Global warming, sea level rise, and extreme weather events have made climate change a top priority for policymakers across the globe. But which policies are best suited to tackle the enormous challenges presented by our changing climate? This Article proposes that policymakers turn to prediction...

Two and a half decades of clean energy policymaking focused primarily on environmental and economic sustainability have yielded considerable environmental and economic benefits. Along the way, however, other policy considerations, such as the social sustainability of the transition to a cleaner,...

This article introduces an investor-oriented framework for the evaluation of renewable energy policy, applies these newly developed criteria to a qualitative comparison of the primary policy instruments, and offers recommendations to enhance the investor appeal of renewable energy in the United...

We examine the relationship between a tree price and a tree age (height) using a Hotelling-Faustmann model of optimal plantation management, which accounts for the possibility of replanting and biological growth. The model's predictions are tested using the data on Christmas tree prices in North...

We examine the relationship between a tree price and a tree age (height) using a Hotelling-Faustmann model of optimal plantation management, which accounts for the possibility of replanting and biological growth. The model's predictions are tested using the data on Christmas tree prices in North...

We analyse the drivers of European Power Exchange (EPEX) wholesale electricity prices between 2012 and early 2022 using machine learning. The agnostic random forest approach that we use is able to reduce in-sample root mean square errors (RMSEs) by around 50% when compared to a standard linear...

Financing renewable energy projects in the United States can be a complex, time consuming, and expensive process. Currently, most equity investment in new renewable power production facilities is supported by tax credits and accelerated depreciation benefits, and is constrained by the pool of...

We analyse the drivers of European Power Exchange (EPEX) retail electricity prices between 2012 and early 2022 using machine learning. The agnostic random forest approach that we use is able to reduce in-sample root mean square errors (RMSEs) by around 50% when compared to a standard linear...

We analyse the drivers of European Power Exchange (EPEX) wholesale electricity prices between 2012 and early 2022 using machine learning. The agnostic random forest approach that we use is able to reduce in-sample root mean square errors (RMSEs) by around 50% when compared to a standard linear...