I gave a talk at the Fall CNI meeting on the work I've been doing on economic models of long-term storage. CNI recorded the talk and I'm expecting them to post the video and the slides. Much of the talk expanded on the talk I gave at the Library of Congress Storage Workshop. The new part was that I managed to remove the assumption that storage prices could never go up, so I was able to model the effect of spikes in storage costs, such as those caused by the floods in Thailand.. Below the fold is the graph.
The Z-axis shows the ratio between the endowment needed for 98% probability of not running out of money in 100 years. The X axis shows the annual percentage rate at which the cost of storage decreases in the absence of the spike. The Y=0 axis assumes no spike in costs. The rest of the Y axis shows the effect of a spike that doubles costs, and takes two years to drop back to its pre-spike value, occurring at Y years after the start.
As you see, if storage costs drop rapidly, the spike has little effect, but if they drop slowly it can have a big impact. Note the "ridge" at Y=4, which is caused by the model's assumption of a 4-year service life for storage hardware. If costs spike just as your current hardware gets to the end of its service life, you are in a world of hurt.