The Effects of Conflict on the Structure of the Economy

Transcription

1 The Effects of Conflict on the Structure of the Economy Nicolás M. Depetris Chuvin Dubi School of Government Oxford Centre for the Anlysis of Resource Rich Economies

2 Abstrct: The presence of conflict ffects people s economic incentives. Some sectors of ctivity flourish, while others suffer. For understnding structurl problems in developing countries nd designing pproprite post-conflict reconstruction policies, it is essentil to understnd in wht wys conflict ffects the structure of the economy. We develop simple model of conflict nd multiple sectors of ctivity, where conflict efforts, the lloction of fctor endowments nd the production outputs re endogenous. We predict tht for modertely destructive conflicts lbor-intensive sectors re most ffected by fighting, while for highly destructive conflicts cpitl-intensive sectors suffer most. In the ltter cse, under some conditions it is lso possible tht in the presence of endogenous conflict - n increse in the price of the cpitl-intensive commodity reduces the output of this sme good. The model further predicts tht export-sectors nd sectors tht require inter-temporl investments re prticulrly exposed to conflict ctivity. In the empiricl prt of the pper, we study the impct of vrious forms of conflict, seprtely nd s n ggregte conflict index constructed with principl component nlysis. We present some bsic stylized fcts bout the effect of conflict on the productive structure of the economy. Conflict reduces the shre of the mnufcturing sector in the GDP, increses the exploittion of some simple nturl resources (i.e. forestry) nd reduces the production of crops. Using industril level dt for developing countries we study the chnnels through which conflict ffects the mnufcturing sector. As expected, we find tht industries tht re more institutionl/trnsction intensive re the ones tht suffer most in conflictive societies. borintensive sectors re lso negtively ffected by conflict. It is lso found tht exporting industries nd sectors requiring externl finncing suffer more during conflict. Our results re robust to sensitivity nlysis. eywords: Conflict, Production Structure, Resource Curse, Post-Conflict Reconstruction. JE Clssifiction: D74, O3, O4. Acknowledgements: We would like to thnk seminr prticipnts in Oxford for helpful comments, nd OxCrre for its hospitlity.

3 . Introduction Nicrgu nd Cost Ric re neighboring countries tht shre the sme colonil pst, the sme Independence Dy, the sme lnguge, nd similr geogrphy nd resource endowment. Fifty yers go their level of development ws similr. However, nowdys, Cost Ric s per cpit GDP is pproximtely five times lrger thn Nicrgu s. Cost Ric rnks 48 th in the Humn Development Index, while Nicrgu rnks 0 th. Their productive structures lso reflect their divergent development pth. Electronics, phrmceuticls, finncil outsourcing, softwre development, nd ecotourism hve become the prime industries in Cost Ric's economy. In contrst, the Nicrgun economy is still bsiclly grrin nd bsed on the production nd export of csh crops such s bnns, coffee, sugr, nd tobcco. Wht re the resons for such divergent pth? While it is hrd to point out only one fctor, probbly prt of the explntion comes from the fct tht in the lst 50 yers Cost Ric hs enjoyed greter pece nd more consistent politicl stbility thn Nicrgu, tht went through long period of dicttorships, the Sndinist rebellion during the 970s nd the Contr Wr during the 980s. The purpose of this pper is to study the effects of conflict on the production structure of the economy. Our hypothesis is tht civil conflict is one of the underlying resons for structurl economic problems in poor countries. Of course, we lso recognize tht more underdeveloped economies hve higher propensity to suffer conflicts due to the lower opportunity cost. We re wre of this endogeneity nd perverse dynmics. In this pper, we emphsize the prt of the reltionship tht hs been less studied, i.e. how conflicts shpe the development pth. Civil wrs led to poorly-developed mnufcturing sector tht does not llow for the incorportion of low-skilled workers, which increses inequlity. It lso leds to the under-exploittion of some nturl resources nd the over-exploittion of others, wht could led to environmentl degrdtion nd incresing poverty. This study is mostly empiricl. After building simple forml model tht highlights the vrious chnnels through which conflict mtters, we construct indices of conflict using different mesures of socio-politicl instbility. With the help of principl components nlysis they re combined in single index. Some bsic stylized fcts of the effect of conflict on the productive structure of the economy re then presented. We find tht conflict reduces the shre of the

4 mnufcturing sector in the GDP, increses the exploittion of some simple nturl resources (forestry) nd reduces the production of crops. We find inconclusive evidence on the effects of conflict on the shre of the griculturl nd service sector in the GDP. We subsequently focus on explining the observed negtive ssocition between conflicts nd mnufcturing growth. Using industril level dt for developing countries we study the chnnels through which conflict my ffect the mnufcturing sector. This dtset llows within country, between industries differences, beyond the trditionl between country differences of the cross-countries studies. As expected, we find tht industries tht re more institutionl/trnsction intensive re the ones tht suffer the most in more conflictive societies. Surprisingly, we find tht lbor-intensive industries rther thn the cpitl-intensive ones experience the worst outcomes in more conflictive countries. We present severl explntions for this result, which is t odd with previous findings of Collier (999). Further, we lso find tht exporting industries nd those sectors requiring externl finncing suffer more during conflict. Our results re robust to sensitivity nlysis. This pper reltes to three brnches of the economics literture. The first brnch is the literture on instbility nd growth using cross-countries regressions. Brro (99) nd Alesin et l (996) find tht greter instbility lowers the growth rte of country. The inverse reltionship lso seems to exist. ondregn nd Poole (990) find tht lower economic growth increses instbility, while Miguel et l (004) conclude tht low growth rtes result in higher risk of civil wrs. In contrst, Alesin et l (996) find tht this effect is only importnt for Coups d Ett. Alesin nd Perotti (995), using composite index for instbility, test chnnel for the inverse reltionship between income inequlity nd growth: income inequlity fuels socil discontent nd increse socio politicl instbility, this cretes uncertinty reducing investment nd therefore growth. This pper lso reltes to the literture on the economics of civil wr. While numerous ppers focus on the cuses of wr, only few ppers study the economic effects of conflict. Collier (999) distinguishes four different economic effects of civil wr: diversion of public resources from productive ctivities to violence, time horizons shortened leding to opportunistic

5 behvior, lost of humn nd finncil cpitl, nd shift wy from vulnerble economic ctivities towrds those tht re less vulnerble. Rohner (006) shows tht conflict cn led to under-exploittion of renewble nturl resources nd over-exploittion of resources with negtive future externlities. From the methodologicl point of view, our pper is lso relted to the literture initited by Rjn nd Zingles (998) emphsizing the comprison of different industries within countries. Most of the empiricl studies ssessing the economic effects of conflict only focus on ggregte mesures of instbility nd growth. Collier (999) is one exception. He uses ntionl ccount dt for Ugnd before nd fter the socil disturbnce tht strted in 97 when President Idi Amin declred economic wr ginst the resident Asin community. He finds importnt chnges in the composition of economic ctivity tht he ttributes to the conflict. To our knowledge, our pper is the first to study systemticlly the effects of conflict on the production structure of country using industril level dt for lrge cross section of countries. Given the importnt economic effects of conflict, our findings re importnt for the understnding of post conflict dynmics, the kind of policies needed to reduce the risk of further conflict, nd the policy constrints nd opportunities the new configurtion of the economy imposes. The rest of this pper proceeds s follows. In the next section we provide brief discussion of the definition nd estimtion of our mesure of conflict. In section 3, we describe our dt nd smple period. In section 4, we derive theoreticl predictions of the effects of conflict on the economy nd provide in section 5 some stylized effects of conflict on the structure of the economy using our smple of developing countries. In section 6 of the pper, we present nd estimte some plusible chnnels through which conflict ffects the production structure of the economy nd in section 7 we conclude. It my lso hve policy implictions on how post conflict id should be llocted. According to the new regultions, t lest 0% of the IDA budget should be llocted to post conflict countries.

6 . Definition nd Mesurement of Conflict We shll not focus only on civil wrs like most of the literture, but tke into ccount other dimensions of conflict, such s coups nd politiclly motivted ssssintions, leding to politicl nd socil instbility. The keen interest in politicl science nd economics for understnding the cuses of civil conflicts hs led to the development of severl dtsets, using diverse sources, nd trying to cpture severl dimensions of the phenomen, such s durtion, intensity nd loction. This welth of informtion leds to the prcticl problem of how to define conflict nd how to mesure it. Hibbs (973) ws one of the first to notice this problem nd suggested to concentrte on six components of politicl violence: riots, nti-government demonstrtions, politicl strikes, rmed-ttck events, nd deths from group violence. Following this pioneering work we decided to nrrow our definition of conflict looking to the following five ctegories: number of politiclly motivted murder of government officils (Bnks 008), numbers of coups (Bnks 008), dummy vrible for civil wr onsets (PRIO dtset, cf. Gleditsch et l 00), the number of deths in civil wrs s proportion of the popultion (Gleditsch et l 00) nd the democrcy/utocrcy index (Polity IV project summrized in Mrshll nd Jggers 000). The first two vribles reflect politicl instbility nd socil conflict tht my or my not led to civil wr. Our third vrible is n indictor for the incidence of civil conflict nd our fourth vrible works s proxy for its intensity. The index for democrcy nd utocrcy is included to correct for possible underreporting in ny of our previous four vribles in utocrtic regimes. When selecting our series, we re ssuming tht the more complete the source of coverge the more likely the dt re to reflect the true distribution of events. As reserchers our min concerns re whether different sources provide dt tht yield the sme underlying

7 structure mong conflict situtions nd if these sources provide dt tht led to the sme substntive conclusions in hypothesis testing nd model building (Jckmn nd Boyd, 979). For tht reson, we will provide throughout our nlysis robustness checks using different dimensions nd sources for our dt. To combine the five selected vribles into single index for our econometric estimtions we follow Alesin nd Perotti (996) nd employ principl components nlysis to crete n index of conflict 3. We use the first principl component of the five vribles listed bove to construct our Conflict Index =.34 Assssintions +.5 Coups Onset Civil Wr Deth in Civil Wr Autocrcy. All the estimted signs re s predicted by the theory. Since we stndrdized ll the vribles ppering in the index, the order of mgnitude of the effects of ech vrible re comprble. The first component explins round 30% of the totl vrince. In order to verify the relibility of our conflict index, we precede to some robustness checks. The first check consists in introducing sensible vritions to the index. We selected five vribles bove to estimte our index. However, Bnks (008) hs severl other lterntive vribles to mesure politicl instbility nd conflict. We use these lterntive vribles (see Appendix B for the list) to estimte other versions of the conflict index. In ll cses, the expected sign corresponds to the one predicted by the theory. In most cses, the indices order the countries in the sme wy nd when they do not, the differences re negligible. The second robustness check for our conflict index consists in compring the countries rnk order with the fcts. In section 5, we will focus on the economic effects of conflicts during the 980s. For tht reson, we re prticulrly interested in gurnteeing the qulity of the conflict index for dt of the lte 970s nd the 980s. According to our index, El Slvdor, Peru, Philippines, Guteml nd Irn were the most conflicted countries during tht period. In contrst, Cote d Ivoire, esotho, Jordn, Mlwi, nd Albni were the less conflictive during the See Theil (97) for description of the principl components method. 3 Venieris nd Gupt (986) nd Gupt (990) construct similr indexes by pplying the method of discriminnt nlysis to lrge smple of countries.

8 980s in our smple of developing countries. To check for the ctul fcts, we use the Encyclopedi of Conflicts since World Wr II (Edited by Ciment, 006). According to this book, ll our five top countries suffer from conflict in the 980s: El Slvdor Civil Wrs (970s nd 980s), Peru Shining Pth Rebellion (970s-997), Philippines Moro Uprising (970s-980s), Guteml Civil Wr (970s-990s), nd Irn the Islmic Revolution in 979 nd the Wr with Irq ( ). None of the five less conflict countries in our index suffered mjor politicl instbility during the 980s. Further, when we estimte the sme index using only dt for the 990s nd beginning of 000s, the rnking significtively chnges nd once gin the top nd bottom countries corresponds with the nrrtive in Ciment s book. In section 4 nd 5, we will further discuss the robustness of our results to chnges in the specifiction of our conflict index. 3. Dt nd Smple Period Our min tsk will be to look t the effects of conflict cross industries in developing countries. For tht purpose, we use the Industril Sttistics Dtbse (003) of the United Ntions Industril Development Orgniztion (UNIDO). This dt is vilble t the 3-digit level of the Interntionl Stndrd Industril Clssifiction (ISIC, revision ) for bout forty yers. The vlue dded dt is only extensively vilble in the 980s nd therefore we focus on tht period to keep our smple s lrge s possible 4. We would like to focus on long-term growth nd t the sme time use the most relible dt vilble. On tht bsis, our first selection criterion is to include those industril sectors for which we hve enough observtions to compute the verge vlue dded growth rte over t lest five-yer period in the 980s. Our im is to study the effects of conflict on the economic structure only in the developing world nd for countries tht re roughly comprble. For tht 4 During the robustness nlysis we use dt for the 990s, resulting in much smller smple size.

9 reson, our second selection criterion is to include in our nlysis only low-income nd low middle-income countries. Our cut off is per cpit GDP PPP lower thn $7000 (constnt 000 interntionl $) in 980, the first yer of our smple. Applying the two criteri reduces our smple to the 50 developing countries in Appendix A. The UNIDO dtbse contins dt on 8 industries in these countries (see the first two columns in Appendix C for description). The rest of the dt is stndrd. The mnufcture, griculturl, nd service dt s shre of GDP is from the World Development Indictors (WDI). The forestry volume dt nd the crop index dt come from the Food nd Agriculturl Orgniztion (FAO). The dt nd their sources re described in detil in Appendix B. 4. The Effects of Conflict on the Economy: Theory 4. The Setting In this section, we present simple model of endogenous conflict to illustrte the plusible chnnels through which conflict my ffect the structure of the economy. We strt from stndrd model of n interntionlly open country with two sectors nd two fctors of production, s described in Jones (965). Similr to Dl Bo nd Dl Bo (008), we include pproprition in this frmework. In their model the min effect of pproprition is to reduce the vilble lbor endowment. In severl respects our frmework is complementry to theirs: First, their model cptures mostly orgnized crime not leding to cpitl destruction, wheres we include government nd rebel contest s occurring in civil wrs nd resulting in cpitl destruction. Second, while they emphsize the impct of shocks nd vrious policies on the intensity of pproprition, our focus lies mostly on generting empiriclly testble predictions of how conflict ffects the structure of the economy. Thus, in contrst to Dl Bo nd Dl Bo (008) s purely theoreticl contribution, we llow for vrious dditionl chnnels through which conflict mtters, which will then guide our empiricl strtegy.

10 There re two sectors, nd, nd two fctors of production, cpitl nd lbor, where the totl fctor endowments re, resp.. The output prizes re denoted p, resp. (p is normlized to ), the fctor prizes re r per unit of nd w for unit of. The cpitl nd lbor tht is engged in the sectors nd, re lbeled,,, nd respectively. The production functions tke eontieff form nd re s follows: () Y min ;, Y min, where,,, re the mounts of production fctors required to produce unit of output of the commodities nd, respectively. Additionlly there re two conflict ctivities: bor cn be spent for government soldiering, G, nd for rebellion, R. The vlue of rents secured trough pproprition is s follows: () Y G G N ; R Y N R G R G R where N=rents from nturl resources. The bove expression cptures the bsics of conflict over resource rents. 5 As in Dl Bo nd Dl Bo (008) it is ssumed tht pproprition is lbor-intensive. In contrst, however, we tke into ccount tht prt of cpitl is destroyed in conflict. In prticulr, the disposble 5 N could lso be interpreted s some other prize to be pproprited, like e.g. foreign id or ego rents from office.

11 income in the presence of conflict becomes G ), where prmeter cptures how cpitl-destructive conflict is. ( R All results below would go through if we llowed for prt of production output being cptured in conflict or if we included prticulr fighting technologies (such s in Rohner, 006). Further, including cpitl in the contest success functions or llowing for further forms of lbordestruction in conflict would not chnge the qulittive implictions of the frmework. Wht is crucil for our results is tht in conflict both totl disposble cpitl nd lbor re reduced nd tht in some instnces either or re reltively more strongly ffected. 4. The Equilibrium Exogenously given re the reltive output price p, the production technology prmeters,,,, the fctor endowments nd, nd the nturl resource rents N. Endogenously derived will be the fctor prices r nd w, the production nd pproprition fctor lloctions,,,, G nd R nd the output nd pproprition levels Y, Y, Y G, nd Y R. We shll strt by chrcterizing the fighting equilibrium. The first order conditions led to the following rection functions 6 (note tht the lbor opportunity costs w G, resp. w R re included in the optimiztion functions): (3) RF G R N ( R ) G R ; w RF ( R G ) R G G w N 6 The FOC s for the Nsh Equilibrium led directly to the solution but we follow the literture in showing the rection functions first.

12 The intersection of the two rection functions corresponds to the Nsh Equilibrium 7, which tkes the following vlues: * G * R N /(4w). These vlues feed into the production equtions. Now the lbor endowment tht is disposble for production becomes: * * N /(w). Similrly, the cpitl vilble for production becomes G R ( * G ) ( N ) /(w). The following lemm is intuitive: * R emm : Conflict is most intensive (i.e. high G nd R ) in countries with low slries (i.e. low w) nd lrge rents from nturl resources (i.e. high N). * * * * Proof: Follows from G / w 0, R / w 0, G / N 0, R / N 0. This is consistent with the empiricl studies of the determinnts of civil wr (Collier, Hoeffler nd Rohner, 009). We shll initilly focus on competitive production equilibrium with n interior solution (i.e. without speciliztion). Thus, the following conditions hve to hold. The zero-profit condition implies: (4) r w ; r w p The production fctors re fully employed when: 7 We focus in the Nsh Equilibrium tht is the stndrd solution in the literture of conflict when there re strtegic interctions. However this my not be the only solution s other sort of equilibrium constructs re possible. For instnce, the government might tke ccount of the effects of its own choice on the choice of the rebel leder, or vice vers. Also, if conflict is costly nd commitment technologies were vilble, (coopertive) rent shring equilibrium could be sustinble.

13 (5) ) ) /( ( w N Y Y ; ) /( w N Y Y This leds to following fctor prices nd output levels: (6) p w ; p r (7) w N w N Y )] /( [ )] ) /( ( [ (8) w N w N Y )] ) /( ( [ )] /( [ Introducing w into Y, resp. Y we obtin: (9) ) ( ) ( p N p N Y (0) ) ( ) ( p N p N Y

14 We shll now perform some comprtive sttics. Without loss of generlity we cn ssume tht sector is cpitl-intensive nd tht >, <. The following intermedite result is strightforwrd: emm : An increse in the price of the cpitl-intensive good p increses r, reduces w nd in this wy leds to higher conflict efforts G, resp. R. Proof: The first hlf of this lemm is simply the well-known Stolper-Smuelson result nd follows from r / p 0, resp. w / p 0 in eqution (6). The second hlf of this lemm follows from G / w 0, resp. R / w 0 in eqution (3). A vrint of this intermedite result of emm is lso found in Dl Bo nd Dl Bo (008) s relted model of crime. In contrst, the rest of our results presented below re novel, nd hve to the best of our knowledge not been obtined before in the literture. Now, we shll nlyze whether cpitl- or lbor-intensive sectors suffer most from conflict. Proposition : For modertely destructive conflicts (i.e. low μ) lbor-intensive sectors suffer most, while in very destructive conflicts (i.e. high μ) cpitl-intensive sectors re most ffected. Proof: For low levels of μ the reduction in disposble lbor previls, while for lrge levels of μ the decrese in vilble cpitl domintes. It follows from equtions (9) nd (0) tht in the former cse the reltive size of the lbor-intensive sector shrinks, while in the ltter cse the cpitl-intensive sector is downsized.

15 Empiriclly, conflict is mostly cpitl-destructive in rich countries, where fighting technologies re more powerful nd high-profile trgets re redily vilble. 8 In these countries lso non-tngible forms of cpitl like brnd nmes or reputtion for politicl stbility re most frgile. This leds to the following corollry: Corollry : Empiriclly, conflicts in low-income countries re expected to hurt lbor-intensive sectors most extensively, while in high-income countries cpitl-intensive sectors re most ffected by conflict. Proof: Follows from Proposition. Interestingly, this is consistent with the empiricl evidence tht driving forces nd effects of conflict re very different for rich versus poor countries (Collier nd Rohner, 008). Next, we shll ssess how price chnges ffect the outputs of the two sectors. Proposition : If conflict is not very destructive (i.e. low μ), mrginl increse in the reltive price of the cpitl-intensive commodity, p, increses the output Y of the corresponding sector nd decreses the output Y of the lbor-intensive sector. In contrst, if conflict is very destructive (i.e. high μ), mrginl increse in p decreses the output Y of the cpitlintensive sector nd increses the output Y of the lbor-intensive sector. Proof: Follows from equtions (9) nd (0). If μ is low: Y p 0, Y p 0. In contrst, if μ is lrge: Y p 0, Y p 0. / / / / 8 Our findings contrst with Dl Bo nd Dl Bo (008) s prediction tht conflict lwys hrms lbor intensive sectors most, which is driven by their ssumption tht conflict does not reduce the stock of vilble cpitl.

16 Note tht here we focused on mrginl chnges in reltive prices. For lrger chnges in prices speciliztion in the production of one single commodity cn occur in the underlying frmework. The result of Proposition is interesting. The possibility tht exogenous price increses in commodity cn reduce the output of this sme commodity my seem t first sight prdoxicl. This finding is due to the chnnel of conflict: An increse in p leds to lower wges w, which reduces the opportunity cost of pproprition. If conflict is very destructive the disposble cpitl cn be reduced to such n extent tht the output of the cpitl-intensive commodity Y ctully decreses. 4.3 Extensions nd Further Comprtive Sttics So fr we focused on the effects of conflict on sectors of vrying fctor-intensity. Now we shll put emphsis on other empiriclly relevnt spects of the structure of n economy. For this purpose we shll in the following extensions close the fctor intensity chnnel nd ssume tht =, =,. In this cse, the country will specilize in sector if p >, nd specilize in sector if p <. We shll ssume tht initilly p = nd no speciliztion occurs. In such setting clerly n increse in p will increse the output of commodity by triggering speciliztion towrds sector. However, often, s it ws mentioned bove, n increse in the price of the good the countries specilize in, triggers conflict becuse it increses the mount of rents vilble for grbbing. In the light of this, we cn nlyze the effects of conflict on domestic versus export sectors. To fix ides, let us ssume tht sector produces n exported good, while sector produces exclusively for the domestic mrket. Countries in civil wr re often subject to trde snctions or export brriers brodly understood 9, 9 During conflict bsic infrstructure is dmged or inccessible, externl finncing (export credit) scrce, nd contrcts riskier.

17 which mkes it hrder to export nd increse costs for given price level p, resulting in the following empiriclly testble prediction: Proposition 3: In setting with smll differences in fctor intensities, where price chnges trigger speciliztion, export sectors re expected to suffer more from conflict thn domestic sectors. Proof: Follows from the discussion bove. Our simple frmework cn lso generte predictions on how the investment requirements of sectors influence their vulnerbility in conflict. Assume tht in sector the returns to investment re received with some lg nd tht future gins re discounted. Initilly, production tkes plce in both sectors, with δp =. Conflict reduces the discount fctor δ of future pyoffs by decresing life expectncy. Put differently, s producers know tht with some positive probbility they get killed in conflict they discount future rewrds more hevily. This leds to δp <, which triggers speciliztion wy from sector to sector which delivers immedite gins. This cn be summrized in the following proposition. Proposition 4: In setting with smll differences in fctor intensities, where price chnges trigger speciliztion, sectors tht require future investments (i.e. mnufcturing, crop frming) re expected to suffer most from conflict. Proof: Follows from the discussion bove. 5. The Effects of Conflict on the Economy: Some Stylized Fcts

18 The presence of conflict lters the incentives, constrints, nd plnning time horizons of the economies tht suffer it. We re interested in getting some stylized fcts of the effects of conflict on the economic structure of country. However, this tsk poses severl prcticl chllenges. The first problem is how to mesure conflict. As we mentioned in section of this pper, the vrible is multidimensionl nd hrd to pin down in numericl vlue. For the purpose of this pper, we re more interested in getting rnking for conflictive countries thn prticulr meningful number. For tht reson, we decided to construct n index of conflict using principl components nlysis. The second prcticl problem is tht often sttistics re the first csulty in conflict. cking superior informtion to those who constructed the dt, our only remedy is to work with verge dt over long periods of time, check for outliers, nd see if pttern emerges. We lso control for country nd time effects to try to minimize this difficulty. In the next section, we cn prtilly void this problem by looking between industries vrition insted of the typicl cross-countries regressions. To estimte the effect of conflict on the structure of the economy, we plot the log of the vrible of interest in country ginst the conflict index for two seprte dtes, fter controlling for GDP pc PPP, GDP PPP pc squre, time nd country fixed effects s displyed in eqution (7) below: ogy jt = + *Conflict jt + *GDPpcPPP jt + * GDPpcPPPsq jt + * timedummy + * country indictors(j) + jt (7) Since we include fixed effects, the ssocition between conflict nd the dependent vrible is temporl, within countries, over time, rther thn reltionship between countries. The dependent vrible is the verge for , nd For the conflict vrible, we use our benchmrk index from section verged over , nd We include the previous five yers in the conflict index estimtes to pick up the fct tht the current configurtion of country my hve been very much ffected by recent conflicts 0. 0 Our min results re not ffected if we verge the conflict vrible over nd

19 Our first vrible of interest is mnufcturing growth. As pointed out by Jones nd Olken (008), prcticlly ll countries which hve hd sustined period of growth in the post-wr period hve experienced lrge increse in their shre of mnufcturing. Our regressions results (Tble, first column) show tht increses in the conflict level re ssocited with reduction in the shre of mnufcture in the GDP. The coefficient estimte suggests very importnt effects: chnge in conflict from the first qurtile to the third qurtile implies reduction in the shre of mnufcturing in totl GDP of bout 7 percentge points. The reltionship showed in Figure is robust to different specifictions of the conflict index nd to the removl of the most influentil observtions. Without further nlysis, we do not know if the reltionship is csul. However, the rgument for reverse cuslity is unconvincing -s the country get poorer or the income distribution more unequl nd the mnufcturing shrinks, it become more prone to conflict- becuse we hve controlled for initil per cpit GDP. Given the importnce of mnufcturing growth in the development process, we will further study the issue in next section. In prticulr, we will test some possible chnnels through which conflict ffects mnufcture growth. Figures nd 3 show the reltionship between conflict nd griculturl nd service respectively. The estimted coefficients in the second nd third columns in Tble re not significntly different from zero. This result does not chnge if we use different vritions in the conflict index or if we check for outliers. These no results re hrdly surprise. Production in the griculturl sector drops on verge by.3% per yer during periods of violent conflict (Messer et l 998). However, we re mesuring griculturl s shre of GDP nd given the importnt negtive effect we found for the mnufcturing sector it my be the cse tht the griculturl sector suffers reltively less s it is less complex nd more vitl ctivity. Furthermore, the rgument for reverse cuslity here is much stronger thn in the cse of the mnufcturing sector. There re mny exmples where issues within the griculturl sector hve unquestionbly hd direct impcts on the outbrek of violent conflict. In the cse of the service sector, the vrible is not very informtive nd we could hrdly expect to find ny effect Angol is n extreme exmple, hving production drop by s much s 44.5% during the wr yers from Crisis in the griculturl sector hs been cited s contributing fctor to the conflicts in Rwnd nd Cote d Ivoire (UNU-IAS, 004) s well s in over two dozen other conflicts in direct or indirect fshion (de Soys nd Gleditsch, 999).

20 of conflict s it includes from very complex business services to very simple personl services tht my be ffected in very different wys during conflict. The exploittion of nturl forests is very simple economic ctivity in the development world. For tht reson, we would expect conflict to increse the utiliztion of this nturl resource in detriment of more complex ctivities tht required coordintion nd resources tht re not vilble during conflict. The brekdown in coopertion nd shortening of time horizons my lso led to n overexploittion of this resource since the negtive externlity my not be internlized. e Billlon (000) illustrtes this in the cse of Cmbodi where the forest exploittion for timber finnced the continution of the civil wr, leding to the depletion of Cmbodi s most vluble resource. Our estimte (column four in Tble ) shows positive effect of conflict in the forestry production volume (Figure 4). However, conflict in the long run my led to n brupt decrese in forestry production if the overexploittion depletes this resource. More cler is the effect conflict hs in crops production (Figure 5), one of the min ctivities in the development world. This is n ctivity tht requires n investment tht tkes some time to mture. Conflict ffects the provision of the infrstructure nd finncil cpitl required to rise csh crops. It lso reduces the plnning horizon leding mny frmers to focus only on subsistence griculture. It is lso well recorded fct tht rebel fctions usully trget crops producers to ffect the bility of the government to rise revenues from the crops commerciliztion (Meredith 005). Our estimted coefficient in column five of Tble is negtive nd significtive. We found the sme results when we tried with sensible vritions in our definition of conflict. To sum up, in this section we found tht conflict hs sizble negtive effect on the mnufcture shre of GDP, while it does not hve ny evident effect on the shre of griculture nd the service sector. We lso found tht ctivities, such s forestry, tht involve nturl resource tht is esily sizble increse during conflict, while other ctivities tht require investment decrese in the presence of conflict. In the next section, we explore in more detil the effects of conflict on the mnufcturing sector.

21 6. Conflict nd Production Structure: The Chnnels The mnufcture shre in GDP declines with conflict, but wht re the deep underlying cuses? To nswer this question, we use the methodology developed in Rjn nd Zingles (998) to test chnnels through which conflict my hve n effect on the production structure. This methodology moves wy from the between countries differences of cross-countries regressions where endogeneity is big concern to within countries between industries differences. However, to be vlid, this methodology needs technology to be similr mong the countries being compred, nd for tht reson, we decided to focus on developing countries. In the model of the previous section, we suggested tht conflict my ffect to the lrgest extent those productive sectors tht re most complex, nd require most intermedite inputs nd coordintion mong different gents in the economy. We would like to check this by looking whether industries tht might be most ffected by chnnel grow differentilly in countries where the chnnel is likely to be more opertive (countries where conflict is more extensive). Therefore, our estimtion strtegy is to run regressions of the form: GrowthVA ji = + *Conflict j * IndustryChrcteristic i + * IndustryInitilVAShre ji + * IndustryIndictors i + * CountryIndictors j + ji (8) Our dependent vrible is the rel nnul verge vlue dded growth of industry i in country j during the 980s, the period for which our smple is lrger nd the vlue dded dt more relible. The explntory vribles include the initil period shre of industry i in totl vlue dded in country j, country nd industry fixed effects, nd the interction term between the country-specific conflict level nd the industry-specific chrcteristics through which the chnnels operte. Our focus is the coefficient β ssocited with this interction term.

22 We hve to define now the industry chrcteristics tht we shll use to test the effects of conflict. We re interested in three different groups of industry chrcteristics: (i) Institutionl Complexity 3, (ii) Production Fctor Intensity, nd (iii) Exportbility. (i) Institutionl Complexity We expect industries tht re trnsction intensive, nd require complex contrcting nd specific inputs to rely more on the institutionl environment in which they operte. Therefore, they should be the most ffected during conflict becuse of the effect it hs on the generl qulity of the country s institutions nd policies. To estimte the chnnels, we use two different mesures developed using the US economy s benchmrk. Both mesures use the Input Output mtrix of the US economy to obtin the level of institutionl complexity of industry i. The first industry chrcteristic we use is the reltion specific investment mesure developed by Nunn (007). He sks whether or not the input is sold in n orgnized exchnge (thick mrket) nd for ech industry he gets mesure of the proportion of its intermedite goods tht re reltionship-specific. The second industry mesure is Herfindhl index of the intermedite good requirements from other industries. This mesure ws first used by Blnchrd nd remer (997) nd lter by Cown nd Neut (007) nd the ide is tht the fewer the industries n industry buys from the less it needs institutionl qulity. The ssumption behind this pproch is tht the existing structure of intermedite good use in the US is driven by technology differences cross sectors, nd tht these technologicl differences persist cross economies (Cown nd Neut, 007). The first two columns in Appendix C show these mesures for the 8 industries. We then move to estimte eqution (8) using our two mesures of industry-specific institutionl complexity. The results pper in the first two columns in Tble where the industry nd country fixed effect coefficients hve been removed for presenttion simplicity. The two 3 Which is wht Collier (999) clls trnsction intensive sectors.

23 estimted coefficients re negtive s expected: industries tht re more institutions intensive suffer more during conflict. This result is in line with the findings of Collier (999). Our first institutionl complexity proxy, the reltion specificity vrible, is significntly different from zero when we use our benchmrk conflict index, while the second proxy, the Herfindhl index is not. To check for the robustness of our result, we use different specifictions for our conflict index, in line with wht we did in the previous section. In ll cses, the estimted coefficients remin negtive for both proxies, significntly different from zero for the reltionship specificity vrible, nd for some cses now the Herfindhl vrible becomes significntly different from zero. A second source of concern is the possibility tht our results re driven by omitted country-level vribles tht re correlted with the conflict index nd hve differentil effect cross industries. The min cndidte for this omitted vrible is officil id. Conflict countries often receive post-conflict id to help rebuild their economies. It is well documented fct (Rjn nd Subrmnin, 005) tht id hs negtive effect on governnce nd therefore ffects more those industries tht re governnce/institution intense. To control for this possibility, we include interctions of our complexity vrible with the mount of id (s shre of GDP) the country received during the 980s. The introduction of this term results in negligible chnges in our previous estimtes. (ii) Production Fctor Intensity Conflict generlly ffects the price nd vilbility of inputs required in the production process. Physicl cpitl is destroyed nd the investment rtes remin low during conflict. Wrs nd confronttions kill nd displce people. Skilled workers often leve the country nd prt of the lbor force becomes prt of government nd rebels rmies. Finncil cpitl often lso leves the country reducing the vilbility of credit to finnce working cpitl nd lrge opertions.

24 To study these chnnels, we chrcterize industries ccording to their fctor intensity. The first mesure we use is the logrithm of the cpitl lbor reltion tht Cown nd Neut (007) estimte using US dt to construct mesure of the fctor intensity for ech industry. Our second mesure is the lbor shre vlues from Rjn nd Subrmnin (005). They estimte the lbor fctor intensity s the wge to vlue dded for ech industry cross developing countries during the 980s. Our lst mesure of fctor intensity is the finncil dependence vrible in Rjn nd Zingles (998). This vrible mesures the externl finncil dependence for ll firms in industry i during the 980s. Columns 3-5 in Appendix C show these three industry-specific vribles. We once gin estimte eqution (8) using the three industry specific vribles mentioned in the previous prgrph. The estimtes (columns 3 to 5 in Tble ) show tht conflicts hve lrger negtive effect on vlue dded growth in those sectors tht re more lbor intensive nd tht depend more on externl finncing. Specificlly, we find the estimted coefficient on the interction term between conflict nd lbor intensity nd between conflict nd finncil dependence to be negtive in the three cses nd significntly different from zero in the cses of the lbor intensity nd externl finncil dependence vribles. This lst result is not surprising; conflicts re often ssocited to mjor disruptions in domestic cpitl mrkets nd cpitl flights. In contrst, the finding tht lbor nd not cpitl intense sectors suffer more during conflict goes ginst previous findings (Collier, 999). This is result tht requires more study nd probbly more disggregte study t the country-conflict specific level. A possible explntion could be tht civil conflicts re lbor intensive in the developing world nd tht physicl cpitl is less mobile thn lbor in the short run 4. We crry out severl robustness checks. Our bsic results re not ffected by sensible vritions in our conflict index. The estimte of β could be bised due to combintion of crosssector differences in fctor intensity nd cross-country differences in reltive fctor prices tht re correlted with conflict. Unfortuntely, it is hrd to find good proxies for fctor prices in 4 Conflicts in the developing world re often chrcterized by importnt loss of lives nd the displcement of lrge prts of the popultion.

25 developing countries. We use different mesures of finncil development 5 under the ssumption tht poorly-developed finncil mrkets imply higher effective costs of cpitl nd tht firms in those countries substitute cpitl for lbor. The introduction of the finncil dependence term does not significntly ffect our previous results. (iii) Exportbility Further, we re interested in ssessing whether exporting industries suffer more or less from conflict. We use two industry-specific mesures developed by Rjn nd Subrmnin (005). The first mesure of exportbility consists in the verge rtio of export to vlue dded cross developing countries during the 980s. The second mesure is dummy vrible tking the vlue if the industry i hd rtio of exports to vlue dded bove the industry medin vlue during the 980s. The lst two columns in Appendix C disply the vlues of these two mesures cross the 8 industries. The lst two columns in Tble show the estimtes of eqution (8) for the exportbility vribles. In both cses, the coefficients re negtive nd highly significntly different from zero, indicting tht exporting sectors suffer more during conflict. This result is robust nd it is not ffected by prudent vritions in our conflict index. This result does not come s surprise since there is welth of necdotic evidence of conflicts were rebels trget ctivities tht re the min source of export revenue for the government, like coffee in Colombi or oil in the Nigerin delt. Exporting sectors lso require dvnce finncing nd infrstructure, two sectors tht re often ffected by conflict. However, 5 We pproximte finncil development using the extensive set of indices found in the World Bnk s Finncil Development nd Structure dtbse. However, dt is not vilble for ll the countries in our smple nd therefore we lose some observtions when we do this robustness check.

26 the result could lso hve gone the other wy round, since the government my stimulte exporting sectors during conflict to obtin extr revenue for distributive or defense purposes. Our estimtes could lso be bised due to endogeneity issues. Higher export growth my generte dditionl rents to fight for or commodity price collpses my increse poverty, which could fuel conflict. The bis could go either wy nd we do not hve dt vilble to disentngle the two effects. The correltion between country specific commodity export price index 6 nd our conflict index is very low. The introduction of this extr interction term in (8) does not ffect our previous results. To summrize, the reduction in mnufcturing shre in conflict countries cn be explined by severl chnnels. In this section, we found evidence tht conflict ffects more industries tht require good institutions, re lbor intensive, need externl finncing, nd export n importnt prt of their production. These results re robust to sensible vritions in our conflict index nd to the introduction of control vribles to tke into ccount possible omitted vrible bis. 7. Conclusions Most of the literture on civil wrs focuses on its cuses. The present contribution insted looks t the effects of conflict on the structure of the economy. We develop n index of conflict using principl component nlysis nd pply it to ssess the effects of conflict cross economic ctivities in smple of developing countries. We find tht conflict reduces the shre of the mnufcturing sector in the GDP, which my hve importnt effects on the developing pth of these countries. In contrst, in prticulr 6 The commodity export price index comes from Collier nd Goderis (007)

27 those ssocited to nturl resources, re likely to be over-exploited during conflict leding in the long run to environmentl degrdtion nd incresing poverty. We do not find conclusive evidence on the effect of conflict on the griculturl nd service shre of GDP. Using industril level dt for smple of developing countries in the 980s, we find tht industries tht re more institutionl, lbor, nd externl finnce intensive re the most ffected by conflict. Exporting sectors lso suffer from wr. These results re robust to sensible vritions in our conflict index nd to severl checks for omitted vribles bis. While we could not rule out the possibility tht our results re driven by defective nd incomplete dt, the use of inpproprite proxies, or by other omitted vribles, the results provide benchmrk for future studies. This is one of the first ppers to look systemticlly t the economic effects of conflict nd further work is needed. In prticulr, we cme round the problem of defining conflict using n index, but this could nd should be improved trying to disggregte different dimensions of conflict such s durtion, intensity, loction nd motivtion. Some of the industry chrcteristics used to estimte the chnnels were bsed on US dt tht my not be relevnt for developing countries nd lterntive proxies should be considered. Future work should lso consider strtegies to instrument for conflict nd wys to tke the nlysis to the country cse study level.

28 Appendix A: ist of Countries in the Smple Albni Cote d'ivoire Jmic Ppu New Guine Algeri Dominicn Republic Jordn Peru Bngldesh Ecudor eny Philippines Bolivi Egypt, Arb Rep. esotho Senegl Botswn El Slvdor Mdgscr Sri nk Burundi Ethiopi Mlwi Syrin Arb Republic Cmeroon Fiji Mlysi Togo Centrl Africn Rep. Ghn Muritius Turkey Chile Guteml Morocco Uruguy Chin Hondurs Nicrgu Venezuel, RB Colombi Indi Nigeri Zimbbwe Congo, Rep. Indonesi Pkistn Cost Ric Irn, Islmic Rep. Pnm

29 Appendix B: Dt Sources nd Description Mcroeconomic Vribles Source Mnufcture s % of GDP World Development Indictors Agriculture s % of GDP World Development Indictors Service s % of GDP World Development Indictors Crop Index Food nd Agriculturl Orgniztion Foretry Production Volume Food nd Agriculturl Orgniztion Popultion World Development Indictors GDP Per Cpit, PPP (constnt 000 interntionl $) World Development Indictors Industry evel Dt Growth Rte of Vlue Added ij : Industry i's nnul growth rte of vlue dded in UNIDO (003) country j, verged over ech decde Initil Industry Shre ij : Industry i's in country j totl mnufcturing vlue dded t UNIDO (003) the beginning of ech decde Reltion specific investment: for ech industry get mesure of the proportion of its intermedite goods tht re reltionship-specific Nunn (007) Herfindhl Index of Intermedite good requirements from other industries Blnchrd nd remer (997) og /: US dt to construct fctor intensity for ech industry bor shre: wge to vlue dded for ech industry cross developing countries during the 980s. Finncil Dependence: mesure of externl finncil dependence for ll firms in industry i during the 980s Exportbility in the 980s: verge rtio of export to vlue dded cross developing countries Exportbility dummy: tkes vlue if industry i hs rtio of exports to vlue dded bove the industry medin vlue Cown nd Neut (007) Rjn nd Subrmnin (005) Rjn nd Zingles (998) Rjn nd Subrmnin (005) Rjn nd Subrmnin (005) Vribles in the Conflict Index Number of politiclly motivted murder of government officils Bnks (008) Number of coups Bnks (008) Dummy for wr onsets Gleditsch et l (00) Number of deth in civil wrs Gleditsch et l (00) Autocrcy/Democrcy scores (0 to 0) Polity IV Alterntive Vribles in the Conflict Index Number of generl strikes with more thn 000 people involved Bnks (008) Number of rmed ctivity, sbotge etc in the im of overthrowing government Bnks (008) Number of government crisis Bnks (008) Number of systemtic purges of opposition Bnks (008) Number of violnt demonstrtion involving more thn 00 people Bnks (008) Number of nti-government demonstrtions Bnks (008) Number of ttempted revolutions Bnks (008) Number of mjor constitutionl chnges Bnks (008) Dummy for coups Bnks (008)