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Loose Cannons: War Veterans and the Erosion of Democracy in Weimar Germany

Published online by Cambridge University Press:  02 February 2023

Christoph Koenig*
Affiliation:
Assistant Professor, University of Rome Tor Vergata, Department of Economics and Finance, Via Columbia 2, 00133 Roma, Italy and Honorary Research Fellow, University of Bristol, School of Economics, The Priory Road Complex, Priory Road, BS8 1TU Clifton, United Kingdom. E-mail: [email protected].
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Abstract

This article shows that democracy in Weimar Germany was eroded by the political legacy of WWI. Using novel data on WWI veterans and an election panel from 1893–1933, I find that former soldiers are associated with a sizeable, persistent, and momentous shift in political preferences from left to right. I provide suggestive evidence that war participation made veterans highly receptive to nationalism and Anti-Communism. This alienated them from leftwing parties and drove the majority toward the political right. Contrary to historical accounts, veterans’ shifts in political preferences cannot be explained by exposure to violence or other polarizing post-war events.

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the Economic History Association

Far more [German WWI] veterans managed subsequently to lead unremarkable humdrum lives than sought refuge in a life of violence. (…) Yet, they did vote.

—Richard Bessel (Reference Bessel and Roseman1995)

The rise of rightwing extremism in Europe shortly after WWI led to the breakdown of many democratic regimes and culminated in a second, even deadlier, world war. Social science has discussed several factors common to both winners and losers of WWI which may explain this coincidence. One part of the literature has noted the role of war veterans in the rise of Fascism in several countries (Ward Reference Ward and Stephen1975; Alcalde Reference Alcalde2017). The Red Menace theory, on the other hand, interprets the surge in rightwing extremism as a political backlash against the Communist uprisings triggered by WWI, most notably Russia’s October Revolution (Linz Reference Linz and Laqueur1976; Luebbert Reference Luebbert1991; Brustein and Berntson Reference Brustein and Berntson1999). So far, these two factors and their explanatory power for the rise of Fascism in Interwar Europe have been studied in isolation and corroborated by little empirical evidence.

In this article, I study the interplay between WWI veterans and Anti-Communism during the most significant democratic breakdown of the Interwar period and modern history—Weimar Germany. Following a near military defeat and a short, non-violent revolution in October 1918, the German Empire swiftly transformed from a constitutional monarchy into a parliamentary democracy. This process was enabled and overseen by a majority coalition of left and centrist parties and eventually led to the end of WWI in November 1918. The newly founded Weimar Republic, however, collapsed already in 1933 when a rightwing coalition between the Nazi Party and the conservative German National People’s Party (DNVP) enabled Adolf Hitler’s seizure of power.

The role of WWI participants, a sixth of the post-war population and half of all male voters, in Weimar democracy’s decline is a contentious issue in historical research. Several scholars have claimed that veterans were brutalized by war or blamed the democratic transition for the defeat. As a result, they allegedly helped bring down democracy by getting involved in rightwing parties or paramilitary groups. Recent research has called this association into question by highlighting the activities of many former soldiers on the side of the left. Footnote 1 Yet, the focus has so far been entirely on individuals or groups, whereas nothing is known about the collective political impact of WWI veterans. Similarly, a link between WWI participants and the spread of Anti-Communism in Weimar Germany has not been explored empirically up to now. My paper attempts to fill these gaps in existing research by assessing veterans’ impact on election results and making progress in understanding its mechanisms and the general insights to be drawn from it.

This empirical investigation faces two key obstacles: the destruction of almost all WWI rosters and the non-random selection in and out of the veteran population via draft and survival, which may be linked to underlying political preferences. I tackle the first issue by leveraging census data to approximate the number of surviving WWI participants. Concerning selection, I adopt two strategies: first, I exploit the fact that parliamentary elections were already taking place before the war with comparable parties and platforms. This allows me to create a panel of 362 constituencies over 14 elections from 1893 to 1933 and apply a Differences-in-Differences (DiD) framework. This approach identifies within-constituency variation in election results, assuming that, conditional on key drivers of draft and survival, the population share of veterans was assigned as good as randomly. My second strategy combines the DiD with an instrumental variables (IV) approach and exploits occupation-specific differences in exemptions for workers across war-related industries as a source of exogenous variation in war participation.

The first core result of this article is that veterans did contribute to the decline of the Weimar Republic in the sense that they significantly raised votes for the anti-democratic rightwing parties that would later enable Hitler’s seizure of power. Constituencies with a 1 percentage point (pp) higher share of veterans per capita increased support for the right, on average, by 1.2 pp compared to pre-war elections. The magnitude suggests a multiplier effect, and that war participants likely passed their opinions on to non-combatants as well. These estimates are also quantitatively relevant: a one standard deviation (SD) increase in the veteran share (2 pp) raised votes for the right by 12.8 percent of their post-war SD. A more speculative counter-factual, assuming the entire absence of veterans (or no effect on voting), thus implies an average reduction of the rightwing vote share by 17 pp, which could have enabled pro-democratic coalitions after the crucial elections of 1932/33 leading to Hitler’s chancellorship. These results are robust to several checks concerning the validity of the identifying assumptions. The IV strategy yields qualitatively similar results of an even higher magnitude, most likely driven by the higher political responsiveness of the areas from which the IV estimates are identified.

Beyond the general increase in rightwing votes, my analysis also documents three novel and historically relevant empirical facts: first, veterans’ impact was both instant and persistent. Using an event study, I show that the effect occurs already during the elections for the constitutional assembly in January 1919—only two months after WWI had officially ended—and thus renders it unrelated to several potentially catalyzing post-war events like the Versailles Treaty, the Hyperinflation, and the rising power of paramilitary groups like the Stahlhelm in the 1930s. Thereafter, the effect persists with only little changes until the final Weimar elections in 1933. Second, the gains for the right came almost entirely at the expense of the moderate political left rather than the center. WWI participants thus allowed the right to make inroads into the working class as early as 1919, before the Great Depression. Finally, looking at individual parties reveals that veterans were not exclusively supporting the Nazi Party. Rather, the main beneficiary was the conservative DNVP.

Which mechanisms could explain these findings? The effect’s timing and persistence suggest that WWI shifted veterans’ political preferences from redistribution to nationalism. One possibility could be that the traumatic WWI defeat increased the appeal of conspiracy theories like the stab-in-the-back myth that (falsely) blamed the defeat on the preceding German revolution in 1918 and an alleged cooperation of the moderate left with radical Bolsheviks at home and abroad. Rightwing parties were the most likely beneficiaries since they were staunchly anti-communist and, unlike others, could offer a highly inclusive form of nationalism as an alternative identity to former leftwing soldiers.

Several pieces of evidence speak in support of this interpretation: first, veterans did not harm centrist parties, which could hardly be associated with Communism. The far-left, in turn, was not affected, which suggests that soldiers actually supporting Communism were not responding. Secondly, when the Nazi Party included more leftwing elements into its strategy in the 1930s, veterans completely withdrew their support and exclusively benefited the firmly anti-communist DNVP. Thirdly, the effects do not seem to hinge on changes in political supply. Finally, war participants also voted similarly in referenda and presidential elections when party loyalty mattered less.

This paper relates to several research areas in the social sciences. First, I contribute to the empirical literature in political economy and economic history seeking to explain the success of rightwing parties in Weimar Germany. I add to this research by quantifying the impact of veterans and providing the first empirical evidence linking WWI to the success of rightwing parties in Germany prior to WWII. Footnote 2

Secondly, this study links to research on the political effects of war participation. Footnote 3 My study complements existing work with evidence from Weimar Germany indicating that veterans swung elections to the right due to a popular anti-communist conspiracy theory. The power of narratives for interpreting war experiences was also a crucial factor in other democratic breakdowns after WWI such as Austria and Italy (Alcalde Reference Alcalde2017).

Thirdly, I add to research on religious coping after traumatic experiences (Belloc, Drago, and Galbiati Reference Belloc, Drago and Galbiati2016; Bentzen Reference Bentzen2019) and a broader literature on the impact of collective, life-changing events (Giuliano and Spilimbergo Reference Giuliano and Spilimbergo2014; Depetris-Chauvin, Durante, and Campante Reference Depetris-Chauvin, Durante and Campante2020). Since veterans’ susceptibility to anti-communist conspiracy theories seems to result from coping with the defeat in WWI, my findings illustrate the wider relevance of this mechanism in secular contexts. The case of Weimar Germany also shows that, when a life-changing event like WWI alters the political preferences of a substantial part of the electorate, this can dramatically change a country’s political landscape and eventually contribute to the decline of democracy.

Lastly, my study lends support to the Red Menace theory, which attributes the rise of Fascism after WWI to Anti-Communism (Linz Reference Linz and Laqueur1976; Luebbert Reference Luebbert1991; Brustein and Berntson Reference Brustein and Berntson1999). In one of the few related empirical studies, Acemoglu et al. (Reference Acemoglu, Giuseppe de Feo and Russo2020) find that Red Menace fears among Italy’s middle class helped Mussolini’s election victory. Those fears, however, were not spread by WWI veterans. My paper adds to this literature in two ways: firstly, I show that among German veterans, Anti-Communism could even hold great appeal for working-class voters. Secondly, I find that this created a steady rightwing support base, which was potentially also crucial in enabling Hitler’s seizure of power.

HISTORICAL CONTEXT

WWI and the End of the German Empire

The German Empire was proclaimed in 1871 following Prussia’s victory over France. It was a constitutional monarchy under Prussia’s leadership, featuring the first publicly elected national parliament on German territory after an initial failed attempt in 1848. Under Emperor Wilhelm II, the German Empire started a period of unpredictable and provocative foreign policy, which isolated it from most of its former European allies, most notably Russia and the United Kingdom. As a result, it took only a spark in the form of the assassination of Archduke Franz Ferdinand of Austria to start WWI on the 28th of July 1914 (Berman Reference Berman2001; Hewitson Reference Hewitson and James2008). Among the German population, the initial excitement about the war faded very quickly with an increasing death toll, unpredictable duration of the war, frequent food shortages, and generally gloomy outlook. This resulted in several strikes but also the secession of the anti-war, farleft fringe (USPD) from the Socialist Party (SPD) and a new, informal coalition between the main leftwing and centrist parties to hold the Supreme Army Command (OHL) accountable (Mommsen Reference Mommsen1996).

By September 1918, the situation of the German Army had deteriorated to such an extent that the OHL admitted defeat to the Emperor. A new grand government was formed, and a few days later, Germany officially asked for an armistice. When the OHL rejected the conditions set by the Allied Forces in late October 1918, Chancellor von Baden sacked the military leadership and issued political reforms, which turned Germany into a parliamentary monarchy. The war, however, continued until the end of October, when a mutiny by the German Navy in the city of Kiel sparked a rebellion and the formation of workers’ and soldiers’ councils that took over civilian and military power.

This non-violent rebellion eventually led to the proclamation of the German Republic on the 9th of November (Büttner Reference Büttner2008). Two days later, WWI was officially ended by an armistice after four years of fighting and more than 10 m soldiers killed (Prost Reference Prost, Daniel, Gatrell, Janz, Jones, Keene, Kramer and Nasson2014).

A key reason for Weimar democracy’s failure 15 years later was that the German Army was still not technically defeated when the armistice was signed. This soon gave rise to the stab-in-the-back myth, a highly popular conspiracy theory according to which Germany had not lost WWI but was betrayed by an unreliable home front allegedly wound up by foreign Bolshevik activists and Jews with the support of the domestic political left and center. Organizations and parties on the right heavily used this myth as a propaganda tool to discredit the new democratic state and used it to connect Anti-Semitism with existing Red Menace fears of an imminent violent coup by the radical left (Barth Reference Barth2003).

Red Menace fears within the German population were fostered by the rebellions of November 1918 and the fact that the interim government was led by the two leftwing parties SPD and USPD. Especially problematic was that the USPD’s revolutionary part, which later became the Communist KPD, openly sought to create a Soviet Germany also by violent means (Brustein and Berntson Reference Brustein and Berntson1999). In light of this, the SPD started to collaborate with centrist parties but also increasingly relied on deeply reactionary paramilitary units, like the Freikorps, to maintain its power and territorial integrity.

Veterans during the Weimar Republic

Despite comprising at most 400,000 members, many of whom had never even served in WWI, the Freikorps significantly shaped the stereotypical image of Germany’s 11.2 m WWI veterans as brutalized and unable to fit into post-war society (Mosse Reference Mosse1990; Diehl 1993). Only recently has historical work begun to question this brutalization hypothesis (Schumann Reference Schumann2003; Ziemann Reference Ziemann2003). In fact, it has been noted that most veterans were presumably looking for stability after a period of war and revolution and returned to an unspectacular, civilian life. Also, the stylized image of the crippled, impoverished, and embittered former WWI soldier seems only true for a small fraction (Bessel Reference Bessel1993).

While most research has focused on significant groups or individual WWI participants, little is known about the political impact of the average veteran. This may be because it included almost all men born between 1869 and 1900 but a large part of those claiming to represent the so-called front generation was also not even part of it. Some scholars have noted that not all veterans supported the anti-democratic right, but that only the majority of those becoming politically active and claiming to represent the front generation did so (Diehl Reference Diehl and Stephen1975; Bessel Reference Bessel and Roseman1995). An actual investigation into veterans’ party orientation or electoral impact has, however, thus far not been conducted.

DATA

Panel Data of Reichstag Elections

To track changes in Germany’s voting behavior over time, I compiled a panel dataset covering all parliamentary elections held since the foundation of the German Empire until 1933. The panel is based on two existing datasets on elections in Imperial and Weimar Germany. Footnote 4 I complement this with election results for the National Assembly in January 1919 that took place only two months after WWI ended and thus provide an invaluable measure of post-war political preferences unaffected by other significant events like the Versailles Treaty. In my analysis, I focus on elections from 1893 to 1933, covering 20 years before and after the onset of WWI in 1914. Footnote 5 Comparing voting results over almost 40 years and different political regimes, however, raises several important questions.

One important issue is the comparability of parties across time. I tackle this by assigning each party to one of seven party groups based on classifications of Imperial and Weimar Germany’s party systems: Communist, Socialist, Left-Liberal, Catholic-Minority, Right-Liberal, Conservative, and Antisemite. Footnote 6 To capture significant changes in political orientation and reduce complexity, I collapse party groups further into three political camps for most of my analysis: Leftwing (Socialist, Communist), Center (Left-Liberal, Catholic-Minority, Right-Liberal), and Rightwing (Conservative, Antisemite). These camps also roughly correspond to supporters and enemies of democratization since the left was the main driving force against the monarchy before WWI while the right was the fiercest opponent of Weimar democracy. Footnote 7 Figure 1 shows aggregate vote shares in the area of post-war Germany for each camp in the sample period 1893 to 1933. One can see clearly that soon after WWI, the left’s rise and the right’s decline stopped and reverted while the downward trend of the center continued. The main boost in rightwing votes during the rise of the Nazi Party, however, did not happen until the 1930s.

FIGURE 1 NATIONAL ELECTION RESULTS IN THE GERMAN EMPIRE AND THE WEIMAR REPUBLIC

Notes: The dark grey-shaded area marks the WWI period. The vertical lines denote the last pre-WWI and the first post-WWI election. Data covers only the area contained in Weimar Germany’s borders and therefore may differ from official national aggregates for elections prior to 1922.

Source: Author’s calculations.

The second issue is the comparability of the electorate and the electoral system. The parliamentary elections held in the German Empire were relatively free and fair given the time period (Berman Reference Berman2001). Yet, suffrage was only granted to men aged 25 or older. The political reforms of 1918 introduced female suffrage and reduced the minimum voting age to 20, which effectively doubled the electorate. Since post-war data does not allow identifying these new voters, shifts in electoral behavior after WWI could also stem from simultaneous compositional changes in the electorate. Work on female voters in the Weimar Republic, however, has revealed that women voted along similar dimensions as men and predominantly stuck with their political camp (Sneeringer Reference Sneeringer2002). Crucially to this analysis, my empirical results also hold when controlling for the population share of women above 19 and men aged 20 to 25. Footnote 8

Finally, voting results during the German Empire were almost exclusively published for constituencies (Wahlkreise). Each single-member constituency typically consisted of 2–4 counties (Kreise) with occasional overlaps, and only followed political boundaries for small states and administrative districts. Footnote 9 Conveniently, the initial 397 constituencies were never adjusted in response to population growth for political reasons and thus remained stable until WWI (Jesse Reference Jesse and Niedermayer2013). My units of analysis are the 362 constituencies contained within Weimar Germany’s borders. After WWI, Germany was divided up into a few large constituencies, but results were now published at the county level. This allows re-constructing post-war vote counts as well as other variables for each pre-war constituency. Constituency-level summary statistics are provided in Online Appendix Table B.1. Footnote 10

A Disaggregated Estimate of Germany’s WWI Veterans

Germany’s war veterans were never explicitly counted for statistical purposes. However, since the Prussian Army Archive was destroyed in WWII, official statistical publications remain virtually the sole source of information on WWI participation across constituencies. Footnote 11 The key ingredient for estimating the number of surviving WWI soldiers is the wartime census of December 1917, which provides county-level figures of the female and civilian male population. Since the German army consisted exclusively of men, war participation led to a notable gender gap among the civilian population in the 1917 census. The male-female gap closed down again in the first post-war census conducted only 22 months later, in October 1919. Footnote 12 The abnormal difference in civilian male and female population change, $$\Delta Me{n_{17 - 19}} - \Delta Wome{n_{17 - 19,}}$$ during this short period thus provides a close proxy for the number of war participants in 1917 who survived the war.

Equation (1) shows how the exact number of all WWI veterans could be recovered if one actually knew the amount of surviving soldiers in 1917. This would essentially require also accounting for soldiers who had not yet joined the army as well as those who had left for non-fatal reasons such as disability or work-related exemptions.

(1) \begin{align}Veterans = (Soldier{s_{17}} &- SoldiersDea{d_{18}}) + SoldiersJoi{n_{18}}\\ &+ SoldiersQui{t_{14 - 17}}\end{align}

The veteran estimate used in this paper is stated in the top line of Equation (2). It approximates the ideal measure in Equation (1) by summing up the difference in male and female population growth from 1917–1919 mentioned previously and the number of men born in 1900, which were the only cohorts drafted after 1917 (Nash Reference Nash1977). While this estimate gets reasonably close to the actual amount of WWI veterans, it also introduces several sources of measurement error. In short, my veteran estimate assumes no gender-specific differences in births, civilian deaths and migration between 1917 and 1919 (ε = 0), the draft of the entire 1900 cohort (v = 0), and no man quitting the army up to 1917 for other reasons than death (ξ = 0): Footnote 13

(2) \begin{align}& Veterans \approx (\Delta Me{n_{17 - 19 }} - \Delta Wome{n_{17 - 19}}) + MenDraftabl{e_{18}}\\ &\quad = \underbrace {(\Delta Me{n_{17 - 19}} - \Delta Wome{n_{17 - 19}} - \varepsilon )}_{(Soldier{s_{17}} - SoldiersDea{d_{18}} )} + \underbrace {(MenDraftabl{e_{18}} - V)}_{SoldiersJoi{n_{18}}} + \underbrace \xi _{SQui{t_{14 - 17}}}\end{align}

The aggregate number of surviving German soldiers for the German Empire, according to my estimate is about 9 m, which is below the 11 m stated in official sources. This gap can be explained by soldiers called back to work in war-related industries during the 1917 census (64.7 percent), pre-census dropouts due to non-fatal reasons (21.8 percent), and those still held as prisoners of war during the 1919 census (13.3 percent). Footnote 14 This suggests that, at least in terms of size, ξ is by far the most important error term. The potentially significant mismeasurement due to gender-specific internal migration after WWI, however, cannot be assessed with countrylevel aggregates.

Bearing those caveats in mind, I calculate my main treatment variable, Veterans p.c., as a constituency-level version of the estimate noted previously divided by the last pre-war census population of 1910. This veteran share ranges from 0.06 to 0.20 and has a mean and median of roughly 0.14. Figure 2 shows the spatial distribution by deciles across the 362 constituencies discussed in the subsection on panel data of Reichstag elections. Footnote 15 While veterans as a share of the population are quite dispersed across Weimar Germany, they are also visibly underrepresented in highly industrialized West Germany and over-represented in the more rural North and East. This is consistent with the aforementioned undercount of soldiers on temporary leave from the army to work in war industries during the 1917 census.

FIGURE 2 VETERANS PER CAPITA ACROSS WEIMAR GERMANY BY CONSTITUENCIES

Source: Author’s calculations.

Control Variables

In my empirical analysis, I control for several potential confounders. Footnote 16 These include, for instance, the size of the draftable population (all men born between 1869 and 1900), pre-war military personnel, as well as male students, which were particularly likely to volunteer. I also add the differential growth between men and women in 1910–19 to approximate mismeasurement coming from internal gender-specific migration in 1917–19. A crucial driver of war participation were exemptions for employees in war-related industries. Lower draft rates in these occupations, however, were compensated by higher drafts in non-war industries. Due to the close alignment between blue-collar employment and support for leftwing parties, I control not only for men working in war-related industries but also blue-collar jobs in general. Lastly, I also adjust for the share of Catholics, which is negatively correlated with veterans and was a primary driver of political orientation at the time.

In Online Appendix Section A.1, I regress Veterans p.c. on several sets of variables. The controls mentioned earlier jointly explain almost half of the variation (R 2 ≍ 0.44). The other half comes from two sources: one of these is differences in exemption rates within war-related industries. Accounting additionally for the share of occupations where labor input by young adult men was particularly difficult to replace, increases the R 2 to about 0.49. In the instrumental variable estimates subsection, I use the prevalence of these low draft occupations as an instrument for war participation. The second source of variation is idiosyncrasies in recruitment and survival. I show this by adding fixed effects (FEs) for three tiers of prewar military territorial organization to the regressions. FEs for corps and brigade areas, which correspond to actual army units, increase the R 2 only moderately to 0.67. The addition of recruitment area FEs, on the other hand, raises it to about 0.93. This suggests that most of the variation unexplained by the baseline controls comes from idiosyncrasies in draft stringency rather than different levels of battle exposure and survival probability.

ESTIMATION STRATEGY

My first identification strategy uses a DiD framework to estimate the effect of veterans per capita on voting. The panel structure of the data allows using constituency and election FEs and thus identifying from within-constituency variation net off any election-specific trends. The baseline DiD specification reads as follows.

(3) $$Vot{e_{it}} = \alpha + {\gamma _i} + {\lambda _t} + {\beta _t}(Veterans \, p{c_i} \times Pos{t_t}) + \mu \, X_{it} + {\varepsilon _{it}}$$

This model regresses vote shares Vote it on constituency dummies γ i , election FEs λ t, and X it equal to interactions of election FEs and the set of time-invariant control variables. Standard errors are clustered at the constituency-level to account for the correlation of unobservable characteristics over time. My main variable of interest is the interaction of the time-invariant veteran share Veterans pc i with the dummy variable Post t taking value 1 for elections after WWI. The estimated effect thus captures the partial correlation between the veteran share and the average change in election results after the war.

A causal interpretation of this estimate requires the assignment of veteran shares across constituencies to be as good as random, conditional on covariates. In addition, quasi-random assignment should not only hold for aggregate-level but also individual-level unobservables to avoid concerns about ecological fallacy. As discussed in the subsection for control variables, the remaining variation after controlling for baseline covariates is driven by occupation-related exemptions and idiosyncrasies in recruitment and survival. Quasi-random assignment posits that these are uncorrelated with pre-existing political leanings. This is supported by a visual inspection of the distribution of veterans after accounting for observables and the absence of systematic correlations with pre-war party support and voting trends. Footnote 17 For a valid DiD, quasi-random assignment also requires the validity of the common trends assumption and the absence of correlated shocks, which require the identifying variation to be unrelated to pre-WWI vote trends and other crucial events between 1912 and 1919.

I conduct two checks for the validity of the parallel trend assumption: first, I add constituency-specific linear trends to my baseline results. Second, I run an event-study analysis in the subsection for timing and alternative channels, which dissects the impact of veterans for each election. Showing the absence of confounding events is more complex since WWI was followed by many highly polarizing events like the Versailles treaty, coup attempts, or hyperinflation, and each could have been a formative event for WWI participants. Similarly, Veterans pc i could pick up political radicalization among the dependents of killed soldiers, whose population share is mechanically related to that of surviving soldiers via overall draft rates.

I meet those concerns in several ways. Through the event-study analysis mentioned earlier, one can inspect whether the treatment effect coincides with any other significant post-war developments. The influence of events prior to January 1919, like WWI deaths, is assessed in horserace regressions. Regarding the influence of remaining unobservables, I exploit the prevalence of low-draft occupations within war-related industries and their strong negative effect on war participation. Conditional on the occupational composition of war-related employment being exogenous to underlying political preferences, this variation can be used as an instrument for the share of veterans. Footnote 18

THE POLITICAL IMPACT OF GERMAN WWI VETERANS

DiD Estimates

The baseline DiD results for the three-party camps are reported in Table 1. The first specification in each column triplet includes only the interaction term Veterans pc i × Post t and FEs for constituencies and elections, and yields highly significant coefficients on all three outcomes. A 1 pp higher veteran share is thus associated with a 1.61 pp decrease in leftwing votes after WWI and a 0.68 and 0.93 pp increase in center

TABLE 1 DID ESTIMATES (BASELINE RESULTS)

Notes: Observations are at the constituency-level. The sample period is 1893 up to 1933 and includes 14 Reichstag elections. Standard errors clustered at the constituency-level in parentheses: *p < 0.1; **p < 0.05; ***p < 0.01. Included control variables are % Male WWI-eligible, % ΔGrowth M-F 1910–19, % Male blue-collar (all), % Male blue-collar (war), % Military, % Male students, % Catholics. All controls are interacted with Election FE.

Source: Author’s calculations.

and rightwing votes, respectively. The second column for each party camp is the preferred baseline specification stated in Equation (3), which also adjusts for covariates. This diminishes the effect on leftwing votes to –1.31 but does not affect significance. The effect on centrist votes, however, almost falls to zero and is no longer significant, while the one on rightwing votes climbs to 1.23. Adding constituency-specific linear trends in the third column of each triplet, on the other hand, only slightly changes the estimates and does not suggest that these are driven by linear pre-trends.

In terms of magnitude, these are large effects. Raising the veteran share by 0.021, the equivalent of one SD, implies an increase in the rightwing vote share by 0.025 or 12.8 percent of an SD, in the post-war period. The impact of WWI participants on rightwing votes is thus not far from that of other structural factors like medieval pogroms and association density on Nazi votes found in earlier research. Footnote 19 Assuming the entire absence or no political effect of WWI veterans would have resulted in an average reduction of the rightwing share by 0.17 and a simultaneous increase in leftwing votes of 0.18. This hypothetical change in the parliamentary power balance would have prevented a rightwing majority at the end of the Weimar Republic and may have avoided the breakdown of democracy. In light of these implications as well as the potential threats to identification outlined previously, these results should be treated with caution at this stage and will be revisited later in the subsection on counterfactual.

Timing and Alternative Channels

Figure 3 uses an event study that disentangles the veteran effect for every election with respect to 1912. This allows for the inspection of non-linear pre-trends but also offers a perspective on the baseline results’ timing. Overall, the event study supports the assumption of no pre-trends. None of the pre-war coefficients for the right and center are significant, and the correlation with the veteran share in 1912 is very close to that in 1893, almost 20 years earlier. The left sees a significant small drop in 1903, which, however, quickly reverts and is mirrored by small gains for both the right and the center. No party camp exhibits clear anticipatory patterns. The post-war coefficients also suggest again that veterans predominantly affected left- and rightwing parties, whereas the center’s gains are tiny and never significant at conventional levels. Footnote 20

FIGURE 3 EVENT STUDY GRAPH FOR THE THREE PARTY CAMPS

Notes: Coefficients and 95 percent confidence intervals for the effect of veterans per capita on election results for each election between 1893 and 1933, normalized to the effect in 1912. The right-hand side of the regression specification is equivalent to the preferred baseline: Column (2) of Table 1. The light grey-shaded area marks the WWI period.

Source: Author’s calculations.

There are several additional important aspects to these results: firstly, the electoral shift from left to right already materialized in the January 1919 election, only two months after WWI officially ended. The Paris Peace Conference that would draft the Versailles Treaty had just started by then, and other polarizing events potentially related to the presence of veterans, such as the Kapp coup (1920), the Ruhr Uprising (1920), or the French Ruhr Occupation (1923), were still in the future. The Stahlhelm, which became the most active rightwing ex-servicemen club in the 1930s, had just been founded a month earlier (Berghahn Reference Berghahn1966). All in all, this leaves only a rather small time window of other post-war events, most notably the Spartacist uprising by the radical left, to confound the DiD results. Secondly, the veteran effect pre-dates the left-right swing in aggregate voting patterns after 1920 (see Figure 1). This implies that without veterans’ impact, pre-war electoral trends would have seen a sharp break in 1919, benefiting the left at the expense of the political right. Thirdly, the post-war coefficients for all camps are very stable over time, especially for the left, which hints at a genuine change in political preferences related to veterans rather than an issue-related short-term vote swing. The early and persistent anti-left effect also speaks against the widespread assumption that rightwing parties’ success among the German working class started only after the Great Depression in the 1930s (Brustein Reference Brustein1996). Finally, since the veteran measure was calculated based on the October 1919 census, the treatment onset in January 1919 provides evidence against politically selective migration in the following years.

The timing of the effect rules out several competing explanations but leaves a few alternatives open: some of these arise from the strong relationship between veterans per capita and the share of deceased WWI soldiers. For instance, casualties may have led to political radicalization among those bereaved by the war or reflected different levels of social cohesion in units’ main recruitment areas. Another possibility is that veterans could be linked to the strength of far-left groups. This seems plausible since the German revolution was sparked by a mutiny in the German Navy, and soldiers formed many of the revolutionary councils that replaced the pre-war administration during the interim period. If there was a correlation between veterans and the far-left, the baseline results could mask a simple political backlash after the Spartacist Uprising in Berlin only a few days before the 1919 election (Mommsen Reference Mommsen1996). Anti-Communism would thus constitute a confounder to the veteran effect rather than a mechanism through which it operated.

Table 2 provides evidence against both competing explanations. The first column for each party camp adds an interaction between WWI casualties per capita and Post . Footnote 21 Doing so has virtually no effect on the veteran coefficient for any party camp. In the second column of each camp, I restrict the sample to Bavaria and a few other constituencies for which I can include an interaction with officially deceased WWI soldiers per capita. The left-right shift is more pronounced in this subset and shows an insignificant reduction in centrist votes, but does not qualitatively change my findings. In the third specification of each party group, I add an interaction based on the vote share of the far-left USPD in 1919 as an indicator of the far-left’s strength. The estimates show that Red Menace fears led to a marginally significant shift in votes from left to center but do not invalidate the veteran coefficients that provide evidence against this alternative explanation. Footnote 22

TABLE 2 ALTERNATIVE CHANNELS

Notes: Observations are at the constituency-level. The sample period is 1893 up to 1933 and includes 14 Reichstag elections. Standard errors clustered at the constituency-level in parentheses: *p < 0.1; **p < 0.05; ***p < 0.01. Included control variables are % Male WWI-eligible, % ΔGrowth M-F 1910–19, % Male blue-collar (all), % Male blue-collar (war), % Military, % Male students, % Catholics. All controls are interacted with Election FE.

Source: Author’s calculations.

Instrumental Variable Estimates

I tackle remaining endogeneity concerns by using war-related exemptions as an alternative source of variation. More precisely, I instrument veterans per capita with the share of male workers in low-draft occupations using a high share of draftable men (>45 percent) among their employees during wartime: iron and coal mining, extraction of graphite, asphalt, oil and amber, quarrymen, shipbuilding, manufacturing of non-rifle firearms, and pharmacists.

Instrument validity requires the following exclusion restriction to be satisfied: conditional on covariates, the share of low-draft occupations affects voting only through its negative effect on war participation. Several factors support this assumption: firstly, about half the low-draft employment is typically in mining or shipbuilding, where location is pre-determined by geography and thus less prone to endogeneity concerns. Footnote 23 This is also shown in Figure 4, which depicts the spatial distribution of the instrument’s identifying variation after conditioning on baseline controls. Secondly, as the map shows, low-draft occupations are displaying considerable geographic dispersion and, crucially, do not coincide with the industrial heartlands and leftwing strongholds of West and Central Germany. Finally, the conditional correlations between low-draft occupations and pre-war vote shares are small and never go in the direction predicted by the IV. Footnote 24

FIGURE 4 MEN IN WAR-RELATED LOW-DRAFT OCCUPATIONS ACROSS WEIMAR GERMANY BY CONSTITUENCIES (RESIDUAL AFTER BASELINE CONTROLS)

Source: Author’s calculations.

Column (1) in Table 3 shows a strong, highly significant first-stage coefficient indicating that a lpp increase in low-draft male employment translated into a 0.72 pp decrease in the population share of veterans. The F-statistic on the excluded instrument of 34.0 renders a bias due to weak instruments unlikely. The first specification for each party camp repeats the baseline DiD results, while the second and third columns show the raw reduced-form effect of the instrument and the 2SLS estimates.

TABLE 3 INSTRUMENTAL VARIABLE ESTIMATES

Notes: Observations are at the constituency-level. The sample period is 1893 up to 1933 and includes 14 Reichstag elections. Standard errors clustered at the constituency-level in parentheses: *p < 0.1; **p < 0.05; ***p < 0.01. Included control variables are % Male WWI-eligible, % ∆Growth M-F 1910–19, % Male blue-collar (all), % Male blue-collar (war), % Military, % Male students, % Catholics. All controls are interacted with Election FE.

Source: Author’s calculations.

Qualitatively, the IV estimates confirm the OLS results, but in terms of magnitude, they are about twice as high for both left- and rightwing. Yet, one has to remember that the instrument only estimates a local average treatment effect on the compilers, which are workers who do not become veterans because they work in low-draft occupations or participate in WWI because they do not hold such a job. Since I control for the overall prevalence of all war-related occupations, the effect is identified in highly industrialized areas that may yield notably higher effects for several reasons: one is that the target population to persuade into voting rightwing was particularly high in those areas since they were the political heart-land of the Socialist party. In addition, research has pointed out that the tight social fabric of Germany’s working-class milieu may have provided a particularly fertile ground for the spread of rightwing extremist views after WWI (Szejnmann Reference Szejnmann and Fischer1996). While this does not invalidate the IV findings, it renders them less suitable for making general inferences, and they should thus be mainly regarded as additional evidence in support of my main results. The remainder of this paper will therefore continue to refer to the more conservative DiD baseline estimates.

MECHANISMS

The Role of Anti-Communism

As a first step to uncover the mechanisms behind my findings, I zoom into the party camps in Table 4 and estimate the baseline specification using individual party groups and turnout as outcomes. The first column

TABLE 4 DID ESTIMATES FOR TURNOUT AND PARTY GROUPS

Notes: Observations are at the constituency-level. The sample period is 1893 up to 1933 and includes 14 Reichstag elections. Standard errors clustered at the constituency-level in parentheses: *p < 0.1; **p < 0.05; ***p < 0.01. Included control variables are % Male WWI-eligible, % ∆Growth M-F 1910–19, % Male blue-collar (all), % Male blue-collar (war), % Military, % Male students, % Catholics. All controls are interacted with Election FE. Turnout and Antisemite votes are not available for 1919.

Source: Author’s calculations.

shows no impact on turnout. For the leftwing, we see that using only support for the Socialist SPD after WWI without Communist votes yields similar results as Table 1. Footnote 25 This suggests that veterans mainly affected the left’s moderate and clearly pro-democratic parts rather than its radical fringes. Within the center, veterans had almost no effect on left-liberals, while yielding insignificant increases and reductions in Catholic-minority and right-liberal votes, respectively. Looking at the rightwing in Columns

(5) and (6) shows the conservatives as the clear winner and no significant impact on the Antisemite vote share. This contrasts with the widespread perception that veterans as a social group were predominantly supporting the Nazi Party. Footnote 26

Table 4 provides some first insights about the potential mechanisms behind my findings: the absence of a clear impact on centrist parties and the far-left favor a direct voter transition from moderate left to rightwing rather than a gradual shift across the entire political spectrum. This is already surprising from a rational viewpoint since soldiers’ support for the left, if anything, should have increased as WWI created more need for redistribution to make up for war-induced disabilities. Crucially, parties’ politico-economic orientations did not significantly change after WWI. A persistent voter transition without major changes in party platforms strongly hints at a shift in individual political preferences and suggests that moderate left veterans turned toward nationalism—the main selling point of rightwing parties. A general reorientation away from redistribution, on the other hand, seems unlikely since Communist votes were not affected by this shift.

Why would moderate left soldiers turn toward nationalism and rightwing parties after WWI? A plausible explanation for this could be anti-communist sentiments spread via the stab-in-the-back myth. While this would be broadly in line with the Red Menace theory in the sense that rightwing parties gained from Anti-Communism after WWI, it raises the question why such sentiments would also affect moderate left veterans as opposed to the more rational fears of the propertied middle class. A straightforward explanation for this could be that soldiers particularly longed for an easy and seemingly coherent rationalization of the traumatic defeat in 1918. Such demand for reason bears a strong resemblance to religious coping after natural disasters, whose historical relevance has also recently been discussed by economists (Belloc, Drago, and Galbiati Reference Belloc, Drago and Galbiati2016; Bentzen Reference Bentzen2019).

If veterans were indeed susceptible to the stab-in-the-back myth and Anti-Communism, neither the losses of the moderate left SPD nor the gains of the conservatives are surprising. Footnote 27 While the far-left actually favored a Soviet Germany and the Catholic-bourgeois parties of the center could hardly be associated with Communism, the allegation of secretly collaborating with foreign Bolsheviks was mainly problematic for the moderate left. The conservative DNVP, on the other hand, had started to spread fears of a leftwing revolution and the stab-in-the-back myth since its creation in late 1918 (Thimme Reference Thimme1969). In spite of being founded by key figures of Imperial Germany’s nationalist and monarchic elites, the DNVP re-branded itself as an inclusive, classless people’s party under the unifying theme of nationalism and successfully wooed blue-collar workers. Footnote 28 This appears to have been a key factor in attracting veterans disenchanted with the SPD since the right-liberal DVP, which used very similar anti-communist propaganda but remained skeptical of the working class, did not benefit at all (Liebe Reference Liebe1956; Frye Reference Frye1963). Footnote 29

The final three columns in Table 4 provide further support for the Anti-Communism channel. More precisely, they show a notable shift in veterans’ party preference during the last three elections in 1932 and 1933 that moved the effect on the Nazi Party entirely toward the DNVP. Footnote 30 This seems puzzling at first since the Nazi vote share increased from 18 to 37 percent between 1930 and 1932, and voting for the far less successful DNVP was likely counterproductive in aiding a rightwing takeover of power. If veterans were susceptible to Anti-Communism, however, this shift is not overly surprising. Since 1930, the Nazis have upped their anti-capitalist rhetoric, fiercely attacked the DNVP for its middle-class links, and even founded their own trade union, which became involved in several strikes (Beck Reference Beck2016). This new leftwing-nationalist course was also actively denounced in the conservatives’ campaigns (Jones 2015). Hence, if veterans’ support for nationalist parties was driven by Anti-Communism, the change in the Nazi Party’s tactics should have precisely created the patterns observed in the data.

Alternative Mechanisms

There are two other potential explanations: first, veterans’ attitudes could have been altered by any other effect of war beyond the feeling of defeat. Second, rather than a change in veterans’ political preferences and political demand, my findings could be driven by a shift in political supply. Table 5 assesses the plausibility of these channels using a triple-diff design, which allows the baseline OLS results for left- and rightwing parties to vary with an additional factor. More precisely, I include interactions between Veterans i × Post t and a dummy to determine whether a variable linked to a particular mechanism is above the sample median. This new interaction term quantifies how the veteran effect in the half of the sample above the median differs from the one below. An interaction between the respective median dummy and Post t is also included in each regression but not reported.

TABLE 5 ROLE OF DIRECT WAR EFFECTS AND POLITICAL SUPPLY

Notes: Observations are at the constituency-level. The sample period is 1893 up to 1933 and includes 14 Reichstag elections. Standard errors clustered at the constituency-level in parentheses: *p < 0.1; **p < 0.05; ***p < 0.01. Included control variables are % Male WWI-eligible, % ∆Growth M-F 1910–19, % Male blue-collar (all), % Male blue-collar (war), % Military, % Male students, % Catholics. All controls are interacted with Election FE. All constituent terms of interaction effects are included in the estimation but only relevant ones are reported in the table. Source: Author’s calculations.

I start by exploring the impact of direct economic and psychological effects of war: exposure to violence, disability, and political socialization. As discussed earlier in the subsection on veterans during the Weimar Republic, the historical literature on Weimar Germany has extensively debated whether the traumatic experiences of WWI soldiers paved the way for a violent post-war society and the rise of the Nazi Party. Columns (1) and (2) in Table 5 indicate a significantly different effect in the high-casualty part of the sample for the leftwing, which, however, goes in the opposite of the expected direction. Veterans’ effects on the rightwing, in turn, do not seem to depend on WWI casualties and thus speak against the brutalization hypothesis.

Closely related to this are the economic effects of war-induced disability. While the new government did its best to reintegrate the 2.7 m war-disabled veterans, their preferential treatment through protected job types, for example, also alienated them from the rest of the population (Bessel Reference Bessel1993; Cohen Reference Cohen and David2012). This alienation or general dissatisfaction with the benefit system could have led those disabled by the war into political extremism. In specifications 3 and 4, I allow the baseline effect to differ depending on the population share of male individuals eligible for WWI-related benefits from the 1924 census of the war-disabled. These new interactions are small

and insignificant at conventional levels, which rules against the important role of WWI-induced economic shocks and disability.

The last war-related mechanism concerns the importance of experiences from ages 18 to 25 for the development of political attitudes (Krosnick and Alwin Reference Krosnick and Alwin1989; Giuliano and Spilimbergo Reference Giuliano and Spilimbergo2014). Since many WWI draftees were in this age group, the war may have influenced elections through identity formation among its youngest participants. The literature has noted that the so-called front generation was still accustomed to the stability and predictability of the pre-war period but saw this world turned upside down through military defeat and the leftwing-led revolution in 1918 (Bessel Reference Bessel and Roseman1995; Verhey Reference Verhey2000). I test this possible explanation in Columns (5) and (6) by using the share of men aged at most 25 during wartime among the draftable population. For the leftwing, the interaction estimate goes against the expected direction. The effect on the right is statistically indistinguishable from zero. Footnote 31

Another competing explanation could be that veterans’ change in voting was triggered by a shift in political supply after WWI. For instance, veterans may have become rationally anti-communist through actual exposure to far-left activity, which was likely higher in leftwing strongholds. Alternatively, moderately left veterans could have been actively targeted by rightwing parties or groups after 1919. The remaining specifications in Table 5 test the plausibility of these mechanisms. Interactions with the 1919 USPD vote share in Columns (7) and (8) indicate that veterans benefited the right less in far-left strongholds. This suggests that Communist activists may have successfully obstructed the DNVP’s 1919 campaign rather than driving voters into the arms of the right. In specifications 9 and 10, I look at the impact of DNVP propaganda capacity in 1919. This is approximated by the 1914 chapter intensity of the German National Association of Commercial Employees (DHV), which, according to historians, was a crucial vehicle for the DNVP’s initial efforts in attracting blue-collar workers (Liebe Reference Liebe1956; Ohnezeit Reference Ohnezeit2011). The coefficients suggest that this mechanism also cannot explain the veteran effect. Online Appendix Table B.7 provides further evidence against a shift in political supply. Footnote 32

Insights from Referenda and Presidential Elections

So far, the analysis has two important drawbacks: first, one cannot distinguish political preferences from party loyalty and rule out the possibility that veterans supported the DNVP for other reasons than nationalism and Anti-Communism. Second, parliamentary votes do not allow inferring an order of preference over parties and policies. This forbids answering the historically relevant question of whether veterans’ strong support for the DNVP should be interpreted as a closer alignment of preferences or as a rejection of the Nazi Party and Hitler’s seizure of power. I tackle both issues by exploring veterans’ effects on two referenda and two presidential elections. To account for constant, yet unobserved, preferences for particular parties and policies, I add the (non-interacted) baseline controls and seven party strength variables. These are identical to the seven sets of estimated constituency fixed effects for each party group in Column (2) of Table 1 and Columns (2) to (7) in Table 4. Footnote 33

The first two columns in Table 6 present veterans’ impact on referenda turnout. Footnote 34 The 1926 referendum was on expropriating Germany’s former aristocracy. This was a classic leftwing, redistributional topic, and the right made heavy use of anti-communist propaganda to discourage voters from supporting it (Ohnezeit Reference Ohnezeit2011). Column (1) shows that veterans reduced turnout in this ballot. The 1929 ballot was about rejecting the so-called Young plan, which finalized Germany’s WWI reparations. This was a classic rightwing issue and framed as a ballot on Germany’s national sovereignty and supposed “enslavement.” As Column (2) shows, former soldiers increased turnout in this referendum. Taken together, both results suggest that it was indeed the DNVP’s stance on nationalism and Anti-Communism that won them veterans’ political support.

TABLE 6 VETERAN EFFECT ON REFERENDA AND PRESIDENTIAL ELECTION RESULTS

Notes: Observations are at the constituency-level. Robust standard errors in parentheses: *p < 0.1; **p < 0.05; ***p < 0.01. Included control variables are % Male WWI-eligible, % ∆Growth M-F 1910–19, % Male blue-collar (all), % Male blue-collar (war), % Military, % Male students, % Catholics.

Source: Author’s calculations.

Specifications 3 to 6 look at the presidential election of 1925, where candidates are roughly classified by their endorsing party camps. The effects on the first round show a strong shift from left to right arising from war participation and thus strongly resemble the baseline party results. Importantly, the vast majority of former soldiers’ votes went to Karl Jarres who was a right-liberal endorsed by the DNVP. The Nazi Party candidate Ludendorff gained to a much lower degree. In the second round, rightwing parties agreed to nominate the independent former WWI General Paul Hindenburg, and, as shown in Column (6), the veteran effect moved almost entirely to this new rightwing candidate. As shown in Online Appendix Table B.8, this came at the expense of Wilhelm Marx of the Centre Party, who was endorsed by the Socialist SPD rather than the far-left Thälmann, and thus reaffirms that war participants only hurt the moderate part of the leftwing. Footnote 35

In 1932, Hindenburg became the candidate of the center and moderate left to prevent Adolf Hitler from becoming president (Mommsen Reference Mommsen1996). In this election, war participants completely withdrew their support for Hindenburg and voted for the even more rightwing candidates Hitler and Duesterberg, who was endorsed by the DNVP and leader of the paramilitary Stahlhelm group. According to Columns (8) and (9), the majority of veterans opted for Duesterberg. The effect on Hitler’s votes is smaller and less precisely estimated, with a p-value of about 0.18. After Duesterberg dropped out, the DNVP leadership advised its voters to abstain and endorsed neither of the remaining candidates (Jones 2015). In spite of this recommendation and the availability of another nationalist option in the form of Hindenburg, Column (10) shows that the majority of former soldiers apparently supported Hitler in the second round. These results indicate that, even though veterans on most occasions went with the DNVP and its candidates, they were not opposed to the Nazi Party and in 1932 supported Hitler’s (unsuccessful) bid for becoming president.

Counterfactual

My analysis finishes by revisiting the thought experiment in the DiD estimates subsection and, having established the baseline estimates’ robustness, providing a more accurate counterfactual of Weimar Germany’s political landscape without the political influence of WWI veterans. In order to do this, I take the event-study estimates from Figure 3 at face value and calculate counter-factual vote shares for the leftwing and rightwing in all parliamentary elections after WWI under the assumption of no veteran effect. Footnote 36 This does not consider the actual seat allocation in parliament, but, given that the Weimar Republic used proportional representation, seat shares should be closely linked to popular support. Figure 5 shows the results from my calculations. Footnote 37

FIGURE 5 COUNTERFACTUAL EVOLUTION OF PARLIAMENTARY ELECTION RESULTS IN THE GERMAN EMPIRE AND THE WEIMAR REPUBLIC ASSUMING NO VETERAN EFFECT AFTER WWI

Notes: The dark grey-shaded area marks the WWI period. The vertical lines denote the last pre-WWI and the first post-WWI election. Data covers only the area contained in Weimar Germany’s borders and therefore may differ from official national aggregates for elections prior to 1922. For better visibility, the distance between elections in 1932 and 1933 has been artificially stretched.

Source: Author’s calculations.

The first thing to note is that the broad electoral trends between 1912 and 1920 would have been very different had it not been for WWI veterans. The rightwing would have suffered heavy electoral losses. Veterans’ shift in political preferences seems to have prevented this scenario as well as a much clearer victory for the left. According to my calculations, leftwing parties would have seen considerably higher vote shares throughout the Weimar period. Even during the last Weimar election in 1933, they would have received about 48 percent of the vote, compared to only 37 percent for all rightwing parties combined. While one can naturally only speculate what would have happened under such a scenario, it is certain that non-Nazi coalitions would have been much easier to achieve throughout the 1930s. As the graph clearly shows, the revival of the right in the wake of the Great Depression would have happened also without veterans’ influence. Footnote 38

CONCLUSION

This paper provides empirical evidence of the effect of WWI veterans on election outcomes during the Weimar Republic. Using a new election panel from 1893 to 1933 as well as novel disaggregated estimates of WWI veterans, I show that areas with a higher population share of former soldiers significantly shifted electoral support from leftwing to rightwing parties after WWI. The effects are sizeable and imply that, on average, former soldiers increased support for rightwing parties by 14 pp and reduced it for the left by 15 pp. I show that this effect already hits two months after the end of WWI and persists until the last democratic elections in 1933.

I present several results supporting the idea that veterans’ political preferences shifted toward Anti-Communism and nationalism due to war participation. While Anti-Communism drove war participants away from leftwing parties, the classless nationalism offered by rightwing parties provided a natural new ideological home for former working-class voters. Importantly, this finding cannot be explained by the direct effects of war participation or changes in political supply. A highly likely explanation is that veterans’ search for a reason after the traumatic defeat in WWI was met by the stab-in-the-back myth conspiracy theory that blamed the defeat on an alleged betrayal by leftwing parties.

Footnotes

I would like to thank Ran Abramitzky, Toman Barsbai, Sascha O. Becker, Dan Bernhardt, Letizia Borgomeo, Maristella Botticini, Peter Buisseret, Allan Drazen, Christian Dustmann, Jon Eguia, Josip Glaurdić, Mark Harrison, Stephan Heblich, Saumitra Jha, Ethan Kaplan, Sharun Mukand, Luigi Pascali, Nico Voigtländer, Hans-Joachim Voth, Fabian Waldinger, Ekaterina Zhuravskaya, and Yanos Zylberberg for important discussions and useful insights and Kalle Kappner and Felix Kersting for sharing their data. The paper also benefited from feedback of participants at numerous seminars and conferences and comments by Dan Bogart and three referees. Santiago Bello, Isabel Lauterjung, Man Li, and Xiaoran Liang provided excellent research assistance. Financial support by the ESRC DTC Warwick is gratefully acknowledged.

1 This division of the literature exists also in other European countries (Alcalde Reference Alcalde2017). Accounts linking German WWI veterans to the political right can be found in Mosse (Reference Mosse1990) and Diehl (1993). Schumann (Reference Schumann2003) and Ziemann (Reference Ziemann2003), for instance, have argued against this association.

3 Closely related work include Grossman, Manekin, and Miodownik (Reference Grossman, Manekin and Miodownik2015), Cagé et al. (Reference Cagé, Dagorret, Grosjean and Jha2020), Weaver (Reference Weaver2020), Cáceres-Delpiano et al. (Reference Cáceres-Delpiano, de Moragas, Facchini and González2021), and Navajas et al. (2022).

4 See Online Appendix Section D.1 for details.

5 While 1919 was not an actual parliamentary election, virtually the same parties were competing as in 1920. Figure 1 shows that 1919 was not an outlier, and aggregate voting patterns changed only in subsequent ballots. My sample period starts in 1893 to focus on the post-Bismarck period and exclude the peak time of election agreements between the conservative and right-liberal cartel parties. Also, Antisemite parties were not explicitly recorded in the data before the 1890s. In Online Appendix Table B.3, I show that an extended sample starting in 1871 produces qualitatively similar results.

6 See Sperber (Reference Sperber1997) and Jesse (Reference Jesse and Niedermayer2013). A complete list of all individual parties in each group can be found in Online Appendix Section D.2. Antisemite is a separate category since the Nazi Party NSDAP was one of the major parties in the Weimar Republic. The Communist parties USPD and KPD split off from the Socialist SPD only after WWI and can thus not be credibly analyzed separately from the SPD. The Centre Party (Zentrumspartei) is called Catholic to avoid confusion with the Centre Party camp encompassing Catholic-Minority as well as Liberal parties.

7 One may argue that the Communist KPD is widely considered an enemy of Weimar democracy. The subsection on the role of Anti-Communism, however, shows that the extreme left is not vital for the effects on leftwing votes.

8 See Online Appendix Table B.5 for details.

9 These constituencies differ from those for electing the Prussian House of Representatives. Unlike those during the Weimar Republic, they were also all single-member constituencies. To mitigate the impact of strategic voting, I use only first-round results throughout.

10 All variables and their sources are described in Online Appendix Section D.1. Overlaps and county border changes are accounted for using a combination of area- and population-weights and explained in greater detail in Online Appendix Section D.3. For further details, see also Koenig (2022).

11 Data exists for WWI-injured pension recipients, which amounted to only 660,000 in 1924 compared to the estimated 11 million German WWI veterans. Surviving primary material for the Kingdoms of Bavaria, Saxony, and Württemberg accounts for only 22 percent of all war participants.

12 Soldiers at the front were not counted in 1917 since its main purpose was estimating local food requirements. The two wartime censuses of 1916 and 1917 were in fact carried out by the Office of War Nourishment’s Economic Department (Volkswirtschaftliche Abteilung des Kriegsernährungsamtes) instead of the Imperial Statistical Office. Soldiers at the front were counted only in 1916, but no information on their original residence was collected, which is only one of several inaccuracies in this census (Bayerisches Statistisches Landesamt 1919).

13 Formally, ε = ( MenBorn WomenBorn ) – (MenCivilDead WomenDead) + (MenNetMigr 18-19WomenNetMigr 18-19). ΔMen 17-19 already deducts soldiers inside German Empire and foreign prisoners of war in 1917 and accounts for temporal absences and presences.

14 The number of 9 m veterans accounts for the population living in areas lost after WWI and ceded before the 1919 census. See Online Appendix Section D.4 for further details on the calculations.

15 Areas are grouped into deciles to visually accentuate the variation. A density plot and map of the actual, continuous variable Veterans p.c. are shown in Online Appendix Figures C.1 and C.2.

16 See Online Appendix Section A.1 for a detailed motivation and discussion.

17 Online Appendix Figure C.3 shows the distribution of veterans after accounting for observables. Online Appendix Figure C.11 shows that this variable also does not correlate with 1907 and 1912 vote shares. Online Appendix Figure C.12 provides graphical evidence against a violation of the common trend assumption in the raw data.

18 As shown by Spenkuch (Reference Spenkuch2018), a valid and micro-founded IV strategy can resolve concerns about ecological fallacy when using aggregate data to infer individual behavior.

19 The impact of a one SD increase in medieval pogroms (a dummy variable) on Antisemites/ Nazi votes in 1924 and 1928 in Voigtländer and Voth (Reference Voigtländer and Voth2012) is 6.7 and 13 percent of an SD, respectively. For association density and the Nazi vote share of 1928, 1930, and 1933 studied by Satyanath, Voigtländer, and Voth (Reference Satyanath, Voigtländer and Voth2017), the effect ranges between 15 and 19 percent of an SD.

20 Online Appendix Figure C.13 shows that these patterns are qualitatively similar without adding any controls. In Online Appendix Table B.4, I add election-specific FEs for six tiers of military and civilian administration. This leaves leftwing losses largely unaffected but attenuates the results for the right and shifts electoral gains more toward the center. The most likely explanation is a geographic component in voting, especially for the right, which is entirely absorbed by these specifications. In Online Appendix Figures C.14, C.15, and C.16, I plot the baseline coefficients for each party camp after leaving out single states or Prussian provinces one at a time. Reassuringly, these results indicate that the effects are not driven by a particular region.

21 This source covers 90 percent of all reportedly injured German WWI soldiers but only lists the soldiers’ (imperfectly) geo-coded place of birth and can only discern fatal from non-fatal injuries for about 3 percent of all casualties. See Section D.1 of the Online Appendix for further details.

22 Online Appendix Section A.2 shows that results are also robust when including measures of social capital and alternative indicators of far-left strength.

23 In Online Appendix Table B.6, I modify the instrument to include only geographically pre-determined low-draft occupations: iron and coal mining, extraction of graphite, asphalt, oil and amber, and shipbuilding. The corresponding estimates are very similar to using all low-draft occupations.

24 The raw geographic distribution of blue-collar employment is shown in Online Appendix Figures C.17 (all), C.18 (war), and C.19 (low-draft). The correlations with pre-war votes are shown in Online Appendix Figure C.20.

25 Communist votes are unavailable for the full sample period as they split from the SPD after WWI.

26 The corresponding event-study graphs in Online Appendix Figure C.21 indicate that the split may have been more even, but the effect on the conservatives was higher in almost all post-war elections. One exception was May 1924, when Antisemites were represented by an electoral alliance of conservative secessionists and the Nazi Party. During the elections of 1932 and 1933, the veteran effect on Antisemites entirely drops to zero, which is discussed later.

27 The stab-in-the-back myth also explicitly blamed Jews for Germany’s defeat. Yet, several points rule against a prominent role for Anti-Semitism in my findings: first, the effect on the DNVP peaked in 1932 and 1933 under Alfred Hugenberg, who was not strongly promoting Anti-Semitism (Jones Reference Jones2014). Secondly, the results in Online Appendix Table B.8 reveal that veterans benefited from Theodor Duesterberg in 1932, who had Jewish ancestry. Finally, they did not harm the left-liberal DDP, which the right often denounced as the party of the Jews.

28 The DNVP’s re-branding was mainly in words. Its policies were still dominated by the interests of big industry and large landowners, like their predecessor parties (Ohnezeit Reference Ohnezeit2011).

29 Visual evidence of Anti-Communism and Red Menace fears in DNVP and DVP propaganda is provided in Online Appendix Figures C.24, C.25, and C.26. Another reason for the DVP’s inefficient anti-communist propaganda could have been its low credibility given its participation in government. Yet, this only started in 1920 and did not coincide with changes in the veteran effect on right-liberal votes shown in Online Appendix Figure C.21e.

30 A visualization of these effects is shown in the event-study graphs in Online Appendix Figure C.21.

31 For the left, this implies that the baseline results were driven by constituencies with comparatively older draftees. Yet, the similarity with the interactions for casualties p.c. cautions that this may also be driven by the negative correlation between combat exposure and age.

32 Online Appendix Sections A.3 and A.4 also rule out middle-class fears and misogyny among veterans as alternative mechanisms. Further alternatives could be experiences that the available data cannot measure, such as deployment against Communist insurgents in the Baltic states, fighting under the command of influential individuals as in Cagé et al. (Reference Cagé, Dagorret, Grosjean and Jha2020), or exposure to army propaganda. Experiences common to larger army units, however, are also unlikely since including election-specific corps and brigade FEs in Online Appendix Table B.4 have little impact on the leftwing and only shift the rightwing gains more toward the center.

33 I use party strength variables for both leftwing and Socialist vote shares in order to separate unobserved preference for the moderate Socialist party from that for the far-left.

34 Due to the high approval rates (94 percent in 1926 and 96 percent in 1929), turnout is a more reliable measure of support. The effect on all outcomes from these elections is shown in Online Appendix Table B.8. Including FEs based on turnout would not meaningfully change these estimates (results available on request).

35 According to my estimates, veterans increased Hindenburg’s vote share on average by 13.4 pp. Since Hindenburg won the second round by a margin of only 3 percent, he would have lost this election if, on average, less than a quarter of war participants had changed their choice.

36 I first adjust constituency-level vote shares by deducting the veteran share multiplied by the event-study coefficient for a particular election and party camp. The adjusted vote shares are then translated into votes, aggregated at the election level, and converted into vote shares again.

37 The election for the national assembly is omitted since votes for the centrist DVP and the conservative DNVP were often difficult to separate in 1919, which led to a somewhat overstated coefficient for the right and a predicted share below zero. Online Appendix Figure C.22 shows counterfactual vote shares for all elections and parties. In line with the above conjecture, one can see that the predicted centrist share was also higher in 1919 than in subsequent elections.

38 Online Appendix Figure C.23 shows that this conclusion would not change even when comparing the shares of pro- and anti-democratic parties where Communist votes are added to the rightwing.

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Figure 0

FIGURE 1 NATIONAL ELECTION RESULTS IN THE GERMAN EMPIRE AND THE WEIMAR REPUBLICNotes: The dark grey-shaded area marks the WWI period. The vertical lines denote the last pre-WWI and the first post-WWI election. Data covers only the area contained in Weimar Germany’s borders and therefore may differ from official national aggregates for elections prior to 1922.Source: Author’s calculations.

Figure 1

FIGURE 2 VETERANS PER CAPITA ACROSS WEIMAR GERMANY BY CONSTITUENCIESSource: Author’s calculations.

Figure 2

TABLE 1 DID ESTIMATES (BASELINE RESULTS)

Figure 3

FIGURE 3 EVENT STUDY GRAPH FOR THE THREE PARTY CAMPSNotes: Coefficients and 95 percent confidence intervals for the effect of veterans per capita on election results for each election between 1893 and 1933, normalized to the effect in 1912. The right-hand side of the regression specification is equivalent to the preferred baseline: Column (2) of Table 1. The light grey-shaded area marks the WWI period.Source: Author’s calculations.

Figure 4

TABLE 2 ALTERNATIVE CHANNELS

Figure 5

FIGURE 4 MEN IN WAR-RELATED LOW-DRAFT OCCUPATIONS ACROSS WEIMAR GERMANY BY CONSTITUENCIES (RESIDUAL AFTER BASELINE CONTROLS)Source: Author’s calculations.

Figure 6

TABLE 3 INSTRUMENTAL VARIABLE ESTIMATES

Figure 7

TABLE 4 DID ESTIMATES FOR TURNOUT AND PARTY GROUPS

Figure 8

TABLE 5 ROLE OF DIRECT WAR EFFECTS AND POLITICAL SUPPLY

Figure 9

TABLE 6 VETERAN EFFECT ON REFERENDA AND PRESIDENTIAL ELECTION RESULTS

Figure 10

FIGURE 5 COUNTERFACTUAL EVOLUTION OF PARLIAMENTARY ELECTION RESULTS IN THE GERMAN EMPIRE AND THE WEIMAR REPUBLIC ASSUMING NO VETERAN EFFECT AFTER WWINotes: The dark grey-shaded area marks the WWI period. The vertical lines denote the last pre-WWI and the first post-WWI election. Data covers only the area contained in Weimar Germany’s borders and therefore may differ from official national aggregates for elections prior to 1922. For better visibility, the distance between elections in 1932 and 1933 has been artificially stretched.Source: Author’s calculations.

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