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MAXIMIZING HAPPINESS IN FUTURE

POSITIVE OIL PRICE SHOCKS

by

James D. Coan

April 7, 2009

A Senior Thesis presented to the Faculty of the Woodrow Wilson School ofPublic and International Affairs in partial fulfillment of the requirements for thedegree of Bachelor of Arts.


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Acknowledgements

I would first like to thank my thesis adviser Amy Craft for spending hoursanswering my many questions. Before taking her energy economics class lastyear, I would think of policies to reduce oil consumption without really analyzing

the damage the oil use caused. This paper is a direct result of my desire to knowmore about the costs of an oil shock.The notion that this work is my senior thesis gives the impression that it is

an endeavor lasting one year. Yet oil and energy have been interests of minesince 10

thgrade, and I thank all of those who provided opportunities for me to

learn about the field through internship opportunities. Jon Hurwitch at Sentech,Inc. in Bethesda, Maryland gave me my first internship before my junior year ofhigh school, and I then learned from Therese Langer at the TransportationProgram of the American Council for an Energy-Efficient Economy, and FrankVerrastro, Dave Pumphrey, and Jen Bovair among others at the Center forStrategic and International Studies.

Much of my learning came from entering policy contests about energy,and I thank those at Chrysler (then DaimlerChrysler), the Brookings Institution,the Roosevelt Institution, and the Presidential Forum on Renewable Energy fordeciding to put up a little money to encourage students to think about automotivetechnology or policy.

This paper covers two huge bodies of literature, and I must thank theleading scholars in these fields for making my work possible (as well as thosewho created the database Scopus for making the process of finding their workeasy). Of all those working on the effects of oil on the economy, the work ofeconomists James Hamilton and Lutz Kilian proved the most influential for me.Additionally, I am grateful for the work of Daniel Kahneman, Rafael Di Tella,Robert MacCullough, Andrew Oswald, Alois Stuzer, Bruno Frey, and manyothers for their work with happiness and subjective well-being. I knew nothingabout surveys of well-being before starting, and I find the possibilities ofanalyzing a whole suite of policies using happiness as a metric extremely exciting.I plan to use the work in this paper for years to come.

Deviating some from effusive praise, I admit that my interest in oil policyblossomed to a large extent because I felt an opening for creativity while so fewpolicy ideas to reduce oil use were able to be seriously discussed on Capitol Hillbefore 2007.

However, I am fine giving excessive praise to my parents who havesupported me through all my pursuits including energy. There are relatively littlethings they have done like bankrolling the many printer cartridges I went throughwhile I was home. But the core point of this paper is that happiness and not justmoney is what matters. I thank them for much more for always checking in tomake sure I was getting enough sleep while fighting mononucleosis and lymedisease during this process and making sure I was staying generally happy whilewriting about happiness.


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Table of Contents

Abstract_________________________________________________________ 4

Executive Summary________________________________________________ 5

Chapter 1: Another Oil Shock Is Very Possible__________________________10

Chapter 2: The Traditionally Measured Impacts of an Oil Shock____________ 19

Chapter 3: Measuring Happiness_____________________________________ 47

Chapter 4: How an Oil Shock Impacts Happiness________________________ 86

Chapter 5: Maximizing Happiness in the Next Positive Oil Price Shock______ 99

Works Cited____________________________________________________ 112

Appendix A: Data on Impacts of an Oil Shock_________________________ 119

Appendix B: Subjective Well-being Data______________________________122


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Abstract

Oil prices skyrocketed in the first part of 2008. While the world iscurrently mired in an economic downturn that has substantially reduced demand,

another rapid increase in the price of oil known as an oil shock has a reasonablyhigh risk of occurring again. Factors contributing to previous shocks includingpolitical instability in the Middle East, the power of the Organization ofPetroleum Exporting Countries (OPEC), and growth in developing countries areall expected to be present in the future.

These oil shocks impact a whole host of factors that affect well-being.Some like income and various macroeconomic variables are negatively affected,but there are also benefits from reduced vehicle miles traveled. While the effectscan be qualitatively described as bad or good, it is difficult to know howindividuals are impacted and which impacts are the most significant.

This paper tries to quantify the impact by combining literature on oil

shocks with another body of literature that analyzes surveys of happiness or lifesatisfaction of individuals. These subjective well-being surveys have beengiven since the 1970s, and economists have analyzed them to find connectionsbetween individual well-being and the variables an oil shock impacts.

The negative impacts are at least an order of magnitude worse than theoffsetting positive ones. For a one-year-long $20/barrel shock, the worst impactappears to be related to a fear effect of unemployment among the generalpopulation. Manufacturers inflexibility in response to changing consumerpreferences appears to be a major cause of unemployment, although changes tothe trade deficit can also play a significant role at times.

Types of policies that can reduce the negative impacts of an oil shockshould primarily attempt to reduce consumption of gasoline and diesel, but therealso may be some benefit from encouraging manufacturing flexibility, giving cashtransfers to lower-income individuals during a shock, increasing domesticsupplies, and taxing gasoline to reduce volatility in consumer automobilepurchases.


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Executive Summary

Despite the current economic crisis, oil prices will likely once again

quickly increase much as they did in 1973, 1979, 1990, and between 2002-2008.

The political uncertainty in the Middle East and the power of OPEC that led to the

oil shocks before this decade are still present, and the most recent major oil

price increase that culminated with prices reaching over $147/barrel in the

summer of 2008 demonstrates that rapidly increasing demand and potentially

speculation can also cause oil prices to rise. With all these risk factors for another

shock, it is reasonable to try to reduce the risks of a future shock through

government policy.

In order to make appropriate policy from the perspective of the U.S.

government, the impacts of an oil shock on the well-being of U.S. residents must

be known. Chapter 2 analyzes the effect of a unit standard deviation oil price

shock, which translates into a sudden increase in the price of oil of about

$20/barrel, or the equivalent to about 50 cents/gallon of gasoline. A shock

negatively impacts income and various macroeconomic variables (unemployment,

GDP, inflation, and interest rates) while tending to increase the trade deficit,

which can pose risks. However, by reducing vehicle miles traveled (VMT) and

oil use, a shock also has some positive impacts of reduced air pollution, traffic

and traffic deaths.

Economic analyses of oil shocks show that the impact of an oil shock on

macroeconomic variables may only have 20-25% of the effect as it once had in

the 1970s. Elasticity of VMT with respect to the price of gasoline has also


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declined substantially. However, impacts on individual incomes have not

declined nearly as precipitously, and the effects on the trade deficit and dollar

may be more significant.

This body of literature gives only a sense of how these changes actually

impact the well-being of individuals. For instance, rising unemployment is

clearly bad, but it is difficult to know how the negative impact compares with

other impacts of a shock. Without this knowledge, it becomes close to impossible

to have a good sense of whether any particular government policy designed to

reduce the impacts of a future shock will actually improve well-being on the

whole.

To fill this gap, Chapter 3 surveys another body of literature that has

analyzed surveys of happiness or life satisfaction. These subjective well-being

(SWB) surveys have been administered to hundreds of thousands of people in the

U.S. and Europe since the early 1970s. Various economists have used these

surveys to calculate how income changes, macroeconomic variables, and

commuting time affect SWB. For instance, these surveys show that a given short-

term income loss is about five times worse than the same long-term gain, and

becoming unemployed is as bad as falling from the top of the income distribution

to the bottom. The surveys also provide a way to think about how to account for

premature death from traffic fatalities and air pollution.

These surveys are considered quite reliable. Responses to these SWB

surveys are well-correlated with a host of outward signs of well-being such as

assessments of happiness by friends and family and the frequency of authentic


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smiles (Blanchflower and Oswald 2004). Temporary mood changes rarely affect

answers, and answers to questions about life satisfaction and happiness are quite

similar (Eid and Diener 2004; Di Tella et. al. 2001).

When using SWB surveys, all the impacts of an oil shock can be

combined into one common metric of well-being. Such an outcome corresponds

well to the goals of Thomas Jefferson in theDeclaration of Independence, the

Utilitarian philosophers Jeremy Bentham and John Stuart Mill, and utility-

maximizing modern-day economists, who all believe it is desirable to maximize

well-being (or utility) of individuals.

Chapter 4 combines the work of Chapters 2 and 3 in order to determine

the actual impact of a unit oil price shock on SWB. The effect is overwhelmingly

negative, as negatives outweigh positives by at least an order of magnitude, even

when accounting for the sensitivity analyses. The most prominent negative

impact is due to a population-wide response to a higher unemployment rate, likely

from feelings of greater job insecurity. Traditional economic techniques that only

focus on the decisions of individuals rather than surveying their feelings could not

have led to such a conclusion.

Chapter 5 concludes the paper by discussing possible policies that could

potentially maximize SWB given a future oil shock. These policies address the

mechanisms that lead to the negative effects of oil price shocks. Consumers feel

an income loss primarily because of changes in gasoline prices. One major reason

that macroeconomic variables are affected appears to come from a change in

consumer purchasing behavior away from certain durable goods, toward more


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efficient products, and between different industries. This change in behavior can

expose frictions in various industries that cannot quickly respond to preference

changes, resulting in unemployment and GDP loss. Impacts to the trade deficit

and the dollar can also substantially influence the movement of macroeconomic

variables, especially interest rates. Changes to the trade deficit and the dollar may

actually lead to benefits for the U.S. in the short-term in some instances, but an oil

shock increases risks of substantially negative impacts.

Reduced consumption of fuel should reduce impacts on individual budgets

and minimize changes in consumer behavior. A fuel economy standard, rebates

and taxes on new vehicles based on efficiency, a program to purchase inefficient

used vehicles, and a gasoline tax can all reduce consumption. In some

circumstances, it may be helpful to make direct cash transfers to lower-income

households during an oil shock. The government can also look into mandating

more flexible automobile manufacturing and increasing domestic supply. Future

studies can analyze the cost of implementing these various policies using the

SWB calculations in Chapter 3.

Despite the advances in this paper that allow policymakers to think about

well-being together rather than many disparate individual metric, good judgment

is still essential. Policies should be targeted on the basis of a judgment of the

magnitude, duration, timing, frequency, and to some extent source of future

shocks. The uncertainty for many of the impacts to macroeconomic variables is

quite large. Finally, this paper discusses many ethical issues including

discounting future happiness and accounting for premature death and the well-


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being of children, future generations, foreigners, and non-human animals. The

use of SWB surveys can be a great advance in the analysis of policy, particularly

to address oil shocks, but they alone will not provide all the answers.


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Chapter 1: Another Oil Shock Is Very Possible

Four years from now, we may expect the price of oil still to be at $115a barrel, though we would in fact not be all that surprised if it is as low as $34 oras high as $391!

- James D. Hamilton, energy economist (June 2008)

In the next couple of decades, a reasonably high risk exists that oil prices

will once again rapidly increase. This hypothesis inspires this paper.

Historical evidence supports this prediction of one or more relatively sudden and

noticeable increases in oil prices, a phenomenon known as a positive oil price

shock.1

At least six different oil shocks have affected the U.S. since WWII, five

of which have occurred since 1973. Political events in the Middle East that

resulted in rapid reductions of supply primarily caused the shocks before 1998.

Tensions that could lead to future supply reductions are still present in the region.

Yet this most recent price increase in the last decade appears to show that

increased demand and possibly speculation in oil can also result in price increases

(Hamilton 2008b).

Historical Oil Shocks and Price Movements 1945-1998

Five major political events have triggered sudden reductions in oil output

for the world market between WWII and Operation Desert Storm, as shown in

Table 1.1.

1 Some writers (i.e. Hamilton 2003) have tried to formalize the notion of an oil shock, but thegeneral idea of a relatively rapid and noticeable price change is sufficient for the purposes here.


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Table 1.1: Political Events that Led to Supply Reductions

Date Event Drop in WorldProduction (%)

Nov. 1956 Suez Crisis 10.1

Nov. 1973 Arab-Israeli War and OPEC Response 7.8

Nov. 1978 Iranian Revolution 8.9Oct. 1980 Iran-Iraq War 7.2

Aug. 1990 Persian Gulf War 8.8

Source: Sill 2007

All the political events that caused these reductions clearly occurred in the

Middle East. It should be noted that the 1973 reduction was a result of an oil

embargo in which Arab nations within the Organization of Petroleum Exporting

Countries (OPEC)2

refused to sell oil to the U.S. and a few other nations who

supported Israel during the Arab-Israeli War, which is also known as the Yom

Kippur War. The embargo lasted from October 1973 until March 1974. There

had been a much less successful oil embargo in 1967 after the Six-Day War (State

2009).

However, as shown in Figure 1.1, these supply reductions led to oil shocks

of very different magnitudes and durations.

2 Currently twelve countries comprise OPEC: Algeria, Angola, Ecuador, Iran, Iraq, Kuwait, Libya,Nigeria, Qatar, Saudi Arabia, the United Arab Emirates, and Venezuela. Angola joined in 2007.Ecuador was a member from 1973-1992 and then rejoined in 2007. Indonesia was a member from1962-2008.


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Figure 1.1: Real Oil Price Since 1945

Source: Hamilton 2008b using monthly average West Texas Intermediate prices3

This graph shows the impact of these various supply shocks, which had

widely different effects in terms of magnitude and duration:

1956: Despite a very large reduction in production, world prices stayed

relatively constant. At the time, the U.S. was still a dominant and growing

supplier of oil and had enough spare capacity through the Texas Railroad

Commission to mitigate the impact of the supply shock on price (Yergin 1991).

1973: Prices almost immediately increased by about $30/barrel, more than

doubling the price of oil. The prices stayed relatively constant for more than the

next five years, not significantly changing until the next oil price shock.

1979: Although the Iranian Revolution and the Iran-Iraq War were two

separate political events in 1978 and 1980, oil prices only spiked once beginning

in the spring of 1979. The magnitude of the increase at its maximum was about

$50/barrel. Unlike the previous oil shock, prices began to retreat soon after

3 They are deflated with the September 2008 consumer price index (CPI).


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reaching their peak, although they still remained above the levels of the 1973-

1979 period in real terms until 1985.

1990: The price of oil very briefly increased about $30/barrel and then

came back down to its original level in a matter of a few months.

In addition to the positive shocks, the graph also indicates a negative

supply shock in 1986 when Saudi Arabia steeply increased its production, leading

to an oil glut and precipitous drop in prices (Yergin 1991). Additionally, although

prices were generally low before 1973 and from 1986-1998, the volatility in the

second half of the period is much greater (Regnier 2007). The oil prices had been

generally set at a nominal level, so they fell gradually in real terms before 1973,

but afterward factors such as higher summer demand and varying worldwide

economic conditions affected prices (Sill 2007). Even with this volatility, the

prices generally stayed between $20-$40/barrel in real terms.

Varied Reasons for Oil Price Increases Since 1998

The price of oil rose dramatically from 1998 to mid-2008. The increase

can be split into three main shocks, each of increasing magnitude from spring

1999 fall 2000, summer 2002 summer 2006, and winter 2007 summer 2008.

The increases were about $20/barrel, $50/barrel, and $80/barrel respectively.

After each rise, prices quickly fell by roughly $20/barrel for a short period of time.

The increases occurred for a variety of reasons, some of which are similar

to drivers of the price before 1998. Supply restrictions were a likely cause of a

brief shock of about $10/barrel from January-March 2003. A roughly two-month-


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long Venezuelan oil strike began in December 2002, and the markets likely

responded to the increasing likelihood of the invasion of Iraq, which occurred in

March 2003 (BBC 2003). In 2002, Venezuelan oil production had been 2.9

million barrels/day (mb/d), and Iraqs was 2.1 mb/d, compared with total world

production of 75 mb/d, meaning that a disruption of supply from either country

was significant (BP 2008).

As was the case in the 1980s and 1990s, business cycles and seasonal

patterns also drove the price of oil. For instance, oil prices had fallen in 1998

during the Asian financial crisis, and they fell again in 2001, probably in response

to the U.S. recession at the time. Prices then began increasing again in 2002 as

the U.S. economy recovered.

However, demand also appears to have driven the price of oil after 2002.

Hamilton (2008b) among others supports the theory that strong global demand for

oil, especially from rapidly developing nations such as China, has contributed to

an increase in the oil price in the past decade. Developing a new oil field requires

a long lead time, allowing growth in demand to outpace new supplies for years.

Concerns about the availability of supply likely exacerbated the impact of

demand growth on price. National Oil Companies control much of the worlds

supply, and some countries have restricted international access to these sites (Jaffe

and Soligo 2007). Economists doubt the presence of an actual approaching

physical peak of oil production, arguing that production is responsive to price and

that many substitutes for oil (i.e. unconventional fuels, biofuels, and electrified

vehicles) can be brought into the market within an intermediate timescale


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(Watkins 2006). However, restrictions on the physical access to sources of oil

and these time lags needed to bring these alternatives to market create

opportunities for prices to increase markedly before markets and governments can

sufficiently respond.

Additionally, as Congress heatedly debated during the summer of 2008,

speculators may also have contributed to some of the price increase, at least in

the last shock beginning in early 2007. Spector (2008) believes this argument,

noting that many new players got involved in the oil market who were heavily

weighted toward assuming the price would continue to increase. Hamilton

(2008b) provides theoretical support, saying that if buyers had different amounts

of information, they could push up prices. In this case, risk-averse people would

not balance these ill-informed speculators who are betting on increased prices. Of

course, this herd mentality in terms of speculators could also run in reverse,

quickly driving prices down.

Gasoline Price Shocks

Gasoline prices rather than oil prices are responsible for much of the

impact on individual incomes, the broader economy, and reduced driving. In

general, the price of gasoline tracks the oil price. A barrel of crude oil is

equivalent to 42 gallons, so a $1/barrel increase in the price of oil should translate

into an increase of 2.38 cents/gallon assuming all other components of the price of

gasoline such as the refinery margin and taxes remain constant.


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However, refinery margins that make up much of the difference between

the oil price and gasoline price can fluctuate. In rare cases like in 2005 in the

aftermath of Hurricanes Katrina and Rita, gasoline and oil prices can move in

opposite directions. Some damaged refineries in the U.S. along the Gulf Coast

shut down, creating a shortage of gasoline supply that led to a very significant

price shock for gasoline in the U.S. This gasoline shock occurred even as the

world price of oil declined slightly (Edelstein and Kilian 2007). A future natural

disaster could cause another gasoline price shock in the absence of an oil price

shock if this spare refining capacity issue is not fixed.

Significant Potential for Future Shocks

The supply and demand causes of previous oil shocks are quite likely to be

present in the future. The possibility of a future oil price shock is a real risk, and

public policy can try to minimize the potential for losses should prices rise

quickly again.

Political instability is still present in many of the largest exporters, and

OPEC is willing to cut supply in order to raise prices as has been shown already

in 2009 (Reuters 2009). A brief look at major oil exporters points to any number

of problems that could lead to a supply shortage. For instance, Venezuelan and

Russian leaders have asserted themselves through resource nationalism, and

fighting in Nigeria has caused reductions in production (Jaffe and Soligo 2007).

Terrorism poses a threat to major oil exporters, such as in February 2006 when

two cars carrying explosives tried to ram the gates of the Abqaiq oil production


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facility in Saudi Arabia that could have taken 4-5 mb/d off of the market for one

year had it succeeded (BBC News 2006).

These supply constraints could have even greater impact on prices today

than in the 1970s. The short-term elasticity of demand for gasoline has dropped

very steeply from between -0.21 and -0.34 in the 1975-80 period to only between

-0.034 and -0.077 between 2001-06 (Hughes et. al. 2008). Gasoline is currently

about 45% of overall oil use, but it appears as though the price elasticity of overall

oil use is very similar to the elasticity for gasoline; Hamilton (2008b) calculates

an elasticity for oil of -0.26 for the years 1978-81 (EIA 2009b). Inelastic demand

can lead to greater price increases by amplifying the effect of a supply shock. The

five-fold or so reduction in elasticity more than outweighs the relatively minor

reduction in production from OPEC and the Middle East since the 1970s, as

shown in Table 1.2. Considering that OPEC and the Middle East have 61% and

75% of world proved reserves of crude oil respectively, the long-run trend should

be toward greater concentration of production (BP 2008).4

Table 1.2: Proportion of Oil from OPEC and Middle East Down Slightly

Year WorldProduction(mb/d)

OPECProduction(% of World)

Middle EastProduction(% of World)

U.S. Production(% of World)

1973 58.5 53.1% 36.3% 17.9%

1979 66.1 47.5% 33.3% 15.3%

1990 65.5 38.3% 26.8% 13.6%

2003 77.0 41.1% 30.3% 9.6%2007 81.5 43.2% 30.8% 8.4%

Source: BP 2008

4 This statement does not assume alternative fuels, which can reduce the concentration.


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Predicting when the next supply shock is inexact, but it is clear that no 20-

year period has gone by since WWII without a significant reduction in supply.

Since 1945, a major supply reduction has occurred about every ten years.5

Compared with supply issues, the possibility of demand growth again

causing oil prices to rise may seem improbable given the current state of the

world economy, but given an outlook of a couple of decades, it is very possible

that oil demand will recover. Developing countries still have much room to

increase their oil consumption. For example, residents of China currently only

use about 10% of U.S. consumption per capita (Hamilton 2008b).

Unlike the potential supply and demand constraints, the influence of

speculators may somewhat diminish if governments curtail their ability to get

involved in the oil market. More broadly looking at investment, however, would

indicate that currently low prices for oil may lead to future price shocks if it

discourages investment searching for new supplies in the present.6

While a price shock might not happen in the next couple of decades or

longer, history indicates that another shock has a high likelihood of occurring.

Public policy should address this risk, but appropriate policies can only be

designed with an understanding of the magnitude and composition of the effects

of an oil price shock.

5 There is an average of 9.7 years (+/- 1.8 years) between the major supply reductions in 1956,1973, 1978, 1980, 1990, and 2003.6 It could also blunt the political drive to implement policies that would reduce consumption.


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Chapter 2: The Traditionally Measured Impacts of an Oil Shock

Nowadays people know the price of everything and the value of nothing- Oscar Wilde, The Picture of Dorian Gray (1891)

An oil shock affects many variables that can increase or decrease well-

being. For this paper, the effects are divided into four broad categories: 1) income

loss; 2) changing macroeconomic variables (unemployment, gross domestic

product (GDP), and inflation/interest rates); 3) trade deficit; and 4) benefits of

driving less (reduced traffic deaths and property damage, traffic congestion, and

air pollution). The first three categories have negative impacts, while the fourth is

positive.

This chapter contains many numbers that estimate these impacts, but they

should be approached with caution. The impacts on macroeconomic variables

and trade deficit are quite uncertain. Additionally, as author Oscar Wilde reminds

us with the quote above, these numerical impacts themselves are just numbers.

They do not correspond to well-being until they are combined with the effects on

happiness described in Chapter 3.

In contrast, the descriptions of the mechanisms that lead to the changes in

macroeconomic variables and the trade deficit can directly influence the types of

policies considered. For instance, it appears as though much of the reason for the

decline in GDP and rise in unemployment is due to changing consumer behavior

and the subsequent inability of manufacturers to respond to the changes quickly.

Therefore, polices that reduce consumers percentage changes in income and

those that try to increase flexibility of manufacturing may have merit. Yet if the


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major cause of a GDP loss were due to a supply shock that manufacturers felt,

governments should probably focus more on giving tax breaks to businesses.

A Unit Positive Oil Shock

The effects in this chapter are described for a one standard deviation unit

oil shock, or unit shock for short. In other words, a unit shock occurs when

the price of a barrel of oil increases by one standard deviation, which is

determined by looking at historical oil prices. This measurement is used in many

of the analyses that try to measure the impact of an oil shock on macroeconomic

variables, so it is adopted for this paper.

A unit shock is $20/barrel in current dollars, which is slightly under

$.50/gallon of refined product. This figure was calculated using costs of imported

crude oil since 1973 (EIA 2009a; EIA 2009b). Various measurements starting

with 1973 using monthly, quarterly, and yearly data and ending in 1988, 1993,

and 2008 all yielded standard deviations between $18 and $20.50/barrel. Various

end dates were tested because some of the analyses end earlier than other,

potentially altering the definition of a unit shock.

The standard deviation for gasoline prices has a slightly wider range with

values of $.47/gallon to $.54/gallon depending on the end date for the data (EIA

2009b). For this analysis, it will be assumed that the effect on gasoline prices of a

unit shock is $.50/gallon. The slightly higher figure of $.54/gallon measures data

until 2008, which also includes the gasoline-specific shocks near the time of

Hurricanes Katrina and Rita described in Chapter 1.


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EFFECTS ON INCOME

An oil shock will be thought of as a tax on consumers. Consumers have

an expected budget that includes some fuel usage, and a higher price for fuel

reduces disposable income to pay for that fuel as well as all other goods.

Changes to the price of gasoline and motor oil account for over 90% of the

costs, with fuel oil and other fuels as the remainder (BLS 2008). The impact

strongly depends upon the income quintile of the consumer, as shown in the table

below, with reductions ranging from about 0.5-2% of income from a unit shock.7

Thus, if gasoline prices are $2/gallon, gasoline accounts for about 2-8% of income,

making it a very significant component of a family budget.

Table 2.1: Effects of an Oil Price Shock on Income by Quintile

IncomeQuintile

Income AfterTaxes

GallonsUsed

Expense of$.50/gallonincrease

% of After-tax income

1 (lowest) $10,534 402 $201 1.91

2 $27,419 674 $337 1.23

3 $45,179 907 $453 1.004 $70,050 1,128 $564 0.81

5 $150,927 1,404 $702 0.47

Sources: BLS 2008; EIA 2009b

The impact of the oil price increase may be less for some consumers who

can reduce their fuel consumption. These consumers reveal their preferences that

the marginal use of the fuel is worth less than the elevated price for it. However,

this effect is small in the short-run because there are low short-run elasticities of

3-7%, and higher-income consumers for whom the higher price is less significant

are the ones who are more elastic (Hughes et. al. 2008). They recognize that it

7 This calculation assumes that all fuel is the price of gasoline. It appears as though residual fueloil is about one-half of the


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may seem surprising that higher-income individuals have more elastic demand,

but they often have multiple vehicles that consume different amounts of fuel, and

they also take more unnecessary trips that can be cut back.

This calculation may underestimate the impact on some consumers who

need to borrow extra money to pay for their gasoline use. Much of this borrowing

will occur on credit cards, which had an average interest rate of 13.5% as of July

2008 (Woolsey and Schulz 2009).

IMPACTS ON MACROECONOMIC VARIABLES

How an Oil Price Shock Impacts Macroeconomic Variables

Scholars disagree on the mechanisms by which an oil price shock changes

macroeconomic variables. Nevertheless, their work points to four major potential

causes: 1) a supply shock that impacts businesses; 2) altered consumption patterns

among consumers and firms; 3) trade deficit impacts; 4) a Federal Reserve

response. Altered consumption patterns negatively impact the economy when

businesses are not flexible enough to respond to changes in preferences, thus

leading to GDP loss and unemployment.

The first notion that an oil shock impacts business by raising production

costs is a conventional explanation for how the shock is transmitted through the

economy (Guo and Kliesen 2005). This impact could then lower firms profits

and reduce their willingness to invest in capital goods (Cologni and Manera 2008).

It is also plausible that these firms would lay off employees in order to become


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more profitable. Those who were laid off and those who feared getting laid off

would then reduce their purchases of goods, further worsening the economy.

A more recent explanation is that an oil shock harms the economy by

changing the consumption patterns among consumers and to some extent firms.

Edelstein and Kilian (2007) take an in-depth look at how consumer purchasing

behavior changes with an oil price shock. They attribute changes in behavior to

an unexpected loss of discretionary income and an uncertainty effect that reduces

willingness to purchase goods, especially certain durables like automobiles. In

their opinion, other possible mechanisms from the consumers include an

increased desire to save, known as precautionary saving, and a desire to avoid

spending on goods that use more energy. The effect from consumers can be both

a result of decreased income and greater uncertainty about future energy costs,

and the uncertainty can especially hurt vehicle sales (Kilian 2008).

This change in consumer behavior can hurt businesses and lower the

firms willingness to invest. It can also lead to difficult labor and capital

reallocations (Gronwald 2008). Various sectors can be affected to different

degrees, and these imbalances as well as the inability to coordinate among firms

can harm the economy (Lardic and Mignon 2008).

The third mechanism involves the impact of oil imports on the trade

deficit and U.S. dollar. However, the impact may be positive or negative,

especially depending upon the willingness of foreign lenders to fund the deficit

and the confidence of foreigners in the dollar and U.S. economy more broadly

(Higgins et. al. 2006). A greater trade deficit can potentially make it more


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difficult to find capital to fund the deficit, raising interest rates. Higher interest

rates can deter investment and therefore impact GDP and other macroeconomic

variables. Yet a weaker U.S. dollar will tend to boost exports, also impacting

these variables but potentially in a positive way.

Finally, some have argued that a large percentage of the impacts on the

economy are due to the monetary policy response to the oil shock rather than the

shock itself. Bernanke et. al. (1997) provides a clear example of this reasoning.

They say that most or even all of the reduction in GDP from the shocks of 1973,

1979, and 1990 are due to a monetary response.

Plausibility of Transmission Mechanisms from Shock to Macroeconomy

Although no clear consensus exists, it appears as though the literature

generally supports the consumer-based demand-side account. The transmission

channel through trade also seems very plausible. In contrast, the supply-side and

monetary policy impacts appear to have more limited impacts, although they are

still present for some industries and in some circumstances.

Consumer spending accounts for more than 70% of GDP, making

relatively small percentage changes in consumption behavior quite significant

from the perspective of manufacturers (Goodman 2008). Two economists who

have extensively studied the impact of oil on the broader economy, James D.

Hamilton and Lutz Kilian, both believe consumers are the dominant force in

affecting macroeconomic variables, particularly GDP. Noting that rising oil

prices until 2005 had still not led to a decline in consumer consumption or a


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recession, Hamilton writes how the experience is consistent with the belief that

the key mechanism whereby oil shocks affect the economy is through a

disruption in spending by consumers and firms (Hamilton 2008a). Edelstein and

Kilian (2007) make an even stronger argument for the preeminence of this effect,

arguing that in the absence of a consumer and firm response, the effects of

energy price shocks on the economy will be small.8 Few if any economists have

tried to directly contradict this argument, although some have emphasized

different mechanisms such as the monetary policy response.

While fewer have directly tried to emphasize the importance of changes to

the trade deficit and U.S. dollar, the magnitudes involved suggest that they could

both significantly impact macroeconomic variables. In 2007, U.S. net imports

were about 12 mb/d, so a year with a price that is $20/barrel higher would amount

to a trade deficit that is larger by about $85 billion assuming everything else stays

constant (How Dependent 2008). Such a value is about 0.6% of GDP, which is

relatively significant. It may seem somewhat small considering the trade deficits

in this past decade were sometimes more than 6% of GDP. However, many

commentators were concerned at such deficits that were very large from an

historical perspective (Iley and Lewis 2007). And as Figure 2.1 shows, with

higher prices, a large percentage of the deficit can at least be calculated from oil

prices. Finally, Rebucci and Spatafora (2006) calculate that there can be

significant impacts to macroeconomic variables from changes to the trade deficit.

8 This may seem surprising considering oil is a major manufacturing input.


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Figure 2.1: Oil As Large Percentage of Trade Deficit

Source: The Economist (FEER 2008)

In comparison, there are fewer arguments in favor of attributing negative

outcomes of an oil shock as primarily being a result of a supply shock to

businesses or monetary policy. Lee and Ni (2002) find that it is only a supply

shock to firms that are very oil-intensive, whereas others are primarily impacted

because of changes in consumer preferences. Automobile manufacturers, for

instance, are primarily negatively impacted from changes in the purchasing

decisions of consumers, not from higher prices that make manufacturing more

expensive. As for monetary policy, quite a few papers have argued that monetary

policy can be significant, but it does not account for the majority of the negative

impact on output (Hamilton 2008a). One criticism of the Bernanke et. al. (1997)

paper is that it omitted impacts in quarters three and four after the shock, which is

when oil shocks actually have their largest effect on GDP (Hamilton and Herrera

2004).


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How an Oil Shock Impacts the Magnitude and Importance of the Trade Deficit

In theory, a larger trade deficit can have a short-term impact of raising

interest rates in order to attract new investors who are willing to lend to the U.S.

Longer term, there is a concern about the sustainability of the trade deficit.

However, oil exporters have shown great willingness to lend to the U.S., which

could minimize or even reverse the interest rate effect. Additionally, the value of

foreigners investments in the U.S. will likely fall, and these valuation effects

can lead to the seemingly ironic result that the U.S. has an improved international

investment position (IIP) even with a larger trade deficit (Helbling et. al. 2005).

This IIP is the basis for the notion of sustainability of the trade deficit.

Nevertheless, although a larger trade deficit may have benign or even somewhat

positive consequences, it can be risky, and it is unclear whether future lenders will

be as willing to lend to the U.S

First of all, an oil shock probably does not lead to an increase in the trade

deficit as large as 0.6% of GDP because U.S. exports to oil exporting nations also

increase. At least to the Middle East, Higgins et. al. (2006) calculates that 20% of

U.S. dollars used to buy additional imports of oil return to the country as the

Middle East imports more U.S. goods. This impact may be relatively small

considering that only about 16% of gross imports of oil to the U.S. come from the

Persian Gulf, and the U.S. might not increase its exports as much to larger

importers such as Canada, Mexico, and Venezuela (EIA 2008).

Still, the trade deficit should increase (in the absence of changes to the

dollar see next sub-section How an Oil Shock Impacts the Dollar), and such


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an effect would normally lead to higher interest rates to attract new lenders. Yet it

appears as though up to half of the money oil exporters gain from higher prices is

invested back into U.S. treasury securities, reducing interest rates in the process

by up to one-third of a percentage point (Rebucci and Spatafora 2006).9

If true, it

is quite possible that interest rates actuallyfall during an oil price shock. Exports

to the U.S. in 2007 only accounted for about 11% and 22% of Middle East and

OPEC total exports (BP 2008; EIA 2008). But if half of new oil money is going

to the U.S., it implies that more dollars are coming into the U.S. than leaving to

purchase the oil. This increase in demand for U.S. securities would increase,

driving down the yields and therefore, the interest rate.

The immediate impact on the sustainability of deficit may also counter

expectations because the value of foreigners investments can fall. In 2003, for

instance, the IIP of the U.S. essentially remained unchanged despite a large trade

deficit because the value of U.S. foreign assets increased significantly while the

dollar depreciated (Helbling et. al. 2005). Industrial countries such as the U.S.

tend to have assets denominated in foreign currencies.

In the long-run, both potentially sanguine effects on the trade deficit and

its sustainability could turn sour. It appears as though countries in the Middle

East that were first cautious with their spending at the beginning of the oil price

increase from 2002-2005 began spending much more of their money by 2008

9 According to Rebucci and Spatafora (2006) and Higgins et. al. (2006), it appears as though oilexporters in the Middle East use British intermediaries to buy U.S. securities in the most recent oilprice increase of from 2002 to 2008. Economists cannot measure the origins of the purchasesdirectly, but they know that the U.S.s trade deficit must be offset with a trade surplus somewhere.Although the surpluses in Asia were large, they were still smaller than those in the Middle East.These economists believe the countries in the Middle East use British intermediaries or lend tocountries like Japan that then invest in U.S. securities, making an indirect investment with fundsoriginating in the oil exporting countries.


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(Rebucci and Spatafora 2006; How 2008). Thus, less money would be available

to buy U.S. treasuries, causing interest rates to rise with fewer foreign lenders.

The trade deficit would probably not directly shrink much because the Middle

East is only a small market for U.S. goods (Higgins et. al. 2006). Additionally, it

cannot always be expected that the U.S. can continue to run trade deficits without

increasing its risk. The positive valuation effects from declines in domestic asset

prices or the dollar cannot be expected to continue indefinitely.

Although the U.S. may be fine with a large trade deficit, doing so carries

risks. Helbling et. al. (2005) note the possibility of abrupt changes toward

rebalancing that can have significant impacts on macroeconomic variables. They

say this potential is especially prominent during turbulent economic times such

as during an oil shock.

How an Oil Shock Impacts the Dollar

An oil shock should impact the value of the dollar, but the direction and

magnitude is also unclear. A decline in the value of the dollar is likely the more

desirable outcome because it would counteract the increasing trade deficit by

making exports more competitive. However, a declining dollar may reduce the

willingness of foreign governments with large dollar reserves to finance future

U.S. deficits if the value of their dollar holdings decline. If these lenders move

away from dollars toward a broader basket of currencies, interest rates could

increase.


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In theory, an oil importer such as the U.S. should have a declining

currency (Throop 1993). However, Benassy-Quere et. al. (2007) calculate that

during the 1974-2004 period, the U.S. dollar tended to increase in response to a

positive oil shock. But they argue that the dollar may now follow its theoretical

pattern because it fell during the oil price increase of the 2002-2004 period, which

some are attributing to the rise of China as a major oil importer. Yet the

magnitude of this trend is questionable because many Middle East countries peg

their currencies to the dollar (Petrodollar 2006). When oil prices rise, the

currencies of oil exporters should also rise. Since the currencies are pegged to the

dollar, the exporters need to purchase dollars, causing the dollar to appreciate.

Assuming the dollar does fall during a shock, it would tend to reduce the

trade deficit, although the magnitude of this effect is also quite uncertain. Ogawa

and Kudo (2007) find a small effect, saying a 30% depreciation is needed to

reduce the trade deficit by 0.7% of GDP, or only slightly larger than the

magnitude the deficit is expected to rise after a unit shock. Yet Feldstein (2006)

believes such a change in the dollar would reduce the trade deficit by a much

larger value of more than 3% of GDP.

Regardless of the exact magnitude, it appears as though a reduction in the

value of the dollar is not guaranteed to offset the risks from a larger trade deficit.

Risks of higher interest rates and a painful adjustment process to reduce the trade

deficit remain.


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QUANTITATIVE IMPACTS ON MACROECONOMIC VARIABLES

The values cited in this section are found in Appendix A: Data on Impacts

of an Oil Shock.

Effect on Unemployment

Davis and Haltiwanger (2001) have the most comprehensive paper

concerning the impact of an oil price shock on employment. They find a quite

dramatic impact when looking at 4-digit Standard Industrial Classification (SIC)

manufacturing labor data from 1972-1988. Also, the types of businesses affected

seem to be more capital intensive and to a lesser extent more energy-intensive.

Compared with their findings in the 1970s and 1980s, the employment

impact today is likely much smaller. Edelstein and Killian (2007) find that

employment losses from 1988-2006 are only about 1/5 of the magnitude they

were from 1970-1987. This trend seems to be similar to that shown at the end of

the Davis and Haltiwanger paper, which showed that the response when analyzing

the 1972-1993 period was only 70% of what it was when the data set ended in

1988.

Davis and Haltiwanger (2001) only analyzes manufacturing, but the

impact on jobs in other sectors of the economy are likely relatively similar. The

change in employment is probably closely tied to consumer preferences; if

consumers change their preferences away from a given industry, that industry will

probably suffer, resulting in job losses. An oil price shock impacts many service

sector industries, including restaurants, airline tickets, and tourism, so job losses

are bound to be in more sectors than manufacturing (Kilian 2008). In addition,


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the original unemployment effect of Davis and Haltiwanger (2001) of 2.19

percentage points at its peak for the 1972-1988 period is very similar to the 2.32%

impact in Edelstein and Kilian (2007) for the 1970-1987 period. (Note: All future

references to percentage point changes to the unemployment rate, inflation, and

interest rates will use the percentage symbol, %). Since they begin with very

similar values, it seems reasonable to use a value similar to the more recent

Edelstein and Kilian figure of 0.55% for the analysis.

For the analysis, the assumption will be that the maximum rise in

unemployment is 0.5% with a sensitivity analysis of between 0.25% and 0.75%

for a unit oil price shock. This figure is generally in line with Annual Energy

Outlooks prediction of about a 0.2% and 0.4% employment change in years one

and two from a $20/barrel unit oil shock (AEO 2006). The actual value might be

toward the lower end considering the difference between the two periods in

Edelstein and Kilian (2007) may actually be part of a more continuous trend.

Also, the rising energy prices of this most recent decade did not appear to

substantially increase unemployment.10

The duration of the unemployment and the total reallocation are also

important in order to determine how long people were unemployed and how many

are likely to feel its long-term effects. Davis and Haltiwanger (2001) provide

good guidelines for these two questions. Assuming 0.5% is the maximum

increase in unemployment seven quarters after the oil price shock, the increase in

10 However, the unemployment rate during the Bush Administration was not as low as it was in the1990s under Clinton when oil prices were lower and had smaller fluctuations. Somecommentators have described the recovery after the 2001 recession as jobless, and it is possiblethat increases in oil prices contributed. (Groshen and Potter 2003).


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unemployment in quarters 3, 11, and 15 will be 0.05%, 0.25%, and 0.11%. All of

this unemployment is assumed to last one year, although this technique may

slightly underestimate the impact considering the greatest increase in

unemployment occurs in quarter 4, and many of those people are still unemployed

nearly one year later in quarter 7. As for reallocation, the maximum impact is

about 1.5 times greater than the maximum unemployment, so the reallocation is

assumed to be 0.75% for a unit oil price shock.

This analysis will not include the reduction in unemployment volatility

that Wolfers (2003) argues reduces well-being in addition to higher

unemployment itself. It would be difficult to know how the unemployment rate

would change in the absence of oil price shocks. As Hamilton (2008a) notes, oil

price increases have preceded nine of ten recessions since WWII, and recessions

are major sources of unemployment volatility. Yet some recessions with

attendant unemployment volatility would almost certainly have occurred in the

absence of oil price shocks. The upper end of the unemployment sensitivity

analysis can help account for the volatility.

Effect on GDP

A large body of work has analyzed the impact of an oil price shock on

GDP. Most of the analyses of the effect on GDP are calculated in terms of the

elasticity of GDP given the price of oil (Jones et. al. 2004). In order to make them

relevant to this paper, these elasticities must be converted into the effect of a unit


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shock. A constant elasticity has limited importance because it would tend to give

too much (little) weight to price changes at low (high) oil prices.

Many papers find an elasticity of about -0.055 (Jones et. al. 2004). Most

of these papers focus on the oil shocks between 1973 and 1990. Given that the

real average monthly oil price from 1973-1988 was over $51, and the average

price from 1973-1993 is over $45, an average price of $50 is assumed (EIA

2009b). Thus, a $20 oil shock is a 40% increase. A GDP elasticity of -0.055

would indicate an impact of about -2.2% in terms of GDP.

Yet as Edelstein and Kilian (2007) and Hamilton (2008a) argue, the

impact of oil prices on GDP as well as other macroeconomic variables has

declined significantly since the 1970s, biasing this calculation strongly upward.

The effect on unemployment since the late 1980s seems to be about 20-25% of

what it was in the 1970s, and the effect on GDP is likely relatively similar. More

specifically, the effect of an oil price change on real consumption and real

residential fixed investment in the 1988-2006 period are only 26% and 28% of

what they were from 1970-1987 (Edelstein and Kilian 2007). Assuming the

effect is 27% as large as it was previously leads to an impact of -0.6% for GDP

from a unit shock.

This effect shows the maximum shock rather than the trajectory of the

shock, which is what consumers would feel. Using Figure 2.2, it is possible to see

that the largest impact occurs in quarters three to five after the shock. The graph

shows a maximum impact of about -0.55% and an average impact over the five

quarters with a negative effect of -0.33%. In other words, the average impact is


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about two-thirds of the value of the maximum, so the average effect on GDP from

a unit shock is calculated to be -0.4% for five quarters.

Figure 2.2: GDP Response to an Oil Price Shock

Source: Sill 2007

This paper employs a sensitivity analysis for each of the variables that are

uncertain. For the sensitivity analysis in regards to GDP, the lower value will be

half of the midpoint calculation, or -0.2% of GDP for five quarters. The upper

bound uses the models from the Annual Energy Outlook, which show an impact

in years one and two of about -0.5% per year (AEO 2006).

It should be noted that the effect on GDP seems to be conditional on many

factors including the presence of existing business problems, the response of the

Federal Reserve, and the source of the shock. Hamilton (2008a) notes how an oil

price increase although not necessarily a shock preceded nine of the ten

recessions since WWII, so an oil price increase may accelerate or unleash

downturns in the business cycle and therefore have more of an impact than is

calculated in this paper. The Federal Reserve, in an attempt to control inflation,


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might sacrifice growth in the presence of higher interest rates. Finally, if the

source of the shock is due to increased demand rather than a supply shortage, it is

possible that there will be no negative GDP impact at all. The increased demand

could boost GDP to a larger extent than the high oil price retards it (Kilian 2008).

Effects on Inflation and Interest Rates

An oil price shock should tend to increase both inflation and interest rates.

They are discussed together because they are very well-correlated, and the data on

interest rates are somewhat sparse. Welsch (2007) finds a correlation between the

two variables of over 0.84, by far the highest correlation of any two

macroeconomic variables.11

Higher inflation is one of the first impacts of an oil shock, but much of the

initial increase is the same as an income effect from higher oil prices. Oil is part

of a basket of goods a consumer purchases. As the price of oil rises, overall

inflation increases. Oil also has the potential to lead to spillover inflation,

which is its inflationary impact on other parts of the economy (Chen 2009).

However, Van den Noord and Andre (2007) find that this spillover effect into

core inflation that excludes volatile commodity prices is much smaller today

than it was in the 1970s. They speculate that this decline may be due to a change

in monetary policy in the U.S. toward keeping inflation low beginning with Fed

Chairman Paul Volcker in the early 1980s and increasing trade openness that

11 The next closest is between growth and inflation, which is -0.36. The correlation betweeninflation and interest rates is likely quite high because the interest rate is a nominal figure thatshould take inflation into account. The correlation may not be quite as high during an oil shock,but they do interact.


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allows for inexpensive goods to flow into countries and counteract inflationary

pressures.

Overall, Chen (2009) provides the most comprehensive analysis of the

impact of a shock on inflation. He calculates that the inflationary impacts of a

shock have declined significantly for most developed countries since the 1970s.

Since 1981, he finds a short-term elasticity of inflation of 0.0028, which means a

unit shock starting at $50/barrel would only increase inflation by 0.1 percentage

points. He finds that long-term inflation would increase more by over 1%. Other

sources find impacts of between 0.4% and 1.0% (Cologni and Manera 2008; AEO

2006).

Like inflation, interest rates are likely to rise, but the changes can come

from a variety of sources.12

Overall, even if real interest rates remain constant,

they will necessarily have to increase in nominal terms to keep pace with inflation.

Additionally, if the Federal Reserve chooses to counteract potential inflationary

pressures, interest rates will rise. Tied in with monetary policy, there may be a

liquidity preference as people rebalance portfolios, and if the Fed does not meet

growing money demand, interest rates will rise (Cologni and Manera 2008)

Unfortunately, there are relatively few accessible quantitative estimates of

a shocks impact on interest rates. Two papers only present graphs that are quite

difficult to discern (Gronwald 2008; Huang et. al. 2005). Cologni and Manera

(2008) do provide an estimate specifically for the 1990 shock, finding an increase

12 They are likely to rise from domestic pressures. An influx of capital from oil exporters maykeep them down.


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of about 0.4% for a unit shock. The effects seem to essentially end once the oil

shock is over.

The effects on both inflation and interest rates are quite uncertain, with a

range of 0.1%-1% for inflation and one data point of 0.4% for interest rates. The

sensitivity analysis will take this great uncertainty into account, ranging from

0.1% to 1.4%. The midpoint will be 0.5%.

UNCERTAIN NATIONAL SECURITY RISKS (AND BENEFITS?)

Higher oil prices have the potential to strengthen autocratic regimes of oil

exporters such as Iran, Venezuela, and Russia. In an oil price shock, Hugo

Chavez of Venezuela and Mahmoud Ahmadinejad very likely have more leeway

to bluster and complicate the foreign policy of Western nations because they have

more resources they can use to build support domestically.

However, an increase in oil prices in some ways may benefit U.S. security.

As of 2005, Saudi Arabia had an unemployment rate of perhaps 20%, and The

Economistnotes how unemployed young men are prime targets for extremists

because they are disaffected and seem hopeless (Recycling 2005). With oil

money, the Saudi economy can potentially try to develop jobs for them. Similarly,

Jones (2009) explains that the Saudi royal family only began supporting more

extreme clerics once again in the 1990s as a way to build support when there was

a lack of oil money, also demonstrating how there may be a positive relationship

between oil prices and security.


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Because of the uncertainty of these impacts, they will be ignored for this

analysis. Additionally, it should be noted that U.S. oil policy is limited in what it

can do about security risk. The price of oil is global, and if there is an oil shock,

oil exporters get revenue from around the world. While it is possible that U.S.

policies to reduce oil consumption or increase supply may lower prices or

diminish some of the impact of a future shock, these outcomes are much less

certain than the fact that the impact of a given future oil shock should be reduced

with these policies. This paper is based on the view that an oil shock is likely in

the future because of a whole host of problems related to political instability,

resource access, and demand growth that the U.S. can influence but not control.

BENEFITS FROM REDUCED DRIVING AND FUEL CONSUMPTION

Higher prices should lead to reduced demand for oil. Immediately after a

shock, much of the change should come from reduced driving. However, some

families with multiple vehicles can switch to their more efficient vehicle, reducing

consumption without changing their behavior. Consumer preferences for new

vehicles should also move toward more efficient vehicles, leading to an

improvement in efficiency that should last for the entire lifetime of the vehicle.

Reduced driving should reduce the number of traffic deaths. It should also

reduce traffic congestion, which should shorten commuting time to work. Lower

oil consumption should improve local air pollution and reduce emissions of

greenhouse gases (GHGs) that contribute to global warming. Reduced driving

may also benefit air pollution in certain urban areas with less traffic congestion.


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As a first-order approximation, each of these impacts should be

proportional to the decrease in vehicle-miles traveled (VMT) or gasoline

consumed. The overall price elasticity of gasoline demand was between -0.034

and -0.077 between 2001 and 2006, and the elasticities oil demand are quite

similar to those for gasoline (Hughes et. al. 2008; Hamilton 2008b). Again

assuming a $50/barrel starting price that increases $20/barrel, these elasticities

imply a short-term reduction in oil consumption of between 1.4% and 3.1% with

an average of 2.25%. Reduced driving is only a portion of this reduction.

Assuming that half of the reduction comes from fewer VMTs, the short-term

reduction in driving is between 0.7% and 1.5% with an average of 1.1%.

However, a simple proportion between reduced VMT or oil consumption

and the associated benefits do not seem appropriate in all circumstances. Benefits

to traffic congestion and GHGs could be less than the reduction in driving or oil

use would indicate. Yet impacts to traffic deaths and air pollution may be greater

than proportional.

Commuting Time

With reduced driving, traffic should decrease, allowing people to get to

work quicker than they otherwise would have. However, it is quite possible that

the effect will be smaller than the percentage reduction in VMT if people reduce

pleasure trips or combine trips for errands more than they reduce driving to work.

Additionally, commuting time can only be reduced by a limited amount because

there is a minimum time needed to travel in the absence of traffic; the minimum


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time should be the distance traveled divided by the speed limit. On the other hand,

the impact of reduced driving could have more than proportional effects in certain

places if the reduction of a few cars on the road leads to significantly higher road

speeds.

These different possibilities will spread the sensitivity analysis from 0.4%

to 2% because the effect has greater uncertainty. The midpoint for VMT

reduction of 1.1% will stay the same. In 2005, the average one-way commute

was 25.1 minutes (AP 2006). With this reduction in VMT, the average reduction

in one-way commuting time should fall between 6 30 seconds with a midpoint

of 16.5 seconds.

Traffic Deaths

Reduced VMT should also result in fewer traffic deaths. Data from the

increase in driving post-9/11 and the significant decrease in 2008 indicate that a

reduction in VMT will have a greater than proportional impact on traffic deaths.

For instance, Sivak and Flannagan (2004) find that traffic fatalities for drivers

(who make up about 70% of traffic fatalities) increased 8.8% in the last quarter of

2001 (FARS 2008). Yet the increase in VMT during this last quarter was only

2.9% (FHA 2003).

Similarly, while VMT in 2008 dropped by about 3.5-4%, fatalities

dramatically declined by about 10% (NHTSA 2008). Part of this decline is due to

a long-running decrease in fatalities per 100 million miles driven, which had

fairly steadily decreased from 1.64 to 1.36 from 1997 to 2007 (FARS 2008).


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However, the drop in 2008 is so steep that it indicates that traffic deaths decline

disproportionately faster than declines in VMT. Theoretically, it is possible that

riskier drivers are the first to reduce (or after an incident like 9/11, increase) their

driving (Sivak and Flannagan 2004).

For this analysis, it will be assumed that driving deaths will decrease at

twice the rate of the decline in VMT. Therefore, a unit shock will cause driving

deaths to decline between 1.4% and 3% with a midpoint of 2.2%. In 2007, 41,059

people died in traffic-related incidents13 (FARS 2008). Therefore, between 575

and 1230 fewer people should die in traffic accidents with a midpoint of 905.

Air Pollution

The burning of oil is responsible for the emission of many localized air

pollutants such as particulate matter (PM) and ozone (O 3). These pollutants can

reduce happiness by leading to a reduction in agricultural output, visual pollution

in the form of haze, respiratory problems, and premature death (Krewski 2009).

For this analysis, it will be difficult to measure those effects except for the

reduction in expected life span (e.g. Pope et. al. 2009) Studies on how air

pollution, particularly PM, affect life expectancy are quite well-developed.

PM is the particular air pollutant from the burning of oil that appears to

reduce life expectancy. The Environmental Protection Agency (EPA) has two

classifications for PM based on the size of the particles PM2.5 and PM10 which

represent particles that are under 2.5 micrometers and 10 micrometers in diameter

13 This number accounts for about 30,000 vehicle occupants and slightly more than 5,000motorcyclists and 5,000 pedestrians/bicyclists.


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respectively. Pope et. al. (2009) finds that a reduction of 10 micrograms of PM2.5

per cubic meter increases life expectancy by 0.61 years +/- 0.20 years. Such a

finding is relatively similar to the indirect approaches of other studies that

measured the relative risk of dying and then applied the finding to actuary tables

(Krewski 2009).

In their reanalysis of the two major studies of air pollution, Krewski et. al.

(2003) find that the relative risk of dying from PM pollution is relatively similar

to that for sulfate (SO42-). Yet almost all of the sulfate pollution comes from

electric power plants, very few of which use oil (EPA 2002).

PM2.5 can be directly emitted, which is known as primary emission, but

most of atmospheric PM2.5 is from the emission of precursors or secondary

particles. These particles include criteria pollutants as defined by the Clean

Air Act such as sulfur dioxide (SO2) and volatile organic compounds (VOCs)

(EPA Basic 2008). On-road vehicles directly contribute to PM2.5 with road dust,

and they were responsible for 25% of VOCs as of 2000 (EPA 2002). Although

the composition of the PM can affect the health impacts, it is generally acceptable

to group PM from any origin together (Bell et. al. 2008).

The national mean level of PM2.5 in 2007 was 11.9 micrograms per cubic

meter, so if there were no PM2.5 emissions at all, it could be expected that life

expectancy would increase about 0.73 years (EPA 2008).14

However, not all of

these emissions are from oil. A reasonable estimate could assume that 40% PM

14 This technique may somewhat underestimate the effects of reducing emissions. Even low levelsof emissions are responsible for health problems, and data suggest that citizens in areas with lowlevels of PM2.5 pollution may experience a boost in life expectancy effect greater than 0.61years/10 microgram reduction (Pope et. al. 2009).


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emissions are from oil; oil provides about 40% of total U.S. energy (EPA 2009).

Forty percent is also in between the percentage of total emissions of local air

pollutants such as carbon monoxide from on-road vehicles (~55%) and nitrogen

oxides (~35%) and VOCs (~25%) (EPA 2008). With this estimation technique, if

all oil use were stopped today, life expectancy would increase 0.29 years.

However, the reduction in air pollution from an oil shock is not long-

lasting unless it leads to a significant change in the type of vehicles purchased.15

Given that an average person lives about 80 years, a one-year change in PM2.5

would increase life expectancy by 1.3 days (SSA 2004). Finally, the actual

reduction in PM2.5 emissions from a price shock should be the reduction in oil use

with a slight increase to account for the reduction in traffic congestion for some

areas. Adding the reduction in oil use with reduced VMT would imply a

reduction of between 2.1 4.5% per year of air pollution from oil with a midpoint

of 3.3%. Such a decrease would imply an increase in life expectancy of between

40 85 minutes per person with a midpoint of slightly over one hour for a unit oil

shock lasting one year.

Actually assuming an increase in life expectancy of about an hour may

seem almost comical, but it can be significant when calculated over the entire

population. This impact may be biased downward because it does not include

health impacts such as increased hospital visits and reduced health outcomes from

greater respiratory ailments. It should be noted that this calculation contains

many uncertain assumptions, so it should be used as a general guide for the order

15 An oil price shock may have an impact on sources of energy such as electricity that also emitpollutants, but the direct impact from reduced oil use is probably the most significant. Kilian(2008) and Edelstein and Kilian (2007) have estimations of cross-elasticities.


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of magnitude of the effect of reduced localized air pollution rather than treated as

a precise estimate.16

Emissions of Greenhouse Gases

In general, the reduction in oil consumption and increased efficiency of

new vehicles purchased should reduce greenhouse gas emissions (GHGs) that

contribute to global warming. However, higher prices can also lead to more

exploration of new sources with higher GHGs such as tar sands in Canada, and it

can increase the popularity of sources with many other externalities such as corn

ethanol and fuel from palm oil (Kockleman et. al. 2008). Due to this uncertainty

to even the direction of the effect from an oil price shock, it will not be included

in the calculation. Chapter 3 has a discussion of the difficulty of calculating GHG

impacts, especially as they relate to a framework based on happiness.

OVERALL IMPACTS

Table 2.2 on the following page summarizes the quantitative information

in the chapter for easy access. The last column lists whether the estimates given

in the chart may be underestimated or overestimated. For instance, the income

figures are potentially underestimated because they do not take into account that

people may have needed to borrow money to pay for the fuel.

16 Additionally, the largest reductions in air pollution have come from tightened vehicle standardsfor local air pollutants, which significantly impacts the calculation presented here (EPA 2008).


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Table 2.2: Quantitative Estimates of Impacts from Unit Shock

Effect Unit Mid-point

Lowerbound

Upperbound

Figures PossiblyUnderestimated orOverestimated?

Income

change 1

st

quintile

Dollars

lost peryear

-201 N/A N/A Underestimated: If

needed to borrow

Incomechange 2

nd

quintile

Dollarslost peryear

-337 N/A N/A Underestimated:: Ifneeded to borrow

Incomechange 3rdquintile

Dollarslost peryear

-453 N/A N/A Underestimated:: Ifneeded to borrow

Incomechange 4

th

quintile

Dollarslost peryear

-564 N/A N/A Underestimated: Ifneeded to borrow

Incomechange 5thquintile

Dollarslost peryear

-702 N/A N/A Underestimated: Ifneeded to borrow(rarer for thisgroup)

Employment Percent inyears 1-4

-0.05, -0.5,-0.25,and -0.11

50% ofmid-point

50%higherthanmidpoint

Overestimated: Joblosses from oilshocks may havecontinued todecline

JobReallocation

Percent inyears 1-4

-0.75 -0.375 -1.125 Overestimated: Joblosses from oil

shocks may havecontinued todecline

GDP Percentper year

-0.4 (5quarter)

-0.2 (5quarter)

-0.5 (2years)

Inflation andInterest Rates

Percentper year

0.5 0.1 1.4

QuickerCommute

Secondseach way

16.5 6 30 Overestimated:Traffic

ReducedTraffic Deaths

Number 905 575 1230

Air Pollution IncreasedLifespan(minutes)

62 40 85 Underestimated:Unable to accountfor health impactsfor those alive


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Chapter 3: Measuring Happiness

We hold these truths to be self-evident, that all men . . . are endowed bytheir Creator with certain unalienable Rights, that among these are Life, Liberty,and the pursuit of Happiness

- Thomas Jefferson,Declaration of Independence (1776)

Economists have tried to maximize utility, and this chapter shares this goal.

As Kahneman et. al. (1997) explain, economists have used decision utility,

researching what decisions individuals make in order to discover what maximizes

utility.

However, this approach has substantial limitations that an analysis of an

oil shock makes quite clear. An oil shock changes so many variables

microeconomic, macroeconomic, trade, environmental, and traffic-related. An

approach focusing on decision utility has difficulty weighing the importance of

the relative components and finding what impacts of an oil shock are most

detrimental or beneficial.

While it is possible to use a decision utility framework to try to estimate

specific benefits and costs, the process is extremely uncertain and inadequate.

One would assume a declining marginal utility of income, but trying to value how

an income loss affects people of different income and how people adapt is quite

arbitrary and subject to ideology. The impact of unemployment on well-being

would require questionable proxies such as a look at increased use of products

and services used for coping with stress such as alcohol, cigarettes, and

psychological counseling. However, the unemployed have less money to spend

on these products, making a valuation even more complicated. Additionally, it is


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essentially impossible to identify losses from changes to GDP, inflation, and

interest rates in addition to a loss of income.

Decision utility is somewhat more useful for the positive impacts of an oil

shock. Various methods such as contingent valuation can be used for air pollution.

Economists have also calculated a statistical value of a life and the monetary

impacts of traffic congestion (Frey and Stutzer 2005).

These effects are put in terms of dollars, which is problematic because a

dollar does not have the same value in every context. A declining marginal utility

of income assures that a dollar to a poorer person should have more value that it

does to someone of greater means.

In contrast, this paper uses subjective well-being (SWB) surveys that

ask residents to rate their happiness or life satisfaction. Contrasting it with

decision utility, Kahneman et. al. (1997) call this approach experienced utility,

and it directly gauges how people feel about their lives. Economists have then

taken the hundreds of thousands of responses since the 1970s and have calculated

the direct impacts on happiness of income, unemployment, other variables

discussed in this paper. These calculations directly measure the impact of

particular changes without requiring complicated and quite dubious proxies. Just

as economists currently try to create utility functions, these economists create

happiness or life satisfaction equations, assuming that these feelings are

dependent on various situational factors.

Some may be uneasy using measures of self-reported happiness to make

policy, but as Jefferson wrote in theDeclaration of Independence, happiness is


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fundamental to the goals of America. Maximizing happiness and utility were

central to the ideas of 19th

century Utilitarian philosophers such as Jeremy

Bentham and John Stuart Mill, and their ethics live on in modern economics (Frey

2008). Since their time, the scientific study of happiness has advanced greatly,

allowing governments to figure out what policies can maximize the happiness of

its residents.

By calculating the benefit of reducing oil use in terms of happiness, this

paper provides half of the information needed for what has been described as a

life satisfaction cost-benefit analysis (LS-CBA) (Diener and Seligman 2004; Frey

and Stutzer 2005). The data in this chapter could be used to help analyze the

costs of various policies to reduce oil use such as a fuel economy standard,

completing the LS-CBA. Diener and Seligman (2004) believe that such an

approach can be used in tandem with more traditional metrics such as the

unemployment rate and changes in GDP to provide a more complete picture of

how to address policy questions. At this time, it appears that no comprehensive

quantitative guide to how various changes affect happiness or life satisfaction has

been created that would facilitate a LS-CBA, and none of these cost-benefit

analyses has been conducted for any policy. Layard (2005) and Frey (2008) have

gone the farthest by making some general suggestions for public policy based

upon the surveys, but they do not complete a LS-CBA.


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BACKGROUND ON SUBJECTIVE WELL-BEING SURVEYS

The Subjective-Well Being Surveys

Hundreds of thousands of citizens have taken SWB surveys. They

strongly differ from traditional economic techniques that solely look at the

decisions of individuals (Frey and Stutzer 2005). The term SWB will be used

throughout this paper interchangeably with happiness. At various times, specific

surveys that ask about either happiness or life satisfaction will be identified.

The surveys ask similar questions, but more focus on life satisfaction than

happiness. The U.S. is different from European nations in that the U.S.s survey

focuses on happiness only. The Eurobarometer did ask a happiness question from

1975-1986 that closely mirrored the U.S. question, but the survey apparently no

longer asks it (Di Tella et. al. 2001). The following questions are listed in Layard

et. al. (2008):

United States General Social Survey (USGSS happiness): Taken alltogether, how would you say things are these days? Would you say

you are very happy, pretty happy, or not too happy? (Effective scale

1-3)

Eurobarometer (happiness): Taking all things together, how wouldyou say you are these days would you say youre very happy, fairly

happy, or not too happy these days? (Effective scale 1-3)

Eurobarometer (life satisfaction): On the whole, are you very satisfied,fairly satisfied, not very satisfied, or not at all satisfied with the life

you lead? (Effective scale 1-4. )


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German Socio-Economic Panel (GSOEP life satisfaction): Inconclusion, we would like to ask you about your satisfaction with your

life in general. Please answer according to the following scale: 0

means completely dissatisfied, 10 means completely satisfied. How

satisfied are you with your life, al things considered? (Actual scale 0-

10)

These surveys have each been asked to at least tens of thousands of people.

The Eurobarometer even has more data points, with information on over 250,000

Europeans from 1975-1991, meaning that the survey has probably reached about

half of a million people by now (Di Tella et. al. 2001). The GSOEP tracked some

of the same people over a period of more than one decade, allowing a long-term

view of the impacts and adaptation of individuals to major life events such as

marriage, death of a family member, and unemployment (Lucas 2007).

The Reliability and Usefulness of SWB Surveys

Researchers have found strong correlations between self-reported

happiness and life satisfaction and a whole range of other outward signs of those

emotions. Blanchflower and Oswald (2004) document many of the correlations

such as persons recall of positive vs. negative life events, assessments of persons

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