An Investigation of the Gains from Commitment in Monetary Policy

This paper proposes a simple framework for analyzing a continuum of monetary policy rules characterized by differing degrees of credibility, in which commitment and discretion become special cases of what we call quasi commitment. The monetary policy authority is assumed to formulate optimal commitment plans, to be tempted to renege on them, and to succumb to this temptation with a constant exogenous probability known to the private sector. By interpreting this probability as a continuous measure of the (lack of) credibility of the monetary policy authority, we investigate the welfare effect of a marginal increase in credibility. Our main finding is that, in a simple model of the monetary transmission mechanism, most of the gains from commitment accrue at relatively low levels of credibility. In our benchmark calibration, a commitment expected to last for only 6 quarters is enough to bridge 75% of the welfare gap between discretion and commitment. This seems to justify the well known concern of monetary policy makers about their credibility, even in a world with limited access to commitment technologiesCommitment, discretion, credibility, welfare

An Investigation of the Gains from Commitment in Monetary Policy

This paper proposes a simple framework for analyzing a continuum of monetary policy rules characterized by differing degrees of credibility, in which commitment and discretion become special cases of what we call quasi commitment. The monetary policy authority is assumed to formulate optimal commitment plans, to be tempted to renege on them, and to succumb to this temptation with a constant exogenous probability known to the private sector. By interpreting this probability as a continuous measure of the (lack of) credibility of the monetary policy authority, we investigate the welfare effect of a marginal increase in credibility. Our main finding is that, in a simple model of the monetary transmission mechanism, most of the gains from commitment accrue at relatively low levels of credibility. In our benchmark calibration, a commitment expected to last for only 6 quarters is enough to bridge 75% of the welfare gap between discretion and commitment. This seems to justify the well known concern of monetary policy makers about their credibility, even in a world with limited access to commitment technologies.Commitment, discretion, credibility, welfare

Intertemporal disturbances

Disturbances affecting agents' intertemporal substitution are the key driving force of macroeconomic fluctuations. We reach this conclusion exploiting the asset pricing implications of an estimated general equilibrium model of the U.S. business cycle with a rich set of real and nominal frictionsBusiness Cycle, Fluctuations, Euler equation, shocks, frictions

Calculating and Using Second Order Accurate Solutions of Discrete Time Dynamic Equilibrium Models

We describe an algorithm for calculating second order approximations to the solutions to nonlinear stochastic rational expectations models. The paper also explains methods for using such an approximate solution to generate forecasts, simulated time paths for the model, and evaluations of expected welfare differences across different versions of a model. The paper gives conditions for local validity of the approximation that allow for disturbance distributions with unbounded support and allow for non-stationarity of the solution process.

Causes of the Great Recession of 2007-9: The Financial Crisis is the Symptom not the Disease!

Globalization has made it possible for labor in developing countries to augment labor in the developed world, without having to relocate, in ways not thought possible only a few decades ago. We argue that this large increase in the developed world’s effective labor supply, triggered by geo-political events and technological innovations, coupled with the inability of existing institutions in the US and developing nations themselves to cope with this shock set the stage for the great recession. The financial crisis in the US was but the first acute symptom.

Jump-Robust Volatility Estimation using Nearest Neighbor Truncation

We propose two new jump-robust estimators of integrated variance based on high-frequency return observations. These MinRV and MedRV estimators provide an attractive alternative to the prevailing bipower and multipower variation measures. Specifically, the MedRV estimator has better theoretical efficiency properties than the tripower variation measure and displays better finite-sample robustness to both jumps and the occurrence of "zero'' returns in the sample. Unlike the bipower variation measure, the new estimators allow for the development of an asymptotic limit theory in the presence of jumps. Finally, they retain the local nature associated with the low order multipower variation measures. This proves essential for alleviating finite sample biases arising from the pronounced intraday volatility pattern which afflict alternative jump-robust estimators based on longer blocks of returns. An empirical investigation of the Dow Jones 30 stocks and an extensive simulation study corroborate the robustness and efficiency properties of the new estimators.

A Functional Filtering and Neighborhood Truncation Approach to Integrated Quarticity Estimation

We provide a first in-depth look at robust estimation of integrated quarticity (IQ) based on high frequency data. IQ is the key ingredient enabling inference about volatility and the presence of jumps in financial time series and is thus of considerable interest in applications. We document the significant empirical challenges for IQ estimation posed by commonly encountered data imperfections and set forth three complementary approaches for improving IQ based inference. First, we show that many common deviations from the jump diffusive null can be dealt with by a novel filtering scheme that generalizes truncation of individual returns to truncation of arbitrary functionals on return blocks. Second, we propose a new family of efficient robust neighborhood truncation (RNT) estimators for integrated power variation based on order statistics of a set of unbiased local power variation estimators on a block of returns. Third, we find that ratio-based inference, originally proposed by Barndorff-Nielsen and Shephard, has desirable robustness properties and is well suited for our empirical applications. We confirm that the proposed filtering scheme and the RNT estimators perform well in our extensive simulation designs and in an application to the individual Dow Jones 30 stocks.