Trade Liberalization, Exports and Technology Upgrading: Evidence on the Impact of MERCOSUR on Argentinean Firms Paula Bustos * August 2009

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1 Trade Liberalization, Eports and Tecnology Upgrading: Evidence on te Impact o MERCOSUR on Argentinean Firms Paula Bustos * August 2009 Abstract Tis paper studies te impact o a regional ree trade agreement, MERCOSUR, on tecnology upgrading by Argentinean irms. To guide empirical wor, I introduce tecnology coice in Melitz s (2003) model o trade wit eterogeneous irms. Te joint treatment o te tecnology adoption and eporting coices sows tat te increase in revenues produced by trade integration can induce eporters to upgrade tecnology. An empirical test o te model reveals tat irms in industries acing iger reductions in Brazil s taris increase teir investment in tecnology aster. Te eect o taris on entry in te eport maret and tecnology adoption is igest in te upper-middle range o te irm size distribution, as predicted by te model. * I am grateul to Pilippe Agion, Pol Antras, Elanan Helpman and Marc Melitz or teir advice and support. For elpul suggestions and comments, I also wis to tan Ivan Fernandez-Val, Manuel Amador, Elsa V. Artadi, Tomas Caney, Pascaline Dupas, Antara Dutta, Doireann Fitzgerald, Marius Hentea, Gustavo Lugones, Kennet Rogo, and Karine Seraty. All remaining errors are mine. CREI and Universitat Pompeu Fabra. paula.bustos@up.edu; web address: ttp://

2 . Introduction Trade liberalization can increase productivity by inducing a better allocation o production actors or te adoption o more advanced tecnologies. Te recent trade literature [Melitz (2003), Bernard, Eaton, Jensen, and Kortum (2003), Pavcni (2002) and Tybout (2003)] as empasized te irst cannel: trade integration reallocates maret sares towards eporters, te most productive irms, increasing aggregate productivity. In tis paper I sow tat, in addition, te resulting increase in revenues can induce eporters to invest in new tecnologies. I study te impact o a regional ree trade agreement on tecnology upgrading by Argentinean irms. To guide empirical wor, I introduce tecnology coice in a model o trade wit eterogeneous irms. In te model, more productive irms mae iger revenues, tus are te only ones tat ind paying te ied costs to enter te eport maret proitable, lie in Melitz s (2003). In addition, only te most productive irms adopt te most advanced tecnology. Tis is because te beneit o adoption is proportional to revenues, wile its cost is ied. In tis setup, a bilateral reduction in taris increases eport revenues more tan it decreases domestic revenues, inducing more irms to adopt te new tecnology. I test te model in te contet o a regional trade liberalization episode: MERCOSUR. I directly estimate te impact o te reduction in Brazil s taris on entry in te eport maret and tecnology upgrading by Argentinean irms. Brazil s taris provide a good source o arguably eogenous variation, as tey ell rom an average o 29% in 99 to zero in 995, and varied etensibly across industries. Indeed, a loo at te aggregate data suggests tat MERCOSUR ad a strong impact on Argentina s eports: between 992 and 996 eports to Brazil quadrupled wile eports to te rest o te world increased only 60%. Te irm-level panel data set I analyze is uncommon in tat it contains direct measures o spending in several dimensions o tecnology, namely computers, sotware, tecnology transers, patents and innovation activities perormed witin te irm lie R&D. Tis permits to build a direct and compreensive measure o investment in tecnology instead o relying on te estimation o residuals rom te production unction as proies or te level o tecnology. In addition, te survey contains a series o questions asing weter te irm perormed a certain category o innovation or improvement in products or production process during te period tat I use to perorm robustness cecs. 2

3 In a irst analysis o te data I cec weter te sorting pattern predicted by te model is consistent wit te observed dierences between eporters and non eporters operating in te same industry. In te model, underlying productivity dierences produce a sorting o irms in tree groups: te most productive irms bot eport and use te advanced tecnology, te intermediate group eports but still uses te old tecnology and te least productive irms use te old tecnology and serve only te domestic maret. Indeed, in 992 eporters ad, on average, a iger level o spending in tecnology per worer tan non eporters in te same industry. Te model also predicts tat during te liberalization period bot old and new eporters upgrade tecnology aster tan non eporters, wic is conirmed by te data. In particular, new eporters were not more tecnology intensive tan non eporters beore liberalization, but upgrade tecnology aster as tey enter te eport maret during te liberalization period. Te patterns in te data described above sow tat tere is a coincidence between entry in te eport maret and tecnology upgrading but do not provide an answer to te question o weter trade liberalization induced irms to adopt new tecnologies. Indeed, bot entry in te eport maret and tecnology upgrading could be caused by oter economic reorms undertaen in te same period i tese ad eterogeneous eects on irms wit dierent caracteristics. 2 Ten, a second step in te empirical analysis attempts to establis causality by lining eporting and tecnology adoption directly to te reduction in Brazil s taris or imports rom Argentina. Note tat tis is a direct test o te model were bot te decision to enter te eport maret and to adopt a new tecnology are endogenous, and tus a unction o taris. Te model predicts tat in industries were taris all more, bot te productivity cuto to enter te eport maret and to adopt te new tecnology all more. Ten, to asses te impact o alling taris on te eport decision I estimate te cange in te probability tat a irm enters te eport maret as a unction o te cange in Brazil s taris at te industry level. I ind tat irms in sectors wit a iger reduction in taris are more liely to enter te eport maret. Te average reduction in taris (24 percentage points) increases te probability to enter te eport maret by 0 to 2 percentage points. 2 For eample, capital account liberalization could ave made credit available or middle sized irms allowing tem to enter te eport maret and upgrade tecnology. 3

4 Net, to asses te impact o alling taris on te tecnology adoption decision I estimate te cange in spending in tecnology 3 as a unction o te cange in taris. I ind tat irms increase teir spending in tecnology aster in industries were taris all more. Te average reduction in Brazil s taris increases spending in tecnology by 0.20 to 0.28 log points. I ind tat te reduction in taris as a positive eect o te same magnitude on old and new eporters, as suggested by te witin industry patterns in te data reported above. Finally, I test te model s prediction tat tat te reduction in taris induces irms in te middle range o te productivity distribution to enter te eport maret and upgrade tecnology, but sould not aect irms in te lower and upper ranges o te distribution. I ind tat te reduction in Brazil s taris ad a stronger eect on bot entry in te eport maret and tecnology upgrading in te 3 rd quartile o te irm size distribution. 4 Te estimated eects on te 3 rd quartile are about double te size tan te average eects or all irms reported above. Te empirical identiication o te eect o alling eport costs on entry in te eport maret and tecnology upgrading is based on a generalized dierences and dierences estimation, were te sources o variation are te canges in Brazil s taris or imports rom Argentina across time ( ) and across 4-digit-SIC industries. Note tat, as MERCOSUR mandates tat taris all to zero in all industries, I relate canges in tecnology spending to te initial level o Brazil s taris. Te ocus on canges in tecnology dierences out time-invariant industry caracteristics tat migt be correlated wit Brazil s taris. Te use o te initial level o Brazil s taris minimizes reverse causality concerns. Still, a main potential problem is tat oter reorms carried out in te same period could ave ad eterogeneous eects on industries wit dierent caracteristics. 5 I address tis concern by sowing tat results are robust to controls or industry trends at te 2-digit-SIC dissagregation level and te liely determinants o Brazilian trade policy: sill, capital intensity and te elasticity o demand o te industry at te 4-digit SIC dissagregation level. 3 As measures tecnology I use spending in tecnology, spending in tecnology per worer and spending in tecnology over sales, all produce similar results. 4 I use initial irm size measured as employment relative to te 4-digit-industry mean in 992 as a proy or productivity, as te survey does not provide or measures o value added nor a long enoug series o investment tat would permit to calculate productivity as a residual o an estimated production unction. 5 For eample, capital account liberalization could ave beneited capital-intensive industries disproportionately. I Brazil s trade policy was also targeting tese industry caracteristics, te estimates o te eects o taris migt pic up te impact o tis oter policy. 4

5 Te model developed in tis paper builds on an etensive teoretical literature analyzing te eects o trade on tecnological cange. 6 In particular, it was inspired by te insigt tat a reduction in trade costs increases te sare o irms tat eport and use te most advanced tecnology in Yeaple (2005). Te model I present diers rom Yeaple s in tat eterogeneity in eporting and tecnology coice is te result o e-ante eterogeneity in productivity. 7 To my nowledge, te model presented in tis paper is te irst to sow tat wen irms are eterogeneous te presence o ied tecnology adoption costs implies tat te trade-induced reallocations o maret sares towards eporters can induce tem to upgrade tecnology. Tis dierential eature o te model is important to interpret te empirical indings reported above: te reduction in taris induced tecnology adoption mostly te 3 rd quartile o te irm size distribution, and not only new eporters but also irms tat were already eporting upgrade tecnology wen variable trade costs all. Te empirical wor presented in tis paper is related to te literature tat analyzes te question o weter eport maret participation as a positive impact on productivity. Te irst studies by Clerides, Lac and Tybout (998) or Colombia, Meico and Morocco; and Bernard and Jensen (999) or te U.S. ind tat eporters ave iger productivity tan non eporters, but tis is because e-ante more productive irms become eporters, wile tere are no eects o eporting on productivity. Instead, recent papers in tis literature lie Van Biesebroec (2005) and De Loecer (2007) ind increases in productivity ater irms enter te eport maret in Ivory Coast and Slovenia, respectively. Tis paper diers rom tis literature in tat te outcome o interest is tecnology instead o productivity; and tat it analyzes te eect o bilateral trade liberalization on tecnology adoption, not te eect o eporting. Te ocus on investment in tecnology as te outcome o interest as te advantage o isolating a particular mecanism troug wic irm-productivity can improve. 8 Earlier studies 6 Grossman and Helpman (99) provide a compreensive analysis o te eects o economic integration on innovation and growt; Eaton and Kortum (200) discuss te eect o lower barriers to trade on innovation, in particular, in teir baseline model te eect o a bigger maret size is counteracted by te increased competition wit tecnologies embedded in imports, so tat tere is no eect o lower barriers to trade on innovation. 7 In Yeaple (2005) all irms are e-ante omogeneous, but in equilibrium all irms are indierent between entering te eport maret and adopting te new tecnology or serving only te domestic maret and remaining using te old tecnology. 8 A similar approac was ollowed by Veroogen (2008) wo develops a model were increased trade wit more developed countries increases production o ig quality goods and tests it in te contet o Meico s 994 devaluation. Te mecanism generating quality upgrading in is model is te iger valuation or ig quality goods 5

6 ave oten estimated productivity as a residual in te production unction. Tese residuals not only capture dierences in tecnical eiciency across irms but also dierences in maret power, actor maret distortions, or canges in te product mi, as suggested by te recent wor by Foster, Haltiwanger, and Syverson (2008), Hsie and Klenow (2008) and Bernard, Redding and Scott (2008), respectively. More importantly, canges in tecnology not only aect productivity but can ave implications or actor marets i new tecnologies use silled labor more intensively. Indeed, several studies ave documented increases in te relative demand or sill in developing countries during te trade liberalization period, 9 leaving te open question o weter sill-biased tecnological cange migt ave been an endogenous response to trade liberalization. Tis paper provides evidence or a particular cannel troug wic increased trade can induce irms to upgrade tecnology, namely increased eport revenues. Te estimation o te impact o a reduction in a trading partner s taris on investment in tecnology instead o te eect o eport maret participation parallels te comparative static eercise tat naturally emerges rom a model were bot te decision to eport and adopt tecnology are endogenous, tus eac variable is a direct unction o taris. Tis eercise is aimed to address te policy question o wat is te eect o a reduction in a trading partner s taris on tecnology investment, or wic comparison o eporters and non eporters across time can only oer indirect evidence. Indeed, te inding tat entry in te eport maret is not associated wit increases in productivity in te absence o trade reorms can be eplained by entry responding to temporary opportunities to sell in a oreign maret. Te opposite inding, even in te contet o a trade reorm, can t be ully attributed to it, specially in te contet o simultaneous implementation o oter maret-oriented reorms tat migt ave made it possible or some irms to invest in productivity improvements and tus enter te eport maret. Te empirical metodology implemented in tis paper ollows te literature measuring te eects o trade liberalization in economic outcomes troug canges in taris. 0 Te ocus o o consumers in developed countries, te U.S. in tis case. Instead, in tis paper te analysis ocuses on trade liberalization between two countries o a similar level o development, Argentina and Brazil, tus te mecanism generating tecnology upgrading is o a dierent nature: increased revenues or eporters to a country wit identical omotetic preerences. Still, in te model tecnology upgrading can be interpreted alternatively as reducing marginal production costs or increasing quality. 9 Goldberg and Pavcni (2007) review and discuss tese studies. 0 Tis literature includes studies on te impact o trade liberalization in inequality lie Attanasio, Goldberg and Pavcni (2004) or Colombia, Topalova (2005) or India, and te study in te impact o trade liberalization in productivity in Colombia by Fernandes (2007). 6

7 most studies as been unilateral trade liberalizations wile te analysis o regional or bilateral trade liberalizations are rare. Te irst study o te impact o a trading partner s reduction in taris using plant-level data was Treler s (2004) analysis o te Canada-U.S. Free Trade Agreement. To my nowledge, tis paper s analysis o MERCOSUR is te irst study o te impact o a trading partner s reduction in taris or a developing country. Not surprisingly, te eects o trade on tecnology adoption seem to be dierent in tis contet. Tis can be seen by comparing te results presented ere wit tose in a contemporaneous study o te Canada-U.S. Free Trade Agreement by Lileeva and Treler (2007). Altoug te results are not directly comparable because te metodologies used are dierent, teir inding tat te reduction in U.S. taris only induced productivity increases in te least productive new entrants in te eport maret or te case o Canada contrasts wit te indings or Argentina were te reduction in Brazil s taris induced tecnology upgrading mostly in te 3 rd quartile o te irm-size distribution and not only in new but also in old eporters. As I discuss in te teoretical section o te paper, te result tat old eporters upgrade tecnology wen trade costs all only obtains wen te costs o tecnology adoption are ig (relative to ied eporting costs) wic is more liely to be te case in developing countries. Te remaining o te paper is organized as ollows. Te net section presents te teoretical model and derives te empirical predictions on te eects o trade liberalization on entry in te eport maret and tecnology upgrading. Section 3 describes te trade liberalization episode and te data set. Section 4 presents te empirical strategy and tests te predictions o te model. Section 5 concludes. 2 Teory Tis section develops a simple model o te decision to enter te eport maret and upgrade tecnology by eterogeneous irms. I consider te case o two symmetric countries engaging in bilateral trade liberalization. Eac economy consists o a single monopolistically competitive industry were irms produce dierentiated products under increasing returns to scale, and using a single actor o production, labor, as in Krugman (979, 980). Firms are eterogeneous in productivity, ace ied eporting costs as in Melitz (2003), and can coose to increase teir productivity by paying a ied tecnology adoption cost, as in Yeaple (2005). 7

8 2. Set up o te Model I consider te simple case o two symmetric countries endowed wit L units o labor used to produce dierentiated products in a single industry. Te symmetry assumption ensures tat wages, wic are te numeraire, and all aggregate variables are te same or bot countries. I present te discussion rom te point o view o te ome country. Entry Te supply side is caracterized by monopolistic competition. Eac variety is produced by a single irm, and tere is ree entry into te industry. Firms are eterogeneous in teir productivity in te sense tat marginal labor costs vary across irms using te same tecnology. Tis idiosyncratic component o labor productivity is indeed by, tat also indees irms and varieties. To enter te industry in a given country, irms pay a ied entry cost consisting o units o labor. Entrants ten and draw teir productivity rom a nown cumulative distribution unction G( ) =. Tecnology Ater observing teir productivity irms decide weter to eit te maret or stay and produce. Firms produce varieties using a tecnology tat eatures a constant marginal cost and a ied cost, bot in terms o labor. Firms can coose to upgrade teir tecnology in te ollowing sense: by paying an additional ied cost tey can reduce teir marginal cost o production. Tis can be represented as a coice between two dierent tecnologies l and, were eatures a iger ied cost and a lower marginal cost. Te resulting total cost unctions under eac tecnology are: TC ( q, ) = l q q TC( q, ) = η γ Ten, in tis setup, tere is a part o irm productivity tat is te result o luc but irms can also tae actions to increase teir productivity. A simple interpretation would be tat beore entering an industry irms engage in product development, but te value o tat product/its marginal production cost is revealed only ater it as been developed and tus te cost o product e Alternatively, eterogeneity in productivity can be interpreted as quality: more productive irms produce a good o iger quality, in te sense tat consumers are willing to pay more or te same amount o te good. 8

9 development is sun. At te production stage, irms can tae actions to increase te quality o te product or urter reduce its marginal cost, by paying a iger ied production cost every period. Finally, in every period tere is an eogenous probability o eit (δ ). Serving te Foreign Maret Ater entry, a irm can coose to eport, in wic case it must incur an additional ied cost. In addition, eported goods are subject to per-unit iceberg costs, so tat units need to be sipped or unit to mae it to te oreign country. Demand Preerences across varieties ave te standard CES orm, wit an elasticity o substitution = /( ρ) >. Tese preerences generate a demand unction E p( ω) q( ω) = or every P P variety ω, were P = ω Ω level o spending in te country. p( ω) dω is te price inde o te industry and E is te aggregate 2.2 Firm Beavior Proit Maimization Under CES preerences te proit maimizing price is a constant marup over marginal costs. Ten, a irm wit productivity using tecnology l carges te price p d l ( ) = in te ρ domestic maret and a iger price in te eport maret p l ( ) =. I instead te irm uses ρ tecnology, it carges lower prices in bot marets: p d ( ) = and p ( ) =. ρ γ ρ γ To mae te joint decision o weter to enter te eport maret and weter to adopt tecnology, irms compare te total proit o eac o te our possible coices, wic are described below. 9

10 Proits i only serving te domestic maret and using tecnology l: d π l ( ) = E ( P ) ρ Proits i only serving te domestic maret and using tecnology : d π ( ) = E ( Pρ) γ η Proits i also eporting and using tecnology l: π ( ) = l ( ) E( Pρ) Proits i also eporting and using tecnology : π ( ) = ( ) E( Pρ ) γ η Note tat te assumption tat bot countries are identical and trade costs are symmetric implies tat te price inde ( P ) and te ependiture level ( ) E in oreign are te same as at ome. Eporting and tecnology coices are represented in Figure, were te our possible proits are depicted as a unction o irm's productivity. 2 wen <, were Te equilibrium depicted is obtained is deined as te level o productivity above wic a irm using d tecnology l inds eporting proitable [ π ) = π ( ) ] and is deined as te level o l ( l productivity above wic an eporter inds adoption o tecnology proitable [ π ) = π ( ) ]. In Appendi A I sow tat in tis equilibrium irms sort into our dierent ( l groups: te least productive irms ( < ) eit, te low productivity irms ( < < ) serve te domestic maret and use tecnology l, te medium productivity irms ( < < ) only still use tecnology l but also eport, and te most productive irms ( ) < bot eport and use tecnology. Note tat in Figure using tecnology and only serving te domestic maret is always dominated by some oter coice. Note also tat tere is a range o productivity levels were eporting is proitable but adopting tecnology is not, so tat te marginal eporter uses tecnology l. I ocus in tis case ( ) < in wat ollows and provide te necessary parameter 2 More precisely a transormation o irm's productivity:. 0

11 restrictions or tis ordering o cutos to apply. Te opposite case ( ) > is one were te equilibrium eatures no eporters using te low tecnology, wic is inconsistent wit te empirical indings I report in te net section. Figure Eporting and Tecnology Coices π l π π d l π d η η Eit * Tecnology L Don t Eport Tecnology L Eport Tecnology H Eport To solve or te industry equilibrium it is useul to state te conditions or eit, entry in te eport maret and tecnology adoption as a unction o te eit cuto, wic I do net. Eit For te least productive irms proits are igest wen using tecnology l and only serving te domestic maret, ten te eit cuto is deined by: Eporting d π l ( ) = 0 E( Pρ ) ( ) = 0 () can be epressed as a unction o or te marginal irm (eq. ): d by using l ( ) π l ( ) π = and te zero proit condition = (2)

12 note tat as long as >, > Tecnology Coice tus only te most productive irms eport. Te marginal irm adopting tecnology is an eporter, ten te adoption cuto ( ) is deined by: π ( ) π ( ) = 0 l ( γ )( ) E( Pρ ) ( ) = ( η ) Te beneit o using tecnology (te L.H.S. o te equation above) is tat te irm maes iger revenues, as demand is elastic ( > ). Te cost o using tecnology (te R.H.S. o te equation above) is its iger ied cost. Note tat tis cost is te same or all irms wile te beneit is increasing in productivity. Tis is wy tecnology coice is caracterized by a cuto productivity level φ above wic all irms use tecnology. Net, can be epressed as a unction o by substituting te zero proit condition or te marginal irm (eq. ) in te equation above: = ( ) η γ Note tat te sare o active irms adopting tecnology (tat is ( ) (3) ) is iger te lower are variable trade costs. Tis is so because a reduction in trade costs increases te total revenues o eporters relative to tose o te marginal irm wic only serves te domestic maret. By comparing equations (2) and (3) we can see tat te parameter restriction required or tat tecnology adoption costs are ig enoug relative to ied eporting costs: > is = ( ) η γ > 2.3 Industry Equilibrium Te equilibrium price (P), number o irms (M) and te distribution o active irms' productivities in te economy are determined by te ree entry condition. Free entry requires tat te sun entry cost equals te present value o epected proits: 2

13 3 ( ) [ ] _ π δ = G e (4) were ( ) G is te probability o survival and _ π are per-period epected proits o surviving irms. d p _ π π π = were d _ π are epected proits rom domestic sales, ) ( ) ( = G G p is te probability o eporting and _ π are epected eporting proits. Ten, to solve or te ree entry condition (eq. 4) we need to solve or epected proits _ π. Te derivations are detailed in Appendi A: ( ) = _ π (5) ( )( ) ( ) = η γ η By substituting te solution or average proits (eq. 5) in te ree entry condition (eq. 4) we can solve or te eit cuto: ( ) e * = δ (6) By substituting te solution or te eit cuto (eq. 6) in eqs. 2 and 3 a solution or te eporting and tecnology adoption cutos can be obtained: ( ) = δ e (7) ( ) ( ) = γ η δ e (8) Finally, welare is determined by te inverse o te price inde, wic can be obtained by substituting te eit cuto (eq. 6) in te eit condition (eq. ): ( ) L P e = δ ρ (9)

14 Discussion To interpret te solution or epected proits in eq. 5 note tat = p ( ) were p = p ( ) ( ) and p = can be written as: are te raction o surviving irms tat eport and adopt te ig tecnology, respectively. Ten, epected proits are proportional to epected ied costs ( ). It is straigtorward to sow tat in te simple case o a closed economy wit only one tecnology te solution or epected proits is te same as in eq. 5 but wit =. Ten, epected proits are proportional to te variable proits o te marginal surviving irm, wic must be equal to. In te open economy, wit probability p te irm becomes an eporter, and in tat case epected proits are augmented in proportion to, te variable eporting proits o te marginal eporter. Finally, wit probability p te irm adopts te ig tecnology, in wic case epected proits are augmented in proportion to te variable adoption proits o te marginal adopters wic are ( ). Note tat as a reduction in variable trade costs increases te raction o irms tat eport p and te raction o irms adopting te ig tecnology p, 3 epected proits increase. 2.4 Bilateral Trade Liberalization In tis section I analyze te impact o bilateral trade liberalization on entry in te eport maret and tecnology upgrading. I sow tat a reduction in trade costs increases eport revenues, inducing more irms to enter te eport maret and upgrade tecnology. Tis increases epected proits, inducing more entry into te industry. Increased entry reduces te price inde and tus irms only serving te domestic maret loose revenues. As a result, te least productive irms mae negative proits and eit. More ormally, I sow in Appendi B tat wen variable trade costs () all:. Te raction o surviving irms tat eport ( ( )) and te raction o surviving o irms tat use tecnology ( ( )) increase. Tis can be directly seen in eqs. (3) and (4). 3 Tis can be directly seen in eqs. 2 and 3. 4

15 π 2. Epected proits increase, tat is < 0 P 3. Te price inde alls, tat is > 0 * 4. Te eit productivity cuto increases, tat is < Te productivity cuto or eporting decreases, tat is > 0 _. 6. Te productivity cuto or adopting tecnology decreases ( > 0 ), as long as not all Discussion irms eport ( > ). Te new result in te model is tat te reduction in variable trade costs induces more irms to upgrade tecnology (Result 6). Wat maes adoption o te new tecnology proitable or te most productive eporters is te increase in total revenues. 4 Still, it is important to note tat tis is not a maret size eect: an increase in maret size as represented by an increase in L does not aect te tecnology adoption cuto. Instead, te result is due to te asymmetric eect o trade liberalization in models o eterogeneous irms wit ied eporting costs: wile irms serving only te domestic maret loose revenues, eporters see teir revenues increase. Indeed, tis result requires tat domestic revenues all less tan eport revenues increase. I sow in Appendi C tat tis can never be te case wen te marginal irm is an eporter. In tat case, as alls ree entry induces te price inde to all enoug to mae te proits o te marginal irm equal to zero. I tis irm is an eporter, te price inde alls enoug to mae te reduction in domestic proits completely oset te increase in eport proits. An alternative intuition or tis result is tat as countries engage in bilateral trade liberalization, irms loose domestic revenues because tere are more oreign irms and increased oreign sales, but gain eporting revenues. Te second eect dominates as long as eporters can serve te oreign maret but ace te entry o only a raction o oreign irms. 4 Te beneit o tecnology adoption is proportional to revenues wile its cost is ied. 5

16 3 Contet and Data 3. Trade Liberalization In tis section I describe te regional and unilateral trade liberalization policies undertaen in Argentina at te beginning o te 990 s. Altoug tese policies ad started to be discussed in te late 980 s, te dept and pace o te reorms implemented in 99 were largely unepected. Te newly elected president ad promised populist policies during te campaign, namely a widespread increase in wages, but is government implemented a set o maret oriented reorms. Many observers believed tat te newly built consensus or te reorms was largely due to te 989 and 990 yperinlations, and te crisis in te socialist bloc. In particular, political arguments avoring MERCOSUR in Argentina and Brazil were based in te view tat ater te all in te Berlin Wall te world would be organized in regional blocs, as te recent emergence o NAFTA and creation o te EU suggested. 5 Argentina started reducing import taris wit respect to te rest o te world beore MERCOSUR was launced, in te contet o debt-related negotiations wit te World Ban and te IMF. Between October 988 and October 99 tere were major revisions o trade policy, oten related to canges in macroeconomic policy aimed at controlling yperinlation. By October 99, te average nominal tari was 2%, ranging rom 0% to 35%, were rates were increasing in te value-added o production o eac good. Manuactures were concentrated in te range o 5% to 22%. Almost all import licenses were eliminated, wit te eception o te automobile industry. Finally, in October 993 imports o new capital goods were eempted o taris. MERCOSUR was establised by Argentina, Brazil, Paraguay and Uruguay in Marc 99. Te agreement establised generalized, linear and automatic reductions in taris, and te adoption o a common tari wit tird countries. Te tari reductions were generalized in te sense tat te same reduction relative to te m..n rates was to be applied to all goods. Tey were to be implemented gradually according to a semi-annual timetable starting by a 54% reduction in December 99, and inising at 00% in December Tis new agreement 5 For a discussion o te policy debates in Argentina and Brazil during te period o launcing o MERCOSUR see Campbell, Rozemberg and Svarzman (999). 6 Te timetable o reductions relative to m..n. rates was: 54% by December 99, 6% by June 992, 68% by December 992, 75% by December 993, 82% by December 993, 89% by June 2004 and inally 00% by December

17 was in sarp contrast wit te regional integration treaty signed in 988, were reductions in taris were gradually negotiated sector by sector and ree trade was to be acieved in 0 years. Te Customs Union was establised in 995 wit te adoption o a Common Eternal Tari (CET), wit an average level o 2%. Taris varied between 0 and 20% across industries. Inputs and materials ad te lowest taris, ollowed by semi-inised industrial goods, capital and IT goods, 7 and inal goods. Tere were eceptions to internal ree trade or a limited number o products, special regimes or sugar and automobiles and some products aced tari rates dierent rom te CET. MERCOSUR seems to ave ad a big impact on Argentinean eports. Between 992 and 996, eports to Brazil quadrupled, wile eports to te rest o te world only increased 60%. As a result, growt in eports to Brazil eplains 50% o te growt in total eports during tis period. Tis migt be related to deep reduction in Brazil s taris in tis period. Table reports summary statistics or m..n taris at te 4-digit-SIC industry level o aggregation in te period under study. 8 Te irst row reports te level o Brazil s m..n. taris in 99 tat are te baseline or te MERCOSUR tari reductions tat started in December 99. Te average reduction in Brazil s taris aced by Argentinean irms between December 99 and December 994 was 29 p.p. Also, tari reductions varied etensibly across industries, as initial m..n taris varied between o 84 p.p. and 0 p.p.. As te panel o irms I analyze covers te period , I use te level o Brazil s m..n taris in 992 as te baseline or te calculation o tari reductions in te period Tese are on average 24 p.p, sligtly lower tan 99 taris but relect a similar variation across industries, as teir correlation is As m..n. taris in Argentina were already low beore MERCOSUR was launced, te baseline or te reduction in Argentina s taris or imports rom Brazil was only 3 percentage points on average (Table ). Still, tere was signiicant variation in taris across 4-digit-SIC 7 According to Berlinsi et al. (2006) te common eternal taris or capital goods (4%) and inormation tecnology and telecommunication (6%) were te most diicult to agree upon. Argentina avored low taris wile Brazil wanted iger protection. Tus, national taris were to converge to te AEC by 200 or capital goods and 2006 or IT goods, rom above in te case o Brazil and rom below in te case o Argentina. 8 Te source o te tari data is UNCTAD-TRAINS. Taris or eac 4-digit-SIC-industry are obtained as a weigted average o te 9-digit-HS-products witin eac 4-digit-SIC-industry, were te weigts are given by imports o eac product. Tus, wen computing Brazil s m..n taris in 992 weigts or eac product witin a 4- digit industry are based on Argentina s eports to Brazil o tat product in eac year. An alternative is to obtain 4- digit-sic-industry as simple averages o m..n taris or 9-digit-HS-products witin eac industry, but tese give similar results as teir correlation is

18 industries, rom 0 to 22 p.p. Surprisingly, imports rom Brazil grew eactly at te same rate as imports rom te rest o te world during tis period (60%). As Argentina s unilateral trade liberalization occurred beore te period under study, between 992 and 996 Argentina s average import taris wit respect to te rest o te world increased sligtly ( p.p.). Still, tere were canges in taris in bot directions, rom -0 p.p. to 5 pp. across 4-digit-SIC industries. Te modiications on import taris during tis period are partly related to te convergence to te CET, tat partly relected te structure o protection in Brazil. 9 In addition, Table reports average m..n. input taris or Argentina as tese are used or robustness cecs in te empirical analysis o te impact o Brazil s taris on entry in te eport maret and tecnology upgrading. Te input tari or eac industry is computed as weigted average o te taris o all inputs used, were te weigts are based on te cost sare o eac input obtained rom te input-output matri o Argentina, as described in Appendi D. Te baseline m..n rates or Argentina s input tari reductions w.r.t Brazil were smaller tan te output taris reported above, wit an average level o p.p. in 992. Similarly, te canges in Argentina s input taris w.r.t. te world were smaller tan te output taris, ranging rom -3 to 6 p.p. Finally, an important point to note is tat te start o MERCOSUR tari reductions respect to m..n. rates, December 99, just precedes te period under study Still, eports seem to ave reacted to tari declines wit a lag. Te data on aggregate Argentinean industrial eports to Brazil sows tat tese started growing in 993, as depicted in Figure 2. Tus, it is liely tat te relevant overall tari reductions in te period are te ull 00% reduction over m..n. rates between December 99 and 994 and not te 32% remaining reduction tat occurred between December 992 and 994. Tus, in te empirical analysis I set te cange in Brazil s taris w.r.t Argentina between 992 and 996 to minus te level o Brazil s m..n taris in 992. Similarly, I set te cange in Argentina s taris w.r.t Brazil between 992 and 996 to minus te level o Argentina s m..n taris in 992. Note tat te application o a 00% or 32% tari reduction w.r.t. m..n taris in 992 does not aect te estimation o te average impact o taris on entry in te eport maret or tecnology upgrading 9 Berlinsy et al. (2006) and Cang and Winters (2002) provide a more detailed discussion o Argentina and Brazil s trade policy measures in te 990 s. 8

19 as in te irst case te estimated coeicient is 0.32 times smaller but te average cange in taris is (/0.32) times bigger. 20 It does aect te interpretation o te results, toug, as te implied responses o entry in te eport maret and spending in tecnology to a given tari cange are 0.32 times smaller wen considering te ull 00% reduction. Ten, te reported estimates can be considered as a lower bound. Figure 2 Eports rom Brazil to Argentina Sample o 04 industries wit positive trade in Millions o US$ Year Brazil s Trade Policy As te source o identiication o te eect o tari reductions on entry in te eport maret and tecnology upgrading are te dierences across industries in te level o m..n taris in Brazil in 992, it is important to discuss Brazil s trade policy in more detail. Lie Argentina, Brazil implemented a program o unilateral trade liberalization between 988 and 994. Berlinsi, Kume and Vaillant (2006) note tat te tari structure in 988 was based on te taris implemented in 957 under te import substitution policy. Tey argue tat te irst reorms implemented in did not ave signiicant eects on te degree o protection o te domestic industry as NTBs, wic were te main instrument o protection, were not modiied. Instead, ater a new government too power in marc 990 NTBs were eliminated 20 For eample, i te cange in Brazil s taris is set to minus te level o m..n taris in 992 multiplied by 0.32, estimated coeicients are /0.32 times bigger but ten te average reduction in Brazil s taris in te period is 0.32 times smaller, tus te estimated eect o te average reduction o taris is te same. 9

20 and taris were reduced gradually according to a timetable ending in January 994. Te new taris would vary between 0 and 20%, ecept or a ew goods acing 30-35% tari rates. 2 Brazil s m..n tari rates in 992 relect a transition between te old and new tari structure. As a result, tey display tari rates above 30 p.p. or some unsilled, labor-intensive industries protected under te import substitution policy lie toys, tetiles and rubber and also or sill-intensive industries tat were protected under te new policy lie domestic appliances, oice accounting and computing and te car industry. Possibly as a result, te correlation between Brazil s taris in 992 and an eogenous measure o sill intensity o te industry 22 is very low (-0.002). Instead, taris are negatively correlated wit a measure o capital intensity (- 0.2), suggesting tat Brazil protected labor-intensive industries. As te omission o industry caracteristics tat are correlated wit Brazil s trade policy migt induce biases in te estimation o te impact o te reduction in Brazil s taris on entry in te eport maret and tecnology upgrading, I include in te regressions 2-digit-SIC-industry dummies tat absorb part o te correlation between canges in taris and industry caracteristics. Ater including 2-digit-SICindustry dummies te correlation between capital intensity and taris alls to -0.06, altoug te correlation between taris and sill intensity increases to Tus, in addition to including 2- digit-sic-industry dummies I control or measures o capital, sill intensity and te elasticity o demand Firm-Level Data Te data I analyze comes rom te Survey on Tecnological Beavior o Industrial Argentinean Firms [Encuesta sobre la Conducta Tecnologica de las Empresas Industriales Argentinas (ETIA)] conducted by te National Institute o Census and Statistics in Argentina (INDEC). Te survey covers te period and was conducted in 997 over a sample o,639 industrial irms. Te sample is representative o irms owning establisments wit more tan 0 employees, and is based on 993 census data. Altoug according to te census only 5% o 2 According to Berlinsi et al. (2006) te 0% taris corresponded to commodities and eportables, 0% or agricultural products and teir derivates, 0,5 and 20% or products using basic inputs wit 0% taris and 20% or te rest o te products. Te main eceptions to te general rule were IT goods wit a 35% tari, domestic appliances (30%) and te car industry (35% tari). 22 I use measures o average capital and sill intensity in te industry in te U.S. in te 980 s obtained rom te NBER productivity database (see Appendi D or details). 23 I use te elasticity o substitution in te industry as estimated by Broda and Weinstein (2006). Te correlation o te elasticity o demand wit taris is low: 0.05 and 0.06 wit controls or 2-digit-SIC-industry dummies. 20

21 establisments ad more tan 0 employees, tey represented 90,7% o te value o output, 90,9% o industrial value added, 87,9% o employment and 94,% o te wage bill. 24 As te survey was conducted in 997, it does not contain inormation on irms tat were active in 992 and eited aterwards. I ocus my analysis on a balanced panel o,380 irms present bot in 992 and 996 or wic tere is inormation on sales, employment and belong to 4-digit-SIC industries wit inormation on Brazil s taris. Te survey contains inormation on several dimensions o spending on tecnology upgrading. Firms upgrade tecnology by perorming various innovation activities lie internal R&D, paying or tecnology transers and buying capital goods tat embody new tecnologies; and wit dierent purposes lie canging production processes, products, organizational orms or commercialization. I constructed a measure o spending on tecnology (ST) tat includes te ollowing: spending on computers and sotware; payments or tecnology transers and patents; and spending on equipment, materials and labor related to innovation activities perormed witin te irm. 25 Te survey contains inormation on ST or all years in te period , wile inormation on all te rest o te variables (sales, eports, imports, employment by education, investment) is only available or te years 992 and 996. Te survey also contains some binary measures o tecnology adoption: a list o 9 yes/ no questions asing weter te irm perormed a certain category o innovation or improvement in products or production process during te period As an eample, one o tese categories is: product dierentiation and anoter macinery and equipment associated to new production process. I use tis inormation to construct an innovation inde equal to te raction o categories or wic te irm gave positive answers. A detailed description o te questions is contained in Appendi D. Te main measure o tecnology I use in te empirical analysis is tecnology spending wile te binary measures o tecnology are used to perorm robustness cecs. I tin tecnology spending is a better measure o tecnology or two reasons. First, te inormation as 24 Te sample is te same as te one used or te Encuesta Industrial Annual, te standard yearly industry survey used to compute Industrial GDP. A description o sampling metodology or Encuesta Industrial Annual by te National Statistics Oice (INDEC) is available at 25 Lie R&D, adaptation o new products or production processes, tecnical assistance or production, engineering and industrial design, organization and commercialization. 2

22 a panel structure tat can be used to control or unobserved irm and industry caracteristics. Second, it is a more objective measure in te sense tat it does not depend on te interpretation o wat an improvement or innovation is. Finally, anoter unusual eature o te survey is tat it contains inormation on employment by education. I use tis inormation to construct measures o employment in primary scool equivalents, sill intensity and sales per worer as described in Appendi D. Table D. in Appendi D contains summary statistics by eport status or te main variables o interest or te initial year in te data, Industry-Level Data In te empirical section I use controls or 4-digit-SIC industry caracteristics tat migt be correlated wit canges in taris. First, average capital and sill intensity in te industry in te U.S. in te 980 s obtained rom te NBER productivity database (see Appendi D or details). I also use te elasticity o substitution in te industry as estimated by Broda and Weinstein (2006). Finally, data on eports rom Brazil to Argentina in te years 992 and 996 were obtained rom te U.N. COMTRADE database. Tis inormation is aggregated at te 4-digit-SIC industry. 4 Empirics In tis section I test te predictions o te teoretical model developed in section 2. First, I cec weter te sorting pattern o irms into eporting and tecnology use predicted by te model is consistent wit te observed caracteristics o eporters and non-eporters in te same 4-digit- SIC industry. Second, I test te main predictions o te model: tat a reduction in variable trade costs causes entry in te eport maret and tecnology upgrading. To establis causality, I use te dierential canges in Brazilian taris across 4-digit-SIC industries to sow tat irms are more liely to enter te eport maret and upgrade tecnology in industries were taris ell more. 4. Witin-Industry Patterns in te Data In te model, underlying productivity dierences produce a sorting o irms into tree groups: te low productivity irms only serve te domestic maret and use te low tecnology, te 22

23 medium productivity irms still use te low tecnology but also eport, and te most productive irms bot eport and use te ig tecnology. In tis setting a reduction in variable trade costs increases eporting revenues inducing irms in te middle-range o te productivity distribution to enter te eport maret and upgrade tecnology. Figure 3 illustrates te eects o trade liberalization or irms in eac part o te productivity distribution. Te upper line represents productivity cutos to adopt te ig tecnology and to enter te eport maret beore liberalization (, represents te cutos ater liberalization (, 0 0 ), wile te lower line ). Witin te group o irms tat were already eporting beore liberalization ( < ) tose in te upper range o productivity ( < ) were already using tecnology, wile irms in te range < < adopt it only aterwards. 0 Witin te group o irms tat enter te eport maret ater liberalization ( < < ), tose in 0 0 te upper range ( < < ) enter te eport maret and adopt te new tecnology, wile tose in te lower range ( < < ) enter te eport maret but eep te old tecnology. Figure 3 Eect o Falling Variable Trade Costs * * 996 Eit Stay Non Eporter Low Tec Start eporting Stay Low Tec Start eporting Switc to Hig Tec Continue eporting Switc to Hig Tec Continue eporting Stay Hig Tec 23

24 To cec weter te sorting pattern depicted in igure 3 and te parameter restrictions required to obtain it are consistent wit te data I divide irms into tree groups: continuing eporters, 26 new eporters, 27 and never eporters 28 and compute dierences in caracteristics or irms operating witin te same 4-digit-SIC industry. Table 2 reports tat, on average, continuing eporters ave a 0.37 log points iger level o spending in tecnology per worer a tan never eporters in 992. Tis is consistent wit at least a raction o tem already using te ig tecnology beore liberalization. Interestingly, tey increase spending in tecnology 0.27 log points aster tan never eporters during te liberalization period ( ), wic is consistent wit a raction o tem adopting te ig tecnology ater liberalization. Firms tat would enter te eport maret ater liberalization are not signiicantly more tecnology intensive tan never eporters in 992 (Table 2). In contrast, ater liberalization tese new eporters become more tecnology-intensive tan irms tat do not eport, increasing teir spending in tecnology per worer 0.34 log points aster between 992 and 996. Te patterns in te data described above sow tat tere is a coincidence between entry in te eport maret and tecnology upgrading, but can t establis weter it is epanded eport opportunities tat cause tecnology adoption, vice versa, or weter bot are caused by a tird actor. Some alternative eplanations or te results in Table 2 can be ruled out: as tese are based on comparisons o eporters and non eporters witin industries, tey are robust to macroeconomic socs tat aect all irms equally (an eample could be ecange rate appreciation) or to socs tat aect all irms witin an industry (an eample could be ast tecnological cange in a particular industry). Still, te act tat witin eac sector eporters and new eporters are upgrading tecnology aster tan oter irms could relect oter socs tat aect middle and ig productivity irms dierentially. Tis is particularly plausible in a contet were several reorms were implemented at te same time. For eample, capital account liberalization, tat could acilitate access to credit to inance tecnology upgrading and entry in oreign marets to medium and big irms but not to small irms in te presence o credit constraints. Ten, te net step in te empirical analysis attempts to establis causality by lining 26 Firms tat were already eporting in Firms tat eport in 996 but were not eporting in Firms tat do not eport in 992 nor