Search Results
Working Paper
Uniform Priors for Impulse Responses
There has been a call for caution when using the conventional method for Bayesian inference in set-identified structural vector autoregressions on the grounds that the uniform prior over the set of orthogonal matrices could be nonuniform for key objects of interest. This paper challenges this call. Although the prior distributions of individual impulse responses induced by the conventional method may be nonuniform, they typically do not drive the posteriors if one does not condition on the reduced-form parameters. Importantly, when the focus is on joint inference, the uniform prior over the ...
Working Paper
Asymmetric expectation effects of regime shifts in monetary policy
This paper addresses two substantive issues: (1) Does the magnitude of the expectation effect of regime switching in monetary policy depend on a particular policy regime? (2) Under which regime is the expectation effect quantitatively important? Using two canonical DSGE models, we show that there exists asymmetry in the expectation effect across regimes. The expectation effect under the dovish policy regime is quantitatively more important than that under the hawkish regime. These results suggest that the possibility of regime shifts in monetary policy can have important effects on rational ...
Working Paper
The Dynamic Striated Metropolis-Hastings Sampler for High-Dimensional Models
Having efficient and accurate samplers for simulating the posterior distribution is crucial for Bayesian analysis. We develop a generic posterior simulator called the "dynamic striated Metropolis-Hastings (DSMH)" sampler. Grounded in the Metropolis-Hastings algorithm, it draws its strengths from both the equi-energy sampler and the sequential Monte Carlo sampler by avoiding the weaknesses of the straight Metropolis-Hastings algorithm as well as those of importance sampling. In particular, the DSMH sampler possesses the capacity to cope with incredibly irregular distributions that are full ...
Working Paper
Methods for inference in large multiple-equation Markov-switching models
The inference for hidden Markov chain models in which the structure is a multiple-equation macroeconomic model raises a number of difficulties that are not as likely to appear in smaller models. One is likely to want to allow for many states in the Markov chain without allowing the number of free parameters in the transition matrix to grow as the square of the number of states but also without losing a convenient form for the posterior distribution of the transition matrix. Calculation of marginal data densities for assessing model fit is often difficult in high-dimensional models and seems ...
Working Paper
Evaluating Wall Street Journal survey forecasters: a multivariate approach
This paper proposes a methodology for assessing the joint performance of multivariate forecasts of economic variables. The methodology is illustrated by comparing the rankings of forecasters by the Wall Street Journal with the authors? alternative rankings. The results show that the methodology can provide useful insights as to the certainty of forecasts as well as the extent to which various forecasts are similar or different.
Working Paper
The Transmission of Financial Shocks and Leverage of Financial Institutions: An Endogenous Regime-Switching Framework
We conduct a novel empirical analysis of the role of leverage of financial institutions for the transmission of financial shocks to the macroeconomy. For that purpose, we develop an endogenous regime-switching structural vector autoregressive model with time-varying transition probabilities that depend on the state of the economy. We propose new identification techniques for regime switching models.Recently developed theoretical models emphasize the role of bank balance sheets for the build-up of financial instabilities and the amplification of financial shocks. We build a market-based ...
Working Paper
Likelihood-preserving normalization in multiple equation models
Causal analysis in multiple equation models often revolves around the evaluation of the effects of an exogenous shift in a structural equation. When taking into account the uncertainty implied by the shape of the likelihood, we argue that how normalization is implemented matters for inferential conclusions around the maximum likelihood (ML) estimates of such effects. We develop a general method that eliminates the distortion of finite-sample inferences about these ML estimates after normalization. We show that our likelihood-preserving normalization always maintains coherent economic ...
Working Paper
Markov-switching structural vector autoregressions: theory and application
This paper develops a new and easily implementable necessary and sufficient condition for the exact identification of a Markov-switching structural vector autoregression (SVAR) model. The theorem applies to models with both linear and some nonlinear restrictions on the structural parameters. We also derive efficient MCMC algorithms to implement sign and long-run restrictions in Markov-switching SVARs. Using our methods, four well-known identification schemes are used to study whether monetary policy has changed in the euro area since the introduction of the European Monetary Union. We find ...
Working Paper
Minimal state variable solutions to Markov-switching rational expectations models
We develop a new method for computing minimal state variable solutions (MSV) to Markov-switching rational expectations models. We provide an algorithm to compute an MSV solution and show how to test a given solution for uniqueness and boundedness. We construct an example that is calibrated to U.S. data and show that the MSV solution in our example is unique. This solution can potentially explain in three different ways the observed reduction in the variance of inflation and the interest rate after 1980: The policy rule might have changed, the variance of the fundamental shocks might have ...
Working Paper
Perturbation methods for Markov-switching DSGE models
This paper develops a general perturbation methodology for constructing high-order approximations to the solutions of Markov-switching DSGE models. We introduce an important and practical idea of partitioning the Markov-switching parameter space so that a steady state is well defined. With this definition, we show that the problem of finding an approximation of any order can be reduced to solving a system of quadratic equations. We propose using the theory of Grobner bases in searching all the solutions to the quadratic system. This approach allows us to obtain all the approximations and ...