We study the repeated implementation of social choice functions in environments with complete information and changing preferences. We define dynamic monotonicity, a natural but non-trivial dynamic extension of Maskin monotonicity, and show that it is necessary and almost sufficient for repeated Nash implementation, regardless of whether the horizon is finite or infinite and whether the discount factor is “large” or “small
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