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Erschienen in: Empirical Economics 6/2020

26.11.2019

On the pernicious effects of oil price uncertainty on US real economic activities

verfasst von: Amélie Charles, Chew Lian Chua, Olivier Darné, Sandy Suardi

Erschienen in: Empirical Economics | Ausgabe 6/2020

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Abstract

The last five decades have witnessed dramatic changes in crude oil price dynamics. We identify the influence of extreme oil shocks and changing oil price uncertainty dynamics associated with economic and political events. Neglecting these features of the data can lead to model misspecification that gives rise to: firstly, an explosive volatility process for oil price uncertainty, and secondly, erroneous output growth dynamic responses to oil shocks. Unlike past studies, our results show that the sharp increase in oil price uncertainty after mid-1985 has a pernicious effect on output growth. There is evidence that output growth responds symmetrically (asymmetrically) to positive and negative shocks in the period when oil price uncertainty is lower (higher) and more (less) persistent before (after) mid-1985. These results highlight the importance of accounting for outliers and volatility breaks in oil price and output growth and the need to better understand the response of economic activity to oil shocks in the presence of oil price uncertainty. Our results remain qualitatively unchanged with the use of real oil price.

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Fußnoten
1
Baumeister and Peersman (2013) use a time-varying-parameter VAR model to demonstrate that changes in the crude oil market have been gradual. While their model specification permit inference on the gradual dynamic of change in the price elasticity of oil supply and demand, we do not impose this structure to our model given that our basis of comparison is the model of Elder and Serletis (2009, 2010, 2011). Be that as it may, the application of the variance break test is able to detect whether there has been a change in the volatility process of oil price change partly explained by this gradual change in the price elasticity of oil supply and demand.
 
2
The proxy for uncertainty which is measured by the conditional variance of oil prices is subject to certain caveats. This proxy measures the dispersion in the forecast error produced by the econometric model estimated using historical data, and it therefore may not capture other forward-looking components of uncertainty other than the one parameterised in the model. Nevertheless, the use of autoregressive conditional heteroskedasticity-based measures of uncertainty is widespread in the empirical literature for modelling output growth uncertainty (Grier et al. 2004; Chua et al. 2011), inflation uncertainty (Engle 1982; Elder 2004), and oil price uncertainty (Elder and Serletis 2009, 2010).
 
3
Recently, Rodrigues and Rubia (2011) have studied the size properties of Sansó et al.’s (2004) ICSS algorithm for detecting structural breaks in variance under the hypothesis of additive outliers. Their results indicate that neglected outliers tend to bias the ICSS test. They advise applying the modified ICSS algorithm on outlier-adjusted return series to identify sudden shifts in volatility.
 
4
Elder and Serletis (2010) undertook a robustness analysis post-1986, but this was for the purpose of addressing the effect of the 1986 Tax Reform Act on investment. Specifically, following the sharp drop in oil prices in 1986 the decline in real GDP growth rate was primarily due to declines in private nonresidential investment expenditures. The fall in private nonresidential investment expenditures can be attributed to provisions in TRA86 such as the repeal of the investment tax credit and the elimination of some real estate tax shelters.
 
5
Rahman and Serletis (2012) study the effects of oil price uncertainty on the Canadian economy using a multivariate conditional variance specification that does not impose this assumption.
 
6
One damaging aspect of the tax reform is its application of the alternative minimum tax (AMT) to the main tax mechanisms for drilling cost and capital recovery, which comprise current year expensing of intangible drilling costs and the remnants of percentage depletion. In theory, producers can recover AMT tax payments through credits when and if they become so profitable that their regular income tax exceeds AMT tax. However, most producers are not that profitable. To the extent they cannot recover AMT payments, and lost opportunity costs associated with them, producers pay taxes on drilling capital.
 
7
The test of Laurent et al. (2016) is similar to the non-parametric tests for jumps proposed by Lee and Mykland (2008) and Andersen et al. (2007) for low-frequency data.
 
8
The critical values are defined by \(g_{T,\lambda }=-\log \left( -\log (1-\lambda )\right) b_{T}+c_{T}\), with \(b_{T}=1/\sqrt{2\log T}\), and \( c_{T}=(2\log T)^{1/2}-[\log \pi +\log (\log T)]/[2(2\log T)^{1/2}]\). Laurent et al. (2016) suggest setting \(\lambda =0.5\)
 
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Metadaten
Titel
On the pernicious effects of oil price uncertainty on US real economic activities
verfasst von
Amélie Charles
Chew Lian Chua
Olivier Darné
Sandy Suardi
Publikationsdatum
26.11.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Empirical Economics / Ausgabe 6/2020
Print ISSN: 0377-7332
Elektronische ISSN: 1435-8921
DOI
https://doi.org/10.1007/s00181-019-01801-6

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