Should-Attend: I think this paper is badly mistitled. It should be "Indiana Jones Gojko Barjamovica, Thomas Chaney, A. Kerem Cosar, Ali Hortacsu, and the Lost Cities of the Cuneiform Administrative Documents":

Gojko Barjamovica et al.: Trade, Merchants and Lost Cities of the Bronze Age: "Seminar 211: Economic History | October 16 | 2-3:30 p.m. | 597 Evans Hall...

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...Gojko Barjamovica, Thomas Chaney, A. Kerem Cosar, and Ali Hortacsu: Trade, Merchants and Lost Cities of the Bronze Age: We analyze a dataset of business documents inscribed in the cuneiform script and preserved on clay tablets informing us about the long-distance caravan trading system that connected northern Iraq, northern Syria and central Turkey in 19th century BCE. The standard gravity specification fits this ancient trade data remarkably well. Using data on modern-day trade of Turkish cities with Iraq and Syria, we find persistent patterns across four millennia. An inverse-gravity exercise suggests a methodology for estimating the location of lost cities. The size distribution of merchant coalitions is approximately Pareto...


  • 1000 copper = 10 silver = 1 gold
  • 1 shekel = 10 g
  • 1 deben = 80 g
  • 1 mina = 500 g
  • 1 talent = 30000 g

Econ au dk fileadmin Economics Business Research TGF DIEW2016 KCosar pdf

"Given the nature of the barter economies, it’s hard to characterize the value of copper as money or a trade good. Nevertheless, we know from historical records that 1 deben of copper (90 g) was worth 1 kit (9 g) of silver. We also know that a 58 kg sack of wheat traded for 2 debens. With wages for an unskilled laborer running at approximately 200 kg of grain per month, a day’s wage was worth something in the order of 31 g of copper – a price that works out to approximately $0.25 in today’s copper prices. Other known prices include 5 deben (450 g, or almost 1 pound) for a linen shirt and 140 deben for a cow. As is often the case, manufactured goods cost significantly more in the days before mass production..."


  • Construct ancient trade dataset...
  • Inverse gravity estimation...
  • Locate lost cities...
  • ????
  • PROFIT!

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