Measuring Economic Growth from Outer Space

GDP growth is often measured poorly for countries and rarely measured at all for cities. We propose a readily available proxy: satellite data on lights at night. Our statistical framework uses light growth to supplement existing income growth measures. The framework is applied to countries with the lowest quality income data, resulting in estimates of growth that differ substantially from established estimates. We then consider a longstanding debate: do increases in local agricultural productivity increase city incomes? For African cities, we find that exogenous agricultural productivity shocks (high rainfall years) have substantial effects on local urban economic activity.economic growth; remote sensing; urbanization; income measurement

Measuring Economic Growth from Outer Space

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.”

The global spatial distribution of economic activity:nature, history and the role of trade

We study the distribution of economic activity, as proxied by lights at night, across 250,000 grid cells of average area 560 square kilometres. We first document that nearly half of the variation can be explained by a parsimonious set of physical geography attributes. A full set of country indicators only explains a further 10%. When we divide geographic characteristics into two groups, those primarily important for agriculture and those primarily important for trade, we find that the agriculture variables have relatively more explanatory power in countries that developed early and the trade variables have relatively more in countries that developed late, despite the fact that the latter group of countries are far more dependent on agriculture today. We explain this apparent puzzle in a model in which two technological shocks occur, one increasing agricultural productivity and the other decreasing transportation costs, and in which agglomeration economies lead to persistence in urban locations. In countries that developed early, structural transformation due to rising agricultural productivity began at a time when transport costs were still relatively high, so urban agglomerations were localized in agricultural regions. When transport costs fell, these local agglomerations persisted. In late developing countries, transport costs fell well before structural transformation. To exploit urban scale economies, manufacturing agglomerated in relatively few, often coastal, locations. With structural transformation, these initial coastal locations grew, without formation of more cities in the agricultural interior

Has climate change driven urbanization in Africa?

This paper documents strong but differentiated links between climate and urbanization in large panels of districts and cities in Sub-Saharan Africa, which has dried substantially in the past fifty years. The key dimension of heterogeneity is whether cities are likely to have manufacturing for export outside their regions, as opposed to being exclusively market towns providing local services to agricultural hinterlands. In regions where cities are likely to be manufacturing centers (25% of our sample), drier conditions increase urbanization and total urban incomes. There, urban migration provides an "escape" from negative agricultural moisture shocks. However, in the remaining market towns (75% of our sample), cities just service agriculture. Reduced farm incomes from negative shocks reduce demand for urban services and derived demand for urban labor. There, drying has little impact on urbanization or total urban incomes. Lack of structural transformation in Africa inhibits a better response to climate change

The global distribution of economic activity: nature, history, and the role of trade

We explore the role of natural characteristics in determining the worldwide spatial distribution of economic activity, as proxied by lights at night, observed across 240,000 grid cells. A parsimonious set of 24 physical geography attributes explains 47% of worldwide variation and 35% of within-country variation in lights. We divide geographic characteristics into two groups, those primarily important for agriculture and those primarily important for trade, and confront a puzzle. In examining within-country variation in lights, among countries that developed early, agricultural variables incrementally explain over 6 times as much variation in lights as do trade variables, while among late developing countries the ratio is only about 1.5, even though the latter group is far more dependent on agriculture. Correspondingly, the marginal effects of agricultural variables as a group on lights are larger in absolute value, and those for trade smaller, for early developers than for late developers. We show that this apparent puzzle is explained by persistence and the differential timing of technological shocks in the two sets of countries. For early developers, structural transformation due to rising agricultural productivity began when transport costs were still high, so cities were localized in agricultural regions. When transport costs fell, these agglomerations persisted. In late-developing countries, transport costs fell before structural transformation. To exploit urban scale economies, manufacturing agglomerated in relatively few, often coastal, locations. Consistent with this explanation, countries that developed earlier are more spatially equal in their distribution of education and economic activity than late developers

The View from Above: Applications of Satellite Data in Economics

The past decade or so has seen a dramatic change in the way that economists can learn by watching our planet from above. A revolution has taken place in remote sensing and allied fields such as computer science, engineering, and geography. Petabytes of satellite imagery have become publicly accessible at increasing resolution, many algorithms for extracting meaningful social science information from these images are now routine, and modern cloud-based processing power allows these algorithms to be run at global scale. This paper seeks to introduce economists to the science of remotely sensed data, and to give a flavor of how this new source of data has been used by economists so far and what might be done in the future. </jats:p

Replication Data for: "Economic and Political Factors in Infrastructure Investment: Evidence from Railroads and Roads in Africa 1960-2015"

This dataset contains total lengths of paved roads (including highways) and improved roads for 1960-2015 and railroads 1862-2015 for each country in Africa, along with several other country-year level data from various sources described in detail in the paper. The roads data, from Jedwab and Storeygard (2019b), are based on Michelin road maps. The rail data are from Jedwab and Moradi (2016), based on various sources

Mobility and Congestion in Urban India

We develop a methodology to estimate robust city-level vehicular speed indices, exactly decomposable into uncongested speed and congestion. We apply it to 180 Indian cities using 57 million simulated trips measured by a web mapping service. We verify the reliability of our simulated trips using a number of alternative data sources, including data on actual trips. We find wide variation in speed across cities that is driven more by differences in uncongested speed than congestion. Denser and more populated cities are slower, only in part because of congestion. Urban economic development is correlated with faster speed despite worse congestion.Peer reviewe