# The Height of Swiss Mercenaries, c. 1725 - c. 1865

Cédric Chambru, Simon Hediger, Jakob Metzler, Ulrich Woitek

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Cédric Chambru, Simon Hediger, Jakob Metzler, Ulrich Woitek. The Height of Swiss Mercenaries, c. 1725 - c. 1865. 2025. hal-05130188

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CERGIC Working Papers

No. 0012

June 2025

The Height of Swiss Mercenaries,
c. 1725 – c. 1865

Cédric Chambru

Simon Hediger

Jakob Metzler

Ulrich Woitek

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JEL codes: J11, N13, N33, O11.

Keywords: Anthropometrics, Biological Living Standards, Switzerland, 18th century, 19th century.
# The Height of Swiss Mercenaries, c. 1725 – c. 1865*

Cédric Chambru<sup>b</sup> Simon Hediger<sup>a,d†</sup> Jakob Metzler<sup>a</sup> Ulrich Woitek<sup>a,c</sup>

<sup>a</sup>Department of Economics, University of Zurich, Switzerland

<sup>b</sup>Center for Economic Research on Governance, Inequality and Conflict,
École normale supérieure de Lyon, CNRS

<sup>c</sup>CESifo Munich, Germany

<sup>d</sup>Academic Chair for Regulation in Law, Medicine, and Technology,
Department of Health Sciences and Technology, ETH Zurich, Switzerland

June 5, 2025

## Abstract

This paper examines the evolution of the biological standard of living using anthropometric data from approximately 22,000 Swiss mercenaries born between c. 1725 and c. 1865. Analyzing mercenary data presents two key challenges: left-truncation due to height requirements and potential selection bias across regiments. We address these issues by estimating regiment-specific minimum height thresholds to account for variations in recruitment standards and resource constraints, and by controlling for regiment affiliation to mitigate selection bias. Our findings indicate a decline in average height beginning in the 1770s and continuing into the first half of the 19th century, with no evidence of recovery. While the unique nature of the mercenary sample limits broad generalizations, our results align with the economic hardships of the late 18th century, the challenges of early industrialization, and existing anthropometric evidence from Switzerland and other European countries.

<footnote>*We are grateful to Jörg Baten, Matthieu Leimgruber, as well as the participants of the European Historical Economics Society Conference in Vienna and the Swiss Economic History Circle Workshop in Gerzensee for their valuable comments and suggestions. We also thank Damien Bregnard and Philipp Krauer for generously sharing their data. We are especially grateful to Jonas Balmer, Esther d'Overschie, Hanna Engelhart, Virginia Follonier, Leon Frielingsdorf, Ramon Gmür, Joel Hampton, Max Heinsius, Filip Karin, David Leu, Joel Lohnke, Severin Schmider, Nicolas Schneebeli, Lara Schreier, Elie Sieber, Irina Storrer, Gabriela Wüthrich, and Maximilian Zschokke for reliable research assistance. This research was funded by Swiss National Science Foundation grant No. 182294.</footnote>

<footnote>†Corresponding author; e-mail address: hedigers@ethz.ch.</footnote>
# 1 Introduction

Switzerland is known as one of Europe's early industrializer. The fundamental transformations in its economic and political structure during the 18th and 19th centuries brought prosperity in the long run, but the contemporary effects are largely unknown. To better understand how the standard of living in Switzerland developed during this period, we analyze changes in average human stature between c. 1725 and c. 1865, thus focussing on the so-called “biological standard of living”, a term coined by John Komlos in 1987 (Baten and Blum, 2012, p. S67, fn 3). Since a change in average adult height is a suitable indicator for changes in the standard of living during childhood and adolescence (e.g. Bogin, 1999; Fogel, 2004; Tanner, 2010; Floud et al., 2011), this concept allows us to quantify the impact of the changing socio-economic and epidemiological environment on the human body, expanding the measurement of welfare beyond the usual economic proxies.<fnref n="1" />

We estimate the trend in height based on data for Swiss mercenaries, a very specific group of society. Our findings indicate that for this population, the decline in stature began before 1770, aligning with the trend observed in Austria-Hungary by Komlos (2009, Figure 2, p. 344). Compared to the 18th century, average heights remained lower throughout the first half of the 19th century, with no clear sign of recovery. We face two challenges posed by the type of data we analyze. First, our data are truncated to the left due to minimum height requirements, which varied across branches of service. In addition, recruiters often did not strictly enforce the height selection criteria. Hence, the truncation point needs to be estimated (Komlos, 2004), which, in our case, is done on a regiment-specific basis. Since there is not much overlap in terms of time coverage between the regiments, this also accounts for potential time variation in the minimum height requirement. The second challenge is that the decision to join a mercenary regiment potentially introduced a sample selection bias, independently of whether this decision was made by the individual or whether an authority forced the individual to join. When estimating the birthyear trend, we therefore control for the regiment, not only to capture differences in terms of branches of service or employers, but also to account for the specific situation around the measurement year. Failing to control for regiment would significantly overstate the decline in average height from the 18th to the 19th century.

Our paper relates to a large literature on the historical evolution of heights. A first strand of this literature studies the observed paradox between periods of economic growth during the industrialization and the relative decline in biological wellbeing. Because higher incomes enable improved nutrition and living conditions, one would expect a stable positive correlation between measures such as GDP per capita and height. However, there is ample evidence that this is not always the case: during the early stages of industrialization, average human height declined. Beginning with the work of Komlos (1985) on Austria-Hungary, the literature discusses this phenomenon in the European context as “Early Industrial Growth Puzzle” (Steckel, 2024, p. 1796).

Besides Austria-Hungary, a long list of Western European countries has been studied, including Belgium (Alter et al., 2004), France (Komlos et al., 2003), German regions (Baten, 2000; Ewert, 2006; Cinnirella, 2008a), Italy (A’Hearn, 2003), the Netherlands (Drukker and Tassenaar, 1997; Tassenaar, 2019), Portugal (Stolz et al., 2013), Spain (Ramon-Muñoz

<footnote n="1">¹For overviews of the development of anthropometrics, and its strengths and pitfalls in measuring the evolution of living standards and wellbeing, see Steckel (1995, 2008a,b, 2024); Komlos (2008); Harris (2021).</footnote>
and Ramon-Muñoz, 2016; Martinez-Carrión, 2016), Sweden (Sandberg and Steckel, 1987), and the United Kingdom (Komlos, 1993; Cinnirella, 2008b; Blum and McLaughlin, 2019). Building on these results, Baten and Blum (2012, 2014) compiled a global dataset of male height trends for cohorts born between 1810 and 1980. For Western Europe, they identify a decline from 1810 to 1840 (Baten and Blum, 2014, Figure 3, p. 154). Our analysis adds to this literature by providing a long-term height series for a sample of 22,000 Swiss mercenaries spanning c. 1725–c. 1865.

We are not the first to look at human stature in Switzerland. However, there is only limited evidence on the changes in the biological standard of living before the foundation of the federal state in 1848 and the implementation of mandatory military service. An early example is Edouard Mallet’s work from 1835 on Genevan conscripts born between 1805 and 1814 (Staub et al., 2011). Due to the short time period, no trend can be established with Mallet’s data. The study by Kues (2007, Part II, pp. 45-73) on Swiss mercenaries in the British service covers birth cohorts 1816-1820 to 1831-1835. Kues (2007) finds a decrease in heights from the 1810s to the 1830s. More recently, Koepke et al. (2018) analyze the heights of convicts and passport holders. They show a decline in heights for male low socio-economic status (SES) passport holders born between 1770 and 1870. For high SES passport holders, the trend is less pronounced, while the height of male convicts born between 1800 and 1870 shows no clear trend. Our contribution lies in examining a distinct social group – Swiss mercenaries – whose characteristics shape both the methodological approach and the interpretation of results.

Because of the nature of our data, a second strand of the literature is relevant for us, discussing the caveats of using historical military data to study the changes in height over time. For instance, Bodenhorn et al. (2017) find that the decline in the height of voluntary military personnel during the early phase of the industrialization is attributed to a persistent sample selection bias induced by unobserved time-specific factors, e.g. due to the increasing number of alternative employment opportunities. The early industrial growth puzzle survives the critique (see the discussion in Komlos and A’Hearn, 2016; Zimran, 2019; Bodenhorn et al., 2019). In our case, we have also to take into account the possibility that joining a regiment was not necessarily a voluntary decision – during the Napoleonic Wars, Switzerland was forced to contribute soldiers serving in the French army. In this case, selection bias could have been introduced by the decision of the authorities, not the individual.

On the demand side, the requirements to join a regiment might have changed over our observation period. Fourie et al. (2020) highlight how changes in military technology at the turn of the twentieth century increase the relative value of shorter individuals, which could lead to an overall decline in the mean height of soldiers. The standard weapon for the period under analysis was the muzzle-loading rifle with flintlock mechanism. Together with training improvements, such as those implemented in the Prussian army before 1740 (Weigley, 1991, p. 170), every innovation speeding up the loading procedure could in principle help to reduce the minimum height requirement. Examples for such innovations were the introduction of the paper cartridge (since about 1700; Ortenburg 1986, p. 66) or the steel ramrod (Prussia: 1718, Austria: 1742-44, France: 1745; Ortenburg 1986, p. 65). It was not before 1834 that European armies started to replace the flintlock with the percussion lock (Ortenburg, 1988, p. 48). These developments might have caused a reduction in the minimum height requirement, respectively a reduction in the strictness with which
this requirement had to be enforced. Especially relevant for us, the weakening of the re-
quirement could have also been a solution to the ressource problems during the Napoleonic
Wars (Section 2).

2 Historical Background

2.1 Switzerland before 1848

Between 1750 and 1850, Switzerland experienced significant political transformations, leading to the adoption of a federal constitution and the establishment of the modern Swiss state in 1848.<fnref n="2" /> Prior to the French invasion in 1798, Switzerland was a loose association of sovereign entities known as the Swiss Confederacy (*Alte Eidgenossenschaft*), with a weak central body, the Swiss Diet (*Tagsatzung*), which was effectively controlled by a local partriciate. In 1798, the Confederacy was replaced by the short-lived Helvetic Republic, a centralized state dominated by France. The constitution was an attempt to implement a modern state based on the principles of popular sovereignty, separation of powers, and legal equality. Internal trade barriers, tithes and the guild system were abolished. Widespread revolts against this new order were driven by a lack of general acceptance and the adverse effects of the French occupation. Napoleon's Act of Mediation in 1803 marked a partial return to the old Confederacy, retaining some successful elements of the Republic, although Switzerland remained a French protectorate. The Mediation regime ended in 1813, replaced by a new Charter in 1815, assigning the Diet new responsibilities, including foreign trade, military, and foreign relations. However, the Restoration period (1815-1830) was also a step backward, reintroducing internal trade barriers and the guild system. Growing opposition to this regime led to cantonal constitutional revisions and liberal reforms. The Regeneration period (1830-1848) was marked by a struggle between liberals and conservatives, often with a religious dimension, culminating in a civil war in 1847. The liberals' victory over the conservative cantons (*Sonderbund*) paved the way for the establishment of a federal state in 1848, with a constitution that balanced centralization with cantonal sovereignty. Switzerland was thus the only European country where the events of 1848 led to a successful outcome.

Switzerland is one of the earliest industrialized regions in Europe (Bairoch, 1982).<fnref n="3" />
The political changes mentioned above both shaped and resulted from the rapid eco-
nomic development. Organized as a putting-out system, the main driving factor of proto-
industrialization was the textile industry, benefiting from the expanding trade with France
after the 1740s and peaking around 1750-1770. After 1770, the economic situation dete-
riorated starting with a subsistence crisis 1770/71, followed a drastic drop in the textile
exports to France from 1785 onwards, and the arrival of cheap English textile products in
1790s.

The Swiss industrialization and mechanization process started slowly from 1800 until about 1850. During this first phase, the protection guaranteed by the Continental System of Napoleon helped the industry. After the war, an economic downturn followed 1816-1818,

<footnote n="2">²For the political development, see Church and Head (2013, Chapters 4, 5).</footnote>

<footnote n="3">³For the economic situation, see also Bergier (1983, pp. 167-187), Pfister (1992, pp. 77-100), Church and Head (2013, Chapters 4, 5).</footnote>
caused by a subsistence crisis (Kurmann, 2011) and the return of British competition. This resulted in widespread unemployment of textile workers, which persisted until the 1830s (Pfister, 1992, p. 99). The number of employed workers in the cotton industry declined by 60 per cent between 1780 and 1827 (Bergier, 1983, p. 209). In 1832, protest against the consequences of mechanization became violent, leading to the Uster Fire, the only reported incident of Luddism in Switzerland (Bürgi and Schmid 2013, Church and Head 2013, p. 148). When the pace of the industrialization accelerated after 1850, the economic situation improved again.

## 2.2 The Mercenary Trade

The economic development had an impact on the importance of the mercenary service, which has been a major economic factor in Switzerland during the Late Middle Ages and the Early Modern Period (Peyer, 1978). Swiss mercenaries were in high demand from the early 16th century, with France as the main employer. Their reputation built on the success of Swiss infantry in the military conflicts of that era (Church and Head, 2013, pp. 63-68). For a long time, the cantons played the role of the intermediary between the foreign employer and the military entrepreneur. In the period of interest, the Swiss mercenary service was a public undertaking. The motivation for the state to get involved was the considerable public income contribution and the vent-for-surplus function of the service.

In terms of numbers, Henry and Krauer (2023, Section 3) report estimates of 900,000 to two million soldiers fighting abroad in Swiss regiments between 1500 and 1850. Considering that the Swiss population in 1798 was 1,664,832 (Schuler, 2023, p. 56), these estimates seem very high. However, about half the individuals who served in these regiments were foreigners (Henry and Krauer, 2023, Section 3).

The introduction of standing armies in the 17th century brought changes, particularly in discipline and the extension of mandatory service, making enlistment less appealing. Additionally, the expansion of the textile industry created alternative employment opportunities, further reducing the pool of potential recruits and increasing the costs for recruiters to find soldiers who met the necessary criteria. As a result, enforcement of the minimum height requirement became more lenient.<fnref n="4" />

The base of the business was a contract, the *Kapitulation*. The foreign employer entered into an agreement with a single or multiple cantons, or the Federal Diet. The *Kapitulation* regulated the number of troops, their composition, the terms of the employment, and the recruitment requirements. The main military unit of a *Kapitulation* was the regiment, subdivided into battalions and companies, and consisted of about 1500 to 4000 soldiers.

A typical example for the recruitment procedure at the beginning of the 19th century can be found in the state archive of the canton Aargau (StAAG BA 09 0517). Most importantly, the procedure was highly regulated: there was an official recruitment commission in place (*Werb-Commission*) since 1804, which ensured compliance with the regulations, both on the cantonal and the state level (*Werb-Reglement 1804*; *Allgemein-Eidgenössisches Werb-Reglement 1806*; *Werb-Reglement für den Kanton Aargau 1806*). Recruitment without cantonal permission (“*Werb-Patent*”) was prohibited, and information on recruits had to

<footnote n="4">⁴As an example, see Eyer (2008, pp. 360-364) and Eyer (2010, p. 205) for a discussion of the increasingly difficult situation in the Neapolitan service.</footnote>
be recorded. Recruits had to be 18-40 years old, and were supposed to join voluntarily and uncoerced ("freiwillig und ungezwungen").

In general, the recruitment process was similar across time and cantons. Recruiters were often soldiers from the regiments they recruited for. They were supported by civil agents, which could be family, friends, or public officials. Traditionally, the recruiters, wearing their unit's uniform and joined by drummers to announce themselves, passed through towns and then set up at the *Werbeplatz*, where they received the interested men. These men were measured and enlisted if they met the requirements. Measurement was without shoes, and both prest money (enlistment bonus) and payment for the recruiter depended on the height of the recruits. The men were then transported in large groups to the regimental barracks, located in the countries for which they had enlisted. There, the final decision regarding their approval was made by military officials.<fnref n="5" />

The *Kapitulation* defined overall height requirements that the recruiters had to adhere to. A sample of 14 contracts in the period 1757-1825 shows that the general requirements varied across regiments, with a minimum of 162.4cm and a maximum of 167.8cm for "normal" soldiers (see Table 8 in the appendix). As elite troops, the *Gardes Suisses* in 1764 and the *Cent Suisses* in 1816 were supposed to be taller (173.2cm and 184.1cm, respectively). Moreover, even within a regiment, the requirements varied dependent on the branch of service. For example, the *Kapitulation* with France in 1812 states that for *fuseliers*, a minimum height of 167.8cm applied, while *voltigeurs* (skirmish units) had to be at least 154.3cm tall (Burin de Roziers, 1902, p. 252). Sometimes, other exceptions were made for age (recruits aged 16-20 years could be smaller), war time (reduction of height requirement by one inch), and specific duties, such as drummers.

Since in the period 1798-1815, the specific situation of the Napoleonic Wars made recruitment even more difficult, the cantons and the state had to come up with solutions going beyond advertisement. The 1803 *Kapitulation* with France required Switzerland to contribute 16'000 soldiers aged 18-40 years to Napoleon's army.<fnref n="6" /> Each canton was obliged to provide a proportional share based on its population size. The fact that the actual formation of the four regiments took until 1805 (1st Regiment) respectively 1806-1807 (2nd, 3rd and 4th Regiment) is due to the difficulty to find enough native Swiss volunteers, which Napoleon apparently insisted on (Dempsey, 2002, p. 277). Difficult excess demand situations and budget constraints provided incentives for the recruiters to embark on illegal practices (e.g. Suter, 1971, pp. 44-49, 124-128). The actual extent of these practices remains unclear, but more importantly, it also motivated the authorities to adjust the official recruitment process, legally abandoning the principle of voluntariness.

Again, the above mentioned source from the state archive of Aargau can serve as a typical example for local solution attempts. To meet the quota, the canton tried first to grant bonus payments (December 12, 1808). That did not work, as a letter from the cantonal government to the bailiff of the district of Rheinfelden shows (December 17, 1812). The suggestion was to allow petty criminals the choice between enlistment and sentence.

<footnote n="5">⁵See Suter (1971, Chapter 4) for a description of the typical process in Central Switzerland. Another example for the procedure is a *Kapitulation* between Switzerland and Spain in 1804, where it was agreed on a minimum height requirement varying with age slightly, and a minimum share of Swiss recruits. Measurement was without shoes, and the service was supposed to be voluntary (Canton de Fribourg, 1804, pp. 238-239).</footnote>

<footnote n="6">⁶*Militär-Kapitulation zwischen Frankreich und der Schweiz*; see Roucard (2006) for a discussion.</footnote>
The predicted consequence was that the quota would be met. As additional benefit, a reduction of the number of petty crimes was expected, because potential offenders would be sent away to fight for France. In the end, the decision of the cantonal government was that in general, recruits should join voluntarily. If there were not enough recruits, forced recruitment of swindlers, gamblers, drunkards and thugs should be attempted. In addition, forced recruitment could also be applied to individuals with undisciplined conduct, unmarried or negligent fathers, and those opposing recruitment or spreading disturbing rumors (January 19, 1813).

Desertion was a serious problem in the 18th and early 19th century. For the Seven Years' War (1756-1763), it is estimated that the European armies lost about 20 per cent per year due to disease and desertion, not counting the soldiers killed in action (Dziennik, 2024, p. 19). This was also the case for the Swiss regiments: in his study of the Aargau mercenaries in the Bernese regiments in the Netherlands, France and Sardinia, Pfister (1980, 1984) reports average annual deserters' shares of 6 to 10 per cent. The maxima range from 16 to 32 per cent (Table 1).<fnref n="7" />

<table><caption>Table 1: Annual Deserters' Shares from Bernese Regiments</caption><thead><tr><th></th><th>Period</th><th>Average (%)</th><th>Minimum (%)</th><th>Maximum (%)</th></tr></thead><tbody><tr><td>Netherlands</td><td>1701-1796</td><td>5.93</td><td>1.39</td><td>16.15</td></tr><tr><td>France</td><td>1702-1791</td><td>5.60</td><td>0.79</td><td>20.05</td></tr><tr><td>Sardinia</td><td>1738-1797</td><td>9.99</td><td>2.08</td><td>32.02</td></tr></tbody></table>

Source: Pfister (1980, Tables 1, 2, pp. 271-274; 1984, Table 1, pp. 344-345)

Besides the hardship of the military service abroad, an important motive for soldiers who decided to desert was forced re-enlistment because of debts to the regiment (Pfister, 1984, pp. 84-85). Moreover, there was also the possibility of attempting to re-enlist in another regiment under a different name and receive the prest money multiple times (de Weck, 2006, Section 1).

## 3 Data

Due to the authorities' efforts to gain greater control over the trade, a substantial body of archival sources on mercenary service in Switzerland has been preserved, particularly from the 18th century onward. These administrative records, created as part of this oversight, offer detailed information on individual recruits, most notably in the form of regimental lists (Hitz, 2015, p. 31). Our primary sources are lists compiled during recruitment from 1750 to 1884 for 24 regiments (including the *Helvetische Legion*, see the discussion below). The data on the regiments *Eptingue*, *Courten* and the *Niederländische Ostindienkompanie* are from secondary sources.<fnref n="8" /> The preliminary figures provided by Foerster (2010, p. 248,

<footnote n="7">⁷In their analysis of a mercenary company from the canton of Valais, Fayard Duchêne and de Riedmatten (1997, pp. 123-138) provide a detailed discussion of the dynamics of desertion. In 1793, the desertion rate in this specific company was as high as 35.57% (Fayard Duchêne and de Riedmatten, 1997, p. 124).</footnote>

<footnote n="8">⁸Bregnard (1996), Fayard Duchêne and de Riedmatten (1997), Gally-de Riedmatten (2014), Krauer (2024). A detailed list of sources can be found in Table 9 in Appendix D.</footnote>
250) in Table 7 (Appendix C) show that we cover a substantial part of the total number of regiments.

The lists include data on the regiment, recruit's name, municipality or canton of origin, age or date of birth, enlistment date, and height at enlistment. In some lists, occupation is included, but information on rank and type of soldier (grenadier, fusilier, etc.) is not frequently enough reported to be useful for our analysis. The sources cover lists from six employers: France, the Netherlands (the Dutch Republic and the Kingdom of Holland), the United Kingdom, the Kingdom of the Two Sicilies (Sicily and Naples), the Kingdom of Sardinia, and the Helvetic Republic. The height of the mercenaries was measured in feet (French, Rhinelandic, British), Piedmontese *onces*, and occasionally in centimeters. To ensure comparability for the statistical analysis, we convert the data to centimeters.<fnref n="9" />

We include the individuals serving in the standing army of the Helvetic Republic, not the militia troops. These soldiers were not mercenaries in the traditional sense – volunteers hired to fight for a foreign employer (Rogger and Hitz, 2014, pp. 30-33). However, this definition has been challenged. Sikora (2003) argues that domestic recruitment was also significant for the standing armies of the 17th and 18th centuries and suggests that the defining characteristic should be voluntariness. By including soldiers recruited for the standing army of the Helvetic Republic, we align with Sikora's broader definition of mercenary service in the sense of voluntariness as formal requirement. At the same time, we note that in praxis, the degree of voluntariness varied over time, especially at the end of the Napoleonic Wars, as we discussed in Section 2.

We exclude mercenaries born abroad, focusing instead on those who were “Swiss”. Although the modern Swiss Confederation was not established until 1848, this is not an ahistorical approach. Most employers placed great importance on quotas specifying how many recruits should be “Swiss”, a term that roughly referred to a territory matching today’s borders, established in 1815 (Section 2). For the sake of simplicity, we have assigned municipalities of origin to their corresponding modern cantons. The main difference is that we merged the cantons Jura and Berne.

We start with about 37,000 individuals and remove incomplete records. It is also possible that the same individual was recorded multiple times in the raw data. In Section 2, we discussed the likelihood of deserters re-enlisting under false identities to obtain the enlistment bonus more than once. However, legal re-enlistment also presents a possibility. While deserters likely re-enlisted under false identities and can only be detected if they were found out and remarked on in the source, we address the issue of legal re-enlistment by implementing a simple routine. We classify a pair of observations as a “double entry” if it meets three criteria: (1) 80 percent of the characters in the surname and birthplace/canton match, (2) the individuals share the same birth year, and (3) the difference in height (cm) is 2 cm or less. For each such pair, one observation is excluded from the analysis (522 individuals). In total, the cleaning process (removing incomplete records, removing duplicates) reduces the final sample size to 21,782.

Table 2 shows the descriptive statistics for these individuals by regiment, together with employer and measurement/birth periods. We do not have a regiment covering the entire period, both in terms of birthyears and entry years (Figure 1). Note that in Table 2, we

<footnote n="9">⁹Units: 1 foot = 12 inches = 144 lines. Conversion factors (cm): 0.2255829 (French lines), 0.2179538 (Rhinelandic lines), 0.212 (British lines), Twelve Piedmontese *onces* = 1 Turin foot, which is equal to 0.51377m (Gally-de Riedmatten, 2014, p. 304).</footnote>
present unconditional moments: because of the truncation problem, the raw means are too high, and the standard deviations too low. The regional distribution and the distribution across occupational categories are displayed in Tables 3 and 4. Table 3 shows that our data are clearly not representative in terms of regional coverage. The same can be said about occupational categories (Table 4). The fact that the share of skilled workers is so high might reflect the vulnerability of this group with respect to fluctuations in overall economic activity and hence, the dependence on alternative employment opportunities.
<table><caption>Table 2: Summary Statistics (Height) by Regiment</caption><thead><tr><th rowspan="2">Regiment</th><th rowspan="2">Employer</th><th colspan="2">Period</th><th>Age</th><th colspan="5">Height</th><th rowspan="2">N</th><th rowspan="2">%</th></tr><tr><th>Measurement</th><th>Birth</th><th>AV</th><th>AV</th><th>MED</th><th>SD</th><th>MIN</th><th>MAX</th></tr></thead><tbody><tr><td>Johann Baptist Stuppa</td><td>FRA</td><td>1756 - 1767</td><td>1726 - 1746</td><td>26</td><td>173.68</td><td>173.70</td><td>4.25</td><td>164.45</td><td>182.27</td><td>43</td><td>0.20</td></tr><tr><td>Eptingue</td><td>FRA</td><td>1758 - 1770</td><td>1726 - 1749</td><td>25</td><td>172.74</td><td>172.07</td><td>4.27</td><td>163.72</td><td>187.40</td><td>347</td><td>1.59</td></tr><tr><td>Pfyffer</td><td>FRA</td><td>1755 - 1792</td><td>1725 - 1769</td><td>25</td><td>172.85</td><td>172.35</td><td>4.87</td><td>161.29</td><td>191.52</td><td>1347</td><td>6.18</td></tr><tr><td>Von Salis-Zizers</td><td>FRA</td><td>1765 - 1792</td><td>1736 - 1771</td><td>25</td><td>174.15</td><td>174.04</td><td>4.68</td><td>162.42</td><td>184.08</td><td>54</td><td>0.25</td></tr><tr><td>Courten</td><td>SRD</td><td>1775 - 1797</td><td>1738 - 1776</td><td>25</td><td>166.30</td><td>165.90</td><td>5.45</td><td>153.06</td><td>184.10</td><td>171</td><td>0.79</td></tr><tr><td>Stürler</td><td>NLD</td><td>1757 - 1799</td><td>1728 - 1778</td><td>26</td><td>169.43</td><td>168.26</td><td>5.16</td><td>156.93</td><td>185.91</td><td>727</td><td>3.34</td></tr><tr><td>Helvetische Legion</td><td>SWI</td><td>1798 - 1802</td><td>1758 - 1781</td><td>25</td><td>171.34</td><td>170.54</td><td>5.14</td><td>154.30</td><td>197.61</td><td>1165</td><td>5.35</td></tr><tr><td>Dunant</td><td>ESP</td><td>1779 - 1808</td><td>1743 - 1786</td><td>27</td><td>171.19</td><td>170.54</td><td>4.59</td><td>155.65</td><td>186.78</td><td>293</td><td>1.35</td></tr><tr><td>Jann</td><td>ESP</td><td>1805 - 1808</td><td>1765 - 1786</td><td>27</td><td>171.11</td><td>170.54</td><td>4.63</td><td>162.42</td><td>182.72</td><td>79</td><td>0.36</td></tr><tr><td>Ragettli</td><td>FRA</td><td>1806 - 1813</td><td>1766 - 1792</td><td>27</td><td>168.78</td><td>167.83</td><td>5.50</td><td>154.30</td><td>186.78</td><td>544</td><td>2.50</td></tr><tr><td>De Castella</td><td>FRA</td><td>1806 - 1813</td><td>1767 - 1792</td><td>27</td><td>168.18</td><td>167.83</td><td>5.85</td><td>154.30</td><td>198.96</td><td>706</td><td>3.24</td></tr><tr><td>Von May</td><td>FRA</td><td>1807 - 1813</td><td>1768 - 1792</td><td>26</td><td>167.37</td><td>166.71</td><td>5.73</td><td>154.52</td><td>183.17</td><td>281</td><td>1.29</td></tr><tr><td>Perrier</td><td>FRA</td><td>1806 - 1816</td><td>1768 - 1795</td><td>27</td><td>168.80</td><td>168.28</td><td>5.93</td><td>151.59</td><td>188.14</td><td>457</td><td>2.10</td></tr><tr><td>Sprecher</td><td>NLD</td><td>1814 - 1816</td><td>1775 - 1795</td><td>26</td><td>168.28</td><td>167.39</td><td>5.01</td><td>156.93</td><td>183.08</td><td>163</td><td>0.75</td></tr><tr><td>Auf der Maur</td><td>NLD</td><td>1816 - 1827</td><td>1778 - 1805</td><td>27</td><td>169.63</td><td>168.70</td><td>5.33</td><td>156.93</td><td>187.00</td><td>111</td><td>0.51</td></tr><tr><td>Ziegler</td><td>NLD</td><td>1814 - 1828</td><td>1775 - 1807</td><td>26</td><td>168.44</td><td>167.39</td><td>5.23</td><td>154.31</td><td>201.17</td><td>1294</td><td>5.94</td></tr><tr><td>Von Högger</td><td>FRA</td><td>1816 - 1830</td><td>1776 - 1809</td><td>26</td><td>172.85</td><td>171.89</td><td>4.10</td><td>162.42</td><td>189.49</td><td>645</td><td>2.96</td></tr><tr><td>Bleuler</td><td>FRA</td><td>1816 - 1830</td><td>1777 - 1809</td><td>26</td><td>167.98</td><td>167.16</td><td>4.35</td><td>157.01</td><td>189.49</td><td>1227</td><td>5.63</td></tr><tr><td>Von Steiger</td><td>FRA</td><td>1816 - 1830</td><td>1777 - 1809</td><td>27</td><td>168.75</td><td>167.83</td><td>4.39</td><td>162.42</td><td>188.14</td><td>148</td><td>0.68</td></tr><tr><td>Von Affry</td><td>FRA</td><td>1816 - 1830</td><td>1778 - 1809</td><td>26</td><td>172.30</td><td>171.78</td><td>4.09</td><td>162.42</td><td>189.49</td><td>592</td><td>2.72</td></tr><tr><td>Ludwig von Sonnenberg</td><td>KTS</td><td>1825 - 1849</td><td>1785 - 1828</td><td>26</td><td>170.14</td><td>169.64</td><td>5.16</td><td>157.01</td><td>193.55</td><td>1955</td><td>8.98</td></tr><tr><td>Von Salis-Soglio</td><td>KTS</td><td>1826 - 1855</td><td>1787 - 1834</td><td>26</td><td>169.40</td><td>168.51</td><td>5.38</td><td>152.95</td><td>200.32</td><td>4515</td><td>20.73</td></tr><tr><td>Britische Schweizer Legion</td><td>GBR</td><td>1855 - 1855</td><td>1815 - 1834</td><td>27</td><td>167.50</td><td>167.27</td><td>5.61</td><td>152.64</td><td>189.53</td><td>1964</td><td>9.02</td></tr><tr><td>Niederländische Ostindienkompanie</td><td>NLD</td><td>1848 - 1884</td><td>1814 - 1863</td><td>27</td><td>167.12</td><td>167.00</td><td>5.65</td><td>151.00</td><td>195.00</td><td>2954</td><td>13.56</td></tr></tbody><tfoot><tr><td colspan="12">Total: 21782</td></tr></tfoot></table>

AV: average, MED: median, SD: standard deviation, N: number of mercenaries; SWI: Swiss, ESP: Spain, FRA: France, GBR: United Kingdom, KTS: Kingdom of the Two Sicilies, NLD: Netherlands, SRD: Sardinia.
<figure><img src="image_6.png" /><figcaption>Figure 1: Coverage by Regiment</figcaption></figure>

Fill color: number of observations; border color: employer (Swiss (SWI), Spain (ESP), French (FRA), Great Britain (GBR), Kingdom of the Two Sicilies (KTS), Dutch (NLD) or Sardinian (SRD)). The number in brackets on the right of the regiment name is the estimated truncation point (see Section 4 for details).
<table><caption>Table 3: Regional Coverage</caption><thead><tr><th rowspan="2">Canton</th><th colspan="5">Observations</th></tr><tr><th>Population</th><th>% Pop.</th><th>Merc.</th><th>% Merc.</th><th>Ratio</th></tr></thead><tbody><tr><td>ZG</td><td>12,487</td><td>0.74</td><td>367</td><td>1.68</td><td>2.27</td></tr><tr><td>BS</td><td>16,934</td><td>1.00</td><td>474</td><td>2.18</td><td>2.18</td></tr><tr><td>TG</td><td>70,862</td><td>4.18</td><td>1,880</td><td>8.63</td><td>2.06</td></tr><tr><td>BL</td><td>29,108</td><td>1.72</td><td>699</td><td>3.21</td><td>1.87</td></tr><tr><td>VS</td><td>60,444</td><td>3.56</td><td>1,424</td><td>6.54</td><td>1.84</td></tr><tr><td>SG</td><td>129,533</td><td>7.64</td><td>2,941</td><td>13.50</td><td>1.77</td></tr><tr><td>SH</td><td>23,318</td><td>1.37</td><td>525</td><td>2.41</td><td>1.76</td></tr><tr><td>SZ</td><td>34,232</td><td>2.02</td><td>743</td><td>3.41</td><td>1.69</td></tr><tr><td>LU</td><td>91,124</td><td>5.37</td><td>1,872</td><td>8.59</td><td>1.60</td></tr><tr><td>AR</td><td>38,197</td><td>2.25</td><td>689</td><td>3.16</td><td>1.40</td></tr><tr><td>GR</td><td>72,903</td><td>4.30</td><td>941</td><td>4.32</td><td>1.00</td></tr><tr><td>AI</td><td>9,355</td><td>0.55</td><td>116</td><td>0.53</td><td>0.96</td></tr><tr><td>AG</td><td>125,669</td><td>7.41</td><td>1,521</td><td>6.98</td><td>0.94</td></tr><tr><td>SO</td><td>45,840</td><td>2.70</td><td>545</td><td>2.50</td><td>0.93</td></tr><tr><td>NW</td><td>8,496</td><td>0.50</td><td>95</td><td>0.44</td><td>0.88</td></tr><tr><td>GL</td><td>22,809</td><td>1.34</td><td>251</td><td>1.15</td><td>0.86</td></tr><tr><td>ZH</td><td>179,801</td><td>10.60</td><td>1,746</td><td>8.02</td><td>0.76</td></tr><tr><td>FR</td><td>66,298</td><td>3.91</td><td>603</td><td>2.77</td><td>0.71</td></tr><tr><td>GE</td><td>46,436</td><td>2.74</td><td>378</td><td>1.74</td><td>0.64</td></tr><tr><td>BE</td><td>308,057</td><td>18.16</td><td>2,258</td><td>10.37</td><td>0.57</td></tr><tr><td>VD</td><td>144,711</td><td>8.53</td><td>1,033</td><td>4.74</td><td>0.56</td></tr><tr><td>OW</td><td>10,580</td><td>0.62</td><td>73</td><td>0.34</td><td>0.55</td></tr><tr><td>UR</td><td>11,843</td><td>0.70</td><td>69</td><td>0.32</td><td>0.46</td></tr><tr><td>NE</td><td>46,615</td><td>2.75</td><td>240</td><td>1.10</td><td>0.40</td></tr><tr><td>TI</td><td>90,309</td><td>5.32</td><td>299</td><td>1.37</td><td>0.26</td></tr></tbody><tfoot><tr><td>Total:</td><td>1,695,961</td><td></td><td>21,782</td><td></td><td></td></tr></tfoot></table>

The population data comes from the 1798 census (hsso.ch, Table B.01a). Columns 3 and 5 show the percentage shares of the population and mercenaries relative to the total. The ratio (% Mercenaries / % Population, last column) indicates over-/underrepresentation by the mercenary sample.
<table><caption>Table 4: Age, Height and Occupational Shares</caption><thead><tr><th rowspan="2">SEP</th><th>Age</th><th colspan="5">Height</th><th rowspan="2">N</th><th rowspan="2">%</th></tr><tr><th>AV</th><th>AV</th><th>MED</th><th>SD</th><th>MIN</th><th>MAX</th></tr></thead><tbody><tr><td>1</td><td>26</td><td>170.16</td><td>169.84</td><td>6.00</td><td>159.64</td><td>186.78</td><td>86</td><td>0.39</td></tr><tr><td>2</td><td>27</td><td>169.86</td><td>169.19</td><td>6.37</td><td>157.01</td><td>200.32</td><td>180</td><td>0.83</td></tr><tr><td>3</td><td>26</td><td>168.95</td><td>168.54</td><td>5.45</td><td>152.64</td><td>201.17</td><td>5404</td><td>24.81</td></tr><tr><td>4</td><td>25</td><td>169.89</td><td>169.19</td><td>5.15</td><td>151.59</td><td>189.49</td><td>1212</td><td>5.56</td></tr><tr><td>5</td><td>27</td><td>168.35</td><td>167.90</td><td>5.66</td><td>154.55</td><td>189.49</td><td>1212</td><td>5.56</td></tr><tr><td>6</td><td>26</td><td>169.49</td><td>169.19</td><td>5.56</td><td>151.00</td><td>197.61</td><td>13688</td><td>62.84</td></tr></tbody><tfoot><tr><td colspan="8">Total: 21782</td><td></td><td></td></tr></tfoot></table>

Note: The occupational categories are based on HISCLASS 5, with 1: elite; 2: lower middle class; 3: skilled workers; 4: self-employed farmers and fishermen; 5: unskilled workers and farm workers; category 6 is for missing values.

# 4 Method

In estimating the birth period effect accurately, we face two major challenges. The first challenge is due to the variation of the recruitment process across regiments and across time. This is potentially also the case for the motivation to join a regiment, introducing a selection bias. In order to identify this bias, we need to control for regiments and/or the situation in the measurement period. In our baseline model (Section 4.1), we use the fact that the measurement periods covered by the regiments are only partially overlapping to capture a combined measurement period/regiment effect. In the robustness checks discussed in Appendix A, we disentangle the two effects as far as it is possible.

The second challenge is caused by the minimum height requirement: historical heights from military records usually suffer from left-truncation and heaping. To tackle the truncation problem, we apply an extension of the Heintel (1996) method, assuming that truncation is regiment specific (Section 4.2).

## 4.1 Main Model

Our starting point is the following linear regression for individual heights $h_i$

$$h_i = \mu + \sum_{a=1}^{A-1} \alpha_a A_{i,a} + \sum_{b=1}^{B-1} \beta_b B_{i,b} + \sum_{r=2}^{R} \pi_r R_{i,r} + \\ + \sum_{c=2}^{C} \psi_c C_{i,c} + \sum_{o=1}^{O} \omega_o O_{i,o} + \kappa T_i + u_i, \quad (1)$$

where the $u_i$ are identically and independently Gaussian distributed across mercenaries with expectation zero and variance $\sigma^2$. The variables $A_{i,a}$, $B_{i,c}$, $R_{i,r}$, $C_{i,c}$ and $O_{i,o}$ are age, birth period, regiment, canton and occupation specific dummies. Finally, $T_i$ represents a region and year specific temperature anomaly (Swiss Plateau: Wetter and Pfister 2013, Swiss Alps: Trachsel et al. 2010). Table 5 displays a detailed list of all the included variables.
<table><caption>Table 5: List of Variables</caption><thead><tr><th>Variable</th><th>Description</th></tr></thead><tbody><tr><td>Age</td><td>Separate dummies for ages 21 and 22.<br>The age group 23-40 represents the reference group.</td></tr><tr><td>Birth period</td><td>Dummies in steps of 5 years from 1725-1864.<br>The reference cohort is 1860-1864.</td></tr><tr><td>Regiment</td><td>Regiment specific dummy variables, the reference regiment is Pfyffer.</td></tr><tr><td>Canton</td><td>Canton specific dummy variables.<br>Luzern is the reference canton.<br>Note: BE and JU are merged.</td></tr><tr><td>Occupation</td><td>Dummies for the 6 occupation groups.<br>1-5 are according to HISCLASS 5, 6 is unspecified.<br>The reference group is 3.</td></tr><tr><td>Temperature anomaly</td><td>Region and year specific temperature anomalies.</td></tr></tbody></table>

In more compact form, equation (1) can be written as

$$h_i = \mathbf{x}_i^\top \boldsymbol{\theta} + u_i, \quad (1')$$

where

$$\boldsymbol{\theta} := \left( \mu, (\alpha_a)_{a=1}^{A-1}, (\beta_b)_{b=1}^{B-1}, (\pi_r)_{r=2}^{R}, (\psi_c)_{c=2}^{C}, (\omega_o)_{o=2}^{O}, \kappa \right)^{\top}$$

is the vector of the p regression coefficients, and

$$\mathbf{x}_i^\top := \left( 1, (\mathcal{A}_{i,a})_{a=1}^{A-1}, (\mathcal{B}_{i,b})_{b=1}^{B-1}, (\mathcal{R}_{i,r})_{r=2}^{R}, (\mathcal{C}_{i,c})_{c=2}^{C}, (\mathcal{O}_{i,o})_{o=2}^{O}, \mathcal{T}_i \right)$$

the vector of covariates.

## 4.2 Parameter Estimation

To tackle the truncation problem, we apply an extension of the Heintel (1996) method, assuming that truncation is regiment specific (see the discussion in Komlos, 2004). Each individual i is recruited into a regiment l, $l = 1, \dots, L$, with regiment specific minimum height requirement $a^{(l)}$. For reasons discussed above, this truncation point is not necessarily equal to the minimum height of recruits in a specific regiment l. But if it was known, we could simply drop the recruits smaller than required. In this case, the set of selected recruits is

$$S := \{i = 1, \dots, N : h_i \geq a_i\},$$
where $a_i$, the minimum height requirement relevant for individual $i$, is determined by the recruit's regiment:

$$a_i := a^{(l)} \quad \forall i \in \text{Reg}_l, l = 1, \dots, L.$$

The set $\text{Reg}_l$ holds the indices of recruits in the $l^{th}$ regiment. Since the regiment specific truncation point $a^{(l)}$ is unknown (Section 1), we estimate the parameters $a_i$ and $\theta$ in a two-step procedure.

**Step 1** The truncation parameters are estimated applying a modified version of the method proposed by Heintel (1996). For each regiment $l$ and a grid of equally spaced candidate points

$$h \in \mathcal{U}_l := \{h_{l,\min}, h_{l,\min} + s, h_{l,\min} + 2s, \dots, h_{l,\max} - s\}, \quad (2)$$

where $h_{l,\min} := \min(\{h_i\}_{i \in \text{Reg}_l})$, $h_{l,\max} := \max(\{h_i\}_{i \in \text{Reg}_l})$ and $s > 0$, we estimate the unconditional regiment specific density $f_l$ from the observed heights as

$$\hat{f}_{N_l}(h) := \frac{1}{\tau_{N_l} N_l} \sum_{i \in \text{Reg}_l} K \left( \frac{h - h_i}{\tau_{N_l}} \right). \quad (3)$$

Because of the heaping problem, we slightly deviate from Heintel (1996) by specifying $K(\cdot)$ as triweight smoothing kernel based on the beta(4,4) density. We choose the oversmoothed bandwidth selector of Wand and Jones (1994, p. 61) for $\tau_{N_l}$. The estimated truncation parameter is the candidate point where the difference in density estimates is maximal:

$$\hat{a}^{(l)} := \arg \max_{h \in \mathcal{U}_l} \hat{f}_{N_l}(h) - \hat{f}_{N_l}(h + s). \quad (4)$$

**Step 2** Given the estimated truncation parameters, the regression coefficients of equation (1') are estimated through maximum likelihood (ML). Assuming the distribution function of $u_i$ belongs to the location-scale family, the log-likelihood, given the data and the estimated truncation parameter, is given by

$$\ell(\tilde{\theta}, \tilde{\sigma} | \{h_i, \mathbf{x}_i, \hat{a}_i\}_{i \in \hat{S}}) := \sum_{i \in \hat{S}} \left[ \log \left( f\left( \frac{h_i - \mathbf{x}_i^\top \tilde{\theta}}{\tilde{\sigma}} \right) \right) - \log(\tilde{\sigma}) - \log \left( 1 - F_{\mathbf{x}_i^\top \tilde{\theta}, \tilde{\sigma}}(\hat{a}_i) \right) \right], \quad (5)$$

where $f$ is the probability density function and $F$ the cumulative distribution function. The set $\hat{S}$ is the set of selected recruits determined by the estimated truncation points $\hat{a}_i = \hat{a}^{(l)} \forall i \in \text{Reg}_l, l = 1, \dots, L$. For the ML-estimates we obtain

$$\hat{\eta} = (\hat{\theta}^\top, \hat{\sigma})^\top := \arg \max_{\tilde{\theta}, \tilde{\sigma}} \ell(\tilde{\theta}, \tilde{\sigma} | \{h_i, \mathbf{x}_i, \hat{a}_i\}_{i \in \hat{S}}). \quad (6)$$
Expression (6) generally has no closed form solution and is solved numerically.<fnref n="10" />

Based on the parameter estimates, we calculate the height trend for a representative individual using

$$ \hat{h}_b := \hat{\beta}_b + \hat{\theta}_{-\text{Birth}}^{\top} \bar{\mathbf{x}}_{-\text{Birth}}, \quad (7) $$

where $\hat{\theta}_{-\text{Birth}}$ are the estimated regression coefficients without the estimated birth period effects and $\bar{\mathbf{x}}_{-\text{Birth}}$ are the variable specific averages without the birth period dummies.

Finally, we calculate the difference of the average estimated birth period effects before 1800 ($\bar{\beta}^{<1800}$) and after 1800 ($\bar{\beta}^{\ge 1800}$):

$$ \hat{\Delta} := \bar{\beta}^{<1800} - \bar{\beta}^{\ge 1800}. \quad (8) $$

## 4.3 Construction of Confidence Intervals

Because estimating the truncation parameter in the first step produces an additional layer of uncertainty, we can not construct classical confidence intervals via the inverse of the Hessian matrix of the log-likelihood. In addition, the heaped nature of the height observations invalidates classical inference. Therefore we use a non-parametric bootstrap to construct symmetric confidence intervals.

Let

$$ \hat{\xi} \in \{\hat{\theta}_1, \dots, \hat{\theta}_p, \hat{h}_1, \dots, \hat{h}_B, \hat{\Delta}\}, $$

i.e. $\hat{\xi}$ represents either the jth estimated regression coefficient $\hat{\theta}_j, j = 1, \dots, p$, the bth estimated trend parameter $\hat{h}_b, b = 1, \dots, B$ or the estimated trend difference $\hat{\Delta}$. Similarly,

$$ \hat{\xi}_w^* \in \{\hat{\theta}_{w,1}^*, \dots, \hat{\theta}_{w,p}^*, \hat{h}_{w,1}^*, \dots, \hat{h}_{w,B}^*, \hat{\Delta}_w\} $$

is either the jth estimated regression coefficient, the bth estimated trend parameter or the estimated trend difference from the wth bootstrap sample, $w = 1, \dots, W$. With $\omega_w^* := |\hat{\xi}_w^* - \hat{\xi}|$, the resulting $(1 - \alpha)$% bootstrap confidence interval for $\xi$ is given by

$$ CI_{(1-\alpha)\%}(\xi) := [\hat{\xi} \pm c^*(1-\alpha)], \quad (9) $$

where $c^*(\lambda)$ denotes the $\lambda$ quantile of the empirical distribution of $\{\omega_w^*\}_{w=1}^W$. We set $W = 10,000$ and $\alpha = 0.05$.

<footnote n="10">¹⁰We apply the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm. For a more detailed discussion of truncated linear regression models see Hayashi (2011, Chapter 8.2).</footnote>
# 5 Results

> In some of the smaller cantons, manufactures have been introduced, which, by furnishing a greater quantity of employment, and at the same time a greater quantity of exports for the purchase of corn, have of course considerably increased their population. But the Swiss writers seem generally to agree, that the districts where they have been established, have upon the whole suffered in point of health, morals and happiness.
> 
> Malthus (1803, p. 280)

In the second edition of his *Principle of Population* published in 1803, Malthus considerably extended the empirical part in support of his ideas about population dynamics. Among material on other European countries, Book II contains a chapter “Of the Checks to Population in Switzerland” (Malthus, 1803, Book II, Chapter V). The chapter is based on contemporary literature on Swiss demography, but also on his own experiences from travelling the country in 1802 (James, 1979, p. 96-98). In the paragraph quoted above, Malthus stresses the adverse effect of increasing economic activity during the early stages of industrialization on public health.

As far as health is concerned, our main result displayed in Figure 2 supports the view of the “Swiss writers” mentioned by Malthus, not just for “some smaller cantons”, but more general for the social group represented by the mercenaries. The height trend calculated based on equation (7) shows a significant decline in heights until 1795-99.<fnref n="11" /> The point estimates show a continuation of the decline during the difficult first phase of industrialization. However, the effects for the first half of the 19th century are only very imprecisely measured. What we can say is that compared to the situation in the 18th century, heights were lower and stayed at this lower level until the end of our observation period. As the sensitivity analysis in Appendix A shows, the result is robust with respect to changes in the set of control variables and/or estimation techniques.

Turning to the partial birth periods effects in Figure 2, and Table 6, we see that the confidence intervals include zero for all periods. To test whether there is an overall trend, we calculate the difference between the average estimated birth period effects before 1800 and after 1800 (equation 8). This difference is 2.51cm, with 95%-confidence interval [0.63cm, 4.39cm]. We therefore conclude that there is a significant difference between average height in the second half of the 18th century compared to the first half of the 19th century.

<footnote n="11">¹¹The underlying parameters can be found in Table 6.</footnote>
<figure><img src="image_7.png" /><figcaption>Figure 2: Estimated Birth Cohort Effects (Equation 1)</figcaption></figure>

The reference birth period is 1860-1864. The confidence intervals are estimated as described in Section 4.3 (dark gray bars: birth cohort effects; light gray bars: height trend). The blue curve is generated applying a loess smoother to the estimated birth cohort effects. The vertical axis on the right represents the estimated birth cohort effect plus the average effect of all the control variables (equation 7).
<table><caption>Table 6: Estimated Parameters of Model (1)</caption><thead><tr><th>Variable</th><th>Coeff.</th><th>Boot CI</th><th>Variable cont.</th><th>Coeff.</th><th>Boot CI</th></tr></thead><tbody><tr><td>Intercept</td><td>167.23</td><td>[162.24, 172.21]</td><td>Canton OW</td><td>0.79</td><td>[-1.10, 2.69]</td></tr><tr><td>1725-1729</td><td>2.70</td><td>[-1.43, 6.83]</td><td>Canton SG</td><td>-0.08</td><td>[-0.60, 0.43]</td></tr><tr><td>1730-1734</td><td>0.63</td><td>[-3.26, 4.52]</td><td>Canton SH</td><td>0.35</td><td>[-0.43, 1.12]</td></tr><tr><td>1735-1739</td><td>0.28</td><td>[-3.53, 4.08]</td><td>Canton SO</td><td>1.48</td><td>[0.16, 2.80]</td></tr><tr><td>1740-1744</td><td>2.15</td><td>[-1.55, 5.86]</td><td>Canton SZ</td><td>0.57</td><td>[-0.22, 1.36]</td></tr><tr><td>1745-1749</td><td>3.34</td><td>[-0.32, 6.99]</td><td>Canton TG</td><td>0.78</td><td>[0.19, 1.38]</td></tr><tr><td>1750-1754</td><td>1.66</td><td>[-3.19, 6.51]</td><td>Canton TI</td><td>1.43</td><td>[0.22, 2.63]</td></tr><tr><td>1755-1759</td><td>2.90</td><td>[-1.01, 6.82]</td><td>Canton UR</td><td>-0.35</td><td>[-2.26, 1.56]</td></tr><tr><td>1760-1764</td><td>1.74</td><td>[-2.57, 6.04]</td><td>Canton VD</td><td>2.29</td><td>[1.34, 3.24]</td></tr><tr><td>1765-1769</td><td>2.57</td><td>[-1.81, 6.95]</td><td>Canton VS</td><td>-0.58</td><td>[-1.29, 0.13]</td></tr><tr><td>1770-1774</td><td>3.17</td><td>[-0.72, 7.07]</td><td>Canton ZG</td><td>1.29</td><td>[0.01, 2.57]</td></tr><tr><td>1775-1779</td><td>1.43</td><td>[-3.03, 5.89]</td><td>Canton ZH</td><td>0.26</td><td>[-0.38, 0.89]</td></tr><tr><td>1780-1784</td><td>1.44</td><td>[-3.04, 5.92]</td><td>Johann Baptist Stuppa</td><td>1.32</td><td>[-0.80, 3.44]</td></tr><tr><td>1785-1789</td><td>0.88</td><td>[-3.52, 5.27]</td><td>Eptingue</td><td>-1.22</td><td>[-3.01, 0.58]</td></tr><tr><td>1790-1794</td><td>-0.11</td><td>[-4.75, 4.52]</td><td>Von Salis-Zizers</td><td>0.83</td><td>[-0.74, 2.41]</td></tr><tr><td>1795-1799</td><td>-0.55</td><td>[-5.48, 4.38]</td><td>Courten</td><td>-5.22</td><td>[-8.72, -1.72]</td></tr><tr><td>1800-1804</td><td>-0.43</td><td>[-5.38, 4.52]</td><td>Stürler</td><td>-3.43</td><td>[-5.01, -1.85]</td></tr><tr><td>1805-1809</td><td>-0.18</td><td>[-5.02, 4.66]</td><td>Helvetische Legion</td><td>-1.54</td><td>[-3.42, 0.35]</td></tr><tr><td>1810-1814</td><td>-0.28</td><td>[-5.04, 4.49]</td><td>Dunant</td><td>-2.52</td><td>[-3.65, -1.38]</td></tr><tr><td>1815-1819</td><td>-0.95</td><td>[-5.76, 3.87]</td><td>Jann</td><td>-1.99</td><td>[-4.19, 0.22]</td></tr><tr><td>1820-1824</td><td>-0.55</td><td>[-5.33, 4.23]</td><td>Ragettli</td><td>-1.87</td><td>[-5.37, 1.63]</td></tr><tr><td>1825-1829</td><td>-0.99</td><td>[-5.80, 3.82]</td><td>De Castella</td><td>-2.20</td><td>[-6.03, 1.64]</td></tr><tr><td>1830-1834</td><td>-1.41</td><td>[-6.28, 3.47]</td><td>Von May</td><td>-2.94</td><td>[-6.90, 1.02]</td></tr><tr><td>1835-1839</td><td>-2.12</td><td>[-6.85, 2.60]</td><td>Perrier</td><td>-1.10</td><td>[-5.08, 2.88]</td></tr><tr><td>1840-1844</td><td>-1.27</td><td>[-6.03, 3.49]</td><td>Sprecher</td><td>-2.43</td><td>[-5.78, 0.92]</td></tr><tr><td>1845-1849</td><td>-0.62</td><td>[-5.55, 4.31]</td><td>Auf der Maur</td><td>-1.60</td><td>[-5.27, 2.07]</td></tr><tr><td>1850-1854</td><td>-0.55</td><td>[-5.53, 4.43]</td><td>Ziegler</td><td>-1.86</td><td>[-5.35, 1.64]</td></tr><tr><td>1855-1859</td><td>-1.39</td><td>[-6.36, 3.57]</td><td>Von Högger</td><td>-0.21</td><td>[-2.54, 2.11]</td></tr><tr><td>Age 21</td><td>-1.45</td><td>[-2.03, -0.87]</td><td>Bleuler</td><td>-3.35</td><td>[-7.02, 0.31]</td></tr><tr><td>Age 22</td><td>-0.78</td><td>[-1.13, -0.42]</td><td>Von Steiger</td><td>-4.18</td><td>[-7.06, -1.30]</td></tr><tr><td>Canton AG</td><td>0.26</td><td>[-0.32, 0.83]</td><td>Von Affry</td><td>-0.16</td><td>[-1.99, 1.67]</td></tr><tr><td>Canton AI</td><td>0.70</td><td>[-1.13, 2.53]</td><td>Ludwig von Sonnenberg</td><td>0.61</td><td>[-3.48, 4.70]</td></tr><tr><td>Canton AR</td><td>-1.43</td><td>[-2.30, -0.56]</td><td>Von Salis-Soglio</td><td>-0.33</td><td>[-4.56, 3.91]</td></tr><tr><td>Canton BE</td><td>0.96</td><td>[0.44, 1.49]</td><td>Britische Schweizer Legion</td><td>-0.45</td><td>[-4.74, 3.85]</td></tr><tr><td>Canton BL</td><td>0.19</td><td>[-0.53, 0.91]</td><td>Niederländische Ostindienkompanie</td><td>-1.31</td><td>[-5.49, 2.86]</td></tr><tr><td>Canton BS</td><td>0.74</td><td>[-0.24, 1.72]</td><td>SEP 1</td><td>1.77</td><td>[0.05, 3.49]</td></tr><tr><td>Canton FR</td><td>1.49</td><td>[0.52, 2.47]</td><td>SEP 2</td><td>1.31</td><td>[-0.16, 2.77]</td></tr><tr><td>Canton GE</td><td>1.71</td><td>[0.63, 2.79]</td><td>SEP 4</td><td>-0.36</td><td>[-1.08, 0.35]</td></tr><tr><td>Canton GL</td><td>0.23</td><td>[-0.83, 1.30]</td><td>SEP 5</td><td>0.32</td><td>[-0.24, 0.89]</td></tr><tr><td>Canton GR</td><td>1.24</td><td>[0.46, 2.02]</td><td>SEP 6</td><td>0.82</td><td>[0.30, 1.35]</td></tr><tr><td>Canton NE</td><td>0.70</td><td>[-0.36, 1.75]</td><td>Temperature anomaly</td><td>0.02</td><td>[-0.16, 0.20]</td></tr><tr><td>Canton NW</td><td>2.12</td><td>[0.30, 3.94]</td><td>σ</td><td>6.56</td><td>[5.87, 7.25]</td></tr></tbody></table>

Rows 1725-1729, ..., 1855-1859: birth periods; rows Johann Baptist Stupa, ..., Niederländische Ostindienkompanie: regiments. Reference groups: birth period 1860-1864, age ≥ 23, canton LU. regiment Pfyffer and SEP 3. The bootstrap confidence intervals are calculated as described in Section 4.3.
Komlos (2009, p. 344-348) summarizes the literature on Europe’s “Early Industrial Growth Puzzle”. During this period, rapid population growth combined with sluggish technological progress in agriculture resulted in a decline in living standards. Unlike the 17th century, however, these challenges did not culminate in a severe subsistence crisis, largely due to the improved economic conditions brought about by early industrialization. However, the development led to a decline in the biological standard of living reflected in a reduction of average human stature. In 18th-century Switzerland, the population grew by approximately 40 per cent, increasing from an estimated 1,200,000 in 1690 to 1,695,961 in 1798 (hsso.ch, Table B.01a). This growth was primarily driven by demographic changes in protoindustrial regions, where higher fertility rates, earlier marriages, and reduced mobility of young males – now able to find work locally – contributed to the population increase (Head-König, 2012, Section 5). At the same time, technological progress in agriculture was slow, despite the effort of learned societies to disseminate knowledge about techniques to improve productivity.<fnref n="12" /> Because of the slow technological progress in agriculture, the relative price of nutrients increased.

In addition, Komlos (2009, p. 344-348) mentions the stress caused by the transformation of the economic system as a negative influence on the biological standard of living. In addition, the increasing degree of commercialization might have played a role: The reduction of subsistence farming led to increasing vulnability with respect to short-run economic fluctuations.<fnref n="13" /> And, of course, the period is characterized by a series of adverse exogenous shocks, such as the Napoleonic wars or the climate related hunger crises in 1770/71 (e.g. Collet, 2019) and 1816/17 (e.g. Frommelt et al., 2017).

Turning to the measurement year effects, the first graph in Figure 3 shows a plot of the estimated truncation points against the weighted average of the measurement period of the respective regiment. For reasons discussed above in the introduction, there is clearly a reduction in the de-facto minimum height requirement, from about 168cm around 1760 to 158cm around 1860. Interestingly, the minimum height requirement for the Swiss army implemented in 1874 was 155cm, very close to our estimate for 1860 (Staub, 2010, p. 147).

When looking at the effect of the measurement period, it is not just the minimum height requirement which we have to consider. As argued in the introduction, it is crucial to take the general situation at the time of recruitment into account to mitigate the selection bias caused by the fact that joining the mercenary service is by and large voluntary. It is the role of the regiment dummy variable to control to some extent for this phenomenon. Table 2 and Figure 1 show that there is not much overlap between the measurement periods of the regiments. Therefore, the estimated parameters reflect not only differences with respect to branch of service or employer compared to the reference regiment (Pfyffer, French service), but also changes with respect to the impact of the general situation during the measurement period of this regiment (1755-1792).

<footnote n="12">¹²Pfister (1985, Chapter 10) lists three major fields for the modernization attempts: the introduction of the potato, the use of leguminous crops in crop rotation, and permanent indoor farming. For milk production, a simulation of the potential consequences shows a substantial increase of about 140 per cent (Pfister, 1985, Table 2/6, p. 114). But Pfister (1985, p. 115-116) also stresses the fact that natural and institutional obstacles prevented a fast implementation of the potential improvements.</footnote>

<footnote n="13">¹³See the literature on business cycles and human stature (Woitek, 2003; Tassenaar and Jacobs, 2004; Brabec, 2005; Sunder and Woitek, 2005). Examples for the literature on the effect of the changing situation in the protoindustrialized regions of Switzerland are Bodmer (1960, p. 213-232), Hauser (1961, p. 184-185), Jäger et al. (1986, p. 44-45), Holenstein (2014, p. 324-325), and Gabathuler (2017, p. 31-33).</footnote>
<figure><img src="image_8.png" /><figcaption>Figure 3: Minimum Height Requirements and Measurement Year/Regiment Effects</figcaption></figure>

Notes: The estimated mimimum height requirements (Figure 1) and the regiment effects (Table 6) are plotted against the weighted average of the measurement period for the regiment. The weight for a specific year is given by the number of observations. Lower plot: the diameter of the circle reflects the number of observations, and a dark blue colored circle represents a parameter significantly different from zero (5% level). The red curve is a smoothing spline based on the underlying data.

The plot of the regiment parameters in the second graph of Figure 3 shows a u-shaped
temporal pattern. At the start and the end of the observation period, the differences to the
regiment *Pfyffer* are small and very imprecisely estimated. For the period 1780-1825, there
are sizeable negative deviations from the average height of the reference regiment, four of them actually significant:<fnref n="14" /> *Courten* (measurement period: 1775-1797, Sardinian service), *Stürler* (measurement period: 1757-1799, Dutch service), *Dunant* (measurement period: 1779-1808, Spanish service), and *Von Steiger* (measurement period: 1816-1830, French service). The effect is sizeable – if we look at the point estimates, the averages are 1.5cm - 5cm smaller than the reference category. This result points towards the increasing difficulties of finding suitable recruits at the time of the Napoleonic Wars discussed in Section 2. Alternatively, the example from the canton Aargau (Section 2) and parts of the literature (e.g. Peyer 1978, p. 713, Moos 1995, p. 129-131) suggest a “vent-for-surplus” interpretation: municipalities used the opportunity of forced recruitment to get rid of unproductive troublemakers and petty criminals, typically with lower socio-economic position. After 1815, the situation started to turn back to normal again. On top of the climatic differences already captured by the cantonal effects, we do not find a significant impact of temperature anomalies on the height of mercenaries. The cantonal effects are difficult to compare with results from the literature, because our sample is not representative with respect to regional coverage (Section 3).<fnref n="15" /> This is also true for the occupational structure. However, the pattern is reasonable: mercenaries with SEP 1 (elite) are on average 1.8cm taller than the mercenaries from the reference category SEP 3 (skilled workers). SEP 2 (lower middle class), SEP 4 (self-employed farmers and fishermen), and SEP 5 (unskilled workers and farm workers) are not distinguishable from SEP 3. Mercenaries with unknown occupation turn out to be on average 0.8cm taller than the reference category.

Another possibility to analyze the impact of the measurement year and the regiment on the change in height is to estimate measurement year and regiment specific trends. Appendix B describes the procedure, and Figures 4 and 5 show the results. When looking at the overall picture of both approaches, we see a negative estimated height trend, very much in line with the result in Figure 2. Even more interesting, for all measurement periods and regiments with birth cohorts during the decline of the proto-industry, we estimate a negative height trend. On the other hand, for a given birth cohort, the estimated height level between different regiments and measurement periods can vary substantially.

<footnote n="14">¹⁴If we look at the point estimates only, there are just three regiments (out of 23) for which the regiment effects are positive: *Johann Baptist Stuppa* (measurement period: 1756-1767, French service), *Von Salis - Zizers* (measurement period: 1765-1792, French service), and *Ludwig von Sonnenberg* (measurement period: 1825-1849, Kingdom of the Two Sicilies).</footnote>

<footnote n="15">¹⁵It might be worthwhile to point out that we find a sizeable negative and significant effect of about 1.4cm for mercenaries from the canton Appenzell Ausserrhoden (AR) compared to the reference canton Lucerne (LU). This is also the case at the end of the 19th century: AR recruits measured 1884-1891 (birthyears: 1865-1872) were on average 3.4cm smaller than LU recruits (Rühli et al., 2008, Figure 7).</footnote>
<figure><img src="image_9.png" /><figcaption>Figure 4: Regiment Specific Height Trend</figcaption></figure>
<figure><img src="image_10.png" /><figcaption>Figure 5: Measurement Year Specific Height Trend</figcaption></figure>
# 6 Conclusion

How did the biological standard of living respond to the changes brought about by the onset of industrialization? Examining height data of Swiss mercenaries born between 1725 and 1865, we are facing two challenges: First, our mercenary records suffer from left-truncation due to height requirements in the recruitment process. Second, the changing conditions on the supply and demand side of the mercenary labor market potentially produce a measurement period selection bias.

We deal with the first challenge by estimating the minimum height requirement separately for each regiment to account for variations in recruitment standards, resource constraints, and advancements in military technology. Beginning at approximately 168cm in the 1760s, the truncation point declined to 158cm by the 1860s, aligning closely with the official minimum height requirement established by the Swiss army in 1874. To account for sample selection bias, we control for the regiment and find evidence for a reduction in measurement period related height around 1800. A plausible explanation for this pattern is the challenging conditions experienced during the Napoleonic Wars.

Our results indicate a decline in average height during the second half of the 18th century, starting around the 1770s, with no signs of recovery in the first half of the 19th century. This result remains robust across different sets of control variables and estimation techniques. Given the specific nature of the mercenary population, it is not feasible to generalize from this finding to the general Swiss population. Nevertheless, the result is broadly in line with European height trends and the already existing evidence from Switzerland reported in the anthropometric literature. The decline in height during the late 18th century aligns with the economic challenges faced by Switzerland during that time, while the persisting low during the first half of the 19th century corresponds with the prevailing understanding of a difficult first phase of industrialization, as described by contemporaries and economic historians.
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# Appendix A Sensitivity Analysis

## A.1 Regiment and Measurement Period Specific Truncation Point Estimation (MTrunk)

For regiments with more than 100 observations for each measurement period, we estimate the truncation point regiment and measurement period specific. The regiments for which this is possible are *Helvetische Legion*, *Ragettli*, *De Castella*, *Ludwig von Sonnenberg*, *Von Salis-Soglio* and *Britische Schweizer Legion*.<fnref n="16" /> For the other regiments we keep the estimated regiment specific truncation parameter. The rest of the analysis remains as described in Section 4.

## A.2 Measurement Period Dummies (Naive)

The heights are modeled via the following linear regression

$$h_i = \mathbf{x}_{\text{Naive},i}^{\top} \boldsymbol{\theta}_{\text{Naive}} + \ddot{u}_i, \quad \forall i \in S, \qquad (10)$$

where

$$\boldsymbol{\theta}_{\text{Naive}} := \left( \ddot{u}, (\ddot{\alpha}_a)_{a=1}^{A-1}, (\ddot{\beta}_b)_{b=1}^{B-1}, (\gamma_m)_{m=1}^{M-1}, (\ddot{\psi}_c)_{c=2}^{C}, (\ddot{\omega}_o)_{o=2}^{O}, \ddot{\kappa}, \nu \right)^{\top},$$

and,

$$\mathbf{x}_{\text{Naive},i}^{\top} := \left( 1, (\mathcal{A}_{i,a})_{a=1}^{A-1}, (\mathcal{B}_{i,b})_{b=1}^{B-1}, (\mathcal{M}_{i,m})_{m=1}^{M-1}, (\mathcal{C}_{i,c})_{c=2}^{C}, (\mathcal{O}_{i,o})_{o=2}^{O}, \mathcal{T}_i, (\mathcal{E}_{i,e})_{e=2}^{E} \right).$$

The only difference to the main methodology Section 4 is that instead of controlling for the regiment, we include measurement period dummies and $\mathcal{E}_{i,e}$, dummies representing the $i^{th}$ mercenary's employer, where France is the reference category (see Table 2 and Figure 1 for a brief overview of the employers). The measurement period dummies are constructed in 5 year steps, ranging from 1755–1884, where 1880–1884 is the reference period. Obviously, this results in a high correlation between the age, birth cohort and measurement period dummies.

The resulting estimated height trend is then given by

$$\hat{h}_{\text{Naive},b} := \hat{\beta}_b + \hat{\boldsymbol{\theta}}_{-\text{Birth,Naive}}^{\top} \bar{\mathbf{x}}_{-\text{Birth,Naive}}. \qquad (11)$$

## A.3 Deaton-Paxson Normalized Measurement Period Dummies (DP)

Heights are modeled via the following linear regression

$$h_i = \mathbf{x}_{\text{DP},i}^{\top} \boldsymbol{\theta}_{\text{DP}} + \tilde{u}_i, \quad \forall i \in S, \qquad (12)$$

<footnote n="16">¹⁶The mercenaries of the *Britische Schweizer Legion* are measured in a single year only (1855).</footnote>
where

$$ \theta_{\text{DP}} := \left( \tilde{\mu}, (\tilde{\alpha}_a)_{a=1}^{A-1}, (\tilde{\beta}_b)_{b=1}^{B-1}, (\tilde{\gamma}_m)_{m=3}^{M}, (\tilde{\psi}_c)_{c=2}^{C}, (\tilde{\omega}_o)_{o=2}^{O}, \tilde{\kappa}, \tilde{\nu} \right)^{\top}, $$

and,

$$ \mathbf{x}_{\text{DP},i}^{\top} := \left( 1, (\mathcal{A}_{i,a})_{a=1}^{A-1}, (\mathcal{B}_{i,b})_{b=1}^{B-1}, (\mathcal{M}_{i,m}^{*})_{m=3}^{M}, (\mathcal{C}_{i,c})_{c=2}^{C}, (\mathcal{O}_{i,o})_{o=2}^{O}, \mathcal{T}_{i}, (\mathcal{E}_{i,e})_{e=2}^{E} \right). $$

In contrast to naive approach above (Section A.2), the measurement period specific dummy variables $\mathcal{M}_{i,m}$ are normalized according to Deaton and Paxson (1994a,b), resulting in

$$ \mathcal{M}_{i,m}^{*} = \mathcal{M}_{i,m} - (m-1)\mathcal{M}_{i,2} + (m-2)\mathcal{M}_{i,1}, \quad m = 3, \dots, M, \qquad (13) $$

where we assume that the measurement period effects average to zero and are orthogonal to a time trend:

$$ \begin{gathered} \tilde{\alpha}_1 = 0; \quad \tilde{\beta}_1 = 0; \\ \sum_{m=1}^{M} \tilde{\gamma}_m = 0; \quad \sum_{m=1}^{M} m \tilde{\gamma}_m = 0. \end{gathered} $$

The reason behind this transformation is the perfect linear relationship between age, cohort and measurement period. The Deaton-Paxson normalization is suited to deal with a cyclical measurement effect, not the distortion of the long-run height trend Bodenhorn et al. (2017) have in mind. However, we think that this is also a worthwhile exercise.

The resulting estimated height trend is then given by

$$ \hat{h}_{\text{DP},b} := \hat{\beta}_b + \hat{\theta}_{-\text{Birth,DP}}^{\top} \tilde{\mathbf{x}}_{-\text{Birth,DP}}. \qquad (14) $$

To arrive at equation (13), we start with the assumptions above and their implications for $\tilde{\gamma}_1$ and $\tilde{\gamma}_2$:

$$ \begin{align*} \begin{pmatrix} 1 & 1 \\ 1 & 2 \end{pmatrix} \begin{pmatrix} \tilde{\gamma}_1 \\ \tilde{\gamma}_2 \end{pmatrix} &= \begin{pmatrix} -\sum_{m=3}^{M} \tilde{\gamma}_m \\ -\sum_{m=3}^{M} m \tilde{\gamma}_m \end{pmatrix}; \\ \begin{pmatrix} \tilde{\gamma}_1 \\ \tilde{\gamma}_2 \end{pmatrix} &= \begin{pmatrix} 2 & -1 \\ -1 & 1 \end{pmatrix} \begin{pmatrix} -\sum_{m=3}^{M} \tilde{\gamma}_m \\ -\sum_{m=3}^{M} m \tilde{\gamma}_m \end{pmatrix}; \\ \tilde{\gamma}_1 &= \sum_{m=3}^{M} m \tilde{\gamma}_m - 2 \sum_{m=3}^{M} \tilde{\gamma}_m = \sum_{m=3}^{M} (m-2) \tilde{\gamma}_m; \\ \tilde{\gamma}_2 &= \sum_{m=3}^{M} \tilde{\gamma}_m - \sum_{m=3}^{M} m \tilde{\gamma}_m = -\sum_{m=3}^{M} (m-1) \tilde{\gamma}_m. \end{align*} $$
Plugging $\tilde{\gamma}_1$ and $\tilde{\gamma}_2$ into Model (12) results in

$$
\begin{align*}
h_i &= \tilde{\mu} + \dots + \sum_{m=1}^{M} \tilde{\gamma}_m \mathcal{M}_{i,m} + \epsilon_i = \\
&= \tilde{\mu} + \dots + \tilde{\gamma}_1 \mathcal{M}_{i,1} + \tilde{\gamma}_2 \mathcal{M}_{i,2} + \sum_{m=3}^{M} \tilde{\gamma}_m \mathcal{M}_{i,m} + \epsilon_i = \\
&= \tilde{\mu} + \dots + \sum_{m=3}^{M} (m-2) \tilde{\gamma}_m \mathcal{M}_{i,1} - \sum_{m=3}^{M} (m-1) \tilde{\gamma}_m \mathcal{M}_{i,2} + \sum_{m=3}^{M} \tilde{\gamma}_m \mathcal{M}_{i,m} + \epsilon_i = \\
&= \tilde{\mu} + \dots + \sum_{m=3}^{M} \left( \underbrace{\mathcal{M}_{i,m} - (m-1)\mathcal{M}_{i,2} + (m-2)\mathcal{M}_{i,1}}_{\mathcal{M}_{i,m}^*} \right) \tilde{\gamma}_m + \epsilon_i .
\end{align*}
$$

A.4 Penalized Maximum Likelihood Estimation (Penalized)

The relationship between heights and independent variables is again assumed linear. How-
ever, now we include both regiment and measurement period dummies. The assumed model
structure is given by

$$
h_i = \mathbf{x}_{\text{Pen},i}^{\top} \boldsymbol{\theta}_{\text{Pen}} + \dot{u}_i, \quad \forall i \in S, \qquad (15)
$$

where

$$
\boldsymbol{\theta}_{\text{Pen}} := \left( \dot{\mu}, (\dot{\alpha}_a)_{a=1}^{A-1}, (\dot{\beta}_b)_{b=1}^{B-1}, (\dot{\pi}_r)_{r=2}^{R}, (\dot{\gamma}_m)_{m=1}^{M-1}, (\dot{\psi}_c)_{c=2}^{C}, (\dot{\omega}_o)_{o=2}^{O}, \dot{\kappa} \right)^{\top},
$$

and,

$$
\mathbf{x}_{\text{Pen},i}^{\top} := \left( 1, (\mathcal{A}_{i,a})_{a=1}^{A-1}, (\mathcal{B}_{i,b})_{b=1}^{B-1}, (\mathcal{R}_{i,r})_{r=2}^{R}, (\mathcal{M}_{i,m})_{m=1}^{M-1}, (\mathcal{C}_{i,c})_{c=2}^{C}, (\mathcal{O}_{i,o})_{o=2}^{O}, \mathcal{T}_i \right).
$$

The above design matrix is highly collinear. Hence, we penalize the regression coeffi-
cients in the likelihood (5) as follows

$$
\ell_{\text{Pen}}(\tilde{\boldsymbol{\theta}}_{\text{Pen}}, \tilde{\boldsymbol{\sigma}} | \{h_i, \mathbf{x}_{\text{Pen},i}, \hat{a}_i\}_{i \in \hat{S}}) := \ell(\tilde{\boldsymbol{\theta}}_{\text{Pen}}, \tilde{\boldsymbol{\sigma}} | \{h_i, \mathbf{x}_{\text{Pen},i}, \hat{a}_i\}_{i \in \hat{S}}) + \frac{\lambda}{2} \sum_{j \in \text{Pen}} \tilde{\boldsymbol{\theta}}_{\text{Pen},j}^2, \quad (16)
$$

where Pen contains all the regression coefficient indices apart from the birth period effects and $\lambda$ is a regularization parameter. In other words we penalize all the coefficients apart from the birth cohort effects. Since the first and second derivative of (16) still exist, the maximization of the above penalized likelihood is done in the same way as described at the end of Section 4. The optimal regularization parameter is found via 10-fold cross-validation.

The resulting estimated height trend is then given by

$$
\hat{h}_{\text{Pen},b} := \hat{\beta}_b + \hat{\boldsymbol{\theta}}_{-\text{Birth},\text{Pen}}^{\top} \tilde{\mathbf{x}}_{-\text{Birth},\text{Pen}}. \qquad (17)
$$
## A.5 Results of the Sensitivity Analysis

Figure 6 summarizes the estimated average heights of the methods described in Sections A.1-A.4. For comparison reasons, we also include the result of the main text (Section 4). Since the birth cohort effect can not be distinguished from the measurement period effect and age effect, the naive approach of Section A.2 results in a too extreme negative height trend estimate. The DP approach of Section A.3 tackles the issue of the perfect linear relationship between birth year, measurement year and age, nevertheless, the estimated height trend is not trustworthy. The reason is the fact that we only observe one regiment (Niederländische Ostindienkompanie) at the very end of our measurement period, restricting the number of birthyears for those particular measurement years. Compared to our main result, the penalized approach of Section A.4 results in a very similar trend.

<figure><img src="image_11.png" /><figcaption>Figure 6: Sensitivity Analysis</figcaption></figure>

# Appendix B Regiment and Measurement Year Specific Analysis

## B.1 Regiment Specific Analysis

For regiments $l = 1, \dots, L$, the heights are modeled via the following regiment specific linear regressions

$$h_i = \mathbf{x}_{\text{Reg},i}^{\top} \boldsymbol{\theta}_{\text{Reg}}^{(l)} + \hat{u}_i, \quad \forall i \in S^{(l)}, \qquad (18)$$
where

$$S^{(l)} := \{i \in \text{Reg}_l : h_i \ge a_i\},$$

$$\boldsymbol{\theta}_{\text{Reg}}^{(l)} := \left( \mu^{(l)}, (\acute{\alpha}_a^{(l)})_{a=1}^{A-1}, (\acute{\beta}_b^{(l)})_{b=1}^{\acute{B}-1}, \acute{\kappa}^{(l)} \right)^{\top},$$

and,

$$\boldsymbol{x}_{\text{Reg},i}^{\top} := \left( 1, (\mathcal{A}_{i,a})_{a=1}^{A-1}, (\mathcal{B}_{i,b})_{b=1}^{\acute{B}-1}, \mathcal{T}_i \right).$$

The birth cohorts vary across regiments, indicated by the acute on top of the birth period index, and there is not a single regiment covering all the birth periods. The last birth cohort in a specific regiment forms the reference group, respectively.<fnref n="17" /> For each of the 12 regiments, the estimation is carried out as described in the main text in Section 4, without control variables for cantons and socioeconomic position.

The resulting estimated regiment specific height trends are given by

$$\hat{h}_{\text{Reg},b}^{(l)} := \hat{\beta}_{b}^{(l)} + \hat{\theta}_{-\text{Birth,Reg}}^{(l)\top} \bar{\boldsymbol{x}}_{-\text{Birth,Reg}}^{(l)}, \quad (19)$$

## B.2 Measurement Period Specific Analysis

For measurement periods $m = 2, \dots, M-1$, that is 1760–1879 in 5 years steps, the heights are modeled via the following measurement period specific linear regressions

$$h_i = \boldsymbol{x}_{\text{Measure},i}^{\top} \boldsymbol{\theta}_{\text{Measure}}^{(m)} + \acute{u}_i, \quad \forall i \in S^{(m)}, \quad (20)$$

where where Measure$_m$ holds the indices of the $m^{th}$ measurement period,

$$S^{(m)} = \{i \in \text{Measure}_m : h_i \ge a_i\},$$

$$\boldsymbol{\theta}_{\text{Measure}}^{(m)} = \left( \mu^{(m)}, (\acute{\alpha}_a^{(m)})_{a=1}^{A-1}, (\acute{\beta}_b^{(m)})_{b=1}^{\acute{B}-1}, \acute{\kappa}^{(m)} \right)^{\top},$$

and,

$$\boldsymbol{x}_{\text{Measure},i}^{\top} = \left( 1, (\mathcal{A}_{i,a})_{a=1}^{A-1}, (\mathcal{B}_{i,b})_{b=1}^{\acute{B}-1}, \mathcal{T}_i \right).$$

The birth cohorts vary across measurement periods. We use the same acute on top of the birth period index as in the regiment specific analysis above, and there is not a single measurement period covering all the birth periods. The last birth cohort in a specific measurement period forms the reference group, respectively. As in the regiment specific analysis, we do not control for cantons and socioeconomic position. For each of the 24 measurement periods, the estimation is carried out as described in the main text in Section 4.

<footnote n="17">¹⁷For five regiments (Johann Baptist Stuppa, Von Salis-Zizers, Jann, Von Steiger, Auf der Maur) the total number of observations is below 100, after excluding individuals with a birth period with less than 30 observations. Hence, these five regiments are not included in this analysis.</footnote>
The resulting estimated measurement period specific height trends are given by

$$ \hat{h}_{\text{Measure},b}^{(m)} = \hat{\beta}_{b}^{(m)} + \hat{\theta}_{-\text{Birth,Measure}}^{(m)\top} \tilde{\boldsymbol{x}}_{-\text{Birth,Measure}}^{(m)}. \quad (21) $$
# Appendix C Swiss Mercenary Regiments: Background Information

<table><caption>Table 7: Swiss Regiments (Overview)</caption><thead><tr><th rowspan="2"></th><th colspan="2">Before 1797</th><th colspan="2">After 1815/15</th></tr><tr><th>Regiments</th><th>Companies</th><th>Regiments</th><th>Companies</th></tr></thead><tbody><tr><td>France</td><td>12</td><td>193</td><td>6</td><td>120</td></tr><tr><td>Netherlands</td><td>6</td><td>68</td><td>4</td><td>64-82</td></tr><tr><td>Sardinia</td><td>4</td><td>44</td><td>1</td><td>12</td></tr><tr><td>Spain</td><td>4</td><td>60</td><td>6</td><td>60</td></tr><tr><td>Naples</td><td>4</td><td>38</td><td>4</td><td>48</td></tr></tbody></table>

Preliminary figures provided in Foerster (2010, p. 248, 250). In addition, there were Swiss soldiers in other units (e.g. since 1831 the French Foreign Legion), and smaller elite units such as the Cent-Suisses.

<table><caption>Table 8: Official Minimum Height Requirements: Examples</caption><thead><tr><th>Regiment</th><th>Canton</th><th>Employer</th><th>Year</th><th>Height</th></tr></thead><tbody><tr><td>Karl von Reding</td><td>SZ</td><td>ESP</td><td>1757</td><td>167.8</td></tr><tr><td>Dunant</td><td>SG</td><td>ESP</td><td>1758</td><td>167.8</td></tr><tr><td>von Jaun</td><td>UR/other catholic cantons</td><td>KTS</td><td>1774</td><td>165.1</td></tr><tr><td>von Reding und Betschart</td><td>SZ</td><td>ESP</td><td>1779</td><td>165.1</td></tr><tr><td>von Thurn</td><td>SG</td><td>ESP</td><td>1779</td><td>165.1</td></tr><tr><td>Jann</td><td>UW</td><td>ESP</td><td>1793</td><td>165.1</td></tr><tr><td>4 Regiments</td><td>Swiss Confederation</td><td>FRA</td><td>1803</td><td>167.8</td></tr><tr><td>5 Regiments</td><td>Swiss Confederation</td><td>ESP</td><td>1804</td><td>165.1</td></tr><tr><td>Ziegler</td><td>SH, SG, AG, TG</td><td>NLD</td><td>1814</td><td>164.8</td></tr><tr><td>Line Regiments</td><td>Swiss Confederation</td><td>FRA</td><td>1816</td><td>165.1</td></tr><tr><td>Guard Regiments</td><td>Swiss Confederation</td><td>FRA</td><td>1816</td><td>167.8</td></tr><tr><td>4 Regiments</td><td>Swiss Confederation</td><td>KTS</td><td>1826</td><td>165.1</td></tr></tbody></table>

Cantons: SZ: Schwyz; SG: St. Gallen; ZH: Zurich; SH: Schaffhausen; AG: Aargau; TG: Thurgau, UR: Uri, UW: Unterwalden.

Employers: ESP: Spain; FRA: France; NLD: Netherlands; KTS: Kingdom of the Two Sicilies.

Archives: StASZ: State Archive Schwyz; StiASG: Abbey Archives St. Gallen; StAZH: State Archive Zurich; StAF: State Archive Fribourg.

Sources: StASZ HA.III.2065, StiASG Rubrik 9 Faszikel 2, StiASG Rubrik 9_Faszikel 9, StiASG Rubrik 9 Faszikel 7, StAZH OS AF 1 (p. 120-133), StAZH OS AF 2 (p. 409-481), StAZH OS NF 1 (p. 53-84), StAZH OS NF 1 (p. 309-350), StAZH OS NF 1 (p. 309-350), StAF DM VI 56
<figure><img src="image_12.png" /><figcaption>Figure 7: Estimated Minimum Height Requirements</figcaption></figure>
# Appendix D Sources

<table><caption>Table 9: Sources</caption><thead><tr><th>ID</th><th>Archive</th><th>Signature</th><th>Regiment</th><th>Employer</th><th>Measurement Year</th></tr></thead><tbody><tr><td>(1)</td><td>AAEB</td><td>B 241a/22 GF</td><td>Eptingue</td><td>FRA</td><td>1753 - 1770</td></tr><tr><td>(2)</td><td>AEV</td><td>Augustin de Riedmatten I, R 2/13</td><td>Courten</td><td>SAR</td><td>1778 - 1795</td></tr><tr><td>(3)</td><td>AEV</td><td>Mf35 66/1-2</td><td>Courten</td><td>SAR</td><td>1772 - 1797</td></tr><tr><td>(4)</td><td>AEV</td><td>SE 30</td><td>Courten</td><td>SAR</td><td>1775 - 1793</td></tr><tr><td>(5)</td><td>BAR</td><td>B0#1000/1483#2761*</td><td>Helvetische Legion</td><td>SWI</td><td>1798 - 1799</td></tr><tr><td>(6)</td><td>BAR</td><td>B0#1000/1483#2946*</td><td>Helvetische Legion</td><td>SWI</td><td>1798 - 1802</td></tr><tr><td>(7)</td><td>BAR</td><td>B0#1000/1483#2947*</td><td>Helvetische Legion</td><td>SWI</td><td>1801 - 1802</td></tr><tr><td>(8)</td><td>BAR</td><td>B0#1000/1483#2948*</td><td>Helvetische Legion</td><td>SWI</td><td>1800 - 1802</td></tr><tr><td>(9)</td><td>BAR</td><td>B0#1000/1483#2949*</td><td>Helvetische Legion</td><td>SWI</td><td>1801 - 1801</td></tr><tr><td>(10)</td><td>BAR</td><td>B0#1000/1483#2950*</td><td>Helvetische Legion</td><td>SWI</td><td>1800 - 1801</td></tr><tr><td>(11)</td><td>BAR</td><td>J4.12#1000/1268#17*</td><td>Britische Schweizer Legion</td><td>GBR</td><td>1855 - 1855</td></tr><tr><td>(12)</td><td>BAR</td><td>J4.14#1000/1269#1*</td><td>Von Salis-Soglio</td><td>KTS</td><td>1827 - 1831</td></tr><tr><td>(13)</td><td>BAR</td><td>J4.14#1000/1269#2*</td><td>Von Salis-Soglio</td><td>KTS</td><td>1826 - 1842</td></tr><tr><td>(14)</td><td>BAR</td><td>J4.14#1000/1269#3*</td><td>Von Salis-Soglio</td><td>KTS</td><td>1842 - 1850</td></tr><tr><td>(15)</td><td>BAR</td><td>J4.14#1000/1269#4*</td><td>Von Salis-Soglio</td><td>KTS</td><td>1850 - 1855</td></tr><tr><td>(16)</td><td>NA</td><td>2.10.50 121 - 2.10.50 254</td><td>Ndl. Ostindienkompanie</td><td>NLD</td><td>1848 - 1884</td></tr><tr><td>(17)</td><td>StAAG</td><td>DM01/0073</td><td>Ziegler</td><td>NLD</td><td>1815 - 1828</td></tr><tr><td>(18)</td><td>StAAR</td><td>Aa.49-03-03</td><td>Stürler</td><td>NLD</td><td>1747 - 1780</td></tr><tr><td>(19)</td><td>StAAR</td><td>Ca.H11-05</td><td>Sprecher</td><td>NLD</td><td>1814 - 1816</td></tr><tr><td>(20)</td><td>StAAR</td><td>Ca.H11-06</td><td>De Castella</td><td>FRA</td><td>1807 - 1813</td></tr><tr><td>(21)</td><td>StAAR</td><td>Ca.H11-06</td><td>Perrier</td><td>FRA</td><td>1807 - 1811</td></tr><tr><td>(22)</td><td>StAAR</td><td>Ca.H11-06</td><td>Ragettli</td><td>FRA</td><td>1806 - 1813</td></tr><tr><td>(23)</td><td>StAAR</td><td>Ca.H11-06</td><td>Von May</td><td>FRA</td><td>1807 - 1811</td></tr><tr><td>(24)</td><td>StABS</td><td>Fremde Staaten Frankreich F 7.4.</td><td>Ragettli</td><td>FRA</td><td>1806 - 1812</td></tr><tr><td>(25)</td><td>StABS</td><td>Fremde Staaten Frankreich F 7.5.</td><td>De Castella</td><td>FRA</td><td>1807 - 1811</td></tr><tr><td>(26)</td><td>StABS</td><td>Fremde Staaten Frankreich F 7.6.</td><td>Perrier</td><td>FRA</td><td>1806 - 1816</td></tr><tr><td>(27)</td><td>StABS</td><td>Fremde Staaten Frankreich F 7.7.</td><td>Bleuler</td><td>FRA</td><td>1816 - 1830</td></tr><tr><td>(28)</td><td>StABS</td><td>Fremde Staaten Frankreich F 7.7.</td><td>De Castella</td><td>FRA</td><td>1812 - 1813</td></tr><tr><td>(29)</td><td>StABS</td><td>Fremde Staaten Frankreich F 7.7.</td><td>Perrier</td><td>FRA</td><td>1812 - 1813</td></tr><tr><td>(30)</td><td>StABS</td><td>Fremde Staaten Frankreich F 7.7.</td><td>Ragettli</td><td>FRA</td><td>1813 - 1813</td></tr><tr><td>(31)</td><td>StABS</td><td>Fremde Staaten Frankreich F 7.7.</td><td>Von Affry</td><td>FRA</td><td>1816 - 1829</td></tr><tr><td>(32)</td><td>StABS</td><td>Fremde Staaten Frankreich F 7.7.</td><td>Von Högger</td><td>FRA</td><td>1816 - 1830</td></tr><tr><td>(33)</td><td>StABS</td><td>Fremde Staaten Frankreich F 7.7.</td><td>Von May</td><td>FRA</td><td>1813 - 1813</td></tr><tr><td>(34)</td><td>StALU</td><td>AKT 13/701</td><td>Johann Baptist Stuppa</td><td>FRA</td><td>1755 - 1767</td></tr><tr><td>(35)</td><td>StALU</td><td>AKT 23/20 C</td><td>Von Salis-Zizers</td><td>FRA</td><td>1776 - 1780</td></tr><tr><td>(36)</td><td>StALU</td><td>COD 1780</td><td>Von Salis-Zizers</td><td>FRA</td><td>1752 - 1794</td></tr><tr><td>(37)</td><td>StALU</td><td>COD 1795</td><td>Pfyffer</td><td>FRA</td><td>1735 - 1792</td></tr><tr><td>(38)</td><td>StALU</td><td>COD 1880</td><td>Dunant</td><td>ESP</td><td>1803 - 1808</td></tr><tr><td>(39)</td><td>StALU</td><td>COD 1880</td><td>Jann</td><td>ESP</td><td>1805 - 1808</td></tr><tr><td>(40)</td><td>StALU</td><td>COD 1885</td><td>Ludwig von Sonnenberg</td><td>KTS</td><td>1825 - 1840</td></tr><tr><td>(41)</td><td>StALU</td><td>COD 1895</td><td>Ludwig von Sonnenberg</td><td>KTS</td><td>1841 - 1849</td></tr><tr><td>(42)</td><td>StASG</td><td>KA R.61a B 1</td><td>Bleuler</td><td>FRA</td><td>1816 - 1830</td></tr><tr><td>(43)</td><td>StASG</td><td>KA R.61a B 1</td><td>De Castella</td><td>FRA</td><td>1812 - 1813</td></tr><tr><td>(44)</td><td>StASG</td><td>KA R.61a B 1</td><td>Perrier</td><td>FRA</td><td>1812 - 1813</td></tr><tr><td>(45)</td><td>StASG</td><td>KA R.61a B 1</td><td>Ragettli</td><td>FRA</td><td>1812 - 1813</td></tr><tr><td>(46)</td><td>StASG</td><td>KA R.61a B 1</td><td>Von Affry</td><td>FRA</td><td>1816 - 1830</td></tr><tr><td>(47)</td><td>StASG</td><td>KA R.61a B 1</td><td>Von Högger</td><td>FRA</td><td>1816 - 1830</td></tr><tr><td>(48)</td><td>StASG</td><td>KA R.61a B 1</td><td>Von May</td><td>FRA</td><td>1812 - 1813</td></tr></tbody></table>

Continued on next page
<table><caption>Table 9 continued</caption><thead><tr><th>ID</th><th>Archive</th><th>Signature</th><th>Regiment</th><th>Employer</th><th>Measurement Year</th></tr></thead><tbody><tr><td>(49)</td><td>StASG</td><td>KA R.61a B 2</td><td>Ziegler</td><td>NLD</td><td>1815 - 1828</td></tr><tr><td>(50)</td><td>StASH</td><td>Militaria OD 10</td><td>Stürler</td><td>NLD</td><td>1736 - 1796</td></tr><tr><td>(51)</td><td>StATG</td><td>4'482'5</td><td>Perrier</td><td>FRA</td><td>1807 - 1812</td></tr><tr><td>(52)</td><td>StATG</td><td>4'482'5</td><td>Von May</td><td>FRA</td><td>1807 - 1812</td></tr><tr><td>(53)</td><td>StATG</td><td>4'482'6</td><td>Bleuler</td><td>FRA</td><td>1816 - 1828</td></tr><tr><td>(54)</td><td>StATG</td><td>4'482'6</td><td>Von Högger</td><td>FRA</td><td>1816 - 1828</td></tr><tr><td>(55)</td><td>StATG</td><td>4'482'8</td><td>De Castella</td><td>FRA</td><td>1806 - 1812</td></tr><tr><td>(56)</td><td>StATG</td><td>4'482'8</td><td>Ragettli</td><td>FRA</td><td>1806 - 1812</td></tr><tr><td>(57)</td><td>StATG</td><td>4'484'2</td><td>Ziegler</td><td>NLD</td><td>1814 - 1828</td></tr><tr><td>(58)</td><td>StAZG</td><td>E 61.15</td><td>Auf der Maur</td><td>NLD</td><td>1816 - 1828</td></tr><tr><td>(59)</td><td>StAZG</td><td>E 61.15</td><td>Von Affry</td><td>FRA</td><td>1816 - 1816</td></tr><tr><td>(60)</td><td>StAZG</td><td>E 61.15</td><td>Von Högger</td><td>FRA</td><td>1816 - 1830</td></tr><tr><td>(61)</td><td>StAZG</td><td>E 61.15</td><td>Von Steiger</td><td>FRA</td><td>1816 - 1830</td></tr><tr><td>(62)</td><td>StiASG</td><td>Bd. 828</td><td>Dunant</td><td>ESP</td><td>1785 - 1795</td></tr><tr><td>(63)</td><td>StiASG</td><td>Rubrik 27 Faszikel 4b</td><td>Dunant</td><td>ESP</td><td>1779 - 1784</td></tr></tbody></table>

**Archives:** AAEB: Archives de l'ancien Évêché de Bâle, AEV: Archives de l'Etat du Valais, BAR: Bundesarchiv, NA: Nationaal Archief Netherlands, StAAG: Staatsarchiv Aargau, StAAR: Staatsarchiv Appenzell Ausserrhoden, StABS: Staatsarchiv Basel-Stadt, StALU: Staatsarchiv Luzern, StASG: Staatsarchiv St. Gallen, StASH: Staatsarchiv Schaffhausen, StATG: Staatsarchiv Thurgau, StAZG: Staatsarchiv Zug, StiASG: Stiftsarchiv St. Gallen.

**Employers:** FRA: France, SAR: Sardinia, SWI: Switzerland, GBR: United Kingdom, KTS: Kingdom of the Two Sicilies, NLD: Netherlands, ESP: Spain.

**Secondary Sources:** (1): Bregnard (1996); (2): Fayard Duchêne and de Riedmatten (1997); (3) and (4): Gally-de Riedmatten (2014); (16): Krauer (2024).