Asymptotic equivalence for inhomogeneous jump diffusion processes and white noise

We prove the global asymptotic equivalence between the experiments generated by the discrete (high frequency) or continuous observation of a path of a time inhomogeneous jump-diffusion process and a Gaussian white noise experiment. Here, the considered parameter is the drift function, and we suppose that the observation time $T$ tends to $\infty$. The approximation is given in the sense of the Le Cam $\Delta$-distance, under smoothness conditions on the unknown drift function. These asymptotic equivalences are established by constructing explicit Markov kernels that can be used to reproduce one experiment from the other.Comment: 20 pages; to appear on ESAIM: P\&S. In this version there are some improvements in the exposition following the reports suggestion

Credit risk transfers and the macroeconomy : [This Draft: September 2010]

The recent financial crisis has highlighted the limits of the “originate to distribute” model of banking, but its nexus with the macroeconomy and monetary policy remains unexplored. I build a DSGE model with banks (along the lines of Holmström and Tirole [28] and Parlour and Plantin [39] and examine its properties with and without active secondary markets for credit risk transfer. The possibility of transferring credit reduces the impact of liquidity shocks on bank balance sheets, but also reduces the bank incentive to monitor. As a result, secondary markets allow to release bank capital and exacerbate the effect of productivity and other macroeconomic shocks on output and inflation. By offering a possibility of capital recycling and by reducing bank monitoring, secondary credit markets in general equilibrium allow banks to take on more risk. Keywords: Credit Risk Transfer , Dual Moral Hazard , Monetary Policy , Liquidity , Welfare JEL Classification: E3, E5, G3 First Draft: December 2009, This Draft: September 201

Asymptotic equivalence for density estimation and gaussian white noise: An extension

The aim of this paper is to present an extension of the well-known as-ymptotic equivalence between density estimation experiments and a Gaussian white noise model. Our extension consists in enlarging the nonparametric class of the admissible densities. More precisely, we propose a way to allow densities defined on any subinterval of R, and also some discontinuous or unbounded densities are considered (so long as the discontinuity and unboundedness patterns are somehow known a priori). The concept of equivalence that we shall adopt is in the sense of the Le Cam distance between statistical models. The results are constructive: all the asymptotic equivalences are established by constructing explicit Markov kernels.Comment: 11 pages. arXiv admin note: text overlap with arXiv:1503.0453

Optimal monetary policy rules with labor market frictions

This paper studies optimal monetary policy rules in a framework with sticky prices, matching frictions and real wage rigidities. Optimal monetary policy is given by a constrained Ramsey plan in which the monetary authority maximizes the agents’ welfare subject to the competitive economy relations and the assumed monetary policy rule. I find that optimal policy should deviate from the strict inflation targeting since the policy maker faces a typical unemployment/inflation trade-off. In this context and unlike a standard New Keynesian model stabilizing inflation is not sufficient to stabilize the marginal cost (hence the output gap) since the latter also depends on the evolution of unemployment. The matching frictions add a congestion externality since the number of unemployed in the market and their bargaining power reduce the probability of forming matches. Hence optimal monetary policy features unemployment targeting along with inflation targeting. JEL Classification: E52, E24matching frictions, optimal monetary policy rules, wage rigidity