Monday 13 November 2017

Trade, merchants, and the lost cities of the Bronze Age

An interesting new NBER working paper on Trade, Merchants, and the Lost Cities of the Bronze Age by Gojko Barjamovic, Thomas Chaney, Kerem A. Coşar and Ali Hortaçsu.

NBER Working Paper No. 23992
Issued in November 2017
NBER Program(s): ITI
We analyze a large dataset of commercial records produced by Assyrian merchants in the 19th Century BCE. Using the information collected from these records, we estimate a structural gravity model of long-distance trade in the Bronze Age. We use our structural gravity model to locate lost ancient cities. In many instances, our structural estimates confirm the conjectures of historians who follow different methodologies. In some instances, our estimates confirm one conjecture against others. Confronting our structural estimates for ancient city sizes to modern data on population, income, and regional trade, we document persistent patterns in the distribution of city sizes across four millennia, even after controlling for time-invariant geographic attributes such as agricultural suitability. Finally, we offer evidence in support of the hypothesis that large cities tend to emerge at the intersections of natural transport routes, as dictated by topography.
Alex Tabarrok writes on this paper at Marginal Revolution:
In a stunningly original paper Gojko Barjamovic, Thomas Chaney, Kerem A. Coşar, and Ali Hortaçsu use the gravity model of trade to infer the location of lost cities from Bronze age Assyria! The simplest gravity model makes predictions about trade flows based on the sizes of cities and the distances between them. More complicated models add costs based on geographic barriers. The authors have data from ancient texts on trade flows between all the cities, they know the locations of some of the cities, and they know the geography of the region. Using this data they can invert the gravity model and, triangulating from the known cities, find the lost cities that would best “fit” the model. In other words, by assuming the model is true the authors can predict where the lost cities should be located. To test the idea the authors pretend that some known cities are lost and amazingly the model is able to accurately rediscover those cities.

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