In their post on the World Bank blog, Dr. Quy-Toan Do, Dr. Andrei Levchenko, and Dr. Lin Ma (DLM for short) make three claims that they suggest undermine our finding that the 2008 one-time sale of ivory corresponded with a discontinuous 66% increase in elephant poaching globally. First, they claim that the discontinuity vanishes for sites reporting a large number of carcasses—i.e., there was only a sudden increase in poaching in 2008 at sites reporting a small number of total carcasses. Second, they claim that price data for ivory (which they do not make public) from TRAFFIC do not show the increase in 2008 that they argue would be expected if the one-time sale had affected ivory markets. Third, they claim that re-assigning a seemingly small proportion of illegal carcasses counted in 2008 to be legal carcasses makes the finding of a discontinuity in 2008 less than statistically significant, and they speculate that a MIKE (CITES) initiative to improve carcass classification may explain the discontinuous increase in poaching in sites with small numbers of carcasses.
In this post, we systematically demonstrate that none of these concerns are valid. First, as it turns out, the discontinuity does hold for sites reporting a large number of carcasses, so long as one does not commit a coding error that causes a systematic omission of data where poaching was lower before the one-time sale, as did DLM. Furthermore, we show that DLM misreported methods and excluded results that contradicted their narrative, and that they made other smaller coding errors in this part of their analysis. Second, we note that, notwithstanding various concerns we have about the ivory price data, our original paper had already derived why an increase in poaching due to the one-time sale would not have a predictable (and possibly no) effect on black market ivory prices. Finally, we note that (i) DLM provide no evidence that training on carcass identification could have led to a discontinuous change in PIKE (in fact, the provided evidence contradicts that hypothesis), and that (ii) in the contrived reclassification exercise modeled by DLM, the likelihood of surveyors making the seven simultaneous errors DLM state is very likely is in fact, under generous assumptions, actually less than 0.35%— i.e. extraordinarily unlikely.
Overall, while DLM motivated an interesting exercise in which we show that our result is robust to classification of sites based on the number of carcasses found, they provided no valid critiques to our analytical approach or results. The central conclusion, that our results should be dismissed, was the result of a sequence of coding, inferential, and logical errors.