Adaptive local VAR for dynamic economic policy uncertainty spillover

TL;DR

This paper introduces an adaptive local VAR model for real-time analysis of economic policy uncertainty spillovers, effectively capturing both abrupt and smooth changes in dependency over time.

Contribution

It develops a novel local VAR approach that adaptively estimates time-varying dependencies, improving upon traditional rolling window methods in economic uncertainty analysis.

Findings

The model effectively detects sudden and smooth breaks in data.

Empirical results show the model's superiority over rolling window estimation.

Created a crisis index based on data homogeneity.

Abstract

The availability of data on economic uncertainty sparked a lot of interest in models that can timely quantify episodes of international spillovers of uncertainty. This challenging task involves trading off estimation accuracy for more timely quantification. This paper develops a local vector autoregressive model (VAR) that allows for adaptive estimation of the time-varying multivariate dependency. Under local, we mean that for each point in time, we simultaneously estimate the longest interval on which the model is constant with the model parameters. The simulation study shows that the model can handle one or multiple sudden breaks as well as a smooth break in the data. The empirical application is done using monthly Economic Policy Uncertainty data. The local model highlights that the empirical data primarily consists of long homogeneous episodes, interrupted by a small number of heterogeneous ones, that correspond to crises. Based on this observation, we create a crisis index, which reflects the homogeneity of the sample over time. Furthermore, the local model shows superiority against the rolling window estimation.