Thanks for the follow-up, Karen.

As mentioned in the TIMES documentation, in the perfect foresight mode the TIMES model has "complete knowledge of the market's parameters, present and future. Hence, the equilibrium is computed by maximizing total surplus in one pass for the entire set of periods."

When solving the model by optimizing with perfect foresight, the model does not iterate over the periods considered, but all model periods are optimized simultaneously. This type of model solution is also called inter-temporal optimization. And it has the mathematical property that all the prices in all of the model periods are known when optimizing the decision variables in any period (e.g. investments in 2006).

For another reference, you could, for example, see what the International Handbook on the Economics of Energy (2009) says about perfect foresight models:

http://books.google.fi/books?id=7XWzMbuAHusC

Quote from page 62: "A major criticism of most models of optimal extraction of a depletable resource is that they are 'perfect foresight' in nature. In particular, the dynamic optimization framework used in such models allows all future prices to influence the current outcome, meaning we typically solve for optimal paths."

Quote from page 261: "Perhaps one of the most limiting is the assumption of perfect foresight over the forecast horizon. This assumption results in 'optimistic' solutions based on the underlying assumption of perfect knowledge by firms and consumers of not only current but future energy prices as well as technology and technological change."

I am not sure whether these explanations can convince you. But as far as I understand, the inter-temporal optimization mode of TIMES can, indeed, take into account the inter-dependencies between e.g. the investment decisions in 2006 and the endogenous prices in 2020, simultaneously.

As mentioned in the TIMES documentation, in the perfect foresight mode the TIMES model has "complete knowledge of the market's parameters, present and future. Hence, the equilibrium is computed by maximizing total surplus in one pass for the entire set of periods."

When solving the model by optimizing with perfect foresight, the model does not iterate over the periods considered, but all model periods are optimized simultaneously. This type of model solution is also called inter-temporal optimization. And it has the mathematical property that all the prices in all of the model periods are known when optimizing the decision variables in any period (e.g. investments in 2006).

For another reference, you could, for example, see what the International Handbook on the Economics of Energy (2009) says about perfect foresight models:

http://books.google.fi/books?id=7XWzMbuAHusC

Quote from page 62: "A major criticism of most models of optimal extraction of a depletable resource is that they are 'perfect foresight' in nature. In particular, the dynamic optimization framework used in such models allows all future prices to influence the current outcome, meaning we typically solve for optimal paths."

Quote from page 261: "Perhaps one of the most limiting is the assumption of perfect foresight over the forecast horizon. This assumption results in 'optimistic' solutions based on the underlying assumption of perfect knowledge by firms and consumers of not only current but future energy prices as well as technology and technological change."

I am not sure whether these explanations can convince you. But as far as I understand, the inter-temporal optimization mode of TIMES can, indeed, take into account the inter-dependencies between e.g. the investment decisions in 2006 and the endogenous prices in 2020, simultaneously.

Anyway, in TIMES you are by no means limited to the perfect foresight assumption, but can choose between various alternative ways of running the model.