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Discussion Paper
Bayesian skepticism on unit root econometrics
This paper examines several grounds for doubting the value of much of the special attention recently devoted to unit root econometrics. Unit root hypotheses are less well connected to economic theory than is often suggested or assumed; distribution theory for tests of other hypotheses in models containing unit roots are less often affected by the presence of unit roots than has been widely recognized; and the Bayesian inferential theory for dynamic models is largely unaffected by the presence of unit roots. The paper displays an example to show that when Bayesian probability statements and ...
Report
Forecasting and conditional projection using realistic prior distribution
This paper develops a forecasting procedure based on a Bayesian method for estimating vector autoregressions. We apply the procedure to 10 macroeconomic variables and show that it produces more accurate out-of-sample forecasts than univariate equations do. Although cross-variable responses are damped by the prior, our estimates capture considerable interaction among the variables. ; We provide unconditional forecasts as of 1982:12 and 1983:3. We also describe how a model such as this can be used to make conditional projections and analyze policy alternatives. As an example, we analyze a ...
Conference Paper
Inflation expectations, uncertainty, the Phillips curve, and monetary policy
As with many important theories, the long run value of Phillips curve theories may lie in the new flames that are emerging from its dying embers.
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
Bayesian methods for dynamic multivariate models
If multivariate dynamic models are to be used to guide decision-making, it is important that it be possible to provide probability assessments of their results. Bayesian VAR models in the existing literature have not commonly (in fact, not at all as far as we know) been presented with error bands around forecasts or policy projections based on the posterior distribution. In this paper we show that it is possible to introduce prior information in both reduced form and structural VAR models without introducing substantial new computational burdens. With our approach, identified VAR analysis of ...
Conference Paper
Fiscal consequences for Mexico of adopting the dollar
Conference Paper
Inflation and growth - commentary
Discussion Paper
Understanding unit rooters: a helicopter tour
Discussion Paper
Solving nonlinear stochastic optimization and equilibrium problems backwards
In a stochastic equilibrium model some stochastic processes are usually exogenously given, while others are either chosen optimally by agents or emerge from market equilibrium conditions. When we simulate such a model, often we aim at studying the relations among variables in the model as we vary parameters of policy and of behavior of economic agents. We are no more certain (indeed often less certain) of what is reasonable or interesting behavior for the exogenous variables (some of which may be unobservable) than of the variables chosen by agents or fixed in markets. It turns out that if we ...