oil price volatility and economic activity

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Exposure Draft: 25-Sep-02
OIL PRICE VOLATILITY AND ECONOMIC ACTIVITY:
A SURVEY AND LITERATURE REVIEW
Raphael Sauter
and
Shimon Awerbuch, Ph.D. 1
IEA Research Paper
IEA, Paris
August 2003
Summary _____________________________________________________________ 2
1.
Oil price changes and economic output _____________________________________ 4
2.
The influence of oil price volatility _________________________________________ 7
3.
Stock markets _________________________________________________________ 10
4.
The Financial Risk of Oil and Natural Gas Price Volatility ____________________ 11
5.
Conclusion ___________________________________________________________ 11
6.
References: ___________________________________________________________ 12
7.
Table: Overview of the studies cited and their principal results _________________ 15
ADD: David L. Greene and Nataliya I. Tishchishyna,
Costs of Oil Dependence: A 2000 Update
Oak Ridge National Laboratory May 2000 , ORNL/TM-2000/152
Youngho Chang and Chan Jiang -- Oil Price Fluctuations and Chinese Economy – 2003 - draft.
1
Sauter, a research assistant at the IEA, is on loan from the Department of Political Science,
Free University of Berlin; he holds a Master's degree of Political Sciences. Awerbuch is
Senior Advisor¸ Energy Economics, Finance and Technology, IEA.
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Summary
This paper surveys recent research in the area of oil price movements and their effect on
economic and financial performance in IEA countries. To the extent they correlate
negatively with economic indicators, future oil (and natural gas) price streams represent a
highly risky obligation for energy consumers. Every time oil (and natural gas) prices rise,
economic activity– e.g. people's income and the value of their assets– declines by some
measure. Based on capital market theory (and common sense), any future cost stream that
rises at a time when economic activity and asset values are in decline is highly risky. This
adds an important dimension to fossil price risk and the idea of energy security and diversity.
The existence of a negative relationship between oil prices and macroeconomic activity has
become widely accepted since Hamilton’s 1983 work indicating that oil prices increases
reduced US output growth between 1948-1980. Hamilton's results have been confirmed and
extended by a number of other researchers.
More recently, the research emphasis has broadened to include not only the effects of
changes in oil price level (mean price in a given period), but also the effects of price volatility
(standard deviation in a given period) as well. The evidence confirms that volatility has a
considerable influence on economic output. For example, recent US EIA estimates blamed
oil price volatility between 1999 and 2001 for a loss of 0.7 percentage points of GDP growth
in the U.S. economy.2 This translates to losses that potentially range in the tens and even
hundreds of billions.
The idea that rising oil prices and price volatility serve to stifle economic activity and reduce
asset values has by now become widely accepted in the literature and seems virtually
axiomatic. For example, Yang, Hwang and Huang (2002) flatly state that "Higher [oil]
prices [yield] subsequent recessions in oil consuming nations, as oil prices are negatively
correlated to economic activities."3
The negative relationship between oil prices and asset values suggests that the financial risk
of oil price fluctuations should be observable. Beta, a standard finance risk indicator,
measures the covariance between fluctuations in an asset's value and fluctuations in the value
of a widely diversified asset portfolio. A number of researchers, using different data and
different estimation procedures, find that the estimated Beta for oil (and natural gas) is
negative,4 which implies a strong negative covariance risk with a widely diversified asset
portfolio. This has several implications. First, it implies that traditional electricity generating
cost estimates significantly understate the cost of fossil-based generation. Further, a negative
beta for fossil fuels clearly suggests that fossil fuel price spikes have a double whammy effect
for consumers. They not only drive up the cost of everything from driving to switching on the
lights, but they also produce measurable declines in consumers' wealth–– higher energy
prices eventually lower their incomes and the value of their homes and other assets.
It is therefore essential that policy makers fully understand the impact of fossil fuel price
movements on their national economies. Moreover, it is essential that policy makers
understand that one of the principal implications of the negative relationship between fossil
2
3
Energy Information Administration, http://www.eia.doe.gov/oiaf/economy/energy_price.html, 07/18/2002
Yang, Hwang and Huang, 2002, 107
4
Stoft and Kahn, 1993; Awerbuch 1993, 1995, 1995a; Bolinger, Wiser, and Golove 2002
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price movements and the economy is that traditional fossil-based electricity cost estimates are
significantly understated relative to renewables and other non-fossil technologies.
Principal Findings From the Literature
1. The economic effect of oil price increases has been quantitatively measured.
The table below shows the economic impact of a 10% increase in oil prices as reported in
three papers. The average historic oil price (1989 to 2000) is $17.63 USD, so that a 10%
increase ($1.76) implies a GDP growth decrease in the different studies as follows:
Approximate Historic GDP Decreases After a 10% Oil Price Increase a/
Authors
Hooker
Hamilton (2000)
Rotemberg and Woodford
a
Period
Studied
1948-1972
1948-1980
1948-1980
% GDP Growth
Decrease
0.6
1.4
2.5
Quarters after
initial price shock
3-4
4
5-7
Average historic oil price (Refiner acquisition cost) is $17.63 US; 10% price increase = $1.76 USD
The table suggests that relatively small oil price increases yield sizeable economic losses.
The range of loss in response to a $2.50 (e.g. approximately 10%) price increase is 0.6 to
2.5 GDP growth percentage points. Translated to the total economic activity of IEA
countries such GDP growth reductions could total in the tens and even hundreds of
billions USD.
For example: the year-2000 GDP for the US and the EU-15 is $9,896 billion and $7,836
billion respectively. A 3% economic growth would translate to a GDP increase of about
$300 billion for the US and about $240 billion for the EU. Averaging the three results in
the table above yields an annual GDP reduction of 1.5%. Therefore, a 10% oil price
increase, would cut an expected 3% GDP growth by half, or 150 billion USD in the US
and 120 billion USD in the EU. If this GDP reduction were to last between three and six
months, the combined effect for the US and the EU would be a loss in the range of $67.5
– $135 billion USD. Using Rotemberg-Woodford's upper range estimate would yield a
three-six month GDP reduction in the range of $112.5 – $225 billion USD.
Of course, this is only an illustration, based on the estimates in the table above, which
were estimated using data for the years 1948 -1980. As previously noted, more recent
data suggest that GDP losses are driven by oil price volatility as well as price level, a
result that is more difficult to illustrate with a simple example.
2. Oil price and volatility patterns seem to change after 1986: Most oil price movements
in the 1948-1985 period consisted in price increases. Starting in 1986 the pattern changes.
There are large price increases and decreases that reflect a substantial rise in the volatility
of real oil price.
3. Oil price increases matter substantially more than oil price decreases. But the degree
of this asymmetry depends on the previous volatility of oil prices. Volatility weakens the
economic response to oil price changes. When it comes to oil price movements, it is the
degree of surprise that matters.
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4. Price volatility creates uncertainty in investments and reinforces sectoral shifts in
labor markets. Thus, monetary and fiscal policy measures, e.g. increasing interest rates,
and therefore increasing prices only explain a part of the oil price – macroeconomy
relationship.
5. In the postwar period, especially after 1986, oil price hikes had a significant and
detrimental effect on stock markets. The stock returns are negatively affected by both
current and lagged oil price variables. The effects of oil shocks on the US and Canadian
stock markets can be completely explained by their effects on contemporaneous and
future real cash flows. Higher costs of production due to higher oil prices will cause
earnings to decline.
1. Oil price changes and economic output
Basic studies establishing the oil price economic growth relationship
Hamilton (1983) stated that the correlation between oil price evolution and economic output
was not of a historical coincidence for the 1948-72 period. An increasing oil price was
followed 3-4 quarters later by slower output growth with a recovery beginning after 6-7
quarters. These results also apply to the period 1973-1980. The negative effect is more
distinct in inflationary times.
It wouldn’t have been possible to anticipate these reductions in real GNP growth on the basis
of the previous situation of output, prices, or money supply.
In general, Hamilton’s results have been confirmed by several subsequent studies. In 1986,
Gisser and Goodwin indicated for the analyzed period from 1961 to 1982 that the oil price
hadn’t lost its potential to predict GNP growth.
Moreover, they presented two interesting results concerning the relationship between oil price
changes and macroeconomic variables. First, they showed that monetary and fiscal policy
measures alone cannot explain the effects of oil price shocks on macroeconomy after oil
market disruptions. Thus, oil shocks also have an impact on economic output by other means
than inflationary cost-push effects. Second, oil price effects on the U.S. economy did not
change after 1973 when the OPEC period began.
Hooker (1996) confirmed Hamilton’s results and demonstrated for the period 1948-72 that
the oil price level and its changes do exert influence on GDP growth. This is shown by an
increase of 10% in oil prices that led to a GDP growth roughly 0.6 % lower in the third and
fourth quarters after the shock.5
According to Hamilton's (2000) calculations with data from 1949:2 to 1980:4, a 10% increase
in oil prices will result four quarters later in a level of GDP growth that is 1.4% lower than it
actually would be.
Regarding Hamilton’s analysis, more data was added by further investigations until 1988 –
including the oil price collapse in 1986. The real price of oil was considered in the analysis
(Mork 1989), as well. Instead of using the producer price index (PPI) for crude oil, which
5
Hooker, 1996, 199
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merely reflects controlled prices of domestically produced oil6, Mork operated with the
refiner acquisition cost (RAC) for (domestic and imported) crude oil since 1974.
The study verified Hamilton’s result as to a negative correlation between output growth and
oil price increases. The correlation is even stronger than expected.
A supposed linear relationship between oil price changes and economic growth would imply
a stimulation of economic growth by an oil price decline. However, in the 1980s, economic
output growth was slowed down by oil price changes although oil price declines occurred as
well. Thus, Mork examined possible asymmetric effects of oil market disruptions.
Asymmetry in effects
Asymmetry in effects means that oil price increases have a clear negative impact on
economic growth while oil price declines don’t affect economic activity significantly. Mork
(1989) examined the asymmetric response to oil changes by decomposing oil price changes
in real price increases and decreases. The analysis showed for the U.S. economy that “the
correlation with price decreases is significantly different and perhaps zero.”7
Mork, Olsen and Mysen (1994) confirmed the asymmetry in effects for other OECD
countries. In comparison with the other countries, oil price increases seem to slow down
economic growth in the U.S. to a great extent, even if this country is less dependent on
imported oil than countries like Germany, France, and Japan.
Lee et al. (1995) also revealed the stability of asymmetric effects in the period before and
after 1985 and whether or not it depended on other variables.
In order to explain the so-called “asymmetry puzzle”, the asymmetric mechanism between
the influence of oil price changes and economic activity, Ferderer (1996) focused on three
possible ways: counterinflationary monetary policy, sectoral shocks, and uncertainty.
Originally, three other models were also supposed to have the potential to explain the oil
price macroeconomy relationship, but could be excluded due to the fact that they presume a
symmetric relationship between oil price changes and output growth. These are: the model of
real balances (supposes that oil price increases lead to inflation which lowers the quantity of
real balances in the systems), the income transfer model (describing income transfer between
oil exporting and oil importing countries) and finally the potential output model (suggesting
that oil and capital are complements, so that an increasing oil price decreases the economy’s
productive capacity).
Ferderer finds a significant relationship between oil price increases and counterinflationary
policy responses. Nevertheless, the analysis shows that oil price increases help predict output
growth irrespective of monetary policy variables. In addition, Ferderer showed that monetary
policy measures in response to decreases in real oil prices closely resemble those for oil price
increases. Therefore, asymmetric monetary policy responses can only explain a part of the
asymmetric oil price-output relationship. Ferderer suggests that sectoral shocks and
uncertainty channels could account for part of the asymmetry effects but this would need
additional research.
6
The Texas Railroad Commission (TRC) controlled the U.S. domestic oil price in the pre OPEC-period by
influencing the quantity of U.S. oil production.
7
Mork, 1989, 744
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Balke et al. (2002) give a similar explanation of the asymmetric effects oil price shocks have
on macroeconomic activity. Monetary policy cannot alone explain real effects of oil price
shocks on real GDP. They also conclude that interest rates seem to be an important
mechanism through which oil prices affect economic output. Possible explanations are
anticipation of asymmetric real effects and Ferderer’s suggestion of investment uncertainty.
Oil price volatility emphasizes the role of these two channels (see 2.).
Exogenous oil price shocks and imperfect competition
Rotemberg and Woodford (1996) asked in a considerably different approach how come that
oil prices have such an impact on the economy when the factor of production in question, oil,
represents only a small part of the total marginal cost of production. In their analysis,
Rotemberg and Woodford focus on private added value subtracting government added value
because their theories of pricing and production decisions do not apply to governmental
demand.
In order to explain the apparent contradiction, they included the effects on real wages and the
imperfectly competitive product market model in their analysis.
Using data from 1948:2 to 1980:3, they observed that
“private output does indeed decline following a positive innovation in oil prices. A 1
percent increase in oil prices results in a reduction in output of about -.25 percent
after five-seven quarters.” 8
Interestingly, this decline in output is higher in the second year following the oil price change
than in the first.
Finally, Rotemberg and Woodford estimated that after an oil price increase of 10%, real
wages would fall by 1% after five or six quarters9.
Moreover, Chaudhuri (2000) showed another important relationship between oil prices and
real prices of primary commodities. The analysis showed that the non-stationary behavior of
real commodity prices is due to the non-stationary behavior of real oil prices. Of course, this
impact varies depending on the commodities. This is also the case even if oil is not being
used directly in the production of commodities. A change in the oil price may affect the
prices of primary commodities through the impact of the oil price changes on real exchange
rates.
8
Rotemberg and Woodford, 1996, 555
The period (1948-1980) chosen by Rotemberg and Woodford seems to weaken their results because volatility
gets much greater after 1980.
9
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2. The influence of oil price volatility
Most oil price movements from 1948 - 1985 consisted in price increases. From 1986
onwards, the pattern is changing. There are large price increases and decreases reflecting a
substantial rise in the volatility of the real oil price. Volatility is defined as the standard
deviation in a given period.
Recent experience has shown the magnitude of oil price volatility: in the first quarter of 1997,
the world oil price expressed in nominal dollars per barrel was at $21.02 and fell to a low of
$10.86 in the first quarter of 1999. Then, in the second quarter of 1999, the world oil price
began to rise dramatically to a high of $29.11 in the third quarter of 2000.10
Thus, Hooker (1996) argued that the relationship oil price-U.S. economy growth had changed
and could not be described neither by a linear relation between oil prices and output nor by
the asymmetric relation presented by Mork (1989) after 1986 and increasing oil price
volatility. Hooker’s analysis could not confirm that only oil price increases have a negative
effect on economic growth, while oil price decreases don’t affect macroeconomy. These
results are completed by subsequent studies.
Hamilton (1996) agreed with Hooker and found out that the majority of increases in oil prices
since 1986 have been followed immediately by even larger decreases. Therefore, he proposed
to compare the current price of oil with the price level of the previous year rather than only
compare it with the price level of the previous quarter; he introduced the ‘net oil price
increase’ (NOPI)11. Applied on the data after 1986, it showed that individual price increases
were simple corrections to earlier declines except for the time during the Gulf War, which
was followed by the first recession in the US.
In contrast to Hooker, Hamilton demonstrated that the relation between GDP growth and
NOPI remains statistically significant when the full sample from 1948:1 to 1994:2 is used.
Thus, Hamilton concluded that even if oil price increases seemed to have had a smaller
macroeconomic effect after 1973, oil supply disruptions have a major effect on
macroeconomy as the Gulf War showed.
Oil price shocks
Lee et al. (1995) showed that it’s not sufficient any more to explore the issue of causality of
real oil price to the macroeconomy through 1992 with the ‘classical’ instrument - the oil price
level variable - but that volatility has to be taken into account.
Using the same instruments as Mork (1989), they showed that in the period after 1988 which has not been considered by Mork – the sole consideration of changes in the real oil
price had lost its power to predict real GNP.12
10
Energy Information Administration, http://www.eia.doe.gov/oiaf/economy/energy_price.html, 07/18/2002
“It compares the price of oil each quarter with the maximum value observed during the preceding four
quarters. If the price of oil in quarter t is lower than it had been at some point during the previous four quarters,
the series is defined to be zero for date t.” Hamilton 1996, 217
12
Lee, Shwan and Ratti, 1995, 41
11
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Including the oil price shock variable in their analysis, which measures how a given oil price
change differs from the historic pattern, they can also predict GNP growth after 1988. So, it’s
the surprise of an oil shock that implies a greater impact on real GNP growth (and
unemployment). Low volatility on the oil markets before a strong oil price increase lead to a
higher impact of the oil price shock on macroeconomy than a highly volatile oil price
environment. What matters is the surprise of an oil shock.
Using a 24-quarter horizon, they predict the largest negative economic growth impulse 4
quarters after the oil price shock; recovery begins about 6 quarters later. The effect of an oil
shock diminishes considerably after ten quarters.13
Ferderer (1996) showed that both oil price changes and oil price volatility have a negative
impact on output growth, but in different ways: volatility has a negative and significant
impact on output growth, immediately and again eleven months later, whereas oil price
changes have a significant impact on output growth after about one year.
In addition, Ferderer observed that oil price volatility strongly correlates with real oil price
increases. So, oil price increases are considerably more important for oil price volatility
variance than negative real oil price changes.
In order to explain the phenomenon of fluctuations in industrial production, oil price
volatility largely dominates the oil price level. Oil price volatility explains 22% of the
forecast error variance for industrial production at the 24-month horizon, while the oil price
level explains only 9%.14 So it’s rather the volatility of oil prices than the level of oil prices
that has an important influence on economic growth according to Federer.
Hooker (1996) also emphasized the importance of volatility for the period after 1973. He
discovered that in the period from 1973:4 to 1994:2, changes in oil price levels could not
predict neither unemployment nor GDP growth any more. On the contrary, oil price volatility
can predict the GDP in the 1973-1994 period. 15 This suggests again that it is not the oil price
level but its volatility to have a significant negative impact on economic activity in the period
from 1973 to 1994.
Ferderer’s (1996) analysis of the asymmetric mechanisms between oil price changes and
macroeconomy demonstrated the effect of volatility on economy in two primary ways:
uncertainty in investments and sectoral shifts.
Uncertainty in investments
Uncertainty in investments means that volatility in oil prices is more important than the level
of oil prices, as regular changes in oil prices increase uncertainty whether to invest or not.
Ferderer refers to Bernanke who has shown it was ideal for companies to postpone
13
Lee, Shwan and Ratti, 1995, 51
Ferderer, 1996, 23
15
Hooker, 1996, 205
14
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irreversible investment expenditures when they experienced increased uncertainty concerning
the future oil price.16
Unemployment growth through sectoral shifts
After an oil price shock in a multi-sector economy, where the shift of specialized labor and
capital from one sector to another is very costly, workers don’t change immediately to
another sector but wait for conditions to improve. This can reduce aggregate employment.
Loungani (1986) examined the effect of world oil market disruptions on the reallocation
process in U.S. labor market. Loungani’s analysis from 1947 to 1982 for 28 industries
showed that oil price increases in the 1950s and 1970s seem to account for disturbing the
labor reallocation process.
Furthermore, Ferderer (1996) indicated that “aggregate unemployment rises when relative
price shocks become more variable.”17
This implies that volatility in oil prices would reinforce disturbance of sectoral adjustment on
the labor market and therefore lead to greater unemployment.
Lee et al.’s analysis confirmed this hypothesis. Real oil price surprise has a greater impact on
unemployment (as to GNP growth) than changes of the level. A stable environment before
the surprise reinforces this effect. Unemployment begins to rise 4 quarters after the oil shock
through 8 quarters after the shock that is not offset at later dates. Papapetrou (2001)
confirmed negative effects of oil price shocks on employment.
Papapetrou’s (2001) analysis showed that an oil price shock has a negative effect on
employment. Increasing costs of production result in lower output and lower levels of
employment, so she concluded:
“Oil price shocks explain a significant proportion of the fluctuations in output growth
and employment growth. Oil price shocks have an immediate negative effect on
industrial production and employment.”18
Oil price volatility and the difficulty of forecasting GDP growth
In recent works it is widely accepted that increasing oil price volatility has a great impact on
the macroeconomy and largely dominates the oil price level. Investments are postponed and
the labor market's reallocative process is disturbed.
Hamilton (2000) concluded that
“the nature of the nonlinearity is an asymmetry in which oil price increases matter
substantially more than oil price decreases and in which the sensitivity of the
16
Ferderer, 1996, 3
Ferderer, 1996, 3
18
Papapetrou, 2001, 530-531
17
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economy to oil price changes seems to be dampened by previous volatility of oil
prices.”19
Hamilton pointed out that “there is not enough information in the historical experience to
choose one particular functional form unambiguously over another”20 in order to predict GDP
growth. However, nonlinear representations as Lee et al. (1995) and Hamilton (1996)
suggested are superior to linear forecasting models. Moreover, it’s obvious that oil price
increases are considerably more important than oil price decreases. Oil price changes in a
volatile market environment are less useful to forecast GDP growth.
Nevertheless, this does not question the “abundant evidence that exogenous disruptions in
petroleum supplies […] are an important factor in causing the economic downturns.”21
3. Stock markets
Jones and Kaul (1996) belong to the first authors to analyze the reaction of international stock
markets to oil shocks by current and future changes in real cash flows and/or changes in
expected returns. Their study considered stock markets in the US, Canada, UK and Japan,
taking different institutional and regulatory environments into account.
Except for the UK, oil prices allow to predict stock returns and output through 1991 in the
other three countries.
It shows that in the postwar period oil price hikes had a “significant, and (on average)
detrimental effect on the stock market of each country”22.
It is “dramatic” in the case of Japan and less important for Canada. The stock returns of each
country – except UK – are negatively affected by both current and lagged oil price variables.
The latter are negatively more significant. This rises the question whether oil shocks induce
any variation in expected stock returns or whether the stock markets are inefficient. Due to
measurement errors for all macroeconomic variables, the authors emphasize that “the ‘true’
effects of oil shocks on stock returns are likely to be even stronger.”23
The results showed that the effects of oil shocks on the US and Canadian stock markets can
be explained completely by their effects on current and future real cash flows. However, real
cash flows and expected return proxies cannot explain the fluctuations on the stock markets
in Japan and the UK. For the stock markets of these two countries, the authors assume that
postwar oil shocks seem to have generated volatility.
Sadorsky (1999) and Papapetrou (2001) contributed further studies of stock markets.
Sadorsky’s analysis is based on monthly data from 1947 to 1996 - in contrast to quarterly
data used in the study of Jones and Kaul. The analysis showed that an oil price shock has a
negative and statistically significant initial impact on stock returns. Higher production costs
due to higher oil prices will cause earnings to decline. An efficient stock market will react
with an immediate decline in stock prices.24 Thus, individual oil price shocks depress real
stock returns.
19
Hamilton, 2000, 25
Hamilton, 2000, 34
21
Hamilton, 2000, 35
22
Jones and Kaul, 1996, 471
23
Jones and Kaul, 1996, 472 (explained in Appendix B)
24
Sadorsky, 1999, 458
20
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Sadorsky divided the period of his analysis, 1947 to 1996, into two sub-periods. The analysis
showed that oil price shocks had a larger impact after 1986. Thus, there’s rather a change in
dynamics than a change in the response of the system to these shocks.25
Finally, Sadorsky concludes “oil price shocks had a significant impact on real stock returns
although this impact was strongest after 1986 […].”26
Papapetrou (2001) estimated that real stock returns are affected negatively. This impact lasts
for approximately 4 months.
Ciner (2001) extended existing studies on the relationship between oil prices and the stock
market by testing for nonlinear linkages considering recent works on this subject (Hamilton
2000). Prior studies as the one by Hung, Masulis, and Stoll (1996 hereafter HMS) gave
evidence for a significant causality from oil futures to stocks of individual companies, but
showed no impact on a broad-based index like the S&P 500. Thus, they concluded that
influence of oil price shocks on the aggregate economy is rather “myth than reality” 27. Ciner
refuted this conclusion criticizing this study for not detecting sufficient nonlinear linkages.
Using HMS data, Ciner demonstrates a significant nonlinear causal correlation between crude
oil futures returns to S&P 500 index returns and evidence that stock index returns also affect
crude oil futures. This indicates a feedback relation between S&P 500 stock returns and crude
oil futures. The analysis for the 1990s (from March 1990 until March 2000) - when volatility
had increased - provided an even stronger nonlinear relationship than for earlier samples and
backed up Sadorsky (1999).
4. The Financial Risk of Oil and Natural Gas Price Volatility
Section to be written
Significant negative betas reported for natural gas by:
LBNL, (Steve Stoft and Ed Kahn 1993), around -0.7
LBNL ( Mark Bollinger and Ryan Wiser 2002) -- about -0.7 or smaller
Awerbuch, 94, 96, -1.00, -0.5, eventually -0.1
Imply that natural gas and oil present high cost-risk to consumers in IEA countries.
5. Conclusion
Since the 1980s, oil price volatility is more significant in its effect on economic activity than
the oil price level. A volatile environment weakens the effect of price level changes since it
reduces the "surprise." Increasing volatility creates market uncertainties that induce
companies to postpone their investments. Furthermore, volatility affects labor markets by
25
Sadorsky, 1999, 465
Sadorsky, 1999, 450
27
Ciner, 2001, 204
26
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disturbing the reallocative process among sectors. Again, it is the surprise of an oil price
increase that matters.
Hooker, Hamilton and Rotemberg/Woodford demonstrate similar results. They predict a
decline of output growth after about four quarters. The magnitude of the slow down,
however, diverges among these authors: for a 10 % increase in oil prices, Hooker predicts a
decline of 0.6 %, Hamilton a 1.4% decline and Rotemberg/Woodford predict as much as
2.5%. Rotemberg/Woodford’s inclusion of the effect on real wages and the fact that they
supposed an imperfectly competitive product and market model led to this result.
Hamilton (2000) concluded in his study on different models predicting GNP growth
evolution with the variable of oil price changes and oil price volatility that there’s not enough
historical experience to express this relationship in one clear model in order to make clear
predictions. However, there’s no doubt about the negative impact of oil price increases and
oil price volatility on economic growth during the last decades.
He emphasises that it’s less the level of oil prices suggested by production-function-based
models (Rotemberg, Woodford 1996) to influence economic growth than disruption in
supplies or surprise in pricing as it is proposed by dislocation-based interpretation (Loungani
1986). This is also evident for the stock markets since the relationship has become even
stronger after 1986 when the high price volatility on oil markets began. An oil price shock
leads to an immediate decline of real stock returns.
6. References:
Awerbuch, S. [1993], The Surprising Role of Risk and Discount Rates in Utility Integrated-Resource
Planning, The Electricity Journal, Vol. 6, No. 3, (April), 20-33
Awerbuch, S. [1995], Do Consumers Discount the Future Correctly? A Market-based Valuation of
Fuel Switching, (with William Deehan), Energy Policy, Vol. 23, No. 1 (January), 57-69
Awerbuch, S. [1995a], Market-Based IRP: It’s Easy!!!, The Electricity Journal, Vol. 8, No. 3 (April),
50-67
Balke, N.S., Brown, S.P.A., Yücel, M.K., [2002], Oil Price Shocks and the U.S. Economy: Where
Does the Asymmetry Originate?, The Energy Journal, 23, 3, 27-52
Bolinger, M., Wiser, R., Golove W. [2002], Quantifying the Value that Wind Power Provides as a
Hedge against Volatile Natural Gas Prices, Lawrence Berkeley National Laboratory.
Chaudhuri, K. [2000], Long Run Prices of Primary Commodities and Oil Prices, Working Papers, The
University of Sydney.
Ciner, C. [2001], Energy shocks and Financial Markets: Nonlinear Linkages, Studies in Nonlinear
Dynamics and Econometrics, October, 5 (3), 203-212
Ferderer, J. P. [1996], Oil Price Volatility and the Macroeconomy, Journal of Macroeconomics 18 1,
Winter, 1-26
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Gisser, M.; Goodwin, T.H. [1986], Crude oil and the macroeconomy: Tests of some popular notions.
J. Money Credit Banking 18 1, pp. 95-103
Hamilton, J.D. [1996], This is what happened to the oil price-macroeconomy relationship, Journal of
Monetary Economics 38, 215-220
Hamilton, J.D. [2000], What is an oil shock?, NBER Working Paper 7755
Hooker, M.A. [1996], What happened to the oil price-macroeconomy relationship?, Journal of
Monetary Economics 38, 195-213
Hung, R.D.; Masulis, R.W.; Stoll, H.R. [1996], Energy shocks and financial markets, Journal of
Futures Markets, 16, 1-27
Jones, C.M.; Kaul, G. [1996], Oil and the Stock Markets, The Journal of Finance, Vol LI,
No. 2
Kahn, E., Stoft, S. [1993] (unpublished draft), Analyzing Fuel Price Risks Under Competitive
Bidding. Berkeley, Calif.: Lawrence Berkeley National Laboratory.
Lee, K.; Ni, Shwan; Ratti, R.A. [1995], Oil Shocks and the Macroeconomy: The Role of Price
Variability, Energy Journal, Vol. 16, 39-56
Loungani, P. [1986], Oil price shocks and the dispersion hypothesis. Rev. Econ. Stat. 68 3, 536-539.
Mork, K.A., Olsen, O. and Mysen, H.T. [1994], Macroeconomic responses to oil price increases and
decreases in seven OECD countries. Energy Journal 15 4, 19-35.
Mork, K. [1989], Oil and the Macroeconomy, When Prices Go Up and Down: An Extension of
Hamilton’s Results, Journal of Political Economy, vol. 97, No. 51
Papapetrou, E. [2001], Oil price shocks, stock market, economic activity and employment in Greece,
Energy Economics Vol. 23 (5) September, 511-532.
Rotemberg, J.J.; Woodford, M. [1996], Imperfect Competition and the Effects of Energy Price
Increases on Economic Activity, Journal of Money, Credit, and Banking, Volume 28, Issue 4,
Part 1 Nov., 550-577
Sadorsky, P. [1999], Oil price shocks and stock market activity, Energy Economics 2, 449-469
Yang, C.W.; Hwang, M.J.; Huang, B.N. [2002], An analysis of factors affecting price volatility of the
US oil market, Energy Economics 24, 107-119
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7. Table: Overview of the studies cited and their principal results
Authors and
period studied
Hamilton (1983)
1948-1980
Objective / General idea
Demonstrates that historic
correlation between oil
price increases and
economic recessions is not
a statistical coincidence.
Assumes that disruptions
in the world oil market
generate significant
unemployment through
sectoral shifts.
Comparison to
other studies
Comments
Oil price increase was followed 3-4 quarters later by slower output
growth with a recovery beginning after 6-7 quarters.
Nominal oil price increase could be expected to lead to a minor
output effect during inflationary times than in noninflationary times
Show that oil price effects on economic output cannot be explained
only by monetary and fiscal policy.
The relationship between oil price shocks and U.S. economy didn’t
change after 1973.
Gisser, Goodwin
(1986)
1961-1982
Loungani (1986)
1947-1982
Quarterly employment data for 28
industries
Mork (1989)
1948-1988
Results
Confirm Hamilton´s
observation (1983)
regarding a similar
relationship before
and after 1973
Oil price increases in the 1950s and 1970s appear to account for
disturbing the labor reallocation process.
Analyses if Hamilton’s results remain correct when the oil market
collapse of the 1980s and the real oil price are considered as well.
Shows an even stronger negative correlation between oil price
increase and output growth than Hamilton.
Despite of oil price declines in the 1980s, economic output growth is
slowed down by oil price changes  asymmetry in effects.
Confirms
Hamilton’s (1983)
observation of a
negative correlation
between output
growth and oil price
increases and
extends data until
1988.
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Exposure Draft: 25-Sep-02
Authors and
period studied
Lee et al. (1995)
1950-1992
Ferderer (1996)
1970-1990
daily spot market
oil prices
Rotemberg and
Woodford (1996)
1948-1980
Objective / General idea
Results
Objective: Examinating
causality of real oil price
to the macroeconomy
through 1992
In a long period of stability, oil price shocks (= surprise) have a
greater impact than in a volatile environment.
- For output growth in a 24-quarter horizon the largest negative
impulse appears 4 quarters after the oil price shock, recovery
begins about 6 quarters after the shock.
- Unemployment begins to rise 4 quarters after the oil shock
through 8 quarters after the shock that is not offset at later dates.
To explain the asymmetry
in effects
-
Volatility and oil price changes have a stronger and more
significant impact on economic activity than monetary policy
variables
- Oil price increases are accompanied by greater volatility
- Oil price volatility and the Federal funds rate dominate the oil
price level in terms of explaining fluctuations in industrial
production
- Volatility has a negative and significant impact on output growth
immediately and again eleven months later.
- Oil price changes have a significant impact on output growth
after about one year.
Imperfectly competitive market models can explain the great effect of
oil price changes on output growth and real wages.
- A 1% increase in oil prices results in a reduction in output of
about -.25 percent after 5 - 7 quarters
- After an oil price increase of 10%, real wages fall by 1% after 5
or 6 quarters after this increase
The decline in output and real wages gains importance in the second
year after the oil price shock.
Comparison to
other studies
The important point
of this study is the
inclusion of the
variable oil price
shock, that means
the measure of how
a change in the
given oil price
differs from the
historical pattern.
U.S. economy is
affected by oil
market disruptions
from the 1970s til
the 90s through
sectoral shocks and
uncertainty as
shown by Lee et al.
Comments
Ferderer finds
evidence that
volatility has a
greater impact than
the oil price level!
The period chosen
seems to weaken the
qualitative results
because oil price
declines and volatility
occur in the 1980s.
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Exposure Draft: 25-Sep-02
Authors and
period studied
Hooker (1996)
1948-1994
Objective / General idea
Hamilton (1996)
1973-1994
Due to the oil price
volatility since 1986, the
period of the previous year
has to be considered rather
than only the previous
quarter when analyzing oil
price development (net oil
price increase (NOPI))
Hamilton (2000)
1949:1999
Chaudhuri (2000)
1973-1996
Results
1948-1972:
10% increase in oil prices led to GDP growth roughly 0.6 % lower in
the third and fourth quarters after the shock
1973-1994:
Neither unemployment nor GDP growth can be predicted by oil
prices levels.
However, GDP growth could be predicted sometimes by volatility .
Relation between GDP growth and NOPI remains statistically
significant for the full period from 1948:1 to 1994:2.
Comparison to
other studies
Refutes the linear
relation between oil
prices and output
(Hamilton 1983) and
the assymmetric
relation based on oil
price increases
(Mork 1989).
Hamilton agrees
completely with
Hooker refuting
linearity and
asymmetry in the oil
price macroeconomy
relationship.
Comments
Oil price increases matter substantially more than oil price decreases.
Increases that occur after a long period of stable prices have a bigger
impact than those that simply correct previous decreases.
From 1949 to 1980 a 10% increase in oil prices resulted four quarters
later in a level of GDP growth that was 1.4% lower.
But today, there is not enough historical experience to choose one
particular functional form unambiguously over another.
Real oil prices have an influence on real commodity prices, even if
oil is not being used directly in the production of commodities. An oil
price change may affect the prices of primary commodities.
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Stock markets
Authors and
period studied
Jones, Kaul
(1996)
U.S.: 1947-1991
Canad.: 1960-1991
Japan: 1970-1991
UK: 1962-1991
Objective / General idea
Objective: examinating if
stock prices rationally
reflect the impact of news
on current and future real
cash flows in the U.S.,
Canada, Japan and UK.
Sadorsky (1999)
1947-1996
Papapetrou
(2001)
1989-1999 for
Greece
Ciner (2001)
1983-2000
28
Results
Oil price hikes had a “significant, and (on average) detrimental
effect on the stock market of each country”28. It is “dramatic” in
the case of Japan and much weaker for Canada.
- For each country –except UK – both current and lagged oil price
variables affect stock returns negatively. The fact that the latter
has a greater negative influence suggests that oil shocks induce
some variation in expected stock returns or the stock market’s
inefficiency.
The average value of a negative shock is 20% larger in absolute value
than the average value of a positive shock.
- Oil price shocks have an immediate significant impact on real
stock returns, this impact was strongest after 1986. Increasing oil
prices depress real stock returns.
- After 1986 there’s rather a change in dynamics than a change in
the response of the system. Thus, oil price volatility shocks play
an important asymmetric role.
In a mid- and long-term relationship, oil price shocks account for
20% (up to 22%) of change in industrial production.
1) Effects of an oil price shock including industrial production:
- Immediate increase of interest rates
- Immediate decrease of industrial production (peak after 4
months)
- Immediate decrease of real stock returns
2) Effects of an oil price shock including employment:
- Immediate increase of interest rates
- Decrease of employment (after 4 months)
- Decrease of real stock returns
Significant nonlinear causality from crude oil futures returns to S&P
500 index returns and evidence that stock index returns also affect
crude oil futures, suggesting a feedback relation.
The relation is even stronger in the 1990s.
Comparison to
other studies
Comments
-
The study back up
the results of Jones
and Kaul by using
monthly data instead
of quarterly data.
Confirms
Sadorsky’s (1999)
results of stronger
effects of oil price
shocks after 1986.
Jones and Kaul 1996, 471
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