Flexible shrinkage in high-dimensional Bayesian spatial autoregressive models

This article introduces two absolutely continuous global-local shrinkage priors to enable stochastic variable selection in the context of high-dimensional matrix exponential spatial specifications. Existing approaches as a means to dealing with overparameterization problems in spatial autoregressive specifications typically rely on computationally demanding Bayesian model-averaging techniques. The proposed shrinkage priors can be implemented using Markov chain Monte Carlo methods in a flexible and efficient way. A simulation study is conducted to evaluate the performance of each of the shrinkage priors. Results suggest that they perform particularly well in high-dimensional environments, especially when the number of parameters to estimate exceeds the number of observations. For an empirical illustration we use pan-European regional economic growth data.Comment: Keywords: Matrix exponential spatial specification, model selection, shrinkage priors, hierarchical modeling; JEL: C11, C21, C5

Introducing shrinkage in heavy-tailed state space models to predict equity excess returns

We forecast S&P 500 excess returns using a flexible Bayesian econometric state space model with non-Gaussian features at several levels. More precisely, we control for overparameterization via novel global-local shrinkage priors on the state innovation variances as well as the time-invariant part of the state space model. The shrinkage priors are complemented by heavy tailed state innovations that cater for potential large breaks in the latent states. Moreover, we allow for leptokurtic stochastic volatility in the observation equation. The empirical findings indicate that several variants of the proposed approach outperform typical competitors frequently used in the literature, both in terms of point and density forecasts

Bayesian state-space modeling for analyzing heterogeneous network effects of US monetary policy

Understanding disaggregate channels in the transmission of monetary policy is of crucial importance for effectively implementing policy measures. We extend the empirical econometric literature on the role of production networks in the propagation of shocks along two dimensions. First, we allow for industry-specific responses that vary over time, reflecting non-linearities and cross-sectional heterogeneities in direct transmission channels. Second, we allow for time-varying network structures and dependence. This feature captures both variation in the structure of the production network, but also differences in cross-industry demand elasticities. We find that impacts vary substantially over time and the cross-section. Higher-order effects appear to be particularly important in periods of economic and financial uncertainty, often coinciding with tight credit market conditions and financial stress. Differentials in industry-specific responses can be explained by how close the respective industries are to end-consumers.Comment: JEL: C11, C23, C32, C58, E52; Keywords: production networks, monetary policy shocks, high-frequency identification, spatio-temporal modelin

Implications of macroeconomic volatility in the Euro area

In this paper we estimate a Bayesian vector autoregressive model with factor stochastic volatility in the error term to assess the effects of an uncertainty shock in the Euro area. This allows us to treat macroeconomic uncertainty as a latent quantity during estimation. Only a limited number of contributions to the literature estimate uncertainty and its macroeconomic consequences jointly, and most are based on single country models. We analyze the special case of a shock restricted to the Euro area, where member states are highly related by construction. We find significant results of a decrease in real activity for all countries over a period of roughly a year following an uncertainty shock. Moreover, equity prices, short-term interest rates and exports tend to decline, while unemployment levels increase. Dynamic responses across countries differ slightly in magnitude and duration, with Ireland, Slovakia and Greece exhibiting different reactions for some macroeconomic fundamentals.Comment: Keywords: Bayesian vector autoregressive models, factor stochastic volatility, uncertainty shocks; JEL: C30, F41, E3