Regime-Dependent Effects of Uncertainty Shocks: A Structural Interpretation

Lhuissier, Stéphane; Tripier, Fabien

doi:10.2139/ssrn.3354571

Cited by 8 publications

(10 citation statements)

References 51 publications

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“…2 See, for example, Lhuissier (2017) and Lhuissier and Tripier (2019), for applications of such a method in the context of multivariate-equation Markov-switching models. 3 Albert and Chib (1993) develop a Gibbs sampling for AR time series subject to Markov mean and variance shifts.…”

Section: A Gibbs Samplermentioning

confidence: 99%

Bayesian Inference for Markov-switching Skewed Autoregressive Models

Lhuissier

2019

SSRN Journal

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We examine Markov-switching autoregressive models where the commonly used Gaussian assumption for disturbances is replaced with a skew-normal distribution. This allows us to detect regime changes not only in the mean and the variance of a specified time series, but also in its skewness. A Bayesian framework is developed based on Markov chain Monte Carlo sampling. Our informative prior distributions lead to closed-form full conditional posterior distributions, whose sampling can be efficiently conducted within a Gibbs sampling scheme. The usefulness of the methodology is illustrated with a real-data example from U.S. stock markets.

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Section: A Gibbs Samplermentioning

confidence: 99%

Bayesian Inference for Markov-switching Skewed Autoregressive Models

Lhuissier

2019

SSRN Journal

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“…Our study is connected with the empirical literature investigating whether uncertainty shocks have state-dependent e¤ects according to the economic phase when a shock hits. Among others, Caggiano, Castelnuovo, and Groshenny (2014), Chatterjee (2018), andFigueres (2020) employ non-linear Structural VAR techniques to enquire whether contractionary vs. expansionary phases are important in determining the impact of uncertainty shocks, whereas Alessandri and Mumtaz (2019), Angelini, Bacchiocchi, Caggiano, andFanelli (2019), andLhuissier andTripier (2019) investigate whether …nancial or volatility regimes are important for the real e¤ects of uncertainty shocks. This study focuses on the role of consumer con…dence.…”

Section: Introductionmentioning

confidence: 99%

“…Caggiano, Castelnuovo and Groshenny (2014), Chatterjee (2018), Caggiano, Castelnuovo andFigueres (2020), and Paccagnini and Colombo (2020), among others, employ non-linear Structural VAR techniques to enquire whether contractionary vs. expansionary phases are important in determining the impact of uncertainty shocks. Alessandri and Mumtaz (2019), Angelini et al (2019), andLhuissier andTripier (2019) investigate whether financial or volatility regimes are important for the real effects of uncertainty shocks. Jackson, Kliesen and Owyang (2020) study whether periods of low vs. high uncertainty have a role in the propagation of uncertainty shocks as well.…”

Section: Introductionmentioning

confidence: 99%

“…Alessandri and Mumtaz (2019), Angelini et al . (2019), and Lhuissier and Tripier (2019) investigate whether financial or volatility regimes are important for the real effects of uncertainty shocks. Jackson, Kliesen and Owyang (2020) study whether periods of low vs. high uncertainty have a role in the propagation of uncertainty shocks as well.…”

Section: Introductionmentioning

confidence: 99%

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The Impact of Pessimistic Expectations on the Effects of COVID‐19‐Induced Uncertainty in the Euro Area*

2021

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We estimate an Interacted-VAR model allowing for the impact of uncertainty shocks to depend on the average outlook of the economy measured by survey data. We …nd that, in response to the same uncertainty shock, industrial production and in ‡ation's peak decrease is around three and a half times larger during pessimistic times. We build scenarios for a path of innovations in uncertainty consistent with the COVID-19-induced shock. Industrial production is predicted to experience a year-over-year peak loss of between 15:1% and 19% peaking between September and December 2020, and subsequently to recover with a rebound to pre-crisis levels between May and August 2021. The large impact is the result of an extreme shock to uncertainty occurring at a time of very negative expectations on the economic outlook.

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“…(Figure7) which explores conditional output responses in the benchmark model (M 1), abstracting from …nancial frictions (M 6), and under ‡exible prices (M 7).34Balke (2000) also examines, in the context of a threshold VAR, whether the e¤ects of shocks depend on current credit conditions. More recently, the amplifying role of credit frictions for the e¤ects of uncertainty shocks has been explored empirically byAlessandri andMumtaz (2019) andL'huissier andTripier (2019). For the asymmetric e¤ects of shocks (monetary policy shocks), see e.g Barnichon and Matthes (2018)…”

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confidence: 99%

In No Uncertain Terms: The Effect of Uncertainty on Credit Frictions and Monetary Policy

Balke¹,

Martínez‐García²,

Zhang³

2021

gwp

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We examine the interaction of uncertainty and credit frictions in a New Keynesian framework. The model considers credit frictions arising from costly-state verification in the provision of loans to fund the acquisition of capital by entrepreneurs and includes three types of time-varying stochastic volatility shocks related to monetary policy uncertainty, financial risk (micro-uncertainty), and macro-uncertainty. Key parameters are estimated by the Simulated Method of Moments using U.S. data from 1984:Q1 until 2014:Q4. We find: 1. Micro-uncertainty has first-order effects that are significantly larger than the effects of macro-uncertainty and monetary policy uncertainty. 2. Poor credit conditions exacerbate the economic drag from micro-uncertainty shocks, amplify the effects of monetary policy shocks, and mitigate the impact of TFP shocks. 3. A degree of asymmetry and non-scalability appears in response to monetary policy shocks, dependent on the degree of nominal rigidities and initial conditions. 4. Monetary policy uncertainty accounts for about one-third of the business cycle volatility largely by affecting the size of monetary policy shocks.

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Regime-Dependent Effects of Uncertainty Shocks: A Structural Interpretation

Cited by 8 publications

References 51 publications

Bayesian Inference for Markov-switching Skewed Autoregressive Models

Bayesian Inference for Markov-switching Skewed Autoregressive Models

The Impact of Pessimistic Expectations on the Effects of COVID‐19‐Induced Uncertainty in the Euro Area*

In No Uncertain Terms: The Effect of Uncertainty on Credit Frictions and Monetary Policy

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