Financial Shocks and the Real Economy in a Nonlinear World: From Theory to Estimation

Silvestrini, Andrea; Zaghini, Andrea

doi:10.2139/ssrn.2618420

Cited by 4 publications

(4 citation statements)

References 53 publications

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“…On the contrary, the second model allows for the financial cycle to affect the business cycle, and the resulting cycle differs from the univariate one. In particular, the business cycle (dark blue line) is deeper and longer than the univariate one, suggesting that financial boom and bust may have a significant impact on economic activity(Silvestrini and Zaghini, 2015). Finally, the unrestricted multivariate model, which delivers the highest log-likelihood, allows both for feedback from the financial to the business cycle and vice versa.…”

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confidence: 98%

Real and financial cycles: estimates using unobserved component models for the Italian economy

et al. 2019

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In this paper we examine the empirical features of both the business and financial cycles in Italy. We employ univariate and multivariate trend-cycle decompositions based on unobserved component models. Univariate estimates highlight the different cyclical properties (persistence, duration and amplitude) of real GDP and real credit to the private sector. Multivariate estimates uncover the presence of feedback effects between the real and financial cycles. At the same time, in the most recent period (2015-2016), the multivariate approach highlights a wider output gap than that estimated by the univariate models considered in this paper.JEL Classification: C32, E32, E44.

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confidence: 98%

Real and financial cycles: estimates using unobserved component models for the Italian economy

et al. 2019

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“…Christiano, Eichenbaum, and Evans () and Bernanke, Boivin, and Eliasz () are pioneering examples for the identification of monetary shocks using a Cholesky approach. This assumption is extensively used also to identify financial shocks (e.g., Lown and Morgan , Gilchrist and Zakrajšek , Hubrich and Tetlow , Silvestrini and Zaghini , Prieto, Eickmeier, and Marcellino ).…”

Section: Econometric Methodologymentioning

confidence: 99%

Labor Market and Financial Shocks: A Time‐Varying Analysis

Corsello¹,

Landi²

2019

J of Money Credit Banking

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We estimate a time-varying VAR model to analyze the effects of a financial shock on the U.S. labor market. We find that a tightening of financial conditions is highly detrimental to the labor market. We show that while negative financial shocks have been responsible for increases in unemployment, our model does not find significant contributions of financial shocks during periods of expansion. The source of this asymmetry is the time-varying standard deviation of the identified shock, which is higher in times of financial distress; on the other hand, we find that the transmission mechanism does not significantly change over time.JEL codes: C32, E24, E44

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“…It allows capturing dynamic relationships among variables going beyond the central moments in data series, that is, in the edges of distributions. Thus, this technique is suited to dissecting nonlinearity in the European macrofinancial linkages which is reported in the literature, for example, by Mittnik and Semmler (2013), Schleer and Semmler (2015), Silvestrini and Zaghini (2015). In addition, the quantile smooth local projections we adopt are more robust to a model misspecification compared with the conventional vector autoregressions.…”

Section: Introductionmentioning

confidence: 94%

Macrofinancial linkages in Europe: Evidence from quantile local projections

Stolbov

Shchepeleva

2020

Int. J Fin Econ

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The paper investigates macrofinancial linkages in the sample of 16 European economies over January 1997–December 2019 from a new twofold perspective. First, we put a particular emphasis on the role of news‐based sentiment measures in these relationships, that is, economic policy uncertainty and global geopolitical risk. Second, we pursue a hybrid econometric approach to capture a presumably nonlinear nature of these linkages by building on different quantiles of the data series and estimating impulse responses from smooth local projections (Barnichon and Brownlees, Review of Economics and Statistics, 101(3), 522–530, 2019). Our results legitimize such approach as the number of statistically significant impulse responses based on this approach is skewed towards upper (75th and 90th) quantiles. We find that global economic policy uncertainty index dampens the growth rates of industrial production in Austria, France, Italy, Luxembourg and Slovakia, which calls for specific measures to mitigate this adverse effect at the national level, for example, by curtailing yellow journalism, populist ideas and disbeliefs. However, there is only minor evidence for the relationship running between economic policy uncertainty and financial stress. Global geopolitical risk appears irrelevant in the country‐ and panel‐level analyses. Meanwhile, the VIX index performs a pervasive role in undermining industrial production and increasing economic policy uncertainty in Europe.

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Financial Shocks and the Real Economy in a Nonlinear World: From Theory to Estimation

Cited by 4 publications

References 53 publications

Real and financial cycles: estimates using unobserved component models for the Italian economy

Real and financial cycles: estimates using unobserved component models for the Italian economy

Labor Market and Financial Shocks: A Time‐Varying Analysis

Macrofinancial linkages in Europe: Evidence from quantile local projections

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