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.”

In this paper, using panel data, I estimate plant level production functions that include variables that allow for two types of scale externalities which plants experie nce in their local industrial environments. First are externalities from other plants in the same industry locally, usually called localization economies or, in a dynamic context, Marshall, Arrow, Romer [MAR] economies. Second are externalities from the scale or diversity of local economic activity outside the own industry involving some type of cross-fertilization, usually called urbanization economies or, in a dynamic context, Jacobs economies. Estimating production functions for plants in high tech industries and in capital goods, or machinery industries, I find that local own industry scale externalities, as measured specifically by the count of other own industry plants locally, have strong productivity effects in high tech but not machinery industries. I find evidence that single plant firms both benefit more from and generate greater external benefits than corporate plants. On timing, I find evidence that high tech single plant firms benefit from the scale of past own industry activity, as well as current activity. I find no evidence of urbanization economies from the diversity of local economic activity outside the own industry and limited evidence of urbanization economies from the overall scale of local economic activity. Issues and the LiteratureA number of productivity studies (e.g., Ciccone and Hall (1996), Henderson (1986), Nakamura (1985), and Sveikauskas (1975) have attempted to sort out whether local scale externalities are localization-MAR economies from the scale of local own industry activity versus urbanization-Jacobs 1 Support of the National Science Foundation (Grant No. SBR-9730142) is gratefully acknowledged. I thank Joyce Cooper for her help and Tim Dunne for advice on the use of the LRD. I thank Duncan Black, Areendam Chanda and Yukako Ono for excellent assistance. I thank Will Strange for helpful comments on an earlier version of the paper entitled "Evidence on Scale Economies and Agglomeration," as well as participants in seminars at Washington, Harvard, Penn State, and Clark Universities. Comments by Ed Glaeser spurred me to look at endogeneity issues more carefully. I also benefited from discussions with Tom Holmes. The research in this paper was conducted while the author was a Census Bureau research associate at the Boston

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This paper studies the advertising agency industry in Manhattan to infer networking benefits among agencies in close spatial proximity. We use economic census data that allow us to distinguish locations at a fine level of geographic detail, so as to infer the strong effect on productivity of having more near advertising agency neighbours. Paying close attention to identification issues, we show, however, that there is extremely rapid spatial decay in the benefits of more near neighbours, even in the close quarters of southern Manhattan, a finding that is new to the literature. This suggests that high density of similar commercial establishments is important in enhancing local productivity for those industries found in large cities, where information sharing plays a critical role. Our results indicate that the benefits of more near neighbours are largely capitalized into rents rather than wages, challenging an existing literature, which estimates wage equations alone to infer agglomeration benefits. Copyright © 2008 The Review of Economic Studies Limited.

This paper models and estimates net urban agglomeration economies for cities. Economic models of cities postulate an inverted U shape of real income per worker against city employment, where the inverted U shifts with industrial composition across the urban hierarchy of cities. This relationship has never been estimated, in part because of data requirements. China has the necessary data and context. We find that urban agglomeration benefits are high-real incomes per worker rise sharply with increases in city size from a low level. They level out nearer the peak and then decline very slowly past the peak. We find that a large fraction of cities in China are undersized due to nationally imposed, strong migration restrictions, resulting in large income losses. Copyright 2006 The Review of Economic Studies Limited.