Statistically identified SVAR model with potentially skewed and fat-tailed errors

Anttonen, Jetro; Lanne, Markku; Luoto, Jani

doi:10.2139/ssrn.3925575

Cited by 5 publications

(13 citation statements)

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“…Uncertainty and financial shocks affect economic activity through multiple channels. We study the macroeconomic effect of financial and uncertainty shocks in the United States using a new approach by Anttonen et al (2021), where a the errors of the SVAR model follow a generalized t distribution. Due to non-Gaussianity of the error process, the structural shocks are statistically identified, and their economic interpretation is based on the properties of the impulse response functions.…”

Section: Discussionmentioning

confidence: 99%

“…We estimate our model using a Bayesian framework for non-Gaussian SVARs proposed by Anttonen et al (2021). The estimation is based on the identification method proposed by Lanne et al (2017) and Lanne and Luoto (2020) by introducing a more general distributional assumptions for the shocks, namely that the shocks follow a skewed generalized t distribution (henceforth, sgt-distribution).…”

Section: Empirical Literature On Financial and Uncertainty Shocksmentioning

confidence: 99%

“…To ensure that the model is uniquely identified, we follow Anttonen et al (2021) by restricting the parameter space such that no shock process follows a Gaussian distribution 2 .…”

Section: The Svar Model With Potentially Skewed and Fat-tailed Errorsmentioning

confidence: 99%

“…Although statistical identification been used to study the macroeconomic effcts of the financial shock (Brunnermeier et al (2021)) and the uncertainty shock (Carriero et al (2021)) separately, these types of identification techniques have not been previosly used to identify uncertainty and financial shocks simultaneously. To this end, we propose a new approach to identifying the financial and uncertainty shock based on non-Gaussianity by Anttonen et al (2021), which builds on the pioneering work Lanne et al (2017). The structural shocks are first identified based on their distributional properties, and the structural shocks are given economic labels based on the properties of the impulse response functions.…”

Section: Introductionmentioning

confidence: 99%

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Macroeconomic Effect of Uncertainty and Financial Shocks: a non-Gaussian VAR approach

Palmén¹

2022

Preprint

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Empirical Literature On Financial and Uncertainty Shocksmentioning

confidence: 99%

“…To ensure that the model is uniquely identified, we follow Anttonen et al (2021) by restricting the parameter space such that no shock process follows a Gaussian distribution 2 .…”

Section: The Svar Model With Potentially Skewed and Fat-tailed Errorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Macroeconomic Effect of Uncertainty and Financial Shocks: a non-Gaussian VAR approach

Palmén¹

2022

Preprint

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“…. , n follows a skewed generalized t distribution that was also entertained in Anttonen et al (2021).…”

Section: Model Specificationmentioning

confidence: 99%

Simultaneous identification of fiscal and monetary policy shocks

Mansur

2022

Empir Econ

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This research contributes to the literature on the effects of fiscal and monetary policy by exploiting non-Gaussianity of the time series for the identification of a Bayesian structural vector autoregression model. Using quarterly US data from 1954:IV to 2006:IV and from 1985:I to 2020:III, we formally assess the plausibility of theoretically predicted signs to label fiscal policy, monetary policy, and business cycle shocks. The impulse responses of consumption to the fiscal policy shock depend to some extent on the sample period, but the implied fiscal multiplier is always less than unity. On investment, there is a lagging crowding-out effect with a high probability, but it is not strongly evident in the latter sample. As for the responses after a contractionary monetary policy shock, we find a weakening output after some lags consistent with the leading monetary policy literature. The business cycle shock turns out to matter for government spending only in the long run, while it is already important for the federal funds rate in the short run.

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Statistical identification in panel structural vector autoregressive models based on independence criteria

Herwartz,

Wang

2024

J of Applied Econometrics

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SummaryThis paper introduces a novel panel approach to structural vector autoregressive analysis. For identification, we impose independence of structural innovations at the pooled level. We demonstrate robustness of the method under cross‐sectional correlation and heterogeneity through simulation experiments. In an empirical application on monetary policy transmission in the Euro area, we find that bond spreads rise significantly after an unexpected monetary tightening. Furthermore, the central bank responds to offset effects of adverse financial shocks. Additionally, we document sizable heterogeneity in country‐specific output responses.

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Statistically identified SVAR model with potentially skewed and fat-tailed errors

Cited by 5 publications

References 0 publications

Macroeconomic Effect of Uncertainty and Financial Shocks: a non-Gaussian VAR approach

Macroeconomic Effect of Uncertainty and Financial Shocks: a non-Gaussian VAR approach

Simultaneous identification of fiscal and monetary policy shocks

Statistical identification in panel structural vector autoregressive models based on independence criteria

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