The effect of oil uncertainty shock on real GDP of 33 countries: a global VAR approach

ABSTRACT

In this paper, we investigate the effect of oil price uncertainty shock on real Gross Domestic Product (GDP) of 33 developed and emerging economies using the Global Vector Autoregressive (VAR) framework that allows us to capture the transmission of global shocks while simultaneously accounting for distinct characteristics of individual countries. Utilizing quarterly data over the period of 1980Q1 to 2019Q2, we show that, in general, oil price uncertainty shock has a statistically significant negative impact on GDP for 28 out of the 33 countries, but with varying magnitude and persistence. Overall though, we find the adverse effect on real GDP to be relatively stronger for the developed group of countries than the emerging ones. Hence, our results suggest that policymakers must be ready to undertake expansionary policies (of varying order) in the wake of an oil price uncertainty shock to prevent deep recessions, except in the cases of Norway, Philippines and Saudi Arabia, for which output tends to increase in a statistically significant manner.

KEYWORDS:

• Oil price uncertainty shock
• real GDP
• GVAR
• developed and emerging countries

JEL CLASSIFICATION:

• C32
• E32
• Q02

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Notes

¹ See: https://www.econ.cam.ac.uk/people-files/emeritus/mhp1/GVAR/GVAR.html.

² The daily data is obtained from Global Financial Data: https://globalfinancialdata.com/.

³ The GFCy index is based on the works of Miranda-Agrippino and Rey (2020) and Miranda-Agrippino, Nenova, and Rey (2020), and is generated as the common global factor extracted from a dynamic factor model (DFM) that involves a comprehensive panel of 1004 risky assets including equity and corporate bond indices that represent Europe, North America, Latin America, Asia-Pacific, and Australia as well as commodity prices excluding precious metals. Miranda-Agrippino and Rey (2020) show that this single common global factor alone accounts for over 20% of the common variation in the price of risky assets globally despite the heterogeneity of the asset markets included in the panel. The monthly data is available from 1980M1 to 2019M4 at: http://silviamirandaagrippino.com/code-data, which is converted to quarterly values by taking a three-month averages, and in turn determines our sample period of 1980Q1 to 2019Q2.

⁴ Interestingly, while the initial impact on Chile is significantly negative, it depicts a significantly positive impact thereafter. At the same time, India, is found to witness a sharp short-lived negative impact followed by an initial rise in real GDP.