Prepared for the Handbook of Economic Forecasting, vol 2 This chapter reviews Bayesian methods for inference and forecasting with VAR models. Bayesian inference and, by extension, forecasting depends on numerical methods for simulating from the posterior distribution of the parameters and spe-...

Inflation did not fall as much as many economists expected as the Great Recession hit the US economy. One explanation suggested for this phenomenon is that the Phillips curve has become flatter. In this paper we investigate the stability of the US Phillips curve, employing Bayesian VARs to...

In this paper we assess whether the relation between the corporate bond-yield spread and the real economy has been stable over time. Using quarterly US data from 1953Q1 to 2018Q2, we estimate Bayesian VAR models which allow for drifting parameters and/or stochastic volatility and conduct formal...

Prepared for the Handbook of Economic Forecasting, vol 2 <p> This chapter reviews Bayesian methods for inference and forecasting with VAR models. Bayesian inference and, by extension, forecasting depends on numerical methods for simulating from the posterior distribution of the parameters and spe-...</p>

This paper has two major objectives. First, we develop and implement a Bayesian generalized factor model that allows for non-orthogonality of the idiosyncratic factors and the flexibility of cross-sectional and time series dimensions. Second, we evaluate the significance of the orthogonality...

Bayesian model averaging is applied to robustly ascertain the determinants of various output volatility measures, including the downside semideviation of growth rates. Financial sophis- tication variables are found to have qualitatively different effects on volatility. The ratio of govern- ment...

Bivariate time series data often show strong relationships between the two components, while both individual variables can be approximated by random walks in the short run andare obviously bounded in the long run. Three model classes are considered for a time-series model selection problem:...

The question of variable selection in a regression model is a major open research topic in econometrics. Traditionally two broad classes of methods have been used. One is sequential testing and the other is information criteria. The advent of large datasets used by institutions such as central...

This paper studies an alternative quasi likelihood approach under possible model misspecification. We derive a filtered likelihood from a given quasi likelihood (QL), called a limited information quasi likelihood (LI-QL), that contains relevant but limited information on the data generation...

This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the...