This is pretty cool – an interactive website that lets you explore a real-world carbon trading research problem while learning new tricks in R.

Many economists would agree that the most efficient way to fight global warming would be a world-wide tax or an emmission trading system for greenhouse gases. Yet, if only a part of the world implements such a scheme, a reasonable concern is that firms may decide to relocate to other parts of the world, causing job losses and less effective emmission reduction…

In their article ‘Industry Compensation under Relocation Risk: A Firm-Level Analysis of the EU Emissions Trading Scheme’ (American Economic Review, 2014), Ralf Martin, Mirabelle Muûls, Laure B. de Preux and Ulrich J. Wagner study the most efficient way to allocate a fixed amount of free permits among facilities in order to minimize the risk of job losses or carbon leakage. Given their available data, they establish simple alternative allocation rules that can be expected to substantially outperform the current allocation rules used by the EU.

As part of his Master’s Thesis at Ulm University, Benjamin Lux has generated a very nice RTutor problem set that allows you to replicate the insights of the paper in an interactive fashion. You learn about the data and institutional background, run explorative regressions and dig into the very well explained optimization procedures to find efficient allocation rules. At the same time you learn some R tricks, like effective usage of some dplyr functions.

It’s an interesting question at a time when some U.S. states and Canadian provinces have started introducing carbon trading and taxation schemes that differ from their neighbors (sometimes because their neighbors have nothing at all). Perhaps there is a win-win where a policy can gradually phase out less productive, dirtier industries while replacing them with cleaner and higher-value-added industries, then sharing enough of the wealth so everyone benefits.