Spatial Diffusion of Economic Shocks in Networks
Paul Raschky () and
Yves Zenou ()
No 12854, CEPR Discussion Papers from C.E.P.R. Discussion Papers
The aggregate economic impact of any developmental project depends on its effects within the chosen administrative region as well as its economic spillovers into other regions. However, little is known about how these spillovers propagate through geographic, ethnic and road networks. In this paper, we analyze both theoretically and empirically the role of these networks in the spatial diffusion of local economic shocks. We develop a network model that shows how a district's level of prosperity is related to its position in the network. The network model's first-order conditions are used to derive an econometric model of spatial spillovers that we estimate using a panel of 5,944 districts from 53 African countries over the period 1997-2013. To identify the causal effect of spatial diffusion, we exploit cross sectional variation in the location of mineral mines and exogenous time variation in world mineral prices. Our results show that road and ethnic connectivity are particularly important factors for diffusing economic spillovers over longer distances. We then use the estimated parameters from the econometric model to calculate the key player centralities, which determine which districts are key in propagating local economic shocks across Africa. We further show how counterfactual exercises based on these estimates and the underlying network structure can inform us about the potential gains from policies that increase economic activity in specific districts or improve road connectivity between districts.
Keywords: economic development; key player centrality; Natural resources; networks; spatial spillovers; Sub-Saharan Africa; Transportation (search for similar items in EconPapers)
JEL-codes: O13 O55 R12 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-dev, nep-net and nep-ure
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Working Paper: Spatial Diffusion of Economic Shocks in Networks (2018)
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