Government Reputation and Fiscal Capacity
Emin Ablyatifov and
Georgy Lukyanov
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Emin Ablyatifov: Unknown
Georgy Lukyanov: TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement
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Abstract:
How does uncertain implementation shape fiscal policy over time? We study an uninformed fiscal authority that chooses a distortionary tax-financed mandate and audit intensity while a privately informed executive decides whether to deliver or divert the proceeds. Reputation is the Bayesian state variable linking current fiscal control to future capacity. In a two-period benchmark, a mandate is also an experiment: delivery sacrifices current rents but preserves future access. We prove that the dynamic activation threshold is no greater than the square of the static reputation cutoff; the bound is exact and independent of discounting in a linear-benefit, quadratic-cost economy. A positive trial mandate may therefore be optimal when every positive tax is statically undesirable. In the infinite-horizon model, posterior reputation is a bounded martingale and its one-step conditional variance admits an exact policy-dependent formula. Zero mandates can create closed inactive classes in which fiscal activity and learning stop together. On a finite approximation, we compute stationary equilibria with noisy signals, endogenous auditing, and spending-need shocks and certify them against every action in a common adaptive cloud. The equilibria display history-dependent limiting fiscal capacity, non-monotone auditing, and nonlinear responses to spending need: shocks leave mean reputation unchanged but alter its dispersion and exposure to the inactive region.
Keywords: Optimal taxation; Government reputation; Ramsey problem; Credibility; Fiscal capacity (search for similar items in EconPapers)
Date: 2026-10-21
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