Queens∗
Oeindrila Dube†

S.P. Harish‡

March 2017

Abstract
Are states led by women less prone to conflict than states led by men? We answer thisquestion by examining the effect of female rule on war among European polities over the
15th-20th centuries. We utilize gender of the first born and presence of a female sibling
among previous monarchs as instruments for queenly rule. We find that polities led byqueens were more likely to engage in war than polities led by kings. Moreover, the tendency of queens to engage as aggressors varied by marital status. Among unmarriedmonarchs, queens were more likely to be attacked than kings. Among married monarchs, queens were more likely to participate as attackers than kings, and, more likely tofight alongside allies. These results are consistent with an account in which marriages
strengthened queenly reigns because married queens were more likely to secure alliancesand enlist their spouses to help them rule. Married kings, in contrast, were less inclined
to utilize a similar division of labor. These asymmetries, which reflected prevailing gender norms, ultimately enabled queens to pursue more aggressive war policies.

JEL Classification Codes: N43, D74, H56, F51, J16, J20∗ First draft: April 1, 2015.

We are grateful to Michael Eisner for sharing data on regicides with us. We
would also like to thank Guido Alfani, Katherine Casey, Latika Chaudhury, Mark Dincecco, Francesco Drago,
Arindrajit Dube, James Fearon, Thiemo Fetzer, Andrej Kokkonen, Stelios Michaelopoulos, William Monter,
Sendhil Mullainathan, Aprajit Mahajan, Rohini Pande, Debraj Ray, Frances Rosenbluth, Jake Shapiro, Alastair
Smith, Joachim Voth and Austin Wright, as well as participants from seminars and conferences at Harvard,
Stanford, Paris School of Economics, Vancouver School of Economics, Yale, CUNY, Berkeley, University of
Chicago, New York University, Bocconi, EEA-2016, APSA-2015, MPSA-2015, and Barcelona-GSE Summer Forum 2015, for many helpful comments and suggestions. Michael Xu and Oliver Xie provided excellent research
assistance.
† Professor, University of Chicago. odube@uchicago.edu.
‡ Post-doctoral Fellow, McGill University. harishsp@gmail.com.

1

Introduction

Does female leadership lead to greater peace? On the one hand, it is commonly argued thatwomen are less violent than men, and therefore, states led by women will be less prone
to violent conflict than states led by men. For example, men have been held to “plan almost all the world’s wars and genocides [Pinker, 2011, p.684]”, and the democratic peace
among the developed nations has been attributed to rising female leadership in these places[Fukuyama, 1998]. On the other hand, differences in individual aggression may not determine differences in leader aggression. Female leaders, like any other leader, ultimately haveto consider how war affects their state as a whole. And, setting overly conciliatory war policies would weaken their state relative to other states. As a consequence, war policies set byfemale leaders may be similar to war policies set by male leaders.1
A state’s aggression in the foreign policy arena, and its decision to go to war, is arguably
one of the most consequential policy outcomes, and one in which the national leadershipplays a critical role. Despite its importance, there is little definitive evidence of whether
states vary in their tendency to engage in conflict under female versus male leadership.
This stands in contrast to other arenas such as economic development, where a growing
body of evidence has documented policy differences arising as a consequence of female
leadership [Chattopadhyay and Duflo, 2004, Beaman et al., 2012, Clots-Figueras, 2012, Brollo
and Troiano, 2016]. The existing studies that do relate female leadership to external conflict
focus exclusively on the modern era [Koch and Fulton, 2011, Caprioli, 2000, Caprioli andBoyer, 2001, Regan and Paskeviciute, 2003], and are also difficult to interpret since women
may gain electoral support and come to power disproportionately during periods of peace[Lawless, 2004].
In this paper, we examine how female leadership affected war among European states
historically, exploiting features of hereditary succession to surmount this identification chal1 Some scholars have suggested that female leaders such as Indira Gandhi or Margaret Thatcher, who readily

used military force to achieve their policy objectives, may have done so as a form of “male posturing,” since
they operated in a context where most states were led by men [Ehrenreich and Pollitt, 1999].

1

lenge. We focus on the 15th-20th centuries and polities that had at least one female ruler during this period. As with electoral systems, women in hereditary systems may have gained
power more during times of peace, or when there was no threat of imminent war [Pinker,
2011]. However the way in which succession occurred also provides an opportunity to identify the effect of female rule. In these polities, older male children of reigning monarchs were
given priority in succession [Monter, 2012, p. 36-37]. As a result, queens were less likely tocome to power if the previous monarchs had a first-born child who was male; and, more
likely to come to power if previous monarchs had a sister who could potentially follow as
successor. We use these two factors as instruments for queenly rule to determine whether
polities led by queens differed in their war participation relative to polities led by kings.
Importantly, our paper analyzes the question of whether states led by women are lessprone to engage in conflict than states led by men. This is conceptually distinct from thequestion of whether women, as individuals, are less violent than men,2 in part because war
policies are set by leaders based on broader strategic considerations beyond personal inclinations toward violence.
To conduct our analysis, we construct a new panel dataset which tracks the genealogy
and conflict participation of European polities during every year over 1480-1913. Our primary sample covers 193 reigns in 18 polities, with queens ruling in 18% of these reigns.
We include polity fixed effects, holding constant time invariant features of a polity that affect conflict, and exploit variation over time in the gender of the ruler. Using the first born
male and sister instruments, we find that polities ruled by queens were 27% more likely toparticipate in inter-state conflicts, compared to polities ruled by kings. These estimates are
economically important, representing a doubling over mean war participation over this period. In contrast, we find that queens were no more likely to experience civil wars or othertypes of internal instability.
An obvious concern with our IV analysis is that the lack of a first-born child who is male
2 While this is not the focus of our analysis, there is a large literature around this question, for example,

McDermott et al. [2009], Schacht et al. [2014].

2

may itself trigger conflicts over succession, regardless of whether a woman comes to power.
However, we conduct a number of falsification tests which show that the a first-born son
does not affect war participation in the contemporaneous reign, or in an auxiliary sample of
18 polities that never had queens over this period. Thus, if there are other ways in which
first born males affect conflict, they do not manifest under these circumstances.
A second concern is that the presence of a sister among previous monarchs (an aunt, fromthe stand-point of the current period monarch) may be correlated with the presence of othersiblings (i.e., other aunts and uncles) who may also have fought for the throne. However,
we are able to control for all of the total siblings of the previous monarchs and show thatthe results are unaffected if we remove wars of succession from the sample. Importantly,
we demonstrate that the results are insensitive to dropping any particular queen, and any
particular polity. In addition, we show the robustness of our results to numerous othercontrols and specifications, including a reign level specification which collapses the annual
data to the reign level, as well as a dyadic specification.
We examine two potential accounts of why female ruler may have increased war participation. The first account suggests that queens may have been perceived as easy targets ofattack. This perception—accurate or not—could have led queens to participate more in wars
as a consequence of getting attacked by others.
The second account builds on the importance of state capacity. During this period,
states fought wars were primarily with the aim of expanding territory and economic power[Mearsheimer, 2001, Goertz and Diehl, 2002, Copeland, 2015]. Wars of this nature demandedfinancing, spurring states to develop a broader fiscal reach [Besley and Persson, 2009, Karaman and Pamuk, 2013, Gennaioli and Voth, 2015]. As a result, states undertaking wars
required greater capacity. Queenly reigns may have had greater capacity than kingly reigns
for two reasons, both of which themselves reflect prevailing gender norms from this period.
First, queenly reigns may have been able to secure more military alliances. While marriage
brought alliances for both male and female monarchs, male spouses were typically more
involved with the military of their home countries (than female spouses). This was a direct3reflection of taboos on female military leadership during this time period. As a consequence,
male spouses were also plausibly better positioned to cement alliances on behalf of queens.
Second, queens often enlisted their spouses to help them rule, in ways that kings wereless inclined to do with their spouses — an asymmetry again reflects gender identity norms.
For example, queens put their spouses in charge of the military or economic reforms, which
effectively meant there were two monarchs overseeing state affairs, as compared to one. This
greater spousal division of labor may also have enhanced the capacity of queenly reigns,
enabling queens to pursue more more aggressive war policies.
To test these accounts, we disaggregate war participation by which side was the aggressor, and examine heterogeneous effects based on the monarch’s marital status. We find thatamong married monarchs, queens were more likely than kings to fight as aggressors, and tofight alongside allies. Among unmarried monarchs, queens were more likely than kings tofight in wars in which their polity was attacked. These results provide some support for theidea that queens were targeted for attack: Unmarried queens, specifically, may have been
perceived as weak and attacked by others. But this did not hold true for married queens
who instead participated as aggressors. The results are consistent with the idea that thereigns of married queens had greater capacity to carry out war, and asymmetries generated
by gender identity norms played a role in shaping this outcome [Bertrand et al., 2015b].3
We also consider and present evidence against several alternative accounts. Queens may
also have fought to signal they were militarily strong, which is a type of signaling implied by
the influential bargaining model of war [Fearon, 1995]. However, if queens were signaling,
there should be larger effects on war participation earlier in their reigns, when it would havebeen most valuable to send signals to maximally discourage future attacks. Yet, we observeno such differential effect. A second alternative account suggests that it was not the queen,
but a persuasive male advisor (such as a foreign minister), who was actually responsible for
3 Bertrand et al. [2015b] finds that gender identity norms creates an aversion to wives earning more thanhusbands in the modern period. Analogously, our results suggest that gender identity norms in Europe historically created asymmetries in women occupying leadership positions, for example, in the context of themilitary or as a spouse to a reigning king.

4

setting war policy in queenly reigns. In this were the case, the gender effect on war should beeven larger among monarchs who acceded at a younger age, since these monarchs are more
likely to be influenced by advisors. However, we observe no differential effect based on ageof accession, which casts doubt on the idea that war participation was driven by advisors.
Rather we interpret our results as reflecting the direct consequence of having a queen, andassociated decisions made by the monarchs themselves.
In broad terms, we see our results providing evidence for the idea that leaders matter[Jones and Olken, 2005, Pande, 2003], including in shaping policy outcomes. Most proximate to our paper are studies that examine female leadership and inter-state war. Thesestudies have found mixed results. For example, Koch and Fulton [2011] find that among
democracies over 1970-2000, having a female executive is associated with higher defense
spending and greater external conflict, while having a higher fraction of female legislators
is associated with lower defense spending and conflict. Other studies have also found that
more female legislators are associated with less external conflict [Caprioli, 2000, Caprioli
and Boyer, 2001, Regan and Paskeviciute, 2003]; that female voters are less likely to support
the use of force internationally [Conover and Sapiro, 1993, Shapiro and Mahajan, 1986, Jelenet al., 1994, Wilcox et al., 1996, Eichenberg, 2003]; and that female leaders and greater gender equity is correlated with lower rates of internal conflicts [Caprioli, 2000, Melander, 2005,
Fearon, 2010]. These results may partly reflect the greater willingness to elect female leadersduring times of peace. Owing to this concern, we exploit a plausibly exogenous source ofvariation in female rule. By focusing our analysis on war over the 15th-20th centuries, we
also take an identification-based approach to analyzing history [Nunn, 2009].
Our paper fits into the broader literature of how female political leadership affects public
policies, including spending patterns [Chattopadhyay and Duflo, 2004, Breuning, 2001] education [Clots-Figueras, 2012, Beaman et al., 2012] and corruption [Brollo and Troiano, 2016];
as well as how female corporate leadership affects firms outcomes [Matsa and Miller, 2013,
Bertrand et al., 2015a, Ahern and Dittmar, 2012].
It also relates to the literature examining how female socialization affects male behav5

ior. These studies have shown how mothers influence their sons’ labor market outcomes[Fernández et al., 2004]4 ; and that having a daughter or sister affects male legislative voting[Washington, 2008], party identity [Healy and Malhotra, 2013], and judicial decision-making[Glynn and Sen, 2015]. The combined effect of ethnicity and female socialization has also
been found to influence decision-making, for example in Ottoman decisions to fight Europeans [Iyigun, 2013].
Our analysis is also related to several recent papers that have documented importantcharacteristics of European monarchies. For example, reigns became longer with the spreadof feudalism and parliamentarianism [Blaydes and Chaney, 2013]; hereditary succession
promoted economic growth under weak executive constraints [Besley and Reynal-Querol,
2015]; 5 ; and succession through primogeniture increased monarch survival [Kokkonen andSundell, 2014] during a period when regicides also declined [Eisner, 2011]. Consequently,
we examine related outcomes such as reign length and regicide in our analysis.6
Few papers have systematically examined the determinants of conflict historically. An
exception is Iyigun et al. [2017], which shows how conflict responded to climate change over
1400-1900, given its effects on agricultural production. A larger literature has demonstrated
the long-run economic and political legacy of conflict. A number of influential papers haveadvanced war as a key factor leading to state development [Tilly, 1992, Besley and Persson,
2009, Gennaioli and Voth, 2015], and demonstrated how modern day political and economic
development reflect historical conflict and military competition between states [Dincecco
and Prado, 2012, Voigtländer and Voth, 2013a,b]. In contrast, our goal is to examine conflict incidence historically, and assess whether gender played a role in shaping the conflict
trajectory of European polities.
4 Fernández et al. [2004] use variation in World War II as a shock to women’s labor force participation todemonstrate that wives of men whose mothers worked are also more likely to work. Abramitzky et al. [2011]
also use variation stemming from World War I mortality to demonstrate how the scarcity of men can improvetheir position in the marriage market. This paper highlights the influence of past war on marriage-related
outcomes, while our findings suggest the role of marriage in influencing war-related outcomes.
5 Abramson and Boix [2012] document another channel for European growth, showing that industrialization
took place in territories with strong proto-industrial centers, regardless of executive constraints.
6 We are able to examine regicides as Eisner [2011] generously shared his data with us.

6In the remainder of the paper, we discuss mechanisms through which female leadership
can influence war; describe our data; outline the empirical strategy; present the results; andconclude.

2

Mechanisms

2.1

Gender and Perceived Weakness

One account of how female rule influenced war participation focuses on other leaders’ perceptions that women were weak and incapable of leading their countries to war. While
male monarchs were typically also military commanders, this role remained taboo for female monarchs in Europe during the period we study [Monter, 2012, p. 49]. In fact, thelegitimacy of female rule was often questioned on the very grounds that women could notlead their armies into battle. For example, when Mary Tudor became queen of Englandin 1553, many strongly opposed the succession of a woman. The Protestant reformer John
Knox then declared that women were incapable of effective rule for “nature...doth paintthem forth to be weak, frail, impatient, feeble, and foolish... [Jansen, 2002].”
These perceptions may have led other leaders to view queens as easy targets of attack.
Take the case of King Frederick II of Prussia who declared that “no woman should ever beallowed to govern anything”, and who has been described by historians as a “notorious
misogynist” [Monter, 2012, p. 166]. Frederick’s perception of women as incapable rulers
fueled his sense that it would be easy to seize Austrian territory, when it came under the ruleof Queen Maria Theresa in 1745. A month after Maria Theresa acceded, Frederick invaded
Silesia, the richest of the provinces within her territory [Beales, 2014, p. 132]. Accounts ofperceived weakness such as this one suggest that queens may have participated more inwars in which they were attacked by other rulers.

7

2.2

Gender and Reign Capacity

A second account of female rule and war participation builds on the importance of state capacity in warfare. Over the 16th-20th centuries, European wars were frequent and increasingly required extensive financing and military management. Both factors became especially
important with the advent of the “Military Revolution” in the 1500s, which introduced new
military technologies and spurred larger militaries, making war more expensive. For example, the widespread use of cannons led to the use of stronger, more costly fortifications,which were required to withstand cannon fire [Gennaioli and Voth, 2015].7
Army sizes also grew with new forms of fortification and gunpowder technology [Hoffman, 2011, Roberts, 1955, White, 1962, Bean, 1973].8 And, during this period, many countries introduced standing armies and permanent navies, with professional soldiers trainedon an ongoing basis. For example, the armed forces of England grew 3-fold over 15501780, while the armed forces of Austria increased 28-fold over this same time [Karaman andPamuk, 2010]. Larger armies with professional soldiers required greater military management, as well as greater financing. The need for war financing led to larger more centralizedstates, with more extensive fiscal infrastructure for collecting revenue [Tilly, 1992, Gennaioli
and Voth, 2015, Karaman and Pamuk, 2013]. Ultimately, fighting wars effectively required
greater capacity, in both collecting revenue and overseeing large armies.
The demands of war and its implications for state capacity point to another reason why
female rule may have altered their states tendency to participate in wars: female reigns
may have had greater capacity to carry out war. There are two ways in which this greater
capacity could have emerged, both of which reflect prevailing gender norms of this time
period. First, queenly reigns may have been able to forge more military alliances. Whilemarriage brought alliances for both male and female monarchs, male spouses were typicallymore engaged with military matters in their home countries than female spouses – often
7 For example, engineers devised the trace italienne fortification to protect cities but these were very expen-

sive to construct.
8 This trend continued into the 19th century, with military size spiking after the introduction of railroads in1859 [Onorato et al., 2014].

8because they oversaw wars in their home countries prior to marriage or served as ranking
officers in the military of their home countries, which remained taboo for females. This
direct involvement of male spouses with military affairs of the home country plausibly put
them in a better position to cement alliances with their spouses country. Alliances, in turn,served to strengthen the fighting position of a polity, by spreading the burden and costs offighting over numerous partners.
Second, queens may have utilized their spouses to a greater degree in helping them rule.
Queens often put their male spouses in charge of official state matters, which kings wereless inclined to do with their female spouses. This asymmetry again reflected prevailing
gender norms, as it was more acceptable for male spouses to hold these positions and help
their spouses govern, than it was for female spouses to be allocated such positions [Beemand Taylor, 2014, p. 4]. This asymmetry may have been consequential for war participation
since greater division of labor under queenly reigns could have freed up time and resources
for queens to pursue additional policy objectives such as more aggressive war policies.
There are numerous examples of queens putting their spouses in positions of power.
Since women could not serve as heads of militaries, queens would often appoint their husbands to this role, and in many cases, their marriage contracts even specified this arrangement. This was the case with Queen Doña Maria II of Portugal, who married Prince Augustus Francis Anthony in 1836, and appointed him to be the chief of the army [Alves, 2014, p.
166].
Many male spouses (called king consorts) played critical roles in military conquests, even
if they were not official heads of militaries. For example, Mary of Burgundy relied heavily
on her husband Maximilian, heir to the Holy Roman Empire, for leading successful military campaigns against the French [Monter, 2012, p. 89]. Ferdinand V, who co-ruled theKingdoms of Leon and Castile with Isabella I over 1474-1504, also played an essential role.
Ferdinand helped Isabella defeat her niece, Joan of Castile, who challenged her succession.
He also led the Spanish conquest of Granada, expunging the last Islamic state from Spanish
soil, and was key in engineering Spain’s conquest of the new world.
9

Though the degree of direct involvement in wars varied across reigns, king consorts weretypically involved in governing some aspect of state affairs. For example, some spouses
played important roles in carrying out economic reforms and boosting the state’s fiscal capacity, which were needed for financing wars. Francis Stephen essentially single-handedly
revitalized the financial system of the Austrian monarchy and raised money for an army
during the 1740s when his wife Maria Theresa was its ruler [Beales, 2014].
Other spouses helped shape the monarchy’s foreign policy position, even if they did notoversee wars. For example, Prince Albert was Queen Victoria’s most trusted advisor, andshaped both her colonial policy and public relations image [Urbach, 2014]. Victoria, in turn,was said to be most active as a ruler during Albert’s lifetime. In short, when queens put theirspouses into positions of power, the polity in some sense, received the benefit of oversightfrom two monarchs.
Spouses played a unique role in two regards, compared to other family members or advisors. Spouses helped solve the ages old problem of who to trust ruling, since most polities
had laws in place that prevented spouses from becoming monarchs and taking power intheir spouses’s place, unless they were already designated an official co-monarch at the startof the reign.9 This is in contrast to siblings, who could directly contest power. In addition,
spouses could bring with them the alliance of another country, which immediate family
members, or advisors who did not originate from royal families, could not provide. Thus,
more alliances, and support through spousal division of labor, may have strengthened theoverall capacity of queenly reigns, enabling hem to participate in wars more aggressively.

2.3

Empirical Implications

The accounts above lead to the following empirical implications. If the perceived weakness
account holds, having a queen should lead to greater participation in wars in which thepolity is attacked. In contrast, if the reign capacity account holds, having a queen should
9 There were notable exceptions. One was Catherine the Great, who became empress of Russia in 1762 upon

the death of her husband Peter III, though she originated from royal German lineage, and was not an official
co-monarch at the start of Peter III’s reign.

10lead to greater participation in wars in which the polity is the aggressor. This effect should be
especially large for married queens, relative to single queens or kings. In addition, if queens
who have the support of a spouse are best positioned to forge alliances, married queens
should participate disproportionately in wars in which their polity is fighting alongside an
ally.

3

Data and Sample Description

Testing these empirical implications requires data tracking genealogy and war among European polities. No pre-existing dataset contains this information. We construct a new dataset
from various sources, covering the period 1480-1913. Our sample starts in 1480 since this is
the first year for which war data is available. Our sample ends at the onset of World WarI, after which time monarchs had relatively limited power in deciding when their polities
should go to war. We provide an overview of data construction here, and provide greater
detail in the Data Appendix.

3.1

Genealogy Data

Panel Structure—. We use Morby [1989] as the starting point for constructing our polity-year
panel. This source provides a list of polities that existed in Europe over this period.10 Our
main sample includes 18 polities that had at least one queen during this time. Table A.1 lists
these polities and Figure 1 locates them on a map.11
For each polity, Morby provides a chronological listing of rulers, along with the startand end years of their reign. Following this structure, we define a reign as a period in
10 Morby refers to these units as kingdoms. While some of these units — such as the Kingdom of England,

the Kingdoms of Leon and Castile, and the Tsardom of Russia — are formally defined as kingdoms, others—
such as The Medici and their Successors in Florence or The Principality of Monaco — are more accurately
described as independent states. We use the term polity to encompass both kingdoms and states.
11 This map was created by overlaying six georeferenced historical vector maps from Euratlas(http://www.euratlas.com/) at the turn of each century, over 1500-2000. The boundaries of the polities arefrom different time periods, and do not necessarily match present day borders or show the maximum geographical area attained by each polity historically. The aim of the map is simply to show the polities appearing
in our sample.

11

which a given monarch or set of monarchs rule the polity. Our sample includes 193 reigns,
34 of which were ruled by at least one monarch who was female, constituting 18% of thesample. In most reigns, there is a single monarch. However, in 16 reigns, multiple monarchs
rule simultaneously. Most of these cases of multiple rule reflect two monarchs co-rulingsimultaneously. This includes cases of (1) a husband and wife ruling jointly, as in the caseof Suzanne and Charles I, who co-ruled the Duchy of Bourbonnais over 1505-1521 or (2)father and son ruling together, as in the case of Ivan III the Great and Ivan the Younger who
co-ruled the Tsardom of Russia over 1471-1489.12
A monarch can govern in multiple reigns, by ruling alone in one reign and co-ruling withanother monarch during another reign.13 Thus within the 193 reigns, there are 194 distinct
monarchs. Among the 34 reigns with queens, there are 29 distinct queens. Even if a queen
was married, her spouse was not necessarily designated an official co-monarch with the titleof king. In 24 of the reigns with queens, women ruled as sole regents, which we designate ascases of “Solo queens.” (Among these 24 reigns, 14 were cases in which queens were married, but nonetheless governed as sole regents — which highlights the distinction between
being a sole regent, i.e., solo queen, versus being a monarch who is single or unmarried).
In 10 of the remaining cases queens co-ruled with their spouses. In one reign alone, two
women co-ruled together.14
Geneaology Variables—. For each monarch, we are able to gather genealogical informationfrom the Catalog of Royal Family Lineages [Tompsett, 1994], which conveniently follows thesame polity and ruler listing as Morby [1989], enabling highly accurate matching. For eachruler, we code the ruler’s age at accession, marriage year, marriage dissolution year, andspouse birth and death years. This allows us to track if the rulers were married, and if their
12 In five additional cases, there is multiple rule because one ruler governed the polity for less than a year

before being deposed. For example, Edward V ruled the Kingdom of England for a part of 1483 before he wasdeposed and his brother Richard III took over as the monarch.
13 For example, Queen Suzanne ruled the Duchy of Bourbonnais on her own over 1503-1504. She ruled
together with her husband Charles III over 1505-1521. Upon her death, Charles III ruled on his own, from1522-1527.
14 This was the case of Mary I and Lady Jane Grey, who ruled the kingdom of England in the same year
(1553).

12spouses were living during their reign. In addition, we record the birth and death year of
their children and siblings.
Although gender is not listed separately, we are able to use the listed name to establish
gender of children and siblings. If gender was not readily readily apparent from the name,or the name itself was not listed, we conducted an exhaustive search of additional sources
to locate this information. We are only unable to establish gender in 2% of the children and
6% of the siblings, and control for missing gender children / siblings in these cases.
Our instruments are based on the gender of the sibling and first born child of the “previous monarchs”, which often will be monarchs of the previous generation in systems ofhereditary succession. Thus in constructing our instruments, in most cases, the previous
monarchs are simply those who ruled in the previous reign. However, in 30 reigns, co-ruleand one monarch ruling across multiple reigns break the correspondence of previous generations to previous reigns. In these cases, our definition of previous monarchs differ frommonarchs in the last reign. We detail these cases in Section 2 of the data appendix.15
We also generate measures of whether the monarchs are married. We define a monarch as
married during their reign if he or she has a (living) spouse at any point during their reign.16(In cases of co-rule, we consider if either monarch has a spouse during the reign). This
marital measure differs from whether the monarch was ever married: He or she may also
be unmarried during a reign either because their rule precedes marriage, or because they
were married previously, but lost their spouse owing to death or separation. For example,
11% of the rulers in our sample never married, but 24% of the reigns are composed of rulers
without spouses.
15 As an example, in the case of Suzanne and Charles III of Bourbonnais, when Suzanne rules by herself, andSuzanne and Charles III rule together, and Charles rules by himself, we consider Suzanne’s father Peter II andher uncle Charles II, who ruled alongside Peter in a previous reign to be the relevant previous generation andutilize them as the appropriate monarchs in the instrument sets for these three reigns involving Suzanne andher husband Charles.
16 Monarchs who were married in their reign tended to be married for most of their reign. In our sample,
the average fraction of the reign in which the monarchs are married was .72 (while the median fraction was.85). We use this measure of marital status rather than annual variation in the year in which the monarchs get
married since this timing is more plausibly endogenous to annual variation in war incidence.

13

3.2

War Data

We code data on war participation for each polity from Wright [1942]. Importantly, this data
source tracks when each participant enters and exits each war, which allows us to measure
war participation with relative precision.
The listing includes larger wars, described as “all hostilities involving members of thefamily of nations, whether international, civil, colonial, imperial, which were recognized asstates of war in the legal sense or which involved over 50,000 troops” [Wright, 1942, p. 636],
as well as smaller wars, described as “hostilities of considerable but lesser magnitude, notrecognized at the time as legal states of war, that led to important legal results” [Wright,
1942, p. 636].
It also disaggregates wars based on type, including Balance of Power wars, which areinter-state wars involving European nations17 ; Defensive wars, which are inter-state wars
between European states and the Ottoman empire; Imperial wars, which are colonial conflicts; and Civil wars which are internal to a single European nation.
Balance of Power wars are the most prevalent form of conflict, both in terms of the number of wars, and conflict incidence. Our main sample contains 75 balance of power wars,
29 imperial wars, 7 defensive wars, and 28 civil wars. As shown in the descriptive statistics (Table 1), polities find themselves engaged in a Balance of Power war during 21% of
the sample years; in Imperial wars during 3% of the years; in Defensive wars during 1%of the years; and in civil wars during 5% of the years. For our initial results examination,
we aggregate Balance of Power wars together with Defensive and Imperial wars, to form acomprehensive measure participation in any external conflict. But given their prevalence,
we view participation in Balance of Power wars as our main dependent variable.
A natural concern is whether this data is truly comprehensive and measures the full
extent of war among European polities over this period. This is challenging to assess since
17 Balance of power wars almost exclusively take place among European polities.

There are a handful of
exceptions documented in the Data Appendix. For example, the Russo-Japanese War in 1904-05 also involved
Japan, and some wars involved the Ottoman Empire which was based out of what is Turkey today.

14

there are few other data sources that track participation in wars in a fine-grained manner –i.e., those that track wars, specifically, as opposed to other more broader types of violence,and in a way that enables us to observe when each participant enters and exits the war.
However, in the Data Appendix (Section 5) we compare war prevalence in our data to war
prevalence in two other data sources which track wars for at least part of the time period
covered by our our analysis. We find that wars are not systematically under-represented inour data. If anything, these other sources are missing relatively more wars compared to the
Wright data source.
Aggressor Coding—. Wright also demarcates which side is the aggressor in the conflict—i.e., which side initiated the war. The concept of the aggressor is conceptually clearest andmost precisely measured for Balance of Power wars, which involve European polities, one ofwhich Wright codes as having initiated the war. In contrast, the colonizing power is always
assumed to have initiated imperial wars; rebels are always assumed to have initiated civil
wars; and no participant is defined as an aggressor in defensive wars [Wright, 1942, p. 637].
This is an additional reason we focus more on participation in Balance of Power wars as our
main dependent variable.
As with any aggressor coding in a conflict setting, Wright’s coding of aggressor is subjective. We rely on this coding, rather than on our own, to minimize our potential bias in thismeasure. Nonetheless, if Wright over-attributed aggressive participation to female rulers,
this could potentially bias our results. However, the pattern of results we observe basedon marital interactions would require a very particular form of bias, in which Wright overattributed aggression to women who were married during their reigns and under-attributed
aggression to women who were single or widowed during their reign. We view this particular form of bias to be unlikely, since it would require extensive detailed institutional
knowledge on the timing of marriage and spousal deaths. This reduces our concerns thatthe results are driven by coding bias, which we also discuss further in section 5.4.
Allies Coding—. In addition, we also code realized alliances, which we measure as whether
polities were participating in wars in which they were fighting alongside another polity.
15

Specifically, we used web sources that provide a description of the wars to determine which
polities in our sample were allies.

3.3

Data on Other Measures of Stability

Besides war participation, we examine additional outcomes related to internal instability, including the length of reign, and whether a monarch died of unnatural causes. This variable iscoded on the basis of regicide data by Eisner [2011], which measures whether a monarch was
killed or died of other unnatural causes, for the period prior to 1800. We supplemented thisinformation from Eisner [2011] other sources to create an equivalent indicator of whether
the monarch died of unnatural causes for the duration of our sample period.18
We are also able to examine whether monarchies come to an end via unification, partition,or capture; or transform into republics, based on data recorded by Morby [1989]. Finally, we
are able to observe territorial change under each reign, using Centennia Historical Atlas,which provides 10 snapshots each of territory each year, for most of the European polities
in our sample. Based on this data, we can observe if the contiguous territory under a polity
increased by comparing snapshots at the beginning and end of the ruler’s reign.19 We use
this to generate three measures of changes in contiguous territory – an indicator that equals 1
if territory was lost (and 0 otherwise); another indicator that equals 1 if territory was gained(and 0 otherwise); and an ordered variable that equals -1 if territory was lost, 0 if there wasno territorial change, and +1 if there was territorial gain.

3.4

Main Sample

Our main sample spans 1480-1913, and includes 18 polities that ever had a queen. Not every polity existed for every year: on average, each polity existed for 199 years, though thisranges from 9 years to 419 years. This results in an unbalanced panel of 3,586 observations.
18 See the data appendix Section ?? for greater detail.
19 We are not able to observe the precise increase in area within the reign without access to the GIS data

underlying the snapshots provided by Centennia.

16Periods in which a polity is a republic are not a part of the sample, since our goal is to compare the rule of female monarchs to male monarchs, rather than republics. Table 1 provides
the descriptive statistics of key variables used in our analysis, at the polity by year panel
level.

3.5

Auxiliary Sample

We also coded genealogy and war participation in an auxiliary sample of polities that neverhad queens, which we use to conduct falsification tests and examine instrument validity.
This sample is comprised of 149 reigns across 18 other polities for which we were able tomatch the units in the war and genealogy data.20 These polities are also listed in Table A.1
and shown in Figure 1. The data appendix details why we are missing data for some polities(which are also shown using hatched lines in Figure 1). Importantly, it was not possible for
us to include the German kingdoms, which typically had multiple houses co-ruling different
sub-regions within their polities. These could not be matched to the war data since Wright[1942] does not discern which specific sub-regions participated in each war.

4

Empirical Strategy

Using this data to examine the effect of queens on war requires two additional steps – examining how succession occurred and developing relevant instruments. We discuss these in
the sub-sections below.

4.1

Succession Laws

Succession was partly governed by laws which dictated who could rule. Laws of succession
varied tremendously across European polities. Some laws de jure barred women from coming to power. Chief among these were Salic law, which governed succession in the French
20 We include a more detailed discussion of the polities in the auxiliary sample in Section ?? of the data

appendix.

17monarchy after 1317. As a consequence no queen regnants, who ruled in their own right,
came to power in France.21
Other systems de facto prevented women from coming to power. This is true of systemsof elections. During our sample period, elections in European monarchies were not broadbased: rather a group of elites voted for a monarch among a selected pool of candidates, whowere typically all from royal families [Kokkonen and Sundell, 2014]. This succession law
was used perhaps most famously in the Holy Roman Empire, where seven prince-electors
would choose an emperor. No female was ever elected to head the Holy Roman Empire, orindeed any European government, until Margaret Thatcher was elected prime minister in1979 [Monter, 2012, p.40].
A third group of laws allowed women to come to power under particular circumstances.
This was true of certain types of primogeniture, which broadly is the principle of letting
the oldest son inherit power. For example, under male preference primogeniture, “[i]f themale line of particular heir fails, then the eldest daughter of the most recent male sovereign
may succeed to the throne” [Corcos, 2012, p.1604]. This system preferred males but allowed
females to succeed.22
In broad-brush terms, England, Portugal and Russia practiced primogeniture for large
durations of their history. However laws of succession also changed substantially over time,even within given polities. These changes may have arisen endogenously in response to theconditions such as wars or the availability of male heirs. For example, in 1713, the Austrianmonarch Charles VI (who had no sons) put forward the Pragmatic Sanction, which declaredthat his daughter Maria Theresa — and, failing her — his younger daughter Maria Anna
should succeed him as monarch [Beales, 2014, p.127].23
21 France did have queen consorts who married reigning kings or queen regents who were essentially acting

monarchs on behalf of child heirs who were too young to rule [Corcos, 2012]. Note that identifying the effect ofqueen regents would require a different empirical strategy than the one we use in this paper since gender of thefirst-born child and gender of the siblings of previous monarchs do not have predictive power in determining
whether queen regents came to power.
22 Absolute primogeniture, where the oldest child inherits regardless of gender, was not practiced in any
monarchy during our sample period. It was only first adapted in 1980, by Sweden.
23 The Kingdom of Sweden also reversed itself on the question of female rule several times. It prohibitedfemale inheritance from 1654 until 1683 and again after 1720 [Monter, 2012, p.34].

18

The potential endogeneity of these laws to the presence of male heirs and conflict makeit problematic to use them to identify the effect of female rule on war. In addition, no data
source systematically tracks which polities had which types of law in place year to year.
So instead of relying on how succession worked in law, we instead exploit how succession
worked in practice.
Though formal succession laws varied across polities and years, as Monter [2012, p.3637] describes, in practical terms:
Four general principles governed dynastic successions to major states almost everywhere Christian Europe – they were (1) legitimate birth (2) masculine priority(3) direct over collateral descent and (4) primogeniture.
In his 1579 treatise on female rule, Chambers [1579] also wrote, “it is a general rulethat women succeed in the absence of males” and “If a decreased king anywhere else [butFrance] left legitimate daughters but no legitimate sons, the oldest surviving daughter tookprecedence over more distantly related males. [cited in Monter, 2012, p.114]” These guiding
principles motivate our empirical strategy and our instruments for whether queens were in
power.

4.2

Pathways to Becoming a Queen

Since the oldest son of a monarch had priority in succession, if the previous monarchs had
a first-born child who was male, this increased the chance of having the male child become
ruler, or having a king during the next period. Conversely, if the oldest daughter was female,or the only child was female, this increased the chance of having a queen, as older daughters
would be given priority over other more distantly-related males such as nephews or uncles.
For example, Mary, the only child of King Charles the Rash, became queen of Burgundy andthe Low Countries in 1477. Marie Adelaide, the eldest child of William IV came to rule theGrand Duchy of Luxembourg in 1912. Based on this idea, we utilize whether the first-born
legitimate child of the previous monarch(s) was male as one of our instruments for whether
19a queen hold power.
Of course if the previous monarchs did not have any children, or the children died by thetime of accession, or were too young to rule at the time of accession, then the throne could
pass to a sibling of the monarch instead. If the previous monarchs had a sister then thethrone could pass to her, as she would be given priority over more distantly related males.
For example, Ulrika Eleanora became ruler of Sweden in 1718. She was preceded by her
brother Charles XII, who never married or had children. In addition, all of their brothers
had died by the time Charles’ reign drew to an end, leaving Ulrika as the heir. Since having
a sister enhanced the chance of having a female accede, we also use whether the previous
monarchs had a sister as a second instrument for having a queen in power.
While the paragraphs above provide motivating examples, Figure 2 systematically traces
out the circumstances under which queens came to power. It shows that among the 29
queens in our sample, 23 are cases when the previous monarchs lacked a first-born child
who was male, including eight cases in which the previous monarchs had no children. These
cases are shown in grey. The figure shows that in 23 of the 29 queen cases (shown in aqua),
the previous monarchs had a sister.
The figure also highlights how the death of male heirs played a role in the pathwayof queens becoming queens. Among six queen cases where the previous monarchs had
multiple children and a male first-born child, in all but one case, the males had died by thetime of accession. Thus non-compliance emerges in part based on the death of older malebrothers. In addition, among nine cases where the monarchs had multiple children, and thefirst-born child was female, again in only one case was there a younger male child who wasalive at the time accession occurred.24
The death of these siblings may be endogenous to conflict or circumstances associatedwith conflict. For example, male children may die at a young age if the reigning monarchs
engage in war; or, it is even possible that siblings who are particularly aggressive may end
24 Section ?? data appendix provides details on the two cases of queens who came to power with a brotherliving at accession.

20

up killing their brothers and sisters to rise to power and subsequently lead their polities
to war. Given this potential endogeneity, we avoid using information about the death ofchildren in the instrument sets. For example, we do not examine the gender of only thosechildren who have survived by the time accession occurs. In fact we instead check the robustness of our findings to controlling for the number of dead children (and siblings) among
previous monarchs.
Overall, our instrumental variables strategy is based on the idea that succession washereditary, and our instruments will predict queenly reigns if succession typically proceeded
within a family lineage. Of course, occasionally the lineage changed, and on rare occasions,laws even changed to facilitated non-hereditary succession.25 These discrete cases could
potentially weaken the strength of the first-stage. However ultimately, first-stage F-statistics(presented in the results below) demonstrate that succession was sufficiently hereditary forgender of the first born and presence of a sister in the past reign to be strong predictors ofqueenly rule.

4.3

Instrumental Variables Specification

We use a Instrumental Variables (IV) strategy to estimate the effect of queens on their polity’s
conflict participation. We use whether the previous monarchs had a male first born child,and whether they had a sister to instrument for whether a queen is in power.
The second stage of the IV estimation is given by:

d pr )δ + X0 φ + ε
Wprdy = α p + τd + ( Queen
prdy
pr

(1)

where Wprdy are war-related outcomes in a polity p, reign r, decade d and year y, suchas whether the polity is participating in a war in a given year. α p are polity fixed effects; τd
are decade fixed effects; X is a vector of controls that vary at the reign level (detailed below);
25 For example, in 18th century Russia, Peter the Great’s succession law of 1722 gave the ruling tsar the rightto appoint his or her successor. This opened the door to ambiguity in how succession could occur, leading to aseries of successions via coups, depositions, and appointment by the privy council.

21

d pr is the instrumented indicator of whether a queen rules during a given reign.
and Queen
By incorporating polity fixed effects, we exploit variation over time in when the polity isruled by a female monarch versus a male monarch. By incorporating decade fixed effects,
we control for decade to decade variation in conflict incidence throughout Europe.
The first stage is given by:Queen pr = α p + τd + First-Born Male pr−1 + Sister pr−1 θ + X0pr ρ + ω prd(2)

where First-Born Male pr−1 is an indicator of whether the previous monarch(s) had alegitimate first born child who was male; Sister pr−1 is an indicator of whether the monarch(s)in the previous reign had a female sibling. We use Two-Stage Least Squares to estimate
equations (1) and (2) together in a one-step procedure.
Standard Errors —. The queen variable, as well as the two instruments, vary at the levelof the reign. However, war incidence annually may be serially correlated over time within apolity, for example, if particular polities tend to experience spurts of war during particular
centuries. To account for this potential serial correlation, we cluster the standard errors at thepolity by century level. There are 67 such clusters in our main specifications. In addition, it
is worth noting that when a polity finds itself at war, this can either be because it has decided
to attack another polity, or because another polity has decided to attack it. This suggests thatwhen examining participation in external wars, the standard errors may even be correlated
across polities fighting in the same wars. We account for this in two steps. First, we subject
our analysis of aggregate war participation to a specification using dyadic data, in which
we cluster our standard errors at the dyad level. Second, we separately examine effects
on participation in wars in which the polity was the aggressor. Specifications using thisoutcome are less subject to concerns that correlated errors across polities fighting on opposite
sides affect the estimates, as conflict initiation, by construction, represents the actions of one
side in the conflict.
Control Variables —. The First-Born Male variable is defined to be zero if the previous

22monarchs had no legitimate children. So we additionally control for whether the rulers had
any legitimate children with two variables: The first indicates if they had any children forwhom birth years are not missing, and the second indicates if they had any children withmissing birth years. This disaggregation helps account for measurement error since we canmost accurately identify who is first born when there are no missing birth years. These“any children” controls also account for plausibly endogenous reasons why the previous
monarchs may not have had children, such as war in the past reign that led them to die
young, which may also affect war in the current reign.26 In addition, we control for threecases in which the previous monarchs are co-rulers who are unrelated to one another, since
the gender of the first born may be relatively less informative of the actual successor in thesecases.
In all our specifications, we also control for whether the gender of the sibling and genderof the first-born are missing. As discussed in the data section above, we identify gender
based on name or an exhaustive search if the name is missing from Tompsett [1994]. However, we are still unable to find the name of five first-born children. We believe these are very
likely to be girls — as Jansen [2002] documents in detail, it is common royal genealogies toprovide limited information about female children. However, we do not impose this assumption, and instead control separately for whether gender of the first-born is missing. We
are analogously missing gender information for siblings of 10 previous monarchs, and also
control for whether there are any siblings with missing gender. We additionally control forwhether our search filled in any missing demographic information.These controls comprise
our standard controls throughout the tables.
Polity Boundaries —. Some of our polities changed boundaries substantially over thisperiod — some polities have come to an end as one unit, and re-emerged as a part of anotherunit after unification or capture by another kingdom. For example, the Kingdoms of Leonand Castile are present in our sample as a polity from 1480 until the first decade of the 1500s,
at which point Spain emerges as another polity which lasts through to 1913. We address this26 We also include war in the past reign as auxiliary controls in some specifications.

23

in two ways. First, by including polity fixed effects, we look only at changes over timewithin a given polity. For example, we exploit variation over time within the Kingdoms ofLeon and Castile when it is in existence, and over time Kingdom of Spain after it comes into
existence. Second, we show that having a queen in power does not influence outcomes suchas whether the monarchy drew to an end by via unification, partition or capture, or throughtransformation into a republic.
Exogeneity of Instruments —. We use gender of the first born since this is arbitrarily determined by nature, and thus plausibly exogenous to conflict in the polity. In contrast, whether
the monarchs have any child who is male or the number of children who are male could bea function of their effort. For example, rulers could actively continue having children until
they have a son. This effort may be correlated with other characteristics such as aggressive
behavior, which may, in turn, affect the proclivity to participate in conflict aggressively, as
well as the legacy of conflict left behind in the polity.
We also exploit the gender of the first born, rather than gender of the oldest surviving
child at accession, since there may be selection bias in who survives. For example, children
who are able to survive harsh conditions may be stronger, and strength may be correlatedwith a tendency to be aggressive and fight aggressively, including in warfare. In addition,
if siblings kill each other off in their ambition to become monarchs, the strongest monarchs
may the ones who survive and fight wars aggressively once they become rulers. We instead
control for the number of dead siblings as auxiliary controls.
The sister instrument is arguably less arbitrarily determined than the first born malevariable. In the absence of changes in the ruling house, whether the previous monarchs havea sister is equivalent to whether the monarchs from two periods ago had a daughter. Thus,
this instrument is subject to the concern that monarchs who were aiming to have at least one
son or a child of both genders may have ended up with a daughter and a larger number of
total children two periods ago, which amounts to a larger number of total siblings among
previous rulers (or equivalently, a larger number of aunts and uncles from the perspective of
the current period monarch). If having more of these aunts and uncles means there are more24

individuals who may contest succession, this would represent another alternate pathway
affecting conflict. To close out this potential other channel, we control for the total numberof siblings of previous monarchs in all our main specifications. Since gender of the first-born
is more plausibly exogenous, we additionally present tests of overidentifying restrictions toaddress the exogeneity of the two instruments together, and present additional falsification
tests to examine instrument validity in the results.
Instruments in the Sample—. Table 2 shows two instruments at the level of the reign. The
previous monarchs had a sister in 71.5% of the cases. Conditional on the previous monarchs
having children, there was a male first born in 54% of the sample. The naturally occurring
sex ratio at birth is 52% male [Grech et al., 2002]. Thus the first born ratio in our sample iswithin the margin of error around this naturally occurring ratio, particularly since the firstborn children with missing gender are likely to be female. In addition, we compared thesex ratio at birth in our data sources to records for Europe in the Human Mortality Database(HMD).27 In these sources, we found the median sex ratio at birth to be 53%, with the range
spanning from 51% in Sweden to 55% in Portugal.
In addition, we can be reasonably confident that our genealogical data is complete, andthat we are not missing many first born children in entirety for the following reasons. Sexselective infanticide was not a common phenomena in Europe over this period [Siegfried,1986]. Moreover, the Tompsett [1994] data source records even infants who died at birth:
For example, we verify that children with the same birth year and death year are includedin the catalog. Overall, these checks and the similarity of the sex ratio at birth figures acrossour data and the HMD data bolsters our confidence regarding the accuracy of our genealogydata.
27 The HMD contains records of births from various national statistical and other academic sources, and it

includes 9 of the 18 polities appearing in our main sample - see Section ?? of the data appendix for greater
detail.

25

5Results

In this section, we present evidence on how queens affect war participation. We begin byshowing the OLS and IV results. We next address instrument validity and present sensitivity
checks. We then present results disaggregated by aggressor and marital status to examine
the perceived weakness and reign capacity accounts. We close by examining alternative
accounts.

5.1

Queens and War: Main Results

Table 3 examines the OLS relationship between queens and war participation. The firsttwo columns examine the aggregated external war participation variable, while the lattercolumns show disaggregated effects on balance of power wars, defensive wars, and imperial wars, respectively. The even numbered controls include our standard controls. These
are not needed for the OLS specifications, but we include them for comparability to the IV
specifications.
The results show that polities led by queens participated in external wars more relative
to polities led by kings. The estimate in column (2) indicates a differential war participation
rate of 8.6%. The results also show that this effect stems from greater participation in Balanceof Power wars: The coefficients in columns (3)-(4) are substantial and precisely estimatedwhile the coefficients for other types of war are both small in magnitude and statisticallyinsignificant. This is perhaps unsurprising given that Balance of Power wars are by far themost prevalent form of external conflict.
However, the OLS estimates in Table 3 may be downward biased — for example, if theelite allowed queens to come to power more during times of stability, or prevented themfrom coming to power during times of war. In fact, even some reigning queens articulated
the view that women should not govern if they had to lead armies into battle. This was the
position of Ulrika Eleanora who asked that the Swedish Riksdag that her husband Frederick
be made co-regent [Persson, 2014].
26

To account for this potential bias, we present the IV estimates in Table 4. The secondstage results again demonstrate that queens participate in external wars more than kings,
and that these effects are concentrated in Balance of Power wars. The coefficient in column (1) suggests that the likelihood of external conflict is 27% higher for queens relative tokings. The larger coefficient on the IV estimate relative to the OLS estimate is consistent withdownward bias on the OLS estimates.
The bottom of Table 4 shows that the instruments together make for a strong first stage:
the Kleibergen-Paap F-statistic is 13.7. Individually, each instrument also has a statisticallysignificant effect on the likelihood of a queen coming to power. If the previous monarchs
had a first-born male, this reduced the likelihood of a queen coming to power by 21.2%.
In contrast, if they had a sister, this increased the likelihood of queen coming to power by
18.9%.
In Appendix Table A.2, we present results using other variants of the instrument set,
including interactions of the sister and first-born male instruments; interactions of the thesister instrument with an indicator that the monarch had no legitimate children; as well as
each of the instruments individually. Although the strength of the first stage and precision of
the second stage estimates vary across specifications, all instrument sets yield second-stage
coefficients of similar magnitudes, indicating that the results are not especially dependent on
any one particular IV approach. For example, estimate with the first-born male instrumentis .341 and marginally insignificant with a p-value of .11. This is reassuring in that the has
the advantage that gender of the first child should essentially be determined by a coin flip,
and is unaffected by the fertility behavior of previous monarchs. We use the first born maleand sister instruments together since this yields the strongest first stage among potential
instrument sets. We address potential concerns regarding the exclusion restriction and thevalidity of the instruments in the section below.

27

5.2

Examining Instrument Validity

We present tests of over-identifying restrictions (at the bottom of Table 4). These tests fail toreject the null that the instruments together are valid – i.e., that, conditional on the exogeneity of one instrument, the other instrument is also exogenous. This is reassuring as a firststep. In the remainder of this section, we directly address and present evidence against several other ways in which the instruments could affect conflict beyond their effect on queens.
First, the previous monarchs were more likely to have had a sister if their parents hada larger number of children. This would correspond to previous monarchs having a larger
number of total siblings. If these siblings (i.e., more aunts and uncles from the perspectiveof the current period monarch) were potential contenders for the power, their presence may
have spurred more conflicts over the throne. These wars of succession would then serve as
an alternate channel affecting conflict, violating the exclusion restriction.
In Table 5, we take two steps to address this concern. First, we control for the total number of siblings to close off this alternative channel. In addition, we identify and remove
wars of succession from the sample.28 Table 5 shows that the effect of queens on external
war participation remains precise and increases in magnitude under both changes. In addition, patterns by war type remain unchanged, with the effects clearly concentrated among
Balance of Power Wars. These results indicate that our estimates are not driven by siblingsof previous monarchs initiating conflicts over succession. Going forward, we continue tocontrol for the number of total siblings in all remaining specifications.
A second potential concern lies in the use of the first born male instrument. The lackof a first born make could spur war if it signals uncertainty in succession. Other monarchs
may choose to attack the polity if they see that the first birth did not yield a male heir. If
so, queens would inherit polities that are already participating in more wars, which would
present an alternative path through which the instrument affects war participation. In Table
6, we examine if these effects hold. For completeness, we conduct these tests for all war
28 These five succession wars are all external wars since they involve more than one European power.

28

types (including civil wars). Columns (1) - (5) examine if monarchs who have a first born
male (or sister) end up experiencing more conflict in their current reign. The coefficients are
insignificant, small in magnitude, and display varying signs, suggesting they do not.
We conduct a second, broader falsification. If the presence of a first born male (or sister)in the last reign affects war through some other channel beyond queenly accession, thesevariables should also affect war participation in polities which never had queens. To examine this idea, we test whether the presence of a first-born male and sister in the past reign
affected conflict in the non-queen polities. We find no evidence of such a relationship incolumns (5) - (8). These two falsifications further bolster the validity of our instruments.29
In Table A.3, we turn back to our main sample, and additionally show that there are no
significant effects of having a queen on external conflict in the previous reign (or other measures of internal stability in the previous reign such as reign length and whether monarchs
died of natural causes). This suggests that queens and kings inherited polities that weresimilar in terms of the conflict they had experienced. We also show that that controlling for
conflict and internal stability in the previous reign do not affect the results.
Finally, it is worth noting that most new wars that started during a reign did not start
immediately at the beginning of the reign. For example, new Balance of Power wars started
on average, 8.2 years after the start of reign; and this figure is 8 years for reigns with kingsand 10 years (i.e., even longer) for reigns with queens. This timing is inconsistent with theidea that the lack of a first born male in the prior reign triggers conflict immediately during
the new reign.
The results in Tables 3-5 as well as Table A.3 all demonstrate that the effects on war
participation stem primarily from participation in Balance of Power wars, the most prevalent
29 Acharya and Lee [2015] find that over 1000-1500 AD, the number of male heirs in the past reign affects

internal conflicts (civil wars). Four points are useful in understanding our results together. First, our IV strategy uses the presence of a first-born male, not the number of male heirs. Second, we use the first born male
instrument in conjunction with the sister instrument which is a different and additional source of variation.
Third, our sample begins when their sample ends — and it is possible that succession may have been more
contentious and given rise to more internal conflict during the earlier pre-1500 period, if succession laws wereless detailed during that time. Finally, we find second-stage effects of queens on external wars, not internal
wars (See Table 10). Thus, from the angle of instrument validity, we are most concerned about alternative ways
in which our instruments can affect external wars, not internal wars, which is the focus of their finding.

29

type of conflict in our sample. In the remainder of the paper we focus on this dependent
variable.

5.3

Additional Checks

In this section, we present a number of additional robustness tests, including additional controls, sensitivity checks to address the small number of queens in the sample, and alternative
specifications including those using dyadic data. Table A.4 presents descriptive statistics ofthe additional variables used for these checks.
Additional Controls —. One alternate reason why we observe queen effects on war may
have to do with the presence of dead siblings on the pathway to becoming a queen. In particular, it is possible that sisters of the previous monarchs (aunts from the perspective of
the current period monarch) may have gained power by killing off other potential brothers(uncles) who may have otherwise inherited the throne. Analogously, first born females may
have come to power by killing off younger brothers. If these types of targeted killings areassociated with circumstances or personas that produce more violence then this could again
serve as an alternate channel influencing conflict. However, in Table A.5, we show that controlling separately for the number of dead male and female siblings of previous monarchs,
or the dead male and female siblings of current monarchs do not affect our results.
Another potential concern is that queens, on average, were six years younger at accession. If younger monarchs are more aggressive than older monarchs, then this age difference
may give rise to the results. However, Table A.5 shows that controlling for age also also does
not alter the results.
Finally, it is possible that though queens participate in wars more often, they also participate in wars that are smaller in scope. In remaining columns of Table A.5, we show thatqueens do not participate in wars that are smaller, as measured by the number of participants in these wars.30
Sensitivity Checks —. Our sample includes only 29 queens, which raises the concern that
30 We use this metric given the absence of data on casualties associated with wars in the Wright data source.

30

the results may be driven by a particular queen or a particular polity. We address this concern in several steps. First, we drop each queen iteratively from the sample, and present thecoefficient estimates and 90 percent confidence intervals on the queen coefficient in Figure
3 (left panel). The estimates in the figure display remarkable stability and suggest that theeffects are not driven by any individual queen. Figure 3 (right panel) presents analogous
estimates of the effect of queenly reigns defined on the basis of Solo queens only (who ruled
as the sole regents), for the full sample (shown in the blue triangle), and then dropping eachsolo queen one at a time. The confidence intervals are larger in these specifications but thispanel also corroborates that the effects hold if queenly reigns are restricted to the reigns ofsolo queens, and that these effects are not driven by any particular solo queen.
In Table A.6, we drop not just individual queens, but whole polities from the sample. In
the first six columns, we iteratively drop each of the polities that contribute more than one
queen, and in the seventh column, we drop all remaining polities that contribute just one
queen to the sample. The estimates retain their significance across all of these specifications,demonstrating that England or Spain or Russia, alone, do not drive the effects.31 The estimate is if anything larger in column (7) than remaining columns, indicating that the effects
are not driven by the more minor polities that had the occasional queen.
Alternate Specifications—. In our main specification we compare queens to kings in polities that have, at some point, been ruled by a queen. This arguably constitutes a better
control group relative to kings in polities that have never been ruled by queens. However,it also raises the concern that our finding of more war under queens would be overturned if
we included these non-queen polities in the estimation, especially if war incidence between
kings ruling in these other polities had been very high. First, it is worth noting that the
average rate of war participation is if anything slightly lower in the non-queen polities (forexample, average external war participation is .19 and Balance of Power war participationis .14 in our auxiliary sample of non-queen polities, while the equivalent figures are .25 and
31 This provides reassurance that idiosyncratic features of these polities, such as the changes that allowed forpossible non-hereditary succession in Russia around 1722, do not drive our overall results.

31

.21, respectively, in the main sample of queen polities.)
Second, to address this concern directly, in column (8) of Table A.6, we present a specification which pools together the queen and non-queen polities. We interact our instrumentswith indicators of whether it is a queen polity, to retain predictive power in the first stage.
While the first stage is still weaker under this approach than in our primary specifications,the overall results remain largely unchanged.
In Table A.7, we also present an alternate reign-level specification. In our main specifications, which use annual data, the queen variable varies at the level of the reign, while thewar variables vary at the level of the year. While we adjust our standard errors to accountfor the use of reign-level variation through our clustering strategy, there is still a separate
concern that longer reigns will be given more weight in the annual panel, which may affect our coefficient estimates. To address this concern, we collapse our annual data to thereign level, and run reign level regressions in which the dependent variable is the numberof years the polity is at war, controlling for the length of the reign (in years). We continue to
use polity fixed effects and also incorporate century fixed effects. Here we also cluster the
standard errors at the polity level. Since there are 18 clusters, and standard errors may beunderstated when there are fewer than 30-40 clusters [Cameron et al., 2008], we additionallyadjust the errors using a wild bootstrap procedure (with 1,000 replications). The results inTable A.7 verify the robustness of our main results to this alternate reign level approach.
In Table A.8, we address the concern that the decision of two polities to fight in a war
may not be independent. Our primary specifications, which examine war participation inan annual panel with standard errors clustered at the polity (by century) level, may not account for this form of correlation across standard errors. We therefore convert our data into
dyadic format, where the units are comprised of polity year pairings for each year in which
both polities are in existence. Using this data, we implement specifications in which theindependent variable is whether there is a queen in either polity of the dyad, and the dependent variable is whether the polities are engaged in the same balance of power war during agiven year. We also include decade fixed effects, dyad fixed effects and our standard control
32

variables (either as an indicator of whether either polity in the pair has a given characteristic
in the case of dichotomous controls or as averages in the case of continuous controls). We
cluster the standard errors at the dyad level, as well as the dyad by century level. Table A.8
presents these results. We find that the queen effect remains in place across these specifications, suggesting that correlated across countries fighting in the same wars do not drive ourresults. In addition to presenting these dyadic results, in the next section, we also examine
war participation disaggregated by which polity was the aggressor in the conflict.

5.4

Disaggregating War Effects to Examine the Reign Capacity and Perceived Weakness Accounts

In this section, we further disaggregate the effect of queens on war participation to explore
accounts of why these effects arise.
First, we examine if increased war participation stems from new wars that the reign initiated or from the continuation of old wars that were started previously. Columns (2)-(3)Table 7 show this decomposition. Note that the coefficients on these two outcomes add up
to the coefficient in column (1). The magnitude of the coefficients for the reign entered outcome (.21) and the reign continued outcome (.11) suggest that both entry and continuation
contribute to the queen effect on Balance of Power wars.
Second, we gauge whether queens participate more in wars in which their polity attacked, or in which their polities were attacked, utilizing Wright’s coding of who initiatedthe conflict. Since the aggressor coding is missing for some observations, column (4) shows
the queen effect on Balance of Power war participation in the sub-sample of observations forwhich aggressor variables are available. Columns (5)-(6) present the disaggregated effects.
The coefficients indicate that the queen effect on balance of power war participation (.33)
stems disproportionately from participation in wars in which the polity attacked (.26) thanin wars in which the polity was attacked (.07). This indicates that queens did not end up at
war solely because they were attacked, and that the perceived weakness idea alone cannot

33

account fully for the effects. Since attacking as an aggressor, by definition, represents theactions of one side, these results are also less subject to the concern that correlated standard
errors drive the estimates, which is a concern regarding the war participation outcome, as
this variable, by definition, involves two sides. In that regard, the results in Table 7 complement the war participation estimates in the dyadic specification, to address concerns that
this type of correlation drives the estimated effects.
If the effects on aggressive war participation are driven by cases of co-rule, in which thehusband is an official co-monarch, then it is difficult to interpret them as an effect of female
rule and female decision-making. To address this possibility, in Table A.9, we presents theestimates for the Solo queens, who ruled as the sole regent (i.e., their spouse, if they had one
during their reign, did not hold the title of official co-regent). We find the same results holdhere, which suggests that the effects on aggressive war participation do not simply reflect
decisions made by co-ruling kings.
Did queens typically succeed by pursuing aggressive participation? After all, if monarchs lost wars they engaged in, this could produce major drawbacks, such as loss of territory.
While we cannot observe who won wars, we can observe whether polities gained or lost
territory over the course of particular reigns. This is directly relevant since territorial expansion was a major objective of balance of power wars among European actors. In the second
half of Table A.7, we examine effects on indicators of territorial gain, loss and a ordered variable that includes both. These results demonstrate that queenly reigns are associated witha greater likelihood of territorial gain. Of course territory can be gained for reasons otherthan war. Table A.10 divides the sample based on years in which polities were involved inexternal wars, and shows that the queen effect on territorial gain is both larger and more
precisely estimated for the years in which there were external wars. This provides suggestive evidence that wars played some role in the territorial expansion of queenly reigns. But
overall, we interpret our estimates as indicating that the aggregate set of policies pursued byqueenly reigns, including participation in wars of aggression, led to the greater likelihoodof territorial expansion.
34

The effects in Tables 7, A.7 and A.10 show that queens participated more in wars of aggression. If this reflects greater capacity in queenly reigns, and spouses further bolstered
this capacity providing additional resources and support for the conduct of war, we should
see that the tendency to participate in wars of aggression was especially large among married queens. Table 8 examines whether a queen’s proclivity to attack or be attacked varies
by marital status. As discussed in the data section, a monarch is married in reign if they
have a living spouse during their reign; so a monarch can be unmarried because their reign
preceded marriage, because they never married or because they became widowed.32
We interact this married in reign variable with the Queen indicator, the instruments, andthe control variables. Since marital status varies by age, and age may influence war aggression, we also control for equivalent age at accession interactions. To account for missing
values, we include indicators of whether the marriage and accession age variables are missing, and include interaction terms with these indicators and the endogenous variable, as
well as the instruments and controls.
These results are presented in Table 8. The first two columns show a distinct pattern.
Married queens participate more in wars of aggression, relative to both unmarried queens,
as well as unmarried kings and married kings. Conversely, unmarried queens are most
likely to participate in wars in which their polity is attacked, relative to married queens aswell as kings, married or unmarried.
These results provide two insights regarding the reign capacity and perceived weakness
accounts. First, the differential tendency of married queens to participate in wars of aggression is consistent with the idea that marriage enhanced the reign capacity of queens,enabling them to pursue aggressive war policies. In contrast, marriage did not exert anequivalent effect for kings. For example, in column (1), coefficient on the Married in Reignvariable, which captures the effect of being married for kings, is .027 (and statistically insignificant).
32 For example, there are 10 reigns in which a queen is unmarried during her reign, while there are only 3queens who never married. Similarly, there are 36 reigns in which a king is unmarried during his reign, while
there are only 19 kings who never married.

35

Second, the differential tendency of single queens to get attacked (relative to all othermonarchs) provides some support for the perceived weakness account — i.e., it suggeststhat unmarried queens, specifically, may have been perceived as weak and easy to attack.
It is again important to consider if these effects on aggressive war participation, concentrated among married queens, actually simply reflect the dictate’s of a queen’s husband. We
present evidence against this in several ways. First, we posit that a queen’s husband is most
likely to be influential when he is also an official co-regent. But when we eliminate all casesof queens co-ruling with a co-regent in columns (3)-(4), we continue to observe the same
pattern of results for the solo queens. This suggests that even married queens who were soleregents had greater capacity to fight wars of aggression; and even unmarried queens who
were sole regents tended to be attacked to a greater degree.
In Table 8, the coefficients on the Solo Queen x Married interaction terms are even larger
than those on the Queen x Married interactions. This raises the possibility that king consorts
who were not official co-regents may have been especially militaristic and dominated warmaking decisions. It is even possible that marriages may have been organized strategicallyto wed queens to these militaristic spouses. To account for this, we control for whether the
spouses of monarchs had any military experience prior to the marriage. This variable measures whether they had direct experience as military lieutenants or commanders, or presided
over a war as the adult monarch of a polity prior to their marriage. When we include thisspousal military experience variable and its interactions in columns (5)-(6), the results continue to hold. This suggests that the differential tendency of married queens to participate
as aggressors reflects some factor beyond the militaristic tendency of their spouses. In ourview, these latter estimates provide the most compelling evidence that married queens weremost inclined to fight in wars of aggression.
In addition, qualitative accounts also suggest that queens who involved their spouses
in state matters did not necessarily retract their own decision-making authority in thosematters. For example, Ferdinand played a prominent role during Isabella’s rule, but when
they clashed over important policy issues, such as who the throne would pass to in the36

event of her death, she did not retract her position [Jansen, 2002, p.15]. In addition, thoughFerdinand played a critical in military confrontations, Isabella also never withdrew fromthis realm. During the internal conflict against Juana, she rode throughout her territory togarner support for her cause [Jansen, 2002, p.21]. Her military role only expanded during
the war against Granada:
An “accomplished strategist,” she ultimately moved out from behind the scenes
to center stage, taking the field with the Castilian army in Cordoba, Malaga,
Baeza, and, at last, in Granada, where she appeared wearing armor and mounted
on a warhorse (ibid).
In short, though Isabella relied on her husband, she retained her own decision-making
authority.
In Table A.11, we present two additional checks. We combed through historical records
and found three cases in which the queens could have been considered weak owing to either
their public posture or mental state.33 It is unlikely that these women were major drivers ofdecision-making given their stances, which raises concerns that their husbands may havebeen the key decision makers. However, in columns 1-4 of Table A.11, we find that theour results continue to hold even after we drop these three queens from the sample. This
reinforces the idea that even among queens who were willing and able to serve as decision
makers, married queens pursued war more aggressively.
We also consider the possibility that married queens may have pursued aggressive war
policies not because of capacity, but rather, because they were more likely to have had legitimate male heirs to whom they could bequeath their kingdom. However, columns 5-8 ofTable A.11 show that the results are unaffected if we control for the interaction of queens
with whether the monarchs had a legitimate male child.
33 One case is Juana la Loca who co-ruled Leon and Castile over 1504-1506. As her name suggests, Juana wasmentally incapacitated. Another case is Mary II who co-ruled England with William III over 1689-1695, but
ceded power to him willingly. A third is Ulrika Eleanora, who ruled Sweden (1718-1719), publicly declaredthat women were unfit to rule and abdicated when the Riksdag refused to make her husband a co-monarch.

37

Since there are only 10 unmarried queen reigns and 24 married queen reigns in our sample, this raises the concern that our overall effects on marital interactions are driven by aparticular queen or a particular reign. To verify this is not the case, Figure 4 plots the coefficients and confidence intervals on the marital interaction terms, from specifications withqueens who were sole regents, including all relevant controls such as the spousal military
experience controls. This figure shows that the effects on aggressive war participation are
also insensitive to the exclusion of each queen.
It is also worth noting that the results pattern we observe in Tables 8 and A.11 make itseem unlikely that our results are driven by bias in the Wright’s aggressor coding. For the
results to emerge because of coding bias, it would have to be the case that there is overattribution of aggression to female monarchs who had spouses during their reign relative
to male monarchs who had spouses during their reign; and under-attribution of aggression
to female monarchs who were unmarried during their reign relative to male monarchs who
were unmarried during their reigns. This seems unlikely as it would require relatively precise awareness around the timing of marriage and widowhood.
Next, we examine the second way in which married queens may have had greater capacity to carry out war — through more alliances. We were able to track whether each polity
fought in wars alone, or alongside another polity fighting on its side, for 73 percent of the balance of wars in our sample.34 From this coding effort, we generated an indicator of whether
the polity fought with at least one ally. This serves as the dependent variable in columns(7)-(8) of Table 8. By construction, it is only defined for the years in which a polity was participating in a war. The table shows heterogenous effects based on martial status. Married
kings were more likely to fight alongside an ally (relative to unmarried kings). Moreover,
the tendency to fight with an ally was even greater among married queens (relative to married kings, unmarried kings and unmarried queens). For example, the effect is .117 larger
for married queens than married kings in column (7), and .266 larger for married queens
34 This coding required us to have detailed descriptions of each war, to discern which polities fought onwhich side. This information is not available from Wright, and had to be constructed from various sources.

38

than kings in column (8), which are 18% and 42% above the mean, respectively. These results suggest that marriage brought alliances for all monarchs, but disproportionately so forqueens. This is consistent with the idea that male spouses may have been better positioned
to forge alliances because they were typically more tied to military matters in their homepolities, compared to female spouses.
Overall, the results from Table 8 are consistent with the idea that asymmetries in thedivision of labor, and more alliance formation in queenly reigns relative to kingly reigns
served to strengthen the relative capacity of queens, facilitating their greater participationin external wars. They also corroborate the idea that spouses were unique in being able toprovide this support: They did not directly pose a threat since they typically could not serveas the monarch, and could bring in an alliances, particularly if they originated from otherpolities.35

5.5

Addressing Alternative Accounts

In this section we consider and present evidence against three alternative accounts. One
alternative account posits that queens may have chosen to fight to signal their strength.
Influential accounts of war, such as the bargaining model [Fearon, 1995], imply that states
may fight in order to send a costly signal that they are not as militarily weak as others
perceive. However, if queens were signaling, it would be most advantageous for them tosend this signal early in the reign, to maximally ward off potential attacks over the durationof their rule. This suggests we should observe more aggressive war participation earlier intheir reign. In Table 9, we test this idea by introducing an interaction between the queen
variable and two indicators: one that demarcates the second half of the reign and anotherwhich demarcates the period beyond the first two years of the reign. In these specifications,
we also control for the overall length of reign. For balance of power war participation, as
well as the polity attacked variable, the interaction term is statistically insignificant and also
positive in sign (suggesting, if anything, more war later). This suggests that the queen effects
35 In fact, in our sample, all spouses of queens did originate from other polities.

39

on war do not arise from signaling, specifically.
A second alternate account suggests that aggressive actions undertaken during a queen’s
reign may reflect the actions a foreign minister, rather than the queen herself. This conjecture
is based on two assumptions – that foreign ministers are more aggressive than monarchs,
and that women rulers are more easily influenced by ministers than male rulers.
Scholars throughout history have questioned the second assumption. In 1630, Gregorio
Leti, who produced a biography of Elizabeth I, wrote:
I do not know why men have conceived such a strange and evil opinion of
women so as to consider them incapable of conducting important business . . . if
men see a person of that sex govern a state with prudence and success they will
inevitably take the glory away from her and attribute it to her favorites and ministers. [Monter, 2012, p.153].
Although this assumption has been questioned, if female rulers were in fact more easily
influenced by male ministers, these effects should be larger if they acceded to the throne at a
younger age. This is when they were the most impressionable, and may not have developed
clear policy positions of their own. To test this idea, we introduce interactions of age at accession with the queen variable. Columns (7)-(9) of Table 9 indicate that there are no differential
effects of queens on war based on the age at which they came to power. The queen effecton war is similar regardless of the age at which monarchs acceded. This seems inconsistent
with the idea that ministers were the main force in making war-related decisions.
Rather, these results are more consistent with qualitative accounts that queens did notalways passively receive the advice of ministers. For example, when Frederick invaded
Silesia, Maria Theresa’s elderly ministers advised her to make concessions— yet she refuted
their advice and fought back as she wanted retain all of her territory [Beales, 2014, p.133].
Finally, we examine the account that queens pursued external war strategically because
they faced greater internal instability and sought to unify the polity against an external threat[Ostrom and Job, 1986]. Table 10 shows that having a queen did not affect participation in40

civil war, or differentially impact the length of a monarch’s reign.36 Moreover, it had no
significant impact on the likelihood that a monarch died of unnatural causes including regicide. In addition, having a queen did not bring about the demise of the kingdom: Table 10shows that were no significant effects on whether a kingdom ended, either through partition, unification or capture with another kingdom, or by becoming a republic. This suggeststhat greater internal instability was unlikely to be a key motivating factor for why queens
pursued external war.

6

Conclusion

A common perspective posits that women are less violent than men, and therefore, states
led by women will be more peaceful than states led by men. We examine the effect of female
rule on conflict historically, focusing on Europe over 1480-1913. Our analysis examines how
states fared in terms of conflict under female rulers, which is conceptually distinct from thequestion of whether women, as individuals are less violent than men. We exploit genderof the first-born and presence of a sister in the previous reign as instruments for whether
queens come to power. We find that queenly reigns participated more in inter-state wars relative to kingly reigns, and these effects arise from greater participation in Balance of Powerwars, which took place among European actors. Queens were also more likely to gain territory over the course of their reigns, but were no more likely than kings to experience civil
wars or other internal conflicts.
Notably, queens engaged more in wars in which their polity was the aggressor, though
this effect varies based on marital status. Among unmarried monarchs, queens were attacked more than kings. Among married monarchs, queens participated as attackers morethan kings, and were also more likely to fight alongside allies. These results are consistent
36 It is possible that the distinction between external wars ad civil wars may be unclear in cases where a civil

war results in the creation of a new unit. Column (10) of Table A.5 verifies that queens lead to greater war
participation under an alternate measure of war that aggregates together participation in any war — external
or internal.

41

with an account in which unmarried queens were attacked as they were perceived to be
weak, while married queens had greater capacity to attack, based on both alliances and awillingness to use their spouses to help them rule.
These effects suggest that war policy differed under female leaders than male leaders, inpart because women tended to organize their rule differently than their male counterparts.
These different tendencies themselves reflected prevailing gender norms of the day. For
example, queens were more inclined to put their husbands into positions of power to help
them rule, even if they were not their official co-regent; but under prevailing gender norms,
kings were less inclined to do the same with female spouses. In addition, queens were more
likely to benefit from alliances based on marriage, since male spouses could hold positionsin the militaries of their home countries, and were therefore better positioned to cement
alliances. In contrast, direct military involvement remained taboo for women. In this regard,
gender norms ultimately played a role in why female rule led to greater participation in warof aggression, and in shaping the conflict trajectories of states under male and female rule.
While we cannot extrapolate directly from these results to the current era, we can consider a few potential implications for today’s rulers. These conjectures seem relevant since
existing work has already documented a positive correlation between female executives anda state’s conflict behavior in the modern period [Koch and Fulton, 2011]. Broadly speaking,we may expect to observe systematic differences in war policy based on a ruler’s gender ifmale and female leaders continue organizing their rules differently, including in who they
recruit into their governments, and who they enlist to play supportive roles. The maritalinteractions we uncover for Europe historically also suggest that perhaps the largest genderbased effects today arise in weakly institutionalized settings, where families continue to playa role in solving the challenge of who to trust in leading. This should be the subject of future
research, in further study of gender and conflict.

42

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49

Figure 1
Queen and Non-Queen Polities

Notes. This figure shows the queen polities, non-queen polities and polities not included in our sample. It was created by overlaying six Georeferenced
Historical Vector maps from Euratlas at the turn of each century between 1500-2000. Each polity was identified and chosen from one of these six maps tominimize displayed territorial overlap among polities. The territorial boundaries for different polities are from different time periods, and do not necessarily
match present day borders or show the maximum geographical area covered by each polity historically.

Figure 2
Circumstances under which Queens Came to Power

Queens from cases
where previous
monarchs had…
(29)

ChildrenMore than one child

21

16

Only
child

No Children

5First bornchild female

First bornchild male

8

0

5

First bornchild male

Missing
genderFirst bornchild female

6

1

9

At least one other malechild living at accession

All male children
dead at accession

SistersNo
sisters

SistersNo
sisters

6

2

0

0

No
Sisters sisters

32

Sisters

1

All male children
dead at accession

0

5

1

No
No
Sisters sisters
sisters0

No male children
born before
accession

No other male At least one male childliving at accession
children

4

1

3

5

SistersNo
sisters Sisters

1
No
Sisters sisters

1

0

3

0

5

No
sisters0

Notes. This figure shows the circumstances of the previous monarchs for the 29 queens in our sample. For example, the previous monarchs had children in 21 of 29 queen cases
and lacked children in 8 cases. Among these latter 8 cases, the previous monarchs had sisters in 5 cases and had no sister in 3 cases. The 5 cases where all male children were deadat accession when the previous monarchs had a first born male child includes one case where the death year of one of the sons is missing. Aqua cells show all cases in which there
was at least one sister among previous monarchs. Grey cells show all the cases in which there was no male first born child among previous monarchs.

Figure 3
Dropping Each Queen

Notes. This figure plots the coefficient estimates and 90 percent confidence intervals on the queen variable (leftpanel) and the solo queen variable (right panel) in regressions of participation in balance of power wars, dropping
each queen one at a time. The estimates shown with the blue triangles do not drop any queen.

Figure 4
Estimates Dropping Each Queen: Marital Interactions

Notes. This figure plots the coefficient estimates and 90 percent confidence intervals on the Solo Queen x Married
in Reign interaction term, in regressions of the Polity Attacked variable (left panel) and the Polity was Attacked
variable (right panel), after dropping each queen one at a time. The estimates in the blue triangles do not drop any

Table 1
Summary Statistics of Key Variables
Variable

Obs

Mean

Std. Dev. Min Max

Dependent Variables
In External War
In Imperial War
In Defensive War
In Balance of Power War
In Balance of Power War - Reign Entered
In Balance of Power War - Reign Continued
In Balance of Power War - Kingdom Attacked
In Balance of Power War - Kingdom was Attacked
In Civil War
Reign Length
Monarch Killed
Polity Ends in this Reign
Polity is Partitioned / Captured / Unites with Another
Polity becomes a Republic
Any Ally in Balance of Power War

3586
3586
3574
3577
3577
3577
3563
3563
3586
3586
3058
3586
3559
3559
530

0.248
0.034
0.013
0.214
0.164
0.050
0.086
0.124
0.070
30.746
0.145
0.085
0.067
0.001
0.636

0.432
0.181
0.114
0.410
0.370
0.219
0.281
0.330
0.255
15.677
0.352
0.279
0.250
0.029
0.482

0
0
0
0
0
0
0
0
0
1
0
0
0
0
0

1
1
1
1
1
1
1
1
1
66
1
1
1
1
1

Independent Variables
Queen
Solo Queen
Married in ReignFirst-born male (of previous monarchs)
Sister (of previous monarchs)
Total Siblings (of previous monarchs)
First-born missing gender (of previous monarchs)
Missing gender sibling (of previous monarchs)
At least one child with missing birth year (of previous monarchs)

3586
3586
3410
3586
3586
3586
3586
3586
3586

0.160
0.131
0.836
0.502
0.740
4.302
0.019
0.064
0.118

0.366
0.337
0.370
0.500
0.438
4.145
0.137
0.245
0.323

0
0
0
0
0
0
0
0
0

1
1
1
1
1
22
1
1
1

At least one child without missing birth year (of previous monarchs)
Co-rulers unrelated (among previous monarchs)

3586
3586

0.821
0.008

0.383
0.088

0
0

1
1

Table 2
The Instruments
Male First Born (Previous Monarchs)

Sister (Previous Monarchs)

Yes

84

54%

Yes

138

72.0%

No

71

46%

No

55

28.0%

Notes. The left-side of the table shows the fraction of cases in which the previous monarchs had a male firstborn child among the set of cases in which they had any children. The right side of the table shows the fractionof cases in which the previous monacrchs had a sister.

Table 3
Queens and War: OLS Results

VARIABLES
Queen

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

In External
War

In External
War

In Balance ofPower WarIn Balance ofPower WarIn Defensive
War

In Defensive
War

In Imperial
War

In Imperial
War

0.081*[0.043]0.086**[0.043]0.097**[0.041]0.100**[0.042]-0.003[0.007]0.002[0.006]-0.013[0.026]-0.017[0.026]

Observations
3,586
3,586
3,577
3,577
3,574
3,574
3,586
3,586
R-squared
0.403
0.407
0.396
0.398
0.204
0.260
0.127
0.142
Specification
OLS
OLS
OLS
OLS
OLS
OLS
OLS
OLS
Standard Controls
Y
Y
YY
Notes. Variables not shown include polity and decade fixed effects. Robust standard errors clustered at the polity by century level are shown inparentheses. *** is significant at the 1% level, ** is significant at the 5% level, * is significant at the 10% level.

Table 4
Queens and War: IV Results(1)
In External War(2)
In Balance of Power War(3)
In Defensive War(4)
In Imperial War

Queen

0.265*[0.155]0.299**[0.146]-0.033[0.053]0.044[0.073]Observations
R-squared

3,586
0.390

3,577
0.375

3,574
0.251

3,586
0.131

Instruments

FBM r-1 & Sister r-1

FBM r-1 & Sister r-1

FBM r-1 & Sister r-1

FBM r-1 & Sister r-1

Y

Y

Y

Y

Queen

Queen

Queen

Queen

-0.212***-0.203***-0.213***-0.212***[0.064][0.064][0.064][0.064]Sisterr -1

0.190***

0.190***

0.190***

0.190***

Observations
R-squaredStandard Controls
Kleibergen-Paap F-statistic
Hansen J-statistic
Hansen J-statistic Chi-sq(2) p-val[0.051]
3,586
0.354
Y
13.69
0.015
0.9

[0.051]
3,577
0.355
Y
13.43
0.20
0.66

[0.051]
3,574
0.354
Y
13.66
1.00
0.32

[0.051]
3,586
0.354
Y
13.69
0.32
0.57

VARIABLES

Standard Controls

First Stage:
FBMr-1

Notes. Variables not shown include polity and decade fixed effects. FBM r-1 denotes previous monarchs had a First-Born Male. Sister r-1
denotes previous monarchs had a sister. Robust standard errors clustered at the polity by century level are shown in parentheses. *** issignificant at the 1% level, ** is significant at the 5% level, * is significant at the 10% level. The Hansen J-statistic and Chi-sq(2) p-val
present the test of overidentifying restrictions.

Table 5
Siblings and Wars of Succession(1)
In
External
War(2)
In Balanceof Power
War

(3)
In
External
War(4)
In Balanceof Power
War

(5)
In
External
War

(6)
(7)
In Balance
Inof Power Defensive
War
War

(8)
In
Imperial
War

(9)
In
Defensive
War

(10)
In
Imperial
War

(11)
In
Defensive
War

(12)
In
Imperial
War

Queen

0.288*[0.151]0.324**[0.147]0.364**[0.168]0.398**[0.155]0.379**[0.168]0.414***[0.160]0.076[0.089]-0.033[0.053]0.044[0.073]-0.028[0.058]0.076[0.089]Observations
Specification
Standard Controls
Total Siblings

3,586
IV
Y
Y

3,577
IV
Y
Y

3,586
IV
Y

3,575
IV
Y

VARIABLES-0.028[0.058]

3,586
3,575
3,574
3,586
3,574
3,586
3,574
3,586
IV
IV
IV
IV
IV
IV
IV
IV
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
No
No
No
No
No
No
No
No
SampleAll wars
All wars Succession Succession Succession Succession All wars
All wars Succession Succession Succession Succession
Wars
Wars
Wars
Wars
Wars
Wars
Wars
Wars
Notes. Variables not shown include polity and decade fixed effects. Robust standard errors clustered at the polity by century level are shown in parentheses. *** issignificant at the 1% level, ** is significant at the 5% level, * is significant at the 10% level.

Table 6
Falsification Tests(1)

VARIABLESFBM rSister r
FBM r-1
Sister r-1

Observations
Specification
Standard Controls
Total Siblings
Sample(2)
In Balance
In External of Power
War
War

(3)
In
Defensive
War

(4)

(5)

In Imperial
War

In Civil
War

(6)

(7)
In Balance
In External of Power
War
War

(8)
In
Defensive
War

(9)

(10)

In Imperial
War

In CivilWar-0.032-0.0350.010-0.008-0.008

-

-

-

-

-

[0.035][0.033][0.014][0.019][0.024]

-

-

-

-

-

0.061

0.044

0.019

0.029

0.001

-

-

-

-

-

[0.042][0.039][0.014][0.028][0.032]

-

-

-

-

-

-

-

-

-

-

-0.044-0.057

0.008

0.016

-0.017

-

-

-

-

-

[0.072][0.057][0.035][0.012][0.027]

-

-

-

-

-

-0.030-0.029-0.069

0.025

0.020

-

-

-

-

-

[0.065][0.052][0.049][0.018][0.021]

3,319
OLS
Y
Y
Queen
Polities

3,310
OLS
Y
Y
Queen
Polities

3,307
OLS
Y
Y
Queen
Polities

3,319
OLS
Y
Y
Queen
Polities

3,302
OLS
Y
Y
Queen
Polities

2,903
2,818
2,903
2,903
2,900
OLS
OLS
OLS
OLS
OLS
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Non-Queen Non-Queen Non-Queen Non-Queen Non-Queen
Polities
Polities
Polities
Polities
Polities

Notes. Variables not shown include polity and decade fixed effects. FBMr-1 denotes previous monarchs had a First-Born Male. Sisterr-1 denotes previous
monarchs had a sister. Robust standard errors clustered at the polity by century level are shown in parentheses. *** is significant at the 1% level, ** issignificant at the 5% level, * is significant at the 10% level.

Table 7
War Entry and War Aggression

VARIABLES
Queen

(1)
In Balanceof Power
War

(2)

(3)

(5)

(6)

Reign
Continued(4)
In Balanceof PowerWar

ReignEnteredPolity was
Attacked

PolityAttacked

0.324**[0.147]0.211*[0.116]0.113[0.142]0.331**[0.149]0.067[0.111]0.264*[0.149]

None
None
None
Sample restriction?
Polity Attack variables defined
Observations
3,577
3,577
3,577
3,563
3,563
3,563
Specification
IV
IV
IV
IV
IV
IV
Standard Controls
Y
Y
Y
Y
Y
Y
Total Siblings
Y
Y
Y
Y
Y
Y
Notes. Variables not shown include polity and decade fixed effects. Robust standard errors clusteredat the polity by century level are shown in parentheses. *** is significant at the 1% level, ** issignificant at the 5% level, * is significant at the 10% level. Columns 5 and 6 retricts the sample toobservations for which the Polity was Attacked and Polity Attacked variables are defined.

Table 8
Queens and War: Effects by Marital Status

VARIABLES
Queen
Queen x Married in Reign
Married in Reign
Solo Queen
Solo Queen x Married in Reign

Observations
Specification
Standard Controls
Control Total Siblings
Control Accession Age
Control Spousal Military Experience(1)
PolityAttacked(2)
Polity was
Attacked(3)
PolityAttacked(4)
Polity was
Attacked(5)
PolityAttacked(6)
Polity was
Attacked(7)(8)

Any Ally

Any Ally-0.306[0.324]0.414*[0.214]0.027[0.058]-0.737***[0.231]-0.611***[0.216]0.004[0.050]-0.058[0.069]-0.427[0.345]0.608**[0.269]-0.005[0.054]0.860***[0.265]-0.688***[0.223]0.055[0.070]-0.384[0.360]0.736**[0.302]-0.020[0.061]0.879***[0.312]-0.899***[0.252]-0.525[0.391]0.642***[0.236]
0.291*[0.149]-0.314**[0.139]-0.522[0.409]0.788***[0.259]

3,563
IV
Y
Y
Y

3,563
IV
Y
Y
Y

3,459
IV
Y
Y
Y

3,459
IV
Y
Y
Y

3,372
IV
Y
Y
Y
Y

3,372
IV
Y
Y
Y
Y

530
IV
Y
Y
Y
Y

517
IV
Y
Y
Y
Y

No warNo reigns No reigns No reigns No reigns No reigns
years &
with cowith cowith cowith cowith co- Reigns withrulingrulingrulingrulingrulingco-ruling
None
NonequeensqueensqueensqueensqueensQueensSample Restriction?
Notes. Variables not shown include polity and decade fixed effects. Robust standard errors clustered at the polity by century level are shown inparentheses. *** is significant at the 1% level, ** is significant at the 5% level, * is significant at the 10% level. Accession age is the average age ofaccession of the monarchs in the reign. Spousal military experience is one if the spouse had any military experience prior to marriage.

Table 9
Effects based on Timing and Age

VARIABLES
Queen
Queen x After second half of reign
After second half of reign
Queen x After first two years of reign
Queen x Accession age
Accession age(1)
In Balanceof Power
War

(2)

(3)

(5)

(6)

Polity was
Attacked(4)
In Balanceof PowerWar

PolityAttacked

0.310**[0.155]0.089[0.299]-0.257*[0.150]0.099[0.191]
-

(8)

(9)

Polity was
Attacked(7)
In Balanceof PowerWar

PolityAttacked

PolityAttacked

Polity was
Attacked

0.062[0.106]-0.023[0.265]-0.294*[0.165]0.076[0.188]0.013[0.035]-0.203[0.144]0.137[0.156]-0.014[0.024]-0.088[0.114]-0.038[0.165]0.026[0.027]-0.304*[0.174]-0.011[0.016]0.003[0.002]0.208[0.170]0.014[0.015]0.001[0.002]0.105[0.144]-0.025[0.018]0.002[0.002]

Observations
3,577
3,563
3,563
3,577
3,563
3,563
3,577
3,563
3,563
Specification
IV
IV
IV
IV
IV
IV
IV
IV
IV
Standard Controls
Y
Y
Y
Y
Y
Y
Y
Y
Y
Total Siblings
Y
Y
Y
Y
Y
Y
Y
Y
Y
Reign Length
Y
Y
Y
Y
Y
Y
Notes. Variables not shown include polity and decade fixed effects. Robust standard errors clustered at the polity by century level are shown in parentheses. *** issignificant at the 1% level, ** is significant at the 5% level, * is significant at the 10% level.

Table 10
Queens and Internal Instability(1)

VARIABLES
Queen

(2)

(3)

In CivilWar

ReignlengthMonarchkilled-0.024[0.108]-2.777[10.472]-0.440[0.304](4)(5)
Polityunites/partitioned/
Polity ends captured
0.113[0.172]0.040[0.161](6)
Politybecomes
republic-0.001[0.003]Observations
3,586
3,586
3,058
3,586
3,559
3,559
Specification
IV
IV
IV
IV
IV
IV
Standard Controls
Y
Y
Y
Y
Y
Y
Total Siblings
Y
Y
Y
Y
Y
Y
Notes. Variables not shown include polity and decade fixed effects. Robust standard errors clusteredat the polity by century level are shown in parentheses. *** is significant at the 1% level, ** issignificant at the 5% level, * is significant at the 10% level. Polity ends denotes it is the lastmonarchy of the entity, and Polity becomes republic denotes the monarchy becomes a republic.

Table A.1
Polities with Queens

Non Queen Polities

Burgundy and the Low Countries
Portugal
Spain
Austria
The Duchy of Bourbonnais
The Duchy of Brittany
The Duchy of Lorraine
The Farnese and Bourbons in Parma
The Grand Duchy of Luxemburg
The Kingdom of England
The Kingdom of Navarre (Pamplona)
The Kingdom of Scotland
The Kingdom of Sweden
The Kingdoms of Leon and Castile
The Medici and their Successors in Florence
The Modern Netherlands
The Principality of Monaco
The Tsardom of Russia

Modern Bulgaria
Modern Greece
Modern Serbia and Yugoslavia
The Este in Ferrara and Modena
The Gonzaga in Mantua
The Holy Roman Empire
The House of Liechtenstein
The House of Savoy
The Kingdom of Bohemia
The Kingdom of Denmark
The Kingdom of France
The Kingdom of Hungary
The Kingdom of Montenegro
The Kingdom of Naples and Sicily
The Kingdom of Poland
The Kingdom of the Belgians
The Montefeltro and Della Rovere in Urbino
The Visconti and Sforza in MilanTable A.2
Alternate Instrument Sets
VARIABLES
Queen

Observations
Sample(1)
In Balance of Power War(2)
In Balance of Power War(3)
In Balance of Power War(4)
In Balance of Power War

0.306**[0.147]0.326**[0.148]0.341[0.214]0.364[0.266]

3,577
Queen polities

3,577
Queen polities

3,577
Queen polities

4,081
Queen polities

FBMr-1 & Sister r-1 & FBMr-1 FBMr-1 & Sister r-1 & FBM rInstruments

X Sister r-1

1 X Sister r-1 No Childrenr-1

FBMr-1

Sisterr-1

Kleibergen-Paap F-statistic

8.9

9.9

12.99

12.15

Hansen J-statistic

0.26

2.10

-

-

Hansen J-statistic Chi-sq(2) p-val
0.88
0.34
Notes. Variables not shown include polity and decade fixed effects. All specifications use Sister, First-born male and their interactions with an indicator ofwhether the polity ever had a queen as instruments for queen. Robust standard errors clustered at the polity by century level are shown in parentheses. *** issignificant at the 1% level, ** is significant at the 5% level, * is significant at the 10% level. The Hansen J-statistic and Chi-sq(2) p-val and Chi-sq(2) p-val
present the test of overidentifying restrictions for the specifications in columns (1) and (2) when there are multiple instruments.

Table A.3
Wars and Ruler Death in Previous Reign
Examining Outcomes in Previous Reign

Controlling for Previous Reign Variables

(1)

(2)
(3)
(4)
(5)
(6)
Balance ofExternal
Power Defensiv Imperial Reign Monarch
WarWare WarWarLength- Killed Previous Previous Previous Previous Previous Previous
Reign
Reign
Reign
Reign
Reign
Reign

In
External
War

In
BalanceIn
In
of Power Defensive Imperial
War
War
War

In
External
War

In
BalanceIn
In
of Power Defensive Imperial
War
War
War

Queen

-0.022[0.226]0.200[0.235]0.015[0.094]-0.015[0.200]-1.841[8.822]0.045[0.340]0.302**[0.152]0.313**[0.147]-0.028[0.057]0.089[0.089]0.349*[0.183]0.385**[0.185]-0.033[0.066]0.138[0.118]Observations

3,515

3,515

3,515

3,515

3,515

3,125

3,515

3,506

3,503

3,515

3,125

3,116

3,123

3,125

Y
Y

Y
Y

Y
Y

Y
Y

Y
Y

Y
Y

Y
Y

Y
Y

Y
Y

Y
Y

Y
Y

Y
Y

Y
Y

Y
Y

Y

Y

Y

Y

Y

Y

Y

Y

VARIABLES

Standard Controls
Total Siblings
Previous Reign Controls:
External War?
Balance of Power War?
Defensive War?
Imperial War?
Reign Length?
Monarch Killed?

(7)

(8)

(9)

(10)

Y
`

(11)

(12)

(13)

(14)

Y
Y
Y

Y
Y
Y
Y
Notes. Variables not shown include polity and decade fixed effects. Robust standard errors clustered at the polity by century level are shown in parentheses. *** is significant at the
1% level, ** is significant at the 5% level, * is significant at the 10% level. Previous reign controls refer to whether the previous reign participated in certain types of wars, the killingof a monarch, or the average length of the previous reign, as indicated in each row.

Table A.4
Summary Statistics of Additional Variables
Variable

Obs

Mean

Std. Dev.

Min

Max

Dependent Variables
Number Participants-Balance of Power Wars
Number Participants - External Wars
In All Wars
Reign Level - in Balance of Power War
Reign Level - In External War
Reign Level - Polity Attacked
Territorial Change
Territorial Gain
Territorial Loss

812
903
3,586
193
193
193
166
166
166

6.652
6.194
0.285
3.964
4.606
1.596
0.0361
0.211
0.175

6.830
6.477
0.452
6.973
7.844
4.768
0.622
0.409
0.381

0
0.500
0
0
0
0
-1
0
0

29
29
1
44
44
44
1
1
1

Independent Variables
Reign Years
Age at Accession
Military Experience before Marriage
Second Half of ReignFirst two years of Reign

3,586
3,192
3,499
3,586
3,586

30.75
25.16
0.0369
0.486
0.104

15.68
14.07
0.188
0.500
0.305

1
1
0
0
0

66
66
1
1
1

Table A.5
Robustness Checks with Additional Controls and Outcomes
(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

Queen

0.272**[0.122]0.306**[0.149]0.280**[0.124]0.299***[0.111]0.336**[0.133]0.314***[0.115]0.318**[0.152]-0.994[2.715]0.339[2.365]0.279**[0.120]Observations
Specification
Standard Controls

3,262
IV
Y

3,205
IV
Y

3,255
IV
Y

3,262
IV
Y

3,205
IV
Y

3,255
IV
Y

3,577
IV
Y

903
IV
Y

812
IV
Y

3,586
IV
Y

Y
Y

Y

Y

Y

Y
Y

Y

Y

Y
Y

Y

Y

VARIABLES

Total Siblings
Dead Siblings-Previous Monarchs

(9)
(10)
NumberNumber ParticipantsIn Balance In Balance In Balance In Balance In Balance In Balance In Balance Participants Balance of In Any War
of Powerof Powerof Powerof Powerof Powerof Powerof Power- External
Power
War
War
War
War
War
War
War
Wars
Wars

Dead Children-Previous Monarchs
YY
Dead Siblings-Current Monarchs
YY
Age at Accession
Y
Sample Restriction
None
None
None
None
None
None
None
War Years War Years
None
Notes. Variables not shown include polity and decade fixed effects. Robust standard errors clustered at the polity by century level are shown in parentheses. Column (7)controls for the average age at accession of the monarchs in the reign, as well as a missing age indicator to account for missingness in this variable. The number of war
participants in columns (9) and (10) is the average number of participants conditional on war. *** is significant at the 1% level, ** is significant at the 5% level, * issignificant at the 10% level.

Table A.6
Robustness to Sub-Samples and Additional Samples
(1)

(2)

(3)

(4)
(5)
In Balance of Power War

Queen

0.242*[0.125]0.350**[0.160]0.328**[0.148]Observations
Specification
Standard Controls
Total Siblings

3,158
IV
Y
Y

3,177
IV
Y
Y

VARIABLES

SampleInstruments

0.344*[0.183]0.322*[0.165]

(6)

(7)

(8)

0.236*[0.128]0.542*[0.285]0.348**[0.150]

1,675
IV
Y
Y
Drop all
other
Queen
Polities

6,395
IV
Y
Y

3,550
3,446
3,229
3,227
IV
IV
IV
IV
Y
Y
Y
Y
Y
Y
Y
Y
Queen
Queen
Queen
Queen
Queen
Queen
polities polities polities polities polities Polities No Leon &No England No Russia
No Navarre No Portugal No Sweden
CastileFBM r-1 & Sister r-1

Queen & Nonqueen polities

Sisterr-1 , FBMr-1
and interactions
with indicator of
Queen polity

Notes. Variables not shown include polity and decade fixed effects. Robust standard errors clustered at the polity by century levelare shown in parentheses. Column (7) excludes all other queen polities except the six queen polities omitted in columns (1)-(6). In
column (8), the sister and first born male indicators are interacted with an indicator of whether the polity iis one that had at least one
queen during our sample period. *** is significant at the 1% level, ** is significant at the 5% level, * is significant at the 10% level.

Table A.7
Reign Level Specification
(1)

(6)

(7)

(8)

VARIABLES

Balance ofExternal Power War
War years
years

(3)
(4)
(5)
War Outcomes
PolityBalance ofAttacked
External Power War
years
War years
years

PolityAttacked
years

Territorial
Loss

Territorial
Gain

Territory
ChangeQueen

9.837**

10.487***7.537**

11.539**12.155**7.615*-0.2580.546***(4.444)[0.027](3.936)[0.008](3.276)[0.021](5.358)[0.031](4.993)[0.015](3.903)[0.051](0.269)[0.338][[0.00400]] [[0.0780]][[0.0400]][[0.00800]] [[0.0640]][[0.0340]]

(2)

(9)
(10)
Territorial Outcomes

(11)

(12)

Territorial
Loss

Territorial
Gain

Territory
Change0.804**-0.2410.510***

0.751**(0.155)[0.000](0.327)[0.014](0.269)[0.370](0.195)[0.009](0.368)[0.041][[0.350]][[0.0100]][[0.0300]][[0.378]][[0.0240]][[0.0380]]

Observations
Specification

193
IV

193
IV

193
IV

193
IV

193
IV

193
IV

166
IV

166
IV

166
IV

166
IV

166
IV

166
IV

Standard Controls
Total Siblings

Y

Y

Y

Y
Y

Y
Y

Y
Y

Y

Y

Y

Y
Y

Y
Y

Y
Y

Y
PolityY
PolityY
PolityY
PolityY
PolityY
PolityY
PolityY
PolityY
PolityY
PolityY
PolityY
PolityReign Length
Cluster

Wild Bootstrap
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Notes. Variables not shown include polity and century fixed effects. Standard errors are clustered on polity. Standard errors are shown in parentheses and p-values are shown inbrackets. The wild bootstrapped p-values (using 1,000 replications) are shown in double brackets. *** is significant at the 1% level, ** is significant at the 5% level, * is significant at
the 10% level.

Table A.8
Dyad Specification(1)
In Balance of PowerWar(2)
In Balance of PowerWar(3)
In Balance of PowerWar(4)In Balance of PowerWar

Observations

0.104**[0.044]
37,1160.130**[0.051]
37,1160.104**[0.044]
37,1160.130***[0.050]37,116

Instruments

FBM r-1 & Sister r-1

FBM r-1 & Sister r-1

FBM r-1 & Sister r-1

FBM r-1 & Sister r-1

VARIABLES
Any queenStandard Controls
YYYY
Total Siblings
Y
Y
Dyad
Dyad
Dyad-Century
Dyad-Century
Cluster
Kleibergen-Paap F-statistic
62.62
65.58
36.89
22.67
Notes. This table presents estimates from a dyadic specification. The dependent variable is one if two polities were fighting in thesame balance of power war in a given year. Any queen is one if either polity in the dyad had a queen. All specifications include dyad
fixed effects and decade fixed effects. Standard errors are clustered at the dyad leve in columns 1 and 2 and at the dyad by century
level in columns 3 and 4. *** is significant at the 1% level, ** is significant at the 5% level, * is significant at the 10% level.

Table A.9
Solo Queens(1)

VARIABLES
Solo Queen(2)
In Balance
In External of PowerWar
War
0.366*[0.193]0.415**[0.194]

(3)

(4)

(6)

(7)

Polity was
Attacked(5)
In
Defensive
War

PolityAttacked

In Imperial
War

In CivilWar

0.337*[0.196]0.086[0.142]-0.036[0.074]0.095[0.113]-0.032[0.136]

Observations
3,586
3,577
3,563
3,563
3,574
3,586
3,586
Specification
IV
IV
IV
IV
IV
IV
IV
Standard Controls
Y
Y
Y
Y
Y
Y
Y
Total Siblings
Y
Y
Y
Y
Y
Y
Y
Notes. Variables not shown include polity and decade fixed effects. Robust standard errors clustered at the polity
by century level are shown in parentheses. *** is significant at the 1% level, ** is significant at the 5% level, * issignificant at the 10% level.

Table A.10
Territorial Gain in Reigns with and without War(1)
VARIABLES
Queen

Observations
Specification
Standard Controls
Total Siblings
Reign Length
Cluster
Wild Bootstrapped SE(2)Territorial Gain Territorial Gain
0.179
(0.158)[0.259][[0.226]]
84
IV
Y

0.293
(0.335)[0.382][[0.268]]

(3)

(4)

Territorial Gain Territorial Gain
0.297**(0.121)[0.014][[0.0156]]

0.452***(0.130)[0.001][[0.172]]

84
82
82
IV
IV
IV
Y
Y
Y
Y
Y
Y
Y
Y
Y
PolityPolityPolityPolityYYYYNo External
No External
War
War
External War External War
Sample restriction
Notes. Variables not shown include polity and century fixed effects. Standard errors are clustered onpolity. Standard errors are shown in parentheses and p-values are shown in brackets. Wild bootstrapped
p-values (using 1,000 replications) are shown in double brackets. *** is significant at the 1% level, ** issignificant at the 5% level, * is significant at the 10% level.

Table A.11
Additional Controls and Samples: Effects by Marital Status

VARIABLES
Queen
Queen x Married in Reign
Married in Reign
Solo Queen
Solo Queen x Married in Reign

Observations
Specification
Standard Controls
Control Total Siblings
Control Accession Age
Control Male Children-Current Monarch(1)
PolityAttacked(2)
Polity was
Attacked(3)
PolityAttacked(4)
Polity was
Attacked(5)
PolityAttacked(6)
Polity was
Attacked(7)
PolityAttacked(8)
Polity was
Attacked-0.310[0.325]0.410*[0.212]0.026[0.058]-0.747***[0.239]-0.592***[0.213]0.007[0.050]-0.059[0.070]-0.426[0.346]
0.611**[0.272]-0.005[0.055]0.856***[0.263]-0.688***[0.226]-0.377[0.262]0.504**[0.235]-0.052[0.093]-0.761***[0.222]-0.720**[0.358]0.063[0.107]--0.048[0.128]-0.498[0.318]0.773*[0.411]

0.024[0.098]0.770***[0.257]-0.694***[0.265]

3,551
IV
Y
Y
Y

3,551
IV
Y
Y
Y

3,457
IV
Y
Y
Y

3,457
IV
Y
Y
Y

3,558
IV
Y
Y
Y
Y

3,558
IV
Y
Y
Y
Y

3,454
IV
Y
Y
Y
Y

3,454
IV
Y
Y
Y
Y

No weak
No weakqueens /queens /No reigns No reigns
reigns with reigns with
with cowith coNo weakNo weakcoruling
coruling
rulingrulingqueensqueensqueensqueensNone
NonequeensqueensSample Restriction?
Notes. Variables not shown include polity and decade fixed effects. Robust standard errors clustered at the polity by century level are shown inparentheses. *** is significant at the 1% level, ** is significant at the 5% level, * is significant at the 10% level. Accession age is the average age ofaccession of the monarchs in the reign. Spousal military experience is one if the spouse had any military experience prior to marriage.