计量经济分析 = Econometric analysis

https://link.springer.com/content/pdf/10.2307%2F3343168.pdf

Development as Freedom

We investigate conditions sufficient for identification of average treatment effects using instrumental variables. First we show that the existence of valid instruments is not sufficient to identify any meaningful average treatment effect. We then establish that the combination of an instrument and a condition on the relation between the instrument and the participation status is sufficient for identification of a local average treatment effect for those who can be induced to change their participation status by changing the value of the instrument. Finally we derive the probability limit of the standard IV estimator under these conditions. It is seen to be a weighted average of local average treatment effects.

Evolution and Rationality Some Recent Game-Theoretic Results. Identification and Estimation of Local Average Treatment Effects

Originally published in Contemporary Psychology: APA Review of Books, 1994, Vol 39(2), 225. Reviews the book, The Nature and Origins of Mass Opinion by John Zaller (1992). The author's commendable effort to specify a model of mass opinion formation offers readers an introduction to the prevailing vi

The Nature and Origins of Mass Opinion.

Ethnic Groups in Conflict

Part I Modalities of Distributive Politics: 1 Between clients and citizens: puzzles and concepts in the study of distributive politics Part II The Micro-Logic of Clientelism: 2 Gaps between theory and fact 3 A theory of broker-mediated distribution 4 Testing the theory of broker-mediated distribution 5 A disjunction between the strategies of leaders and brokers? 6 Clientelism and poverty Part III The Macro-Logic of Vote-Buying: What Explains the Rise and Decline of Political Machines?: 7 Party leaders against the machine 8 What killed vote buying in Britain and the United States? Part IV Clientelism and Democratic Theory: 9 What's wrong with buying votes?

Brokers, Voters, and Clientelism: The Puzzle of Distributive Politics

This book challenges the conventional wisdom that natural resource wealth promotes autocracy. Oil and other forms of mineral wealth can promote both authoritarianism and democracy, the book argues, but they do so through different mechanisms; an understanding of these different mechanisms can help elucidate when either the authoritarian or democratic effects of resource wealth will be relatively strong. Exploiting game-theoretic tools and statistical modeling as well as detailed country case studies and drawing on fieldwork in Latin America and Africa, this book builds and tests a theory that explains political variation across resource-rich states. It will be read by scholars studying the political effects of natural resource wealth in many regions, as well as by those interested in the emergence and persistence of democratic regimes.

/pdf/crude-democracy-natural-resource-wealth-and-political-4ocysg16d9.pdf

Crude Democracy: Natural Resource Wealth and Political Regimes

The effect of foreign aid on regime type in recipient countries remains widely debated. In this research note, I argue that a recent focus on “moral hazard” has distracted attention from another mechanism linking foreign aid to domestic political institutions. During the Cold War, donors' geopolitical objectives diminished the credibility of threats to condition aid on the adoption of democratic reforms. The demise of the Soviet Union and the end of the Cold War, on the other hand, enhanced the effectiveness of Western aid conditionality. I reanalyze an important recent study and demonstrate that the small positive effect of foreign aid on democracy in sub-Saharan African countries between 1975 and 1997 is limited to the post–Cold War period. This new empirical evidence underscores the importance of geopolitical context in conditioning the causal impact of development assistance, and the evidence confirms that the end of the Cold War marked a watershed in the politics of foreign aid in Africa.I would like to thank Henry Brady, Jennifer Bussell, Ruth Berins Collier, David Collier, Robert Powell, Jason Seawright, Beth Simmons, Laura Stoker, and two anonymous reviewers for their comments. I am also grateful to Arthur Goldsmith for sharing his data. Any errors are my own.

http://thaddunning.com/wp-content/uploads/2009/12/IO.pdf

Conditioning the Effects of Aid: Cold War Politics, Donor Credibility, and Democracy in Africa

1. Introduction: why natural experiments? Part I. Discovering Natural Experiments: 2. Standard natural experiments 3. Regression-discontinuity designs 4. Instrumental-variables designs Part II. Analyzing Natural Experiments: 5. Simplicity and transparency: keys to quantitative analysis 6. Sampling processes and standard errors 7. The central role of qualitative evidence Part III. Evaluating Natural Experiments: 8. How plausible is as-if random? 9. How credible is the model? 10. How relevant is the intervention? Part IV. Conclusion: 11. Building strong research designs through multi-method research.

Natural Experiments in the Social Sciences: A Design-Based Approach

Social scientists increasingly exploit natural experiments in their research. This article surveys recent applications in political science, with the goal of illustrating the inferential advantages provided by this research design. When treatment assignment is less than “as if” random, studies may be something less than natural experiments, and familiar threats to valid causal inference in observational settings can arise. The author proposes a continuum of plausibility for natural experiments, defined by the extent to which treatment assignment is plausibly “as if” random, and locates several leading studies along this continuum.

Thad Dunning

Papers

Brokers, Voters, and Clientelism: The Puzzle of Distributive Politics

Crude Democracy: Natural Resource Wealth and Political Regimes

Conditioning the Effects of Aid: Cold War Politics, Donor Credibility, and Democracy in Africa

Natural Experiments in the Social Sciences: A Design-Based Approach

Improving Causal Inference Strengths and Limitations of Natural Experiments