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The African Growth Miracle
TL;DR: Measures of real consumption based upon the ownership of durable goods, the quality of housing, the health and mortality of children, the education of youth and the allocation of female time in the household indicate that sub-Saharan living standards have, for the past two decades, been growing about 3.4 to 3.7 percent per annum, i.e. three and a half to four times the rate indicated in international data sets as mentioned in this paper.
Abstract: Measures of real consumption based upon the ownership of durable goods, the quality of housing, the health and mortality of children, the education of youth and the allocation of female time in the household indicate that sub-Saharan living standards have, for the past two decades, been growing about 3.4 to 3.7 percent per annum, i.e. three and a half to four times the rate indicated in international data sets.
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TL;DR: A statistical framework is developed that uses satellite data on lights growth to augment existing income growth measures, under the assumption that measurement error in using observed light as an indicator of income is uncorrelated with measurementerror in national income accounts.
Abstract: GDP growth is often measured poorly for countries and rarely measured at all for cities or subnational regions. We propose a readily available proxy: satellite data on lights at night. We develop a statistical framework that uses lights growth to augment existing income growth measures, under the assumption that measurement error in using observed light as an indicator of income is uncorrelated with measurement error in national income accounts. For countries with good national income accounts data, information on growth of lights is of marginal value in estimating the true growth rate of income, while for countries with the worst national income accounts, the optimal estimate of true income growth is a composite with roughly equal weights. Among poor-data countries, our new estimate of average annual growth differs by as much as 3 percentage points from official data. Lights data also allow for measurement of income growth in sub- and supranational regions. As an application, we examine growth in Sub Saharan African regions over the last 17 years. We find that real incomes in non-coastal areas have grown faster by 1/3 of an annual percentage point than coastal areas; non-malarial areas have grown faster than malarial ones by 1/3 to 2/3 annual percent points; and primate city regions have grown no faster than hinterland areas. Such applications point toward a research program in which "empirical growth" need no longer be synonymous with "national income accounts."
1,449 citations
TL;DR: In this paper, the authors used historical fluctuations in temperature within countries to identify its effects on aggregate economic outcomes, and found that higher temperatures substantially reduce economic growth in poor countries, not just the level of output.
Abstract: This paper uses historical fluctuations in temperature within countries to identify its effects on aggregate economic outcomes. We find three primary results. First, higher temperatures substantially reduce economic growth in poor countries. Second, higher temperatures may reduce growth rates, not just the level of output. Third, higher temperatures have wide-ranging effects, reducing agricultural output, industrial output, and political stability. These findings inform debates over climate’s role in economic development and suggest the possibility of substantial negative impacts of higher temperatures on poor countries. (JEL E23, O13, Q54, Q56)
1,275 citations
TL;DR: In this article, a strong positive relationship between natural resource exports and urbanization in a sample of 116 developing nations over the period 1960-2010 was found. But, although the development literature often assumes that urbanization is synonymous with industrialization, patterns differ markedly across developing countries.
Abstract: We document a strong positive relationship between natural resource exports and urbanization in a sample of 116 developing nations over the period 1960–2010. In countries that are heavily dependent on resource exports, urbanization appears to be concentrated in “consumption cities” where the economies consist primarily of non-tradable services. These contrast with “production cities” that are more dependent on manufacturing in countries that have industrialized. Consumption cities in resource exporters also appear to perform worse along several measures of welfare. We offer a simple model of structural change that can explain the observed patterns of urbanization and the associated differences in city types. We note that although the development literature often assumes that urbanization is synonymous with industrialization, patterns differ markedly across developing countries. We discuss several possible implications for policy.
452 citations
TL;DR: This paper found that even after considering sector differences in hours worked and human capital per worker, as well as alternative measures of sector output constructed from household survey data, a puzzlingly large gap remains.
Abstract: According to national accounts data, value added per worker is much higher in the nonagricultural sector than in agriculture in the typical country, particularly in developing countries. Taken at face value, this “agricultural productivity gap” suggests that labor is greatly misallocated across sectors. In this article, we draw on new micro evidence to ask to what extent the gap is still present when better measures of sector labor inputs and value added are taken into consideration. We find that even after considering sector differences in hours worked and human capital per worker, as well as alternative measures of sector output constructed from household survey data, a puzzlingly large gap remains.
450 citations
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11 Jan 2018TL;DR: Bolt and van Zanden as discussed by the authors proposed a measure of real GDP per capita over the very long run based on modern and historical cross-country income comparisons and incorporated these into a novel measure of the Maddison Project Database.
Abstract: Economists’ understanding of long-run economic development has greatly improved thanks to the historical statistics compiled by the late Angus Maddison. Yet his method for comparing income levels across countries and over time has come under increasing criticism. New estimates of comparative income level often show markedly different outcomes than Maddison’s projection (or extrapolation) method based on a single, modern-day relative income benchmark. In this paper, we draw on modern and historical cross-country income comparisons and incorporate these into a novel measure of real GDP per capita over the very long run. The resulting new version of the Maddison Project Database thereby does greater justice to historical insights and provides a fresh impetus for future research. We present applications to estimating cross-country income convergence and the Balassa-Samuelson effect and demonstrate that how our new measure of real GDP per capita is a substantial improvement. (JEL: C43, C82, E01, N10, O47) 1 Bolt: University of Groningen and Lund University, j.bolt@rug.nl, Inklaar: University of Groningen, r.c.inklaar@rug.nl, van Zanden: University of Utrecht, j.l.vanzanden@uu.nl, de Jong: University of Groningen, h.j.de.jong@rug.nl. We thank Bob Allen, Leticia Arroyo Abad, Luis Bertola, Steve Broadberry, Angus Deaton, John Devereux, Rob Feenstra, Alan Heston, Andre Hofman, Branko Milanovic, Leandro Prados de la Escosura, the Maddison Project Board in general, and participants at the World Economic History Congress 2015 in Kyoto, the Society for Economic Measurement 2016 in Thessaloniki, the International Comparisons Conference 2017 in Princeton, the Economic History Seminar in Wageningen and the CEPR Meeting in Dublin for helpful comments and suggestions.
376 citations
References
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TL;DR: In this paper, the authors discuss methodological issues surrounding those estimates and confirm that primary education continues to be the number one investment priority in developing countries, and also show that educating females is marginally more profitable than educating males, and that the academic secondary school curriculum is a better investment than the technical/vocational tract.
3,182 citations
Posted Content•
TL;DR: In this paper, the joint maximum likelihood estimator of the structural parameters is not consistent as the number of groups increases, with a fixed number of observations per group, and a conditional likelihood function is maximized, conditional on sufficient statistics for the incidental parameters.
Abstract: In data with a group structure, incidental parameters are included to control for missing variables. Applications include longitudinal data and sibling data. In general, the joint maximum likelihood estimator of the structural parameters is not consistent as the number of groups increases, with a fixed number of observations per group. Instead a conditional likelihood function is maximized, conditional on sufficient statistics for the incidental parameters. In the logit case, a standard conditional logit program can be used. Another solution is a random effects model, in which the distribution of the incidental parameters may depend upon the exogenous variables.
2,338 citations
TL;DR: In this article, the authors present a simple yet general method of calculating asymptotically correct standard errors in T-S models, which may be applied even when joint estimation methods, such as full information maximum likelihood, are inappropriate or computationally infeasible.
Abstract: A commonly used procedure in a wide class of empirical applications is to impute unobserved regressors, such as expectations, from an auxiliary econometric model. This two-step (T-S) procedure fails to account for the fact that imputed regressors are measured with sampling error, so hypothesis tests based on the estimated covariance matrix of the second-step estimator are biased, even in large samples. We present a simple yet general method of calculating asymptotically correct standard errors in T-S models. The procedure may be applied even when joint estimation methods, such as full information maximum likelihood, are inappropriate or computationally infeasible. We present two examples from recent empirical literature in which these corrections have a major impact on hypothesis testing.
1,601 citations
TL;DR: In this article, the authors point out that this is true only of standard quadrature techniques such as trapezoidal integration or its improved variants; Gaussian quadratures, on the other hand, is extremely efficient and is well within the bounds of computational feasibility on modern computers.
Abstract: A PROBLEM OF ESTIMATION that has long confronted many economists is the difficulty of estimating the parameters of equations with limited dependent variables on cross-section time-series (i.e., panel) data. While there are widely available packaged computer programs for estimating either (a) cross-section probit and Tobit models or (b) simple permanent-transitory, random-effects panel models with continuous dependent variables, there are no available computationally feasible methods of combining these two models. This is because the likelihood function that arises in such a combined model contains multivariate normal integrals whose evaluation is quite difficult, if not impossible, with conventional approximation methods. There is a widespread feeling among those working in the area that one possible method of evaluation, the use of quadrature techniques, is in principle possible but is in practice computationally too burdensome to consider (e.g., Albright et al. [2, p. 13]; Hausman and Wise [6, p. 12]). In this note we point out that this is true only of standard quadrature techniques such as trapezoidal integration or its improved variants; Gaussian quadrature, on the other hand, is extremely efficient and is well within the bounds of computational feasibility on modern computers. In what follows, we state the nature of the integrals that need to be evaluated, provide a brief exposition of Gaussian quadrature, and provide a numerical illustration of its use in
755 citations
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TL;DR: It is shown that mortality from infectious, respiratory, and digestive diseases, congenital, perinatal, and “ill-defined” conditions, mostly concentrated before age 20 and between ages 20 and 50, is responsible for most of the reduction in life expectancy inequality.
Abstract: Lack of income convergence for the world as a whole has led to concerns about the impact of globalization of markets on world inequality. GDP per capita is usually used to proxy for the quality of life of individuals living in different countries. However, well-being is also affected by quantity of life, as represented by longevity. This paper incorporates longevity into an overall assessment of the evolution of cross-country inequality. The absence of income convergence noticed in the growth literature is in stark contrast with the reduction in inequality after incorporating recent gains in longevity. The paper computes a full' income measure to value the life expectancy gains experienced by 49 countries between 1965 and 1995. Countries starting with lower income tended to grow more in terms of full' income than countries starting with higher income. The average growth rate of full' income is about 140% for developed countries, compared to 192% for developing countries. Additionally, we decompose changes in life expectancy into changes attributable to thirteen broad groups of causes of death. Infectious, respiratory and digestive diseases, congenital and perinatal conditions, and ill-defined' conditions are responsible for most of the mortality convergence observed between 1965 and 1995.
670 citations