factors contributing to global pricing discrepancies for...

Factors Contributing to Global Pricing Discrepancies for Natural Gas

Gaurav Kikani

Advised by Dr. Laura Lynne Kiesling

Prepared for the Mathematical Methods in the Social Sciences (MMSS) Program at

Northwestern University

June 4, 2014

Factors Contributing to Global Pricing Discrepancies for Natural Gas Gaurav Kikani

2

Acknowledgements

There are a number of people without whom this paper would not have been possible.

Foremost, I wish to extend a sincere thank you to my advisor, Professor Laura Lynne Kiesling,

whose knowledge and guidance were instrumental to understanding the economic foundations of

natural gas. Secondly, to Professor William Rogerson and the MMSS program, for having

fostered an environment and curriculum that have allowed me to grow tremendously throughout

college. And finally, to my parents, sister, and brother-in-law, whose unwavering dedication,

love, and support have always emboldened me to pursue my dreams and passions.


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Table of Contents

Introduction 4

Background 5

Literature Review 19

General Methodology 25

Data 26

Proposed Model 29

Conclusion 36

Appendices 42


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Introduction

Over the past decade, natural gas has become increasingly relevant, especially in the

United States, as increased energy consumption has caused countries to seek alternative energy

sources to mitigate oil dependency, which is becoming extremely expensive. According to

estimates in the United States Energy Information Administration’s (EIA) 2013 International

Energy Outlook, natural gas consumption will grow from 113.0 trillion cubic feet in 2010 to

185.0 trillion cubic feet in 2040, and is thus projected to be the fastest-growing fossil fuel

globally.1 These projections support a paradigm shift that has been observed in natural gas

markets in recent years, as rising oil prices have incentivized developments on both the supply-

and demand-sides. Investments in research and development have fundamentally changed

market dynamics as new technology has yielded efficient techniques that have revolutionized the

exploration, extraction, transportation, and utilization of natural gas. These supply-side

developments are mirrored by burgeoning demand as consumers substitute away from costly oil,

seek to diversify energy portfolios to protect national security interests, and drive organically

growing energy demands in emerging market economies.

The long-term effects of dynamic natural gas markets have caused observable

discrepancies in the nature of global natural gas pricing. Historically, natural gas prices have

been pegged to the value of crude oil, moving lockstep, especially on an energy equivalency

basis. However, in recent years, given the shifts in market drivers, we have witnessed a

decoupling in natural gas markets, creating flux in pricing and magnifying regional price

discrepancies. As new trends emerge and the political, environmental, and economic incentives

1 “International Energy Outlook 2013.” U.S. Energy Information Administration, July 2013, p.

41.


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of natural gas evolve, global pricing will continue to fluctuate, creating ambiguity for producers

and uncertainty for consumers.

This paper will seek to explain the various factors that are correlated with pricing and to

understand the significance each factor holds as it pertains to unexplained variance in pricing

observed globally. This area of focus is becoming increasingly relevant to firms and

governments internationally as energy economics and policy become major factors in dictating

global growth. A predictive pricing model for natural gas could prove useful in forecasting long-

term price trends as supply-side dynamics and growth trends in global energy demands cause

further pricing fluctuations.

Background

Among the most prevalent fossil fuels, natural gas represents the most nascent energy

source in terms of its widespread sourcing and use. A combustible mixture of hydrocarbon gases,

mainly methane (CH4), natural gas is formed in processes similar to those in the formation of oil,

namely the decomposition of organic matter deep under the Earth’s crust. Among other factors,

temperature levels dictate which matter is produced: lower temperatures (closer to the Earth’s

surface) create more oil and higher temperatures (deeper below the Earth’s crust) create more

natural gas. After the formation process, the gas’s low density causes it to rise upwards, often

getting trapped in the pores of sedimentary rock.2 There are many variations to the general

structures in which natural gas is found such as “tight” natural gas, shale gas, and methane

hydrates (see Figure 1). Termed as “unconventionals”, these states represent some of the more

2 “Background.” NaturalGas.org, Natural Gas Supply Association,

http://naturalgas.org/overview/background/


6

recent developments in natural gas production and have required cutting-edge technological

innovations to make extraction possible.

Figure 1: Schematic geology of natural gas resources.3

The exuberance in the last few years over natural gas stems from properties that make it

an attractive energy source. Foremost, natural gas is far more abundant than originally believed.

According to data from the EIA, global proved reserves of natural gas increased by

approximately 9% between 2009 and 2012, of which over 15% can be attributed to discoveries in

the United States alone.4 Furthermore, the unconventional gas revolution (e.g. shale, tight gas)

has increased the recoverable resource base by approximately 300%, increasing the estimated

resource life from 60 to 200 years. The International Energy Agency predicts that this

unconventional gas will represent 25% of global gas supply by 2035, compared to its 8% share

3 “Schematic Geology of Natural Gas Resources.” Natural Gas. U.S. Energy Information

Administration, 2010, http://www.eia.gov/oil_gas/natural_gas/special/ngresources.html.

4 “International Energy Statistics.” Countries. U.S. Energy Information Administration, 2013,

http://www.eia.gov/cfapps/ipdbproject/iedindex3.cfm.


7

in 2013.5 This major supply dislocation can largely be attributed to the advent of modern

extraction techniques, which have increased the capacity of producers to economically develop

unconventional gas fields. As these methods begin to be implemented all over the world, the

resource base continues to grow, potentially making natural gas a relatively inexpensive

substitute for oil, which continues to escalate in price. In addition to simply being an alternative

energy source, natural gas also provides geographical diversification for energy consumers, as it

relieves dependence on the resource-rich Organization of the Petroleum Exporting Countries

(OPEC), which often acts as a cartel and creates uncertainty for the energy security of numerous

nations. For example, this has led natural gas to be an especially attractive energy source in the

United States, given that there exists a 330% energy content price gap for the number of units of

energy a single dollar can purchase when comparing oil to natural gas.6

A second benefit that makes natural gas a sought after resource is the environmental

implication of its use. After impurities are removed, natural gas is the cleanest available fossil

fuel, producing 30% less CO2 per unit heat than oil and 45% less than coal. In 2013, coal-fired

power stations generated 37% of the electricity in the United States, but as the Environmental

Protection Agency (EPA) introduces new, more stringent air-quality standards, reliance on these

major polluters will presumably diminish and become uneconomical.7 This hypothesis is

supported by Figure 2, which shows projections by the EIA that natural gas consumption will

significantly increase in nearly all sectors, especially industrials and electric power generation,

5 “Global LNG: Will new demand and new supply mean new pricing?” Ernst & Young Global

Limited, 2013, p. 7.

6 Samantha Azzarello, “Energy Price Spread: Natural Gas Vs. Crude Oil in the U.S.,” Seeking

Alpha, http://seekingalpha.com/article/2012281-energy-price-spread-natural-gas-vs-crude-oil-in-

the-u-s.

7 “Difference Engine: Fuel for the Future?” The Economist, May 27, 2013,

http://www.economist.com/blogs/babbage/2013/05/natural-gas.


8

between 2010 and 2040. As other developed and emerging nations become more

environmentally conscious, there could be an increased shift away from traditional, “dirty”

sources of energy towards cleaner, yet still cost-efficient and abundant, resources.

Figure 2: OECD Americas change in natural gas consumption by country and sector, 2010-2040

(trillion cubic feet).8

Despite the promise of natural gas as a productive energy source that can alleviate a

number of stresses on the global energy economy, there have historically been a number of

challenges along the value chain that have precluded markets from harnessing its full potential.

Foremost, the exploration and production parts of the process are extremely capital intensive,

requiring huge upfront investments in equipment and technology to be able to locate reserves,

drill the wells, and extract the gas. While new techniques such as hydraulic fracturing have

increased the productivity of drilling in a given field, firms still grapple with a high degree of

uncertainty in their ability to drill a well that will yield a marketable quantity of gas and whether

they will be able to offload supply to buyers, so that they can ensure profitability, or at least

8 “International Energy Outlook 2013,” op. cit., p. 44.


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break-even. Thus firms must evaluate a project over a longer time-horizon, requiring

assumptions about volatile factors such as future supply and demand levels, low-price

environments, macroeconomic dynamics, and regulatory conditions.

Aside from the prohibitive costs of developing a field, firms also encounter difficulties

associated with the physical production of natural gas. Natural gas reservoirs exist anywhere

between 5,000 to 25,000 feet below the Earth’s surface, requiring extremely versatile and precise

technology to lift the substance above-ground. Additionally, huge quantities of gas can be found

in unconventional sources, which until recently, could not be exploited in a cost-effective way.

For example, ample amounts of gas exist in the pores of sedimentary rock such as shale, which

are impermeable to the flow of natural gas. Over the past decade, new techniques such as

hydraulic fracturing (i.e. “fracking”) have been used to open up cracks between the pores

through which the gas can flow into the well and be harnessed.9 Although new technologies have

greatly augmented the ability to extract gas and on a cost-effective basis, the uncertainty tied to

initial exploration and the recovery of capital invested can make the economics of such a venture

unviable.

Natural gas markets are additionally challenged by a lack of liquidity stemming from the

regional nature of global gas trade. To put it in perspective, 61% of world oil is traded

internationally, while only a mere 31% of gas is traded abroad.10

Part of this discrepancy arises

due to the substance being abundant in certain geographies, but then being isolated from global

markets. For instance, Qatar and Australia are two of the fastest growing producers of natural

gas, however, both are far removed from end-markets like Japan, which increasingly relies on

imports to address nearly all of its natural gas demand, as evident from Figure 3. Further

9 “Shale.” NaturalGas.org, Natural Gas Supply Association, http://naturalgas.org/shale.

10 “Australian LNG Outlook.” Macquarie Equities Research, 2012, p. 15.


10

complicating matters is that natural gas is extremely difficult to transport, requiring an elaborate

infrastructure and advanced mechanisms due to the gas’s high volume. Pipelines have

historically been the most common means for transporting gas from field to market, but they

require sizable capital investments and are subject to major environmental and regulatory

scrutiny. Transporting to overseas markets has typically been far more problematic as it is

prohibitively expensive. This has spurred the use of liquefied natural gas (LNG) in which gas is

supercooled to -260 degrees Fahrenheit, the temperature at which it condenses into liquid form.

LNG takes up one six-hundredth of the volume of its gaseous form, making it viable to transport

in ocean tankers to foreign markets.11

While recent technological innovations have enhanced

processes such as liquefaction and regasification, making such transportation increasingly

economically viable, delivering natural gas to consumers remains a major source of friction and

inefficiency in global markets.

Figure 3: Japan natural gas net exports/imports (-), 1990-2012. 12

11

“LNG.” NaturalGas.org, Natural Gas Supply Association, http://naturalgas.org/lng.

12 “Country Analysis: Japan.” U.S. Energy Information Administration, 2013,

http://www.eia.gov/countries/country-data.cfm?fips=ja.


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The Past Decade

Despite its high energy capacity, natural gas has not been a usable energy source until

relatively recently. In the nineteenth century, trace amounts of gas were realized as a byproduct

of oil production, but given that there was little demand for the gas, it was valueless. Producers

would therefore simply burn the excess gas or later on, would reinject gas into the ground to

repressurize the formations as a means to boost oil extraction rates. Although these practices still

exist to some extent around the world, a revolution in production technologies has radically

changed natural gas markets since 2000.

New technologies have especially caused a supply-side paradigm shift in natural gas

markets as the shale revolution has led to a rejuvenated industry in the United States. Use of

hydraulic fracturing and horizontal drilling techniques have allowed companies to harness gas

residing in impermeable shale deposits and reservoirs in inaccessible locations under the Earth’s

crust in a cost-effective way; this is reflected in a 39% increase in the amount of recoverable

natural gas resources in the United States between 2006 and 2008, accounting for nearly one-

third of the total domestic resource base.13

Today, shale represents 39% of total dry natural gas

production in the United States, up from 4% in 2005 (Figure 4). Furthermore, projections by the

EIA show that natural gas production in China, Canada, and the United States (the countries with

the largest unconventional reserves) will grow substantially and will skew proportionally toward

unconventional gas production by 2040 (Figure 5).

13

“Shale: Growing Share.” NaturalGas.org, Natural Gas Supply Association,

http://naturalgas.org/shale/growingshare.


12

Figure 4: Shale gas as share of total dry natural gas production in 2012 (billion cubic feet per

day).14

Figure 5: Natural gas production in China, Canada, and the United States, 2010 and 2040

(trillion cubic feet).15

The degree to which these developments have shifted the dynamics of the industry is

exemplified by brand new LNG import terminals in the United States being retrofitted with

liquefaction facilities so as to operate as export terminals, while incurring billions of dollars in

14

“North America leads the world in production of shale gas.” Today in Energy, U.S. Energy

Information Administration, 2013, http://www.eia.gov/todayinenergy/detail.cfm?id=13491.

15 “International Energy Outlook 2013,” op. cit, p. 42.


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costs on each. The effects of these changes are reflected in Figure 6 from the EIA’s Annual

Energy Outlook 2014 in which U.S. net exports of both pipeline and liquefied gas are estimated

to increase significantly.

Figure 6: U.S. natural gas imports and exports, 2000-2040.16

It is important to note, however, that there exists huge production potential in other

regions, namely the Middle East with 40% of global proven natural gas reserves that remains

untapped. As Figure 7 indicates, tremendous production growth is projected for the Middle East,

especially Iran, which has the world’s second-largest reserves of natural gas, after Russia. This

growing, additional supply will further incentivize adoption of natural gas as a primary energy

source globally.

16

“Executive Summary.” Annual Energy Outlook 2014, U.S. Energy Information

Administration, December 2013, http://www.eia.gov/forecasts/aeo/er/executive_summary.cfm.


14

Figure 7: Middle East natural gas production, 1990-2040 (trillion cubic feet).17

Although supply growth is quite evidently escalating at an unprecedented rate, it is

complemented by burgeoning demand, which is projected to increase from 113.0 trillion cubic

feet in 2010 to 185.0 trillion cubic feet in 2040.18

According to the EIA, the demand growth will

occur globally, with non-OECD (Organization for Economic Cooperation and Development)

countries increasing consumption twice as fast as OECD countries (Figure 8). When compared

to oil and coal, natural gas has a lower carbon footprint, making it an environmentally preferable

alternative to the other fossil fuels. As environmental controls become more stringent, especially

in OECD countries, natural gas increasingly becomes the fuel of choice for the industrial and

electricity-producing sectors. In emerging markets, economic growth is the primary driver for

strong energy consumption growth, and given natural gas’s positioning as a competitive fuel

source, non-OECD countries are progressively becoming more reliant upon it.

17

“International Energy Outlook 2013,” op. cit., p. 52.

18 “International Energy Outlook 2013,” loc. cit.


15

Figure 8: World natural gas consumption, 2000-2040 (trillion cubic feet).19

As basic economic theory suggests, these supply and demand factors have significant

impacts on the pricing dynamics for natural gas. However, due to the largely regional nature of

natural gas trade, large discrepancies have emerged among regional markets where geographies

abundant in gas resources have depressed prices while net importers pay a premium to cover

their energy demands. As the chart in Figure 9 indicates, there is a sizable discrepancy between

the North American, European, and Asian markets. The widening of the spread circa 2008

reflects the shale revolution and expansion of the natural gas supply base, thereby persistently

depressing prices in the United States and marginally in Europe.

19

“International Energy Outlook 2013.” loc. cit.


16

Figure 9: Global natural gas prices (monthly averages).20

However, natural gas pricing is also closely coupled to other factors, such as oil prices. In

the past, when natural gas markets had not matured, were less liquid, and were subject to more

regulation, natural gas prices were pegged to oil. Given the substitutability of the two energy

sources, it is intuitive for oil and natural gas prices to move in tandem. In fact, on a per unit

basis, natural gas has one-sixth of the energy content of oil. Given that, it is logical to infer that

the price of natural gas should equal one-sixth times the price of crude oil. This and other rules

of thumb historically held for natural gas pricing, however, in recent years, this has no longer

been the case. Both fuels have unique costs with regards to exploration, production,

transportation, and storage, and are utilized for divergent types of end-uses.21

Such momentary

divergences are evident in Figure 10 as Henry Hub (natural gas) and West Texas Intermediate

(crude oil)22

prices decouple gradually after 2000. Furthermore, the supply of oil is becoming

20

“Global LNG: Will new demand and new supply mean new pricing?” op. cit., p. 13.

21 David J. Ramberg and John E. Parsons, “The Weak Tie Between Natural Gas and Oil Prices,”

The Energy Journal, Vol. 33, No. 2 (2012), 13-35.

22 Henry Hub and West Texas Intermediate are pricing indices for natural gas and crude oil

respectively used as benchmarks in the United States.


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relatively scarcer while gas has become abundant. These evolving market dynamics are making

oil indexation of gas pricing more difficult as there are increased competition between sellers,

price-sensitive consumers, deregulation, spot market liquidity, and availability of spot-price-

anchored LNG exports. High-cost projects will be more difficult to protect via bilateral contracts

and high-cost sellers will continue to lose pricing power.23

Figure 10: Natural Gas and Crude Oil Spot Prices, 1991-2010 (real 2010 dollars).24

It is important to note that natural gas has historically been benchmarked regionally, with

different geographies taking varying approaches to constructing the market. Prices were

regulated by governments, competitively determined in the spot markets, or indexed to

competing fuels – such as crude oil. Over time these divergent mechanisms were adopted in

different geographies, with the United States pioneering hub-based pricing based on competitive

trading, while Europe and Asia practiced oil indexation. In the 1990’s, the United Kingdom

23

“Global LNG: Will new demand and new supply mean new pricing?” op. cit., p. 15.

24 “Global natural gas prices vary considerably.” Today in Energy, U.S. Energy Information

Administration, 2011, http://www.eia.gov/todayinenergy/detail.cfm?id=3310.


18

began to deregulate and construct a traded market (National Balancing Point [NBP]) based on

that of the United States. After the United Kingdom’s gas network was connected to Belgium

and the remainder of continental Europe in 1998, hub pricing began to gradually proliferate into

the rest of Europe.25

This decoupling allows natural gas respond to short-term exogenous shocks

in supply and demand. For example, prices can react to events such as hurricanes in the Gulf of

Mexico, which impede production, while also accounting for spikes in demand such as that

stemming from diminished reliance on nuclear power in Japan after the Fukushima disaster.

However, while Europe today continues to adopt independent pricing mechanisms for natural

gas, oil indexation remains the primary practice in Asian markets.

While global pricing discrepancies exist, firms are introduced with arbitrage

opportunities as they can produce for approximately $3/mmBtu in the United States, but sell in

Asian markets for upwards of $15/mmBtu. This divergence in market prices points to

inefficiency since the pricing spread should theoretically correct itself – arbitrage opportunities

should not persist since markets will return to equilibrium. Contrary to the fundamental financial

models regarding market efficiency, however, these arbitrage opportunities have persisted over

time. It is important to note, though, that the lack of liquidity due to lag time in production,

transportation difficulties, and prohibitive up-front capital expenditure requirements can

sometimes make these inefficiencies onerous for firms to exploit.

The continued evolution of global pricing mechanisms for natural gas will have important

ramifications for the supply and demand trends of natural gas and thereby creates a degree of

unpredictability for future prospects as prices diverge between regions. It is possible that

understanding the weighting of various natural gas factors as they pertain to price can produce

25

Anthony J. Melling, “Natural Gas Pricing and its Future: Europe as the Battleground.”

Carnegie Endowment, 2010, p. 10.


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predictive power that can be useful in forecasting the future dynamics of the natural gas markets.

These factors can also help understand whether burgeoning global supply and demand as well as

greater market integration through LNG transport will lead to an eventual convergence in

regional pricing.

Literature Review

Natural gas pricing has quickly become a fertile topic for research, especially as firms

have strong incentives to be able to predict the energy source’s future value. The long-term time

horizons of production projects hinge on being able to forecast market dynamics, and thus there

has been a glut of literature in the past few years on the nature of pricing. However, the scope of

the studies is limited, as they tend to focus on natural gas pricing specifically in the United States

due to elevated interest in the wake of the shale revolution that has flourished in recent years.

Furthermore, most analyses deal with short-term pricing tendencies, especially as they pertain to

near-term exogenous shocks such as weather, seasonality, storage, and natural disasters as

opposed to long-term trends emerging from macroeconomic dynamics. However, as international

markets continue to integrate, global pricing has begun to move towards the forefront of

research, which has yielded some interesting theories as to what the future entails.

A study commissioned by the American Petroleum Institute in 2006 focused primarily on

the trends being seen in North American markets at the time.26

Prior to the financial crisis of

2008, strong economic growth and high oil prices made natural gas a relatively more attractive

fuel. However, the supply-side environment was quite different as predictions were being made

that existing conventional fields were maturing quickly and producers had to undertake more

26

Charles Augustine, Bob Broxson, and Steven Peterson, “Understanding Natural Gas Markets.”

American Petroleum Institute, 2006, p. 15.


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costly extraction via unconventional plays (Figure 11). Citing a tightening supply and demand

balance in North America, the paper predicted upwards price trends and urged exploration of

new natural gas sources and new technologies to maintain supply.

Figure 11: Natural Gas Production by Source, 1990-2025.27

In November 2008, Don Maxwell and Zhen Zhu co-authored a working paper at the

University of Central Oklahoma that sought to use available time-series data to understand the

transportation dynamics that were underlying the global boom in natural gas demand.28

By

employing unit root tests to understand the stationarity of LNG imports and consumption

variables, the researchers were able to use causality tests and variance analysis to study the

effects of various macroeconomic shocks to the system. As a result of the their empirical

analysis, Maxwell and Zhu concluded that natural gas prices and shipping costs were the most

important determinants of United States LNG imports, and that LNG imports were more

27

ibid

28 Don Maxwell and Zhen Zhu, “Natural Gas Prices, LNG Transport Costs, and the Dynamics of

LNG Imports.” United States Association for Energy Economics, 2008.


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sensitive to volatility in gas prices than to shipping costs. The effects of shipping costs tend to be

more muted and occur gradually over a longer time horizon. Taken together, these findings

promote the notion of LNG representing a viable alternative to both domestically produced and

imported pipeline gas. Though the scope of this study was limited exclusive to the United States

in 2008, it perpetuates significant implications for the liquidity of natural gas markets, as LNG

could presumably become a robust method to interlink isolated regional markets.

Stephen Brown and Mine Yucel of the Federal Reserve Bank of Dallas published a paper

in The Energy Journal (2008) that took a rigorous empirical approach to understanding the

factors that drive natural gas prices in the United States.29

They cited the inconsistencies

beginning to surface in historical pricing “rules of thumb”, such as historical 10 to 1 ratios

between oil and natural gas prices, or the more recent 6 to 1 ratio on an energy equivalency basis.

Brown and Yucel contended that natural gas was driven by more dynamic factors that result

from the inability to rapidly fuel-switch between oil and natural gas. These effects would

manifest themselves particularly in the short-run as a result of disruptions in supply such as

seasonality, inclement weather, storage, and disruptions to production. The researchers tested

this hypothesis by employing an error-correction model without exogenous variables and one

with stationary exogenous variables. The models showed that natural gas prices in the United

States are correlated with crude oil prices in the long-run, but are more immediately impacted by

short-term, transitory variables such as those mentioned above.

Building upon the work of Brown and Yucel, David Ramberg and John Parsons,

researchers at the Massachusetts Institute of Technology, sought to further understand natural

29

Stephen P.A. Brown and Mine K. Yucel, “What Drives Natural Gas Prices?” The Energy

Journal, Vol. 29, No. 2 (2008).


22

gas pricing in their paper The Weak Tie Between Natural Gas and Oil Prices (2012).30

They

cited aberrations in the pricing relationship between natural gas and crude oil starting in 2009

that called into question the strong links established in previous studies. Although they

recognized that oil and natural gas prices are evidently cointegrated, Ramberg and Parsons

caution that academics should acknowledge that 1) short-run unexplained volatility is driven by

natural gas-specific factors that Brown and Yucel identified and 2) that the cointegrating

relationship seems to be unstable over time. Their tests on exogenous variables as well as

different time spans yielded conclusions that confirmed their suspicions. The tests verified

Brown and Yucel’s notions of unexplained variance attributed to short-term natural gas-specific

fluctuations. Thus, in the near-term, the cointegrated relationship between gas and oil is

statistically significant, but not entirely reliable as a price predictor. Secondly, the cointegrated

relationship changes over time, presumably due to the omission of technological and economic

forces from previous studies. This analysis thus informs the observations that in recent years

natural gas prices seemed to have decoupled from oil prices, as this shift could be attributed to

technological and value chain developments in the United States. However, Ramberg and

Parsons recognized that similar technological and economic constraints would place a cap on the

amount prices could decouple and that they would never decompose completely.

A 2012 report by Macquarie Equities Research highlighted the recent emergence of LNG

pricing issues to the global stage. Their market data research yielded a few key conclusions:

LNG pricing is becoming a key market driver as demand is shifting to price-sensitive

consumers while supply begins to incorporate more expensive development costs and

stiffer competition.

30

Ramberg and Parsons.


23

While LNG sellers continue to lobby for oil-indexed pricing models, a shift towards

hub-based pricing seems inevitable as supply-side competition escalates, pipeline

networks proliferate across Asia, and deregulation intensifies.

Hub-based or spot LNG pricing would introduce significant competition to proposed

projects globally, thereby subjecting high-cost producers to undercutting and thus

could depress pricing.

Improved pricing mechanisms in Asian markets will create liquidity, greater

flexibility in contracting, and help the market mature – causing buyers to pay less of a

premium to ensure security of supply.

Taken together, the above conclusions perpetuate the notion that global natural gas

markets are poised to undergo a transformation. While regional price discrepancies were the

most exaggerated in 2011, international trade of natural gas is growing at an unprecedented pace

as arbitrage opportunities persist (Figure 12). This increased trade is anticipated to precipitate

integration of the markets. As a result of these developments, in addition to further decoupling

from crude oil prices, Macquarie predicts that gas prices will at least partially converge over

time.


24

Figure 12: Increased international gas trade (via pipelines and LNG) linking regional gas

markets (and perhaps ultimately prices).31

Although the available literature speaks well to changing dynamics in natural gas

markets, there is limited information regarding the relative importance of various long-term

factors that impact pricing. Furthermore, the majority of research is limited to trends in the

United States and how prices behave when the region is considered on an isolated basis.

However, as discussed, the natural gas market is quickly becoming integrated across the global

economy, posing significant questions in terms of future trends and challenges with regards to

forecasting. The remainder of this thesis will seek to propose an empirical approach that could be

useful in determining the relative explanatory significance of macroeconomic variables as they

pertain to natural gas pricing. Such an exploration has become increasingly important as pricing

predictions become economically critical for national governments, energy producers as they

budget capital expenditure projects, and firms that have exposure or correlations to energy

markets.

31

“Australian LNG Outlook,” op. cit., p. 16.


25

General Methodology

The intent of this paper is to build a quantitative model that incorporates empirical data

for natural gas across the value chain that can provide insights into the viability of a predictive

model for pricing. As with any other economic mechanism, the understanding holds that there

are certain factors that drive natural gas pricing characteristics and can help explain the regional

pricing discrepancies observed across the globe. The initial approach is constructed to aggregate

industry panel data for the United States, Japan, and Germany, and to build a regression model

that discriminates between primary and ancillary variables, thereby delineating the strongest

motivators of natural gas pricing.

The primary motivators for selecting the countries that this study focuses on stem from

clear geographical dichotomies as they pertain to natural gas supply-demand characteristics.

Recent market dynamics have been tremendously influenced by the United States’ shale boom,

which has made energy independence and natural gas net exports possible. The outward shift of

the supply curve is juxtaposed with Japan, which relies entirely on liquefied natural gas imports

to meet its energy needs. In the middle of the spectrum is Germany, the geography of which

facilitates a hybrid of pipeline imports from the North Sea as well as transcontinental pipeline

gas sourced from Russia. The geographical and regional differences among the countries in this

panel provide interesting contrasts and magnify some of the explanatory factors for natural gas

pricing.

This analysis takes a traditional economic pricing approach, with the assumption that

equilibrium price derives from the intersection of the supply and demand curves. The method

consists of decomposing each of the supply and demand components independently into their


26

respective factors and equating the aggregate quantities supplied and demanded in order to back

out the pricing equation.

Data

Given that first-order commodity data is widely available, data searches yielded a robust

amount of historical pricing data from BP plc, a British multinational oil and gas corporation.

The time-series dataset (Appendix A) includes natural gas pricing data for Henry Hub32

,

Japanese natural gas imports cif33

, and German natural gas imports cif, and when graphed,

illustrates the price divergence that this study seeks to explain (Figure 13). The BP dataset also

includes net gas production and consumption data for the United States, Japan, and Germany for

the period from 1980 to 2012.

In addition to the price, consumption of natural gas can be defined by a few key drivers

such as seasonality, economic growth, and the price of substitutes. Given that natural gas is a

major source for both heating and cooling, it is reasonable to anticipate fluctuations in gas

demand (and thereby price) when there are deviation in weather patterns in a given country. To

measure volatility in temperatures across geographies, heating and cooling degree days are

useful metrics and can be found as historical time-series data across geographies. Heating degree

days is a measure that quantifies the demand for energy needed to heat a building beyond a

certain baseline, which for our exploration will remain at 65 degrees Fahrenheit. Similarly,

cooling degree days measures the demand for energy needed to cool a building beyond 65

degrees Fahrenheit. By taking these measures together, we can get an understanding of whether a

32

Henry Hub: A natural gas distribution hub in Erath, Louisiana, which serves as an important

price point for United States and foreign natural gas markets. 33

Cif: cost + insurance + freight (average prices)


27

given geography experienced abnormally elevated or low temperatures in a given year, relative

to a mean temperature. Heating and cooling degree day data is provided in Appendix B.

Figure 13: Global natural gas time-series pricing data.

Economic growth is another important driver of natural gas demand, as historical

evidence points to a link between growth and energy demands. Although, recent evidence points

to a weakening tie between the two, especially in the United States,34

for the purposes of this

exploration, we assume that this relationship will remain robust and persist with regards to

natural gas. Given that this analysis spans various countries located in different regions of the

world, with differing population characteristics, economic growth factors can best be captured

34

“U.S. economy and electricity demand growth linked, but relationship is changing.” Today in

Energy. U.S. Energy Information Administration, 2013,

http://www.eia.gov/todayinenergy/detail.cfm.

($/mmBtu)US Henry

Hub

Japan Import

cif

German

Import cif

1984 - 5.10 4.00

1985 - 5.23 4.25

1986 - 4.10 3.93

1987 - 3.35 2.55

1988 - 3.34 2.22

1989 1.70 3.28 2.00

1990 1.64 3.64 2.78

1991 1.49 3.99 3.19

1992 1.77 3.62 2.69

1993 2.12 3.52 2.50

1994 1.92 3.18 2.35

1995 1.69 3.46 2.39

1996 2.76 3.66 2.46

1997 2.53 3.91 2.64

1998 2.08 3.05 2.32

1999 2.27 3.14 1.88

2000 4.23 4.72 2.89

2001 4.07 4.64 3.66

2002 3.33 4.27 3.23

2003 5.63 4.77 4.06

2004 5.85 5.18 4.32

2005 8.79 6.05 5.88

2006 6.76 7.14 7.85

2007 6.95 7.73 8.03

2008 8.85 12.55 11.56

2009 3.89 9.06 8.52

2010 4.39 10.91 8.01

2011 4.01 14.73 10.48

2012 2.76 16.75 11.03

Data Sourced from BP, plc


28

through a per capita measure, which accounts for population size. Thus, we use year-over-year

growth in gross domestic product per capita to explain economic growth, calculated based on

data provided by The World Bank. The time series data and derived growth rates are provided in

Appendix C.

Price of substitutes is the final and arguably most important component of this demand-

side regression analysis. Historically, global markets have pegged natural gas prices to crude oil

prices, largely because gas markets at the time had not matured, were illiquid, and subject to

significant regulation. Since then, markets in the United States have been deregulated and are

subject to large volumes of spot trading, and natural gas typically now prices independently of

crude oil. However, European and Japanese markets have moved to long-term delivery contracts,

making the markets highly illiquid and subject to fluctuations in prices for competing fuels.

Thus, natural gas demand is highly dependent on the availability and substitutability of other

energy sources. To account for this phenomenon, this study incorporates time series pricing data

from BP for various crude oils, depending on from where the respective country sources the

majority of its supplies (Appendix D).

Figure 14: Panel countries by oil source.

Country Oil Source

United States West Texas

Intermediate (WTI)

Japan Dubai Crude

Germany Brent Crude

Supply data, on the other hand, is more limited, especially as the data for many key cost

components is proprietary in nature and thus generally unavailable for the purposes of this


29

analysis. A key component of determining supply characteristics derives from the costs

associated with exploration, production, and the transportation of natural gas. Given that the cost

element of commodity dynamics is presumably one of the most significant drivers of the pricing

mechanism, our original analysis is unable to proceed in the manner devised – regressions yield

highly insignificant results and suffer from omitted variable biases. Although the dataset for this

portion of the regression is incomplete, production, net import, and environmental regulation

factor data procured are available in Appendix E.

Due to the dearth of available data, the immediately actionable quantitative analysis of

this topic arrives at an impasse. The question of natural gas pricing and the uncertainty regarding

long-term pricing trends have quickly become lucrative explorations for various energy

corporations to pursue. Given the first-mover advantage that exists for the firm that solves this

question the soonest, companies are not willing to share their internal cost and sales data so as to

not risk providing full information to competitors. The tenuous nature of this competitive

environment makes it onerous upon researchers who are not backed by large institutional

frameworks within the energy industry to procure the necessary data to run analytics on these

market dynamics. Given the above, our attention shifts instead to a proposed model that, given

the appropriate data, could potentially lead to useful findings and presumably significant

explanatory power regarding the drivers of global natural gas pricing.

Proposed Model

In the presence of complete data, this exploration would seek to employ the below

regression analysis to model the effects of various drivers on natural gas prices. Making the same

assumption as the initial approach, we would assume that the fundamental theories of economics


30

hold in that the market price lays at the intersection of the supply and demand curves. Thus, by

setting quantity demanded ( ) equal to quantity supplied ( , as in (1), we would be able to

predict the equilibrium price as a function of the significant explanatory variables derived from

the regression.

(1)

The proposed quantity demand model (2) would remain largely the same as what is

proposed above, save for two additional explanatory variables – industrial output and electricity

consumption. The historical end-uses of natural gas suggest that the fuel is primarily demanded

by consumers for electricity purposes and by industrial agents that need to power large facilities.

These uses are quite consistent around the world, and thus these variables would be relevant to

include in the panel regressions for each of the three countries. For example, if industrial output

diminished in a given year, there is a high likelihood that plant operations were cut, thereby

reducing the amount of natural gas demanded. The same logic holds for consumption of

electricity. It is important to note there may be some correlation between weather and electricity

consumption, as seasonality drives much of a country’s heating and cooling fluctuations;

possible multicollinearity would need to be addressed based on the results of running basic

ordinary least squares regressions and analyzing the results.

(2)


31

Assuming complete information, the supply model must be significantly more rigorous,

given the enormous complexities and possible permutations in sourcing and supplying natural

gas. For the dependent variable in this regression, amount of gas produced is not an adequate

measure of supply since the supply base derives from a combination of domestic production and

imported fuel (via pipeline or LNG), as shown in equation (3).

(3)

Quantity supplied would then be regressed upon the price of natural gas, the cost of each step

along the value chain, an indication of competition in the market, taxes or tariffs, a measure of

environmental regulations that either incentivize or penalize the production of natural gas, and

finally an error term that can capture one-time supply shocks that occur year-to-year (4).

(4)

Before exploring the cost components of the regression with more granularity, it is

important to explain what kind of data we would require for the other factors, which seek to

magnify specific geography-dependent characteristics of a given market. The competition

variable would derive from time-series data on the number of firms active in a specific market,

normalized for size. The hypothesis is that fluctuations in the number of firms and their

capacities to provide natural gas supplies would cause variance in the total amount of natural gas


32

available to a specific market. Similarly, time-series data for average tax rates (or tariffs) capture

any additional financial barriers imposed upon producers when bringing natural gas to market.

Taxes would cause an upward shift of the supply curve, thereby affecting the equilibrium

quantity and price. Similarly, environmental regulations can impose an added cost burden to

producers or can incentivize production by providing subsidies. Environment regulation in

Europe tends to be stricter than that of the United States, thereby resulting in higher costs of

production for natural gas in Europe. Although quantifying environmental regulatory regimes

can be difficult, a 2001 study co-authored by Daniel Esty from Yale University and Michael

Porter from Harvard Business School created an “environmental regulatory regime” index,

which scores various countries by aggregating assessments of regulatory stringency, structure,

subsidies, and enforcement. In congruence with the previous observations regarding the

relatively stricter regulations in Europe, Germany ranks much higher on the list (score: 1.522),

followed by the United States (score: 1.184), and trailed by Japan (score: 1.057).35

A full list of

the environmental regulatory regime index rankings are provided in Appendix E.

Finally, the costs of natural gas across the value chain, which this study hypothesizes are

the primary motivators of pricing, incorporate a number of considerations and fluctuate

depending on other variables. For the purposes of this analysis, we account for the most

fundamental elements of the value chain – costs associated with exploration, production, and

transportation.

Exploration represents the most significant cost component of the value chain, as locating

natural gas reservoirs requires the use of expensive technology but typically has a low

35

Daniel C. Esty and Michael E. Porter, “Ranking National Environmental Regulation and

Performance: A Leading Indicator of Future Competitiveness?” The Global Competitiveness

Report, Oxford University Press (2001).


33

probability of success (typically in the range of 10% to 30%). While seismic imaging is used to

do early exploration, exploratory wells need to be drilled in order to ultimately prove the

presence of hydrocarbons. The cost of these wells fluctuates depending on the depth of a well,

the type of geological formation one must drill through, and the extent to which cutting-edge

imaging and technology is used to identify potential reservoirs. With the vast majority of

accessible and shallow basin reservoirs already discovered, the effort is shifting towards more

technically difficult areas such as extremely deep reservoirs (25,000 to 30,000 feet below the

Earth’s surface) and offshore (5,000 to 10,000 feet deep). Although time-series data is not

readily available on the year-to-year magnitudes of these costs, exploration wells could cost as

much as $100mm to $200mm each. This shift significantly impacts natural gas economics as

exploratory wells are costly and the probability of building dry wells detracts from expected

returns on investment, thereby having a negative impact on supply, since volume itself cannot

drive firm profits.

Generally, the time period between discovery and actual production is very long, given

that huge amounts of capital investment and infrastructure are required to convert a potential

discovery into an operational field. If existing infrastructure can be utilized, a three to five year

gap is quite common. For more remote discoveries, it can take decades before the appropriate

mechanisms are in place for gas to be successfully extracted and redirected to refineries. Facility

investments often have to be made years before operations begin, and thus need to be

underpinned by large or multi-regional discoveries that can supply the plant for over thirty years.

Furthermore, the industry has evolved to include commercial long-term contracts that must be in

place before investment commitments are made. Thus, production issues add a second degree of

variability in the total cost of producing one unit of natural gas.


34

Transportation costs are the final major component of the value chain and can potentially

provide insights into the fundamental question of the cause of regional pricing discrepancies

since transportation accounts for disparities in geography. Transferring produced natural gas

from sources to markets depends almost entirely on the total distance the commodity needs to be

moved and the means of transportation. All transport methods have substantial up-front

investment costs, requiring the lock-up of large amounts of capital years before operations

commence. This subjects these investments to risks of changing market dynamics and possibly

unviable economics if retail prices decrease significantly and squeeze margins. In recent years,

the increase of LNG transport has linked markets on opposite sides of the globe, opening new

supply channels but also driving up average transport costs, relative to pipeline-restricted, land-

based transports. The advent of floating LNG terminals, a new technology that is being

pioneered by Royal Dutch Shell, will allow for refining and liquefaction to occur offshore, closer

to where gas is being produced to reduce intermediate transportation steps and hence costs. For

the purposes of our model, the transportation cost can be decomposed as in equation (5).

(5)

Given the above, the proposed model, when accounting for the time-series data, we

deduce general regressions of:


35

(6)

and:

(7)

and:

(8)

Where x represents the specific country the observations are for (i.e. United States, Japan,

Germany).

Finally, by combining the equations above, and by setting , one can solve for the

equilibrium price (panel regressions included in Appendix F):


36

(9)

It is important to note that this is an initial model, designed with the main components of

natural gas market dynamics in mind, but given the unavailability of large amounts of data, it is

not possible to test for omitted variable biases, statistical significance, or overall robustness of

the regression. For this analysis to be furthered, data that is currently proprietary in nature must

be procured from firms to quantify what have been identified here as the primary drivers of

natural gas pricing. An initial understanding of this model’s predictive power will be crucial to

gauge how this model can be made more robust, and whether a dynamic market such as natural

gas can be modeled off of historical trends.

Conclusion

Over the last two decades, natural gas has jumped to the forefront of energy economics

as a viable substitute for traditional fuel sources, especially in the context of increasing global

energy demands. Rapidly changing market forces, coupled with improved technologies, have

caused a widening of the pricing spread among countries around the world, and today manifests

itself as a discrepancy as large as $14 per million British thermal units of natural gas between

Japan and the United States.


37

The observed global pricing discrepancies stem from a paradigm shift that occurred in the

markets circa 2008, when the implementation of new extraction techniques such as horizontal

drilling and hydraulic fracturing yielded sizable discoveries in North America. This glut of

newfound supply caused North American natural gas prices to depress as there was less reliance

on imports and expensive transportation methods. Similarly, production in recent years has been

bolstered in the Middle East, providing an abundance of supplies to European markets, causing a

slight downward push on prices there as well. Taken in tandem with burgeoning energy demands

in East Asian markets due to a growing population and fast-pace income growth, the increase in

supplies in western markets has led to a widening pricing disparity. In the interim, the demand

trends have been furthered magnified by substitution away from other conventional energy

sources, due in part to rising oil prices, increased emphasis on cleaner energy sources due to

more stringent environment regulation, and substitution away from nuclear energy in the wake of

the 2011 Fukushima Daiichi nuclear disaster in Japan.

Regional pricing inconsistencies around the world are further substantiated by a simple

thesis: large distances between the sources of natural gas and end-markets lead to transportation

costs that firms pass on to consumers. Upon initial analysis, this hypothesis holds for the three

panel countries used in this exploration. In the United States, transportation is efficient, given

that the sources are largely constrained to the continent and existing pipeline infrastructure can

be leveraged to transport gas in a relatively inexpensive manner. Coupled with the shale boom

that has occurred over the past decade, supply has far outpaced demand and thereby significantly

depressed pricing in domestic markets. Germany represents a more hybrid market, although it

has no LNG terminals currently, it sources all of its supplies from Nordic, Russian, and Dutch

pipelines. Pipeline gas is cheaper than LNG, however, given that the gas is being moved large


38

distances, the transportation component can be costly. Finally, Japan sits on the opposite end of

the spectrum, both far removed from markets and relying on more costly methods of

transportation. The country’s geography as an island does not allow for pipeline transportation,

and thus Japan relies on LNG imports to address virtually all of its natural gas demand, and is the

world’s largest LNG importer. Given that unlike pipeline gas, LNG requires additional steps of

liquefaction, transport by tanker, and regasification upon arrival at the market, gas in Japan

commands a higher price in order for firms to have enough profit incentive to sell.

Initial attempts to model this phenomenon in order to drive analytics about future pricing

trends were unfortunately unsuccessful, entirely due to the proprietary nature of much of the data

that was necessary for the analytics. Cost data pertaining to the exploration, production, and

transportation components of the value chain are not provided readily by firms, especially since

pricing remains an opaque but potentially lucrative topic within the industry. The corporations

that can accurately predict future market dynamics can make more robust capital investment

decisions, anticipate when to increase or decrease production, responsibly control reserves, and

statistically justify how many resources to devote towards exploration and building production

capacity. The pricing question represents a so-called “holy grail” for players within the industry

and thus it quickly becomes clear why it becomes difficult to procure data, especially without the

backing of an institution within the industry.

Despite the dearth of data, we have proposed an initial model that can be used to

decompose price into its fundamental supply-demand components and run regressions that can

quantify the magnitude to which each variable drives natural gas prices. Our approach assumes

that natural gas prices result from equilibrium, using the fundamental notion in economics that

the market-clearing price occurs where quantity demanded equals quantity supplied. By


39

performing basic manipulation of these regression equations, it is shown that the price can be

backed out and thereby predicted.

The next step for this exploration is to find initial data that can be used to evaluate the

accuracy and robustness of the proposed model. Given the multitude of variables at play through

the entirety of the value chain, it becomes crucial to be able to find line-item cost data for each

step of the supply process, as much of the end-price of commodities is determined via the cost

firms incur in bringing the product to market. Beyond this, a regression would also yield insights

into the interplay between production and non-production variables – especially demand

dynamics, taxes, competition and regulatory environments.

From the insights derived through this analysis, this study can produce a hypothesis

regarding the persistence of regional pricing discrepancies for natural gas. Based on the research,

this study predicts that the future will produce a price convergence as new global supplies enter

the markets and as transportation technologies proliferate and improve. Current developments in

the United States alone are moving towards deregulation of natural gas trade. The United States

Department of Energy is beginning to consider applications for non-free trade agreement exports

that will allow the United States to begin exporting globally, allowing domestic suppliers to take

advantage of the shale boom and newfound abundance of resources. By allowing exports that are

not currently permitted, prices in the United States would be allowed to increase as foreign

demand would now vie for the same resources. In conjunction with these increased supplies, the

proliferation of new transportation technologies such as FLNG facilities and a growing pipeline

infrastructure can decrease transportation expenses and can ultimately push foreign natural gas

prices lower. Upward price trends in the United States combined with decreasing pricing in

foreign markets could ultimately reverse the divergent trends occurring over the last few decades


40

and edge towards a median price. However, given inefficiencies, supply-demand fluctuations,

and fundamental differences between markets, this study does not anticipate a “perfect market”

or a single price that is consistent across global markets at any point.

A number of potential stress points exist for this theory, especially those originating

from the basic long-term economic fundamentals of natural gas and oil. Even if export rights are

granted as theorized above, if the volume of natural gas supplies introduced to the markets

outpaces demand, downward pressures on price could be large enough so as to make the

economics of natural gas production unviable for firms. Given the vast capital investments firms

must make years in advance, their reliance on a long-term time horizon opens them up to such

market risks. Unviable production economics could cause firms to begin operating at negative

profits, resulting in drilling moratoriums or a shutdown of facilities. In a similar vein, the recent

resurgence of natural gas has been a direct consequence of consumers shifting away from a

dependence on crude oil as prices rise to historic highs. If the economics of oil improve in the

near future, it is possible that consumers have less of an incentive to substitute to natural gas, and

oil would remain the energy source of choice. Furthermore, natural gas demand could plateau

due to demand inelasticity stemming from the difficulties of changing status quo reliance on

crude oil. A paradigm shift in energy source choice is dependent on adaptation of current

technologies to incorporate natural gas as a viable fuel – a shift for which the impetus must be

extremely large.

The question of natural gas pricing is a complex one, full of intricacies and evolving

variables. As countries grow around the world and energy demands increase, the scrutiny

towards energy policy and dependency on certain resources will only heighten. Combined with

the importance of environmental regulations in the economic arena in recent years, the actions of


41

policymakers and consumers alike will likely shape the viability of long-term shifts in natural

gas supply-demand dynamics. Such explorations in the realm of natural gas pricing will need to

continue and deepen, especially as pricing predictions become critical to plan capital expenditure

projects for producers, energy policies for national governments, and hedging positions for any

entities that have long-term exposures to the energy industry.


42

Appendix A:

Natural gas pricing, production, and consumption time-series data:

(Source – BP Plc)

Year

US Henry

Hub Price

($)

Japan

Price cif

($)

German

Import Price

cif ($)

US

Production

(bcm)

Japan

Production

(bcm)

Germany

Production

(bcm)

US

Consumption

(bcm)

Japan

Consumption

(bcm)

Germany

Consumption

(bcm)

1965 432.67 1.74 2.91

1966 465.88 1.79 3.50

1967 492.38 1.85 4.51

1968 527.60 2.02 7.41

1969 567.93 2.23 10.56

1970 595.06 0.00 11.05 598.60 3.41 15.01

1971 611.92 0.00 13.80 617.12 3.66 19.83

1972 612.32 0.00 16.48 625.84 3.66 25.68

1973 615.35 0.00 18.52 624.37 5.10 33.11

1974 586.53 0.00 19.44 600.97 6.96 41.42

1975 544.71 0.00 17.69 553.24 8.34 43.71

1976 540.81 0.00 18.63 564.82 10.00 46.27

1977 542.63 0.00 18.90 552.76 12.21 49.13

1978 541.47 0.00 20.21 555.79 17.14 52.67

1979 556.81 0.00 20.27 573.15 20.33 58.22

1980 549.44 0.00 18.52 562.86 24.06 57.40

1981 543.15 0.00 19.14 549.46 24.11 54.88

1982 504.61 0.00 17.18 509.73 24.69 50.92

1983 455.74 0.00 18.37 476.71 26.57 52.94

1984 5.10 4.00 494.60 0.00 19.31 508.30 35.73 55.29

1985 5.23 4.25 465.92 0.00 17.42 489.34 38.27 54.65

1986 4.10 3.93 454.74 0.00 16.69 459.34 38.94 54.49

1987 3.35 2.55 470.64 0.00 18.51 487.36 39.94 59.08

1988 3.34 2.22 484.29 0.00 16.69 510.54 42.36 58.16

1989 1.70 3.28 2.00 490.18 0.00 15.73 541.39 44.00 59.52

1990 1.64 3.64 2.78 504.31 0.00 15.93 542.95 48.07 59.92

1991 1.49 3.99 3.19 501.15 0.00 14.70 553.93 50.83 62.89

1992 1.77 3.62 2.69 505.17 0.00 14.92 572.79 52.84 63.03

1993 2.12 3.52 2.50 512.41 0.00 14.85 588.71 53.21 66.39

1994 1.92 3.18 2.35 532.95 0.00 15.57 601.65 56.91 67.94

1995 1.69 3.46 2.39 526.66 0.00 16.06 628.83 57.91 74.45

1996 2.76 3.66 2.46 533.89 0.00 17.40 640.24 61.79 83.60

1997 2.53 3.91 2.64 535.25 0.00 17.10 643.84 64.14 79.18

1998 2.08 3.05 2.32 538.69 0.00 16.71 629.94 66.08 79.70

1999 2.27 3.14 1.88 533.27 0.00 17.85 634.44 69.40 80.15

2000 4.23 4.72 2.89 543.17 0.00 16.88 660.72 72.29 79.47

2001 4.07 4.64 3.66 555.46 0.00 17.04 629.74 74.26 82.89

2002 3.33 4.27 3.23 535.98 0.00 16.99 652.05 72.65 82.60

2003 5.63 4.77 4.06 540.82 0.00 17.69 630.80 79.77 85.54

2004 5.85 5.18 4.32 526.44 0.00 16.37 634.37 77.01 85.86

2005 8.79 6.05 5.88 511.15 0.00 15.80 623.38 78.55 86.25

2006 6.76 7.14 7.85 523.97 0.00 15.61 614.45 83.74 87.18

2007 6.95 7.73 8.03 545.55 0.00 14.30 654.23 90.23 82.91

2008 8.85 12.55 11.56 570.83 0.00 13.03 659.13 93.74 81.23

2009 3.89 9.06 8.52 584.00 0.00 12.18 648.74 87.44 78.02

2010 4.39 10.91 8.01 603.59 0.00 10.63 682.06 94.51 83.30

2011 4.01 14.73 10.48 648.51 0.00 10.00 690.49 105.50 74.52

2012 2.76 16.75 11.03 681.39 0.00 9.04 722.14 116.74 75.24


43

Appendix B:

Heating and cooling degree day data:

(Source – WeatherUnderground.com)

YearUS Heating

Degree Days

US Cooling

Degree Days

Japan Heating

Degree Days

Japan Cooling

Degree Days

Germany

Heating

Degree Days

Germany

Cooling

Degree Days

1960 4,724 1,206

1961 4,540 1,168

1962 4,694 1,179

1963 4,734 1,204

1964 4,515 1,185

1965 4,549 1,153

1966 4,700 1,148

1967 4,609 1,077

1968 4,675 1,137

1969 4,736 1,190

1970 4,664 1,242

1971 4,547 1,204

1972 4,705 1,146

1973 4,313 1,241

1974 4,406 1,117

1975 4,472 1,172

1976 4,726 1,029

1977 4,605 1,285

1978 4,958 1,226

1979 4,781 1,113

1980 4,707 1,313

1981 4,512 1,209

1982 4,619 1,136

1983 4,627 1,260

1984 4,514 1,214

1985 4,642 1,194

1986 4,295 1,249

1987 4,334 1,269

1988 4,653 1,283

1989 4,726 1,156

1990 4,016 1,260

1991 4,200 1,331

1992 4,441 1,040

1993 4,700 1,218

1994 4,483 1,220

1995 4,531 1,293

1996 4,713 1,180 867 1,082 2,799 102

1997 4,542 1,156 2,706 1,524 6,075 365

1998 3,951 1,410 2,757 1,651 5,750 198

1999 4,169 1,297 2,773 1,842 5,419 322

2000 4,460 1,229 2,063 1,271 3,836 139

2001 4,203 1,245 3,156 1,459 5,981 267

2002 4,273 1,396 2,923 1,489 5,686 388

2003 4,459 1,290 3,006 1,243 5,859 453

2004 4,290 1,232 2,001 1,739 4,843 204

2005 4,315 1,397 3,193 1,525 5,792 257

2006 3,996 1,368 2,930 1,365 5,588 495

2007 4,255 1,399 2,700 1,550 5,260 283

2008 4,494 1,277 2,940 1,525 5,447 310

2009 4,493 1,229 2,668 1,413 5,789 269

2010 4,461 1,457 2,954 1,882 6,879 394

2011 4,320 1,321 3,018 1,729 5,377 220

2012 4,524 1,335 3,221 1,658 5,893 266


44

Appendix C:

GDP per capita time-series data and derived growth rates:

(Source – World Bank)

Year

US GDP Per

Capita ($)

US GDP per

Capita

Growth

Japan GDP per

Capita ($)

Japan GDP

per Capita

Growth

Germany

GDP per

Capita ($)

Germany GDP

per Capita

growth

1960 2,881.10 479.00

1961 2,934.55 1.86% 563.59 17.66%

1962 3,107.94 5.91% 633.64 12.43%

1963 3,232.21 4.00% 717.87 13.29%

1964 3,423.40 5.92% 835.66 16.41%

1965 3,664.80 7.05% 919.78 10.07%

1966 3,972.12 8.39% 1,058.50 15.08%

1967 4,152.02 4.53% 1,228.91 16.10%

1968 4,491.42 8.17% 1,450.62 18.04%

1969 4,802.64 6.93% 1,669.10 15.06%

1970 5,246.96 9.25% 2,003.65 20.04% 2,672.02

1971 5,623.59 7.18% 2,234.26 11.51% 3,089.07 15.61%

1972 6,109.69 8.64% 2,917.66 30.59% 3,686.97 19.36%

1973 6,741.10 10.33% 3,931.30 34.74% 4,883.81 32.46%

1974 7,242.32 7.44% 4,281.36 8.90% 5,457.01 11.74%

1975 7,819.96 7.98% 4,581.57 7.01% 6,035.01 10.59%

1976 8,611.46 10.12% 5,111.30 11.56% 6,420.64 6.39%

1977 9,471.53 9.99% 6,230.34 21.89% 7,434.90 15.80%

1978 10,587.42 11.78% 8,675.01 39.24% 9,175.90 23.42%

1979 11,695.36 10.46% 8,953.59 3.21% 10,916.80 18.97%

1980 12,597.65 7.71% 9,307.84 3.96% 11,746.40 7.60%

1981 13,992.92 11.08% 10,212.38 9.72% 9,879.46 -15.89%

1982 14,439.02 3.19% 9,428.87 -7.67% 9,593.66 -2.89%

1983 15,561.27 7.77% 10,213.96 8.33% 9,545.86 -0.50%

1984 17,134.32 10.11% 10,786.79 5.61% 9,012.48 -5.59%

1985 18,269.28 6.62% 11,465.73 6.29% 9,125.12 1.25%

1986 19,114.82 4.63% 16,882.27 47.24% 13,027.20 42.76%

1987 20,100.79 5.16% 20,355.61 20.57% 16,139.05 23.89%

1988 21,483.11 6.88% 24,592.77 20.82% 17,352.34 7.52%

1989 22,922.47 6.70% 24,505.77 -0.35% 17,190.83 -0.93%

1990 23,954.52 4.50% 25,123.63 2.52% 21,583.84 25.55%

1991 24,404.99 1.88% 28,540.77 13.60% 22,603.62 4.72%

1992 25,492.96 4.46% 31,013.65 8.66% 25,604.73 13.28%

1993 26,464.78 3.81% 35,451.30 14.31% 24,735.62 -3.39%

1994 27,776.43 4.96% 38,814.89 9.49% 26,375.85 6.63%

1995 28,781.95 3.62% 42,522.07 9.55% 30,887.87 17.11%

1996 30,068.23 4.47% 37,421.67 -11.99% 29,749.97 -3.68%

1997 31,572.64 5.00% 34,294.90 -8.36% 26,296.53 -11.61%

1998 32,948.95 4.36% 30,967.29 -9.70% 26,547.78 0.96%

1999 34,639.12 5.13% 34,998.81 13.02% 25,956.64 -2.23%

2000 36,467.30 5.28% 37,291.71 6.55% 22,945.71 -11.60%

2001 37,285.82 2.24% 32,716.42 -12.27% 22,840.27 -0.46%

2002 38,175.38 2.39% 31,235.59 -4.53% 24,325.67 6.50%

2003 39,682.47 3.95% 33,690.94 7.86% 29,367.41 20.73%

2004 41,928.89 5.66% 36,441.50 8.16% 33,040.05 12.51%

2005 44,313.59 5.69% 35,781.23 -1.81% 33,542.78 1.52%

2006 46,443.81 4.81% 34,102.21 -4.69% 35,237.60 5.05%

2007 48,070.38 3.50% 34,094.89 -0.02% 40,402.99 14.66%

2008 48,407.08 0.70% 37,972.24 11.37% 44,132.04 9.23%

2009 46,998.82 -2.91% 39,473.36 3.95% 40,270.16 -8.75%

2010 48,357.68 2.89% 43,117.77 9.23% 40,144.51 -0.31%

2011 49,853.68 3.09% 46,134.57 7.00% 44,314.97 10.39%

2012 51,748.56 3.80% 46,730.92 1.29% 42,624.75 -3.81%


45

Appendix D:

Crude oil time-series pricing data:

(Source – BP Plc)

Year

WTI Crude

Prices

($/bbl)

Arabian

Light Sweet

($/bbl)

Brent Crude

Prices

($/bbl)

1972 1.90

1973 2.83

1974 10.41

1975 10.70

1976 12.23 11.63 12.80

1977 14.22 12.38 13.92

1978 14.55 13.03 14.02

1979 25.08 29.75 31.61

1980 37.96 35.69 36.83

1981 36.08 34.32 35.93

1982 33.65 31.80 32.97

1983 30.30 28.78 29.55

1984 29.39 28.06 28.78

1985 27.98 27.53 27.56

1986 15.10 13.10 14.43

1987 19.18 16.95 18.44

1988 15.97 13.27 14.92

1989 19.68 15.62 18.23

1990 24.50 20.45 23.73

1991 21.54 16.63 20.00

1992 20.57 17.17 19.32

1993 18.45 14.93 16.97

1994 17.21 14.74 15.82

1995 18.42 16.10 17.02

1996 22.16 18.52 20.67

1997 20.61 18.23 19.09

1998 14.39 12.21 12.72

1999 19.31 17.25 17.97

2000 30.37 26.20 28.50

2001 25.93 22.81 24.44

2002 26.16 23.74 25.02

2003 31.07 26.78 28.83

2004 41.49 33.64 38.27

2005 56.59 49.35 54.52

2006 66.02 61.50 65.14

2007 72.20 68.19 72.39

2008 100.06 94.34 97.26

2009 61.92 61.39 61.67

2010 79.45 78.06 79.50

2011 95.04 106.18 111.26

2012 94.13 109.08 111.67


46

Appendix E:

Supply-side regression data –

Net import and total supply:

(Source – United States Energy Information Administration)

Year

US Net

Imports

(bcm)

Japan Net

Imports

(bcm)

Germany

Net Imports

(bcm)

US Total

Supply

(bcm)

Japan Total

Supply

(bcm)

Germany

Total

Supply

(bcm)

1990 40.488 50.267 544.802 50.267

1991 46.032 53.147 60.032 547.178 53.147 74.732

1992 53.816 54.084 61.330 558.986 54.084 76.247

1993 61.880 55.307 65.374 574.286 55.307 80.224

1994 68.936 58.808 68.472 601.888 58.808 84.041

1995 75.236 60.405 72.995 601.892 60.405 89.057

1996 77.952 64.391 75.103 611.840 64.391 92.498

1997 79.436 66.433 71.934 614.691 66.433 89.037

1998 83.804 68.931 69.250 622.491 68.931 85.958

1999 95.844 72.139 70.479 629.114 72.139 88.325

2000 99.064 74.973 69.611 642.238 74.973 86.489

2001 100.912 75.337 71.248 656.375 75.337 88.286

2002 97.972 76.165 73.185 633.953 76.165 90.178

2003 91.392 81.036 75.938 632.216 81.036 93.628

2004 95.340 80.316 80.390 621.779 80.316 96.759

2005 101.136 80.010 79.974 612.283 80.010 95.778

2006 96.936 87.642 81.170 620.911 87.642 96.783

2007 106.008 94.558 75.282 651.560 94.558 89.584

2008 84.588 94.325 78.419 655.416 94.325 91.446

2009 75.012 91.774 82.321 659.015 91.774 94.499

2010 72.912 97.683 70.926 676.500 97.683 81.554

2011 54.964 115.153 71.236 703.473 115.153 81.234

2012 42.532 120.251 68.302 723.917 120.251 77.341


47

Environmental regulatory stringency benchmark:

(Source – Daniel C. Esty and Michael E. Porter, “Ranking National Environmental Regulation

and Performance: A Leading Indicator of Future Competitiveness?”)


48

LNG Trade Growth:

(Source – Clarkson Research Services)

Year

LNG Trade

Growth

(bcm)

1985 55.896

1986 56.3312

1987 59.8264

1988 66.2048

1989 70.4888

1990 78.9072

1991 79.3968

1992 82.1848

1993 84.3608

1994 89.3792

1995 93.092

1996 100.3952

1997 113.1248

1998 115.192

1999 125.9632

2000 140.9232

2001 145.044

2002 153.5984

2003 170.2584

2004 178.6088

2005 192.8208

2006 216.8656

2007 233.1584

2008 235.0488

2009 248.3496

2010 301.308

2011 334.6824

2012 325.1896


49

Appendix F:

Panel regressions for the United States, Japan, and Germany:

United States:

Demand:

Supply:

Japan:

Demand:


50

Supply:

Germany:

Demand:

Supply:

factors contributing to global pricing discrepancies for...

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