Impulse response analysis in nonlinear multivariate models

Koop, Gary; Pesaran, M. Hashem; Potter, Simon

doi:10.1016/0304-4076(95)01753-4

Cited by 3,883 publications

(2,204 citation statements)

References 11 publications

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“…If the economy starts below the threshold, but close to it, the response may be different than the case when the economy starts far from the threshold, because the economy may switch to the high state sooner. For this reason, we construct nonlinear IRFs following Koop et al (1996) and Yang (2014, 2016), as detailed in the previous section. It is important to note that, in all cases below, the IRFs are computed allowing the economy to endogenously switch between regimes after the initial oil price shock.…”

Section: Discussion Of Resultsmentioning

confidence: 99%

“…To overcome these issues, we construct nonlinear IRF in the spirit of Koop et al (1996) and Yang (2014, 2016). In a nonlinear environment, the conditional expectations in (6) must be simulated since the impact of the shocks depend on the sign and size of the shock, as well as the history of the system.…”

Section: Nonlinear Irfmentioning

confidence: 99%

“…The procedure to compute the nonlinear impulse-response functions (IRF) follows Koop et al (1996) and Yang (2014, 2016). The reader is referred to the original documents for further details.…”

Section: Computation Of Nonlinear Impulse-response Functionsmentioning

confidence: 99%

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The Asymmetric Effects of Oil Price Shocks on the Canadian Economy

Donayre

Wilmot

2015

SSRN Journal

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A threshold vector autoregression (TVAR) is estimated to study the effects of oil price shocks on Canadian output and price level. While much of the literature has investigated potential asymmetric effects of positive and negative oil price shocks within a linear vector autoregression (VAR), we do so within a nonlinear VAR. Further, we extend the analysis to consider the correlation between asymmetries associated with the business cycle phase and size/sign asymmetries. Positive oil price shocks are found to have a stronger effect on output than negative oil price shocks. This asymmetry is significant in recessions, but lessened during expansions. The results also suggest that the reduction in inflation due to a negative oil price shock is larger than the increase in inflation following a positive oil price shock, especially during periods of low output growth. Yet, neither inflation nor output growth seems to vary disproportionately with the size of the oil price shock. In general, the results are robust to the ordering of the variables in the VAR process and to the time window over which the net oil price change is computed.

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Section: Discussion Of Resultsmentioning

confidence: 99%

Section: Nonlinear Irfmentioning

confidence: 99%

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The Asymmetric Effects of Oil Price Shocks on the Canadian Economy

Donayre

Wilmot

2015

SSRN Journal

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“…Diebold and Yilmaz (2009) use Cholesky decomposition, which yields variance decompositions dependent on the ordering of the variables, whereas Diebold and Yilmaz (2012) extend the Diebold and Yilmaz (2009) model, using the generalized VAR framework of Koop et al (1996) and Pesaran and Shin (1998), in which variance decompositions are invariant to the order of the variables. Both models yield an N × N matrix φ(H) = [φ ij (H)] i,j=1,...N , where each entry gives the contribution of variable j to the forecast error variance of variable i.…”

Section: Spillover Methodologymentioning

confidence: 99%

Dynamic spillovers of oil price shocks and economic policy uncertainty

2014

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This study examines the dynamic relationship between changes in oil prices and the economic policy uncertainty index for a sample of both net oil-exporting and net oil-importing countries over the period 1997:01-2013:06. To achieve that, an extension of the Yilmaz (2009, 2012) dynamic spillover index based on structural decomposition is employed. The results reveal that economic policy uncertainty (oil price shocks) responds negatively to aggregate demand oil price shocks (economic policy uncertainty shocks). Furthermore, during the Great Recession of 2007-2009, total spillovers increase considerably, reaching unprecedented heights. Moreover, in net terms, economic policy uncertainty becomes the dominant transmitter of shocks between 1997 and 2009, while in the post-2009 period there is a significant role for supply-side and oil specific demand shocks, as net transmitters of spillover effects. These results are important for policy makers, as well as, investors interested in the oil market.

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“…We compute the impulse responses to a credit shock following Koop, Pesaran, and Potter (1996) and Pesaran and Shin (1998), since the generalized impulse response functions offer more modelling flexibility.…”

Section: Impulse Responsesmentioning

confidence: 99%

Business Cycle Effects of Credit Shocks in a DSGE Model with Firm Defaults

Pesaran

2016

SSRN Journal

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This paper proposes a theoretical framework to analyze the relationship between credit shocks, firm defaults and volatility, and to study the impact of credit shocks on business cycle dynamics. Firms are identical ex ante but differ ex post due to different realizations of firm-specific technology shocks, possibly leading to default by some firms. The paper advances a new modelling approach for the analysis of firm defaults and financial intermediation that takes account of the financial implications of such defaults for both households and banks. Results from a calibrated version of the model suggest that, in the steady state, a firm's default probability rises with its leverage ratio and the level of uncertainty in the economy. A positive credit shock, defined as a rise in the loan-todeposit ratio, increases output, consumption, hours and productivity, and reduces the spread between loan and deposit rates. The effects of the credit shock tend to be highly persistent, even without price rigidities and habit persistence in consumption behavior. JEL classification: E32, E44, G21 Bank classification: Business fluctuations and cycles; Economic models; Credit and credit aggregates; Financial institutions RésuméLes auteurs proposent un modèle théorique pour l'analyse de la relation entre les chocs de crédit, les défaillances d'entreprises et la volatilité, ainsi que pour l'étude des effets de ces chocs sur la dynamique du cycle économique. Dans ce modèle, des entreprises identiques ex ante se différencient ex post en réponse aux chocs technologiques réalisés, qui sont propres à chaque entreprise et peuvent provoquer sa défaillance. Le nouveau modèle employé par les auteurs pour examiner les défaillances des firmes et l'intermédiation financière tient compte des conséquences financières de ces défaillances à la fois sur les ménages et sur les banques. Les résultats tirés d'une version étalonnée du modèle indiquent qu'à l'équilibre de long terme, la probabilité de défaut d'une entreprise augmente avec son ratio de levier et le degré d'incertitude dans l'économie. Un choc de crédit positif -à savoir une hausse du ratio des prêts aux dépôts -accroît la production, la consommation, le nombre d'heures travaillées et la productivité et réduit l'écart entre le taux prêteur et le taux de rémunération des dépôts. Les retombées du choc de crédit tendent à perdurer longtemps même en l'absence de rigidité des prix et de persistance des habitudes de consommation.

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Impulse response analysis in nonlinear multivariate models

Cited by 3,883 publications

References 11 publications

The Asymmetric Effects of Oil Price Shocks on the Canadian Economy

The Asymmetric Effects of Oil Price Shocks on the Canadian Economy

Dynamic spillovers of oil price shocks and economic policy uncertainty

Business Cycle Effects of Credit Shocks in a DSGE Model with Firm Defaults

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