Macroeconomic Effect of Uncertainty and Financial Shocks: a non-Gaussian VAR approach
The Great Recession highlighted the role of financial and uncertainty shocks as drivers of business cycle fluctuations. However, the fact that uncertainty shocks may affect economic activity by tightening financial conditions makes empirically distinguishing these shocks difficult. This paper examines the macroeconomic effects of the financial and uncertainty shocks in the United States in an SVAR model that exploits the non-normalities of the time series to identify the uncertainty and the financial shock. The results show that macroeconomic uncertainty and financial shocks seem to affect business cycles independently as well as through dynamic interaction. Uncertainty shocks appear to tighten financial conditions, whereas there appears to be no causal relationship between financial conditions and uncertainty. Moreover, the results suggest that uncertainty shocks may have persistent effects on output and investment that last beyond the business cycle.
Code (0)
등록된 구현이 없습니다.
Tasks
Time SeriesTime Series AnalysisSimilar Papers 제목 키워드 기반
Beyond the Traditional VIX: A Novel Approach to Identifying Uncertainty Shocks in Financial Markets
We introduce a new identification strategy for uncertainty shocks to explain macroeconomic volatility in financial markets. The Chicago Board Options Exchange Volatility Index (VIX) measures market expectations of future…
Time SeriesMachine Learning the Macroeconomic Effects of Financial Shocks
We propose a method to learn the nonlinear impulse responses to structural shocks using neural networks, and apply it to uncover the effects of US financial shocks. The results reveal substantial asymmetries with respect…
Macroeconomic Forecasting for the G7 countries under Uncertainty Shocks
Accurate macroeconomic forecasting has become harder amid geopolitical disruptions, policy reversals, and volatile financial markets. Conventional vector autoregressions (VARs) overfit in high dimensional settings, while…
Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks
The shocks which hit macroeconomic models such as Vector Autoregressions (VARs) have the potential to be non-Gaussian, exhibiting asymmetries and fat tails. This consideration motivates the VAR developed in this paper wh…
Bayesian InferenceMitigating Model Drift in Developing Economies Using Synthetic Data and Outliers
Machine Learning models in finance are highly susceptible to model drift, where predictive performance declines as data distributions shift. This issue is especially acute in developing economies such as those in Central…