As strange as it might seem considering the increasingly frightening data and scientific studies being published nearly data (Greenland’s Melting Ice Nears a ‘Tipping Point,’ Scientists Say – NY Times, Oceans warming faster than expected: scientists – Reuters), the effects of climate change are not yet thought of as “Bad” by most Americans.
Despite your humble correspondent’s best attempts, many people simply do not perceive the effects of climate change as exerting a significantly negative impact on the economy or on their daily lives.
This perception will change over the next five to ten years, but one big issue for investors is that it is impossible to know what event or tipping point will cause a change in attitudes sufficient to create an investing catalyst.
This timing issue has already created problems for some very smart capital allocators.
According to an MIT working paper, cleantech investors (mainly VC funds) lost over half the estimated $25 billion in capital deployed in the sector throughout the 2006-2011 period – a figure that included such infamous debacles as Solyndra and KiOR. Japan’s Nihon Keizai Shimbun, quotes the Japan Greenhouse Horticulture Association’s assessment that 60% of all vertical farming ventures in Japan have failed to generate profits, despite high food prices and government subsidies.
Considering these frightening precedents of value destruction, the key to investing in this field is good risk control. Intelligent climate change investors must take steps to limit economic exposure to expensive failures while, at the same time, preserving exposure to the enormous upside potential brought about by the upcoming paradigm shift.
The most important first step in risk control is properly understanding at what stage of development a new adaptation technology stands.
My mental model splits technologies into three categories:
- Evolutionary application of current technology (e.g., improvements to Lithium ion batteries and development of a powerwall)
- Novel adaptation of current technology (e.g., applying sensors and pattern recognition algorithms, IoT, robots, LEDs, and crop sciences to grow food in indoor vertical farms)
- Revolutionary development of new science (e.g., Clean Meat, algal biofuels)
Companies marketing evolutionary applications have the least valuation uncertainty; those marketing revolutionary developments have the most.