We developed a sustainability index (SREE) to permit peer-to-peer comparisons among rare earths projects.

Traditionally the rare earths industry has been using heavy vs light rare earth ratios as predictors of success. In practice this approach is best suited for precious metal projects where success is a correlate of cost of production against the price of gold.

But limited market demand and complex ore composition bring challenges for traditional peer-to-peer comparison among rare earths projects. There is a great deal of variance in the ore composition of deposits, and their sustainability is further affected by location, capital costs and a plurality of other factors that cannot be consolidated into a simple dependant variable such as “cost per once” as in the case of precious metals.

We have a burden of responsibility because the livelihood of many and investor’s money depends on our analyses. And so, we have developed a sustainability index based on multiple regression analyses to permit a weighed comparison among rare earths projects. Multiple regressions are routinely used in social sciences and in ecology but not in mining.

The general purpose of multiple regressions is to learn more about the relationship between several independent or predictor variables and a dependent or criterion variable. For example, a real estate agent might record for each listing the size of the house (in square feet), the number of bedrooms, the average income in the respective neighborhood according to census data, and a subjective rating of appeal of the house. Once this information has been compiled for various houses it would be interesting to see whether and how these measures relate to the price for which a house is sold. For example, you might learn that the number of bedrooms is a better predictor of the price for which a house sells in a particular neighborhood than how “pretty” the house is (subjective rating). You may also detect “outliers,” that is, houses that should really sell for more, given their location and characteristics.

In the social and natural sciences multiple regression procedures are very widely used in research. In general, multiple regression allows the researcher to ask (and hopefully answer) the general question “what is the best predictor of …”. For example, educational researchers might want to learn what are the best predictors of success in high school. Psychologists may want to determine which personality variable best predicts social adjustment. Sociologists may want to find out which of the multiple social indicators best predict whether or not a new immigrant group will adapt and be absorbed into society. In short, predicting the success of rare earths project is quite similar because of the complexity of variables at play.

The trick to multiple regressions is to build a sturdy mathematical model that can be tweaked through trial and errors, and supported by caffeine in industrial amounts.

We arrived to the conclusion that the sustainability of rare earth projects is a correlation of the contribution of Neodymium, Praseodymium, Terbium and Dysprosium to revenue models. We included a subfunction to account for revenues per tonne of ore. We added subfunctions to take into account financial metrics that influence the probability of success such as market cap, enterprise value cash at hand, which are determinants of success in the rare earth industry.

We based the sustainability index (SREE) on the following formula:

SREE= [A Ÿ (Nd&Pr)] + [B Ÿ (Nd&Pr&Tb&Dy)] + [C Ÿ Revenues per tonne]+ [D Ÿ (Nd&Pr)/revenues] + [E Ÿ (Nd&Pr&Tb&Dy)/revenues] + [F Ÿ Market cap] + [G Ÿ Enterprise values] + [H Ÿ Cash in the bank] where A, B, C, D, E, D, F, and H are numerical determinants that control the relative weight of each of the variables.

To help understand the structure of SREE the table below (SAMPLE) shows data from different rare earth projects as of September 1, 2015 — this data was collated from public sources. The different colours shows qualitative weighing of data point. Each line represents one rare earth project.