Germany’s Wartime Occupation of Greece

In May 1941, Axis forces occupied Greece. The country was divided into three occupation zones, the largest of which was administered by Italy. Germany occupied less territory but controlled critical locations including Athens, Thessaloniki, and Crete. Bulgaria was in charge of a relatively small part of the country close to its own borders. From the beginning, the civilian population suffered from expropriations and plunder. The German armed forces requisitioned foodstuffs, causing a major famine during the winter of 1941–1942, leading to an estimated 300,000 deaths (Hionidou Reference Hionidou2006).

Reprisals against potentially uninvolved civilians in areas of armed resistance were first authorized by the German army in April 1941 in Yugoslavia (Mazower Reference Mazower1995). The High Command of the German Armed Forces laid down quotas for reprisal killings: 100 civilians were to be shot for each German soldier killed in a partisan attack, 50 for each soldier wounded, and so forth. Such reprisals against civilians became standard practice of German antipartisan operations in the Balkans and were later extensively used throughout Eastern Europe.

Crete saw the first German reprisals on Greek soil (Nessou Reference Nessou2009).Footnote ⁵ Partisan attacks were often followed by indiscriminate massacres of the civilian population and the destruction of every village near an attack. By 1944, an estimated 2,000–3,000 Greek civilians had been executed by German armed forces on Crete alone (Nessou Reference Nessou2009).

After Italy’s surrender in 1943, German forces occupied the zone held by its former ally. Fighting between guerrilla groups (andartes; mostly the Communist-led Greek People’s Liberation Army) and the Wehrmacht intensified. For example, during an antipartisan sweep by the 117th Jäger Division in the mountains near Kalavryta in the Peloponnese, Greek resistance fighters executed 78 German prisoners. In retaliation, German troops killed 693 of Kalavryta’s inhabitants, including women and children, on December 13, 1943 (Meyer Reference Meyer2002). Some 28 towns and villages in the area were destroyed. Similarly savage reprisals occurred all over Greece, including in the famous cases of Doxato, Kommeno, and Distomo. After the war, the Greek Ministry of Reconstruction estimated that between 11 and 31 thousand Greeks perished in reprisal attacks by German forces, with numerous villages and towns left destroyed (Doxiadis Reference Doxiadis1947, 35–7).

German–Greek Conflict during the Eurozone Crisis

The Greek sovereign debt crisis began in late 2009 when revised budget deficit figures revealed the country’s dire financial situation. This discovery led to successive downgrades of its credit rating. Eventually, with debt markets closed to the Greek government, an EU bailout became inevitable. Appendix Table A.1 summarizes the main events of the debt crisis.

From the beginning, the German government was skeptical of a financial rescue for Greece, emphasizing the scale of tax evasion and corruption as obstacles to any permanent improvement.Footnote ⁶ It finally agreed to the bailout in exchange for harsh austerity measures. Greek public opinion accordingly saw Germany as the instigator of foreign-imposed austerity. Figure A.1 provides evidence of this from our own survey data. Though the majority of respondents (83%) identifies Greek politicians as the single major actor to blame for the crisis, Germany comes in second place (5.58%) and ahead of the EU, the IMF, or US-based banks. More tellingly, when respondents are allowed to blame multiple actors for the crisis, blame attribution toward Germany is high. Over 60% of respondents completely agree with the statement that “Germany imposed austerity measures at a time when Greece was weak. This is what caused the country’s economic crisis.”Footnote ⁷

The reaction to German-imposed austerity was immediate and intense: in February 2010, the Greek Consumers Association called for a boycott of German products—explicitly highlighting the importance of cars.

Incendiary press coverage amplified the animosity. German newspapers portrayed Greeks as lazy cheaters, living it up at the expense of German taxpayers.Footnote ⁸ The cover page of a German weekly featured Aphrodite making a rude gesture; a tabloid urged Greece to sell some of its islands to repay its debts.Footnote ⁹ As the Greek economy contracted and unemployment surged, anti-German sentiment in Greece deepened. During the 2012 visit of German chancellor Angela Merkel to Athens, thousands of demonstrators filled the streets of Athens.Footnote ¹⁰

Memories of Nazi massacres during the Occupation frequently resurfaced in Greece during that period. When a journalist from the Daily Telegraph interviewed Greeks during the Euro debt crisis about their country’s treatment by Germany, the massacre at Distomo immediately came up. A 45-year old bar owner contrasted this atmosphere with the period immediately preceding the crisis: “Five years ago, no one had any problems with Germany.” In the past, family members of the victims of Distomo had sued for reparation payments, taking their case to the German courts and to the International Court of Human Rights. Although Germany’s Constitutional Court dismissed the case in 2003, it was revived when an Italian court awarded victims’ descendants Italian property owned by a German nongovernmental organization. The case reached the International Court in 2012, at the height of the Greek debt crisis, and featured prominently in the Greek press.Footnote ¹¹

One may argue that Germany’s aggression in WWII and German-backed austerity in the 2010s were very different events, unlikely to be associated in anyone’s mind. Yet they were not treated as such by Greek media, politicians, and ordinary people. The associations made derived from a central similarity between past and present: the identity of the foreign power that was perceived as an aggressor. With Germany identified as the instigator of austerity, parallels were also drawn between the effects of WWII and those of the debt crisis. Although not comparable to a historical event that led to mass starvation and the killing of civilians, for many people the debt crisis was one of the worst things they experienced in their lifetimes—businesses bankrupted, pensions cut, and savings devastated. The main actor involved, the adversarial nature of the situation, and the negative implications for people’s lives appear to be the factors that triggered associativeness of collective memory in the case of the Greek debt crisis.

Conflict Index

We compile an index of conflict by computing the frequency of newspaper articles that refer to political tensions between Greece and Germany in a leading Greek newspaper, Kathimerini. We use a supervised learning approach: we first manually code articles relevant to German–Greek conflict and then use search terms distinctive of relevant articles to classify the remaining corpus. We detail our procedure in Section B.1.1 of the Appendix.

Figure 1 plots the share of conflict-related articles for the period 2009–2014. Although there is a gradual rise in the overall conflict article share after 2010, there are also numerous short-term spikes when public arguments between Greek and German politicians grew particularly heated. Several of them are concentrated in 2012, when unrest and protests against austerity in Greece coincided with dissatisfaction around the International Court’s ruling in favor of Germany on the issue of wartime reparations.

Car Registrations

Our main behavioral outcome variable is car sales. We focus on it for three reasons. First, car purchases represent a major purchasing decision, making this variable a good measure of how economic behavior responds to the interaction of time-varying political conflict and collective memory. Second, cars are an iconic German product. Car sales thus allow us to directly link anti-German sentiment to a behavioral measure. Political behavior such as voting is motivated only in small part by anti-Germanism, making the effects of collective memory harder to discern in political outcomes. Finally, from an empirical point of view, data on car sales is available at a high frequency, allowing us to examine how even short-run changes in the salience of current events interact with latent memory.

We use monthly data on new car registrations from the Greek Ministry of Transport and distinguish between German and non-German brands (see Appendix Section B.1.2).

Reprisals

We create a unique dataset of the universe of Greek towns that experienced reprisals by German occupying forces during World War II. With the help of a professional historian, we combine information from a variety of primary sources and secondary literature. A list of sources is provided in Table B.1. The final list contains 400 towns that experienced reprisals in at least one of the sources we consulted.

Figure 2 displays a map of German reprisals. It shows a high concentration of affected towns in Central and Northern Greece and on Crete. These are regions with rugged terrain, which attracted partisan activity, but instances of reprisals are also widely dispersed across the territory. At the prefecture level, average exposure to reprisals is not predicted by any economic, historical demographic, or political factor. Table B.2 in the Appendix shows that the only variables that are significantly higher in prefectures with reprisals are log population, the precrisis German market share, and distance from the prewar road network, which predicted partisan activity. Although our identification strategy does not require that prefectures with and without reprisals are balanced in terms of observables at baseline, our preferred specifications include interactions of all baseline controls with the monthly share of conflict articles to account for any differential responses driven by correlates of reprisal exposure.

Figure 2. The Geography of German Reprisals in Wartime Greece

Our main dataset of time-varying conflict, car sales, and reprisals contains information on 51 prefectures over the period January 2008 to December 2014. The main features of the data are summarized in Table B.3.

Additional Variables

We collect additional data to explore the mechanisms behind the effect of reprisals. Since 1992, the Greek government awarded towns that suffered reprisals during the German occupation martyr status. Towns could apply for this designation, which was decided by a committee of experts and awarded by Presidential Decree. Martyr status did not come with material benefits but did imply stronger and state-sanctioned commemoration of WWII atrocities.

There are 104 towns identified as martyred, of which 54 witnessed mass executions of civilians. The rest were burnt to the ground in retaliation for an insurgency attack against German armed forces in the vicinity (Nessou Reference Nessou2009). Their spatial distribution, which closely follows that of reprisals, is depicted in Figure 2. Table B.2 shows that prefectures with martyr towns are similar to other prefectures across a wide range of characteristics, with the exception of their distance to the prewar road network and a small difference in the share of residents with secondary education.

We also conducted a telephone survey of mayors’ offices in all towns that experienced reprisals to ascertain whether a community organizes a commemorative event or whether a monument exists. There are approximately twice as many towns with a monument or public event as there are places officially recognized as martyred.

Survey

In the summer of 2017, we conducted a telephone survey in Greece. We sampled a total of 928 individuals from 143 municipalities, distributed across 12 prefectures. Respondents were drawn from 30 reprisal towns and 113 control towns that did not see reprisals. For each prefecture, we tried to obtain an approximately balanced sample of respondents between reprisal and control towns.Footnote ¹²

In addition to socioeconomic characteristics, we collected information on respondents’ actual and ideal cars, views of Germany and its role in the crisis, and proxies of activism and national identity. Table B.4 in the Appendix provides summary statistics for our survey sample. The sample is balanced on observables—there are no significant differences of age or gender, and the proportion of unemployed tends to be higher in the locations unaffected by reprisals. Income and education levels are similar, and the cars owned by survey participants are about the same age in both groups.

Empirical Strategy

We begin by estimating the following equation for the share of German car sales in each prefecture i at time t:

(1) $$ {S}_{it}\hskip0.35em =\hskip0.35em {c}_i+{y}_t+{m}_t+{\gamma}_1{A}_t+{\gamma}_2{A}_t\times {T}_i+{e}_{it}, $$

where $ {S}_{it} $ is the share of German cars, $ {A}_t $ is the monthly share of conflict-related news articles, $ {c}_i $ are prefecture fixed effects, $ {y}_t $ are year fixed effects, and $ {m}_t $ are calendar month fixed effects that account for seasonality in the German market share.

In line with existing literature on the effects of violence and conflict (Condra et al. Reference Condra, Long, Shaver and Wright2018; Peffley, Hutchison, and Shamir Reference Peffley, Hutchison and Shamir2015; Voigtländer and Voth Reference Voigtländer and Voth2012), we operationalize the treatment at the prefecture level as an incidence count, equal to the number of towns that fell victim to reprisals.Footnote ¹³ To avoid a mechanically higher number of reprisal attacks in prefectures with more towns, we normalize this count by the total number of towns in existence in a prefecture in 1940. Our main measure of exposure to German war crimes is $ {T}_i $ , the share of a prefecture’s towns in 1940 that experienced an attack, which is equivalent to a prefecture-level incidence rate of reprisals. We also present results with an alternative measure of exposure—the share of population living in affected towns today. The main coefficient of interest is $ {\gamma}_2 $ —the extent to which the German car market share declines differentially in prefectures with more towns that experienced reprisals by the German army during World War II.

The need to aggregate town-level data up to the level of the prefecture—the level at which we have information on car registrations—is an inherent limitation of our setup. In Appendix Section C.5, we show that aggregation influences the precision of our estimates but does not affect the main conclusions we would draw from an analysis at the town level.Footnote ¹⁴

We augment the above specification with interactions of baseline prefecture-level controls with the monthly share of conflict-related articles, as well as interactions of prefecture fixed effects with calendar month fixed effects, to account for prefecture-specific seasonality patterns in car sales.Footnote ¹⁵ Our most parsimonious specification includes a full set of time (month) fixed effects and thus accounts for any unobservable factor that varies at the monthly level and affects all prefectures in the same way. We cluster standard errors at the prefecture level.

Effects on Purchasing Behavior

We present estimation results from Equation 1 in Panel A of Table 1. The share of conflict articles in a given month is negatively associated with the share of German cars, but the effect is not tightly estimated. However, months of high conflict are strongly and significantly correlated with a decline in German car sales in areas with a higher share of reprisal towns.

Table 1. Baseline Results

Note: ^***p $ < $ 0.01, ^**p $ < $ 0.05, *p $ < $ 0.10.

In column 2, we add interactions of the conflict article share with precrisis control variables. This is intended to capture any differential effect that political acrimony between Germany and Greece after 2010 might have had in areas that were different before the crisis. In column 3, we add an interaction of prefecture fixed effects and calendar month fixed effects, thus accounting for seasonality patterns that potentially differ across prefectures. In column 4 we control for a full set of time fixed effects. The interaction coefficient increases in magnitude after these additions.

The estimated effects are substantively large compared with the average precrisis market share of German cars, which is close to 26%. The most parsimonious specification (column 4) implies that, relative to prefectures without reprisals, a prefecture with average exposure to WWII violence experienced a 4 percentage-point drop in the share of German cars at peak conflict (compared with the precrisis period); the most exposed prefecture, with over 30% of towns affected by reprisals, experienced a 17 percentage-point drop.

Our preferred measure for a prefecture’s exposure to reprisals is the share of reprisal towns, as it directly aggregates the unit of treatment assignment (the town) up to the prefecture level. Alternative measures of treatment intensity can be constructed if we first make assumptions about who is treated at the individual level and then aggregate up to the prefecture level. If we assume that the main effect of WWII reprisals is on current residents in affected towns—who also constitute the main decision-making unit that purchases cars—we can use the share of a prefecture’s precrisis (2011) population as a proxy of treatment intensity. Panel B of Table 1 shows that estimated effects using that measure are qualitatively similar to those in Panel A. Relative to prefectures without reprisals, the average prefecture that experienced violence registers a 2 percentage-point drop in the German car market share at peak conflict; the most exposed prefecture registers an 11 percentage-point drop.

The accuracy of this alternative treatment proxy depends on which individuals are actually treated. When a reprisal attack affects not only residents of the town but also those of neighboring towns, a population-based measure will underestimate the effect of reprisals.Footnote ¹⁶ As an additional notable disadvantage, this measure ignores potential postwar migration across towns. Victims of reprisals and their descendants may have moved to nearby towns in the same prefecture, especially in the case of towns razed to the ground by German forces. In line with these observations, magnitudes in Panel B are somewhat smaller than in Panel A.Footnote ¹⁷

Ruling out Alternative Explanations

Effects on Political Outcomes

Our analysis so far has demonstrated that present events that recall the past can directly affect consumer behavior. Do similar effects extend to other aspects of behavior with more direct implications for politics? Here, we examine whether the reactivation of memories of violence affects voting patterns in Greece during the debt crisis. Relative to the analysis of consumption patterns, there are two limitations. First, although the debt crisis spans several election periods, voting outcomes are not observed at the high frequency of car registration data and do not allow us to examine immediate responses to spikes in Greek–German conflict. Second, electoral choices are determined by a host of party positions and characteristics, of which stances against Germany are only one—and arguably, in many cases a minor factor. The nationality of the manufacturer of cars allows us to directly link consumer behavior to consumers’ country-specific attitudes, but the link between party choice and parties’ expressed stance toward Germany is less direct.

We investigate whether voters in areas affected by reprisals were more likely to favor parties that held a critical stance toward Germany during the debt crisis. To identify anti-German parties, we take a data-driven approach and analyze the rhetoric of Greek MPs in parliamentary speeches. Figure 3 displays a measure of negative sentiment in MP speeches mentioning Germany, averaged over the 2009–2015 period. Unsurprisingly, MPs of opposition parties use a more negative tone in speeches referring to Germany compared with MPs from the two major parties of PASOK and Nea Dimokratia (ND). Syriza, the left-wing party that led the antiausterity opposition during the early period of the crisis and took power in the January 2015 legislative election, is significantly more anti-German than are PASOK and ND. It is less anti-German than the Communist Party (KKE), the conservative Christian party (LAOS), or the extreme right party (Golden Dawn), which entered Parliament for the first time during the debt crisis.

Figure 3. Average Sentiment in MP Speeches on Germany

Note: See Appendix Section B.1.3 for the computation of the sentiment measure. Bars denote averages across all party MPs and years for all speeches containing the token “German.”

To examine the time-varying effect of memory on voting behavior, we compare votes for more versus less anti-German parties before and after the crisis and differentially by past exposure to German war crimes. We use electoral data at the lowest level of administrative division, the municipal unit ( $ N\hskip0.35em =\hskip0.35em \mathrm{1,035} $ ), for six legislative elections between 2007 and 2015. The precrisis elections of 2007 and 2009 help rule out the presence of pretrends. We focus on parties that ran in both pre- and postcrisis elections and group them into more (KKE, LAOS, Syriza) and less anti-German (PASOK, ND).Footnote ²⁰ We estimate the following for each party or group of parties:

(2) $$ {V}_{mt}\hskip0.35em =\hskip0.35em \sum_{\tau =\mathrm{Oct}\;2009}^{\mathrm{Jun}2015}\;{\beta}_{\tau }{R}_m\times \unicode{x1D7D9}\left(t\hskip0.35em =\hskip0.35em \tau \right)+{\gamma}_m+{\zeta}_t+{\varepsilon}_{mt}, $$

where $ {V}_{mt} $ denotes the vote share of the party in municipal unit $ m $ and election period $ t $ . $ {\gamma}_m $ and $ {\zeta}_t $ are municipal unit and election period fixed effects, $ {R}_m $ is an indicator for municipal units that contain towns with a past of reprisals, and 1(t = τ) is an indicator equal to one for each election period between September 2007 and June 2015.

Figure 4 shows the results. Effects are relative to the 2007 baseline. There is no difference in vote patterns by reprisal status before the start of the crisis. Beginning with the first postcrisis election in May 2012, vote shares of more and less anti-German parties diverge across municipal units. The vote share of parties critical of Germany increases by up to three percentage points—a percentage equal to the electoral threshold in Greece—in municipal units with past exposure to reprisals. The vote share of PASOK and ND drops. Figure A.2 in the Appendix disaggregates the effects by party. Observed patterns are driven by all parties. The conservative Christian party and KKE, the two parties most critical of Germany in Parliament, experienced an immediate surge in support after the crisis. Support for Syriza increased after June 2012, culminating in the two 2015 elections, when the party had become the most viable opposition force in the fragmented political landscape of Greece. In terms of magnitude, differential support for Syriza is what drives the anti-German vote in reprisal municipal units. In the January and September 2015 elections, Syriza registered a 2 percentage-point higher vote share in municipal units that experienced reprisals.

Figure 4. Vote Share by Party Anti-Germanism and Reprisal Status

Note: The figure displays coefficient estimates of $ {\beta}_{\tau } $ from Equation 2 along with 95% confidence intervals. The dependent variable is, respectively, the aggregate vote share of ND and PASOK (black lines) and Syriza, KKE, and LAOS (gray lines). Standard errors are clustered at the municipal unit level. Table of full estimation results is provided with supplementary materials on the American Political Science Review Dataverse.

To mirror the more aggregate analysis of economic behavior, in Section C.5 of the Appendix we replicate these results at the level of the electoral periphery, a unit of analysis close to the prefecture ( $ N\hskip0.35em =\hskip0.35em 56 $ ). We find effects on voting patterns that are identical in direction but larger in magnitude than those at the municipal unit level, and we provide evidence that this difference is due to the presence of spillovers from localities directly affected by reprisals to neighboring localities.Footnote ²¹ This exercise demonstrates that our results in the analysis of car registrations are not the artifact of aggregation bias.

Taken together, the analyses of party vote shares echo our findings on purchasing patterns and indicate that reactivated memory affects all aspects of behavior, from consumption to political choices.

The Effect of State Recognition

In 1993, the Greek parliament debated recognition of Kalavryta as a martyr town. During the discussion, the idea of launching a procedure to award similar status to other towns affected by reprisals during World War II emerged. Towns destroyed during the German occupation could apply for martyr status designation. A committee of experts was convened to assess applications and award martyr status on the basis of objective criteria relating to housing destruction and population losses during WWII (see Appendix Section B.1.4). These criteria were flexibly interpreted by committee members and were not strictly followed in practice.

Martyr status is a purely honorific designation, with no material benefits for towns that acquired it. However, the martyr label is associated with both greater awareness of local WWII atrocities and a greater visibility of those atrocities in public life. All martyr towns—but not all towns that experienced violence in WWII—commemorate reprisals in some way. Schools in many martyr towns highlight local reprisals when otherwise teaching the history of WWII following Greece’s centralized educational curriculum. As a result, residents of martyr towns have greater awareness than do residents of other reprisal locations of not only WWII events but also their towns’ martyr designation. We provide more qualitative evidence for this claim when we discuss mechanisms behind the effect of martyr status.

We start by providing evidence that the ministerial committee tasked with awarding martyr status to towns affected by reprisals did so by following a relatively simple heuristic. The left plot of Figure 5 is a binned scatterplot of reprisal towns granted martyr status by percentage of destruction, with regression discontinuity curves fitted following Calonico, Cattaneo, and Titiunik (Reference Calonico, Cattaneo and Titiunik2015). The likelihood of receiving martyr status is increasing in the extent of destruction recorded in ministerial sources. The probability of receiving designation jumps around a destruction level of 50%. This is examined more systematically in columns 1–2 of Table A.2 for different polynomials in the destruction variable. Although martyr status jumps discretely, population in 1940 varies smoothly around the 50% threshold (columns 3–4).Footnote ²² As the reading of the committee minutes suggests, there was substantial leeway in making a final determination; the discontinuity at the 50% cutoff suggests that the committee de facto followed the rule of assigning martyr status to borderline cases whenever half or more of the town was registered as destroyed in official records.

Figure 5. Martyr Status and Destruction

Note: Binned scatterplot of towns granted martyr status (left) and towns that applied for martyr status (right) among towns that experienced reprisals, by percentage of destruction. Data restricted to towns with 40% to 60% destruction. Regression discontinuity curves with quantile-spaced partitioning follow Calonico, Cattaneo, and Titiunik (Reference Calonico, Cattaneo and Titiunik2015).

With the exception of Kalavryta, towns had to apply in order to be considered for martyr status. Applications requesting recognition were filed by 56% of towns that experienced reprisals, and 30% (or 54% of those that applied) were eventually granted the martyr designation. Towns with higher levels of destruction were more likely to apply (59% of towns with above 50% destruction compared with 50% of towns below). However, the right plot in Figure 5 and columns 5–6 of Table A.2 reveal no discontinuity in the number of towns that applied for martyr status. This is evidence that the 50% threshold influenced the decisions of the expert committee directly, not through the amount of applications that the committee received.

The evidence from the regression discontinuity design (RDD) and a close reading of the discussions of the committee minutes thus suggest that the awarding of martyr status—although correlated with destruction and population loss—also contains an important accidental element. Therefore, we ask whether the receipt of martyr status influences German car purchases above and beyond the effect of destruction itself. Panel A of Table 2 replicates results from Table 1 for purposes of comparison. In Panel B, we estimate Equation 1 using the share of martyr towns in a prefecture as the source of cross-sectional variation. The differential effect of conflict in prefectures with a higher share of martyr towns is negative and significant. The magnitudes are consistent across specifications, and the estimated effects are large: relative to a prefecture without martyr towns, the average prefecture with state-recognized memory experienced a drop of 5.7 percentage points in the German car market share at peak conflict.

Table 2. The Effect of Martyr Status

Note: ^***p $ < $ 0.01, ^**p $ < $ 0.05, *p $ < $ 0.10.

Next, we conduct a horse race between the time-varying effect of reprisals and of public recognition. We always control for the average extent of destruction in a prefecture to account for the fact that martyr status is more likely to be awarded to towns with higher recorded levels of destruction. Panel C of Table 2 shows that prefectures with a higher share of martyr towns display large and significant differential drops in the German car market share in months of conflict. Prefectures more exposed to reprisals also register a differential drop, though this is smaller in magnitude and not statistically significant. That means that between two prefectures with the same average exposure to reprisals, the one with a higher share of officially recognized martyr towns saw a much sharper fall in German market share—publicly recognized status as a major victim of Nazi aggression matters over and above the occurrence of conflict itself.

Finally, we exploit the discontinuity in the awarding of martyr status at the 50% cutoff of destruction to isolate the exogenous component of public recognition. In Panel D of Table 2, we use the predicted share of martyred towns in a prefecture based on the 50% criterion to explain changes in market share. We create a dummy for towns that are assigned a predicted value > 0.5 in a regression of martyr status on a dummy for destruction higher than 50% and a quadratic polynomial in destruction. We then aggregate towns predicted to receive martyr status at the prefecture level as a share of all towns in 1940. The resulting variable confirms the large and significant effect of martyr status on car sales.

Because we do not have town-level data on car sales, we cannot implement an exact analogue to the RDD specification—showing that a narrow band of destruction driving assignment to martyr status is responsible for declining German market share. Instead, we show that the coefficient on the interaction between martyr status and article share remains negative and significant as the share of reprisal towns in a prefecture with destruction in the range of 25%–75% increases (Table A.3).

Mechanisms

The results of the previous section indicate that designation of martyr status effectively preserves latent collective memory, which can then become reactivated in the presence of associative stimuli. How is this achieved? Our evidence suggests that martyr status designation leads to more intense commemorative activity, directly supported by the state, that not only preserves memory among those affected and their descendants but also transmits it to members of the community without a direct personal or family experience of past violence. We present this evidence below.

The Role of Public Commemoration

On occasions when WWII atrocities are commemorated, residents of martyr towns are also reminded of the official martyr status of their towns. Knowledge of martyr status may itself aid in preserving memory, as residents think of their town as exceptional or of themselves as having a responsibility to remember the past. Is it the strength of commemoration or the label itself that aids the preservation of memory in martyr towns? To address this question, we systematically measure public commemoration and its effects on the reactivation of memory. Many towns in Greece commemorate World War II atrocities, often by public festivities or through memorials. We conducted a telephone survey of municipal offices in all towns that experienced reprisals and coded whether the community commemorates the violence it experienced with a monument or ceremony.

Panels A and B of Table 3 show that the drop in German market share in months of conflict is significantly larger in prefectures with a higher share of towns that commemorate reprisals. The magnitude of the effects is larger than that of exposure to reprisals (Table 1). Public commemoration is an important vehicle of memory preservation, and more memorialization enhances the effects of time-varying conflict in triggering latent memory.

Table 3. Pathways for the Effect of Official Recognition

Note: Reported p-values are from a test for the equality of coefficients on Article share × Share towns w/ memorial (nonmartyr) and Article share × Share martyr towns (Panel C) or Article share × Share pop. w/ memorial (nonmartyr) and Article share × Share martyr pop. (Panel D); ^***p $ < $ 0.01, ^**p $ < $ 0.05, *p $ < $ 0.10.

To understand whether public commemoration is the main driver of martyr status effects, we separately examine the effect of memorials and of official government recognition in Panels C and D of Table 3. Of towns officially recognized as martyr, 95.5% have a public commemoration or memorial, which is consistent with the evidence above on public commemoration being more intense in martyr towns than in other reprisal towns.

We construct a separate measure for the prefecture share of towns (Panel C) or population (Panel D) with a memorial that do not have official martyr status. Both martyr status and memorials in the absence of official recognition strongly predict differentially lower German market shares after 2010. The magnitude of their effects is comparable. Reported p-values indicate that martyr status has somewhat larger (Panel C) or similar effects compared with public commemoration (Panel D). This result suggests that memorials and public ceremonies are central in preserving collective memory. It also indicates that the label of martyr status may matter primarily through the degree of commemoration it brings with it.

We then examine whether the same pattern replicates in the case of voting outcomes. We estimate Equation 2 by including interactions of period dummies with indicators for martyr status and for the presence of memorials in municipal units without official state recognition. Figure 6 displays results remarkably similar to those of Table 3 in the case of cars. The entire differential increase in the vote share of parties critical of Germany comes from municipal units that contain martyr towns. There is no significant difference between officially recognized victim status and commemoration (without martyr status). This supports the interpretation that state recognition of past violence works by raising the visibility of memory in public life. Without such visibility, time-varying conflict fails to trigger associations with past conflict: reprisal towns without official recognition or memorials do not experience differential changes in their voting outcomes postcrisis.

Figure 6. Anti-German Party Vote Shares by Martyr Status and Public Commemoration Activity

Note: The figure displays coefficient estimates and 95% confidence intervals for the interaction between election period and indicators for, respectively, reprisal status (black), martyr status (dark gray), and presence of memorials without official recognition (light gray). The dependent variable is the aggregate vote share of Syriza, KKE, and LAOS. Standard errors are clustered at the municipal unit level. Table of full estimation results is provided with supplementary materials on the American Political Science Review Dataverse.

The presence of memorials is a community-level decision that may be driven by patriotism and other correlates of anti-German sentiment. Although we caution against a causal interpretation of the influence of memorials, the findings in this section arguably suggest an important role for commemorative activities in driving the effects of state-sanctioned memory.

The Role of Family Transmission

Much of the literature on the legacy of conflict has focused on the role of family transmission as a channel of persistence. Our study instead highlights the role of the state in preserving collective memory through institutionalized commemoration. To what extent is there overlap or interaction between these two processes? Our analysis shows that state recognition has an independent effect on memory and behavior, over and above any process of intergenerational transmission. Based on exogenous variation in the degree of recognition as isolated by an RDD, two communities with similar characteristics, and thus presumably similar strength of family transmission, differ in their reactivation of latent collective memory as a result of differences in martyr status.

Although intergenerational transmission does not confound the effect of state sanction, it is possible that the two processes interact. Martyr status ensures visibility of the past for an entire community, but its effects on memory preservation could be stronger for community members with personal or family experience of German atrocities (Dinas, Fouka, and Schläpfer Reference Dinas, Fouka and Schläpfer2021). If that is the case, then state sanction’s effect may be to intensify the process of intergenerational transmission by widening the gap in the memory of conflict between those with familial exposure and everyone else.

Our data do not provide strong evidence for this scenario. Figure 7 plots average responses to survey questions capturing anti-German attitudes (see Table C.3) across reprisal towns (all of which have martyr status) and control towns, comparing individuals native to a town and others. We define as native those respondents born in the town and with at least one parent born in the town. These individuals may either have been directly affected by reprisals or have had family members who were and thus be carriers of local memory through family transmission channels. With the exception of actual purchasing behavior, there is no immediate visual evidence that differences between martyr towns and control locations come from natives. Both natives and nonnatives in martyr towns are less likely to desire a German car and more likely to blame Germany for the crisis than are respondents in control towns. We verify this in Table A.4 where we find no significant interaction effect between a town’s martyr status and a respondent’s native background, either on average or when we control for an additional set of respondent characteristics interacted with the martyr indicator.

Figure 7. State Recognition and Family Transmission

Note: Native refers to individuals born in a town and with at least one parent born in the town; 95% confidence intervals reported.

The survey data then indicate that martyr status does not significantly intensify any effects of intergenerational transmission or, alternatively, that it does not have more of an influence on those for whom intergenerational transmission is likely more active (natives). Combined with the rest of the evidence in this section, it appears that state sanction, working through public commemoration and the visibility of the past in various facets of public life, acts uniformly on the entire community, preserving collective memory for affected members and transmitting it to an equal degree to newer arrivals.