Vicente Jimenez-Gimpel

Monetary policy works largely through expectations: long yields, mortgage rates, and investment depend on expected policy, which markets infer from the central bank's decisions. We build a model in which policy partially reveals the central bank's persistent private assessments, making the sensitivity of market beliefs to policy surprises—and hence monetary transmission—an equilibrium object shaped by systematic policy. A central bank deciding meeting by meeting takes this sensitivity as given, leaving misinterpretation-driven volatility inefficiently high; the optimal ex-ante rule internalizes its effect and lowers it. This commitment gap is a novel form of time inconsistency: it concerns not the promise of future policy but how the systematic rule shapes what today's decision reveals. If the central bank is unsure how markets read its decisions, it becomes cautious, and since policy shapes that uncertainty, caution can be self-reinforcing and have dire welfare consequences. In a richer model disciplined by U.S. macro data, Federal Reserve real-time forecasts, and inflation swaps, commitment sharply dampens belief sensitivity and cuts inefficient output fluctuations by roughly three quarters. These gains are much smaller when the central bank's assessments are public: commitment's value lies mainly in shaping how strongly expectations react to policy surprises.

This paper develops a theory of forward guidance that captures two key features of central bank communication: announcements are not fully state-contingent, and the private sector is wary of policy mistakes. The central bank tailors announcements along two dimensions: (i) vagueness—how tightly the announcement constrains future policy; and (ii) data dependence—how aggressively future policy responds to a public signal of the economy. Three main lessons emerge. First, uncertainty affects communication differently depending on its source: uncertainty about both demand and cost-push shocks increases optimal vagueness, but only demand-side uncertainty increases the optimal degree of data dependence. Second, strict rules are costly: fully precise guidance entails sizable welfare losses that grow with the steepness of the Phillips curve. Third, because of the stabilizing role of announcements, optimal forward guidance differs sharply from simply communicating the best forecast of the future optimal policy rate (Delphic guidance)

A mechanism-design analysis of cost-minimizing procurement from multiple firms with private convex costs, motivated by buying back pollution permits. The thesis characterizes the optimal mechanism and a simpler “sequentially optimal” alternative that runs procurement sequentially—so offers need not depend on the private information of all other firms at once—and finds numerically that the sequentially optimal mechanism is near-optimal, while sequential posted prices perform much worse.