Association for Public Policy Analysis & Management

The black market in Syrian antiquities has recently risen to international prominence because of its possible connection to terrorist organizations, as well as the irreparable damage to scientific knowledge being caused by widespread looting. As with many black markets, our understanding of the antiquities market is hindered by its opacity. But understanding the market’s composition and supply channels is important for optimizing counter-terrorism efforts, allocating limited resources to protect cultural heritage sites, and designing international regulations to mitigate antiquities trafficking. So far, only anecdotal evidence has surfaced to indicate the types of objects entering the black market, and the prices they fetch.

This paper outlines a method for using visible (publicly available) data to impute characteristics of the invisible black market. The method follows a growing trend to use “big data” to answer important policy questions in archaeology; unlike past studies that focus on satellite imagery, our data consist of comprehensive archaeological excavation records and detailed observations of thousands of market sales records. We develop a text-categorization procedure to standardize the sales records’ descriptive text. This categorization produces hundreds of variables that are input to a machine learning algorithm to match objects between two new datasets, thereby allowing us to impute market prices for excavated objects. We then extrapolate the archaeological data to impute the contents and value of looters' pits in the vicinity of the excavations. This method provides the first scientifically-based estimate of the value and composition of the black market.

We discuss several policy-relevant insights that revise our understanding of the antiquities supply chain, the most at-risk sites in the region, and the potential revenue flows to different groups. Although the looting literature has focused on objects with high monetary value, we find high aggregate values for relatively small objects, which are easier to smuggle and are found in abundance. We calculate that our case study sites would be worth a few million dollars each; based on this, we contextualize previous estimates of the value of the antiquities trade (and particularly the revenues made by terror groups). We further discuss how these results might be extended to the rest of the Syria/Iraq region, how the method may be replicated for other sites and regions of the world, and whether the basic framework might apply to studies of other black markets.