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https://doi.org/10.1007/s11356-023-25654-w
RESEARCH ARTICLE
Energy security: therole ofshale technology
MasoudShirazi1,2
Received: 27 April 2022 / Accepted: 27 January 2023
© The Author(s) 2023
Abstract
Sustainable energy systems are sensitive to the countries’ energy portfolio decisions, shaping geopolitics and contributing
to the global energy security (ES). Accordingly, this paper applies the “Markov regime-switching” method to explore the
impact of “the North American shale technology” (NAST) on behavioral regimes of the US energy security measurements
(ESM), e.g., diversity of primary energy demand (
ESII
), net energy import dependence (
ESIII
), non-fossil fuel resource
portfolio (
ESIIII
), and crude oil import dependency (
ESIIV
). The findings confirm time-varying and asymmetric behavior of
the US ESM before and after the NAST. Specifically, the overall interaction of substitution effect and scale effect of NAST
strengthens the US energy systems through
ESII
,
ESIIII
, and
ESIIV
, while
ESIII
leads to higher risks of the US energy sup-
ply security. Consequently, the shale reserves development, diversification of primary energy demand and import supply,
and advanced energy transport and trading policies, are suggested to overcome the barriers in achieving (i) availability, (ii)
accessibility, (iii) affordability, and (iv) acceptability aspects of ES and vulnerability reduction of the US energy systems in
respect of risk and resilience.
Keywords Energy security· Portfolio decision· Shale technology· Asymmetric behavior· Markov Switching Model
JEL Classification Q47· Q42· Q37
Introduction andcontribution
Background
Indeed, energy and the relevant policies are still assessed
today as the top challenges ahead to the nation’s future wel-
fare, way of life, and national security. The development of
energy systems, i.e., technological dynamics and social com-
plexity, needs to focus on (i) energy equity, (ii) energy secu-
rity, and (iii) environmental sustainability, called the “energy
trilemma” (Bale etal. 2015). Currently and based on Bale
etal. (2015), the world’s energy systems are trapped in a
carbon-based fuel portfolio (
CFP
), which is a motivation for
energy security (ES) development (Costello 2007; Shahzad
2020). Therefore, this paper aims to analyze dynamic behav-
ioral features of the US ES that relate to vulnerability reduc-
tion of the energy systems in terms of risk and resilience.
The issue of ES refers to a wide range of aspects (Yergin
2006), from the classic concept, i.e., affordable and reli-
able flow of resource supply (Yergin 1998; Colglazier and
Deese 1983) to contemporary definitions, e.g., environmen-
tal acceptability and accessibility, of energy sources in an
economy (Goldthau 2011)1. Specifically, ES covers 4 As,
including transportation, transmission, and geopolitical
accessibility2, environmental, political, and social accept-
ability, immediate physical availability, and price affordabil-
ity of primary energy sources (Sutrisno etal. 2021).
Particularly, in respect of physical availability, a
resource is available when it is plenty enough for keeping
on an important recoverable energy source. The economic
aspect of ES is described by the price affordability of the
resource acquisition. The accessibility feature of ES relates
Responsible Editor: Roula Inglesi-Lotz
* Masoud Shirazi
masoud.shirazi@uc.pt
1 CeBER andFaculty ofEconomics, University ofCoimbra,
Coimbra, Portugal
2 Cyprus Institute ofMarketing, Nicosia, Cyprus
1 See Cherp and Jewell (2014) for more details.
2 Geopolitical interests and events in the carbon-based energy market
changes, which makes new and renewable energy portfolio appear
more critical in the global energy security (Flouros et al. 2022;
Øverland etal., 2017).
/ Published online: 9 February 2023
Environmental Science and Pollution Research (2023) 30:48415–48435
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1 3
to transmission and transportation barriers, e.g., “long-
term sales contracts”, large infrastructure investments, and
geopolitical factors, among others. From the viewpoint of
environmental acceptability, the issue of ES indicates an
economy’s success in switching from fossil fuels and nuclear
energy to a new and renewable energy portfolio that low-
ers environmental degradation. In respect of infrastructure
within the country, actions held by developed and develop-
ing economies in response to the acceptability concerns are
dissimilar. The policies related to environmental, political,
and social acceptability for developed countries are focused
mainly on how the market mechanism allocates resources.
The objective of these countries is to invest in the research
and development projects of new and renewable energy
sources to capture long-term economic opportunities in
their energy systems since major financial constraints are
not issued in these economies. For developing countries,
acceptability policies are founded on the requirements for
renewable energy development, regional cooperation for
resources, foreign infrastructure investment, and risk and
capital sharing (APERC 2007)3. It is likely that new and
renewable energy sources not only impact geopolitics but
threat and realization of unfavorable geopolitical events,
particularly in institutionally and risky unstable situations,
can also affect investment decisions in such energy sources
by raising the capital cost. These geopolitical acts transfer
negative shocks to the energy markets through the asset pric-
ing mechanisms and return channels as the escalation of the
regional and international geopolitical tensions adversely
influences the energy finance and subsequently ES (Flouros
etal. 2022; Øverland etal. 2017).
Hence, policymakers in both energy-exporting and energy-
importing countries need to adopt comprehensive dynamic
energy policies and therefore, enhance their ESs (Chalvatzis
and Ioannidis 2017; Vivoda 2014; Cohen etal. 2011). How-
ever, the role of ES on resource- and non-resource sectors,
capital formation, technology improvements, and economic
growth of the energy-exporting countries is inevitable since
they are vulnerable to external market shocks (Nepal and
Paija 2019; Griffiths 2017; Bilgili etal. 2016). On the other
hand, as an economy is dependent on the imported-primary
energy sources to cover its primary energy demand (
PED
),
there is a limited possibility to meet its energy consumption
through domestic supply sources, which leads to higher risks
and less resilience (capability to respond to the disruptions)
of the country’s energy supply security4.
Since the 1970s, the ES has been made a priority by
Republican and Democratic presidential authorities and
policymakers. Yet, a regular tool is still missed to measure
the nation’s improvement and then assess the effect of poli-
cies on the United States (US) ES. Compared with 1980, the
USA was one of 15 countries with a 2018 risk score5 lower
than its initial 1980 score, from 1071 (its highest risk score
in the record) to 727, a drop of nearly one-third. The second
and third world’s lowest ES risk scores are established for
New Zealand and Canada with 757 and 802 scores, respec-
tively. Accordingly, for the USA with the world’s lowest
ES risk score, the first energy-usage rank of such economy
among 25 large energy-consuming countries intensifies
the importance of monitoring the time-varying behavioral
characteristics of ES that is necessary to develop the 4 As
dimensions of ES and hence, remain less vulnerable in terms
of risk and resilience, in response to the market shocks of
energy resources (Global Energy Institute. The US Chamber
of Commerce 2020)6.
The US crude oil and natural gas production, particularly
from primarily deep shales (geological or tight oil forma-
tions) have been increased through merging the “horizontal
drilling” with “hydraulic fracturing” technologies, called the
“shale technology”7. The focus of the US shale production
has been shifted from volumes to efficiency and overall per-
formance rates improvement. As a result, the industry has
switched to focus considerably on infrastructure, logistics,
and the supply chain optimization (Scholl 2019). However,
investment in oil and gas infrastructure is rarely a plain affair.
Due to remarkable uncertainties in future energy prices, geo-
political and regulatory challenges, and the large scales of
investments, projects often meet cost overruns and schedule
delays. In particular cases, the interests behind the invest-
ment plans might have to be shifted away (Tan and Bar-
ton 2017). Companies intend to extend the applied policies
that caused bumper profits in 2021, and shale activists are
3 Different priorities regarding diverse interpretations of ES require
specialization in energy policies (APERC 2007).
4 The affecting factors of energy system resilience refer to “techno-
logic diversification”, “spare production capacities”, “diverse suppli-
ers stockpiling”, and “emergency plans” (Yergin 2006).
5 The ES risk index assesses the annual countries' energy-related
vulnerability in the world energy market, which applies quantifiable
information, historical trend data, and governments' projections to
recognize the policy decisions and other affecting factors that relate
negatively or positively to the counties' ES (Global Energy Institute.
The US Chamber of Commerce 2020).
6 See APERC (2007) for the details of the US' ES comprehensive
roadmap, e.g., “Energy Policy Act 2005” and “Asia Pacific Partner-
ship”.
7 Based on Bilgili etal. (2016), China, Argentina, Algeria, the USA,
Canada, Mexico, Australia, South Africa, Russia, and Brazil are the
countries with the largest technically recoverable shale reserves,
respectively. However, these countries can't utilize shale gas as much
as the US utilizes (Auping etal. 2016), which is due to the differ-
ences in the US and the countries with technically recoverable shale
reserves, i.e., the institutional features and the large-scale exploitation
process of the shale reserves (Tian etal. 2014; Kuuskraa etal. 2013).
48416 Environmental Science and Pollution Research (2023) 30:48415–48435
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1 3
cautious of an investor's retaliation if they increase spending
too rapidly. But the issue of capital discipline is developing.
It is perhaps necessary and safer for the companies to expand
again, though at slower rates. Underpinning the profitability,
however, is unsustainable levels of investment. In 2021, most
US shale companies reinvested smaller than 50% of their
cash flows in new drilling activities, as the industry shifted
downward into the “maintenance capex” regime. But initial
wells production rates usually decrease quickly, so the com-
panies require to drill continuously for sustainable output.
Hence, they can just pull back on suggested investment con-
tinually without sacrificing future levels of production and
cash generation (Cahill 2022). In respect of the outcomes,
the “shale technology” decreases the natural gas cost of pro-
duction by declining the
CO2
separation costs via potential
technical and economic infrastructure, lowering the natural
gas price. Also, the intermediate technology of the shale gas
mitigates the US short-term environmental concerns since
the reduced prices of natural gas can decrease the energy
trilemma concerns (Acemoglu etal. 2019)8. Accordingly,
the “North-American shale technology” (NAST) is consid-
ered a potential determining factor to analyze the short- and
long-term behavioral properties of the US energy systems.
Contribution ofthestudy
This article aims to fill in the knowledge gap found through-
out the literature in the field of ES as follows:
First, and based on (APERC 2007) classifications, the
actual time-series of four behavioral indices, e.g., “diversi-
fication of primary energy demand” (
DoPED
), “net energy
import dependency” (
NEID
), “non-carbon-based fuel port-
folio” (
NCFP
), and “net oil import dependency” (
NOID
),
are calculated for the US economy during the period Janu-
ary 1973–April 2021, to analyze the behavior of the US ES
before- and after the NAST. To this end, the suggested time
period is divided, using the breakpoint in year 2006 as the
outset of the NAST (Shirazi and Šimurina 2022; Shirazi
etal. 2021; Geng etal. 2016)9.
Second, the time-series of the long-term trends and short-
term fluctuations of the actual ESM are extracted, using the
Hodrick and Prescott (1997) filter suggested by Ewing and
Thompson (2007). This decomposition helps to recognize
the impact of NAST on the long-term trends as well as the
magnitude, time duration, and the number of cyclical move-
ments (ups and downs) of the mentioned indices to follow
the behavioral characteristics, e.g., risk and resilience, of
the US ES.
Finally, the interconnection of uncertainty, speed-
and expected duration of the specified states through the
“Markov switching autoregressive method with regime
heteroskedasticity” (
MSARH
) is focused to explore the
potential asymmetric and time-varying behavioral switching
regimes of the US’ ESM, in response to the NAST (Shirazi
and Šimurina 2022; Shirazi etal. 2021; Geng etal. 2016)10.
Consequently, the comparative analysis of the findings
leads to identifying the US “portfolio decisions of primary
energy sources” (
PDPES
), declining risks and promote resil-
ience of energy systems, i.e., the equitability, diversification
and imports, and
CO2
-related environmental degradation, by
figuring out its main strengths and weaknesses11.
Therefore, to understand the impact of the NAST on the
behavioral characteristics regarding the performance of the
US ES, the following research questions are investigated:
• What is the difference in the behavior of actual, long-
term trends, and short-term fluctuations of the US ESM,
e.g.,
ESII
,
ESIII
,
ESIIII
, and
ESIIV
, pre-and post (p&p)-the
NAST?
• How are the behavioral features of the switching regimes
(e.g., typical state, uncertainty, and speed of the regimes)
of the US ESM explained p&p-the NAST?
• How is the US ES affected by the interconnection of
uncertainty, speed- and expected duration of specified
switching regimes of the measurements in response to
the NAST?
The overall findings of this paper support the time-
varying and asymmetric behavior of the US ESM p&p-the
NAST. Specifically, the equitability dimension of the US
ES are developed by the NAST that leads to a combination
of fewer risks and higher resilience of the US energy supply
security. Also, a mixture of higher risk and less resilience
is found for the US energy supply security after the NAST,
because the country has been getting highly relies on energy
imports and therefore, there is a limited possibility to meet
its energy consumption through domestic supply sources.
Moreover, results imply that the NAST improves the con-
tribution level of hydro, nuclear, and new and renewable
8 See Mason etal. (2015) for more details in respect of benefits of
the NAST for the US economy.
9 See
the “Material” section of this article for more details.
10 Following APERC (2007), only the actual time-series of these four
ESM are calculated and statically analyzed, for the Asia–Pacific Eco-
nomic Cooperation (APEC) members during the time period before
the NAST, which neither the impacts of the NAST on the behavior of
actual time-series and its decompositions of ESM nor the rest of the
aforementioned contributions of this article (especially the switching
regimes) are addressed.
11 This approach is applicable to develop ES of the countries that
have considerable technically recoverable shale reserves but haven't
significantly started yet to extract the reserves due to the technologi-
cal constraints, and also the economies that are net primary energy
importers to cover their energy consumption.
48417Environmental Science and Pollution Research (2023) 30:48415–48435
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1 3
energy sources (
NRE
) to total
PED
in the US primary energy
system, and hence, a considerable decline of the US'
CO2
-related environmental degradation is concluded12.
Literature andtheory
The first classification of recent studies regarding avail-
ability and accessibility dimensions of ES focuses on the
impact of energy sources’ regional and international trade
networks on ES (Tuchinda etal. 2021; Peng etal. 2021; Shi-
razi etal. 2021; Shepard and Pratson 2020; Dong etal. 2020;
Rodríguez-Fernandez etal. 2020;Shirazi etal. 2020; 2019;
Maltby 2013) and concludes that ES significantly depends
on reliable trade relationships throughout global trade net-
works of both renewables and non-renewables.
The second group of articles investigates determining the
risks around ES, e.g., environment, technology, energy sup-
ply, geopolitics, and economic factors of individual econo-
mies and regions (Kosai and Unesaki 2020a; García Mazo
etal. 2020; Hasanov etal. 2020; Karatayev and Hall 2020;
Lin and Raza 2020; San-Akca etal. 2020; Liu etal. 2020a,
b; Sun etal. 2020; Groissböck and Gusmão 2020; Zeng
etal. 2017; Kiriyama and Kajikawa 2014; Francés etal.
2013; Roques etal. 2008) and finds that
DoPED
, renewa-
bles development, citizen commitment, the mobilization of
technological and economic resources, and finally, a model
of generation, efficiency, and distribution as well as the pre-
ventive- and optimizing control models have constructive
roles in optimization of the security status and therefore,
ES enhancement.
The third category of literature analyzes the perfor-
mance of ES level based on indicators (Shirazi and Fuinhas
2023; Gong etal. 2021; Li etal. 2020; Augutis etal. 2020;
Kosai and Unesaki 2020b; Gasser 2020; Yuan and Lu 2019;
Sarangi etal. 2019; Li and Chang 2019; Le and Nguyen
2019; Gan etal. 2019; Wang and Zhou 2017; Kosai and
Unesaki 2017; García-Gusano etal. 2017; Anvar 2016; Kisel
etal. 2016; Ang etal. 2015; Thangavelu etal. 2015; Mart-
chamadol and Kumar 2014; 2013; Gracceva and Zeniewski
2013; Wu etal. 2012; Augutis etal. 2012; Stirling 2010;
Kruyt etal. 2009; Scheepers etal. 2006) and exhibits that
strategic management, storage and control of resource sup-
ply, higher reserves of energy sources, clean energy develop-
ment, optimization of the energy-consuming terminal struc-
tures, energy efficiency improvement and policy monitoring
increase the ES level in the countries under consideration.
The fourth sort of articles considers the use of poten-
tial opportunities to improve ESM (Yong etal. 2021; Jiang
etal. 2021; Bilgili etal. 2020; Rajavuori and Huhta 2020;
Bekhrad etal. 2020; Coester etal. 2020; 2018; Azzuni and
Breyer 2018) and illustrates the positive impact of invest-
ment screening projects such as integrated energy systems
on ES enhancement that is applicable through wave energy,
cross-country transactions in resource infrastructures,
energy hub security region, subsidized investing in renew-
able energy technologies, e.g., storage and controlling tech-
nologies, data-intensive energy technologies including the
digitalization process of the energy systems, and the shale
development.
Also, from the view of the energy dilemma, the com-
parative analysis between the transition towards renewable
energy sources and prioritizing fossil fuels as reliable sup-
plies is investigated (Taherahmadi etal. 2021; Mabea 2020;
Pérez etal. 2019; Novikau 2019; Gillessen etal. 2019; Lu
etal. 2019; Zaman and Brudermann 2018; Jun etal. 2009).
They conclude that focusing on renewables lowers the
import dependence of the economy, while reliable supplies
through transmission and storage capability can mitigate
the volatility and costs of the energy environment. Also,
the combination of ES perspectives and energy governance
helps developing countries to prevail the barriers of the
energy transition process.
Finally, some recent articles investigate the impact of oil
price shocks (Babajide 2017; Peersman and Van Robays
2012; Van Hove 1993) and energy intensity (Tvaronavičienė
2016; Tvaronavičienė etal. 2015; Dezellus etal. 2015; Dze-
myda and Raudeliūnienė 2014; Raudeliūnienė etal. 2014)
on the energy market. The most related conclusion to ESM
that the oil shocks lead to breaks in consumption patterns.
Also, they show that the development of sustainable entre-
preneurship and energy stewardship has a positive impact
on ES.
Therefore, the studies above, however, show no impli-
cations for the nexus between the “shale technology” and
the behavioral features of the ESM, specifically for the US
economy as the biggest world’s energy user (APERC 2007).
Especially, the US ES is affected by the NAST, through the
substitution effect and scale effect (Acemoglu etal. 2019;
Kuuskraa etal. 2013). Based on the substitution effect, the
process of the NAST facilitates the substitution of coal, oil,
and green energy sources (e.g., nuclear and renewables) by
natural gas throughout the energy portfolio that can enhance
DoPED
. Moreover, the high-carbon replacement effect
(coal- and crude oil replacement via natural gas) reduces the
country's
CO2
emissions. By contrast, the low-carbon energy-
related substitution effect (natural gas-clean energy sources
replacement effect) causes higher
CO2
emissions. It is gener-
ally supposed that the overall substitution effect can poten-
tially decrease
CO2
emissions from resource consumption
12 It is worth noting that the comparison between the results of NEID
and NCFP indices reveal the successful outcome of the US economy
in net oil import independence after the NAST, while the country has
not achieved any developments in import independence for the rest of
primary energy resources.
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1 3
since the high-carbon replacement effect dominates the low-
carbon substitution effect and hence, promotes the
NCFP
, i.e.,
low
CO2
-related environmental degradation, of the economy.
Besides, the NAST through the scale effect contributes to a
price reduction of the energy sources, supposed to have nega-
tive effects on the US NOID as well as
NEID
, which causes
the US ES enhancement through the possibility to meet its
energy consumption via domestic supply sources13.
Accordingly, the efficient
DoPED
should be utilized
to cause the US long-term ES. The US ES is analyzed on
this paper through the 4 As dimensions of primary energy
resources, e.g., coal, crude oil, natural gas, hydroelectric
power, and
NRE
. To this end, four indices, e.g.,
DoPED
,
NEID
, NCFP, and NCFP are calculated to expose the impor-
tance and potential risks and benefits, regarding the US'
PDPES
p&p-the NAST (APERC 2007). Then, the applicable
and comprehensive energy policies are suggested as impor-
tant factors affecting the structure of energy conservation and
vulnerability reduction, i.e., low risk and high resilience, to
increase ES and promote sustainable economic development.
a. DoPED: ESII
DoPED
balances the energy mix to cope with the
market shocks of energy resources that lead to volatil-
ity reduction of fuel prices, contributes to energy price
stability, and promotes the availability, affordability,
and accessibility aspects of ES, based on the preferred
objective priorities of the energy systems (Francés
etal. 2013). The Shannon index is modified to develop
DoPED
and measure biodiversity, which is presented
by ES indicator
I
(
ESII
). Therefore,
ESII
exhibits the
equitability dimension of the US
DoPED
that is shown
below:
where
D
is Shannon’s diversity index,
Pi
shows the share of
primary energy source
i
in total
PED
,
Dmax
displays the maxi-
mum value of
D
, and
i=(1, 2, …,T)
is used to indicate
T
types of primary energy sources. As the indicator is calculated
close to zero, the country is dependent on one primary energy
source, while a value close to 100 indicates that the economy’s
energy supply sources are equally distributed among the major
(1)
D=−
∑T
i=1
(PilnPi
)
(2)
ESI
I= DoPED =
D
Dmax
×
100
primary energy sources. Thus, a fewer risk of the US ES is
concluded as a higher indicator’s value is assessed. The graphi-
cal results of the Hodrick and Prescott (1997) filter for
ESII
are
shown in Fig.3.
b. NEID: ESIII
The second ES indicator is the US
NEID
. The Shannon
index is also transformed to measure the effect of diversifi-
cation and imports on ES. The second indicator (
ESIII
) for
the US economy is weighted by the energy consumption
intensity of each primary energy source as follows:
where
Ci
correction factor for
Pi
,
Dmax
the maximum value of
D
, and
mi
is used to indicate the share of net primary energy
import in energy source
i
. So, the US economy is depend-
ent on domestic primary energy sources to cover its
PED
as
the final value is closer to zero. Conversely, a value close
to 100% exhibits that the country highly relies on energy
imports and there is a limited possibility to meet its energy
consumption through domestic supply sources. Hence, a
higher risk of ES is concluded as a higher indicator’s value
is determined. The graphs of the actual, the cycle, and the
trend calculations of ESIII are depicted in Fig.4.
iii. NCFP: ESIIII
The third ES indicator (
ESIIII
) reflexes the US’ economy’s
success to switch from a
CFP
to
NCFP
. The third indicator
implies the contribution level of hydro, nuclear, and
NRE
to
total
PED
, shown as follows:
The
NCFP
indicator quantifies the progress of a country’s
diversification towards alternative energy sources by improv-
ing the share of non-fossil fuel energy sources (nuclear, and
new and renewable energies) applied to meet energy consump-
tion. Therefore, a considerable potential offset to lower
CO2
-related environmental degradation of the US ES is concluded
as a higher indicator’s value is calculated. The graphical pres-
entation of the calculated
ESIIII
, and its short-term fluctua-
tions, and long-term trend are depicted in Fig.5.
(3)
D=−
∑T
i=1
(CiPilnPi
)
s.t∶C
i=1−m
i
(4)
DoPED
Import Ref lective =
D
D
max
(5)
ESI
II = NEID = 1−
DoPEDImport Ref lective
ESII
(6)
ESI
III =NCFP =
Hydro PED
+
Nuclear PED
+
NRE PED
Total PED
13 The new and renewable energy sources are recognized locally
scaled affordable, which have currently considered weak potential
substitutes for the conventional energy sources, despite their impor-
tance to mitigate energy supply security concerns is growing. This
is due to that the future physical limitations met by the accessibility
dimension of ES are suggested to be reduced through the associated
technology developments (APERC 2007).
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1 3
iv. NOID: ESIIV
The share of the US economy’s net oil imports in its total
PED
is utilized as the fourth ES indicator to calculate the coun-
try’s
NOID
. The suggested indicator is presented below:
Consequently, a higher risk of the US ES is determined as
a higher indicator’s value is measured. The calculated time
series of the actual
ESIIV
for the US economy and its decom-
position into cyclical movements and long-term trend are pre-
sented in Fig.6.
Material andmethods
Material
In order to calculate the actual time-series of the US ESM, the
consumption and net import data in billion cubic feet for each
primary energy source, e.g., coal, natural gas, crude oil, hydro-
electric power, nuclear and new and renewable energy are col-
lected from the US Energy Information Administration (EIA)/
Monthly Energy Review, August 2021 for the period January
1973–April 2021. Also, the impact of NAST on the behavioral
characteristics of the US ESM are examined through divided time
periods, using the breakpoint in year 2006 as the beginning of
the NAST (Shirazi and Šimurina 2022; Shirazi etal. 2021; Geng
etal. 2016). Specifically, the US primary energy market is found
to have overlapped with numerous structural break points, during
the period of the global financial crisis. Therefore, the role of the
financial crisis mentioned above is eliminated to meet the specific
effects of NAST on ESM of the US economy without bias. Conse-
quently, the period of time during the beginning of 1973, January
to the first of January 2006 is suggested as pre-the NAST, and the
time period between 1 of September 2009 and the end of April
2021 is considered as post-the NAST (Shirazi and Šimurina 2022;
Shirazi etal. 2021; Geng etal. 2016; Aruga 2016)14.
Methods
The HP filter
In order to find any potential changes experienced by each
source of primary energy, e.g., the renewable and non-
renewable resources of the US energy system during the
time period under consideration, the Hodrick and Prescott
(1997) filter is applied in this paper to decompose the
actual time-series of primary energy sources to the cyclical
(7)
ESI
IV = NOID =
Net Cr ude Oil Imports
Total PED
movements (short-term fluctuations) and long-term trend of
the US economy p&p-the NAST15. Based on Fig.1, the cal-
culated share of each
PED
, e.g., biomass (a), coal (b), natural
gas (c), petroleum (d), nuclear (e), and total renewable (f), to
total primary energy consumption (
PED
) shows an increas-
ing trend after the NAST for biomass (a), natural gas (c)
and total renewable (f) resources, while the results indicate
a decreasing trend for coal (b) and petroleum (d) with no
significant change for nuclear electric power (d). Also, the
NAST leads to more short-term fluctuations of biomass (a),
coal (b), and total renewable (f), whereas the cyclical move-
ments of natural gas (c), petroleum (d), and nuclear electric
power (e) are not significantly affected by the NAST.
Moreover, the findings exhibit a decreasing trend for the
share of biomass (a), natural gas (d), crude oil (e), and petro-
leum (f) net import (
PENI
) to the total
PED
of the US' econ-
omy after the NAST, while an increasing trend is detected
for electricity (c) as well as clustering ups and downs for
the share of coal (b) net import to total
PED
, following the
NAST (Fig.2). From the other aspect, the short-term fluc-
tuations of the share of biomass (a), coal (b), natural gas
(d), and petroleum (f) net import to total
PED
are intensi-
fied after the NAST, whereas the results show no specific
changes for cyclical movements of electricity (c), and crude
oil (e) primary energy sources.
Accordingly, the potential impacts of the NAST on the
behavioral characteristics of the major ESM should be ana-
lyzed, since the US ES depends on the modes and specifications
of any changes experienced by each source of primary energy.
MSARH
Following Bai and Lam (2019), linear and static
regressions are not appropriate for modeling the behavioral
regimes of the US ESM, if the characteristics of kurtosis
and skewness are determined in the distribution functions
of the measurements. The Markov switching technic,
introduced by Hamilton (1996), helps to indicate that
ESM under different regimes have different characteristics,
which are often experienced in the model’s estimates. In
this regard,
MSARH
can effectively obtain variables’
dynamic characteristics and nonlinearity, which the
linear and static regressions do not capture. Therefore,
this technic facilitates the change in the ESM to switch
14 - The two sub-periods to recognize p&p-the NAST are distin-
guished through the black vertical lines provided in Figs.1, 2, 3, 4, 5, 6.
15 Based on the EIA data category, primary energy consumption
by the source is classified as biomass, coal, natural gas, petroleum,
nuclear, and total renewable, while primary energy net imports by
source are sorted as biomass, coal, electricity, natural gas, crude oil,
and petroleum. Accordingly, the primary energies listed for the con-
sumption (caption, Fig.1) and those for the import (caption, Fig.2)
are inconsistent.
48420 Environmental Science and Pollution Research (2023) 30:48415–48435
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1 3
between different states, considering any changes over
the mentioned time periods. Also, the model explores
the regimes of the ESM p&p-the NAST and then reveals
whether the NAST has led to the change of the US’ ESM,
following their dominant state differences. Accordingly,
the behavioral properties of a variable through a nonlinear
relation, are assumed for modeling, based on the variation
in different regimes. The quantitatively nonlinear models
are categorized into two main classifications in respect
of the switching speed across the determined regimes. In
the first category of the nonlinear models, e.g., “artificial
neural networks” and “smooth transition autoregressive
(STAR)”, the movement from a specified state to another
is determined slowly and moderately. While the regime
transition takes place sharply in the second category, e.g.,
“the Markov regime-switching models (
MRSM
)” and
“Copula method”. The modulation processing depends
on the system situation in the STAR and “artificial
neural network” models, and therefore, the gradual state-
switching process has been assessed. By contrast, the
state-change is introduced as an exogenous switching
process in the
MRSM
(Shirazi and Šimurina 2022; Shirazi
etal. 2021). Moreover, the “dynamic conditional method
of copula-GARCH” is a flexible technique, which is used
to analyze multivariate distributions by modeling heavy
tail, volatility clustering, asymmetric relationships, and
time-varying correlations, especially through the financial
time-series analysis (Bai and Lam 2019; Silva Filho etal.
2014). Notably, the characteristics of peak and thick tails
are better explained by
MSARH
. Despite the number
of switching states being pre-identified, the empirical
studies suggest that
MSARH
models can dominate various
drawbacks (Liang etal. 2019; Cheng etal. 2018). First,
MSARH
models are able to control multiple equilibria and
nonlinearities related to the interaction effects. Second,
various time-series characteristics of variables, including
non-normality, fat-tail, heteroscedasticity, and time-
varying issues are considered. Then, economic cycles are
determined endogenously by
MSARH
models; hence, it is
not required to separate the applied time-series into high
and low fluctuations. Lastly, the p-values of different states
can be explicitly assessed by
MSARH
models, particularly
the transition probability among switching duration and
several economic cycles. Consequently,
MSARH
relates to
the theoretical hypothesis of multiple equilibria and covers
the drawbacks related to the endogeneity issue. Since the
reaction of the US ESM may change in response to shocks
under several regimes p&p-the NAST,
MSARH
is a proper
technique for endogenously identifying the states during
the utilized period (Shirazi 2022; Shirazi and Šimurina
2022; Shirazi etal. 2021; Geng etal. 2016).
Specifically, statistical significance of estimated coef-
ficients (probability values) and the minimum value of
“the Akaike Information Criterion” (AIC) are suggested
-.8
-.4
.0
.4
.8
1
2
3
4
5
6
1975 19801985 19901995 2000 20052010 20152020
aTrendCycle
-6
-2
25
15
25
1975 1980 1985 19901995 20002005 2010 2015 2020
bTrendCycle
-8
-4
4
12
15
20
30
40
1975 1980198519901995 2000200520102015 2020
cTrendCycle
-6
-2
2
6
25
30
35
40
45
50
1975 1980 1985 1990 1995 20002005 20102015 2020
dTrendCycle
-2
-1
0
1
2
0
2
4
6
8
10
1975 198019851990199520002005 2010 20152020
eTrendCycle
-2
0
2
4
4
8
12
16
1975 1980 1985 1990 1995 2000 20052010 2015 2020
fTrendCycle
Fig. 1 The share of each
PED
to total
PED
; a Biomass, b Coal, c Natural Gas, d Petroleum, e Nuclear, f Total Renewable
48421Environmental Science and Pollution Research (2023) 30:48415–48435
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1 3
to determine the number of states. Therefore, the
MRSM
is presented by Hamilton (1989):
where
Yt
denotes the first difference of US' ESM, e.g.,
ESII
,
ESIII
,
ESIIII
, and
ESIIV
,
μ
is the mean, and
δ
is considered
as the standard deviation of
Yt
. As a discrete variable,
St
(St∈{1, 2, …,k})
shows the first difference of the US ESM
in different regimes. It is also noted that the standard devia-
tion (
δ
) and mean (
μ
) of
Yt
are dependent on the specified
regime
St
for the time
t
. Moreover,
φi
is introduced as the
parameters of the used model, and
εt
indicates a random
variable with
i.i.d ∼ N(0,1)
.
(8)
Y
t−μ
S
t
=
∑m
i=1
φi
(
Yt−i −μ
S
t−i )
+δ
S
t
ε
t
Following Hamilton (1990), the state and discrete-time of
the Markov switching process are applied for simulating
St
.
Therefore, the transition matrix probabilities are indicated as:
where
Pij
= Pr
[
S
t
=j
|
|
S
t−
1
=i
]
with
Pi1+P
i2+
⋯
+P
ik =1
for all
i
. Hamilton (1990) suggests the maximum-likelihood
method to estimate the aforementioned parameters. Also,
the value of
St
equals
j
as
εt
is
i.i.d ∼ N(0,1)
and hence, the
conditional probability-density function of the variable
Yt
is:
(9)
P=
⎡
⎢
⎢
⎣
P11 ⋯Pk1
⋮⋱⋮
P1
k
⋯P
kk
⎤
⎥
⎥
⎦
-.15
-.10
-.05
.00
.05
.10
-.3
-.2
-.1
.0
.1
.2
75 80 85 90 95 00 05 10 15 20
aTrendCycle
-2
-1
0
1
2
-6
-4
-2
0
2
75 80 85 90 95 00 05 10 15 20
bTrendCycle
-.15
-.10
-.05
.00
.05
.10
-.1
.0
.1
.2
.3
75 80 85 90 95 00 05 10 15 20
cTrendCycle
-1.5
-0.5
0.5
1.5-6
-4
-2
0
2
4
6
75 80 85 90 95 00 05 10 15 20
dTrendCycle
-6
-4
-2
0
2
4
0
5
10
15
20
25
75 80 85 90 95 00 05 10 15 20
eTrendCycle
-4
-2
0
2
4
-8
-4
0
4
8
12
75 80 85 90 95 00 05 10 15 20
fTrendCycle
Fig. 2 The share of each
PENI
to total
PED
; a Biomass, b Coal, c Electricity, d Natural Gas, e Crude Oil, f Petroleum
48422 Environmental Science and Pollution Research (2023) 30:48415–48435
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1 3
where
It−1
exhibits the captured information till
t−1
.
Accordingly,
θ=(μ
1,μ2,…,μk;σ1,σ2,…,σk)
presents
the vector of parameters to estimate through the model.
Furthermore, as
It−1
is conditional, then the probability
f(St
=j
|
|
I
t−1
;
θ)
is known. Therefore, the probability density
of the variable
Yt
is written as:
Moreover, the log-likelihood criteria for the observable
time period is:
Also, the maximum log-likelihood criteria is mentioned
for the model coefficients to be estimated. Then, the state
probability of
St
is denoted as:
The smooth probability considers that the probability
of the different states is determined, applying the avail-
able information through the sample under consideration.
Accordingly, the smoothed state probabilities are suggested
for each regime at all the time points during the samples,
based on Kim (1994). Hence, the smooth probabilities
through the model are identified as follows:
Finally, the expected time duration of specified regimes
is determined from the transition probability of
Pjj
. Specifi-
cally, the expected duration of regime
j
is as follows:
Consequently, the behavioral properties of
DoPED
and
NCFP
indices of the US ES are affected through the NAST
as follows:
if Uncertainty of “Upward” Regime (σ)
↓↑
& Speed-and
Expected Duration of “Upward” Regime
↑↓yields
→
Risk
↓↑
&
Resilience
↑↓yields
→
Energy Security
↑↓
While the effect of the NAST on the behavioral charac-
teristics of NEID and NCFP of the US ES is summarized as:
(10)
f(Y
t
St=j,It−1;θ) = 1
2πσj
exp
−(Yt−μ
j)2
2σ2
j
(11)
F(
St=j|
|It−1;θ
)
=P
(
St=1|
|It−1;θ
)
F
(
Yt|
|St=1, It−1;θ
)
+P(St=2|
|It−1;θ)F(Yt|
|St=2, It−1;θ)
+⋯+P
(
S
t
=k
|
|
I
t
−
1
;θ
)
F
(
Y
t|
|
S
t
=k, I
t
−
1
;θ
)
(12)
lnF
(θ)=
1
n∑n
t=
1lnF
(
Yt
|
|
It−1;θ
)
(13)
P(
St=j
|
|
It;θ
)
=F
(
St=j
|
|
It−1;θ
)
F
(
Yt
|
|
St=j,It−1;θ
)
F
(
R
t|
|
I
t
;θ
)
(14)
(
St=j
|
|
It;θ)=∑k
i=1P(St=j,St+1=i
|
|
IT;θ)=P
(St=j
|
|
It;θ).∑k
i=1
Pji × P(St+1=i
|
|IT;θ)
P(S
t+1
=i
|
|
I
t
;θ)
(15)
D
jj =
1
(1−P
jj
)
if Uncertainty of “Downward” Regime (σ)
↓↑
& Speed-
and Expected Duration of “Downward” Regime
↑↓yields
→
Risk
↓↑
& Resilience
↑↓yields
→
Energy Security
↑↓
Results anddiscussion
Results
Actual, long‑term trends, andcyclical movements oftheUS
ESM
The ES of an economy develops as the higher values of
ES indices
ESII
and
ESIIII
, and also fewer levels of
ESIII
and
ESIIV
are detected. However, the potential differ-
ent reaction of the ESM in response to the NAST may
be explained by the sensitivity level of energy sources
(e.g., renewable and nonrenewable) consumption and net
import for the specified indicators. Also, the different
roles of crude oil and other suggested energy resources
should be considered to analyze the mentioned reactions
(Babajide 2017). Notably, the energy prices affect the
diversification of primary energy supply that entails
harnessing new energy resources, which is conducive to
the resource equitability and abundance and switching
to non-carbon-based fuel portfolio (Shirazi and Fuinhas
2023).The findings may lead to a structural framework
that is supposed to enhance the US ES and promote sus-
tainable economic development. In the following, the
actual, long-term trends, and short-term fluctuations of
the US' ESM are presented.
a. DoPED: ESII
The Hodrick and Prescott (1997) decomposition of
DoPED
of the US economy (
ESII
) shows an increas-
ing trend with actual values from 75.4 to 91.2% pre-
the NAST, with minimum 91.89% and maximum
99.9% values after the NAST. It indicates that the
US economy’s energy supply sources have been get-
ting more equally distributed among the major pri-
mary energy sources and therefore, a fewer risk of
the US ES is concluded after the NAST. Moreover,
the results exhibit that the NAST leads to greater
magnitudes, and also fewer ups and downs for the
short-term fluctuations of
DoPED
, which is another
implication of the US ES development in terms of
higher resilience after the NAST (Fig.3).
48423Environmental Science and Pollution Research (2023) 30:48415–48435
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1 3
b. NEID: ESIII
Following Fig.4,
NEID
of the US economy (
ESIII
)
has a slowly increasing trend (a relatively flat slop) before
the NAST, while a moderate increase is experienced by
ESIII
after the NAST. Also, the minimum and maximum
actual values of the US
NEID
are 98.8 and 99%, respec-
tively which are high values before the NAST, while they
are 98.99 and 99.3% after the NAST, showing no sign of
a decreasing trend in response to the NAST. Furthermore,
a fewer resilience regarding
NEID
is identified, since the
magnitudes of ups and downs for short-term fluctuations of
ESIII
are considerably increased, after the NAST. Hence, the
overall results exhibit that the US economy highly relies on
energy resource imports p&p-the NAST. As a consequence,
higher risk and less resilience are illustrated for the US ES,
and therefore, there is a limited possibility to meet its energy
consumption through domestic supply sources.
c. NCFP: ESIIII
The third ES indicator is the
NCFP
of the US economy
(
ESIIII
) which shows a slowly increasing trend before the
NAST, while a significant increase is detected for
ESIIII
after the NAST (Fig.5). Also, the actual values of the US
NCFP
are low and changing from 6.5 to 16.5% before the
NAST, with the minimum 15.7% and maximum 24.9% val-
ues after the NAST. Furthermore, the results indicate no
significant changes in the magnitudes and numbers of ups
and downs for short-term fluctuations (resilience) of the
US
NCFP
after the NAST. Therefore, and as the result of
the NAST, a moderate potential offset to lower
CO2
-related
environmental degradation of the US ES is concluded.
d. NOID: ESIIV
The fourth ES indicator of the US economy (
ESIIV
) is
NOID
(Fig.6). The actual time-series of
ESIIV
exhibit an
increasing trend before the NAST, while a considerable
decrease is detected for
ESIIV
after the NAST. Also, the
minimum and maximum actual values of the US
NOID
are
4.5–24.5%, respectively pre-the NAST, while they decrease
from 23.6 to 5.5% after the NAST. Furthermore, the results
indicate moderate changes in the magnitudes and numbers
of ups and downs for the short-term fluctuations of the US
NOID
, after the NAST. Therefore,
NOID
of the US econ-
omy is negatively affected by the NAST, and a fewer risk
with no considerable change in the resilience of the US ES
is found as well, after the NAST.
Descriptive statistics andunit root tests
In the next step, this study investigates the descriptive statistics
and stationarity of the US ESM to support the pre-requisites
of the
MRSM
. Accordingly, and based on Table1, all calcu-
lated time-series of the US ESM are recognized leptokurtic and
skewed p&p-the NAST. Furthermore, they may demonstrate
asymmetric or tail dependence behaviors and may have fully
different types of marginal distributions.
Then, the unit root tests based on automatic bandwidth
selection of (Newey and West 1994; Andrews 1991) as well as
breakpoint unit root test procedure support the conclusion that
all the US ESM are stationary at the 1% statistical significance
level in their first differences p&p- the NAST (Table2). As a
consequence, the
MRSM
is applicable to justify the behavioral
states of the first difference of the US ESM (Bai and Lam 2019).
Fig. 3 DoPED
-4
-2
0
2
4
6
75
80
85
90
95
100
74 76 78 80 82 84 86 88 90 92 94 96 98 00 02 04 06 08 10 12 14 16 18 20
DiversificationofPrimary Energy Demand TrendCycle
Fig. 4 NEID
-.
10
-.
05
.00
.05
.10
.15
98
.6
98
.8
99
.0
99
.2
99.4
74 76 78 80 82 84 86 88 90 92 94 96 98 00 02 04 06 08 10 12 14 16 18 20
NetEnergyImportDep endencyTrendCycle
48424 Environmental Science and Pollution Research (2023) 30:48415–48435
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1 3
Results ofMSARH oftheUS ESM
The regimes of the US ESM are explained by the number of
states, which are determined on the statistical significance
of probability values related to the estimated coefficients
and minimum of the AIC statistic. Accordingly, and based
on the value and the sign of the estimated parameters, two
“downward” (decrease state) and “upward” (increase state)
regimes of the indices are classified in this paper (Shirazi
and Šimurina 2022; Shirazi etal. 2021; Geng etal. 2016;
Zhang and Zhang 2015; Artis etal. 2004; Ferrara 2003)16.
Specifically, the “downward” regime (“upward” regime) is
assessed as the sign of the estimated parameter is negative
(positive) that shows the decrease (increase) state of the
specified regimes.
a. MSARH of the US'ESII
P&p-the NAST, the US
DoPED
shows two regimes. All
parameter estimates of the regimes are found statistically
significant (Table3)17. The two regimes are summarized as
“upward” and “downward”. As the regime switches from
“upward” to “downward”, the uncertainty (
σ
) faced by the
US
DoPED
increases after the NAST, indicating that the
variations of the US
DoPED
are vulnerable to disruption
Fig. 5 NCFP
-
4
-
2
0
2
4
6
5
1
0
1
5
2
0
2
5
3
0
74 76 78 80 82 84 86 88 90 92 94 96 98 00 02 04 06 08 10 12 14 16 18 20
Non-Carbon-BasedFuelPortfolio TrendCy cle
Fig. 6 NOID
-6
-4
-2
0
2
4
0
5
10
15
20
25
74 76 78 80 82 84 86 88 90 92 94 96 98 00 02 04 06 08 10 12 14 16 18 20
NetOil Import DependencyTrendCycle
Table 1 Descriptive statistics of
the US ESM Pre-the NAST
Index Mean Median Max Min Std.Dev Skewness Kurtosis Jarque–Bera (Prob)
ESII
85.91 87.36 91.24 75.44 3.8 − 1.09 2.9 79.5 (0.00)
ESIII
98.91 98.92 99.04 98.78 0.06 − 0.15 1.99 18.1 (0.00)
ESIIII
12.76 13.65 16.41 6.45 2.37 − 0.9 2.73 55.6 (0.00)
ESIIV
15.42 15.34 24.48 4.48 4.5 − 0.1 2.19 11.1 (0.00)
Post-the NAST
ESII
94.83 94.74 99.99 91.89 1.62 0.49 3.1 5.8 (0.06)
ESIII
99.11 99.11 99.3 98.99 0.06 0.54 2.83 7.2 (0.03)
ESIIII
18.95 18.75 24.9 15.7 1.62 0.66 3.92 15.1 (0.00)
ESIIV
15.4 16.2 23.6 5.5 4.7 -0.52 2.42 8.3 (0.02)
16 Refereeing to (Zhang and Zhang 2015; Artis etal.2004; Ferrara
2003), as the results show more than one “upward" or “downward''
regimes, the “slightly”, “moderately” and “sharply” regimes are
detected based on the descending to ascending sizes or magnitudes of
the estimated parameters, respectively.
17 Note: ***, **, * indicate 0.01, 0.05, 0.1 significant level, respec-
tively.
48425Environmental Science and Pollution Research (2023) 30:48415–48435
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1 3
by affecting factors when heading on the decrease phase,
while they almost are the same before the NAST. The
speed (magnitude)- of the “upward” regime is greater
than the “downward” regime p&p-the NAST. Moreover,
the expected duration- of
ESII
in the “downward” regime
(14.2months) is considerably higher than the “upward”
regime (1.6months) after the NAST, while the same speed
is detected before the NAST with a fewer duration level for
the “downward” regime (2.25months). Furthermore, the
transition probabilities show that the “downward” regime
(93%) is more probable to persist than the “upward” regime
(37%) after the NAST, which is consistent with the regime
expected duration results. According to the expected dura-
tions, a “downward” (“upward”) regime is the dominant
or typical state of the US
DoPED
p&p the NAST. Conse-
quently,
DoPED
mitigates the volatility of fuel prices, con-
tributes to the fuel price stability, and hence develops the US
ES in terms of risk and resilience (Kosai and Unesaki 2020a,
Table 2 Unit root test of the
US ESM Pre-the NAST Level First difference
Unit root test Adj. t-Stat (Prob) Breakpoint (Prob) Adj. t-Stat (Prob) Breakpoint (Prob)
ESII
− 3.3 (0.07) − 4.1 (0.3) − 29.3 (0.00) − 23.7 (
<0.0
1)
ESIII
− 7.4 (0.00) − 7.7 (
<0.0
1) − 46.7 (0.00) − 22.3 (
<0.01
)
ESIIII
− 4.1 (0.01) − 4.6 (0.1) − 25 (0.00) − 17.8 (
<0.01
)
ESIIV
− 5.1 (0.00) − 5.4 (
<0.01
) − 23.7 (0.00) − 16.7 (
<0.01
)
ESII
− 4 (0.01) − 4.3 (0.2) − 9.7 (0.00) − 10.4 (
<0.0
1)
ESIII
− 4.8 (0.00) − 5.8 (
<0.01
) − 27.8 (0.00) − 13.1 (
<0.01
)
ESIIII
− 3.8 (0.03) − 4.9 (0.03) − 13.6 (0.00) − 12.6 (
<0.01
)
ESIIV
− 3.6 (0.03) − 5.03 (
0.03
) − 20.9 (0.00) − 11.6 (
<0.0
1)
Table 3 The
MSARH
of the US
ESII
Pre-the NAST
Dependent Variable:
ESII
, AR (1)
“Upward” Regime “Downward” Regime
Variables Coefficients Variables Coefficients
C 0.56*** C − 0.4***
σ
0.49***
σ
0.46 ***
Transition Probability
Regimes “Upward” “Downward”
“Upward” 0.47 0.53
“Downward” 0.44 0.56
Expected Duration
“Upward” Regime: 1.88 “Downward” Regime: 2.25
Durbin-Watson: 2.03 Log-likelihood: − 405.6
Post-the NAST
Dependent Variable:
ESII
, AR (6)
“Upward” Regime “Downward” Regime
Variables Coefficients Variables Coefficients
C 0.14*** C − 0.06**
σ
0.02***
σ
0.9
Transition Probability
Regimes “Upward” “Downward”
“Upward” 0.37 0.63
“Downward” 0.07 0.93
Expected Duration
“Upward” Regime: 1.6 “Downward” Regime: 14.2
Durbin-Watson: 2.07 Log-likelihood: − 166.7
48426 Environmental Science and Pollution Research (2023) 30:48415–48435
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1 3
b; García Mazo etal. 2020; Liu etal. 2020a, b; Sun etal.
2020; Groissböck and Gusmão 2020; Francés etal. 2013;
Roques etal. 2008)18. In respect of diagnostic tests, the find-
ings of Durbin-Watson (DW) statistics pre- (2.03) and post-
(2.07) the NAST show that no autocorrelation problem in
the residuals is assessed in both sub-samples. Besides, the
maximum Log-likelihood value (MLV) detects the goodness
of fit through the models p&p the NAST.
b. MSARH of the US ESIII
Based on Table4, the US
NEID
shows “downward” and
“upward” regimes p&p the NAST. As the regime switches,
the uncertainty faced by
ESIII
is relatively stable p&p-the
NAST, indicating that the short-term fluctuations of
ESIII
are invulnerable to disruption by affecting factors when
the regimes change. Moreover, the speed or size- of the
“upward” regime is greater than the “downward” regime,
which exhibits that the US
NEID
has proceeded to indicate
a fast upward- and sluggish downward movements post-the
NAST, whereas the same speed is detected before the NAST.
Furthermore, the NAST causes markedly higher speed for
the “upward” regime, while the speed of the “downward”
regime is not affected. Consistent with transition probabili-
ties, the “downward” regime of
ESIII
has a larger expected
duration (6.06months) after the NAST. The “downward”
regime is therefore the dominant regime of the US’
NEID
post-the NAST, and also no dominant state is detected pre-
the NAST. Consequently, in respect of risk and resilience,
ES enhancement is achievable through the energy hubs,
cross-border transactions in energy infrastructures and
energy technologies, e.g., storage technologies and the shale
development that is aligned with (Yong etal. 2021; Jiang
etal. 2021; Coester etal. 2020; 2018; Rajavuori and Huhta
2020; Bekhrad etal. 2020; Azzuni and Breyer 2018)19.
Notably, the findings of DW statistics pre- (1.97) and post-
(1.77) NAST indicate no existence of autocorrelation in the
models’ residuals during both sub-samples. Also, the MLV
suggest the goodness of fit for the models’ p&p-the NAST.
c. MSARH of the US ESIIII
Before and after the NAST, the movements of the US
NCFP
have two significant security regimes (Table5), which
are summarized as “upward” and “downward”. However, the
US
NCFP
presents the characteristics of decrease as well
as increase p&p-the NAST. As the regime switches from
“upward” to “downward”, the uncertainty faced by the
ESIIII
decreases after the NAST, while they almost are the same
before the NAST. The speed or size- of the “upward” is
greater in comparison with the “downward” pre-the NAST,
showing a slow decrease and steep increase in reaction to
the NAST, while they are similar after the NAST. Consist-
ent with state transition probabilities, the expected dura-
tion of
ESIIII
in the “downward” regime (5.27months) is
higher than the “upward” regime (2.26months) before the
NAST, while the “downward”- and the “upward” regimes
show the same expected duration (3.6months) after the
NAST. According to the expected duration of the movement
regimes, the “upward” regime is the dominant state of the
US
NCFP
pre-NAST, whereas no dominant state is detected
post-NAST. It is concluded that focusing on
NCFP
decreases
the costs of the US energy environment in terms of risk and
resilience, and hence less
CO2
-related environmental deg-
radation is assessed (Taherahmadi etal. 2021; Acemoglu
etal. 2019; Gillessen etal. 2019; Anvar 2016; Jun etal.
2009; Lacasse and Plourde 1995)20. Moreover, the findings
of the MLV and DW statistics exhibit no concern regarding
the goodness of fit and autocorrelation in the residuals for
both models.
d. MSARH of the US ESIIV
P&p-the NAST, the US
NOID
shows two states. All
estimated parameters of both regimes are statistically sig-
nificant (Table6). The two states are called “downward”
and “upward”. When the regime switches from “upward” to
“downward”, the uncertainty faced by the US
NOID
mark-
edly increases post-the NAST, indicating that movements of
the US
NOID
are more vulnerable to disruption by affecting
factors when the
ESIIV
faces the decrease phase, while it is
stable pre-the NAST. The size- of the “downward” regime
is the same as the “upward” regime post-the NAST, whereas
it is relatively fewer than the “upward” regime before the
NAST. Consistent with transition probabilities, after the
NAST, the “downward” state of the US
NOID
has the larger
expected duration (24.4months), while the two regimes are
relatively the same in expected duration before the NAST.
The “downward” state is therefore the dominant state of
ESIIV
after the NAST. Accordingly, focusing on the advantages
of NAST declines
NOID
of the US economy, and hence,
18 Among member countries of Asia–Pacific Economic Cooperation
(APEC), Canada, New Zealand, and Chile are projected to reduce the
diversification of primary energy demand (APERC 2007).
19 As the diversification of primary energy demand decreases due to
lack of domestic energy resources, the level of NEID increases, which
is experienced by Japan, South Korea, Singapore, Chinese Taipei,
Hong Kong, and Chile (APERC 2007).
20 Most countries around the world have not been successful in con-
siderable environmental degradation through NCFP, showing the
growth rate of non-carbon-based energy sources is not high enough to
cover their future consumption growth (APERC 2007).
48427Environmental Science and Pollution Research (2023) 30:48415–48435
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1 3
the reliable energy supplies can mitigate volatility and vul-
nerability of the energy system, in the respect of risk and
resilience (Acemoglu etal. 2019; Pérez etal. 2019; Novi-
kau 2019; Gillessen etal. 2019; Zaman and Brudermann
2018)21. Besides, the findings of the MLV and the DW statis-
tics indicate that neither “misspecification of the functional
form” nor “autocorrelation in residual terms” is not an issue
through the models.
Discussion
Based on the calculated values of the first ES index,
ESII
,
the equitability dimension of the US'
DoPED
are increased
gradually pre-the NAST, while a significant take-off with
more persistent ups and downs is detected after the NAST
(Fig.3). From the aspect of uncertainty, the country exhibits
less biodiversity in primary energy sources after the NAST,
when
ESII
faces the “downward” regimes. Also, and due to
the higher speed of the “upward” regimes, the economy’s
energy supply sources keep on taking the line of more equal
distribution among the major primary energy sources post-
NAST. Despite the overall positive impacts of the NAST on
ESII
, the dominant “downward” regime in p&p-the NAST is
the sign of concerns for the biodiversity of the US primary
energy sources (Table3). Consequently, the interconnection
of uncertainty, speed- and expected duration of specified
switching regimes of
DoPED
lead to a combination of fewer
risks and higher resilience of the US ES, in response to the
NAST. Specifically, the NAST causes resource availability,
and a negative correlation among energy prices that facili-
tates the replacement of coal, oil, and green energy sources
(e.g., nuclear power and renewable energy resources) by nat-
ural gas in the energy mix that supports the physical avail-
ability, price affordability and accessibility dimensions of
the US ES, and therefore, increases the US
DoPED
(Kosai
and Unesaki 2020a, b; García Mazo etal. 2020; Hasanov
etal. 2020; Liu etal. 2020a, b; Sun etal. 2020; Acemoglu
etal. 2019; Francés etal. 2013).
Following the results of
NEID
, the calculated values of
ESIII
are not decreased after the NAST that shows no sign of
Table 4 The
MSARH
of the US
ESIII
Pre-the NAST
Dependent Variable:
ESIII
, AR (1)
“Upward” Regime “Downward” Regime
Variables Coefficients Variables Coefficients
C 0.01*** C − 0.01***
σ
0.01***
σ
0.01***
Transition Probability
Regimes “Upward” “Downward”
“Upward” 0.36 0.64
“Downward” 0.64 0.36
Expected Duration
“Upward” Regime: 1.57 “Downward” Regime: 1.56
Durbin-Watson: 1.97 Log-likelihood: 1031.7
Post-the NAST
Dependent Variable:
ESIII
, AR (4)
“Upward” Regime “Downward” Regime
Variables Coefficients Variables Coefficients
C 0.07*** C − 0.01***
σ
0.04***
σ
0.02***
Transition Probability
Regimes “Upward” “Downward”
“Upward” 0.07 0.93
“Downward” 0.16 0.84
Expected Duration
“Upward” Regime: 1.08 “Downward” Regime: 6.06
Durbin-Watson: 1.77 Log-likelihood: 270.3
21 It is projected that among 21 member countries of APEC, 9 econo-
mies including the USA, China, Australia, Peru, Chile, Malaysia,
Indonesia, Vietnam, and Thailand will develop their levels of ES in
the terms of NCFP by 2030 (APERC 2007).
48428 Environmental Science and Pollution Research (2023) 30:48415–48435
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1 3
a considerable proper reaction to the NAST. Also, the short-
term fluctuations of
ESIII
are significantly intensified after
the NAST. This is the other sign of no ES development in
response to the NAST in respect of
DoPED
, and imports
through the US energy systems (Fig.4). From the aspect of
uncertainty, the country becomes less vulnerable to disrup-
tion by affecting factors after the NAST, when
ESIII
faces the
“downward” regimes. Also, and due to higher magnitudes of
the “upward” regimes, the US economy gets more dependent
on foreign primary energy sources to cover its
PED
post-the
NAST. Despite the overall improper impacts of the NAST
on ESIII, the dominant “downward” state after the NAST
may lessen the concerns of the US dependency on domes-
tic primary energy sources (Table4). Hence, a mixture of
higher risk and less resilience of ES is concluded for the US
energy systems through the NAST, as the country has been
getting highly relies on energy imports and therefore, there
is a limited possibility to meet its energy consumption via
domestic energy sources. Consequently, the US diversifica-
tion and imports of energy sources should be re-designed
(Gong etal. 2021; Lin and Raza 2020; Li etal. 2020; Augutis
etal. 2020; Kosai and Unesaki 2020a, b; Gan etal. 2019).
Also, the increasing trend and relative stability of the
cyclical movements of the third ES measurement (
ESIIII
)
indicate that the US economy is significantly successful to
switch from
CFP
to
NCFP
after the NAST (Fig.5). From the
aspect of uncertainty, the vulnerability of the US economy to
disruption by affecting factors is increased after the NAST,
when
ESIIII
enters the “upward” regimes. Also, the speed
of “upward” regimes decreases after the NAST, leading to
a higher risk with no markedly change in the resilience of
potential offset in order to lower the US
CO2
-related environ-
mental degradation, which can be intensified by no dominant
“upward” regime post-the NAST (Table5). Accordingly,
the findings imply that the NAST improves the contribution
level of hydro, nuclear, and
NRE
to total
PED
in the US
primary energy systems, and hence a considerable decline in
the US
CO2
-related environmental degradation is concluded.
So, the intermediate technology of the NAST develops the
CO2
-related environmental, political, and social acceptabil-
ity dimensions of the US ES since the price reduction of
natural gas leads to the
CO2
emission decline (Shirazi and
Šimurina 2022; Sutrisno etal. 2021; Acemoglu etal. 2019;
Gillessen etal. 2019; APERC 2007).
Table 5 The
MSARH
of the US
ESIIII
Pre-the NAST
Dependent Variable:
ESIIII
, AR (3)
“Upward” Regime “Downward” Regime
Variables Coefficients Variables Coefficients
C 0.62*** C − 0.25***
σ
0.43***
σ
0.42***
Transition Probability
Regimes “Upward” “Downward”
“Upward” 0.58 0.42
“Downward” 0.19 0.81
Expected Duration
“Upward” Regime: 2.36 “Downward” Regime: 5.27
Durbin-Watson: 1.96 Log-likelihood: − 334.7
Post-the NAST
Dependent Variable:
ESIIII
, AR (3)
“Upward” Regime “Downward” Regime
Variables Coefficients Variables Coefficients
C 0.45** C − 0.42***
σ
0.83***
σ
0.46***
Transition Probability
Regimes “Upward” “Downward”
“Upward” 0.72 0.28
“Downward” 0.28 0.72
Expected Duration
“Upward” Regime: 3.6 “Downward” Regime: 3.6
Durbin-Watson: 1.91 Log-likelihood: − 166
48429Environmental Science and Pollution Research (2023) 30:48415–48435
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1 3
Finally, the actual time-series of
ESIIV
show a consider-
able change from an increasing to a decreasing trend after
the NAST that exposes the share of the US economy's net
oil imports in its total
PED
is decreased. Also, the short-
term fluctuations of
ESIIV
get limited significantly after the
NAST (Fig.6). In contrast, the US concerns in respect of
ES increase, when the “downward” regime of
ESIIV
takes
place. Despite the speed of the “upward” and “downward”
regimes decline after the NAST, the existence of a typical
“downward” state of
ESIIV
may cause a fewer risk but no sig-
nificant change in resilience for the US ES, after the NAST
(Table6). Therefore, the overall signals exhibit that
NOID
of the US economy is properly affected by the NAST in
respect of sustainable development. Hence, and consistent
with (Gan etal. 2019; Biresselioglu etal. 2015; 2012; Lac-
asse and Plourde 1995), the decreasing reliance on import
energy resources reduces the country’s sensitivity to the
effects of the external shocks occurred in the US energy-
importing process. Notably, the comparison between the
results of the second (
ESIII
) and fourth (
ESIIV
) US ESM
reveals the successful outcome of the US economy in
NOID
after the NAST, while the country has not achieved any
developments in import independence for the rest of primary
energy resources22.
Therefore, the US ES can be enhanced in respect of “the
energy trilemma” via the efficient interaction among the
short-term effects, e.g., substitution and scale effect, and the
long-term impacts of the NAST through
DoPED
,
NCFP
,
and
NOID
, while
NEID
declines the US ES, in terms of risk
and resilience23. Accordingly, focusing on the energy-related
concept of economic complexity, i.e., the strategic manage-
ment, control and storage of energy supply, higher reserves of
energy sources, optimized structure of the terminal sectors’
Table 6 The
MSARH
of the US
ESIIV
Pre-the NAST
Dependent Variable:
ESIIV
, AR (3)
“Upward” Regime “Downward” Regime
Variables Coefficients Variables Coefficients
C 0.79*** C − 0.62**
σ
1.05
σ
1.1
Transition Probability
Regimes “Upward” “Downward”
“Upward” 0.29 0.71
“Downward” 0.61 0.39
Expected Duration
“Upward” Regime: 1.4 “Downward” Regime: 1.63
Durbin-Watson: 2.06 Log-likelihood: − 666
Post-the NAST
Dependent Variable:
ESIIV
, AR (3)
“Upward” Regime “Downward” Regime
Variables Coefficients Variables Coefficients
C 0.1*** C − 0.09***
σ
0.004***
σ
1.17**
Transition Probability
Regimes “Upward” “Downward”
“Upward” 0.02 0.98
“Downward” 0.04 0.96
Expected Duration
“Upward” Regime: 1.01 “Downward” Regime: 24.4
Durbin-Watson: 2.07 Log-likelihood: − 209.6
22 Based on Sutrisno etal. (2021), Acemoglu etal. (2019), Gan etal.
(2019), Gillessen et al. (2019), Biresselioglu et al. (2015; 2012),
APERC (2007), Lacasse and Plourde (1995), it is suggested that the
oil supply security is significantly dependent on the movements in the
contributions of energy consumption across oil intensive sectors, eco-
nomic development, diversification of primary energy demand, and
diversification of energy import supply.
23 The overall results present the asymmetric and time-varying
behavioral regimes for the US ESM, e.g., diversification of primary
energy demand, NEID, NCFP, and NCFP, pre-and post-the NAST.
48430 Environmental Science and Pollution Research (2023) 30:48415–48435
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1 3
energy consumption, clean energy development, and energy
efficiency improvement, which is the outcome of the NAST,
is necessary to enhance 4 As dimensions of ES when internal
and external shocks occur in the US primary energy systems.
Different priorities regarding diverse interpretations of
ES require specialization in energy policies since countries
with technically recoverable shale reserves are different in
the institutional features, especially regarding the large-scale
exploitation process of the shale reserves. Nevertheless, it is
expected that switching from underdeveloped and develop-
ing technologies (scale effect) to the change in the institu-
tional characteristics and intermediate technology (compo-
sition effect) and developed technologies (technique effect)
lead to movement towards efficient shale industrialization
process. Based on the results of this work and in respect of
other countries' exploration to the shale reserves, utilization
of the economies of scale in the shale technology devel-
ops the coordinating mechanism in the countries' energy
systems. This process probably enables these countries to
exploit their shale reserves commercially, which leads to
signify utilization of the desirable explicit and implicit ES
outcomes, especially for China, Argentina, Algeria, Mexico,
Canada, Australia, Russia, South Africa, and Brazil that have
technically recoverable shale reserves, but have not markedly
started to extract the shale reserves due to the institutional
and technological constraints.
However, the innovation and technology advancements
of the shale reserves significantly escalate the shale oil and
gas production, which cause undesirable market effects, and
socio-environmental concerns, e.g., the methane emissions
known as the by-product of the shale reserves, and marine
pollution caused by large water intensity of the hydraulic
fracturing (Bilgili etal. 2016; Wang etal. 2014), habitat
destruction, and local anomalies (Mason etal. 2015) that
are mentioned as the major limitations of this research and
therefore, suggested to study by further investigations.
Conclusions
While ES has explicit and implicit impacts on the economy,
the US
PDPES
in terms of “the energy trilemma” shape geo-
politics and affect global ES. The effect of the NAST on ES
performance is known as a necessary condition to overcome the
barriers on the way of vulnerability reduction and promotion of
sustainable economic development for the USA as the world’s
largest energy-consuming economy. Therefore, a comprehensive
analysis is aimed in this research to examine time-varying and
asymmetric behavioral characteristics of the US ES p&p-the
NAST. The US ES is analyzed in this paper through the 4 As
of primary energy resources using the
MSARH
. To this end,
four indices, e.g.,
DoPED
, NEID, NCFP, and NCFP are calcu-
lated to expose the importance and potential risks and benefits,
regarding the US'
PDPES
p&p-the NAST. The findings indicate
that the interconnection of uncertainty, speed and expected dura-
tion of the specified switching regimes of the measurements
support the time-varying and asymmetric behavioral regimes
for the US ESM p&p-the NAST. Also, the overall interaction
of substitution effect and scale effect of the NAST develops the
US ES in terms of risk and resilience, through
PDPES
. Conse-
quently, the relative policy implications are presented as follows:
• Facilitating
DoPED
via the offshore shale institutional
improvements to mitigate the volatility of fuel prices and
hence, contribute to the fuel price stability and long-term
sustainability transitions.
• Developing the shale innovative and intermediate tech-
nologies, and the country’s commitments to NCFP via
R&D loan guarantees to decrease the costs of the US
energy environment and therefore, capture less
CO2
-related environmental degradation
• Alternating analysis of the risks and benefits of the
shale and renewable energy technological changes to
decline the
NEID
of the US economy and thus, more
reliable energy supplies to meet its energy consumption
through domestic supply sources
• Promoting resilience of the US energy systems through
the strategic management, control and storage of energy
supply, higher reserves of energy sources, clean energy
development, optimization of the structure of terminal
energy consumption, and energy efficiency improvement
• Adopting energy transport and trading improvement pol-
icies, regarding the accessibility along major resource
trade routes
Acknowledgements I would like to take this opportunity to thank you
for the effort and expertise that you contribute to reviewing, without
which it would be impossible to maintain the high standards.
Author contribution Masoud Shirazi: Conceptualization, Methodol-
ogy, Software, Data curation, Writing—Original draft preparation, Vis-
ualization, Investigation, Supervision, Validation, Writing—Reviewing
and Editing.
Funding Open access funding provided by FCT|FCCN (b-on).
Data Availability Data is available upon request.
Declarations
Competing interests The author declares no competing interests.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article's Creative Commons licence, unless indicated
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otherwise in a credit line to the material. If material is not included in
the article's Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.
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