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Population, Technology, and Growth: From Malthusian Stagnation to the Demographic Transition and Beyond

American Economic Review 2000 90(4), 806-828
This paper develops a unified growth model that captures the historical evolution of population, technology, and output. It encompasses the endogenous transition between three regimes that have characterized economic development. The economy evolves from a Malthusian regime, where technological progress is slow and population growth prevents any sustained rise in income per capita, into a Post-Malthusian regime, where technological progress rises and population growth absorbs only part of output growth. Ultimately, a demographic transition reverses the positive relationship between income and population growth, and the economy enters a Modern Growth regime with reduced population growth and sustained income growth. (JEL J13, O11, O33, O40)

From Malthusian Stagnation to Modern Growth

American Economic Review 1999 89(2), 150-154 open access
This paper examines the historical evolution of the relationship between population growth, technological change, and the standard of living.It considers several unified models that encompass the transition between three distinct regimes that have characterized the process of economic development: ``The Malthusian Regime," ``The Post-Malthusian Regime," and the ``Modern Growth Regime".We view the unified modeling of this long transition process -from thousand of years of Malthusian stagnation through the demographic transition to modern growth -as one of the most significant research challenges facing economists interested in growth and development.

A Bright Idea for Measuring Economic Growth

American Economic Review 2011 101(3), 194-199
The quantity of human-generated light visible from outer space reflects variation in both population density and income per capita. In this paper we explore the usefulness of the change in visible light as a measure of GDP growth. We discuss the data, and then present a statistical framework that uses lights growth to augment existing income growth measures, assuming that measurement errors in the two series are uncorrelated. For some countries with very poor income measurement, we significantly revise estimates of growth. Our technique also produces growth estimates for cities or regions where no other data are available.

Saving and Growth with Habit Formation

American Economic Review 2000 90(3), 341-355
Saving and growth are strongly positively correlated across countries. Recent empirical evidence suggests that this correlation holds largely because high growth leads to high saving, not the other way around. This evidence is difficult to reconcile with standard growth models, since forward-looking consumers with standard utility should save less in a fast-growing economy because they know they will be richer in the future than they are today. We show that if utility depends partly on how consumption compares to a “habit stock” determined by past consumption, an otherwise-standard growth model can imply that increases in growth can cause increased saving. (JEL D91, E21, O40)

Measuring Economic Growth from Outer Space

American Economic Review 2012 102(2), 994-1028
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."