TheEconomic Costs of Con¯ ict: ACaseStudy of the Basque Country

By ALBERTO ABADIE AND JAVIER GARDEAZABAL*

Thisarticle investigates the economic effects of conict, using the terrorist con ict intheBasque Country as acasestudy. We Žndthat,after the outbreak of terrorism inthe late 1960’ s, per capita GDP inthe Basque Country declined about 10 percentagepoints relative to a syntheticcontrol region without terrorism. In addition,we use the 1998 –1999truce as anaturalexperiment. We Žndthat stocks ofŽ rms witha signiŽcant part of their business in the Basque Country showed a positiverelative performance when truce became credible, and a negativerelative performanceat the end of the cease-Ž re. (JEL D74,G14, P16)

Politicalinstability is believedto have strong ofterrorist and political con ict, the Basque adverseeffects on economic prosperity. How- Countryhad dropped to the sixth position in per ever,to date, the evidence on this matter is capita GDP.1 Duringthat period, terrorist activ- scarce,probably because it is difŽ cult to know ityby the Basque terrorist organization ETA howeconomies would have evolved in absence resultedin almost800 deaths. Basque entrepre- ofpolitical con icts. neursand corporations had been speciŽ c targets Thisarticle investigates the economic impact ofviolence and extortion (including assassina- ofcon ict, using the terrorist con ict in the tions,robberies, and kidnappings-for-ran som). BasqueCountry as a casestudy. The Basque Notsurprisingly, the economic downturn suf- conict is especially interesting from aneco- feredby the Basque economy during those nomicperspective. At the outset of terrorist yearshas been attributed, at least partially, to activityin theearly 1970’ s, the Basque Country theeffect of terrorism. However, little research was oneof the richest regions in Spain, occu- hasbeen carried out to assess the economic pyingthe third position in per capita GDP (out effectsof the con ict. 2 of17regions).In the late 1990’ s, after 30 years Thistype of study is difŽ cult. On the one hand,a puretime-series analysis of theseverity ofterrorism and the evolution of the Basque *Abadie:John F. KennedySchool of Government,Har- economywill be contaminatedby the economic vardUniversity, 79 John F. KennedyStreet, Cambridge, downturnwhich Spain suffered during the sec- MA02138(e-mail: [email protected]);Gardea- ondhalf of the 1970’ s andthe Ž rst halfof the zabal: Departamento Fundamentosdel Ana ´lisisEcono ´mico 1980’s, at the peak of terrorist activity. On the II,Universidaddel Pa ´‡sVasco, AvenidaLehendakari Aguirre83, 48015 Bilbao, Spain (e-mail: jepgamaj@ otherhand, at the outset of terrorism, the bs.ehu.es).We thankJosh Angrist, Esther Du o, Jim BasqueCountry differed from otherSpanish Heckman, MiguelHerna ´n,Miguel Angel Mart ´‡nez,Adolfo regionsin characteristics that are thought to be deMotta, Dani Rodrik, Gonzalo Rubio, Emmanuel Saez, relatedto potentialfor economicgrowth. There- ToddSandler, Jim Stock,Jaume Ventura,Luis Viceira, RichardZeckhauser, and seminar participantsat CEMFI, fore,a simplecomparison of the evolution of Chicago,Harvard/ MIT,the University of California-Santa theBasque economy and the economy of the Cruz,and the 2001 Summer Schoolon Polarization and restof Spainwould not only re ect the effect of Conict inSanSebastian for helpful comments anddiscus- terrorismbut also the effect of pre-terrorism sions.Thanks also go to an anonymous referee forhelpful differencesin economic growth determinants. andconstructive suggestions. David Lo ´pez-Salido,Mikel Tapia,and Fernando Tusell helped us obtain the Ž nancial data.Henry Aray, Francisco Blanch, Sara Piccicuto,and ElenaZoido provided expert research assistance andcon- 1 See Fundacio´nBBV (1999). tributedcomments. Gardeazabal thanksthe Department of 2 Notableexceptions are Walter Endersand Todd Economicsat theUniversity of California-SantaCruz for its Sandler(1991, 1996), who study the effects ofterrorism on hospitalitywhile part of this work was carried out. tourismand foreign direct investment in Spain. 113 114 THEAMERICANECONOMIC REVIEW MARCH 2003

Our analysisrests on twodifferent strategies. variablestechniques can be used to correct for First,we usea combinationof other Spanish reversecausation. However, the validity of in- regionsto constructa “synthetic”control region strumentsin cross-countryregressions has often whichresembles relevant economic character- beenquestioned (see, e.g., N. GregoryMankiw, isticsof theBasque Country before the outset of 1995).Another potential shortcoming of studies Basquepolitical terrorism in the late 1960’ s. basedon country-leveldata is thatpolitical con- Thesubsequent economic evolution of this ictsin different countries may be radically “counterfactual”Basque Country without ter- differentin nature.Such heterogeneity may cre- rorism iscompared to the actual experience of ateproblems when comparing the experiences theBasque Country. We Žndthat, after the ofdifferentcountries and interpreting the results outbreakof terrorism, per capita GDP inthe (JonathanTemple, 1999, discusses heterogene- BasqueCountry declined about 10 percentage ityissues in cross-country regressions). pointsrelative to the synthetic control region. Casestudies, like the one presented in this Moreover,this gap seemed to widenin response article,look like the natural avenue to validate tospikesin terrorist activity. The second part of orrefutethe results given by cross-countrystud- thisstudy uses the unilateral truce declared by ies.Heterogeneity issues are circumvented here ETAinSeptember1998 as a naturalexperiment byfocusingon aparticularcon ict: the terrorist toestimate the effects of the con ict. If the conict in the Basque Country. In addition, as terroristcon ict was perceivedto have a nega- explainedbelow, the Basque con icthas no tiveimpact on the Basque economy, stocks of directeconomic motivation and, in contrast to Žrms witha signiŽcant part of theirbusiness in mostother violent con icts, it does not take theBasque Country should have shown a pos- placein a regionunder particularly harsh eco- itiverelative performance as the truce became nomicconditions. Consequently, temporal vari- credible,and a negativerelative performance at ationin economic prosperity in the Basque theend of thecease-Ž re. We Žndevidencethat Countryduring the period considered in this isconsistent with this conjecture using event studyis unlikely to havehad a substantialeffect studymethods. onthe intensity of terrorist activity, mitigating Mostof the empirical literature on theeffects endogeneityissues. ofpoliticalcon ict on economicvariables have usedcross sections of country-leveldata. Using I.ABriefHistory of ETA’ s TerroristActivity acrosssection of countries,Yiannis P. Venieris andDipak K. Gupta(1986) and Alberto Alesina ETAwas foundedin 1959 to promote the andRoberto Perotti (1996) concluded that po- establishmentof an independent Basque state. 5 liticalinstability has a negativeeffect on invest- However,it was notuntil 1968 that ETA mentand savings. Also using a crosssection of claimedits Ž rst victim.In fact, ETA didnot countries,Robert J. Barro(1991), Paolo Mauro implementlarge-scale terrorist activity until the (1995),and Alesina et al. (1996) have argued thatpolitical instability has a negativeeffect on 3 economicgrowth. Apotentialcaveat of this however,that rapid economic growth produces social disloca- literatureis thatpart of theobserved association tionand may cause politicalunrest. While cross-country stud- betweenpolitical con ict and economic vari- ies haveshown a positiveassociation between povertyand politicalcon ict (see, e.g.,Paul Collier and Anke Hoef er, ablesacross countries is thought to be created 2002),Alan B. Krueger and Jitka Maleckova (2002) provide byreverse causation, since political instability evidencethat, within country, disparities in individual socio- isnot only a causebut also an effect of  uc- economiccharacteristics seem tobe unrelated to participation tuationsin economic variables. 4 Instrumental inpolitically motivated violence. 5 Basques are spreadover the Basque Autonomous Re - gionand Navarra inSpain, and part of theFrench Atlantic PyreneesDepartment. The Basque Autonomous Region in 3 See alsoDouglas A. Hibbs(1973), Gupta (1990), John Spainhas been,however, the main scenario ofthecon ict; B.Londreganand Keith T. Poole(1990), Jess Benhabiband forthe rest ofthe article, we use theterm “theBasque AldoRustichini (1996), and Daron Acemoglu and James A. Country”to refer tothis region. The Basque Autonomous Robinson(2001) on the relationship between politicalin- regionis asmall regionwith an area of7,234 square stabilityand economic variables. kilometers(around 1.5 percent of the total area ofSpain) 4 Conventionally,it has beenargued that economic growth and2.1 million inhabitants in 2000 (around 5.2 percent of promotespolitical stability. Mancur Olson (1963) has argued, thetotal population of Spain). VOL.93NO. 1 ABADIEAND GARDEAZABAL:THE ECONOMICCOSTS OF CONFLICT 115

TABLE 1—CHRONOLOGYOF ETA’S TERRORIST ACTIVITY TABLE 2—ETA’S TERRORIST ACTIVITY, 1968–1997

Year KillingsKidnappings Event Deaths: BasqueCountry 523 1968 2 0Firstvictim of ETA Rest ofSpain 236 1969 1 0 Percentage inthe Basque Country 68.91 1970 0 1 Deaths permillion inhabitants per year: 1971 0 0 BasqueCountry 8.17 1972 1 1 Rest ofSpain 0.22 1973 6 1ETAkillsFranco’ s Prime RatioBasque Country/ Rest ofSpain 37.43 MinisterAdmiral Carrero-Blanco Notes: Authors’computations from Fundacio ´nBBV (1999) 1974 19 0 andSpanish Ministry of Interior (2002). Five additional 1975 16 0DictatorFranco dies deathsin the Basque portion of the French Atlantic 1976 17 4 PyreneesDepartment are notre ected inthe table. 1977 11 1Firstdemocratic elections inSpain after Franco’s death iestthree years of ETA,1978– 1980,witnessed 1978 67 6SpanishConstitution approvedin referendum atotalof 235 victims. In subsequent years, the 1979 76 13Regional Autonomy numberof killingsdecreased gradually. On av- Statutefor the Basque erage,during the 1980’ s, ETA’ sactivityre- Countryapproved sultedin 39 deaths per year; this Ž gurewas 1980 92 13 1981 30 10Attempted military coup. reducedto 16 per year during the 1990’ s. The Spainjoins NATO numberof kidnappings during the sample pe- 1982 37 8 riodwas smallerthan the number of killingsbut 1983 32 5 evolvedsimilarly. In September 1998, ETA de- 1984 32 0 clareda totaland indeŽ nite cease-Ž re. The cease- 1985 37 3 1986 41 3Spainjoins European Žre lastedapproximately 14 months; in November Community 1999,ETA announcedthe end of cease-Ž re. In the 1987 52 1 year2000, ETA killed23 people. 1988 19 1 Inorder to Ž nanceits operations, ETA has 1989 19 1 1990 25 0 usedkidnappings-for-ran som,extortion, and 1991 46 0 (lessfrequently) robberies. The main targets of 1992 26 0Barcelona hoststhe suchmoney-raising activities have been Basque Summer Olympic entrepreneurs,who have since begun to aban- Games donthe Basque Country in large numbers in 1993 14 1 1994 13 0 orderto escape extortion or abduction by the 1995 15 1 terroristgroup. In addition, the terrorist con ict 1996 5 2 hasbeen frequently cited as a deterrencefor 1997 13 1 domesticand foreign direct investment in the 1998 6 0ETAdeclares indeŽnite cease-Žre startingon BasqueCountry (see, e.g., TheEconomist, No- September18 vember25, 2000). 1999 0 0ETAannouncesthe end of Finally,although terrorist attacks have oc- cease-Žre on curredin almost all Spanish regions, most of November 28 ETA’s violentactivity has been concentrated in 2000 23 0 theBasque Country. Table 2 reportsdeaths and Source: SpanishMinistry of Interior(2002). deathsper million inhabitants per year caused byETA for theperiod 1968 –1997.Almost 70 percentof the deaths caused by ETA inSpain mid-1970’s. Table 1 showsthe number of kill- during1968 –1997occurred in the Basque ingsand kidnappings from 1968to 2000.ETA’ s Country.6 Thiscomparison becomes even more terroristactivity was lowbefore 1973 with no morethan two victims in any given year. The deathtoll increased sharply during the mid- 6 Inaddition, Ž vekillings have been attributed to ETA 1970’s, with an average of almost 16 victims duringthe same periodin theBasque portion of theFrench peryear in theperiod of 1974–1977.The blood- AtlanticPyrenees Department. 116 THEAMERICANECONOMIC REVIEW MARCH 2003

TABLE 3—PRE-TERRORISM CHARACTERISTICS , 1960’S

“Synthetic” BasqueCountry Spain BasqueCountry (1) (2) (3) Real percapita GDP a 5,285.46 3,633.25 5,270.80 Investmentratio (percentage) b 24.65 21.79 21.58 Populationdensity c 246.89 66.34 196.28 Sectoralshares (percentage) d Agriculture,forestry, and Ž shing 6.84 16.34 6.18 Energyand water 4.11 4.32 2.76 Industry 45.08 26.60 37.64 Constructionand engineering 6.15 7.25 6.96 Marketableservices 33.75 38.53 41.10 Nonmarketableservices 4.07 6.97 5.37 Humancapital (percentage) e Illiterates 3.32 11.66 7.65 Primaryor without studies 85.97 80.15 82.33 High school 7.46 5.49 6.92 Morethan high school 3.26 2.70 3.10

Sources: Authors’computations from Matilde Mas et al.(1998) and Fundacio ´nBBV (1999). a 1986USD, average for1960 –1969. b Gross TotalInvestment/ GDP,average for1964 – 1969. c Personsper square kilometer, 1969. d Percentages overtotal production, 1961– 1969. e Percentages overworking-age population, 1964 – 1969. strikingonce the Ž guresare expressed in per bettereducated labor force. As aresult,a simple capitaterms to re ect relative exposure to ter- comparisonof the economic performance of the rorism.During the period 1968 –1997,ETA’ s BasqueCountry and the rest of Spain during the activityin theBasque Country, measured as the terrorismyears may not only re ect the impact of numberof deaths per inhabitant per year, was terrorism,but also other pre-terrorism differences 37times as large as in the rest of Spain. 7 whichaffected subsequent economic growth. We approachthis problem by comparing the II.Using Other Spanish Regionsto Construct a economicevolution of the Basque Country dur- “Synthetic”Basque Country Without Terrorism ingthe terrorist era with that of a weighted combinationof other Spanish regions chosen A. AnalyticalMethods and Main Results toresemble the characteristics of the Basque Countrybefore terrorism. We conceptualize Thegoal of this section is to assess the impact sucha weightedaverage of other Spanish re- thatterrorism has had on economic growth for the gionsas a “synthetic”Basque Country without BasqueCountry. Table 3, in columns (1) and(2), terrorism,against which we cancompare the reportsvalues of some variables typically associ- actualBasque Country with terrorism. Let J be atedwith growth potential 8 for theBasque Coun- thenumber of availablecontrol regions (the 16 tryand Spain for theimmediate pre-terrorism Spanishregions other than the Basque Coun- years.During the 1960’ s, relative to the whole try), and W 5 (w1, ... , wJ)9 a ( J 3 1) vector country,the Basque Country had higher per capita ofnonnegative weights which sum to one. The income,higher investment ratio (investment/ pro- scalar wj ( j 5 1, ... , J)representsthe weight duction),was moredensely populated, had a of region j inthe synthetic Basque Country. higherpercentage of industrial production, and a Eachdifferent value for W producesa different syntheticBasque Country, and therefore the choiceof a validsubset of control regions is embeddedin the choice of the weights W. 7 See alsoMark Kurlansky (1999) and CNN (2001)for additionalbackground information on the Basque con ict. As saidabove, the weights are chosen so that 8 See, e.g.,Barro and Xavier Sala-i-Martin(1995). thesynthetic Basque country most closely re- VOL.93NO. 1 ABADIEAND GARDEAZABAL:THE ECONOMICCOSTS OF CONFLICT 117 semblesthe actual one before terrorism. Let X1 3reportsgrowth predictors for thesynthetic be a (K 3 1)vectorof pre-terrorism values of BasqueCountry before terrorism: X*1 5 X0W*. K economicgrowth predictors for theBasque TheseŽ guresgive an indication of how well Country[i.e., those values in Table 3, column theweighted combination of control regions (1)]. Let X0 be a (K 3 J)matrixwhich contains reproducesthe values of growth predictors for thevalues of the same variables for the J pos- BasqueCountry before terrorism. As expected, siblecontrol regions. Let V beadiagonalmatrix thesynthetic Basque Country looks comparable withnonnegative components. The values of tothe actual one, although some growth deter- thediagonal elements of V reect the relative minantscannot be perfectly Ž tted.In particular, importanceof the different growth predictors. duringthe 1960’ s, the Basque Country was the Thevector of weights W*ischosen to mini- Spanishregion with the highest industrial share mize (X1 2 X0W)9V(X1 2 X0W) subject to asapercentageof totalproduction. Therefore, a ... wj $ 0 (j 5 1, 2, ... , J) and w1 1 1 wJ 5 1. convexcombination of other Spanish regions The vector W*deŽnes the combination of non- cannotperfectly reproduce the Basque sectoral terrorismcontrol regions which best resembled sharesbefore terrorism. theBasque Country in economic growth determi- Let Y1 be a (T 3 1)vectorwhose elements nantsat the outset of terrorism. 9 arethe values of real per capita GDP for the Since W* depends on V thereis somethingto BasqueCountry during T timeperiods. Let Y0 besaid about the choice of V.Arguably,the be a (T 3 J)matrixwhich contains the values choice of V couldbe subjective, re ecting our ofthe same variables for thecontrol regions. previousknowledge about the relative impor- Our goalis toapproximate the per capita GDP tanceof each particular growth predictor. Here, paththat the Basque Country would have expe- we adopta moreeclectic method, choosing V riencedin the absence of terrorism. This coun- suchthat the real per capita GDP pathfor the terfactualper capita GDP pathis calculated as BasqueCountry during the 1960’ s isbestrepro- theper capita GDP ofthe synthetic Basque ducedby the resulting synthetic Basque Coun- Country, Y*1 5 Y0W*. try(see AppendixB for details). Figure1 plots Y1 and Y*1 for theperiod Theoptimal weights, W*,arepositive for 1955–1997. The Basque Country and the syn- tworegions, Catalonia and Madrid, with values theticcontrol behave similarly until 1975. From 0.8508and 0.1492 respectively, and take value 1975,when ETA’ s terroristactivity becomes a zerofor theother potential controls. The selec- large-scalephenomenon, Y1 and Y*1 diverge; tionof Catalonia and Madrid by our procedure theBasque Country per capita GDP takesval- ascontrolsfor theBasque Country is notunex- uesup toaround 12 percent below those of the pected,since a visualinspection of the data syntheticcontrol. The gap in per capita GDP revealsthat the values of thepre-terrorism char- seemsto decrease at the end of the period, acteristicsfor thesetwo regions are comparable takingvalues around 8 or9 percentin 1995– tothevalues of the pre-terrorism characteristics 1997.Overall, Figure 1 suggestsa 10-percent for theBasque Country. 10 Column(3) ofTable lossin per capita GDP dueto terrorism for the 1980’s and1990’ s. Statisticalinference on the effect of terrorism 9 Thisapproach is closely related tostatistical matching onthe economy can now be carried out by methodsfor observational studies (see, e.g.,Paul R. Rosen- baum,1995). The reason to restrict theweights in W to be lookingat therelationship between the per cap- nonnegativeand sum to one is to prevent extrapolation outside itaGDP gap(synthetic vs. actual Basque Coun- thesupport of the growth predictors for the control regions. try)and the intensity of terrorismin theBasque Withoutthis restriction (and if all the diagonal elements of V Countryduring the sample period. Since pro- are positive), X wouldbe perfectlyŽ ttedas longas therank 1 ductionfactors are Ž xedin the short run, we of X0 is equal to K,irrespectivelyof how distant is X1 from the elements of X0.Whenthe weights in W are restricted tobe nonnegativeand sum to one, X1 cannotbe perfectly Ž ttedin generaleven if the rank of X0 is equal to K.Inthis case, X1 will Inaddition,Catalonia and the Basque Country were thetwo beperfectly Ž ttedonly if it lies inthe “ support”(convex hull) Spanishregions with highest shares ofindustrial produc- ofthe growth predictors for the control regions. tion.As arobustnessexercise, we checkedthat small per- 10 Likethe Basque Country, relative tothe rest ofSpain turbationsto V donot alter theresults substantively, even duringthe 1960’ s, Catalonia and Madrid had higher levels whenthey occasionally produce small positiveweights for ofpercapita income,population density, and human capital. regionsother than Catalonia and Madrid. 118 THEAMERICANECONOMIC REVIEW MARCH 2003

FIGURE 1. PER CAPITA GDP FOR THE BASQUE COUNTRY

FIGURE 2. TERRORIST ACTIVITY AND ESTIMATED GAP

expectterrorism to have a laggednegative ef- ofdeaths caused by terrorist actions (used as a fecton percapita GDP. InFigure 2, we plotted proxyfor overallterrorist activity). As ex- theper capita GDP gap, Y1 2 Y*1,asa percent- pected,spikes in terrorist activity seem to be ageof Basqueper capita GDP, andthe number followedby increases in the amplitude of the VOL.93NO. 1 ABADIEAND GARDEAZABAL:THE ECONOMICCOSTS OF CONFLICT 119

effectof terrorismor is merelyan artifact of the inabilityof our analysis to reproducethe growth pathfor theBasque Country in the absence of terrorism.To address this question we per- formeda “placebostudy,” applying the method thatwe usedto computethe gap for theBasque Countryto a “nonterrorismregion” (a region otherthan the Basque Country). The idea is to comparethe economic evolution of a regionsim- ilarto the Basque Country, but without high levels ofterrorist activity, to the economic evolution of itssynthetic version, also without high levels of terrorism.The purpose is to assess whether the gapobserved for theBasque Country may have FIGURE 3. IMPULSE-RESPONSE FUNCTION FOR TERRORISM beencreated by factors other than terrorism. ONPER CAPITA GDP GAP AND 95-PERCENT Toconduct this “ placebo”study we chose CONFIDENCE INTERVALS Cataloniawhich was theregion with the largest weightin the synthetic control for theBasque percentageGDP gap.This pattern is conŽrmed Country.In addition to being the region most byFigure3 whichshows the estimatedimpulse- similarto the Basque Country before terrorism responsefunction of terrorism on theGDP gap, ineconomic growth determinants (as measured alongwith 95-percent conŽ dence intervals. The usingour methods), Catalonia resembles the impulse-responsefunction shows the estimated BasqueCountry in many characteristics, some contemporaneousand lagged response of the ofwhich are not directly measured in our data. gapto an increase of terrorist activity, proxied Inparticular,at the end of Franco’s dictatorship, byan increase of one unit in the number of boththe Basque Country and Catalonia were victims.11 Theestimated effect of terrorism on highlyindustrialized regions, and both had his- theGDP gapis negativefor everytime lag, it is toricaldemands for self-governance,which led maximalafter two to three years, and it de- totheŽ rst tworegional autonomy statutes of the creasesmonotonically (in absolute value) after post-Francoera in 1979. Since then, autonomy that.The conŽ dence intervals for thelagged statuteshave been granted to the rest of Spanish responsesdo notcontain zero until the eleventh regions;however, Catalonia and the Basque lag.Terrorist activity explains the GDP gap Countryhave always been among the regions almostperfectly (see last row ofTable B1 in withthe highest degree of political autonomy. AppendixB), andit does so in a waythat is Whilein both regions large fractions of the pop- consistentwith our previous beliefs about the ulationhave traditionally demanded higher levels laggedimpact of terrorism on output. ofself-governance, Catalonia never experienced a large-scaleoutbreak of political terrorism. B. A“PlaceboStudy” Figure4 showsthe actual real per capita GDP pathfor Cataloniaand the one implied by a Of course,a questionremains about whether “syntheticCatalonia” constructed as a weighted thegap shown in Figure1 trulyresponds to the combinationof other Spanish regions (exclud- ingthe Basque Country) as explained above. Theweighted combination of Spanish regions 11 Inotherwords, the impulse-response function in Fig- reproducesper capita GDP for Cataloniawith ure3 plotsthe dynamic multipliers of terrorism onthe gap. highaccuracy up to the late 1980’ s. During Thisfunction was estimated usingan autoregressive distrib- utedlag model assuming no feedback effects between the 1990–1997Catalonia outperformed the syn- gapand terrorism (see, e.g.,Andrew C. Harvey,1990). theticcontrol by around 4 percentin percapita Polynomialdistributed lag models were usedas analterna- GDP. Thisgap does not come as a surpriseif we tivespeciŽ cation, to check therobustness of our results. considerthe heavy investments and economic Estimates basedon polynomial distributed lag models pro- ducedvirtually identical results. See AppendixB fordetails expansionthat Catalonia experienced during onthe estimation of the impulse-response function and thatperiod as a resultof the 1992 Summer conŽdence intervals. OlympicGames hostedin Barcelona. Since 120 THEAMERICANECONOMIC REVIEW MARCH 2003

FIGURE 4. A “PLACEBO STUDY,” PER CAPITA GDP FOR CATALONIA

Cataloniais the main contributor to the syn- economiceffect of terrorism on the Basque theticcontrol for theBasque Country, an ab- Country.To the extent that the regions which normallyhigh level of per capita GDP for form thesynthetic control might have been eco- Cataloniaduring the 1990’ s mayartiŽ cially nomicallyhurt by the con ict, our estimated widenthe GDP gapfor theBasque Country in GDP gapwould provide a lowerbound on the Figure1. Therefore,our placebo study suggests economiceffect of terrorism on the Basque that,while per capita GDP for Cataloniacan be Countryeconomy. On the other hand, the con- reasonablywell reproduced by our techniques, ictmay have diverted investment from the thecatch-up in per capita GDP for theBasque BasqueCountry to other Spanish regions, arti- Countryduring the 1990’ s (relativeto the syn- Žciallyincreasing the magnitude of the gap. theticcontrol region) may have been more pro- However,since the size of thesynthetic Basque nouncedthan what Figure 1 indicates. Countryis much larger than the actual Basque Country,this type of biasis arguablysmall. 12 In C. Discussion thenext section we showevidence that support theview that the effect of thecon ict was small As notedearlier, the Basque Country has outsidethe Basque Country. beenthe main scenario of the terrorist con ict. Amoreimportant criticism of theanalysis in However,ETA hasalso operated in otherSpan- thissection is that, as long as the synthetic ishregions. Even though there is no indication controlcannot reproduce exactly the character- thatentrepreneurs have abandoned Spain as a isticsof the Basque Country before terrorism, resultof the terrorist threat, Basque terrorism theGDP gapmay have been created by differ- mighthave imposed a negativereputational ex- ternalityon other Spanish regions, and foreign investmentmight have chosen alternative des- 12 Forthe 1964 –1975period, GDP forthe synthetic tinationswith no terroristcon icts. If itisinfact regionwas 2.5times larger thanGDP forthe Basque Coun- try;this Ž gureincreased tomore than3 duringthe terrorism thecase that the Basque terrorist con icthas era. Furthermore,investment diverted to regions other than hada negativeeconomic effect on otherSpanish thosein the synthetic Basque Country does not affect the regions,this effect is arguablyweaker than the validityof our analysis. VOL.93NO. 1 ABADIEAND GARDEAZABAL:THE ECONOMICCOSTS OF CONFLICT 121 encesin growth predictors between the Basque Countryand the synthetic control before terror- ism[columns (1) and(3) inTable 3], or byother differencesnot re ected in our data. In partic- ular,it might be argued that the GDP gapwas causedby thehigher industrial concentration in theBasque Country in the pre-terrorism years, sinceterrorism developed during a periodof industrialdecline, when many industrial plants closed.In fact, the industrial share of GDP declined17 percentagepoints (from 45percent to28 percent) for theBasque Country during the1964 –1993period. The industrial share of theGDP decreased15 percentage points (from

38percent to 23percent)for thesynthetic con- FIGURE 5. POPULATION trolduring the same period. Notwithstanding thepotential importance of this criticism, we believethat differences in industrialdecline be- presentedin this section do not re ect this rel- tweenthe Basque Country and the synthetic ativepopulation loss in the Basque Country. controlcannot fully explain the GDP gapbe- Oncethe population dynamics are considered, tweenthe two regions during the 1980’ s and thegap in per capita GDP documentedin this 1990’s. As discussedearlier, the GDP gapseems sectionbecomes even more striking. torespond to the intensity of the terrorist activity Finally,it isworthnoticing that the results in inthe Basque Country. Such association is con- thissection are consistent with the Ž ndingsin sistentwith the interpretation that the gap was Barroand Sala-i-Martin (1995, page 399, Fig- causedby terrorism, and would be left unex- ure11.8), who document an atypically low growth plainedunder the alternative explanation that the ratefor theBasque Country during the period gapwas generatedby a morepronounced indus- 1950–1999relative to other European regions. trialdecline in the Basque Country. 13 Figure5 graphspopulation series for the III.Using ETA’ s 1998–1999Truce BasqueCountry, the syntheticcontrol and Spain asa NaturalExperiment (theseries are normalized to 100in 1964). The populationof the Basque Country and the syn- A. AnalyticalMethods and Main Results theticcontrol grew atsimilar rates during the late1960’ s andthe early and the mid-1970’ s, OnSeptember 16, 1998, ETA announceda wellabove the rate for thewhole country. In the cease-Žre (startingon September 18, 1998). late1970’ s andearly 1980’ s thepatterns of the Fourteenmonths later, on November 28, 1999, serieschanged dramatically; population growth ETAannouncedthe end of the truce. Table deceleratedfor thesynthetic Basque Country 4presentsa chronologyof some of the most andSpain, and became negative for theBasque importantevents related to thetruce. Anecdotal Country.The results on theper capita GDP gap evidencesuggests that the truce was notper- ceivedas credible from thebeginning (note, for example,the Spanish government’ s reactionto 13 Theconnectionsbetween theoil crisis andthe decline theannouncement of the cease-Ž re inTable ofindustrial centers inEurope during the 1970’ s andthe 4,event number 4). In fact, ETA haddeclared 1980’s has beennoted by Derek H.Aldcroft(1993) and othercease-Ž res inthe past, but none of them others.To check thatthe association between theintensity lastedmore than three months; the previous ofterrorism andthe gap does not arise artiŽcially from a 14 differentialeffect ofthe oil crisis inthe Basque Country, we one,in 1996,had only lasted one week. Peace repeated theimpulse-response analysis including contem- poraneousand lagged values of oil prices as additional exogenousvariables. The coefŽcients ontheoilprices vari- ables were notstatistically signiŽ cant andtheir inclusion 14 Theannouncement of the cease-Ž re was precededby left theestimated impulse-responsefunction for terrorist ajointdeclaration subscribed by the main Basquenation- activityon the gap virtually unchanged. alist parties callingfor the end of violence and the start of 122 THEAMERICANECONOMIC REVIEW MARCH 2003

TABLE 4—CHRONOLOGYOF THE TRUCE

Number Date Event 1 September12, 1998 Basque nationalist parties (includingETA’ spoliticalwing) sign joint declaration callingfor the end of violence and the start ofpolitical negotiations with the Spanishgovernment on issues regardingsovereignty 2 September15, 1998 Spanish Minister of Interiorsays thegovernment expects “fake truce”by ETA intendedto regroupand gain popular support 3 September16, 1998 ETA calls cease-Žre startingon September 18 4 September17, 1998 Spanish government expresses “profoundskepticism” about the truce and advisescaution 5 October2, 1998 SpanishPrime Ministersays ETAhas yetto prove its commitment topeace, but promiseschanges in policy towards incarcerated ETAactivistsif peace consolidates 6 October24, 1998 ETAleaders say cease-Žre is “Žrm andserious” in BBCTV broadcast 7 November3, 1998Spanish government says ithas authorizedexploratory contacts with ETA in orderto assess ETA’scommitment tomaintain cease-Ž re 8 February24, 1999 ETA’s communiquepledges to maintain cease-Ž re andalludes to a new “hopefulclimate” 9 May 16, 1999 ETAsays ithas maintainedcontacts with Spanish government 10 June 2, 1999 Spanishgovernment conŽ rms conversationswith ETA 11 August25, 1999 SpanishPrime Ministersays thatcontacts with ETA havebeen interrupted 12 August26, 1999 ETAconŽrms thatthe peace process is paralyzed 13 August28, 1999 ETA’s communiquestates thatthe peace process has reached a“critical stage” inwhich it is eitherconcluded “ orelse itwillrot” 14 November28, 1999 ETA announcesthe end of cease-Ž re prospectsbecame more realistic as time passed Achallengewith this exercise is that there is no withoutterrorist actions and the Spanish gov- obviousway to classify stocks into the Basque/ ernmentconŽ rmed contacts with ETA. Three non-Basquecategories. A classiŽcationthat relies monthsbefore the end of the truce the situation solelyon companies’ registered addresses seems deterioratedas the Spanish government an- problematic.Registered addresses are sometimes nouncedthat the process was paralyzed. chosenfor historic,convenience, or tax-related If Žnancialmarkets are efŽ cient, asset prices reasonsand do not necessarily imply that the shouldre ect all available information and, companyhas an important presence in the area. thus,react only to new information. Therefore, Unfortunately,data on geographical location of ifthe terrorist con ict was perceivedto have a Žrms’activities are rarely available. To solve this negativeimpact on the Basque economy, problemwe adopteda simpleand direct approach. Basquestocks (stocks of Žrms witha signiŽcant Sincewhat is relevant for ourevent study is which partof their business in the Basque Country) companieswere perceivedby the markets as car- shouldhave shown a positiveperformance rel- ryinga signiŽcant part of their business in the ativeto non-Basque stocks (stocks of Ž rms BasqueCountry, we askeda groupof market withouta signiŽcant part of theirbusiness in the analystsat a certainBasque Ž nancialinstitution to BasqueCountry) as the truce became credible. producethis classiŽ cation for us.We usedthis Similarly,Basque stocks should have per- informationto divide stocks into Basque stocks formedpoorly, relative to non-Basque stocks, andnon-Basque stocks. Again, the idea is to label atthe end of the truce. In this section, we use Žrms whichhave a largepart of their business in themethod of event study to explore these theBasque Country as Basque stocks, even if they questions. arenot located in the Basque Country. All other Žrms withlittle exposure in the Basque Country were labeledas non-Basque stocks. 15 We collectedseries of daily stock returns politicalnegotiation (event 1 inTable 4). This declaration andthe subsequent announcement of the truce were inter- pretedby many nonsubscribing parties as maneuvers of Basquenationalist parties tocreate aunitedfront to pursue 15 Thelistof Basque and non-Basque stocks used for the independence. analysisis providedin Appendix B, TableB2. VOL.93NO. 1 ABADIEAND GARDEAZABAL:THE ECONOMICCOSTS OF CONFLICT 123

TABLE 5—DESCRIPTIVE STATISTICS

Non- Basque Basque All Numberof observations 14 59 73 Registeredin the BasqueCountry Fraction 0.57 0.00 0.11 Size 1998 Mean 412.281,999.37 1,695.00 S.D. 362.844,501.26 4,091.61 Min 117.66 17.01 17.01 Max 1,531.6826,778.68 26,778.68 1999 Mean 478.702,948.63 2,474.94 S.D. 348.467,105.34 6,453.67 Min 104.56 15.88 15.88 Max 1,244.6445,347.23 45,347.23 2000 Mean 371.433,346.84 2,776.21 S.D. 406.4311,305.43 10,216.72 Min 56.20 9.12 9.12 Max 1,656.3881,292.33 81,292.33 Book-to-market 1998 Mean 0.68 0.55 0.58 S.D. 0.43 0.34 0.36 Min 0.20 0.09 0.09 Max 1.65 1.80 1.80 1999 Mean 0.72 0.50 0.54 S.D. 0.55 0.29 0.36 Min 0.14 0.07 0.07 Max 2.28 1.38 2.28 2000 Mean 0.86 0.68 0.71 S.D. 0.46 0.43 0.44 Min 0.30 0.08 0.08 Max 1.70 2.26 2.26

Source: Authors’computations from Madrid Stock Exchange online data (http://www.bolsa- madrid.es).Size valuesin millions of United States dollars.Size andbook-to-market Ž gures are forthe beginning of theindicated year (last tradingday of theprevious year). S.D. means standarddeviation. for 1998,1999, and 2000 and constructed two smallerand have a higherbook-to-market buy-and-holdportfolios: one composed of 14 ratio.17 Basquestocks and the other composed of 59 Incontrast with more conventional event non-Basquestocks (see AppendixB for details studysettings, where most of theinformation is onselection of stocks for oursample and con- revealedduring short event windows, the infor- structionof portfolios).Buy-and-hold portfolios mationalcontent of thetruce evolved gradually representthe portfolio of a passiveinvestor duringa 14-monthperiod. Therefore, to study whoconstructed a value-weightedBasque or theeffect of the truce it is important to con- non-Basqueportfolio at the beginning of our trolfor long-runrisk factors in stock returns. sampleperiod. 16 Famaand French (1993) have identiŽ ed three Table5 containsdescriptive statistics for our commonrisk factors in stock returns, which sample.Fifty-seven percent of the Ž rms that composethe often-called Fama-French Three- composeour Basque portfolio have registered FactorModel: addressesin theBasque Country, while none of thenon-Basque Ž rms areregistered in the BasqueCountry. On average, Basque Ž rms are 17 Size isthemarket valueof all outstandingshares ofa commonstock. The book-to-market ratio is theratio of the bookvalue of a stockto its market value.Size andthe 16 Thestrategy of constructing portfolios of Ž rms ex- book-to-marketratio have been shown to explain cross- posedand not exposedto certain risksis oftenused in event sectionalvariation in average stockreturns (see, e.g.,Eu- studies.See, forinstance, Bong Chan Kho et al.(2000). geneF. Fama andKenneth R. French,1992). 124 THEAMERICANECONOMIC REVIEW MARCH 2003

TABLE 6—PORTFOLIO REGRESSIONS, FAMA-FRENCH THREE-FACTOR MODEL

Basque Non-Basque Basque Non-Basque Difference (1) (2) (3) (4) (3)–(4) Constant 20.0004 0.0001 20.0004 0.0001 20.0005 (0.0003) (0.0002) (0.0003) (0.0002) (0.0003) Rm 0.6824 0.8103 0.6739 0.8096 20.1357 (0.0361) (0.0184) (0.0366) (0.0186) (0.0346) SMB 0.3755 20.2253 0.3657 20.2260 0.5917 (0.0461) (0.0234) (0.0464) (0.0235) (0.0445) HML 0.2510 20.1418 0.2553 20.1411 0.3964 (0.0399) (0.0207) (0.0400) (0.0207) (0.0382) Good News 0.0049 0.0005 0.0044 (0.0021) (0.0009) (0.0022) Bad News 20.0017 0.0001 20.0018 (0.0008) (0.0004) (0.0009) R2 0.4891 0.9107 0.4966 0.9107 0.5499

Notes: Heteroskedasticity-robuststandard errors are inparentheses.The sample periodconsists of 747trading sessions for 1998–2000.

j j j m j m (1) Rt 5 a 1 b1Rt 1 b2SMBt HMLt areall signiŽ cant. The coefŽ cients on Rt arepositive in both cases, whereas the coef Ž- j j 1 b3HMLt 1 ARt. cients on SMBt and HMLt havepositive signs for theBasque portfolio and negative signs for j 19 For thecase studied here, Rt isthe excess return thenon-Basque portfolio. Theresiduals of the (overthe risk-free rate)on abuy-and-holdport- regressionsare the estimated abnormal returns folio of j 5 Basque,non-Basque stocks on day onthe Basque and non-Basque portfolios. Ab- m t, Rt istheexcess return on the market portfo- normalreturns are now suited for comparison, lio at time t, SMBt (“smallminus big” ) isthe asthey are adjusted for knownrisk factors. differencebetween the returns of portfolios However,abnormal returns are too noisy to be composedby smalland big size stocks at time t, visuallyinstructive. In order to visuallyinspect and HMLt (“highminus low” ) isthedifference thedifference in performance of the two port- betweenthe returns of portfolios composed by folios,abnormal returns are customarily aggre- highand low book-to-market stocks at time t. gatedthrough time. We calculatecumulative m Rt representsthe usual market factor in stock abnormalreturns as thecompounded abnormal returns,while SMBt and HMLt are meant to returnof a portfoliofrom theday after the capturerisk factors related to sizeand book-to- announcementof the truce: j marketequity, respectively. The residual, ARt, isa zeromean abnormal portfolio return not t explainedby common risk factors. 18 j j (2) CARt 5 $1 1 ARs% 2 1. Columns(1) and(2) ofTable 6 reportthe X s 5 1 D resultsof Ž ttingequation (1) byordinary least squares(OLS) tothe Basque and non-Basque Figure6 graphscumulative abnormal returns m portfolios.The coefŽ cients on Rt , SMBt, and for theBasque and non-Basque portfolios from theannouncement of the truce to the end of 1999(the dashed vertical line around the end of 18 See thein uential article byFama andFrench (1993) andAppendix B formore informationabout the deŽ ni- tionand construction of these variables.Fama andFrench 19 As inFama andFrench (1993), we expectthat returns (1993)and John D. Lyonet al.(1999) discuss the use ofportfolios constructed from stocks with small market ofthe Fama-French Three-FactorModel to calculate long- valuationsand high book-to-market ratios (as theBasque runabnormal returns in event studies. In particular, Fama portfolio)respond positively to SMBt and HMLt, whereas andFrench (1993) have argued that SMBt and HMLt ab- returnsof portfolios constructed from stocks with big mar- sorbthe size andbook-to-market effects inaverage stock ketvaluations and low book-to-market ratios (as thenon- returns. Basqueportfolio) respond negatively to SMBt and HMLt. VOL.93NO. 1 ABADIEAND GARDEAZABAL:THE ECONOMICCOSTS OF CONFLICT 125

FIGURE 6. CUMULATIVE ABNORMAL PORTFOLIO RETURNS

Novemberof 1999 represents the end of the Minister(event number 11), and ending with truce).The Basque portfolio outperforms the theannouncement of the end of the truce by non-Basqueportfolio for mostof the truce pe- ETA(eventnumber 14). Columns (3) and(4) riodexcept at the beginning (when the cease- ofTable 6 reportthe regressions including Žre hadnot gained credibility) and at the end thedummy variables Good Newst and Bad (whenthe cease-Ž re lostcredibility). Newst.Theestimated coefŽ cients on the Toperform a statisticaltest on the effect of dummyvariables represent average daily abnor- thetruce we addedtwo dummy variables to malreturns during the Good News andBad equation(1). Good Newst takesa valueof one News periodsfor theBasque and non-Basque for theperiod between the trading sessions after portfolios.As expected,for theBasque port- event5 andevent 7 inTable 4, and a valueof folio,the coefŽ cient of Good Newst is posi- zerootherwise. Bad Newst takesa valueof one tiveand signiŽ cant while the coefŽ cient of for theperiod between the trading sessions after Bad Newst isnegativeand also signi Žcant.For event11 and event 14 inTable4, anda valueof thenon-Basque portfolio, the effects are small zerootherwise. The Good News periodcom- inmagnitude and not statistically different prises22 trading sessions and the Bad News from zero,which supports the view that Basque period66. During the Good News period,the terrorismhas a minorimpact on the economy credibilityof the truce gained ground, starting outsidethe Basque Country. The last column withthe offer ofa revisionin thepolicy towards ofTable 6 showsthe result for thedifference ETAactivistsin jail, if peaceconsolidated, by regression.The dependent variable for the theSpanish Prime Minister(event number 5), differenceregression is the difference in ex- andculminating with the announcement of the cessreturn between the Basque and the non- authorizationof directcontacts with ETA bythe Basqueportfolios. The difference regression Spanishgovernment (event number 7). In con- canbe interpreted as the one that corresponds trast,the Bad News periodwas characterized tothe portfolio of a passiveinvestor who takes bythe collapse of the peace process, starting alongposition in Basque stocks and a short withthe acknowledgment that contacts had positionin non-Basque stocks. This regression beeninterrupted, made by the Spanish Prime reects a positiveabnormal performance of 126 THEAMERICANECONOMIC REVIEW MARCH 2003

Basquestocks relative to non-Basque stocks isworthnoting that the results in thissection do duringthe Good News periodand a negative notdepend on the adoption of this particular relativeperformance during the Bad News period. model.Two other models of normalreturns, the Theperformances of theBasque and the non- MarketModel and the Constant-Mean-Return Basqueportfolios during the Good News and Modelare perhaps the most common in the BadNews periodscan be easily visualized in eventstudy literature (see John Y. Campbellet Figure6. TheŽ rst shadedarea, around October al.,1997). These two models can be expressed of1998, represents the Good News period;the asspecial cases of the Fama-French Three- secondone, around September to Novemberof FactorModel: 1999,represents the Bad News period.The ab- normalgains in value for theBasque portfolio R j 5 g j 1 ljR m 1 ARj ~MarketModel !, duringthe Good News periodand the losses t t t duringthe Bad News periodare apparent. In j j j contrast,the non-Basque portfolio experienced R t 5 m 1 ARt ~Constant-Mean-ReturnModel !, relativelymodest abnormal changes in value j duringthe two periods. where ARt isagaina zeromean abnormal return for portfolio j and period t.Columns(1)– (6) in B. Discussion Table7 reportthe results of using these two alternativemodels of abnormalreturns in lieuof Noticethat if most of the new information theFama-French Three-Factor Model. The duringthe Good News andBad News periods MarketModel in columns (1)– (3) produces was revealedin certain trading sessions, the resultsvery similar to those in Table 6. The analysisin this section would provide conser- Constant-Mean-ReturnModel in columns (4)– vativeinference about the effect of terrorism, (6) isless suitable to study long-run returns becausethe coefŽ cients on the Good Newst becauseit assumesthat expected returns do not and Bad Newst dummiesre ect average abnor- varyduring the sample period. Using the malreturns during these periods. Even so, the Constant-Mean-ReturnModel, the Basque and coefŽcients on the Good News t and Bad non-Basqueportfolios behave similarly during Newst dummiesare statistically signiŽ cant at theGood News period;however, the non- conventionallevels. Basqueportfolio outperforms the Basque port- Tobetter understand the magnitude of the folioduring the Bad News period. effectsdescribed in this section it is useful to Althoughthe Fama-French Three-Factor model compoundthe daily effects for theGood News isperhaps the most widespread multifactor andBad News periods.Compounding the modelof portfolio returns, other factors have 0.0044coefŽ cient on the Good News t dummy beenproposed in the Ž nanceliterature to ex- overthe 22 trading sessions of theGood News plainstock returns. In particular, factors related period,we obtaina compoundedabnormal re- totheterm premia and the default risk premia of turnof 10.14 percent for theBasque portfolio bondshave been proposed for thatpurpose (see, relativeto the non-Basque portfolio. Analogous e.g.,Nai Fu Chen et al., 1986; Fama and French, calculationsyield a 211.21-percentcom- 1993).The results in Fama and French (1993) poundedabnormal return for theBasque port- showthat these type of term and risk structure foliorelative to the non-Basque portfolio during factorsmay have explanatory power beyond m the66 tradingsessions of the Bad News period. that of Rt , SMLt, and HMLt ina time-series Theseare sizable differences which would be regressionof stock returns. Columns (7)– (9) in difŽcult to explain unless they are attributed to Table7 showthe estimated coefŽ cients for the thedifferential effect of thetruce on Basqueand portfolioregressions when two additional fac- non-Basquestocks. tors, TERMt and DEFt,areincluded to re ect theterm and default risk premia of bonds, re- C. AlternativeModels spectively. 20 ThecoefŽ cients of the term and

TheFama-French Three-Factor Model pro- videsa popularempirical framework toestimate 20 Weconstructed TERMt as thedifference between the long-runnormal portfolio returns. However, it yieldon long-term government bonds and the one-month VOL.93NO. 1 ABADIEAND GARDEAZABAL:THE ECONOMICCOSTS OF CONFLICT 127

TABLE 7—PORTFOLIO REGRESSIONS, ALTERNATIVE MODELS

Fama-French Three-Factor Modelplus term andrisk MarketModel Constant-Mean-ReturnModel structurefactors Non- Non- Non- Basque BasqueDifference Basque BasqueDifference Basque BasqueDifference (1) (2) (3) (4) (5) (6) (7) (8) (9) Constant 20.00040.0001 20.0004 20.00030.0001 20.0004 20.00060.0000 20.0006 (0.0003)(0.0002) (0.0004) (0.0004) (0.0006) (0.0005) (0.0009) (0.0004) (0.0009) Rm 0.46960.9312 20.4617 0.67260.8083 20.1356 (0.0322)(0.0150) (0.0375) (0.0362)(0.0187) (0.0345) SMB 0.3645 20.22720.5917 (0.0461)(0.0237) (0.0445) HML 0.2553 20.14120.3964 (0.0398)(0.0208) (0.0382) TERM 0.02620.0247 0.0015 (0.0478)(0.0258) (0.0452) DEF 20.0341 20.08230.0482 (0.1643)(0.0917) (0.1577) GoodNews 0.00540.0002 0.0052 0.0100 0.0094 0.0006 0.0050 0.0006 0.0044 (0.0023)(0.0010) (0.0026) (0.0033) (0.0039) (0.0028) (0.0022) (0.0009) (0.0022) Bad News 20.00210.0004 20.0025 20.00170.0013 20.0030 20.0020 20.0002 20.0018 (0.0008)(0.0005) (0.0009) (0.0010) (0.0015) (0.0012) (0.0011) (0.0006) (0.0011) R2 0.39390.8887 0.3195 0.0257 0.0127 0.0053 0.4969 0.9109 0.5500

Notes: Heteroskedasticity-robuststandard errors are inparentheses.The sample periodconsists of 747trading sessions for 1998–2000.

riskstructure factors are small and not statisti- IV.Summary and Conclusions callysigniŽ cant. Moreover, the inclusion of the termand risk structure factors in theregression Muchhas been said about the pernicious ef- doesnot change the coefŽ cients and standard fectsof politicalcon ict on theeconomy. How- errors ofthe Good Newst and Bad Newst in a ever,to date little case study research has been substantiveway relative to columns (3)– (5) in producedon this matter. This article presents Table6, although the coefŽ cient of Bad Newst evidenceof a negativeeconomic impact of the inthedifference regression becomes marginally terroristcon ict in the Basque Country. The nonsigniŽcant at conventional levels. Overall, Žrst partof thisstudy shows a 10-percentaver- theresults of our event study appear to be agegap between Basque per capita GDP andthe remarkablyrobust to thechoice of themodel of percapita GDP ofa comparablesynthetic re- normalportfolio returns. 21 gionwithout terrorism which emerges over a periodof two decades. Moreover, changes in theper capita GDP gapare shown to be asso- ciatedwith the intensityof terroristactivity. The Treasurybill rate at t.We constructed DEFt as thediffer- ence between theyields on long-term corporate bonds and secondpart of this study uses the 1998 –1999 long-termgovernment bonds at t. cease-Žre asa naturalexperiment to measure 21 Nai FuChenet al.(1986) and others have suggested to theeffect of thecon ict on themarket value of use innovationsin macroeconomic variablesas factors ex- asampleof Basque and non-Basque Ž rms. We plainingstock returns. As afurtherrobustness check, we showthat Basque stocks outperformed non- extendedthe Fama-French modelincluding as additional factors theunexpected components of macroeconomic an- Basquestocks as thetruce became credible. At nouncements.Following Louis K. C.Chanet al.(1998), we theend of thecease-Ž re, Basque stocks showed proxiedthe unexpected components of macroeconomic an- nouncementsusing one-step-ahead forecast errors from ARIMA models,which we reestimated foreach macroeco- nomicannouncement. Just like the term andrisk structure ments were notsigniŽ cant anddid not change the coefŽ - factors,the factors related tomacroeconomic announce- cients ofinterest in any meaningful way. 128 THEAMERICANECONOMIC REVIEW MARCH 2003 anegativeperformance relative to non-Basque where 5 {(w1, ... , wJ)9 subject to w1 ... W stocks. 1 1 wJ 5 1, wj $ 0 ( j 5 1, ... , J)}, and Althoughwe focushere on the Basque X1, X0, and V areas describedin the text. The conict, the methods applied in this article can solutionto this problem, W*(V),dependson beused to investigate the economic effects of thediagonal matrix V whosediagonal elements conicts elsewhere. The application of thetech- areweights which re ect the relative impor- niquesin this article to the study of other con- tanceof the variables in X0 and X1.We selected ictswill also shed light on the robustness of V suchthat per capita GDP for theBasque theprocedure and serve as cross validation. countryduring the 1960’ s isbestreproduced by Researchof this sort could potentially have thesynthetic control deŽ ned by W*(V). Let Z1 anundesirable impact if terroristslearn that be a (10 3 1)vector containing the real per theiractions affect the economy negatively, as- capitaGDP valuesfor theBasque Country dur- sumingthat is what they want to do. However, ingthe period 1960 –1969.Let Z0 be (10 3 J) we dohopethat, as Paul S. Nelsonand John L. matrixcontaining the values of the same vari- Scott(1992) found that media attention does not ablesfor the J potentialcontrol regions. Then causeterrorism, academic attention does not causeterrorism either. V* 5

APPENDIX A: DATA SOURCES argmin ~Z1 2 Z0 W*~V!!9~Z1 2 Z0 W*~V!!, V [ V Dataon terroristactivity (deaths and kidnap- pings)are provided by the Spanish Ministry of where istheset of all nonnegative diagonal Interior(2002). Regional data on GDP, invest- (K 3 VK)matrices.The weights for thesyn- ment,population density, and sectoral produc- theticcontrol are given by W* 5 W*(V*). tioncome from Fundacio´nBBV(1999). Data Thereare inŽ nitely many equivalent solutions onhuman capital for differentregions have for V* [if V*isasolutionso is V*(c) 5 c z V* beencollected by Mas et al. (1998). In some for anypositive scalar c],sowe cannormalize instances,the series were onlyavailable on a theEuclidean norm of V*(or anypositive di- biennialbasis. In those cases, annual Ž gures agonalelement of V*) to one. were interpolatedas simple averages of the Alternatively,the synthetic Basque Country yearsimmediately preceding and following the couldbe chosento reproduceonly the per capita missingyears. The regions used for theanalysis GDP pathfor theBasque Country during the arethe 17 autonomous communities of Spain 1960’s: (leavingout the small autonomous towns of

Ceutaand Melilla on the coast of Africa). Oil W* 5 argmin ~Z1 2 Z0 W!9~Z1 2 Z0 W!. W [ pricescome from theOECD statisticalcompen- W diumCD-ROM. Data on stockprices, Ž rmsize (marketvalue of outstanding shares), book eq- Thesynthetic region chosen in this manner uity,and dividends are routinely collected by produceda largerGDP gapduring the terror- theMadridStock Exchange (w ww.bolsamadrid. ismyears than the one chosen to reproduce es).Interestrates on one-daypublic debt repur- economicgrowth predictors. However, this chaseagreements and bonds come from theBank procedurecould be less appropriate to con- ofSpain. Data on macroeconomic announce- structcounterfactual per capita GDP paths, mentscan be found at the Spanish National sinceit does not take into account information StatisticalInstitute’ s webpage (ww w.ine.es). aboutknown determinants of economicgrowth (likesectoral composition or human-capital APPENDIX B: TECHNICAL DETAILS endowments).

Estimationof Per Capita GDP Gap. —Con- Estimationof the Impulse-Response Func- siderthe problem, tion.—Sincethe number of periodsis smallwe adopteda convenientparameterization to esti- matethe impulse-response function. We started minimize ~X1 2 X0 W!9V~X1 2 X0 W!, W [ consideringa exibledynamic model with W VOL.93NO. 1 ABADIEAND GARDEAZABAL:THE ECONOMICCOSTS OF CONFLICT 129

TABLE B1—ESTIMATIONOF THE IMPULSE-RESPONSE FUNCTION

(1) (2) (3) (4) (5) m 20.2633 20.1060 20.1155 20.1438 (0.2176)(0.1969) (0.1982) (0.2038)

a1 1.36631.2279 1.2959 1.3141 1.3297 (0.2483)(0.2059) (0.1870) (0.1839) (0.1781)

a2 20.4624 20.3647 20.4076 20.4232 20.4301 (0.2277)(0.1752) (0.1639) (0.1623) (0.1597)

b0 20.0010 20.0075 20.0070 (0.0078)(0.0088) (0.0091)

b1 20.0195 20.0152 20.0224 20.0270 20.0284 (0.0091)(0.0093) (0.0091) (0.0080) (0.0082)

b2 20.0009 20.0144 (0.0087)(0.0112) r 0.0811 (0.2463) Numberof observations 40 41 41 41 41 R2 0.97640.9751 0.9740 0.9736 0.9732

Notes: Estimates ofthe parameters inequation(B1). Standard errors are inparentheses.

AR(1) disturbancessimilar to theone proposed tance[see, e.g., Whitney K. Neweyand Daniel byHarvey (1990, p. 268): McFadden(1994)]. The result is reported in TableB1 column (1). We proceededby sequen-

(B1) G t 5 m 1 a1 G t 2 1 1 a2 G t 2 2 1 b0 D t tiallyeliminating nonsigniŽ cant parameters in columns(2)– (5), which are estimated by least

1 b1 Dt 2 1 1 b2 D t 2 2 1 u t , squares.Our preferredspeciŽ cation, which containsterms in Gt21, Gt 22, and Dt2 1 is ut 5 rut 2 1 1 «t , reportedin column (5). Inverting the autore- gressiveterms, we obtainthe impulse-response where Gt and Dt arerespectively the per capita function: GDP gapand number of deathvictims in period t, and « areserially independent shocks. The 0 if s 5 0 t ­G vectorof unknownparameters u 5 (m, a , a , t 1 s 1 2 ds 5 5 b1 if s 5 1 ­D t b0, b1 , b2, r)9 isto be estimated. Note how- 5a1ds 2 1 1 a2ds 2 2 if s $ 2, ever,that equation (B1) cannot be directlyesti- matedby leastsquares, since the error term ut is where s runsover nonnegative integers. We correlatedwith Gt21 and Gt2 2 byconstruction. reportstandard errors thatare robust to mis- Expressing ut21 interm of lagsof Gt and Dt we speciŽcation. ConŽ dence intervals for theimpulse- get: responsesin Figure3 were constructedapplying thedelta method. Likelihood-based error bands (B2) asinChristopher A. Simsand Tao Zha (1999) producedsimilar results. G t 5 p0 1 p1 G t 2 1 1 p2 G t 2 2 1 p3 G t 2 3 Calculationof Portfolio Returns and Risk 1 D 1 D 1 D p4 t p5 t 2 1 p6 t 2 2 Factors.—We collecteddaily end-of-the-day stockprices from Madrid’s continuous-trading 1 1 « p7 D t 2 3 t , stockexchange market for thesample period January2, 1998 –December29, 2000, for atotal wherethe vector 5 (p0, p1, ... , p7)9 is a of748 daily observations. We restrictedthe nonlinearfunction of u .We estimatedequation analysisto Ž rms withcomplete data for the (B2)consistently by leastsquares for theperiod sampleperiod. This restriction eliminates all 1955–1997. The parameters in u were recov- Žrms whichentered the market during the sam- eredfrom theestimates of byminimum dis- pleperiod, had their quotation suspended or 130 THEAMERICANECONOMIC REVIEW MARCH 2003 mergedwith another Ž rm inthe data Ž le.This ketvaluation. The Basque portfolio contains 14 resultedin a sampleof 81 Ž rms. During1998, stocksand the non-Basque portfolio 59 stocks. stockprices were quotedin Spanish pesetas. TableB2 provides a listof the stocks in the Startingin January 4, 1999, quotations were in Basqueand non-Basque portfolios. euros,thus requiring adjustment by multiplying Thebuy-and-hold portfolios constructed at theeuro Ž guresby the 166.386 peseta/ euro thebeginning of the sample were value Žxedexchange rate. Stock prices were alsoad- weighted.There is no rebalancing (buying or justedfor splits.Then, daily returns were cal- sellingstocks) in the buy-and-hold portfolios, j culatedand adjusted for dividendsand equity reecting a passiveinvestment strategy. Let Vi,t issue(also adjusted for peseta/euroconversion bethe market valuation of all shares of stock i j andsplits). The return on the market portfolio heldin portfolio j in period t. Let Vt be the was proxiedby therate of changeof thegeneral marketvaluation of portfolio j at time t, that is indexof the Madrid Stock Exchange (IGBM) andthe risk-free assetreturn was takento bethe n j V j 5 Vj , returnon the one-day public debt repurchase t O i,t agreements.To construct the size and book-to- i 5 1 marketportfolios, we proceededas in Fama where nj isthe number of stocksin portfoli o j andFrench. Information of size and book-to- j. Let Ri,t bethe market return of stock i in marketratio was notavailable for 7Žrms which portfolio j betweenperiods t 2 1 and t. The reducedthe sample to 74Žrms. We Žrst ranked buy-and-holdinvestme ntstrategyimplies that j j j j stocksaccording to market size and the median V i,t 5 (1 1 Ri,t)Vi,t21 for all t, hence Vt 5 nj j j j nj was usedto split the sample in two groups, ¥ i51 (1 1 Ri,t)Vi,t21 5 Vt21 1 ¥ i51 j j small(S) andbig (B). Then,we classiŽed stocks R i,tVi,t21.Therefore,the return of portfolio j intothree book-to-market groups: the bottom 30 betweenperiods t 2 1 and t is given by percent(L), middle40 percent (M), andtop 30 j j percent(H). Thesize and book-to-market Ž g- Vt 2 Vt 2 1 R j 5 uresused in 1998,1999, and 2000 correspond to t Vj theend of 1997,1998, and 1999 Ž gures,respec- t 2 1 tively.Then, we constructedsix portfolios (S/ L, nj j Vi,t 2 1 S/M,S/H,B/L,B/M,andB/ H)andcomputed 5 Rj O i,tX Vj D dailyvalue-weighted returns on those portfo- i 5 1 t 2 1 lios.The size portfolio used in theregressions is thedaily difference between the average return nj 5 Rj j , onthesmall-size portfolios (S/ L,S/M,andS/ H) O i,tv i,t 2 1 andthe average return on thebig-size portfolios i 5 1 (B/L,B/M,andB/ H). Thebook-to-market port- j j j foliois thedaily difference between the average where v i,t 5 Vi,t/Vt isthe weight of stock i returnon the high book-to-market portfolios inportfolio j at time t.Theevolution of (S/HandB/ H)andthe average return on thelow weightsover time is describedby thefollowing book-to-marketportfolios (S/ LandB/ L).The equation: termpremium factor is the difference between Vj theaverage yield on long-term(ten-year or more) j i,t governmentbonds, and the one-month Treasury v i,t 5 j Vt billrate. The default premium factor is the differ- encebetween the average yield on long-term j j ~1 1 R !V 2 (ten-yearor more) corporateand the average yield 5 i,t i,t 1 nj Vj onlong-term (ten-year or more) government j i,t 2 1 j 1 1 ¥ Ri,t j Vt 2 1 bonds. X i 5 1 X V t 2 1 DD We thencomputed calendar time returns on j j buy-and-holdBasque and non-Basque portfo- ~1 1 Ri,t!v i,t 2 1 lios.We excludedan additional Basque Ž rm 5 nj . sinceits market valuation accounted for 75per- j j 1 1 ¥ Ri,tv i,t 2 1 centof thevalue of Basqueportfolio total mar- i 5 1 VOL.93NO. 1 ABADIEAND GARDEAZABAL:THE ECONOMICCOSTS OF CONFLICT 131

TABLE B2—LIST OF STOCKS

BasqueStocks ACR Aceralia Corporacio´nSideru´rgica,S.A. FAEFaes Fa´brica Esp.Prod. Qu ´‡micos yFarma. ASA TavexAlgodonera, S.A. GUI BancoGuipuzcoano, S.A. AZK AzkoyenS.A. KOI Koipe,S.A. BYB Bodegasy Bebidas,S.A. TUBTubacex,S.A. CAF Construccionesy Auxiliarde Ferrocarril VAS Bancode Vasconia, S.A. CPL Cementos Portland VID Vidrala,S.A. EUR EuropistasConcesionaria Espan ˜ola,S.A. VIS Viscofan,S.A. Non-BasqueStocks ACE AutopistasConcesionaria Espan ˜ola,S.A. GCO Catalana Occidente,S.A. ACS Actividadesde Const. y ServiciosS.A. GPP GrupoPicking Pack, S.A. ACX Acerinox,S.A. IBG IberpapelGestio ´n,S.A. ADZ Adolfo Dom´‡nguez,S.A. MAPCorporacio ´nMapfre,Cia. Int. de Reaseguros AGS Sdad.General Aguasde Barcelona,S.A. MDFGrupo Duro Felguera, S.A. ALB Corporacio´nFinancieraAlba, S.A. MPVMapfreVida, S.A. ALD Aldeasa, S.A. MVCMetrovacesa, S.A. ANA Acciona,S.A. NEANicolas Correa,S.A. AND Bancode Andaluc ´‡a NMQ NuevaMontan ˜adeQuijano, S.A. ARA Energ´‡aeIndustriasAragonesas, S.A. PASBancoPastor, S.A. AZC Asturianadel Zinc, S.A. PIN Prima Inmobiliaria,S.A. BAM Bami, S.A.Inmobiliaria de Construcciones POPBancoPopular Espan ˜ol,S.A. BKT Bankinter,S.A. PSG Prosegur,S.A., Cia. de Seguridad BVA Bancode Valencia, S.A. PUL Puleva,S.A. CAN Hidroele´ctrica delCanta ´brico,S.A. REPRepsol,S.A. CAS Bancode Castilla, S.A. RIO BodegasRiojanas, S.A. CBL Bancode Cre ´ditoBalear, S.A. SED Sedade Barcelona,S.A. (LA) CEP Cia.Espan ˜olade Petroleos,S.A. SOL SolMelia ´,S.A. CPF CampofrioAlimentacio ´n,S.A. TEF Telefo´nica,S.A. CRI Cristaleria Espan˜ola,S.A. UBSUrbanizaciones y Transportes,S.A. CTF CorteŽel, S.A. UNF Unio´nEle´ctrica-Fenosa, S.A. CTG Gas Natural SDG,S.A. (Catalana Gas) UPLUnipapel,S.A. DIN Dinamia CapitalPrivado, S.A. URA Uralita, S.A. DRC GrupoDragados, S.A. URB InmobiliariaUrbis, S.A. ECR Ercros S.A. VAL Vallehermoso,S.A. ELE Endesa,S.A. VDR PortlandValderrivas, S.A. ENC GrupoEmpresarial Ence,S.A. ZNCEspan˜oladel Zinc, S.A. FCC Fomentode Construcciones y Contratas,S.A. ZOT ZardoyaOtis, S.A. FIL Filo, S.A. ZRGBancoZaragozano, S.A. GAL Bancode Galicia, S.A.

Thestarting values of the weights were calcu- Aldcroft,Derek H. TheEuropean economy, j j j j lated as v i,0 5 Mi,0/M0, where Mi,0 is the total 1914–1990.New York:Routledge, 1993. marketvalue of all outstanding shares of stock Alesina,Alberto; Ozler, Sule; Roubini, Nouriel j i inportfolio j inperiod 0 and M0 is the total and Swagel,Phillip. “PoliticalInstability and marketvalue of alloutstanding shares of stocks EconomicGrowth.” Journalof Economic includedin portfolio j.Therefore,at thebegin- Growth, June 1996, 1(2),pp. 189 –211. ningof thesample, the buy-and-hold portfolios Alesina,Alberto and Perotti,Roberto. “Income were value-weightedportfolios. Distribution,Political Instability and Invest- ment.” EuropeanEconomic Review , June REFERENCES 1996, 40(6),pp. 1203– 28. Barro,Robert J. “EconomicGrowth in a Cross Acemoglu,Daron and Robinson,James A. “A Sectionof Countries.” QuarterlyJournal of Theoryof Political Transitions.” American Economics, May 1991, 106(2),pp. 407– 43. EconomicReview ,September2001, 91(4), Barro,Robert J. and Sala-i-Martin,Xavier. Eco- pp. 938–63. nomicgrowth .New York:McGraw-Hill, 1995. 132 THEAMERICANECONOMIC REVIEW MARCH 2003

Benhabib, Jessand Rustichini,Aldo. “Social Programin Development Studies (Princeton, Conict and Growth.” Journalof Economic NJ) WorkingPaper No. 206, May 2002. Growth,March1996, 1(1),pp. 125– 42. Kurlansky,Mark. TheBasque history of the Campbell,John Y.; Lo,Andrew W.and MacKin- world.New York:Walker & Co.,1999. lay,A. Craig. Theeconometrics of Ž nancial Londregan,John B. and Poole,Keith T. “Poverty, markets.Princeton,NJ: PrincetonUniversity theCoup Trap, and the Seizure of Executive Press, 1997. Power.” WorldPolitics ,January1990, 42(2), Chan, LouisK. C.;Karceski, Jason and Lakon- pp. 151–83. ishok,Josef. “TheRisk and Returns from Fac- Lyon,John D.; Barber,Brad M. and Tsai,Chih tors.” Journalof Financial and Quantitative Ling. “ImprovedMethods for Testof Long- Analysis, June 1998, 33(2),pp. 159 –88. RunAbnormal Stock Returns.” Journal of Chen, NaiFu; Roll,Richard and Ross,Stephen A. Finance,February1999, 54(1),pp. 165– 201. “EconomicForces and the Stock Market.” Jour- Mankiw, N.Gregory. “TheGrowth of Nations.” nalof Business , July 1986, 59(3),pp. 383– 403. BrookingsPapers on Economic Activity, CNN. Basquecon ict:Vio lencein Spa in . 1995,(1), pp. 275– 310. Onlineat http:/ /www.cnn.com/SPECIALS/ Mas,Matilde; Perez, Francisco; Uriel, Ezequiel 2001/basque/,2001. and Serrano,Lorenzo. Capitalhumano, series Collier,Paul and Hoefer, Anke. “Greed and histo´ricas .Valencia:Fundacio ´nBancaixa, Grievancein CivilWar” Centre for theStudy 1998. ofAfricanEconomies (Oxford, U.K.) Work- Mauro,Paolo. “Corruptionand Growth.” Quar- ingPaper No. 2002-01, March 2002. terlyJournal of Economics ,August1995, Enders,Walter and Sandler,Todd. “Causality 110(3),pp. 681– 712. betweenTransnational Terrorism andTour- Nelson,Paul S.and Scott,John L. “Terrorism and ism:The Case of Spain.” Terrorism, 1991, theMedia: An Empirical Analysis.” Defence 14(1),pp. 49 –58. Economics, 1992, 3(4),pp. 329 –39. . “Terrorism andForeign Direct Invest- Newey,Whitney K. and McFadden, Daniel. mentin Spain and Greece.” Kyklos, 1996, “LargeSample Estimation and Hypothesis 49(3),pp. 331– 52. Testing,”in Robert F. Engleand Daniel L. Fama,Eugene F. and French,Kenneth R. “The McFadden,eds., Handbookof econometrics , Cross-Sectionof Expected Stock Returns.” Vol.4. New York:Elsevier Science, 1994, Journalof Finance , June 1992, 47(2), pp. pp.2111– 245. 427–65. Olson,Mancur. “RapidGrowth as a Destabiliz- . “CommonRisk Factors in the Returns ing Force.” Journalof Economic History , onStocks and Bonds.” Journalof Financial December1963, 23(4),pp. 529 –52. Economics,February1993, 33(1),pp. 3– 56. Rosenbaum,Paul R. Observationalstudies . New Fundacio´nBBV. RentaNacional de Espan˜aysu York:Springer-Verlag, 1995. Distribucio´nProvincial .Bilbao:Fundacio ´n Sims,Christopher A. and Zha, Tao. “Error Bands BBV, 1999. for ImpulseResponses.” Econometrica , Sep- Gupta, Dipak K. Theeconomics of political vi- tember1999, 67(5),pp. 1113– 55. olence.New York:Praeger, 1990. Spanish Ministryof Interior. Relacio´n v´‡ctimas Harvey,Andrew C. Theeconometric analysis of delterrorismo , 2002. time series.New York:Philip Allan, 1990. Temple,Jonathan. “TheNew GrowthEvi- Hibbs, DouglasA. Masspolitical violence: A dence.” Journalof Economic Literature , cross-sectionalanalysis .New York:Wiley March 1999, 37(1),pp. 112– 56. andSons, 1973. The Economist . “RobustBasques and Regional Kho,Bong Chan; Lee,Dong; Stulz, Rene M. “U.S. Catalans.”Spain Survey, November 25, Banks,Crises, and Bailouts: from Mexicoto 2000,pp. 12– 13. LTCM.” AmericanEconomic Review , May 2000 Venieris,Yiannis P. and Gupta, Dipak K. “Income (Papersand Proceedings ), 90(2),pp. 28 –31. Distributionand Sociopolitical Instability as Krueger,Alan B. and Maleckova,Jitka. “Educa- Determinantsof Savings: A Cross-sectional tion,Poverty, Political Violence and Terror- Model.” Journalof Political Economy , March ism:Is Therea CausalConnection?” Research 1986, 94(4),pp. 873– 83.