Thursday, January 19, 2012

Oil-price shocks have had substantial and statistically significant effects during the last 25 years

Measuring Oil-Price Shocks Using Market-Based Information. By Tao Wu & Michele Cavallo
IMF Working Paper No. 12/19
January 01, 2012


We study the effects of oil-price shocks on the U.S. economy combining narrative and quantitative approaches. After examining daily oil-related events since 1984, we classify them into various event types. We then develop measures of exogenous shocks that avoid endogeneity and predictability concerns. Estimation results indicate that oil-price shocks have had substantial and statistically significant effects during the last 25 years. In contrast, traditional VAR approaches imply much weaker and insignificant effects for the same period. This discrepancy stems from the inability of VARs to separate exogenous oil-supply shocks from endogenous oil-price fluctuations driven by changes in oil demand.


The relationship between oil-price shocks and the macroeconomy has attracted extensive scrutiny by economists over the past three decades. The literature, however, has not reached a consensus on how these shocks affect the economy, or by how much. A large number of studies have relied on vector autoregression (VAR) approaches to identify exogenous oilprice shocks and estimate their effects. Nevertheless, estimation results generally have not provided compelling support for the conventional-wisdom view that following a positive oilprice shock, real GDP declines and the overall price level increases. In addition, the estimated relationship is often unstable over time. This is why, after a careful examination of various approaches, Bernanke, Gertler, and Watson (1997) conclude that “finding a measure of oil price shocks that ‘works’ in a VAR context is not straightforward. It is also true that the estimated impacts of these measures on output and prices can be quite unstable over different samples.”

Traditional VAR-based measures of oil-price shocks exhibit two recurrent weaknesses: endogeneity and predictability. With regard to the first one, VAR approaches often cannot separate oil-price movements driven by exogenous shocks from those reflecting endogenous responses to other kinds of structural shocks. For instance, the oil price increases that occurred over the 2002–2008 period were viewed by many as the result of “an expanding world economy driven by gains in productivity” (The Wall Street Journal, August 11, 2006). The occurrence of such endogenous movements will undoubtedly lead to biased estimates of the effects of oil shocks.

On the other hand, part of the observed oil price changes might have been anticipated by private agents well in advance. Therefore, they can hardly be considered as “shocks.” Most measures of oil-price shocks in the literature are constructed using only spot oil prices. However, when the market senses any substantial supply-demand imbalances in the future, changes in the spot prices may not fully reflect such imbalances. A number of authors (e.g., Wu and McCallum, 2005; Chinn, LeBlanc, and Coibon, 2005) have found that oil futures prices are indeed quite powerful in predicting spot oil price movements, indicating that at least a portion of such movements may have been anticipated at least a few months in advance. Both these concerns underscore the need to pursue a different approach to obtain more reliable measures of exogenous oil-price shocks.

In this paper, we combine narrative and quantitative approaches to develop new measures of exogenous oil-price shocks that avoid the endogeneity and predictability concerns. We begin by identifying the events that have driven oil-price fluctuations on a daily basis from 1984 to 2007. To achieve this goal, we first collect information from daily oil-market commentaries published in a number of oil-industry trade journals, such as Oil Daily, Oil & Gas Journal, and Monthly Energy Chronology. This leads to the construction of a database that identifies the oil-related events that have occurred each day since January 1984. We then classify these daily events into a number of different event types based on their specific features, such as weather changes in the U.S., military actions in the Middle East, OPEC announcements on oil production, U.S. oil inventory announcements, etc. (see Table 1). Next, for each event type we construct a measure of oil-price shocks by running oil-price forecasting equations on a daily basis. Finally, shock series from exogenous oil events are selected and aggregated into a single measure of exogenous oil-price shocks. By construction, these shock measures should be free of endogeneity and predictability problems, and statistical tests are also conducted to confirm their exogeneity. For robustness, we also provide a number of alternative definitions of exogenous oil-price shocks and construct corresponding shock measures for each one of them.

We employ our new, market-information based measures to study the responses of U.S. output, consumer prices, and monetary policy to exogenous oil-price shocks. We also compare the estimated responses with those obtained following two traditional VAR-based identification strategies that are very popular in the literature. Estimation results reveal substantial and statistically significant output and price responses to exogenous oil-price shocks identified by our market-based methodology. In contrast, responses implied by the VAR-based approaches are much weaker, statistically insignificant, and unstable over time. Moreover, we find that following a demand-driven oil-price shock, real GDP increases and the price level declines. This finding is consistent with scenarios in which oil-price fluctuations are endogenous responses to changes in the level of economic activity rather than reflecting exogenous oil shocks. We argue that traditional VAR-based approaches cannot separate the effects of these two kinds of shocks and consequently lead to biased estimates of the dynamic responses.

Our approach is similar in spirit to the narrative approach pursued in a number of existing studies. Romer and Romer (2004, 2010) adopt it in their analyses of monetary policy and tax shocks, Alexopoulos (2011) and Alexopoulos and Cohen (2009) in the context of technology shocks, and Ramey (2009) in her analysis of government spending shocks. With regard to oil-price shocks, several earlier studies have tried to isolate some geopolitical events associated with abrupt oil-price increases and examine their effects on the U.S. economy. Hamilton (1983, 1985) identifies a number of “oil-price episodes” before 1981, mainly Middle East tensions, and concludes that such oil shocks had effectively contributed to postwar recessions in the U.S. Hoover and Perez (1994) revise Hamilton’s (1983) quarterly dummies into a monthly dummy series and find that oil shocks had led to declines in U.S. industrial production. Bernanke, Gertler, and Watson (1997) construct a quantitative measure, weighting Hoover and Perez’s dummy variable by the log change in the producer price index for crude oil, yet they were not able to find statistically significant macroeconomic responses to oil shocks in a VAR setting. Hamilton (2003) identifies five military conflicts during the postwar period and reexamines the effects of the associated oil shocks on U.S. GDP growth. Finally, Kilian (2008) also analyzes six geopolitical events since 1973, five in the Middle East and one in Venezuela, and examines their effects on the U.S. economy. Our study contributes to the literature by constructing a database of all oil-related events on a daily basis. This allows us to identify all kinds of oil shocks and conduct a more comprehensive analysis than earlier studies. Extracting the “unpredictable” component of oil-price fluctuations using an oil futures price-based forecasting model represents another novelty of our work.

More recently, Kilian (2009) has also used information from the oil market to disentangle different kinds of oil-price shocks. In particular, he has constructed an index of global real economic activity, including it in a tri-variate VAR, along with data on world oil production and real oil prices. Using a recursive ordering of these variables, he recovers an oil-supply shock, a global aggregate demand-driven shock, and an oil market-specific demand shock.  Although his approach is completely different from ours, the effects on the U.S. economy of all three kinds of structural shocks estimated in his work are quite close to our empirical estimates.  This, in turn, corroborates the validity of our approach. We present detailed evidence in subsequent sections.

Our study is also related to the ongoing debate about how the real effects of oil-price shocks have changed over time. For instance, VAR studies, such as those of Hooker (1996) and Blanchard and GalĂ­ (2009), have usually found a much weaker and statistically insignificant relationship between their identified oil-price shocks and real GDP growth in the U.S. and other developed economies during the last two to three decades. These results are often cited as evidence suggesting that the U.S. economy has become less volatile and more insulated from external shocks, the result of better economic policy, a lack of large adverse shocks, or a smaller degree of energy dependence (e.g., a more efficient use of energy resources and a larger share of service sector in the U.S. economy), all contributing to a “Great Moderation” starting in the first half of the 1980s. Although we do not challenge this general characterization of the “Great Moderation,” our estimation results reveal a substantial and significant adverse effect of exogenous oil shocks on the U.S. economy, even during the last two and a half decades. Results from VAR studies, in particular the time variation in coefficient estimates, may simply reflect an inadequate identification strategy.

This paper combines narrative and quantitative approaches to examine the dynamic effects of oil-price shocks on the U.S. economy. To correctly identify exogenous oil shocks, we first collect oil-market related information from a number of oil-industry trade journals, and compile a database identifying all the events that have affected the global oil market on a daily basis since 1984. Based on such information, we are able to isolate events that are exogenous to the U.S. economy and construct corresponding measures of exogenous oil-price shocks.  Furthermore, shock magnitudes are calculated by running a real-time oil-price forecasting model incorporating oil futures prices. These procedures help alleviate the endogeneity and predictability problems that have pestered the traditional VAR identification strategies in the literature.

One contribution of our work is the thorough examination of all kinds of oil-related events in the past two and a half decades, more comprehensive than just focusing on geopolitical or military events, as most of the earlier literature has done so far. Moreover, in constructing the database, we have preserved as much primitive information on the oil-market developments as possible, with the hope of facilitating possible future studies by other researchers on the nature and implications of these events. 

After deriving our measures of various kinds of oil shocks, we go on to examine their dynamic macroeconomic effects. We find that exogenous oil-price shocks have had substantial and statistically significant effects on the U.S. economy during the past two and a half decades. In contrast, traditional VAR identification strategies imply a substantially weaker and insignificant real effect for the same period. Further analysis reveals that this discrepancy is likely to stem from the inability of VAR-based approaches to separate exogenous oil-supply shocks from endogenous oil-price fluctuations driven by changes in oil demand. Notably, our study also suggests that the U.S. economy may not have become as insulated from oil shocks during the last two and a half decades as earlier studies have suggested. To examine fully how the oil price-macroeconomy relationship has evolved during the whole postwar period, a thorough study along the same narrative and quantitative approach for the period prior to the “Great Moderation” is called for. This will be the topic for future research.