This paper explores how a principal with time-inconsistent preferences invests optimally in technology or capital. If the current principal prefers her future self to save more, she can increase current investments complementary to future savings and decrease investments in the strategic...

This paper explores how a principal with time-inconsistent preferences invests optimally in technology or capital. If the current principal prefers her future self to save more, she can increase current investments complementary to future savings and decrease investments in the strategic...

We analyze a repeated game in which countries are polluting as well as investing in technologies. While folk theorems point out that the first best can be sustained as a subgame-perfect equilibrium when the players are sufficiently patient, we derive the second best equilibrium when they are...

We characterize the optimal policy and policy instruments for self-enforcing treaties when countries invest in green technology before they pollute. If the discount factor is too small to support the first best, then both emissions and investments will be larger than in the first best, when...

This paper explores how a principal with time-inconsistent preferences invests optimally in technology or capital. If the current principal prefers her future self to save more, she can increase current investments complementary to future savings and decrease investments in the strategic...

We analyze a repeated game in which countries are polluting as well as investing in technologies. While folk theorems point out that the first best can be sustained as a subgame-perfect equilibrium when the players are sufficiently patient, we derive the second best equilibrium when they are...

We characterize the optimal policy and policy instruments for self-enforcing treaties when countries invest in green technology before they pollute. If the discount factor is too small to support the first best, then both emissions and investments will be larger than in the first best, when...