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.

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We introduce imperfect creditor protection in a multi-country version of Schumpeterian growth theory with technology transfer. The theory predicts that the growth rate of any country with more than some critical level of financial development will converge to the growth rate of the world technology frontier, and that all other countries will have a strictly lower long-run growth rate. The theory also predicts that in a country that converges to the frontier growth rate, financial development has a positive but eventually vanishing effect on steady-state per-capita GDP relative to the frontier. We present cross-country evidence supporting these two implications. In particular, we find a significant and sizeable effect of an interaction term between initial per-capita GDP (relative to the United States) and a financial intermediation measure in an otherwise standard growth regression, implying that the likelihood of converging to the U.S. growth rate increases with financial development. We also find that, as predicted by the theory, the direct effect of financial intermediation in this regression is not significantly different from zero. These findings are robust to alternative conditioning sets, estimation procedures and measures of financial development.

I use microeconomic estimates of the effect of health on individual outcomes to construct macroeconomic estimates of the proximate effect of health on GDP per capita. I employ a variety of methods to construct estimates of the return to health, which I combine with crosscountry and historical data on height, adult survival rates, and age at menarche. Using my preferred estimate, eliminating health differences among countries would reduce the variance of log GDP per worker by 9.9 percent, and reduce the ratio of GDP per worker at the 90 th percentile to GDP per worker at the 10 th percentile from 20.5 to 17.9. While this effect is economically significant, it is also substantially smaller than estimates of the effect of health on economic growth that are derived from cross-country regressions.

We provide a theoretical explanation, based on Schumpeterian growth theory, for the divergence in per-capita income that has taken place between countries since the mid 19th Century, as well as for the convergence that took place between the richest countries during the second half of the 20th Century. The argument is based on the premise that technological change underwent a fundamental transformation in the 19th Century, associated with new scientific ideas and the increasingly scientific content of new technologies. We model this transformation as the introduction of a new method for producing innovations, which we call “modern R&D”. In order to use this method a country’s entrepreneurs must have at least some minimum level of skills, which depends on the technological frontier. Countries not fulfilling this requirement can only create new technologies through an older method, which we call “implementation”. A multi-country Schumpeterian growth model incorporating these ideas implies that countries will sort themselves into three groups. Those in the highest group will converge to an “R&D steady state”, while those in the intermediate group converge to an “implementation steady state”. Countries in both of these groups will grow at the same rate in the long run, as a result of technology transfer, but inequality of per-capita income between the two groups will increase during the transition to the

This paper uses annual variation in climate to examine the impact of temperature and precipitation on national economies. We find three primary results. First, higher temperatures substantially reduce economic growth in poor countries. Second, higher temperatures appear to reduce growth rates, not just the level of output. Third, higher temperatures have wide-ranging effects, reducing agricultural and industrial output, investment, innovation, and political stability. Decade or longer increases in temperature also show substantial negative effects on poor countries ’ growth. These findings inform debates over climate’s role in economic development and suggest substantial negative impacts of future climate change on poor countries.

Abstract: This paper explores the relevance of unknown nonlinearities for growth empirics. Recent theoretical contributions and case-study evidence suggest that nonlinearities are pervasive in the growth process. I show that the postwar data provide strong evidence in favor of generalized non-linearities. I provide two alternative mechanisms for making inference about the effects of production-function shifters on growth that do not make a priori assumptions about functional form: monotonicity tests and average derivative estimation. The results of these tests point towards a greater role for structural variables and a smaller role for policy variables than the linear model.

This paper examines the structural determinants of output volatility in developing countries, and especially the roles of geography and institutions. We investigate the volatility effects of market access, climate variability, the geographic predisposition to trade, and various measures of institutional quality. We find an especially important role for market access: remote countries are more likely to have undiversified exports and to experience greater volatility in output growth. Our results are based on Bayesian methods that allow us to address formally the problem of model uncertainty and to examine robustness across a wide range of specifications.

We thank David Albouy and Francesco Trebbi for kindly sharing their data as well as Chris Recent approaches to development accounting reflect substantial model uncertainty at both the instrument and the development determinant level. Bayesian Model Averaging (BMA) has been proven useful in resolving model uncertainty in economics, and we extend BMA to formally account for model uncertainty in the presence of endogeneity. The new methodology is shown to be highly efficient and to reduce many-instrument bias; in a simulation study we found that IVBMA estimates reduced mean squared error by 60 % over standard IV estimates. We also introduce Bayesian over and under-identification tests that are based on model averaged predictive p-values. This approach is shown to mitigate the reduction in power these tests experience as dimension increases. In a simulation study where the exogeneity of the instrument is compromised we show that the classical Sargan test has a power of 0.2 % while our Bayesian over-identification test has a power of 98 % at detecting the violation of the exogeneity assumption. An application of our method to a prominent development accounting approach leads to new insights regarding the primacy of institutions.

... empirics literature has used increasingly sophisticated methods to select relevant growth determinants in estimating cross-section growth regressions. The vast majority of empirical approaches however limit cross-country heterogeneity in production technology to the specification of Total Factor Productivity, the ‘measure of our ignorance’ (Abramowitz, 1956). The central theme of this survey is an investigation of this choice of specification against the background of pertinent data properties when the units of observations are countries or regions and the time-series dimension of the data becomes substantial. We present two general empirical frameworks for cross-country productivity analysis and demonstrate that they encompass the approaches in the growth empirics literature of the past two decades. We then develop our central argument, that cross-country heterogeneity in the impact of observables and unobservables on output is important for reliable empirical analysis. This idea is developed against the background of the pertinent time-series and cross-section properties of macro panel data.