Can Stabilisation Policy Reduce Long‐run Growth?

Blackburn, Keith

doi:10.1111/1468-0297.00391

Cited by 106 publications

(110 citation statements)

References 25 publications

Supporting

Mentioning

103

Contrasting

Unclassified

Order By: Relevance

“…Arguments for a positive association have been based on precautionary motives [Sandmo (1970), Mirman (1971)], rewards for risk-taking [Black (1987)] and learning-by-doing [Blackburn (1999)]. Conversely, Pindyck (1991) …”

Section: A Literature Reviewmentioning

confidence: 99%

The Measurement and Behavior of Uncertainty: Evidence from the ECB Survey of Professional Forecasters

Abel

Rich

Song³

et al. 2015

J. Appl. Econ.

View full text Add to dashboard Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractWe use matched point and density forecasts of output growth and infl ation from the ECB Survey of Professional Forecasters to derive measures of forecast uncertainty, forecast dispersion, and forecast accuracy. We construct uncertainty measures from aggregate density functions as well as from individual histograms. The uncertainty measures display countercyclical behavior, and there is evidence of increased uncertainty for output growth and infl ation since 2007. The results also indicate that uncertainty displays a very weak relationship with forecast dispersion, corroborating the fi ndings of other recent studies indicating that disagreement is not a valid proxy for uncertainty. In addition, we fi nd no correspondence between movements in uncertainty and predictive accuracy, suggesting that time-varying conditional variance estimates may not provide a reliable proxy for uncertainty. Last, using a regression equation that can be interpreted as a (G)ARCH-M-type model, we fi nd limited evidence of linkages between uncertainty and levels of infl ation and output growth.

show abstract

Section: A Literature Reviewmentioning

confidence: 99%

The Measurement and Behavior of Uncertainty: Evidence from the ECB Survey of Professional Forecasters

Abel

Rich

Song³

et al. 2015

J. Appl. Econ.

View full text Add to dashboard Cite

show abstract

“…In contrast, Black (1987) argues that high output volatility and high growth coexist. According to Blackburn (1999), a relative increase in the volatility of shocks increases the pace of knowledge accumulation and, hence, growth, implying a positive relation between output growth volatility and growth (i.e., λ >0).…”

Section: Relationship Between Output Volatility and Economic Growthmentioning

confidence: 99%

Modeling the volatility of real GDP growth: The case of Japan revisited

Fang

Miller

2009

Japan and the World Economy

View full text Add to dashboard Cite

Previous studies (e.g., Hamori, 2000;Ho and Tsui, 2003;Fountas et al., 2004) find high volatility persistence of economic growth rates using generalized autoregressive conditional heteroskedasticity (GARCH) specifications. This paper reexamines the Japanese case, using the same approach and showing that this finding of high volatility persistence reflects the Great Moderation, which features a sharp decline in the variance as well as two falls in the mean of the growth rates identified by Perrons (1998, 2003) multiple structural change test. Our empirical results provide new evidence. First, excess kurtosis drops substantially or disappears in the GARCH or exponential GARCH model that corrects for an additive outlier. Second, using the outlier-corrected data, the integrated GARCH effect or high volatility persistence remains in the specification once we introduce intercept-shift dummies into the mean equation. Third, the time-varying variance falls sharply, only when we incorporate the break in the variance equation. Fourth, the ARCH in mean model finds no effects of our more correct measure of output volatility on output growth or of output growth on its volatility. Journal of Economic Literature Classification: C32, E32, O40

show abstract

“…That is, as we can see from the first row of Panel A in Table 5, the likelihood ratio tests reject the null hypotheses: H 0 : It is worth noting that the direct relation is qualitatively altered by the presence of the indirect influences. That is, when we include the level effects in the model and in particular the negative influence of growth on inflation uncertainty, as predicted by Brunner, the direct impact disappears, that is (3) becomes insignificant (see equation (8) in Table 3). Moreover, inflation, via the nominal uncertainty channel, affects not only growth but real variability as well.…”

Section: Indirect Influences 521 Inflation-growth Link and Level Efmentioning

confidence: 88%

“…In one class of models, where the mechanism is 'creative destruction' the relation/correlation between short-term volatility and long-term growth is positive. In sharp contrast, in models where the mechanism is 'learning-by-doing' the same relation is negative (see Blackburn, 1999 and the references therein). Correlation between the two variables does not imply a causal link.…”

Section: The Effects Of Growth Variabilitymentioning

confidence: 99%

Modeling the Link between US Inflation and Output: The Importance of the Uncertainty Channel

Conrad

Karanasos

2010

SSRN Journal

View full text Add to dashboard Cite

This paper employs an augmented version of the UECCC GARCH specification proposed in Conrad and Karanasos (2010) which allows for lagged in-mean effects, level effects as well as asymmetries in the conditional variances. In this unified framework we examine the twelve potential intertemporal relationships between inflation, growth and their respective uncertainties using US data. We find that high inflation is detrimental to output growth both directly and indirectly via the nominal uncertainty. Output growth boosts inflation but mainly indirectly through a reduction in real uncertainty. Our findings highlight that macroeconomic performance affects nominal and real uncertainty in many ways and that the bidirectional relation between inflation and growth works to a large extend indirectly via the uncertainty channel.Keywords: Bivariate GARCH process, volatility feedback, inflation uncertainty, output variability.JEL Classification: C32, C51, E31. * We would like to thank James Davidson, Marika Karanassou and Ruey Tsay for their valuable suggestions. We have also benefited from the comments received from the participants of the Annual Meeting of the Verein für Socialpolitik (Kiel, 2010), the Annual Meeting of the Society for Nonlinear Dynamics and Econometrics (Novara, 2010)

show abstract

Can Stabilisation Policy Reduce Long‐run Growth?

Cited by 106 publications

References 25 publications

The Measurement and Behavior of Uncertainty: Evidence from the ECB Survey of Professional Forecasters

The Measurement and Behavior of Uncertainty: Evidence from the ECB Survey of Professional Forecasters

Modeling the volatility of real GDP growth: The case of Japan revisited

Modeling the Link between US Inflation and Output: The Importance of the Uncertainty Channel

Contact Info

Product

Resources

About