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– an interview with Professor Dr. Hubert Roeder, Weihenstephan-Triesdorf University of Applied Sciences

“The lower cost of wood pellets in comparison to fossil fuels is often one of the key arguments used to advertise this modern, renewable source of energy. But which factors actually influence the price of pellets? And is it even possible to forecast how the price of wood pellets will develop in Germany in the future? Professor Dr. Hubert Röder from Weihenstephan-Triesdorf University of Applied Sciences claims that it is. He will be presenting his model for predicting developments in the price of A1 wood pellets at the 14th Pellets Industry Forum. In an interview, he describes in advance the major factors influencing these trends.”

1. Professor Röder, how can current and previous price developments be used to draw conclusions about the future?
   It is a relatively established model. We used a multiple regression analysis to investigate which of 19 factors have historically had the greatest influence on the price of wood pellets. The figures analyzed included gas and oil price development data as well as those relating to the cost and availability of raw materials. We also examined the balance of foreign trade with pellets, by which I mean how the import of pellets has changed over time.
2. That sounds rather complex.
   The difficult part was managing to obtain a sequence that was consistent in terms of time. We consulted reference works to retrospectively compile quarterly figures from the last twelve years for all the indicators that we used. After completing our analyses, which we performed by undertaking a variety of statistical procedures, the main components with the most significant influence on pellet prices remained. We employed two models with four and six variables respectively to consolidate our results. Both achieve a coefficient of determination of around 85%, which means we can use the independent variables to calculate the wood pellets price with a probability of 85%.
3. Only a few of the 19 influencing factors have remained in your models. Why is this?
   There are factors that correlate closely with each other. While they still exert an influence, there are other similar factors that have a greater impact.
4. Which factors did you find to be particularly influential?
   The cost of raw materials is by far the most significant factor. Other important elements are the balance of foreign trade, the price of gas and an index of competition between pellet producers. There are indices that can be used to depict the level of competition within an industry. We have calculated these and applied them in the model.
   
   
5. So when calculating the price of pellets in 2020, you must above all be able to forecast the cost of raw materials?
   Yes, that’s right. We have developed a model for calculating the price of pellets using other variables and we are trying to produce forecasts for the future developments of these few variables. Scenarios generally have to be employed for this. While the price of gas is predicted by various institutions, we have to use scenarios to calculate the price of wood as a raw material, which is our key influential factor. Preparing a forecast for the price of wood as a raw material would be a job in itself and in Germany would require regional differences to be taken into account. During my time working for the consulting firm Pöyry, we always calculated this on a case-by-case basis. However, for our current project we have made basic assumptions by forecasting how the production capacity of raw materials required to produce wood pellets in Germany and the volume of imports will develop.
6. What led to the launch of this project?
   At Pöyry I was involved in a multi-client study on the global pellet market. During this project, we calculated worldwide developments in the wood pellet industry and examined the availability of raw materials, production capacities and price developments. In doing so, we noticed that the quantities available in individual countries were easier to express using a model. At that time, we asked ourselves how we could develop a wood pellet pricing model for different countries. I raised the idea with the University and found a student to investigate the topic. My former colleagues from Pöyry and I supervised the student’s master’s thesis together.