Article
Conflict Management and Peace Science
2015, Vol. 32(4) 443–461
Ó The Author(s) 2015
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DOI: 10.1177/0738894214559672
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Almost nuclear: Introducing the
Nuclear Latency dataset
Matthew Fuhrmann
Texas A&M University, USA
Benjamin Tkach
Texas A&M University, USA
Abstract
The capacity to build nuclear weapons—known as ‘‘nuclear latency’’—is widely believed to be
important in world politics. Yet scholarly research on this topic remains limited. This paper introduces
a new dataset on nuclear latency from 1939 to 2012. It discusses coding procedures,
describes global trends, and compares the dataset with earlier efforts to measure nuclear latency.
We show that nuclear latency is far more common than nuclear proliferation: 31 countries developed
the capacity to build nuclear bombs from 1939 to 2012, and only 10 of those states went
on to acquire atomic arsenals. This paper provides one empirical application of the dataset, showing
how the study of nuclear latency can contribute to our understanding of international conflict.
We provide preliminary evidence that nuclear latency reduces the likelihood of being targeted in
militarized disputes. Having the capacity to build nuclear weapons, therefore, may provide deterrence
benefits that we usually associate with possessing a nuclear arsenal.
Keywords
International conflict, nuclear latency, nuclear proliferation
Introduction
Only 10 countries have built nuclear weapons to date. Yet many others have the technical
capacity to proliferate if they so desired. States that could assemble an arsenal relatively
quickly in the event of a crisis, like Japan, possess nuclear latency. Latent nuclear powers, it
is sometimes said, are ‘‘a screwdriver’s turn away’’ from making a nuclear bomb (e.g. Sanger
and Parker, 2012).
Nuclear latency is potentially consequential for world politics. First, the spread of latent
nuclear capabilities could influence international conflict. According to an emerging wisdom,
Corresponding author:
Matthew Fuhrmann, Department of Political Science, Texas A&M University, 4348 TAMU, College Station, TX 77843, USA.
Email: mfuhrmann@pols.tamu.edu
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nuclear latency can deter military attacks (Horowitz, 2013; Levite, 2002/2003; Paul, 2000).
However, a state’s capacity to assemble a nuclear arsenal in short order can also trigger conflict,
as underscored by the ongoing crisis over Iran’s nuclear program. Although it remains
to be seen whether Tehran will build nuclear weapons, the mere possibility that it could expeditiously
assemble a nuclear bomb in the future has led some officials in Israel and the USA
to call for preventive military action against Iran. Second, having the capacity to build
nuclear weapons could provide states with political leverage—even if they never assemble an
arsenal (Volpe, 2013). Henry Kissinger (2012) suggested, for example, that Iran’s nuclear
latency enhances its influence in the Middle East: its latent capacity, he argued, will ‘‘lead
many of Iran’s neighbors to reorient their political alignment toward Tehran’’. Third, nuclear
latency could foment nuclear proliferation by triggering the global diffusion of advanced
nuclear technology. For instance, Iran’s nuclear program might compel some Arab states to
become latent nuclear powers, potentially putting them months away from nuclear arsenals.
Scholarly understanding of nuclear proliferation has increased tremendously over the last
decade. Recent studies have examined why countries build nuclear weapons (e.g. Fuhrmann,
2009a, 2012a; Horowitz, 2010; Hymans, 2006; Miller, 2014; Solingen, 2007), and how nuclear
arsenals influence international conflict (e.g. Fuhrmann and Sechser, 2014; Gartzke and Jo,
2009; Narang, 2014) and crisis bargaining (e.g. Beardsley and Asal, 2009b; Sechser and
Fuhrmann, 2013). Other work analyzes the diffusion of nuclear power plants and related
dual-use technologies (e.g. Fuhrmann, 2008, 2009b, 2012b). Yet we still know surprisingly little
about nuclear latency in political science. As Scott Sagan (2010: 80) writes, nuclear latency
is ‘‘poorly understood’’ despite being ‘‘exceedingly important’’. We currently lack clear
answers to the most basic questions. How common is nuclear latency? Why do countries
develop latent nuclear capabilities? Why do some latent nuclear powers go on to build
nuclear weapons, while others are satisfied with just having the technological capacity to
make bombs? What are the political effects of nuclear latency?
Our understanding of these issues remains limited, in part, because of data unavailability.
Scholars have assembled numerous datasets that make it possible to conduct quantitative
analyses of nuclear politics. For example, we now have datasets on nuclear weapons programs
(Jo and Gartzke, 2007; Singh and Way, 2004), nuclear postures (Gartzke et al., 2014;
Narang, 2014), foreign nuclear deployments (Fuhrmann and Sechser, 2014), and nuclear
assistance (Fuhrmann, 2012a; Kroenig, 2009). Yet we do not yet have an off-the-shelf dataset
that provides a fully accurate picture of nuclear latency in international politics.1
This paper introduces a dataset designed to help scholars obtain a deeper appreciation of
nuclear latency. The Nuclear Latency (NL) dataset provides detailed information on the global
spread of latent nuclear capabilities from 1939 to 2012. The dataset focuses on the development
of enrichment and reprocessing (hereafter ENR) facilities. These nuclear plants
provide countries with the ability to produce fissile material—weapons-grade highly enriched
uranium or plutonium—and acquiring this material is the most difficult step in making
nuclear bombs.2
It is widely believed, therefore, that possessing ENR technology is the most
important feature of nuclear latency (e.g. Sagan, 2010). The NL dataset indicates that 31
countries developed latent nuclear capabilities over the last 70 years. Nuclear latency, is thus
three times more common than nuclear proliferation. In total, our dataset contains 241
ENR facilities built during the nuclear age. We provide information on the operational history,
size, and purpose (whether it served civilian or military functions) of each plant. The
dataset also reveals whether facilities were subjected to safeguards administered by the
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International Atomic Energy Agency (IAEA), and whether they were built covertly or with
foreign assistance.
Scholars could use the NL dataset to examine a host of questions related to the causes
and effects of nuclear latency. This paper provides one empirical application of the dataset,
showing how the study of nuclear latency can contribute to our understanding of international
conflict dynamics. We provide preliminary evidence that nuclear latency reduces the
likelihood of being targeted in militarized disputes. Having the capacity to build nuclear
weapons, therefore, may provide deterrence benefits that we usually associate with possessing
a nuclear arsenal. This finding has implications for the growing literature on the
deterrent effects of nuclear weapons (e.g. Beardsley and Asal, 2009a; Bell and Miller, 2014;
Gartzke and Jo, 2009; Horowitz, 2009; Narang, 2013, 2014; Sobek et al., 2012).3
We proceed in five main parts. First, we discuss existing attempts to measure nuclear
latency, and explain why a new approach is useful. Second, we describe the NL dataset in
greater detail. This section explains what information is contained in the dataset and how
we collected it. The third section discusses global trends in ENR development, drawing on
information contained in the NL dataset. Fourth, we present the empirical application of
the dataset. The final section concludes with a brief discussion of research areas on nuclear
latency.
Prior attempts to measure nuclear latency
Nuclear latency is frequently discussed in the literature on nuclear proliferation, but assessments
of how many countries possess latent nuclear capabilities vary widely. Frank Barnaby
(2004: 68) implies that any state with a civil nuclear program, which could include as many
as 69 countries, has nuclear latency. Jacques Hymans (2006) and Richard Stoll (1996) place
this figure in the high 40s. Mohamed ElBaradei, IAEA Director General from 1997 to 2009,
said in 2004 that there were fewer latent nuclear states: in his view, 40 countries were nuclear
weapons capable (see Sagan, 2010: 82). A lower estimate still comes from Stephen Meyer
(1984), who stated that 34 states were latent nuclear powers—but the data used to generate
this figure are now 30 years old.
These figures are all over the map, in part, because analysts use different metrics to define
nuclear latency. Political scientists typically code latency based on a series of technical and
industrial variables—but the metrics judged to be important often differ. Meyer’s (1984)
measure of nuclear latency is based on 10 variables: national mining activity, domestic uranium
reserves, metallurgists, steel production, construction work force, chemical engineers,
nitric acid production, electrical production capacity, nuclear engineers, physicists, chemists,
and explosive and electronics specialists. Stoll (1992) updated Meyer’s data, but excluded the
uranium requirement, leading to a sharp increase in the number of nuclear-capable states.
Dong-Joon Jo and Erik Gartzke (2007) further modified Meyer’s approach, dropping three
of the original indicators.4
Existing nuclear latency measures from political science have some key limitations (Sagan,
2010). The biggest shortcoming is that they do not account for a country’s ENR capabilities.
Meyer, Stoll and Jo/Gartzke use ‘‘surrogate indicators’’ for a state’s capacity to build ENR
plants—for example, whether a state has operated a research reactor for three or more
years—but they do not directly measure whether a country operates facilities capable of producing
plutonium or weapons-grade highly enriched uranium (see Meyer, 1984: 173–193).
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As a result, existing datasets provide useful proxies for a state’s latent nuclear weapons production
capability, but they do not necessarily allow us to distinguish states that could
assemble a nuclear bomb relatively quickly from other countries. Based on Jo and Gartzke’s
eight-point composite indicator, for instance, Columbia, Peru, Thailand and Venezuela had
the highest possible degree of nuclear latency in 2001. These countries operated research
reactors, but they did not possess more advanced nuclear facilities, like nuclear power plants,
nor did they have the human capital needed to construct bomb-related infrastructure indigenously.
To be sure, they lacked the capacity to make fissile material, the key ingredient for
producing atomic weapons. Most analysts, therefore, would not characterize countries such
as Colombia as having the latent capacity to produce nuclear weapons.
Nuclear assistance datasets, both the military and civilian varieties, usefully account for
the transfer of ENR technologies (Fuhrmann, 2012a; Kroenig, 2009). However, these datasets
only capture ENR capabilities acquired from foreign sources, excluding indigenously built
plants. Because many ENR plants are built without foreign aid, as we will discuss in a subsequent
section, nuclear assistance datasets provide an incomplete picture of nuclear latency.
In the technical literature (e.g. Mozley, 1998), an ENR capability is widely viewed as the
most important indicator of a state’s potential to build nuclear weapons. It is therefore not
surprising that research by nuclear engineers generally does a better job of accounting for a
state’s ability to produce fissile material. For example, Nelson and Sprecher (2010) define
nuclear latency based on whether non-nuclear weapons states have the ability to make
nuclear fuel in large-scale production plants. However, their definition excludes numerous
countries, like South Africa, that have the capacity to make fissile material for bombs on a
smaller scale. Only Argentina, Brazil, Canada, Japan, and the Netherlands satisfy Nelson
and Sprecher’s key criterion. Moreover, the Nelson and Sprecher measure provides a snapshot
of nuclear latency at a single point in time; it does not provide a sense of how patterns
of nuclear latency changed throughout the nuclear era. Zenter et al. (2005) identify states
that sought ENR capabilities in a study designed to examine how long it takes states to master
bomb-related technology. Yet their study does not provide complete details about the
number of ENR plants built by each country, nor does it supply important facility-specific
information, such as whether a plant was intended for civilian or military purposes or
whether it was under international safeguards.
The NL dataset addresses the limitations of existing datasets. Following the advice of
Sagan (2010, 2011), we measure nuclear latency based on states’ ENR capabilities, whether
they are acquired indigenously or from foreign sources. The dataset is also presented as a
time series, providing information about every state’s nuclear capabilities during 73 years of
the nuclear age. It gives details about each ENR plant, allowing researchers to identify latent
nuclear powers according to different criteria, based on the particular characteristics of a
state’s facilities. All of these improvements lead to a more accurate depiction of nuclear
latency in world politics.
Our approach: the Nuclear Latency dataset
The NL dataset identifies all ENR facilities built in the world from 1939 to 2012. All of the
plants in our dataset could, in theory, be used to produce fissile material for nuclear weapons.
We therefore classify every country in the NL dataset has having latent nuclear capabilities.
However, there is significant variation in the bomb-making capabilities of latent
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nuclear powers. Some countries—such as Russia and the USA—built more than a dozen
ENR facilities and produced enough fissile material to make tens of thousands of nuclear
weapons. Others—such as Algeria and Romania—acquired just one facility. We design the
NL dataset so that researchers can account for this variation when measuring nuclear
latency if they so desire. One could measure nuclear latency based on the presence of a single
ENR plant or the number of ENR facilities a country operates. Analysts could also code
latency based on certain facility traits. For instance, one might argue that Yugoslavia was
not really a latent nuclear power because its ENR plants could only produce small amounts
of plutonium on a laboratory scale. This concern is easy to address: analysts could simply
exclude Yugoslavia, and all other states that had only laboratory ENR capabilities, from
their measures of nuclear latency.
When describing the dataset and global trends in this paper, and when conducting the
empirical application, we take a broad approach to nuclear latency, assuming that any state
with at least one operational ENR plant has the capacity to build nuclear weapons. We
recognize, however, that some may view this as a fairly strong assumption. As we mention
later in the article, future research could extend our initial analysis to examine how varying
degrees of nuclear latency may influence international conflict dynamics.
Unit of observation and coding rules
The unit of observation in the dataset is the ENR facility: we compiled facility-specific information
on the operational history, size, and purpose of each plant constructed in the nuclear
age.5
Many countries possess multiple ENR facilities that vary in terms of their characteristics.
Our approach—as opposed to one that uses the country as the unit of observation—
allows us to capture this variation.
Our research strategy for identifying ENR plants consisted of three main steps. First, we
established which countries had the technical, financial, and political capacity to develop
ENR technology. We defined such countries as those that operated at least one research
reactor. This is a fairly low technological threshold: many developing countries, including
Jamaica, operate research reactors. Without a research reactor in operation, therefore, it is
exceedingly unlikely that a state would build ENR facilities. Yet if such a country managed
to do so, its ENR activity would not be included in the NL dataset. Second, for all 69 countries
that built a research reactor, we created ‘‘coding sheets’’ to record all of the relevant
information, including our sources.6
Third, we scoured the open-source record for information
on ENR development, focusing on one country at a time.
Finding verifiable information on each facility was not always an easy task owing to the
national security implications of ENR technology. We cannot be certain that our dataset
contains all ENR plants, since some facilities may remain covert. However, the media has a
fairly good track record of identifying previously covert facilities.7
If secret facilities remain,
they were most likely built in recent years by a state suspected of pursuing ENR technology
for military purposes. It is possible, for instance, that Iran has ENR plants under construction
or in operation that are not included in the NL dataset.
To identify ENR facilities, we consulted a variety of primary and secondary sources,
including trade journals such as Nuclear Fuel, Nucleonics Week, and Bulletin of the Atomic
Scientists. The IAEA’s Nuclear Fuel Cycle Information System was also a useful source,
although it excludes information on many ENR plants used for military purposes. In order
for a facility to be entered into the dataset, we required a minimum of two independent
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sources verifying its existence, although in most cases we identified five or more sources.8
When searching for ENR facilities, we were aware that absence of evidence is not necessarily
evidence of absence. We ruled out the possibility that a state developed ENR technologies if
we found evidence from at least five sources indicating that a state never pursued such facilities.
About half (38 of 69) of the countries on which we collected information fall into this
category.
A few additional points are worth clarifying. First, the NL dataset includes any ENR
facility on which construction started. A facility does not need to successfully operate in
order to be included. It turns out, however, that most facilities in the dataset are ultimately
finished.9
Second, countries may use multiple technologies at the same geographic location.
At Oak Ridge National Laboratory, where the uranium was produced for the Hiroshima
bomb, the USA operated both diffusion and electromagnetic isotope separation enrichment
facilities. We treat these plants as distinct. Another case in point is Russia’s Siberian
Chemical Combine, which began as a gaseous diffusion plant but was converted to a centrifuge
facility in the early 1970s. This one location constitutes two separate facilities in the NL
dataset. Identifying facilities based on technologies, instead of just location, provides a more
accurate measure of a state’s ENR capability. Third, if a state moves a facility, we code the
new location as a separate ENR plant. For example, in the early 2000s Iran moved its uranium
enrichment activities from the Kalaye Electric Company, located in Tehran, to
Natanz. These ENR plants represent distinct facilities in the NL dataset.
Variables
For each ENR plant in the NL dataset, we code the following variables:
 Construction and operation dates—the dataset identifies the years when construction
started and the duration of operation for each ENR facility.
 Facility size—ENR facilities can vary greatly in terms of their size and scope. The
dataset classifies each facility into one of three categories, based on the classification
scheme used by the IAEA: laboratory, pilot and commercial.10
Commercial technologies
are used on an industrial scale, while pilot plants usually precede extensive enrichment
or reprocessing. Laboratory facilities, the smallest of the three, are typically
intended to demonstrate the feasibility of a technology.
 Facility type—the dataset identifies whether a facility employed reprocessing or
enrichment technology. In the case of enrichment plants, it indicates the method used
to increase the concentration of U-235 relative to U-238. The main enrichment methods
can be grouped into several categories: (1) diffusion, (2) centrifugation, (3) electromagnetic
isotope separation, (4) laser, (5) aerodynamic, (6) chemical and ion
exchange, and (7) pyrometallurgical.11
 Military applications—we identify whether an ENR facility was part of a military
complex. The dataset codes facilities as serving a military purpose if at least one of the
following conditions are met: (1) primary or secondary sources explicitly indicate that
a plant was part of a nuclear weapons program; (2) a plant produced, or was intended
to produce, fissile material for nuclear bombs; or (3) the military was involved in the
construction or operation of a plant.12
Some facilities serve weapon-related functions
throughout their lifespans, while others shift between military and civilian
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applications over time. ENR technologies can also serve both functions simultaneously,
as in the case of some French plants.
 Covert—some ENR plants are initially constructed in secret, while the existence of
others is publicly known from the beginning. The dataset identifies whether work on
a plant began covertly. We code facilities as covert if a facility existed unbeknownst
to the international community, based on open-source records. A facility is coded 1 if
built in secret and 0 otherwise.
 Safeguards—we identify whether a facility is under IAEA or regional safeguards. We
code IAEA safeguards based on the Agency’s list of safeguarded facilities. Note, however,
that some facilities on this list are not actually inspected. For example, owing to
budget constraints, the IAEA does not typically conduct on-site inspections of US
ENR plants. There are two regional safeguard agreements included in our dataset:
the European Atomic Energy Community (Euratom) and the Brazilian–Argentine
Agency for Accounting and Control of Nuclear Materials (ABACC).13
These two
agreements cover all non-military facilities in the respective countries. Both IAEA
and regional safeguards can apply to inactive sites; facilities can go offline and continue
to be under safeguards.
 Foreign assistance—the dataset indicates whether a facility was built with foreign
assistance.14
Foreign assistance is the state-sanctioned transfer of key components or
technology necessary for the design, construction, or operation of an ENR facility.
Pakistan’s transfer of centrifuge components to Iran through the A.Q. Khan network,
for example, represents one high-profile example of foreign ENR assistance. We
exclude transfers that are not supported by the state. For example, a private firm’s
sale of ENR-related equipment without authorization from the government would
not count as foreign assistance, according to our definition. This variable also does
not capture transfers of nuclear materials; providing uranium that is eventually used
in a centrifuge plant would not be classified as foreign assistance.
 Multinational—we indicate whether a facility is multinational, that is, owned by more
than one country or a conglomerate. Urenco, a nuclear fuel supply company owned
by the British and Dutch governments and German utilities, operates the most wellknown
multinational ENR plants.
Global trends in ENR development
The NL dataset contains 241 ENR facilities built from 1939 to 2012. Figure 1 illustrates the
frequency of ENR development over time. The number of ENR plants in operation
increased steadily throughout the Cold War. However, the collapse of the Soviet Union led
to a sharp decrease in the number of plants, as Moscow and Washington dismantled a large
portion of their nuclear weapons-related infrastructures. The number of states with ENR
capabilities followed a similar, albeit less dramatic, trend: since the early 1970s, the number
of ENR states has been relatively constant. The peak year for global ENR development was
1987, when 22 countries operated a total of 99 plants globally.
Table 1 lists the countries that built at least one ENR facility, along with the years that a
plant operated. As the table shows, our dataset indicates that 31 countries were ENR-capable
during the nuclear age.15
When measuring nuclear latency based on an ENR capability,
therefore, there are fewer latent nuclear powers than prior efforts would lead us to believe
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(Barnaby, 2004; Hymans, 2006; Jo and Gartzke, 2007; Stoll, 1996). Still, as noted previously,
ENR development is three times more common than nuclear proliferation. The list of ENR
states is remarkably diverse: it contains countries from six continents; democracies and
authoritarian regimes; wealthy states and relatively poor ones; US allies and US enemies;
‘‘rogue’’ regimes and champions of international norms.
All ENR states do not possess the same degree of nuclear latency. ENR capabilities vary
based on the number of plants a state possesses and the size of those facilities. As shown in
Figure 2, some countries—namely, China, France, India, Iran, Russia, the UK, and the
USA—built 10 or more ENR plants. Fifty percent of all ENR countries, however, built five
or fewer plants, and six states—about 19% of all ENR countries—built just one facility.
The number of ENR plants, however, does not always correlate with a state’s capacity to
produce plutonium or highly enriched uranium. It is theoretically possible—depending on
the size of a facility—for a country to produce enough fissile material for a modestly sized
nuclear arsenal with a small number of plants.
In terms of size, laboratory facilities are the most common (40%), followed by commercial
(30%), and pilot plants (30%). States that operate commercial ENR facilities—such as
Brazil, Japan and the Netherlands—generally have the potential to produce the most fissile
material, all else being equal. Yet, as the cases of Israel and North Korea indicate, countries
do not need commercial ENR plants to produce sufficient fissile material for nuclear bombs.
Laboratory facilities, from a nonproliferation standpoint, can be a major concern. Officials
in the USA and elsewhere, for instance, worried about Italy’s sale of a laboratory-scale
reprocessing facility to Iraq in the late 1970s, arguing that it would allow Saddam Hussein
to make nuclear weapons.
Figure 1. Number of ENR facilities and ENR countries over time.
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ENR facilities also vary in their purpose. Roughly 40% of plants served exclusively civilian
purposes—usually making fuel for nuclear reactors—while the other 60% had military
applications. Twenty-two states developed ENR for military purposes, meaning that 71% of
all countries that built enrichment or reprocessing plants did so, at least in part, to have a
bomb-making capacity. Some countries, like Japan, may have developed ENR to keep the
bomb option open, a strategy known as ‘‘nuclear hedging’’ (Levite, 2002/2003). However,
these cases are not classified as military because ENR development was not part of an
ongoing nuclear weapons program. Not surprisingly, Russia and the USA built far more
military ENR plants than other states. Those two countries together accounted for nearly
40% of all military ENR development.
Some facilities are initially built in secret, as we noted above. Sixty-eight percent of the
countries that built at least one ENR facility (21 of 31) constructed a covert plant. All of the
states that pursued an ENR capability secretly arguably had dedicated nuclear weapons programs,
although the degree to which some of these countries wanted the bomb is still
Table 1. Countries with ENR facilities, 1939–2012
Country ENR plant operation years
Algeria 1992–2012
Argentina 1968–1973, 1983–1989, 1993–1994
Australia 1972–1983, 1992–2007
Belgium 1966–1974
Brazil 1979–2012
Canada 1944–1976, 1990–1993
China 1960–2012
Czech Republic (Czechoslovakia) 1977–1998
Egypt 1982–2012
France 1949–2012
Germany (West Germany) 1964–2012
India 1964–1973, 1977–2012
Iran 1974–1979, 1985–2012
Iraq 1983–1991
Israel 1963–2012
Italy 1966–1990
Japan 1968–2012
Libya 1982–2003
The Netherlands 1973–2012
North Korea 1975–1993, 2003–2012
Norway 1961–1968
Pakistan 1973–2012
Romania 1985–1989
Russia (Soviet Union) 1941–2012
South Africa 1967–2012
South Korea 1979–1982, 1997–2012
Sweden 1954–1972
Taiwan 1976–1978
UK 1952–2012
USA 1941–2012
Yugoslavia 1954–1978
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debated. Facilities that serve exclusively civilian purposes—such as those in the
Netherlands—tend to be overt from the beginning.
The number of plants under IAEA safeguards has steadily increased since 1970, when the
nuclear Nonproliferation Treaty entered into force. The percentage of safeguarded plants
remained low from 1970 to 1990, but IAEA safeguards were relatively more common after
the Cold War, owing to the closure of several unsafeguarded ENR plants. At the end of
2012, about 50% of all ENR facilities globally were under international safeguards.
Foreign assistance in building ENR facilities is fairly common: 70 plants were constructed
with some foreign aid. Twenty-seven countries built at least one ENR facility with foreign
nuclear assistance, indicating that about 85% of all latent nuclear powers received some
external aid.16
Joint ownership is another potential way in which international collaboration
in ENR development can occur. Yet relatively few ENR plants in the NL dataset are owned
by more than one country. Multinational ventures are largely a European endeavor: 16 of
the 20 ENR plants under joint ownership are either based in Europe or operated by
Urenco.17
Empirical application: nuclear latency and international conflict
This section provides an empirical application of the NL dataset. We analyze the relationship
between nuclear latency and international conflict. Does nuclear latency influence the
likelihood of being targeted in military disputes? As we noted earlier in the paper, an emerging
wisdom suggests that nuclear latency deters international conflict. It is also possible,
however, that latency increases the risk that states will be targeted in disputes. We conduct
Figure 2. Number of ENR facilities by country.
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some preliminary analysis to determine if latent nuclear capabilities have any effect on deterring
military conflict. Before doing so, we further develop two competing arguments on the
deterrent effects of nuclear latency.
Theoretical expectations
There is a voluminous literature on the political effects of nuclear weapons. Much of the
research in this vein focuses on the bomb’s utility for deterrence.18
A prominent argument
holds that nuclear weapons reduce the risk of conflict, especially major war (e.g. Jervis,
1989; Waltz, 1981). The reason is simple: countries that possess atomic weapons can threaten
nuclear escalation if they are attacked. The possibility of nuclear use dramatically increases
the costs of war and thus makes conflict less likely.19
Could nuclear latency provide states with similar deterrence benefits? If so, why might
that be the case?
The existing literature is mostly silent on these questions. However, it is plausible that
nuclear latency reduces the likelihood of military conflict (e.g. Horowitz, 2013; Levite, 2002/
2003). Latency may allow states to pursue what T.V. Paul (2000: 59) calls a ‘‘virtual deterrence
strategy’’. Latent nuclear powers could not launch an immediate nuclear strike following
an attack, but they could potentially assemble a rudimentary nuclear arsenal in short
order. If a dispute persists for an extended duration, then the nuclear option could be on the
table. Based on this line of thinking, the prospect of nuclear punishment could deter potential
aggressors even if the target does not possess a nuclear arsenal at the onset of a dispute.20
Nuclear latency may provide deterrence benefits even if there is little chance of nuclear use
in the short term. A state with latency may decide, following an episode of military conflict,
that it needs an arsenal of atomic weapons to ward off threats that could emerge in the
future. Potential attackers presumably understand that latent nuclear powers could build
nuclear bombs relatively quickly if their security environment deteriorates. Given that states
generally want to avoid fomenting the spread of nuclear weapons, they may think twice
before initiating military disputes against states with nuclear latency. Thus, latent nuclear
powers may be able to deter conflict by (implicitly) threatening to ‘‘go nuclear’’ following an
attack. To illustrate, imagine that Potential Attacker and Latent Nuclear Power are in the
midst of a political disagreement. Potential Attacker has incentives to avoid actions that leave
Latent Nuclear Power feeling highly threatened. Attacking Latent Nuclear Power could push
that country to weaponize its nuclear program, thereby undermining Potential Attacker’s
security. Potential Attacker therefore might try harder than it otherwise would if it were dealing
with a state that lacked nuclear latency to peacefully resolve its dispute with Latent
Nuclear Power. This leads to the following hypothesis:
Hypothesis 1: Having nuclear latency reduces the likelihood of being targeted in a militarized interstate
dispute.
Nuclear latency may also breed insecurity. Others might perceive a state’s development of
advanced nuclear capabilities as a signal that it intends to build nuclear weapons. If states
come to believe that nuclear proliferation will occur in the absence of external intervention,
they might use preventive military force to forestall a large shift in the balance of power
(Debs and Monteiro, 2014). For example, Israel bombed Iraq (1981) and Syria (2007) to
eliminate facilities that could have been used to build nuclear bombs (Fuhrmann and Kreps,
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2010; Reiter, 2006). Even if states do not believe that nuclear proliferation is imminent, they
may worry that their nuclear-capable rivals will eventually build nuclear weapons. In that
case, putting pressure on the latent nuclear power—by issuing military threats, displaying
force, or launching attacks—may be preferable to more peaceful strategies. Having nuclear
latency, therefore, may actually make a state more susceptible to military conflict.
Hypothesis 1A: Having nuclear latency increases the likelihood of being targeted in a militarized
interstate dispute.
It is also possible, of course, that nuclear latency has nothing to do with international conflict.
We will test the above predictions against the null hypothesis that there is no relationship
between these two phenomena.
Empirical analysis and findings
To test the above hypotheses, we build on an existing study that examines the relationship
between nuclear weapons and military conflict (Gartzke and Jo, 2009). We follow Gartzke
and Jo’s (2009) empirical procedures, adding latency-related variables to their model as
appropriate. Mirroring their approach, we use a standard time-series cross-sectional dataset
that covers the period from 1945 to 2000. The unit of observation is the directed-dyad-year,
which allows us to distinguish between challengers and targets of military disputes. The
dependent variable comes from the Correlates of War Militarized Interstate Dispute dataset
(Ghosn et al., 2004). MID Initiation is coded 1 if the potential challenger initiates a militarized
dispute against the target and 0 otherwise.21
The independent variables from Gartzke
and Jo’s (2009) model, all of which are included in our analysis, are described in the
Appendix.
Our primary independent variable of interest (Nuclear Latency B) measures whether the
potential target in a militarized dispute has latent nuclear capabilities in a given year. This
variable is coded 1 if the target has nuclear latency and 0 otherwise; nuclear powers are coded
0 beginning in the first year that they assemble an arsenal. We operationalize latency based
on a lenient criterion: any non-nuclear weapons state that has an ENR plant in operation is
classified as a latent nuclear power. Future research could extend our study to examine how
different degrees of latency influence international conflict dynamics.
Our analysis also accounts for the latency status of the challenger with the variable
Nuclear Latency A. Some have argued that nuclear weapons make countries more aggressive
(Kapur, 2007), while others posit that having an atomic arsenal induces caution (Waltz,
1981). Nuclear latency might similarly embolden states to take greater risks or, alternatively,
encourage self-restraint when it comes to dispute initiation.
Table 2 displays the results of probit regressions with standard errors clustered by directed
dyad. Model 1 is a replication of Gartzke and Jo’s (2009: 220) model.22
Our findings confirm
their results. Model 2 adds the variables Nuclear Latency A and Nuclear Latency B. The coefficient
on Nuclear Latency B is negative and statistically significant, indicating that nuclear
latency is associated with a lower risk of being targeted in military disputes. This relationship
is substantively meaningful: increasing Nuclear Latency B from 0 to 1 while holding all other
variables constant at their mean values reduces the probability of experiencing a dispute by
nearly 40%.
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Some states with ENR facilities actively pursued nuclear weapons (e.g. Iraq prior to the
1991 Persian Gulf War). Other latent nuclear powers have yet to show serious interest in
nuclear bombs (e.g. the Netherlands). It is worthwhile to distinguish the effects of nuclear
latency from the presence of a nuclear weapons program. To do so, model 3 adds variables
that measure whether the challenger and target have active bomb programs (Nuclear
Weapons Pursuit A and Nuclear Weapons Pursuit B).23
Nuclear Latency B remains negative
and statistically significant, suggesting that nuclear weapons programs do not drive our initial
findings. Nuclear latency appears to provide states with deterrence-related benefits that
are distinct from actively pursuing nuclear bombs. By contrast, the target’s pursuit of
nuclear weapons is statistically unrelated to conflict. Bomb programs therefore do not
appear to suppress military disputes independently from nuclear latency.
These results support Hypothesis 1, but they do not necessarily imply that nuclear latency
is always a source of peace. Although latency reduces the risk of being targeted in disputes,
it may increase the likelihood of conflict initiation. The coefficient on Nuclear Latency A is
statistically significant and positive in model 2. Based on the estimates from model 2, challengers
with nuclear latency are 77% more likely to initiate disputes than challengers without
latency. However, the statistical significance of Nuclear Latency A washes away once we
account for the challenger’s pursuit of nuclear weapons (model 3). We therefore do not find
robust evidence of a relationship between a challenger’s nuclear latency and international
conflict. Bomb programs themselves, though, are associated with an increased risk of dispute
initiation, as indicated by the coefficient on Nuclear Weapons Pursuit A.
In terms of the other variables, Gartzke and Jo’s (2009) initial findings are stable across
models 1–3. Accounting for nuclear latency and nuclear weapons programs, therefore, does
not overturn their main results. Variables that were statistically significant in their model
continue to be significant in our models; those that were insignificant remain so.
Our findings are far from definitive. They do suggest, however, that there may be a relationship
between nuclear latency and international conflict. This relationship has been underappreciated
in the conflict literature to date, and it is worthy of further scholarly examination.
Conclusion
Scholars and policy-makers have long recognized that nuclear latency is important. The current
Iranian nuclear crisis, for example, underscores the significance of nuclear latency for
international conflict and nuclear proliferation. Yet political scientists have yet to devote
much attention to the causes and political effects of nuclear latency. This paper introduced a
new dataset that provides a comprehensive measure of nuclear latency, based on the diffusion
of ENR capabilities. It discussed the features of the dataset, identified key trends, and
provided an illustration of the type of analysis that one could conduct using these data. We
presented initial evidence that nuclear latency is associated with a reduced risk of being targeted
in military disputes. Thus, having the capacity to build nuclear weapons, like possessing
an atomic arsenal, may bolster deterrence.
This paper raises a number of topics for future research on nuclear latency. First, it would
be fruitful to further explore the deterrent effects of nuclear latency. Knowing more about
why latency appears to reduce the risk of being targeted in military disputes would be especially
useful. We conjectured that latency provides a valuable deterrent because states can
threaten to ‘‘go nuclear’’ if they are attacked. However, nuclear latency could be associated
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Table 2. Probit analysis of militarized conflict
(1) (2) (3)
Gartzke and Jo (2009) Latency added Pursuit added
Nuclear Latency A 0.151**
0.072
(0.049) (0.053)
Nuclear Latency B 20.133**
20.148**
(0.044) (0.052)
Nuclear Weapons Pursuit A 0.182**
(0.061)
Nuclear Weapons Pursuit B 0.040
(0.068)
Nuclear Weapons A 0.260**
0.316**
0.333**
(0.070) (0.071) (0.069)
Nuclear Weapons B 20.001 20.053 20.049
(0.077) (0.082) (0.082)
Nuke A 3 Nuke B 20.212 20.210 20.204
(0.135) (0.136) (0.138)
Democracy A 0.023**
0.020**
0.021**
(0.006) (0.006) (0.006)
Democracy B 0.041**
0.043**
0.043**
(0.006) (0.006) (0.006)
Democracy A 3 Democracy B 20.005**
20.005**
20.005**
(0.001) (0.001) (0.001)
Rivalry Status A 0.293**
0.286**
0.277**
(0.032) (0.032) (0.031)
Rivalry Status B 0.157**
0.162**
0.160**
(0.030) (0.030) (0.030)
Dyadic Rivalry 1.113**
1.116**
1.109**
(0.051) (0.051) (0.051)
Contiguity 20.137**
20.137**
20.139**
(0.044) (0.044) (0.044)
Distance (ln) 20.050y
20.050y
20.049y
(0.026) (0.026) (0.026)
Alliance 0.043 0.044 0.045
(0.040) (0.040) (0.040)
CINC A 0.778 0.398 0.265
(0.707) (0.724) (0.708)
CINC B 1.589y
1.972*
1.923*
(0.829) (0.864) (0.862)
CINC A 3 CINC B 0.207 0.064 0.395
(15.833) (16.132) (16.164)
Peace Years 20.062**
20.061**
20.061**
(0.008) (0.008) (0.008)
Spline 1 20.000**
20.000**
20.000**
(0.000) (0.000) (0.000)
Spline 2 0.000**
0.000**
0.000**
(0.000) (0.000) (0.000)
Spline 3 0.000 0.000 0.000
(0.000) (0.000) (0.000)
Constant 22.308**
22.314**
22.315**
(0.081) (0.080) (0.080)
N 1,051,218 1,051,218 1,051,218
Notes: Standard errors in parentheses; y
p \ 0.10, *
p \ 0.05, **
p \ 0.01, two-tailed tests.
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with international conflict for other reasons. More theorizing about this relationship, combined
with qualitative analysis of key cases, might illuminate other causal mechanisms.
Related to this, future empirical work might assess whether nuclear latency causes, or is
merely associated with, a reduced risk of international conflict. We have shown that there is
a correlation between these two variables, but more work is needed to understand whether
this is a causal relationship.24
Second, our preliminary analysis provided some evidence that states with nuclear latency
are more likely to initiate disputes. But we do not yet understand why this might be the case.
A rich literature focuses on how nuclear weapons influence the likelihood that states will
instigate conflict. Scholars might build on this research to explore the possible emboldening
(or restraining) effects of nuclear latency.
Third, it would also be worthwhile to explore the variety of other ways in which latency
might influence world politics. Does the capacity to build nuclear weapons, for instance, provide
states with greater coercive bargaining leverage? Many have argued that nuclear weapons
increase states’ bargaining power in crises, allowing them to extract concessions with
greater ease (e.g. Beardsley and Asal, 2009b). Others question whether the bomb has political
value beyond deterrence (e.g. Sechser and Fuhrmann, 2013). Future work could contribute
to this ongoing debate by exploring the coercive effects of nuclear latency. Important
research along these lines is already underway (Volpe, 2013), but we do not yet fully understand
how and why nuclear latency might carry political leverage.
Finally, the study of nuclear latency is relevant for scholarship on the causes of nuclear
proliferation. The decision to obtain latent nuclear capabilities is a key part of the proliferation
process. Indeed, as we noted throughout this article, no country can build nuclear
bombs without first acquiring the requisite nuclear technology. Analyzing why states obtain
latent nuclear capabilities, then, could help us more fully appreciate the demand for nuclear
weapons in world politics.25
There is also a methodological reason to account for latency in
research on how and why nuclear weapons spread: three times as many states developed
latent nuclear capabilities as built nuclear weapons. This provides greater variation to exploit
in the dependent variable, just as studying less severe but more frequent episodes of international
conflict may give us additional insights into the causes of war.
Funding
This research is part of the ‘‘Correlates of Sensitive Technologies’’ project, funded by the USA
Department of Energy, Nuclear Energy University Programs (NEUP 3149). We thank Paul Nelson,
Garill Coles, and Valerie Lewis, our collaborators on the COST project, as well as William Boettcher,
Jeff Colgan, Bryan Early, Erik Gartzke, Llewelyn Hughes, Mark Nance, Glenn Palmer, Robert
Reardon, Adam Stulberg, participants in the International Studies Association workshop ‘‘A New
Security Dilemma? Politics and Policy at the Energy-Security Nexus’’, and anonymous reviewers for
helpful feedback on this paper. Molly Berkemeier, Miguel Contreras, and Josiah Barrett provided
helpful research assistance.
Notes
1. Scholars have devoted some attention to the measurement of nuclear latency, but existing datasets
have some limitations, which we address later in the paper.
2. ENR facilities also have a civilian application: making fuel for nuclear power plants or research
reactors.
3. For seminal earlier work on this issue see Jervis (1989) and Sagan and Waltz (2002).
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4. Jo and Gartzke exclude construction workforce, steel production, and national mining activity.
5. There must be an attempt to enrich uranium or separate plutonium at a facility for it to be
included in our dataset. Plants that manufacture ENR components are excluded, unless uranium
is enriched or plutonium is reprocessed at those sites. A testing facility that spins centrifuges without
introducing uranium hexafluoride, for instance, would not count as an ENR plant.
6. The coding sheets will be made publicly available on publication of this article at http://
www.matthewfuhrmann.com.
7. The NL dataset contains more than 100 ENR plants that were initially built in secret.
8. Two sources are considered independent when they rely on unique information to substantiate
claims about ENR facilities. To illustrate, consider a stylized example. Source A asserts that an
enrichment plant exists in North Korea. Source B makes a similar claim, and substantiates this
on the basis of Source A only. Source C also provides evidence of an enrichment facility, based
on Source D. Based on our criterion, Source A and Source C are independent but Source A and
Source B are not.
9. Only 20 of the 241 (8%) facilities fail to become operational. Note that some of these facilities will
probably begin operating in the future while construction on others has permanently ceased.
10. We followed the IAEA’s Nuclear Fuel Cycle Information System guidelines for coding facility
capacity.
11. There are distinct reprocessing techniques (e.g. PUREX, Thorex, and bismuth phosphate), but the
dataset does not distinguish between them.
12. In theory, the third condition could be met even if a plant was not part of a nuclear weapons program.
For example, the military could be involved in an ENR plant that was intended to produce
fuel for nuclear submarines. In practice, however, most military-supported facilities are part of a
nuclear weapons program.
13. Euratom was founded in 1952 and ABACC emerged in 1991 with the signing of the Guadaljara
Agreement for the Exclusively Peaceful Use of Nuclear Energy.
14. In some instances, sources indicate that a foreign country helped to build an ENR plant without
providing the name of the facility. In those cases, we conducted further research to determine
which facilities were built with foreign assistance.
15. This number is greater than the maximum number of ENR states depicted in Figure 1 because all
of the states listed in Table 1 did not possess latent nuclear capabilities at the same time.
16. Kroenig’s (2009) dataset on sensitive nuclear assistance indicates that 12 countries received ENR
assistance. We identify more cases of foreign aid, in part, because of differences in coding rules.
In particular, Kroenig excludes ENR-related assistance to states with the indigenous capacity to
construct facilities on their own. For example, he excludes French assistance in constructing a
Japanese commercial reprocessing plant in the 2000s (he includes earlier French assistance to
Japan for a pilot plant in the 1970s). In contrast, we include all ENR transfers, regardless of the
recipient’s domestic capabilities.
17. In most of these cases, facilities were multinational from the beginning. However, in two
instances—Russia’s Angarsk Electrochemical and Norway’s Kjeller Pilot Uranium Plant—joint
ownership occurred after the start of facility operation.
18. The compellent effects of nuclear weapons are more controversial (e.g. Beardsley and Asal, 2009b;
Gartzke and Jo, 2009; Sechser and Fuhrmann, 2013).
19. Empirical support for this argument remains mixed (e.g. Bell and Miller, 2014; Fuhrmann and
Sechser, 2014; Gartzke and Jo, 2009; Huth and Russett, 1984; Narang, 2014; Rauchhaus, 2009).
20. This logic is most applicable to highly industrialized states with the most advanced civilian nuclear
capabilities, like Germany and Japan (Paul, 2000: 59).
21. Gartzke and Jo (2009) measure this variable in year t þ 1.
22. When examining the relationship between nuclear weapons and international conflict, it is important
to control for the dispute history in a dyad (Bell and Miller, 2014). We added a variable measuring
the number of prior disputes two countries experienced, and the main findings were similar.
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23. These variables are coded based on Jo and Gartzke (2007).
24. On the challenges associated with making causal inferences using observational data, see, for
example Imai et al. (2011).
25. This is particularly true since countries may ‘‘hedge’’ when they have an interest in building
nuclear bombs—that is, states might develop latent nuclear capabilities but refrain from taking
the final step towards weaponization, knowing that they could do so quickly in the event of a crisis.
Yet it is also possible that fears of nuclear hedging are overblown and that states develop
advanced nuclear technologies for reasons that have little to do with augmenting military power.
Scholars could assess this possibility by systematically analyzing the causes of nuclear latency.
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Appendix
This Appendix briefly describes the independent variables in Gartzke and Jo’s (2009) model
of international conflict. For further details, see Gartzke and Jo (2009: 218–220).
 Nuclear Weapons A. A dichotomous variable indicating whether the challenger possesses
a nuclear arsenal.
 Nuclear Weapons B. A dichotomous variable indicating whether the target possesses a
nuclear arsenal.
 Nuke A 3 Nuke B. An multiplicative interaction between Nuclear Weapons A and
Nuclear Weapons B.
 Democracy A. A measure of the challenger’s level of democracy based on an 11-point
scale, ranging from 0 to 10.
 Democracy B. A measure of the target’s level of democracy based on an 11-point scale,
ranging from 0 to 10.
 Democracy A 3 Democracy B. A multiplicative interaction term between Democracy
A and Democracy B.
 Rivalry Status A. A dichotomous variable indicating whether the challenger is party to
at least one interstate rivalry.
 Rivalry Status B. A dichotomous variable indicating whether the target is party to at
least one interstate rivalry.
 Dyadic Rivalry. A dichotomous variable indicating whether the challenger and the target
are rivals.
 Contiguity. The geographic proximity between the challenger and the target based on
a six-point scale.
 Distance (LN). The logged great circle distance between the capital cities of the challenger
and the target.
 Alliance. A dummy variable indicating whether the challenger and the target are military
allies.
 CINC A. The challenger’s military power based on the Correlates of War Composite
Indicator of National Capabilities (CINC) index.
 CINC B. The target’s military power based on the CINC index.
 CINC A 3 CINC B. A multiplicative interaction term between CINC A and CINC B.
 Peace Years, Spline 1, Spline 2 and Spline 3. Standard controls for time dependence
recommended by Beck et al. (1998).
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