In this paper, I review the literature on the formulation and estimation of dynamic stochastic general equilibrium (DSGE) models with a special emphasis on Bayesian methods. First, I discuss the evolution of DSGE models over the last couple of decades. Second, I explain why the profession has...

This chapter provides an overview of solution and estimation techniques for dynamic stochastic general equilibrium models. We cover the foundations of numerical approximation techniques as well as statistical inference and survey the latest developments in the field.

We develop an empirical Bayes ranking procedure that assigns ordinal grades to noisy measurements, balancing the information content of the assigned grades against the expected frequency of ranking errors. Applying the method to a massive correspondence experiment, we grade the race and gender...

This study investigates the usefulness of the business tendency surveys collected at the KOF institute for short-term forecasting of employment in Switzerland aggregated in the KOF Employment Indicator. We use the real time dataset in order to simulate the actual predictive process using only...

Recent contributions to the growth literature have argued that the structure of an economy, as measured by its productive capabilities, is a key determinant for inter-country differences in development. Productive capabilities have been shown to be highly predictive of future economic growth,...

We develop a new method to sample from posterior distributions in hierarchical models without using Markov chain Monte Carlo. This method, which is a variant of importance sampling ideas, is generally applicable to high-dimensional models involving large data sets. Samples are independent, so...

Central banks have long used dynamic stochastic general equilibrium (DSGE) models, which are typically estimated using Bayesian techniques, to inform key policy decisions. This paper offers an empirical strategy that quantifies the information content of the data relative to that of the prior...

Some researchers, for example, Koop [1], and Sims [2], have advocated for Bayesian alternatives to unit-root testing over the classical approach using the augmented Dickey-Fuller test (ADF). This paper studies the power of what Koop [1] has called the Objectiveʺ Bayesian approach to unit-root...

We revisit time-variation in the Phillips curve, applying new Bayesian panel methods with breakpoints to US and European Union disaggregate data. Our approach allows us to accurately estimate both the number and timing of breaks in the Phillips curve. It further allows us to determine the...