Reprisals Remembered: German-Greek Conflict and Car Sales During the Euro Crisis

Reprisals Remembered: German-Greek Conﬂict and Car Sales during the Euro Crisis∗

Vasiliki Fouka Hans-Joachim Voth

First draft: December 2012 This draft: May 2013

Abstract

During the debt crisis after 2010, car sales in Greece contracted sharply. This paper examines how much German car sales declined in periods of German-Greek conflict. It shows that German car sales fell sharply in areas affected by massacres during World War II – especially in periods of public conflict between the German and the Greek government. The German government was widely blamed for the harsh austerity measured imposed on Greece as a condition for several bailout packages. This led to public outrage and a rapid cooling of relations between the two countries. We conclude that cultural aversion was a key determinant of purchasing behavior, and reflected the memories of past conflict in a time-varying fashion. We compile a new index of public acrimony between Germany and Greece based on newspaper reports and internet search terms. In addition, we use historical maps on the destruction of villages and the mass killings of Greek civilians by the German occupying forces between 1941 and 1944. During months of open conflict between German and Greek politicians, sales of German cars fell markedly more than sales of those produced in other countries. This is especially true in areas affected by German reprisals during World War II: areas where German troops committed massacres and destroyed entire villages curtail their purchases of German cars to a much greater extent in conflict months than other parts of Greece.

Keywords: Consumer behavior, cultural aversion, political conﬂict, boycott, car sales, Euro crisis, German-Greek relations.

∗We would like to thank Jordi Gali, Luigi Pascali, Giacomo Ponzetto, as well as seminar participants at CREI for their helpful advice. The Hellenic Statistical Authority kindly provided car registration data.

1 1 Introduction

When German Chancellor Angela Merkel visited Athens in 2012, she was greeted by angry protests. Demonstrators carried placards depicting her in Nazi uniform, de- nouncing the rise of a “Fourth Reich”. Since 2010, there has been repeated and severe conflict between the German and the Greek governments. Ever since it was discovered that Greece had forged debt figures, forcing it into a humiliating EU bailout, German politicians in particular were blamed for harsh austerity measures. Adding fuel to the flames of discontent was the fact that politicians in Northern Europe – and especially in Germany – repeatedly made disparaging remarks about the country, and the popular press printed incendiary headlines and insulting images. Greek consumer groups quickly began callling for a boycott of German goods. Strikingly, memories of World War II played an important role in Greek condemnations of German attitudes and policies: German institutions were defaced with swastikas; populist politicians demanded German reparations for war crimes; and newspapers both foreign and Greek recounted German massacres after 1941. In this paper, we examine how these instances of public conflict affected consumer behavior. In particular, we test if areas that suffered German war crimes during the occupation saw sharper changes in purchasing patterns. To trace the impact of cultural aversion – and the way it interacts with location-specific memories – we focus on car purchases. Cars are often seen as an archetypal German product.1 Examining car purchases constitutes a demanding test – they represent a major (and rare) investment. We hypothesize that public conflict and calls for a boycott of German products reduced sales of German automobiles, and that these reductions were greater where the Wehrmacht had destroyed entire villages and committed massacres.

1In the 1980s, Audi discovered that it was not perceived as a German car producer in some of its core markets, such as the UK. It began an advertising campaign featuring a highly idiomatic – and near-inscrutable – German motto (“Vorsprung durch Technik”) to drive home the point of its national origin.

2 We first compile an index of German-Greek political clashes based on newspaper reports in Greece and on the frequency of internet search terms. These indicators show an explosion of conflict after 2010, with eight separate periods of particularly intense public conflict. Sales of German-made cars suffered marked declines during political clashes. We combine this time-series information with detailed data on the location of German massacres during the occupation, 1941-44. Following an upsurge in partisan activity, the German occupying forces adopted a policy of harsh reprisal measures. These involved burning entire villages, and killing the entire civilian population (Ma- zower, 1995). To measure the severity of these attacks at the local level, we use lists drawn up by the Greek government designating localities as “martyred towns”. These are based on a set of criteria including the percentage of homes destroyed, as well as the loss of human life. The locations of these martyred towns are then mapped onto the 50 prefectures into which Greece is divided for administrative purposes. Car registration data are collected and disseminated at the level of the prefecture. We find strong evidence that in areas of Greece affected by Wehrmacht reprisals during World War II, sales of German-made automobiles fell more sharply than elsewhere during conflict months. This suggests that consumer behavior – the purchase of big-ticket items like cars – responds strongly to general public sentiment; where local memories of earlier German wrong-doing could easily be activated, purchases were curtailed sharply. Boycotts are frequently used to articulate political views. Evidence on their effectiveness is mixed. More than half of top brands in the US were targeted by a call for a boycott in the period 1980-2000. There is only limited evidence that consumer behavior is directly influenced by calls for political action. For example, boycotts of French wine after the country’s failure to support the US in Iraq were probably ineffective Ashenfel- ter et al. (2007);2. Teoh et al. (1999) examine the effect of the South African Boycott on

2Chavis and Leslie (2006) earlier concluded that French wine sales in the US suﬀered after the start of the Iraq war.

3 firm valuation, and find that it had no clear impact. In general, the stock prices of firms in calls for boycotts typically do not react (Koku et al., 1997). John and Klein (2003) argue that The main counter-examples include a decline in tourist visits by Americans to France after 2003 (Michaels and Zhi, 2010); lower French car sales in China during the 2008 Olympics (Hong et al., 2011); and suggestive evidence that French-sounding products saw their sales slump in the aftermath of the Iraq war (Pandya and Venkate- san, 2012). In a closely related paper, (Fisman et al., 2012) examine the stock market value of Chinese and Japanese firms after a cooling of Sino-Japanese relations in 2005 and 2010. This followed the introduction of new Japanese textbooks that downplayed events during the Japanese invasion of China in the 1930s. Stock prices fell more for firms that had a higher sales exposure to the other side, especially in industries with large public sector involvement. They find no evidence of systematic changes in stock prices of firms in consumer goods sectors. Our paper also contributes to an emerging literature on the importance of cultural factors in economic and social behavior. Countries that fought numerous wars in the past continue to trade less with each other to the present day, and they engage in less FDI Guiso et al. (2009). Fertility behavior of immigrants’ children is still influenced by their parents’ country of origin (Fernándezand Fogli, 2006), language characteristics are associated with savings behavior (Chen 2012), and inherited trust can influence national growth rates (Algan and Cahuc, 2010). Many attitudes persist over long periods: Italian cities that were self-governing in the Middle Ages are richer and more civic-minded today (Guiso et al., 2007), areas of Africa affected by 19C slave-hunts have lower trust in the present (Nunn and Wantchekon, 2011), and German cities that persecuted their Jews during the Black Death were markedly more anti-Semitic in the 1920s and 1930s (Voigtländerand Voth, 2012). At the same time, culture is not only persistent, it can also change quickly: Atti- tudes towards pre-marital sex have been transformed in the last century (Fernández- Villaverde et al., 2011); Islam changed from an open and tolerant religion to a rela-

4 tively intolerant one (Chaney, 2008); Franco-German conflict in the last 200 years was repeated and seemingly deeply rooted in cultural differences (Mann 1916), but has van- ished in the last 50 years. One of the key challenges for cultural economics is to analyse the conditions for persistence, and the context in which contemporary attitudes are no longer influenced by the past. Relative to the existing literature, we make the following contribution: First, we are among the first to show that actual consumer behavior is modified in response to time-varying cultural aversion,3 and not simply stock-market valuations of large firms mainly selling to the public sector (Fisman et al., 2012). Second, we show that cross- sectional differences in memories of past conflict and “reasons to hate” matter in periods of general conflict. Third, this paper demonstrates that it is not only small consumer expenditures, such as purchases of shampoo or coffee, but purchases of big-ticket items (like cars) that are affected by political conflict. We proceed as follows. Section II presents the history and background of German- Greek conflict since 1941 and describes our data. Section III presents the main results, and section IV shows robustness checks and extensions. Section V concludes.

2 Historical Background and Data Description

In this section, we brieﬂy summarize the history of German-Greek conﬂict during World War II, as well as the period of crisis after the outbreak of the sovereign debt crisis in 2010. Next, we summarize how our data on car sales and on German reprisal measures is constructed.

3As in Michaels and Zhi (2010), Hong et al. (2011), and Pandya and Venkatesan (2012)

5 2.1 German retribution measures in Greece during WWII

Following a military campaign that lasted less than a month, Greece was occupied by Axis forces in May 1941. The country was divided into three occupation zones. The largest one was administered by Italy. Germany occupied a smaller part of the territories, but controlled crucial locations including Athens, Thessaloniki and Crete. Bulgaria administered a relatively small part of the country close to its own borders (Figure 1). From the beginning, the civilian population suffered under the harsh measures of expropriation and plunder that followed the occupation. The German armed forces requisitioned foodstuffs on a vast scale, leading to a major famine during the winter 1941-1942. An estimated 300,000 people died, and the period still survives in Greek collective memory (Hionidou, 2006). Throughout Eastern Europe, the German armed forces targeted the civilian population in a bid to deal with partisan attacks. Shooting of potentially uninvolved civilians in areas of armed resistance was first authorized in April 1941 in Yugoslavia (Mazower, 1995). Following the capture of Crete - involving heavy losses by the Wehrmacht in the face of determined local and Allied resistance – reprisal measures were also used there (Nessou, 2009). General Student, the temporary commander of Crete after the German invasion of the island, explicitly instructed his forces to “leave aside all formalities and deliberately dispense with special courts”, since these were not fit for “murderers and beasts”. The town of Kondomari in Crete was the first to witness a mass execution of civilians by the Germans on Greek soil: 19 people were shot in June 2, 1941, in retaliation for the death of a German military official in the town’s vicinity (Meyer, 2002). Both mass shootings and the burning down of villages became standard practice. Until 1944, an estimated 2-3,000 Greek civilians were executed by the German armed forces on Crete alone, and 1,600 (out of a total of 6,500) towns and villages were destroyed (Nessou, 2009, p. 204). After the defeat of Rommel in El Alamein and the Italian armistice with the allied forces, the Italian-occupied zone of Greece was handed over to the Germans in

6 September 1943. The Italian occupying forces had been notably lax in their attempts to subdue local partisan groups (“andartes”). Following the German take-over, conflict between guerrilla groups (mostly the Communist-led ELAS) and the Wehrmacht inten- sified. An upsurge of terror tactics employed by the occupying forces followed. Partisan attacks were often followed by indiscriminate shootings of civilians and the destruction of every village in a certain radius from the attack. For example, the town of Mousi- otitsa in the northwestern part of Greece had 153 of its inhabitants killed, including women and children, on July 25th 1943. Another 15 other localities in the area were destroyed by the Germans (Nessou, 2009). The massacre was part of a mopping-up operation in response to the killing of a German officer in the town of Zita. Similarly, the entire male population of the town of Kalavryta in the Peloponnese was shot, along with inhabitants of several neighboring towns, for a total number of 696 dead, after guerrillas abducted and killed soldiers of the 117 Jaeger Division in October 1943. One of the last massacres of civilians before the end of the occupation occurred in Distomo, near Delphi. In total, 218 people, including infants, were killed by the Waffen-SS on June 10th 1944. Post-war reports of the Ministry of Reconstruction estimate the total number of dead in Greece due to reprisal measures at 30,000 (Doxiadis, 1947). Memories of Nazi massacres during the occupation are far from erased in Greece today. Family members of the victims of Distomo have tried to claim reparations, taking their case to the German courts and to the International Court of Human Rights. Despite the fact that the Constitutional Court in Germany dismissed the case in 2003, it was recently revived when an Italian court awarded the descendents of the victims property belonging to a German NGO in Italy. The case reached the International Court in 2012 in the middle of the Greek sovereign crisis, and featured prominently in the Greek press.4.

4“The government in the Hague for Distomo”, Kathimerini, 13 January 2011, http://news. kathimerini.gr/4dcgi/_w_articles_politics_2_13/01/2011_428531

7 Data on towns that suffered reprisal measures by the Wehrmacht during the German occupation of Greece come from Presidential Decrees no. 2130 (1993), 399 (1998), 99 (2000), 40 (2004) and 140 (2005). These decrees designate a number of municipalities and communes throughout the country as “martyred towns”. Localities that fall in this category were determined - by a committee created in 1997 by the Ministry of Internal Affairs and Public Administration - to have suffered material and human losses in the period 1941-1944 that fullfill one of the following criteria:

1. Complete destruction of housing stock by arson, bombings or explosions.

2. Loss of 10% of the period’s total population by individual or mass executions, as well as by other causes, e.g. blind shootings of civilians.

3. Destruction of housing stock that approaches 80% of the total and loss of population that approaches 10% of the total, also taking into account the absolute magnitudes of the losses.

This list of locations includes a total of 72 towns, from which we exclude the following: Doxato, Drama, Choristi (under Bulgarian occupation and destroyed by the Bulgarians) and Domeniko, Tsaritsani, Nea Agchialos (destroyed by the Italians). Fig- ure 2 depicts the regional distribution of affected localities. All places on the list of martyred towns suffered due to German reprisals; they were not destroyed by bombing during the war or during the invasion. 54 out of 72 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, 2009). Since data on car registrations, our main dependent variable, are not available at a level of aggregation finer than the prefecture, we construct a prefecture-level index of exposure to German reprisals, in the form of the share of the prefecture’s total population in 1940 that lived in “martyred” localities.

8 2.2 German-Greek relations during the Greek crisis

The Greek sovereign debt crisis began to unfold in late 2009, when revised budget deficit figures revealed the country’s dire financial situation. This lead to successive downgrades of its credit rating. Eventually, with debt markets all but closed to the Greek state, an EU bailout became inevitable. From the beginning, the German government was sceptical of a financial rescue for Greece.5 It finally agreed to the bailout in exchange for harsh austerity measures. From the onset of the crisis, Greek public opinion saw Germany as the instigator of foreign-imposed austerity. The reaction was immediate and intense: In February 2010, the Greek Consumers Association called for a boycott on German products - explicitly highlighting the importance of cars - and instructed consumers on how to identify German manufacturers by the products’ barcode. Animosity was further aggravated by incendiary articles in the popular press. Ger- man newspapers routinely portrayed Greeks as notorious and lazy cheaters living it up at the expense of the German taxpayer.6 A German weekly featured Aphrodite making a rude gesture on the cover page; German populist politicians suggested that Greece should sell some of its islands to repay its debts.7 As the Greek economy contracted and unemployment surged amid severe austerity measures, anti-German feelings in Greece deepened. Greek politicians openly referred to the German special envoy as a “military commander”. In early 2012, Greek president Karolos Papoulias publicly complained that the entire country was being insulted by the German finance minister Wolfgang Schaeuble. During the 2012 visit of German chancellor Angela Merkel to Athens, thou- sands of people demonstrated in the streets of Athens. Much of the criticism of German policy in Greece after 2010 used references to the

5“German “no” to facilitating the repayment of the 110 billion euros”, Kathimerini, 13 October 2010 6“Die Griechendland-Pleite”, Focus Magazine, Nr. 8, 2010. 7“Verkauft doch eure Inseln, ihr Pleite-Griechen”, Bild, 27 October 2010

9 events of World War II, and employed Nazi-era symbols to protest against the way Greece was being treated. Mentions of war crimes and unpaid German reparations became much more frequent in the press. Populist politician fed the frenzy: Former foreign minister Stavros Dimas, addressing the Greek parliament in March 2011, stated that Greece never waived its right to claim reparations and the repayment of the loan that Germany forced on it during Nazi occupation.8 Protesters often carried placards of Angela Merkel in Nazi uniform; popular newspapers would print swastikas surrounded by the stars of the European union to symbolize that EU policy was similarly harsh as Nazi occupation. An article by the English Daily Telegraph illustrates the way in which past conflict suddenly came to matter for Greeks after the start of the debt crisis. In the issue of February 11, 2012, the Telegraph profiled the life of Eleftherios Basdekis, who spent his “entire life beneath a German cloud”. A survivor of the Distomo massacre, he eventually build a successful trucking business, which went bankrupt after the start of the crisis. The article also cited a mother from Distomo saying that she “hated Germany”, that Angela Merkel was “a monster”, and that the Germans “killed Distomo; they stole our gold; they belittle Greece.” A bar owner is quoted as saying “five years ago, no one had any problem with Germany. But now people are getting upset. The Germans say we are lazy, which is not fair”. As the Telegraph article illustrates, hatred of Germans suddenly resurfaced after the outbreak of the debt crisis. In addition, Greeks from towns destroyed after 1941 often interpreted recent acrimony in the light of earlier war crimes. Our hypothesis is that the persistence of collective memories of the German occupation is stronger in areas of Greece that actually fell victim to German atrocities and that the revival of these memories during specific conflict events manifests itself through consumer decisions.

8“The issue of German reparations is open but...”, Kathimerini, 28 March 2012, http://www. kathimerini.com.cy/index.php?pageaction=kat&modid=1&artid=83628&show=Y

10 In order to identify months of heightened conflict in German-Greek relations during the euro crisis, we use information from Lexis-Nexis and Google Insights. Figure 3 shows the frequency of the co-ocurrence of the words “anti-German” and “Greece” in international news media. For the years before 2009, the word pair is virtually inexistent. Thereafter, the frequency count increases sharply, reaching peaks in 2010 and 2011. To obtain a high-frequency measure of perceived German-Greek conflict within Greece, we use data on web searches from Google Insight. Here, we use the number of terms related to the crisis in Greece and the particular role that Germany played in it. For a given search term, the frequency index provided by Google Insights is a normalization of the share of total searches represented by the term in a given time and region.9 We use this index to construct a measure of public interest in German-Greek related issues, based on the following searches - in Greek and from computers whose IP identifies them as located in Greece - for the following terms: “Germans”, “German reparations”, “Distomo”, “Merkel”, “Schäuble”,“Rösler”,“troika”, “firings”, “cuts”, “haircut”, “measures”, “memorandum”. These search terms were selected on the basis of their frequency of appearance in the headlines of Greek newspapers and their general association to issues that posed a source for tension in German-Greek relations during the period 2008-2012. It is surprising that the vague term “Germans” first appears with a non-zero value in the Google index in February 2010, exactly the month when the first austerity measures were announced and the consumer boycott started. The volume of Google hits on the names of German politicians, like chancellor Angela Merkel and Minister of Finance Wolfgang Schäuble jumps discretely in early 2011. In the case of Vice-Chancellor Philipp Röslerit takes on non-zero values in two instances: His visit to Athens in October 2011 and in March 2012,

9Only terms with hits above a certain threshold are considered for the construction of the index. As a result, the index often takes on the value 0 when the search volume for a term is low.

11 when the Greek Ministry for Development issued an official announcement accusing him of “systematically undermining” Greece’s effort to recover.10 The term “memorandum” refers to the various memoranda signed between Greece and the EU/IMF, with which Greece agreed to economic policy conditionality in return for financial help. Though not strictly a term referring to German-Greek relations (like the terms “troika”, “firings”, “cuts”, “haircut” and “measures”) it is related to the general public annoyance caused by the demands for austerity made of Greece during the crisis, which were perceived as primarily German demands, pushed by the German government and voiced by German politicians. For each of the above terms we exctract a monthly search index from Google for the period 2008-2012. The value of the index is practically zero until the second half of 2009. We compute deviations from the mean for each of these series and take first differences. We then sum up the resulting series and end up with an index for the evolution of growth of the popularity of the combined search terms. We identify conflict months based on turning points of the above series. The criterion for identifying a month as a turning point is for it to be a local maximum in the quarter

(yt > yt−1 and yt > yt+1) and to be larger that one standard deviation. The turning points resulting from this procedure are depicted in Figure 4. February 2010 is the obvious ﬁrst big event, followed by a series of turning points coinciding with major episodes in the Greek debt crisis. Several of the event-months are characteristically German-focused, like October 2010, when Germany led the EU summit that decided on Greece’s bailout, by insisting on harsh conditionality and even suggesting that indebted countries be stripped of their voting rights in the future.11 The largest peak in the series is February 2012, a month especially conducive to agitated Greek nationalist feeling, which saw both the dismissal of Greek claims for German war crime reparations in

10“Scatter bomb of Chrisochoidis against R¨osler”,To Vima, 1 March 2012, http://www.tovima. gr/politics/article/?aid=446212 11“EU Agrees to Merkel’s Controversial Euro Reforms”, Spiegel, 29 October 2010

12 the International Court of the Hague and the press statement of the Greek president that he cannot accept insults to his country from Mr. Schäuble.12 In this month, the Google search index for the term “Schäuble”takes on its maximum value. Table 2 offers a summary of the main events coinciding with our identified months of conflict.

2.3 Passenger vehicle registrations

In Greece, the Ministry of Transport and Communications collects data on registrations of new passenger vehicles. These are disseminated by the Hellenic Statistical Authority (HelStat). We have access to monthly information on the number of new passenger vehicles registered in each prefecture for the period from January 2008 to October 2012, by manufacturing plant. The raw data does not contain information on the brand of a registered vehicle. HelStat provides a correspondence list that allows the matching of production plants to car manufacturers. This correspondence does not always distinguish between diﬀerent car brands produced by the same manufacturer. This is especially true in the case of the Daimler group, producer of both Smart and Mercedes vehicles, and for the Fiat group, which also produces Alfa Romeo and Lancia. Despite this issue, we are able to distinguish German from non-German brands in our sample; the former include Volkswagen, Opel, Audi, BMW, Porsche and the brands of the Daimler group.13 For our purposes, a car’s “nationality” is not determined by ultimate ownership of the company, but the place of manufacture of (most) cars. In this sense, we count Seat as a Spanish car maker despite the fact that it is owned by Volkswagen. Summary statistics for the monthly sales of the brands in our sample are given in Table 1. Toyota is the brand with the highest average sales number, followed by Opel

12“Greek president attacks German minister’s insults”, Reuters, 15 February 2012, http://www. reuters.com/article/2012/02/15/us-greece-germany-idUSTRE81E1VK20120215 13Data on vehicle registrations are available from January 2004 on, but we are unable to distinguish German brands in the earlier sample, due to the fact that Daimler was also owner and producer of Chryslers.

13 and Volkswagen. At the opposite end of the spectrum are small luxury car makers such as Ferrari and Maserati, with average sales of only one car per month. To compare like with like, our sample does not include small manufacturers with less than 10 vehicle sales in the total period 2008-2012. Aggregate car sales slumped after the start of the financial crisis. Annual unit sales had totalled close to 180,000 before 2007. By 2011, as the Greek economy contracted at a rapid pace, car sales had fallen to barely 60,000 per annum, a decline by two- thirds within four years. Analysing sales trends of cars in Greece is complicated by the fact that German car manufacturers performed strongly over the last decade. World- wide, the share of German brands has been rising. This partly reflects the recovery of Volkswagen sales and the significant decline in Toyota’s market share.14 Figure 5 compares the share of German cars in the Greek car market with that in the European market overall. The broad trends are very similar. Figure 6 separately depicts the evolution of total car registrations in the period 2008- 2012 in prefectures with and without a history of German reprisals. When excluding Attica, the most populous prefecture and home to the capital Athens, affected and non-affected prefectures show a high degree of co-movement in terms of total vehicles registered. Total registrations are on a downward trend, particularly steep after mid- 2009, which seems to stabilize after 2011. To deal with the fact that many German cars are luxury products – which may have suffered greater declines in sales as a result of the crisis – we will perform part of our empirical analysis for the “Volkswagen category” only – a group of brands that focuses on the production of small family cars (or compact vehicles). This category includes the following brands: Volkswagen, Opel, Citroen, Ford, Honda, Hyundai, Nissan, Peugeot, Renault, Seat, Skoda, Toyota.15

14“VW conquers the world”, The Economist, 7 July 2012, http://www.economist.com/node/ 21558269 15Including other brands to this category (Daewoo, Daihatsu, Isuzu, Kia, Mitsubishi, Subary, Audi)

14 2.4 Control variables and balancedness

Control variables are taken from the 2001 Greek Census and include population, share employed in agriculture, share employed in industry, share with higher education, share with secondary education, and unemployment rate. The 2001 controls do not account for the differential economic reaction of prefectures during the crisis. Unfortunately, variables like the yearly unemployment rate are not available at the prefecture level for the years 2011-2012, in which most of the conflict events take place. To mitigate the crisis effect and to control for prefecture-specific time-varying unobservable factors , we extend our empirical specification to include prefecture-specific fixed effects (prefecture- year interactions). Table 3 reports descriptive statistics for the main prefecture-level controls used in the empirical analysis. Prefectures are generally balanced with respect to observables. With the exception of a higher share of population with secondary education, the economic structure and current and historic population does not significantly differ by reprisal status.

3 Empirical analysis

In this section, we present our main empirical result - the dramatic decline in German car sales in Greek prefectures aﬀected by German massacres relative to sales in other areas during the German-Greek crisis after 2010. This result holds under OLS and when we employ geographical matching. In addition, we show that the results for an IV exercise that instruments for the prevalence of German reprisals.

does not signiﬁcantly alter the results.

15 3.1 Baseline results

We begin with a simple example, comparing three neighboring areas. The prefecture of Achaia, home to the martyred town of Kalavryta, saw 2% of its 1940 population killed or made homeless by German retribution measures. During months of German-Greek conflict in the period 2008-2012, it showed an average drop of 1.5 percentage points in the share of German cars registrations in the Volkswagen category. In contrast, the neighboring prefectures of Korinthia and Aitoloakarnania - not affected by German reprisals – experienced increases of 7.6 and 9.6 percentage points respectively. How general are these differences? As a first step, we perform a difference-in- differences tabulation of the effect of a conflict month on German brand sales. Table 4 presents the basic result. In an average month of German-Greek conflict, prefectures that witnessed German massacres after 1941 experienced a decline in the share of German cars of 3.2 percentage points. In contrast, prefectures that had seen no reprisals experienced a small increase in the share of German cars sold – a plus of 1.1 percentage points. The overall treatment effect is 4.3 percentage points – a large change in the market share of German cars within a single month, equivalent to more than a 12% reduction relative to the pre-crisis level in prefectures with reprisals. In Figure 7, we plot the density of the difference-in-differences in “normal” months and months following a month of conflict. We take the monthly average of log(cars) in reprisal and non-reprisal prefectures, for German and non-German brands in the Volkswagen category and compute:16

[yg − yng]r − [yg − yng]nr

where {g, ng} stand for German and non-German brands and {r, nr} for ‘reprisal’ and ‘non-reprisal’ prefectures respectively. The dotted line represents the density of

16To account for seasonality, we express these ﬁgures as the diﬀerence from their value 12 months earlier.

16 the Diff-in-Diff in months without conflict, and the solid line shows the distribution during months of public antagonism. There is a clear shift of the distribution to the left, indicating a relative drop in the sales of German brands in prefectures affected by reprisals during months of conflict. More formally, we examine the differential effect of an event month on the market share of German brands by estimating the following specification:

yjt = α + λt + β1Ct−1 + β2Dj + γCt−1 ∗ Dj + Xjδ + jt (1)

where yjt is the share of vehicles of German manufacturers registered in prefecture

17 j at time t, λt are year fixed effects, Ct−1 is a dummy for a conflict month, Dj is the share of the prefecture’s 1940 population that lived in towns affected by German reprisals, and Xj is a vector of prefecture controls. The empirical model amounts to a difference-in-differences strategy, comparing the share of German brands between prefectures with and without a past history of German reprisals, in months following a month of conflict relative to months without a conflict event. The only difference from classical DID, is that the treatment variable Dj is not a dummy, but a continuous index proxying for exposure to reprisals. We are interested in the sign and magnitude of the interaction coefficient γ. The baseline estimate of (1) is reported in the first column of Table 5, panel A. The share of German brands seems to increase after months of tension in German-Greek relations. This is true in all prefectures and could be attributed to the fact that all car sales react negatively to event months, since these reflect general developments in the Greek crisis and capture more than just a surge in anti-German feeling. The result might not be so surprising considering that the sample in Panel A of Table 5 includes luxury vehicles. If sales of these fall less as a response to crisis events, the German

17Because of delays between purchasing decisions and car registration, we lag this variable by one period.

17 share of total sales could increase, as most German cars fall in the luxury category. Despite the above, there is always a statistically significant difference between reprisal and non-reprisal prefectures. Prefectures with a higher share of population affected by reprisals register relatively more German cars in normal times, but not so in months following a month of conflict. The magnitude of the interaction coefficient γ implies that a conflict month is correlated with a German car share that is lower by 1.14 percentage points in reprisal prefectures relative to non-reprisal ones. This difference corresponds to approximately 4.6% of the average market share of German brands in the period 2008-2012, an economically significant drop, particularly for a durable good such as cars. In columns (2) and (3) we include prefecture fixed effects and prefecture-specific time trends respectively. The interaction coefficient remains significant and increases in magnitude. In columns (4)-(6), we restrict the sample to the years after the onset of the Greek sovereign default crisis, in which all our episodes of German-Greek tension take place. The direction of the results remains unchanged and the coefficients become slightly larger. Panel B of Table 5 repeats the exercise for cars in the Volkswagen category. This again shows a significant negative interaction effect between the share of the population in reprisal prefectures and months of conflict. In contrast to the above panel, there is no significantly positive effect of a conflict month on the German market share in non- reprisal prefectures. As before, the results are not affected by controlling for prefecture or fixed-effects or prefecture-year interactions. Instead of imposing various assumptions underlying the OLS procedure such as linearity, we also use geographical matching to examine the effect of German-Greek conflict. Every prefecture that experienced German massacres is matched to the two nearest prefectures that did not suffer reprisals. We then take the difference in the share of German cars in total sales between the affected and the unaffected provinces. By matching on geographical proximity, we hope to account for unobserved heterogeneity.

18 3.2 Robustness

The German share of registered vehicles is an informative measure, but its movements are affected by both the denominator and the numerator. In order to capture sales of German vehicles directly - without imposing the expectation that all other countries’ vehicle sales should move in lockstep - we use a triple-difference specification of the form:

log(yijt) =α + λt + β1Ct−1 + β2Dj + β3Gi + γ1Ct−1 ∗ Dj + γ2Ct−1 ∗ Gi

+ γ3Dj ∗ Gi + δ(Ct−1 ∗ Dj ∗ Gi) + Xjπ + ijt

where yijt is the number of vehicles of brand i registered at prefecture j in month

18 t, Dj is the share of the prefectures 1940 population that lived in towns aﬀected by

German reprisals and Gi is a dummy for a German brand. The coefficient δ measures the effect of a conflict month on the gap between German and non-German cars registered in reprisal locations relative to non-reprisal ones. With this specification, we are able to control for unobservable factors that are constant over time and influence car sales differentially in prefectures with a different share of population affected by reprisals, as well as for factors that have a differential influence on German vs non-German car sales. We continue to report specifications controlling for prefecture-specific fixed effects; any confounding factor would have to be a brand-prefecture-specific unobservable that changes on months of conflict. Results are reported in Table 6, for all brands and for the restricted sample of the Volkswagen category. In both cases, German brands register significantly more cars on average. They also seem to be less elastic to conflict episodes: following an event

18 In practice, we use log(yijt + 1) as a dependent variable, in order to deal with the problem of zeros in many prefecture-month-brand cells.

19 month, all car registrations fall, but German brand ones less so. This accounts for the increase in the German market share after conflict months that was reported in Table 5. What is more important, a higher share of population affected by reprisals leads to a smaller reaction of car sales to conflict events. Furthermore, this reaction, or decrease in total car registrations in reprisal prefectures, seems to be accounted for to a larger extent by a drop in German cars. According to the triple interaction coefficient estimated in column (1) and account- ing for average registrations by prefecture reprisal status, an event month signifies an average reduction of 335 cars in reprisal prefectures, 85 of which, or approximately 25%, are German cars. In non-reprisal prefectures only 18% of the total drop - or 179 out of 968 cars - is represented by German brands. The triple difference coefficient decreases slightly when looking at the years 2010-2012 and more so when restricting the sample to the Volkswagen category, but it remains always significant and negative. Despite the fact that conflict episodes are not associated with particular months, there remains the possibility that event months capture the seasonality of car sales. To account for any seasonal registration pattern and as a robustness check, we replace the dependent variable with the residuals of a regression of the log of registered vehicles at prefecture j in month t on month, prefecture and brand dummies and their interactions. In this way we allow for a seasonality pattern that varies by prefecture and brand, though results remain unaffected if we control for seasonality common to all brands and prefectures or all brands within a prefecture. Results are reported in Table 7 - the coefficient of interest δ remains practically unaffected.

4 Discussion

The idea that the (collective) recall of memories can act as a powerful determinant of behavior has a long lineage in psychology, history, and economics. The Roman historian Tacitus famously argued that the “the principal oﬃce of history [is] this: to preserve the memory of virtuous actions, and to prevent evil words and deeds by instilling the

20 fear of an infamous reputation with posterity.” History as collective memory, in other words, serves a utilitarian function – to make people more virtuous. The organised recollection of past events can have other functions as well. An influential school of thought in cultural history traces its roots to the work of Pierre Nora, who analysed how lieux de mémoire (“sites of memory”) acquire their significance. Sites of memory in this approach include physical sites of memory, such as statues, archives, museums, palaces, plus rituals and commemorative practices (such as feasts and celebrations) and physical objects (such as sacred texts). Lieux de mémoire bring the past into everyday life by recalling historical events.19. As such, sites of memory are by definition ”constructed”, reflecting the interests of those who perpetuated the celebration of a particular past event. In economics, much of the focus has been on limitations of individual memory as a limiting factor of optimizing behavior. Becker (1993) considered it as such in his Nobel lecture. Recent work uses imperfect recall as an explanation for various phenomena in behavioral economics, including over- and underreactions to news. Theories of limited rationality offer one way to explain our findings. Faced with sudden conflict, individuals typically search for modes of interpretation that reduce cognitive dissonance. For example, with limited cognitive resources, not all historical examples and precedents will be present in everyones consciousness all the time it takes specific events for them to “come to mind” (Gennaioli and Shleifer, 2010). In the work by Gennaioli and Shleifer, dormant beliefs and preferences can be activated by salient events. Once activated, the “mental matrix”, determined by the sum total of attitudes and beliefs transmitted by parents and friends, contains seemingly convincing explanations that can be used to shed light on puzzling events: Greeks who feel their country is suddenly being punished unfairly by austerity-minded German politicians

19“A lieu de m´emoireis any signiﬁcant entity, whether material or non-material in nature, which by dint of human will or the work of time has become a symbolic element of the memorial heritage of any community” (Nora, 1996)

21 remember tales of German atrocities during World War II and related beliefs about the “German national character”. Such memories can be activated more readily in areas where ancestors had ﬁrst-hand experience of massacres such as geographical areas most exposed to German reprisals.

5 Conclusions

Countries that often went to war with each other in the past still trade less. How does a history of conflict affect consumer behavior? One possibility is that general cultural differences make it more likely that countries go to war, and that they trade less with each other.20 The second possibility is that current events are interpreted through the lens of past experiences, making insults and transgression seem all the more outrageous. Our study shows that boycotts can be effective, and that consumer behavior re- acts particularly sharply in those areas where contemporary conflict sparks memories of earlier misdeeds. We examine the case of Greece after the outbreak of the debt crisis in 2010. Forced to borrow from EU partners, the country had to implement severe austerity measures which led to massive unrest. Many of the policies implemented in exchange for the EU bailout packages were blamed on German policies. Public spats between German and Greek politicians deepened the impression of deeply-rooted an- tagonisms. The Greek public, when protesting, freely used Nazi-era symbols to express its outrage about German demands for more spending cuts and the perceived unfairness of the conditions imposed on Greece. These events affected consumer behavior in Greece. German car sales suffered in months of conflict, but in a differential way. Most affected were areas where German occupying forces during World War II had committed massacres. Prefectures where no major war crimes had been committed saw much smaller declines in car sales. This

20Spolaore and Wacziarg (2009) argue that genetically close populations fight each other more often. This would contradict our intuition if genetic differences translated directly into cultural differences.

22 strongly suggests that public conflict matters for economic behavior in part when it revives latent hatreds, reflecting an earlier history of conflict. It also helps to rationalize why empirical evidence on the effectiveness of boycotts has been mixed. Large effects should mainly be expected where contemporary events trigger memories with earlier events – as was the case with French automobile sales in China (reviving memories of the humiliation of China at the hands of Western powers) and with Sino-Japanese conflict (recalling the war crimes committed by Japan’s armed forces during the invasion of China in the 1930s).

23 References

Algan, Y. and Cahuc, P. (2010). Inherited Trust and Growth. American Economic Review, 100 (5), 2060–92.

Ashenfelter, O., Ciccarella, S. and Shatz, H. J. (2007). French Wine and the U.S. Boycott of 2003: Does Politics Really Aﬀect Commerce? Working Paper 13258, NBER.

Becker, G. S. (1993). Nobel Lecture: The Economic Way of Looking at Behavior. Journal of Political Economy, pp. 385–409.

Chaney, E. (2008). Tolerance, Religious Competition and the Rise and Fall of Muslim Science. mimeo, Harvard University.

Chavis, L. and Leslie, P. (2006). Consumer Boycotts: The Impact of the Iraq War on French Wine sales in the U.S. Working Paper 11981, NBER.

Doxiadis, C. (1947). Thysies tis Ellados: Aitimata kai Epanorthoseis ston B’ Pagos- mio Polemo. Report 19, Hellenic Ministry of Reconstruction, Athens.

Fernandez,´ R. and Fogli, A. (2006). Fertility: The Role of Culture and Family Experience. Journal of the European Economic Association, 4 (2-3), 552–561.

Fernandez-Villaverde,´ J., Greenwood, J. and Guner, N. (2011). From Shame to Game in One Hundred Years: The Rise in Premarital Sex and its Destigmitization. Discussion Paper 8667, CEPR.

Fisman, R., Hamao, Y. and Yongxiang, W. (2012). The Impact of Cultural Aver- sion on Economic Exchange: Evidence from Shocks to Sino-Japanese Relations, working Paper.

Gennaioli, N. and Shleifer, A. (2010). What Comes to Mind. The Quarterly Jour- nal of Economics, 125 (4), 1399–1433.

Guiso, L., Sapienza, P. and Zingales, L. (2007). Social Capital as Good Culture. Working Paper 13712, NBER.

—, — and — (2009). Cultural Biases in Economic Exchange? The Quarterly Journal of Economics, 124 (3), 1095–1131.

Hionidou, V. (2006). Famine and Death in Occupied Greece, 1941-1944. Cambridge: Cambridge University Press.

Hong, C., Hu, W.-M., Prieger, J. E. and Zhu, D. (2011). French Automobiles and the Chinese Boycotts of 2008: Politics Really Does Aﬀect Commerce. The B.E. Journal of Economic Analysis & Policy, 11 (1), 26.

John, A. and Klein, J. (2003). The Boycott Puzzle: Consumer Motivations for Purchase Sacriﬁce. Management Science, 49 (9), 1196–1209.

24 Koku, P. S., Akhigbe, A. and Springer, T. M. (1997). The Financial Impact of Boycotts and Threats of Boycott. Journal of Business Research, 40 (1), 15–20.

Mazower, M. (1995). Inside Hitler’s Greece: The Experience of Occupation, 1941- 1944. New Haven and London: Yale University Press.

Meyer, H. F. (2002). Von Wien nach Kalavryta. Die blutige Spur der 117. J¨ager- Division durch Serbien und Griechenland. Mannheim: Peleus.

Michaels, G. and Zhi, X. (2010). Freedom Fries. American Economic Journal: Ap- plied Economics, 2 (3), 256–81.

Nessou, A. (2009). Deutsche Besatzungspolitik und Verbrechen gegen die Zivil- bev¨olkerung- eine Beurteilung nach dem Volkerrecht. G¨ottingen: Vandenhoeck & Ruprecht.

Nora, P. (1996). From Lieux de M´emoireto Realms of Memory. In P. Nora and L. D.Kritzman (eds.), Realms of Memory: Rethinking the French Past. Vol. 1: Con- ﬂicts and Divisions., XV-XXIV, New York and Chichester: Columbia University Press.

Nunn, N. and Wantchekon, L. (2011). The Slave Trade and the Origins of Mistrust in Africa. American Economic Review, 101 (7), 3221–52.

Pandya, S. and Venkatesan, R. (2012). French Roast: International Conﬂict and Consumer Boycotts – Evidence from Supermarket Scanner Data.

Teoh, S. H., Welch, I. and Wazzan, C. P. (1999). The Eﬀect of Socially Activist Investment Policies on the Financial Markets: Evidence from the South African Boycott. The Journal of Business, 72 (1), 35–89.

Voigtlander,¨ N. and Voth, H.-J. (2012). Persecution Perpetuated: The Medieval Origins of Anti-Semitic Violence in Nazi Germany. The Quarterly Journal of Eco- nomics, 127 (3), 1339–1392.

25 A Tables and Figures

Figure 1: Occupation zones of Greece mapped to modern-day prefectures

Source: 512 Field Survey Company, Royal Engineers, 1943.

26 Figure 2: Map of towns that suﬀered reprisals by German occupying forces, 1941-1944

Notes: “Martyred towns” as characterized by presidential decrees no. 399 (1998), 99 (2000), 40 (2004) and 140 (2005). Population data from 1940 Greek Census.

27 Figure 3: Number of international news articles referring to German-Greek conﬂict 50 40 30 20 Number of articles 10 0 Jul 2007 Jan 2009 Jul 2010 Jan 2012 Jul 2013 Date

Notes: Number of international newspaper articles in English that mention the words “anti-German” and “Greece”. Source: Lexis Nexis.

28 Figure 4: Evolution of popularity of Google search terms related to German-Greek relations, searched from the Greek web 300 200 100 0 Google search index −100 −200

Jan 2009 Jan 2010 Jan 2011 Jan 2012 Jan 2013 Date

Notes: The blue line is the sum of first differences of the demeaned time series of the Google Trends search index for the following search terms - in Greek: “Germans”, “German reparations”, “distomo”, “merkel”, “schäuble”,“rösler”,“troika”, “firings”, “cuts”, “haircut”, “measures”, “memorandum”. The vertical reference lines indicate the turning points in the series that we identify as event months.

29 Figure 5: Share of German brands, Greece vs Western Europe

All brands Volkswagen category .4 .4 .35 .35 .3 .3 Share German brands .25 .25 .2 .2 2008 2009 2010 2011 2012 2008 2009 2010 2011 2012

Greece Western Europe

Notes: Western Europe includes Austria, Belgium, Denmark, Finland, France, Greece, Germany, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain, Sweden, the UK, Iceland, Norway and Switzerland. Source: Hel.Stat. and Association Auxiliaire de l’Automobile (AAA).

30 Figure 6: Evolution of total car registrations 20000 15000 10000 Total car registrations 5000 0

Jan 2008 Jan 2009 Jan 2010 Jan 2011 Jan 2012 Date

Non−reprisal prefectures excluding Attica Reprisal prefectures

Non−reprisal prefectures including Attica

Notes: The ﬁgure depicts the total number of passenger vehicle registrations in Greece for the period 2008-2012. Reprisal prefectures are those that have at least one “martyred” town. The dashed blue line is the time series of car registrations in the non-reprisal prefectures, excluding Attica, the prefecture in which Athens is situated.

31 Figure 7: Kernel density of diﬀerence in diﬀerences 4 2 Density 0

−.4 −.2 0 .2 Difference in differences

Months after event month Other months

Notes: The graph depicts the kernel density of the difference in differences of German vs non-German car sales in the Volkswagen category in reprisal vs non-reprisal prefectures: [yg − yng]r − [yg − yng]nr. yi∈{g,ng} is the average of log(cars + 1) for German and non-German cars in reprisal and non-reprisal prefectures, expressed as the difference from its value in the previous year, in order to account for seasonal sales patterns. The solid line is the average density in months right after an event month. The dashed line is the average density in all other months. Reprisal prefectures are those that have at least one “martyred” town.

32 Figure 8: Marginal eﬀect of a conﬂict month on the share of German brand sales

Notes: Estimated marginal eﬀect and 95% conﬁdence interval from OLS regressions in Table 5, Column (1) of Panel B.

33 Table 1: Average montly car sales in Greece

Manufacturer Mean St. dev. Min Max AUDI 389 277 99 1543 BMW 455 318 90 1334 BENTLEY 1 1 0 5 CHANG’AN 3 3 0 15 CHEVROLET 230 188 5 698 CHRYSLER 91 94 0 361 CITROEN 493 296 87 1358 DACIA 41 30 0 99 DAIHATSU 243 232 4 783 DAIMLER 645 472 51 1785 FERRARI 1 2 0 7 FIATa 953 488 269 2513 FORD 897 506 216 2087 GENERAL MOTORS 25 32 0 129 HONDA 281 232 36 1025 HYUNDAI 841 625 133 2524 JAGUAR 7 11 0 48 JIANGLING 0 0 0 2 KIA 332 285 33 1636 LADA 10 13 0 52 LAMBORGHINI 0 1 0 3 LAND ROVER 15 20 0 79 LOTUS 0 1 0 2 MASERATI 1 1 0 4 MAZDA 285 311 2 1081 MITSUBISHI 221 169 25 675 NISSAN 685 444 86 1998 OPEL 1202 613 384 2806 PEUGEOT 504 335 97 1319 PORSCHE 19 19 0 67 RENAULT 215 136 65 723 SAAB 36 40 0 194 SEAT 423 308 45 1227 SHUANGHUAN AUTO 4 5 0 18 SKODA 511 294 138 1439 SSANGYONG 10 13 0 57 SUBARU 71 66 0 251 SUZUKI 695 532 91 1896 TOYOTA 1452 888 284 3909 VOLKSWAGEN 1182 622 220 2436 VOLVO 136 73 30 319 a Includes Alfa Romeo and Lancia. Source: Hel.Stat. Data for the period January 2008 to August 2012. 34 Table 2: Chronology of Greek crisis and turning point identiﬁcation

Date Event description

February 2010 Deal with EU/ECB/IMF on bailout and ﬁrst austerity package Cover of Focus magazine with title “Cheaters in the Euro-family” dis- plays Aphrodite of Milos making rude gesture Greek Consumer Association calls consumers to boycott German products May 2010 Greece announces series of austerity measures National strikes and large-scale protests in the center of Athens October 2010 Germany refuses time extension for repayment of Greek loans Brussels EU summit sees acceptance of German-engineered new bailout mechanism Merkel-Sarkozy suggestion that indebted countries are stripped of voting rights causes angry responses from Greek politicians November 2010 Troika arrives to Greece in order to ensure implementation of measures voted in May 2010 January 2011 Case of German reparations for WWII crimes on trial in den Haag New wave of measures focused on labor market reforms starts in view of troika’s visit to Greece May 2011 Troika pushes company privatizations and painful labor reforms Discussions for new round of austerity measures (Midterm plan) Talk of Greece leaving the eurozone in the foreign press, initiated by an article in Spiegel. Merkel comment on “lazy Southerners” at political rally attracts large attention in Greek press September 2011 Eurogroup meeting in Brussels pressures Greece to go through with reforms Greek government implements new measures including ﬁrings and pen- sion cuts German Finance minister says it is the Greeks’ decision whether they want to leave the euro, while FDP members suggest a Greek orderly default October 2011 New austerity package is voted amidst severe rioting 50% “haircut” of Greek debt takes place February 2012 Parliament approves new austerity plan International court rules in favor of Germany in trial regarding WWII reparations Greek President Carolos Papoulias declares “I cannot accept Mr Schaeu- ble insulting my country” May 2012 Month of Greek national elections German ministers remind Greece that measures have to be carried through irrespective of government outcome, if the country wants to remain in the Eurozone 35 Table 3: Summary statistics for Greek prefectures

Variable All Non- Reprisal Diﬀerence reprisal

Population 420542 481133 353823 127309 (1084615) (1385816) (442978) (270851) Share employed in agriculture 0.26 0.28 0.24 0.0326 (0.11) (0.11) (0.10) (0.0300) Share employed in industry 0.23 0.21 0.23 -0.0189 (0.08) (0.05) (0.07) (0.0179) Share higher education 0.11 0.11 0.11 -0.00745 (0.03) (0.02) (0.02) (0.00671) Share secondary education 0.18 0.17 0.19 -0.0212 (0.04) (0.03) (0.03) (0.00854)** Unemployment rate 0.12 0.12 0.13 -0.00705 (0.03) (0.02) (0.03) (0.00880) Population in 1940 146868 147034 146637 397 (177369) (223671) (83881) (45389.1) Percentage of 1940 towns 1.06 2.58 aﬀected (2.17) (2.57) Percentage of 1940 population 1.08 2.63 in aﬀected towns (2.42) (3.21)

N 51 30 21

Source: 2001 and 1940 Greek Census.

36 Table 4: Simple comparison of diﬀerences in the average share of German cars in the VW category

Share of German brands

Conflict months Other months Difference (1) (2) (3) Reprisal prefectures 0.312 0.345 -0.033 Non-reprisal prefectures 0.311 0.300 0.011 Difference 0.002 0.044 -0.042

Sample restricted to 2010-2012. Reprisal prefectures defined as having a share of 1940 population affected by reprisals in the 75th percentile of the distribution of affected prefectures. The Volkswagen category includes the following brands: Volkswagen, Opel, Citroen, Ford, Honda, Hyundai, Nissan, Peugeot, Renault, Seat, Skoda, Toyota.

37 Table 5: OLS estimates using shares of German cars

(1) (2) (3) (4) (5) (6)

Panel A: All brands Share pop. affected 0.00541 0.00546 (0.00422) (0.00546) Lagged conflict month 0.0181∗∗∗ 0.0182∗∗∗ 0.0192∗∗∗ 0.0181∗∗∗ 0.0186∗∗∗ 0.0192∗∗∗ (0.00622) (0.00628) (0.00684) (0.00620) (0.00638) (0.00686) Lagged conflict month* -0.00436∗∗∗ -0.00440∗∗∗ -0.00458∗∗∗ -0.00441∗∗∗ -0.00449∗∗∗ -0.00458∗∗∗ Share pop. affected (0.00105) (0.00107) (0.00159) (0.00150) (0.00152) (0.00160)

Mean share pop. aﬀected in reprisal prefectures 0.0263 Mean share of German cars 0.251 0.251 0.251 0.264 0.264 0.264

Observations 2847 2847 2847 1623 1623 1623 R-squared 0.0531 0.298 0.381 0.0376 0.274 0.335

Panel B: Volkswagen category Share pop. affected 0.00833 0.0105 (0.00515) (0.00699) Lagged conflict month 0.0100 0.0103 0.0139 0.0124 0.0130 0.0139 (0.00907) (0.00905) (0.00930) (0.00904) (0.00905) (0.00933) Lagged conflict month* -0.00374∗∗ -0.00382∗∗ -0.00611∗∗∗ -0.00587∗∗∗ -0.00597∗∗∗ -0.00611∗∗∗ Share pop. affected (0.00158) (0.00159) (0.00186) (0.00182) (0.00182) (0.00186)

Mean share pop. aﬀected in reprisal prefectures 0.0263 Mean share of German cars 0.278 0.278 0.278 0.307 0.307 0.307

Observations 2837 2837 2837 1615 1615 1615 R-squared 0.101 0.298 0.381 0.0545 0.276 0.343

Controls Yes No No Yes No No Prefecture fixed effects No Yes Yes No Yes Yes Prefecture-year fixed effects No No Yes No No Yes Restricted to 2010-2012 No No No Yes Yes Yes

Significance levels: *** p< 0.01, ** p< 0.05, * p< 0.1. Years 2008-2012. Dependent variable is share of German brand passenger vehicles registered in a prefecture in a month. The Volkswagen category includes the following brands: Volkswagen, Opel, Citroen, Ford, Honda, Hyundai, Nissan, Peugeot, Renault, Seat, Skoda, Toyota. All regressions include year fixed effects. Prefecture controls include population, share employed in agriculture, share employed in industry, share with higher education, share with secondary education and unemployment rate, all in 2001. Standard errors are clustered at the prefecture level.

38 Table 6: Robustness: Triple diﬀerences

(1) (2) (3) (4) (5) (6) (7) (8)

Panel A: All brands Share pop. affected -0.00955 -0.00498 (0.0147) (0.0121) Lagged conflict month -0.0508∗∗∗ -0.0508∗∗∗ -0.0451∗∗∗ -0.0451∗∗∗ -0.0502∗∗∗ -0.0502∗∗∗ -0.0502∗∗∗ -0.0502∗∗∗ (0.00797) (0.00798) (0.00475) (0.00475) (0.00522) (0.00522) (0.00522) (0.00523) German brand 0.176∗∗∗ 0.183∗∗∗ 0.183∗∗∗ 0.151∗∗∗ 0.156∗∗∗ 0.156∗∗∗ (0.0433) (0.0433) (0.0434) (0.0426) (0.0426) (0.0427) Lagged conflict month* 0.00706 0.00706 0.00241∗∗ 0.00241∗∗ 0.00197 0.00197 0.00197 0.00197 Share pop. affected (0.00542) (0.00542) (0.00103) (0.00103) (0.00135) (0.00135) (0.00135) (0.00135) Lagged conflict month* 0.0186∗ 0.0186∗ 0.0155 0.0155 0.0423∗∗∗ 0.0423∗∗∗ 0.0423∗∗∗ 0.0423∗∗∗ German brand (0.0104) (0.0104) (0.00996) (0.00996) (0.00843) (0.00844) (0.00844) (0.00844) German brand* -0.00129 0.000315 0.000373 0.00340 -0.00310 -0.00181 -0.00181 0.000469 Share pop. affected (0.00818) (0.00870) (0.00874) (0.00601) (0.00799) (0.00849) (0.00850) (0.00694) Lagged conflict month*German brand* -0.00797∗∗∗ -0.00797∗∗∗ -0.00838∗∗∗ -0.00838∗∗∗ -0.00620∗∗∗ -0.00620∗∗∗ -0.00620∗∗∗ -0.00620∗∗∗ Share pop. affected (0.00250) (0.00250) (0.00246) (0.00246) (0.00171) (0.00171) (0.00171) (0.00171) Observations 119000 119000 119000 119000 68000 68000 68000 68000 R-squared 0.194 0.223 0.229 0.626 0.178 0.203 0.205 0.582

Panel B: Volkswagen category Share pop. affected -0.0251 -0.0168 (0.0289) (0.0249) Lagged conflict month -0.120∗∗∗ -0.120∗∗∗ -0.111∗∗∗ -0.111∗∗∗ -0.0997∗∗∗ -0.0997∗∗∗ -0.0997∗∗∗ -0.0997∗∗∗ (0.0159) (0.0159) (0.0117) (0.0117) (0.0116) (0.0116) (0.0116) (0.0116) German brand 0.571∗∗∗ 0.571∗∗∗ 0.571∗∗∗ 0.639∗∗∗ 0.639∗∗∗ 0.639∗∗∗ (0.0433) (0.0433) (0.0435) (0.0471) (0.0471) (0.0473) Lagged conflict month* 0.0154∗ 0.0154∗ 0.00699∗∗∗ 0.00699∗∗∗ 0.00660∗∗∗ 0.00660∗∗∗ 0.00660∗∗∗ 0.00660∗∗∗ Share pop. affected (0.00810) (0.00810) (0.00208) (0.00208) (0.00199) (0.00199) (0.00200) (0.00200) Lagged conflict month* 0.0778∗∗∗ 0.0778∗∗∗ 0.0778∗∗∗ 0.0778∗∗∗ 0.00974 0.00974 0.00974 0.00974 German brand (0.0266) (0.0267) (0.0267) (0.0267) (0.0264) (0.0264) (0.0265) (0.0265) German brand* 0.0115 0.0115 0.0115 0.0115 0.00912 0.00912 0.00912 0.00912 Share pop. affected (0.0112) (0.0112) (0.0113) (0.0113) (0.0126) (0.0126) (0.0127) (0.0127) Lagged conflict month*German brand* -0.0146∗∗∗ -0.0146∗∗∗ -0.0146∗∗∗ -0.0146∗∗∗ -0.0123∗∗ -0.0123∗∗ -0.0123∗∗ -0.0123∗∗ Share pop. affected (0.00412) (0.00413) (0.00414) (0.00414) (0.00463) (0.00464) (0.00465) (0.00465) Observations 34272 34272 34272 34272 19584 19584 19584 19584 R-squared 0.504 0.604 0.616 0.696 0.488 0.574 0.581 0.661

Controls Yes No No No Yes No No No Prefecture fixed effects No Yes Yes Yes No Yes Yes Yes Prefecture-year fixed effects No No Yes Yes No No Yes Yes Brand fixed effects No No No Yes No No No Yes Restricted to 2010-2012 No No No No Yes Yes Yes Yes

Significance levels: *** p< 0.01, ** p< 0.05, * p< 0.1. Years 2008-2012. Dependent variable is log(cars) and observations are brand-prefecture-month cells. The Volkswagen category includes the following brands: Volkswagen, Opel, Citroen, Ford, Honda, Hyundai, Nissan, Peugeot, Renault, Seat, Skoda, Toyota. All regressions include year fixed effects. Prefecture controls include population, share employed in agriculture, share employed in industry, share with higher education, share with secondary education and unemployment rate, all in 2001. Standard errors clustered at the prefecture level.

39 Table 7: Robustness: Removing seasonality

(1) (2) (3) (4) (5) (6) (7) (8)

Panel A: All brands Share pop. affected -0.000921 0.00365 (0.000744) (0.00240) Lagged conflict month -0.00970 -0.00970 -0.00404 -0.00404 -0.00903∗∗∗ -0.00903∗∗∗ -0.00903∗∗∗ -0.00903∗∗∗ (0.00686) (0.00687) (0.00299) (0.00299) (0.00323) (0.00324) (0.00324) (0.00324) German brand -0.00216 -0.00216 -0.00171 -0.0268∗∗∗ -0.0280∗∗∗ -0.0280∗∗∗ (0.00147) (0.00147) (0.00141) (0.00764) (0.00761) (0.00762) Lagged conflict month* 0.00645 0.00645 0.00182∗∗ 0.00182∗∗ 0.00138 0.00138 0.00138 0.00138 Share pop. affected (0.00521) (0.00521) (0.000881) (0.000881) (0.000906) (0.000906) (0.000907) (0.000907) Lagged conflict month* 0.0151 0.0151 0.0120 0.0120 0.0382∗∗∗ 0.0382∗∗∗ 0.0382∗∗∗ 0.0382∗∗∗ German brand (0.0103) (0.0103) (0.00990) (0.00990) (0.00852) (0.00852) (0.00853) (0.00853) German brand* 0.00115∗∗∗ 0.00115∗∗∗ 0.00121∗∗∗ 0.00121∗∗∗ -0.000594 -0.000939 -0.000939 -0.00170 Share pop. affected (0.000335) (0.000335) (0.000328) (0.000328) (0.00230) (0.00226) (0.00226) (0.00170) Lagged conflict month*German brand* -0.00804∗∗∗ -0.00804∗∗∗ -0.00848∗∗∗ -0.00848∗∗∗ -0.00633∗∗∗ -0.00633∗∗∗ -0.00633∗∗∗ -0.00633∗∗∗ Share pop. affected (0.00234) (0.00234) (0.00230) (0.00230) (0.00172) (0.00172) (0.00172) (0.00172) Observations 119000 119000 119000 119000 68000 68000 68000 68000 R-squared 0.200 0.200 0.223 0.223 0.0866 0.0944 0.104 0.223

Panel B: Volkswagen category Share pop. affected -0.00195∗ 0.00639 (0.00113) (0.00398) Lagged conflict month -0.0400∗∗∗ -0.0400∗∗∗ -0.0309∗∗∗ -0.0309∗∗∗ -0.0202∗∗ -0.0202∗∗ -0.0202∗∗ -0.0202∗∗ (0.0134) (0.0134) (0.00883) (0.00883) (0.00912) (0.00913) (0.00916) (0.00916) German brand -0.0138∗∗∗ -0.0138∗∗∗ -0.0138∗∗∗ 0.0500∗∗∗ 0.0500∗∗∗ 0.0500∗∗∗ (0.00381) (0.00381) (0.00382) (0.0120) (0.0120) (0.0120) Lagged conflict month* 0.0137∗ 0.0137∗ 0.00530∗ 0.00530∗ 0.00491∗ 0.00491∗ 0.00491∗ 0.00491∗ Share pop. affected (0.00792) (0.00792) (0.00276) (0.00276) (0.00287) (0.00287) (0.00288) (0.00288) Lagged conflict month* 0.0966∗∗∗ 0.0966∗∗∗ 0.0966∗∗∗ 0.0966∗∗∗ 0.0328 0.0328 0.0328 0.0328 German brand (0.0266) (0.0267) (0.0267) (0.0267) (0.0264) (0.0264) (0.0265) (0.0265) German brand* 0.00209∗∗∗ 0.00209∗∗∗ 0.00209∗∗∗ 0.00209∗∗∗ -0.000255 -0.000255 -0.000255 -0.000255 Share pop. affected (0.000589) (0.000590) (0.000591) (0.000591) (0.00252) (0.00252) (0.00253) (0.00253) Lagged conflict month*German brand* -0.0146∗∗∗ -0.0146∗∗∗ -0.0146∗∗∗ -0.0146∗∗∗ -0.0123∗∗ -0.0123∗∗ -0.0123∗∗ -0.0123∗∗ Share pop. affected (0.00412) (0.00413) (0.00414) (0.00414) (0.00463) (0.00464) (0.00465) (0.00465) Observations 34272 34272 34272 34272 19584 19584 19584 19584 R-squared 0.359 0.359 0.397 0.397 0.204 0.216 0.241 0.255

Significance levels: *** p< 0.01, ** p< 0.05, * p< 0.1. The dependent variable is the residual of a regression of log(carsijt) on month, prefecture and brand dummies and their interactions. The Volkswagen category includes the following brands: Volkswagen, Opel, Citroen, Ford, Honda, Hyundai, Nissan, Peugeot, Renault, Seat, Skoda, Toyota. All regressions include year fixed effects. Prefecture controls include population, share employed in agriculture, share employed in industry, share with higher education, share with secondary education and unemployment rate, all in 2001. Standard errors clustered at the prefecture level.

40 Table 8: Robustness: Excluding Athens and Crete

Excluding Athens Excluding Crete

(1) (2) (3) (4) (5) (6)

Panel A: All brands Share pop. affected 0.00801∗ 0.0158∗∗∗ (0.00404) (0.00184) Lagged conflict month 0.0185∗∗∗ 0.0186∗∗∗ 0.0196∗∗∗ 0.0166∗∗ 0.0168∗∗ 0.0191∗∗∗ (0.00640) (0.00643) (0.00700) (0.00633) (0.00637) (0.00691) Lagged conflict month* -0.00447∗∗∗ -0.00450∗∗∗ -0.00464∗∗∗ -0.00501∗∗∗ -0.00506∗∗∗ -0.00726∗∗∗ Share pop. affected (0.00108) (0.00109) (0.00160) (0.00159) (0.00163) (0.00143) Observations 2791 2791 2791 2623 2623 2623 R-squared 0.101 0.293 0.375 0.128 0.295 0.379

Panel B: Volkswagen category Share pop. affected 0.0108∗∗ 0.0201∗∗∗ (0.00474) (0.00204) Lagged conflict month 0.0109 0.0112 0.0148 0.00718 0.00759 0.0125 (0.00924) (0.00923) (0.00949) (0.00918) (0.00915) (0.00932) Lagged conflict month* -0.00395∗∗ -0.00403∗∗ -0.00625∗∗∗ -0.00363∗ -0.00374∗ -0.00910∗∗∗ Share pop. affected (0.00160) (0.00161) (0.00186) (0.00208) (0.00212) (0.00198) Observations 2781 2781 2781 2613 2613 2613 R-squared 0.135 0.299 0.381 0.160 0.295 0.381

Controls Yes No No Yes No No Prefecture fixed effects No Yes Yes No Yes Yes Prefecture-year fixed effects No No Yes No No Yes