We exploit differences in early colonial experience to estimate the effect of institutions on economic performance. Our argument is that Europeans adopted very different colonization policies in different colonies, with different associated institutions. The choice of colonization strategy was, at least in part, determined by the feasibility of whether Europeans could settle in the colony. In places where Europeans faced high mortality rates, they could not settle and they were more likely to set up worse (extractive) institutions. These early institutions persisted to the present. We document these hypotheses in the data. Exploiting differences in mortality rates faced by soldiers, bishops and sailors in the colonies during the 18th and 19th centuries as an instrument for current institutions, we estimate large effects of institutions on income per capita. Our estimates imply that a change from the worst (Zaire) to the best (US or New Zealand) institutions in our sample would be associated with a five fold increase in income per capita.

you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at

We estimate the respective contributions of institutions, geography, and trade in determining income levels around the world, using recently developed instrumental variables for institutions and trade. Our results indicate that the quality of institutions “trumps ” everything else. Once institutions are controlled for, conventional measures of geography have at best weak direct effects on incomes, although they have a strong indirect effect by influencing the quality of institutions. Similarly, once institutions are controlled for, trade is almost always insignificant, and often enters the income equation with the “wrong ” (i.e., negative) sign. We relate our results to recent literature, and where differences exist, trace their origins to choices on samples, specification, and instrumentation. The views expressed in this paper are the authors ’ own and not of the institutions with which they are affiliated. We thank three referees, Chad Jones, James Robinson, Will Masters, and participants at the Harvard-MIT development seminar, joint IMF-World Bank Seminar, and the Harvard econometrics workshop for their comments, Daron Acemoglu for helpful conversations, and Simon Johnson for providing us with his data. Dani Rodrik gratefully acknowledges support from the Carnegie Corporation of New York. Commerce and manufactures can seldom flourish long in any state which does not enjoy a regular administration of justice, in which the people do not feel themselves secure in the possession of their property, in which the faith of contracts is not supported by law, and in which the authority of the state is not supposed to be regularly employed in enforcing the payment of debts from all those who are able to pay. Commerce and manufactures, in short, can seldom flourish in any state in which there is not a certain degree of confidence in the justice of government.-- Adam Smith, Wealth of Nations I.

Abstract not found

Abstract not found

Among countries colonized by European powers during the past 500 years those that were relatively rich in 1500 are now relatively poor. We document this reversal using data on urbanization patterns, which, we argue, proxy for economic prosperity. This reversal is inconsistent with a view that links economic development to geographic factors. According to the geography view, societies that were relatively rich in 1500 should also be relatively rich today. In contrast, the reversal is consistent with the role of institutions in economic development. The expansion of European overseas empire starting in the 15th century led to a major change in the institutions of the societies they colonized. In fact, the European intervention appears to have created an “institutional reversal ” among these societies, in the sense that Europeans were more likely to impose “extractive ” institutions in densely settled and prosperous areas, while introducing institutions encouraging investment in regions that were previously poor. This institutional reversal accounts for the reversal in relative incomes. We provide further support for this view by documenting that the reversal in relative incomes took place during the 19th century, and resulted from societies with extractive institutions failing to take advantage of industrialization opportunities.

This paper develops the empirical and theoretical case that differences in economic institutions are the fundamental cause of differences in economic development. We first document the empirical importance of institutions by focusing on two “quasi-natural experiments” in history, the division of Korea into two parts with very different economic institutions and the colonization of much of the world by European powers starting in the fifteenth century. We then develop the basic outline of a framework for thinking about why economic institutions differ across countries. Economic institutions determine the incentives of and the constraints on economic actors, and shape economic outcomes. As such, they are social decisions, chosen for their consequences. Because different groups and individuals typically benefit from different economic institutions, there is generally aconflict over these social choices, ultimately resolved in favor of groups with greater political power. The distribution of political power in society is in turn determined by political institutions and the distribution of resources. Political institutions allocate de

We document five stylized facts of economic growth. (1) The “residual ” rather than factor accumulation accounts for most of the income and growth differences across nations. (2) Income diverges over the long run. (3) Factor accumulation is persistent while growth is not persistent and the growth path of countries exhibits remarkable variation across countries. (4) Economic activity is highly concentrated, with all factors of production flowing to the richest areas. (5) National policies closely associated with long-run economic growth rates. We argue that these facts do not support models with diminishing returns, constant returns to scale, some fixed factor of production, and that highlight the role of factor accumulation. Empirical work, however, does not yet decisively distinguish among the different theoretical conceptions of “total factor productivity growth.” Economists should devote more effort towards modeling and quantifying total factor productivity.

NOTE: We will make final revisions to this paper in July 2000, at which time we will make reference to all pertinent papers that have come to our attention by June 30, 2000. If anyone reading this survey knows of a pertinent paper not presently included in the list of references, please send a copy or a reference to one of us. *Djankov is Financial Economist at the World Bank. Murrell is Professor of Economics and Chair of the Academic Council of the IRIS Center, University of Maryland. We would like to thank Judy Hellerstein, John McMillan, John Nellis, and Jan Svejnar for helpful advice and Wooyoung Kim and Tatiana Nenova for research assistance. This research was made possible through support provided by the World Bank and by the U.S. Agency for International Development under Cooperative Agreement No. DHR-0015-A-00-0031-00 to the Center for Institutional Reform and the Informal Sector (IRIS). The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the IRIS Center, US AID, the World Bank, its Executive Directors, or the countries they represent. Enterprise Restructuring in Transition: A Quantitative Survey Abstract. There are now over 125 empirical papers that analyze the process of enterprise restructuring in transition

This paper examines the robustness of explanatory variables in cross-country economic growth regressions. It introduces and employs a novel approach, Bayes-ian Averaging of Classical Estimates (BACE), which constructs estimates by aver-aging OLS coefficients across models. The weights given to individual regressions have a Bayesian justification similar to the Schwarz model selection criterion. Of 67 explanatory variables we find 18 to be significantly and robustly partially correlated with long-term growth and another three variables to be marginally related. The strongest evidence is for the relative price of investment, primary school enrollment, and the initial level of real GDP per capita. (JEL O51, O52,