is 0.6019; Spearman is 0.4550, not significant Ukraine: Pearson is -0.3344; Spearman is -0.3015, not significant Afghanistan: Pearson is 0.1832; Spearman is 0.2388, not significant Egypt: Pearson is -0.2036; Spearman is -0.0889, but not significant Yemen: Pearson is -0.0096; Spearman is -0.2060, not significant Tunisia: Pearson is -0.0265; Spearman is -0.0452, not significant Mexico: Pearson is 0.4544; Spearman is 0.2681, not significant Greece: Pearson is 0.896; Spearman is 0.1609, not significant Macedonia: Pearson is 0.373; Spearman is 0.3924, not significant Sierra Leone: Pearson is 0.5094; Spearman is 0.2858, not significant Zimbabwe: Pearson is 0.2791; Spearman is 0.2612, but not significant Burundi: Pearson is 0.4269; Spearman is 0.2823, not significant Cameroon: Pearson is -0.1538; Spearman is -0.1018, not significant Comoros: Pearson is -0.0408; Spearman is 0.2358, not significant Kenya: Pearson is 0.1287; Spearman is -0.1646, not significant For two countries (Colombia and Côte d’Ivoire), the coefficients are close in their magnitude, although the Spearman coefficients are significant only at the 10 percent level, but not the 5 percent level.

Correlation of First Differences The average correlation coefficients for the first differences in the group of “Partially Free” countries are low for the Former Soviet Union and the Middle East (Table C-1).

• For the Former Soviet Union, the average correlation coefficient is equal to 0.148. Particularly, the coefficients are low for Armenia (0.1871) and Tajikistan (0.1320), and close to zero for the Ukraine (0.0891). Negative coefficients are observed for Kazakhstan (-0.1562), Moldova (-0.1800), and Russia (-0.5188). Satisfactory coefficients for the first differences are found in this group only for Azerbaijan, Belarus, and Georgia.

• For the Middle East, the average is 0.285392. In this group, negative coefficients are observed for Egypt (-0.1292), Iran (-0.0531), and Yemen North (-0.0408), and cloze to zero, but positive, for Tunisia (0.0840).

In other regional groups there are also some countries with negative or zero coefficients: (Malaysia (-0.083), Panama (-0.2525), Angola (-0.0788), Côte d’Ivoire (-0.091), Liberia (0.000), Madagascar (0.0589), Rwanda (–0.2813), Togo (-0.0195), Uganda (0.0211), Chad (-0.218), Comoros (-0.3467), and Equatorial Guinea (-0.3725). The average correlation  APPENDIX C coefficients for other regional groups are the following: Asia (0.4829), Latin America (0.54092105), and Africa (0.408083).

In the group of “Democratic” countries (Table C-2), negative correlations for the first differences are observed for Cyprus (-0.6930), France (-0.0197), and Mauritius (-0.0197), and close to zero coefficient for Trinidad (0.0163). The average for this group is also very low, and equal to 0.11855714.

For “Autocratic” countries (Table C-3), negative coefficients are observed for China (-0.0113), Oman (-0.0496), Yemen South (-0.4123), and Mauritania (-0.0197), and zero correlation for Syria.

There are several countries where the correlation coefficients for the first differences are positive, although correlations between FH and Polity scores are negative (Bahrain, Iraq, and Morocco).

The average correlation coefficient for “autocratic” countries is 0.296829.

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Saturday, January 27, 2007 10:00 a.m. The Aggregation Problem. Can aggregation rules be arrived at (a) within dimensions and (b) across dimensions? Can we provide some guidance to USAID on how to define “Big-D” democracy? Or is it advisable to avoid this highest level of aggregation?

11:00 a.m. History. How important is the historical aspect of the index?

What would have to be sacrificed from the current index in order for it to be extended back to 1960, 1900, or 1800?

11:30 a.m. Management and Payoff. How to make this project work?

Will the necessary data be available? How big a project is this, really? How much time would it take? How much money would it cost? How would it be organized? (Should we rely primarily on students or expert staff? If the latter, would they need to be paid, and if so how much?) What is the potential payoff of this project? Is it worth the money it would take?

12:00 p.m. general Discussion (Lunch meeting). Revisit all issues to see what points of consensus have been reached and what points of disagreement remain. Try to resolve the latter.

Return to issues that need more discussion.

1:30 p.m. Final Recommendations and Conclusions 2:00 p.m. Meeting Adjourns

–  –  –

John Gerring Chapter 3 introduced the Committee’s proposal to develop a disaggregated index, which we believe will better serve USAID’s needs for strategic assessment and tracking. At the meso level, we identified 13

dimensions of democracy that may be independently assessed:

1. National Sovereignty: Is the nation sovereign?

2. Civil Liberty: Do citizens enjoy civil liberty in matters pertaining to politics?

3. Popular Sovereignty: Are elected officials sovereign relative to non-elected elites?

4. Transparency: How transparent is the political system?

5. Judicial Independence: How independent, clean, and empowered is the judiciary?

6. Checks on the Executive: Are there effective checks on the executive?

7. Election Participation: Is electoral participation unconstrained and extensive?

8. Election Administration: Is the administration of elections fair?

9. Election Results: Do results of an election indicate that a democratic process has occurred?

10. Leadership Turnover: Is there regular turnover in the top political leadership?

11. Civil Society: Is civil society dynamic, independent, and politically active?

12. Political Parties: Are political parties well institutionalized?

13. Subnational Democracy: How decentralized is political power and how democratic is politics at subnational levels?

The rest of this section of Appendix C elaborates on some of the issues related to the proposed index, concluding with a more detailed listing of the 13 dimensions listed above.

–  –  –

a given country or territory during a given year. Further work will be required in order to specify what these scales mean in the context of each question. The devil is always in the details.

Coding categories are dichotomous (yes/no), categorical (unranked), nominal (ranked), or interal. In certain cases, it may be possible to combine separate components into more aggregated nominal scales without losing information (Coppedge and Reinicke 1990). This is possible, evidently, only when the underlying data of interest are, in fact, nominal.

There are roughly 100 components in the index as currently constructed.

While this may seem like quite a few, the reader is urged to consider that most of these questions—indeed, the vast majority—are very simple to answer. Thus, it should not take a country expert (or well-coached student assistant) very long to complete the questionnaire. Indeed, this is precisely the point. A longer set of questions is sometimes quicker to complete than a much shorter set of questions, if the latter are vague and ambiguous (due, we suppose, to a high level of aggregation).

For each datum, one should record (a) the coding (numerical or natural language), (b) the source(s) on which the coding was based, (c) the coder(s), (d) any revisions to the initial coding that may have been made in previous iterations of the dataset, (e) any further explanation that might be helpful, and (f) estimates of uncertainty (discussed below). Evidently, it is important that the data-storage software be capable of handling numerical and narrative responses (e.g., MS Access).

Objective/Subjective Measures With respect to attaining greater accuracy, “hard” or “objective” indicators—based on what might be considered factual matters—are preferred over expert opinions. As one example, one might consider how to replace (or supplement) the opinion of country experts about how free the press is with a content analysis of major news outlets. Where the press is free, one would expect to find (a) a dispersion of views across news sources and (b) criticism of political leaders. Both signal the existence of the sort of open debate that is impossible if the press is constrained, and inevitable (one would think) if it is not.

At the same time, it is important to note that the development of an objective measure for a difficult concept such as press freedom is apt to be time-intensive and costly, and may not be possible at all for previous eras.

Additionally, objective indicators are sometimes subject to the problem of “teaching to the test”; governments can attain higher scores by fulfilling some criterion that has little import for democracy.

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