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Institutions Matter?1

Published online by Cambridge University Press:  28 March 2014

Adam Przeworski
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Abstract

The main methodological problem in assessing the impact of political institutions on any kind of performance stems from the possibility that institutions may be endogenous. As a result, institutions cannot be matched for the conditions under which they function. Inferences from such non-experimental observations are subject to several biases and, in the end, our conclusions may not be robust. One should not be confident, therefore, that any institutions would function in the same way under conditions different from those from which they are transplanted.

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Articles
Information
Government and Opposition , Volume 39 , Issue 4 , 2004 , pp. 527 - 540
Copyright
Copyright © Government and Opposition Ltd 2004

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Footnotes

1

This is a revised version of the Government and Opposition/Leonard Schapiro Lecture, delivered to the British Political Science Association, Lincoln, England, 8 April 2004.

References

2 See Douglass C. North, Structure and Change in Economic History, New York, W. W. Norton, 1980; Douglass C. North, Institutions, Institutional Change and Economic Performance, Cambridge, Cambridge University Press, 1990; Douglass C. North, ‘Some Fundamental Puzzles in Economic History/Development’, in W. Brian Arthur, Steven N. Durlauf and David A. Lane (eds), The Economy as an Evolving Complex System II, London, Addison-Wesley. 1997, pp. 223–37.

3 Alasdair MacIntyre, ‘Is a Science of Comparative Politics Possible?’, in Peter Laslett, W. G. Runciman and Quentin Skinner (eds), Philosophy, Politics and Society, Oxford, Basil Blackwell, 1972, pp. 8–26.

4 W. V. Quine, From the Logical Point of View, Cambridge, MA, Harvard University Press, 1953, p. 42.

5 V. I. Lenin, ‘Letter to the Workers of Europe and America’, in Against Revisionism, Moscow, Foreign Languages Publishing House, 1959 [1919], pp. 479–86.

6 For a discussion of this theme in Rousseau, see Steven Holmes, ‘Lineages of the Rule of Law’, in José Maria Maravall and Adam Przeworski (eds), Democracy and the Rule of Law, New York, Cambridge University Press, 2003, pp. 19–61.

7 John Stuart Mill, Considerations on Representative Government, Buffalo, NY, Prometheus, 1991.

8 Condorcet, ‘Essai sur l’application de l’analyse de la probabilité des décisions rendues a la pluralité des voix’, in Olivier de Bernon, Sur les élections et autres textes, Paris, Fayard, 1986, pp. 9–196.

9 For an explanation of these patterns, see Jess Benhabib and Adam Przeworski, ‘The Political Economy of Redistribution under Democracy’, unpublished MS, New York University, 2004, and Adam Przeworski, ‘Democracy as an Equilibrium’, Public Choice, forthcoming, 2004.

10 For an analysis of this question, based on data covering 135 countries between 1950 and 1990, see Adam Przeworski, José Antonio Cheibub, Michael E. Alvarez and Fernando Limongi, Democracy and Development: Political Institutions and Well-Being in the World, 1950–1990, New York, Cambridge University Press, 2000.

11 All income figures are in 1985 purchasing power parity dollars.

12 Fearon, James D., ‘Counterfactuals and Hypothesis Testing in Political Science’, World Politics, 43 (1991), pp. 169–95.CrossRefGoogle Scholar

13 Alexis de Tocqueville, The Old Regime and the French Revolution, New York, Anchor Books, 1955.

14 Important works on counterfactuals, apart from those referred to elsewhere in this paper, include: Yuri Balashov, and Alex Rosenberg (eds), Philosophy of Science: Contemporary Readings, London, Routledge, 2002; Dorothy Edgington, ‘Conditionals’, in Lou Goble (ed.), The Blackwell Guide to Philosophical Logic, Oxford, Blackwell, 2001, pp. 385–414; Nelson Goodman, Fact, Fiction, and Forecast, 4th edn, Cambridge, MA, Harvard University Press, 1979; Holland, Paul W., ‘Statistics and Causal Inference’, Journal of the American Statistical Association, 81 (1986), pp. 945–60CrossRefGoogle ScholarDavid Lewis, Counterfactuals, Cambridge, MA, Harvard University Press, 1973; J. L. Mackie, ‘The Logic of Conditionals’, in Yuri Balashov and Alex Rosenberg (eds), Philosophy of Science: Contemporary Readings, London, Routledge, 2002, pp. 106–14; Judea Pearl, Causality: Models, Reasoning, and Inference, Cambridge, Cambridge University Press, 2000; and Robert C. Stalnaker, Inquiry, Cambridge, MA, MIT Press, 1987.

15 Dawid, A. P., ‘Causal Inference without Counterfactuals’, Journal of the American Statistical Association, 95 (2000), pp. 407–24.CrossRefGoogle Scholar

16 Geoffrey Hawthorn, Plausible Worlds: Possibility and Understanding in History and the Social Sciences, Cambridge, Cambridge University Press, 1991, p. 167.

17 Milan Kundera, The Art of the Novel, New York, Perennial, 2003.

18 Heckman, James, ‘Instrumental Variables: A Study in Implicit Behavioral Assumptions Used in Making Program Evaluations’, Journal of Human Resources, 2 (1997), pp. 441–62.CrossRefGoogle Scholar

19 Gary King and Langche Zeng, ‘When Can History be Our Guide? The Pitfalls of Counterfactual Inference’, http://GKing.Harvard.Edu, 2002.

20 Przeworski, Cheibub, Alvarez and Limongi, Democracy and Development, op. cit.

21 Richard Ned Lebow, ‘What's so Different About a Counterfactual?’, World Politics, 52 (2000), pp. 550–85; 575.

22 King and Zeng, ‘When Can History be Our Guide’, op. cit.

23 Sharun Mukand and Dani Rodrik, ‘In Search of the Holy Grail: Policy Convergence, Experimentation, and Economic Performance’, unpublished MS, Harvard University, 2002, p. 3.

24 Paul R. Rosenberg, Observational Studies, London, Springer-Verlag, 2001, presents an exceptionally clear discussion of the issues involved. Winship, Christopher and Morgan, Stephen L., ‘The Estimation of Causal Effects from Observational Data’, Annual Review of Sociology, 25 (1999), pp. 659–707 CrossRefGoogle Scholar is a good review of the alternative statistical methods.