Climate change is predicted to substantially alter forest growth. Optimally, forest owners should take these future changes into account when making rotation decisions today. However, the fundamental uncertainty surrounding climate change makes predicting these shifts hard. Hence, this paper...

Climate change is predicted to substantially alter forest growth. Optimally, forest owners should take these future changes into account when making rotation decisions today. However, the fundamental uncertainty surrounding climate change makes predicting these shifts hard. Hence, this paper...

Robust forecasting of mining sector revenues is key to effective budgeting (and broader fiscal management) in many resource-rich countries. However, this is challenging in practice, given commodity market volatility, the extended lags (and often opaque processes) between resource discoveries and...

A multi-factor carbon price prediction method MEEMD-LSTM is proposed based on traditional Long Short-term Memory (LSTM) neural network. Multi-factor used in carbon price prediction method included the historical carbon price and other factors which affect carbon price fluctuation. The change...

Modeling the price risk of CO2 certificates is one important aspect of integral corporate risk management related to emissions trading. The paper presents a risk model which may be the basis for evaluating the risk of emission certificate prices. We assume that the certificate price is...

Modeling the price risk of CO2 certificates is one important aspect of integral corporate risk management related to emissions trading. The paper presents a risk model which may be the basis for evaluating the risk of emission certificate prices. We assume that the certificate price is...

We argue that gamma discounting (Weitzman, 2001) can be understood as a veridical approach to combining experts' forecasts, in which experts are treated as either right or wrong and are weighted equally in pursuit of the 'true' forecast. More appropriate is the optimal-seeking approach in which...