Trade, Inequality, and the Endogenous Sorting of Heterogeneous Workers

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1 Trade, Inequalty, and the Endogenous Sortng of Heterogeneous Workers Eunhee Lee Unversty of Maryland Aprl 11, 2017 Latest verson avalable here. Abstract Ths paper presents a new framework to quanttatvely nvestgate the effect of nternatonal trade on between-educatonal-type nequalty and labor reallocaton for a large number of countres. I embed workers occupatonal choce problem nto a mult-country, mult-ndustry, and mult-factor trade model. Internatonal trade and worker s comparatve advantage affect workers labor supply decson together, and, as a consequence, gans from trade dffer across workers. I quantfy the model for 32 countres, 5 educatonal types, 4 ndustres, and 5 occupatons to examne the dstrbutonal effect of trade lberalzaton between 2000 and 2007, usng the mcrodata from household surveys of each country. I fnd that (1) between-educatonal-type nequalty ncreases n hgh-ncome countres and low-ncome countres wth a manufacturng comparatve advantage such as Chna; (2) occupaton-level labor reallocaton s an mportant channel by whch trade shocks are dssemnated across dfferent workers; and (3) trade sgnfcantly contrbutes to macro patterns of ndustry- and occupaton-level employment shfts. Keywords: trade, worker heterogenety, nequalty, occupatonal choce, labor reallocaton JEL Codes: F16, F66, J24, C68, D33 I am very grateful to my advsors Costas Arkolaks, Lorenzo Calendo, Penny Goldberg, and Samuel Kortum for ther gudance and support. I also thank Joaqun Blaum, Jonathan Eaton, Federco Esposto, Sharat Ganapat, Matthew Grant, James Harrgan, Ana Herrera, Nuno Lmao, Sungho Noh, Tommaso Porzo, Peter Schott, John Shea, Meredth Startz, Danel Trefler, Yujung Whang, Chong Xang, Ke-Mu Y, and Jng Zhang for helpful comments. All errors are my own. Department of Economcs, Unversty of Maryland. Emal: lee@econ.umd.edu

2 1 Introducton Ths paper presents a new framework to quanttatvely nvestgate the effect of nternatonal trade on domestc labor markets for a large number of countres. Two labor market outcomes are of man nterest n ths paper. Frst, workers wth dfferent levels of educatonal attanment gan or lose from trade by a dfferent amount: between-educatonal-type nequalty. Second, changes n trade envronment make workers reallocate across dfferent ndustres and occupatons: labor reallocaton. Although tradtonal trade theory predcts that trade smply ncreases nequalty n hgh-ncome countres and decreases nequalty n low-ncome countres (.e., the Stolper-Samuelson theorem (1941)), ths predcton s at odds wth emprcal evdence whch pants much more complcated pctures see Goldberg and Pavcnk (2003; 2004; 2007). Ths paper provdes a mult-country, mult-ndustry, and mult-factor general equlbrum trade model wth heterogeneous workers n order to better quantfy the effect of changes n trade envronment between 2000 and 2007 on those two sets of labor market outcomes for 32 countres around the world. In ths model, two dstnct comparatve advantage structures characterze the nternatonal trade envronment and domestc labor markets, respectvely. Frst, trade s drven by comparatve advantage across countres based on productvty dfferences and relatve factor endowments. Second, the effect of trade s dssemnated dfferentally across workers wthn a country based on comparatve advantage across workers. I characterze the worker-level comparatve advantage by assumng that workers draw dosyncratc ndustry- and occupaton-specfc productvtes condtonal on ther exogenously endowed educatonal type. Then they endogenously sort nto ndustry and occupaton n order to maxmze ther ncomes, as n the Roy (1951) model. Internatonal trade mpacts ths sortng mechansm and, as a consequence, gans from trade are dfferent across workers based on ther comparatve advantage. I also add another mportant ngredent to the model: workers not only choose an ndustry but also an occupaton. Workers engage n dfferent occupatonal tasks wthn the same ndustry based on ther comparatve advantage. As a result, they are affected by ndustry-level trade shocks dfferently dependng on what they actually do wthn an ndustry. Occupaton s another mportant margn through whch trade shocks are dssemnated across workers, because workers 1

3 wth dfferent skll levels show sgnfcantly dfferent patterns of occupaton-level labor allocaton as shown n Fgure A1. Ths model also quanttatvely shows that occupaton-level labor reallocaton s much more tghtly related to workers educaton level, whle ndustry-level labor reallocaton patterns are smlar across dfferent worker types. Thus, gnorng the occupatonal dmenson wll sgnfcantly underestmate the dfferental effect of trade on workers wth dfferent characterstcs. I use ths model to quantfy the dstrbutonal effects of changes n the trade envronment between 2000 and 2007 across 5 worker types defned by educatonal attanment, 4 ndustres, and 5 occupaton categores n 32 countres and the rest of the world. Ths tme perod s partcularly nterestng, because nternatonal trade became an ncreasngly sgnfcant factor after Chna joned the World Trade Organzaton (WTO) n I use nternatonal mcrodata gleaned from household surveys for each country to quantfy workers dfferental responses to trade shocks n dfferent countres. To take the model to the data, I estmate the key parameter, the labor supply elastcty, for four dfferent countres and fve educatonal types. Ths parameter s drectly related to the degree of worker heterogenety. I allow t to be country- and educatonal-type-specfc rather than pre-commt to a specfc assumpton on the degree of worker heterogenety. 1 The model n ths paper also convenently nests exstng trade models n a tractable way usng dfferent values of ths key parameter. Armed wth the parameter estmates, I separately ntroduce two types of trade shocks to perform counterfactuals. I frst measure trade shocks by changes n blateral trade costs, whch are calbrated to match changes n blateral trade flows n the data. The calbraton result shows that trade costs have decreased prmarly n the manufacturng ndustry between 2000 and I also separately look at the effect of changes n trade costs wth Chna, snce Chna has been on the rse n the global market durng the tme of nterest. The second trade shock of man nterest s the change n Chna s factor-neutral productvty as estmated n Hseh and Ossa (2016). 2 1 Workers are homogeneous n most trade models, ncludng the Rcardan and the Heckscher- Ohln trade models. The specfc factors model s the other extreme case, where workers are extremely heterogeneous and thus constraned to a certan ndustry. 2 Many emprcal papers, such as Autor et al. (2013), connect the mport competton from Chna n hgh-ncome countres to the ncrease of productvty n Chna, whch eventually mproves 2

4 The result from counterfactual experments show that changes n the trade envronment between 2000 and 2007 have rased between-educatonal-type nequalty n most hgh-ncome countres and n low-ncome countres wth a comparatve advantage n the manufacturng ndustry such as Chna, Inda, and Indonesa. For example, combnng two trade shocks, U.S. workers wth advanced degrees have had a 1.98% ncrease n welfare, whereas welfare of hgh school dropouts has ncreased by 1.213%. 3 For Chna, ths dscrepancy s predcted to be even larger: e.g., 2.62% ncrease and 1.45% ncrease, respectvely. When between-educatonaltype nequalty s measured by the skll premum, changes n trade envronment explan, 11.42% and 17.07% of the actual changes n the skll premum n the U.S. and n Chna, respectvely. 4 In contrast, n some Latn Amercan countres such as Brazl and Argentna, between-educatonal-type nequalty has decreased due to trade, whch s consstent wth recent emprcal evdence n those countres. Ths paper also quantfes trade-nduced labor reallocaton across ndustres and occupatons. The result shows that the occupaton-level labor reallocaton s very mportant. 5 In order to generate dfferental response to trade shocks across dfferent worker types, t s mportant to look at not only ndustry-level labor reallocaton but also occupaton-level labor reallocaton. Moreover, the result shows that trade nduces a sgnfcant contracton of manufacturng employment as well as a job polarzaton n hgh-ncome countres. 6 In contrast, the model shows that lberalzed trade between 2000 and 2007 generates a contracton of agrcultural employment n low-ncome countres such as Chna and an expanson of agrcultural employment n Latn Amercan countres. The motvaton for ths paper stems from many prevous emprcal studes that Chna s export supply capablty manly through ther cost advantage. 3 In lne wth the nternatonal trade lterature, welfare gans from trade are measured by changes n real ncome caused by changes n the trade envronment assumng consumers have a homothetc preference. 4 I defne the skll premum by the wage premum of college graduates over non-college graduates. 5 Ths s consstent wth results n the macro lterature; e.g., Kambourov and Manovsk (2008) and Groes et al. (2015). A recent paper by Traberman (2016) also emphaszes the occupatonal dmenson to explan the labor market effect of mport competton n Denmark. 6 The polarzaton across skll levels of occupaton s both theoretcally and emprcally wellstuded n the labor economcs lterature see Baumol (1967), Acemoglu (1999) and Autor et al. (2003) on models of the skll-based techncal change, as well as Autor et al. (2008) and Goos and Mannng (2007) for emprcal evdence. A recent paper by Harrgan et al. (2016) studes the effect of trade on polarzaton. 3

5 document the relatonshp between trade and nequalty: e.g., Autor et al. (2013; 2015) and Ebensten et al. (2014) for developed countres, Goldberg and Pavcnk (2003; 2005) and Topalova (2007) for developng countres. I provde a structural model that complements emprcal fndngs n those papers. Ths paper s not the frst to use a quanttatve general equlbrum framework to examne tradenduced nequalty n a large number of countres. Bursten and Vogel (2016) focus on the reallocaton of factors across heterogeneous frms wthn a sector, and Parro (2013) focuses on captal-skll complementarty. Unlke these papers, I focus on workers heterogeneous productvtes and endogenous sortng as the key channel through whch trade mpacts nequalty. In addton, ths paper uncovers the effect of trade on both ndustry- and occupaton-level labor reallocaton wthn many countres. Most mportantly, ths paper contrbutes to the fast-growng lterature on the Roy-lke assgnment model wth worker heterogenety, by Lagakos and Waugh (2013), Hseh et al. (2013), and Bursten et al. (2015). I embed worker-level comparatve advantage nto the gravty structure of standard trade models based on country-level comparatve advantage. 7 Ths paper s dstnct from prevous works n three mportant ways. Frst, workers have heterogeneous productvtes across both ndustres and occupatons. I show quanttatvely that consderng both dmensons s mportant to quantfy the dstrbutonal effect of trade. Second, ths model provdes a full pcture of the nterplay between country-level comparatve advantage and wthn-country worker-level comparatve advantage. Lastly, ths paper quantfes a hgh-dmensonal model of trade, nequalty, and worker heterogenety wth rch mcrodata from household surveys across a large number of countres nstead of focusng on the outcome of a sngle country. Ths paper also contrbutes to the lterature by provdng a quanttatve strategy to experment wth a wde range of trade lberalzaton epsodes regardng changes n trade costs or partner countres productvty nstead of restrcted trade epsodes such as movng to autarky. Moreover, I estmate the key parameter the labor supply elastcty, whch s drectly related to the degree of worker heterogenety n a more general setup accountng for heterogeneous wage dstrbutons between 7 Galle et al. (2015) follow a smlar approach wth heterogenety defned only across ndustres not across occupatons. Later n ths paper, I dscuss a lmt case of my model to match a case wthout occupaton-level worker heterogenety or labor reallocaton. 4

6 worker types and countres. Generalzng the quanttatve Rcardan model of Eaton and Kortum (2002) wth heterogeneous workers, I provde a quanttatve framework for theoretcal foundatons of workers comparatve advantage and trade studed by Ohnsorge and Trefler (2007) and Costnot and Vogel (2010). Ths model also dffers from the search and matchng model n an open economy (Helpman et al. (2016)) or from the model wth transtonal dynamcs of ndustry-level reallocaton (Artuç et al. (2010), Dx-Carnero (2014), and Calendo et al. (2015).) Wth the gravty structure that s n lne wth the welfare analyss of Arkolaks et al. (2012), the model remans quanttatvely tractable by applyng the technque of hat algebra used by Dekle et al. (2008). The algorthm to solve the model s based on Alvarez and Lucas (2007) and Calendo and Parro (2015), but wth multple producton factors occupatons. The structure of ths paper s as follows. In Secton 2, I develop a general equlbrum trade model wth endogenous sortng of heterogeneous workers, and derve welfare and dstrbutonal effects of trade. Secton 3 dscusses the quanttatve strategy, ncludng the estmaton of parameters and the calbraton of trade shocks. In Secton 4, I present counterfactual results to dscuss the effect of trade on labor market outcomes. Secton 5 presents senstvty analyses, and Secton 6 concludes. 2 Model In ths secton, I construct a general equlbrum trade model that descrbes nterrelaton between nternatonal trade and workers occupatonal choce problem wthn a country. Two comparatve advantage structures characterze the model: one, across countres and the other, across workers wthn each country. Workers choose an ndustry and an occupaton to work n based on ther heterogeneous productvtes as n Roy (1951). The parametrzaton of worker heterogenety s closely related to Hseh et al. (2013) and Bursten et al. (2015). 2.1 Envronment Consder an economy wth N countres ndexed by {1,..., N}. Each country has J ndustres ndexed by j {1,..., J} and a contnuum of products e j [0, 1] 5

7 wthn each ndustry j. The trade envronment of each ndustry follows Eaton and Kortum (2002) (EK, hereafter). 8 Preferences Indvduals have common nested CES preferences over J ndustres and wthn-ndustry product varetes: U = ( (C j ) η 1 1 η 1 ) η 1 η 1 1 j where C j = ( 1 0 C (e j ) η2 1 η 2 de j ) η 2 η 2 1 s a CES aggregate consumpton bundle, and η 1, η 2 > 0 are elastctes of substtuton across ndustres and across product varetes, respectvely. Workers Workers nelastcally supply one unt of tme and earn labor ncome. Workers are exogenously classfed by ther types τ {1,..., T} ex ante, whch are mutually exclusve and exhaustve groups emprcally defned by observable worker characterstcs, ncludng educatonal attanment, age, or gender. The total number of type τ workers n country s exogenously gven by L,τ. Each worker solves an occupatonal choce problem by smultaneously choosng the ndustry and occupatonal afflaton generatng the hghest labor ncome, as n the Roy (1951) model. There are O occupatons ndexed by o {1,..., O}. The labor market s perfectly compettve, so that workers earn ther margnal revenue product. The workers occupatonal choce problem depends on workers productvty and the market value of labor n dfferent ndustres and occupatons. I assume that an ndvdual worker ω of type τ has an dosyncratc productvty ɛω j,o for each par of ndustry j and occupaton o, where ɛω j,o s randomly drawn from a Fréchet dstrbuton: F j,o,τ (ɛ) = exp( Tj,o,τ ɛ θ,τ). Ths dosyncratc productvty s nterpreted as effcency unts of labor that worker ω s able to provde to ndustry j wth occupaton o. For smplcty, t s assumed that there s no correlaton between ndustry- and occupaton-specfc draws, but 8 A Rcardo-Roy model combnes the assgnment-based Roy model and the Rcardan trade envronment. Costnot and Vogel (2010) provde a theoretcal foundaton based on the noton of log-supermodularty. Costnot and Vogel (2015) provde an authortatve overvew of both theory and emprcs n ths lterature. 6

8 ths assumpton can be easly generalzed to allow correlatons. 9 Ths parametrzaton s analogous to the quanttatve Rcardan trade model poneered by Eaton and Kortum (2002). The Fréchet dstrbuton s a type II extreme value dstrbuton, and thus the maxmum of ndependently drawn Fréchet random varables agan follows another Fréchet dstrbuton. Ths feature lends great tractablty to derve smple analytc solutons for equlbrum outcomes. Frst, the shape parameter of ths dstrbuton θ,τ governs the wthn-type dsperson of productvty, whch can potentally dffer across countres. As shown n Secton 2.5, ths parameter s related to the elastcty of labor supply at the ndustry and occupaton level. Hence, I wll call t the labor supply elastcty parameter. Worker types wth hgher θ,τ have a more elastc labor supply at the ndustry and the occupaton level. Ths s due to the fact that types wth hgher θ,τ have fewer outlers n productvty, makng them more lkely to adjust to changes n per-unt wages by ndustry and occupaton. Second, the scale parameter T j,o,τ represents the level of workers productvtes, whch governs the absolute advantage of type τ workers n country for (j, o). The worker-level comparatve advantage across types s determned by ratos of ths parameter: for example, type τ workers have a comparatve advantage n (j, o) compared to type τ workers n (j, o ) f T j,o,τ T j,o,τ > Tj,o,τ T j,o. 10,τ Workers comparatve advantage s two-fold. On the one hand, across-type worker comparatve advantage s determned by the rato of T j,o,τ as descrbed above. On the other hand, wthn-type worker comparatve advantage s determned by θ,τ. Worker types wth a smaller θ,τ have stronger comparatve advantage structure for ndustres and occupatons wthn ther types, as ther productvtes are more heterogeneous. Both across-type and wthn-type worker comparatve advantages are mportant to determne the equlbrum labor allocaton and reallocaton n ths model. Producton Workers engage n the producton of fnal goods by choosng an 9 If a correlaton s allowed, the jont dstrbuton functon wll be F,τ (ɛ) = exp[ { (T j,o,τ ɛ θ,τ ) 1/(1 ρ) } 1 ρ ] j,o where ρ s a correlaton parameter. 10 Ths s a stochastc verson of log-supermodularty as Costnot and Vogel (2015) pont out. 7

9 ndustry and an occupaton, where occupatons are factors of producton. Producton of a product varety e j follows a CES technology: Y (e j ) = z (e j ) ( o µ j,o (y j,o (e j γ 1 γ )) ) γ γ 1, (1) where z (e j ) s a country s factor-neutral productvty of producng e j. The occupatonal labor nput from all workers wth occupaton o s denoted by y j,o (e j ). The occupaton-ntensty parameter s gven by µ j,o, and sums to one for each ndustry, and γ s the elastcty of substtuton between occupatons. In the quanttatve analyss, I consder occupatons as complementary producton nputs, as evdenced by Goos et al. (2014) Internatonal Trade There are N countres partcpatng n nternatonal trade, and only fnal goods are traded. I assume that the fnal goods market s perfectly compettve, n whch each country purchases each product from the lowest-cost suppler. The prce of product e j depends on the unt cost of the occupatonal nput bundle c j avalable n ndustry j as well as on the productvty z (e j ). The Heckscher-Ohln channel of ths model s based on the relatve type-level labor supply and endogenous occupatonal choces, whch determnes across-ndustry specalzaton patterns. The Rcardan force of trade, on the other hand, s actve through productvty z (e j ) and determnes wthn-ndustry specalzaton patterns. The productvty z (e j ) s drawn from a Fréchet dstrbuton ndependently for each e j : H j (z) = exp( Aj z νj ), (2) where the scale parameter A j s connected to the absolute advantage of country for ndustry j, and ν j governs the dsperson of productvty across countres. The degree of dsperson s dfferent across ndustres, as ν j depends on the ndustry. 11 If γ, the producton functon becomes lnear n occupatons, analogous to Costnot and Vogel (2010). In ths lmt case, country-level comparatve advantage s exactly transferred to worker-level comparatve advantage wthn countres, f comparatve advantages are characterzed by log-supermodularty. As a consequence, the model predcton becomes closer to the predctons of tradtonal trade theory whch s manly based on the postve assortatve matchng. 8

10 Ths framework s bult on mult-ndustry extensons of the EK model by Chor (2010), Costnot et al. (2011), Donaldson (2012), and Calendo and Parro (2015). 12 Trade s subject to standard ceberg-type costs: d j n 1 for any product n ndustry j produced n and shpped to n. It s assumed that d j n > 1 for = n, d j = 1 for every, and dj n = dj n. Trade costs are dfferent across ndustres Partal Equlbrum Partal equlbrum results are derved separately for workers occupatonal choces, producton, and trade flows between countres. Each result s determned gven the per-unt prce p j,o of occupatonal nput for each country, ndustry, and occupaton. 14 These prces are, n turn, determned n general equlbrum. Occupatonal choce problem A potental wage of worker ω n country wth an dosyncratc productvty ɛω j,o for (j, o) s w j,o,ω = pj,o ɛω j,o. The workers occupatonal choce problem s to choose an ndustry and an occupaton that maxmze w j,o,ω. Usng the Fréchet dstrbuton of workers productvty, the equlbrum probablty that a worker ω of type τ works n ndustry j n occupaton o s π j,o,τ = T j,o,τ (pj,o ) θ,τ,o,o j,o Tj,τ (pj, (3) ) θ,τ whch determnes the ndustry and occupaton-level labor supply. Worker-level comparatve advantage affects ths labor supply functon: workers are more lkely to supply ther labor to the ndustry and the occupaton where they have a comparatve advantage. In addton, the degree of wthn-type comparatve advantage θ,τ affects the responsveness of type τ workers wth respect to changes n p j,o. The same change n p j,o may nduce dfferental labor reallocaton patterns across 12 The parametrzaton n ths paper s most closely related to Calendo and Parro (2015) wth ndustry-specfc ν j. I generalze the labor supply sde by consderng workers endogenous occupatonal choces but smplfy the nput-output lnkage. 13 Ths model can easly be extended to consder tarff and non-tarff parts of trade costs separately wthout much change to the man mplcaton of the model. 14 The per-unt prce for occupatonal nput vares both by ndustry and by occupaton, because the labor supply curve s upward-slopng due to heterogeneous productvtes. Ths varable s dfferent from the actual wage observable n the data whch ncludes unobservable effcency unts of labor. 9

11 dfferent worker types because of the worker-level comparatve advantage. A detaled dervaton of (3) can be found n the Appendx. Gven workers equlbrum choce of (j, o), the probablty dstrbuton of the equlbrum wage of type τ workers s derved by G,τ (w) = exp{ [ T j,o,o,τ (pj ) θ,τ]w θ,τ}. (4) j,o Ths s another Fréchet dstrbuton wth a scale parameter j,o Tj,o,o,τ (pj ) θ,τ and a shape parameter θ,τ. It s mportant to have both a type-specfc and countryspecfc parameter θ,τ, because the data show that the degree of wage dsperson wthn worker types vares sgnfcantly by worker type and country. 15 Ths wage dstrbuton gves the equlbrum average wage: w,τ = [ T j,o,o,τ (pj ) θ θ,τ] 1,τ Γ(1 1 ), (5) j,o θ,τ where Γ( ) s a Gamma functon. I assume θ,τ > 1 for all and τ so that the average wage s well-defned. From (5), f type τ workers have a comparatve advantage n the hgh-payng (j, o), they have relatvely hgher wages on average. Industryand occupaton-level average wages are derved from the type-level average wage (5), employment allocaton (3), and type-level labor supply L,τ, where the frst two depend on the endogenous varable p j,o. 16 Producton and Trade Each frm solves a cost mnmzaton problem by choosng the equlbrum demand for the effcency unts of labor wth each occupatonal task, y j,o (e j ). The CES technology results n the followng equlbrum unt cost functon: c j = ( o (µ j,o ) γ (p j,o ) 1 γ ) 1/(1 γ). (6) The effectve unt cost to produce a varety e j n country s c j /z (e j ). The prce of 15 For example, the data clearly show that better-educated workers are more dspersed n earned wages wthn ther type than less-educated workers are. 16 The average wage of ndustry j s w j = τ,o w,τ L,τ π j,o,τ / τ,o L,τ π j,o,τ and that of occupaton o s w o = τ,j τ,o w,τ L,τ π j,o,τ / τ,j L,τ π j,o,τ. Thus, both wj and w o respond to any endogenous compostonal shft of workers wthn types, whch should be reflected n endogenous changes of π j,o,o. 10

12 a product e j n country n, f t were produced n country s P n (e j ) = ( cj z (e j ) )dj n. Due to perfect competton, the actual prce of e j n country n s gven by P n (e j ) = mn P n (e j ). Equlbrum prce and trade flow are analogous to the results of the EK model. Detals are provded n the Appendx. Next, a gravty equaton shows patterns of wthn-ndustry specalzaton. The probablty that a country n buys a good n ndustry j from a country s λ j n = Aj (cj dj n ) νj Φ j n = Xj n Xn j, (7) where Φ j n N =1 Aj (cj dj n ) νj. From ths gravty equaton, ν j s the elastcty of mports wth respect to trade costs, whch s called the trade elastcty. An ndustry wth less dsperson of productvty across countres has a hgher trade elastcty, because trade flows respond more to changes n trade costs when countres are smlar n productvty. The exact prce ndex P j for ndustry j and country s P j = (Γ( νj + 1 η 2 ν j )) 1 1 η 2 (Φ j ) 1 ν j, (8) where Γ( ) s a gamma functon. I assume ν j + 1 > η 2 so that the prce ndex s well-defned. A country-level exact prce ndex, P = [ j (P j 1 1 η 1 and the )1 η 1] aggregate expendture share λ j are derved from the nested CES preference: λ j = (Pj )1 η 1 j (P j ) 1 η 1. (9) 2.4 General Equlbrum In general equlbrum, goods markets and occupaton markets clear n all countres, and the trade balance condton holds. Fnal goods markets are cleared when E j = N n=1 λ j n Xj n (10) 11

13 holds for each and j, where E j s the value of gross output n ndustry j n country. The total expendture s X j = λ j I, where I s the total spendng whch s equal to the total ncome, I = τ w,τ L,τ + D, wth D beng an aggregate trade defct. Snce workers have heterogeneous productvtes across ndustres and occupatons, the occupaton market clearng condtons are defned for each ndustry and occupaton, makng the total number of equatons (J O) for each country {1,..., N}, (µ j,o ) γ ( pj,o c j ) 1 γ E j = w,τ L,τ π j,o,τ. (11) τ Two market clearng condtons mply the trade balance condton for each country, j N =1 λ j n Xj n D n = j N =1 λ j n Xj. (12) The equlbrum s solved for the per-unt occupatonal prce p j,o o that satsfes the equlbrum condtons (3), (5)-(12). for each, j, and Equlbrum n proportonal changes For more convenent comparatve statcs, another way to characterze the equlbrum s to solve the model for proportonal changes of equlbrum varables. A proportonal change of any varable x s denoted by ˆx = x /x, where x s a varable x at the counterfactual equlbrum. The so-called exact hat algebra (Costnot and Rodríguez-Clare (2014)) followng Dekle et al. (2008) reduces the number of parameters that need to be determned and thus reduces data requrement for quantfcaton. I ntroduce two exogenous shocks n the counterfactual analyss: changes n blateral trade costs ( d ˆj n ) and changes n sector-specfc factor-neutral technology ( j ).17 Specfcally, I consder  j CHN as one of trade shocks n the counterfactual analyss, gven that changes n Chna s productvty are closely related to ther exportng capablty as t s ponted out n many papers n the lterature; e.g., Autor et al. (2013). A counterfactual equlbrum n changes can be easly extended to ncorporate the effect of changes n the other parameters such as T j,o,τ, µj,o, and L,τ, 17 Factor-specfc productvty parameter T j,o,τ can be also tme-varyng. For the man counterfactual analyss, I consder  j as a technology shock n order to focus only on the effect of labor demand shocks. Unlke  j, ˆT j,o,τ has frst-order effects on labor supply and second-order effects on labor demand. 12

14 whch s dscussed n the onlne appendx. All equlbrum condtons (3), (5)-(12) can be re-wrtten n terms of proportonal changes. The counterfactual equlbrum determnes ˆp j,o for each,j, and o that satsfy the followng equlbrum condtons. - Labor supply: Assumng ˆT j,o,τ = 1, - Type-level average wage: ˆπ j,o,τ = ( ˆp j,o ) θ,τ j,o (,o ˆpj ) θ,τπ j,o,τ (13) ŵ,τ = [ j,o ( ˆp j,o - Unt cost of producton: Assumng ˆµ j,o = 1, ĉ j = [ o (µj,o ) γ (p j,o ) 1 γ o (µ j,o ) γ (p j,o ) ) θ,τ π j,o,τ ] 1 θ,τ (14) ξ j,o ( ˆp j,o ) 1 γ ] 1/(1 γ) (15) where ξ j,o s a cost share of occupaton o n ndustry j. 1 γ - Industry-level prce ndex and expendture share: ˆP j n = [ N =1 λ j nâj (ĉj ˆ d j n ) νj ] 1/νj. (16) - Blateral trade flows: ˆλ j = ( ˆP j )1 η 1 j λ j ( ˆP j ) 1 η 1 (17) ˆX j n ˆX j n d j n =  j (ĉj ˆ ˆP j n ) νj = ˆλ j n (18) - Occupaton market clearng condton: Assumng ˆL,τ = 1, ( ˆpj,o ĉ j ) 1 γ Ê j = τ w,τ L,τ π j,o,τ ( τ w,τ L,τ π j,o )ŵ,τ ˆπ j,o,τ, (19),τ 13

15 where changes n the total gross output Ê j are derved by rewrtng the fnal goods market clearng condton as Ê j = N n=1 λ j n Xj n N n =1 λj n X j n ˆλ j n ˆX j n. (20) Change n the ndustry-level total expendture s ˆX j = ˆλ j Î, where Î = τ w,τ L,τ ŵ,τ +D τ w,τ L,τ +D s change n the total ncome n country. I consder the aggregate trade defct D as an exogenous varable whch s fxed as a share of the world GDP, as n Dekle et al. (2008) and n Calendo and Parro (2015). 18 I normalze the sum of p j,o across all countres, ndustres, and occupatons to reman constant between the base year and the counterfactual year Model Mechansm The model frst captures the labor demand channel, whch s the tradtonal channel by whch trade shocks affect factor prces. A dfferental response s generated frst across ndustres wth ndustry-specfc trade elastctes ν j. Together wth the dfferental pattern of the ntal labor allocaton, ths ndustry-specfc trade elastcty s the key parameter that captures dfferental mpact of trade across workers. 20 The elastcty of substtuton γ between occupatons n producton also carres weght n the labor demand channel, snce demands for dfferent occupatons are nterrelated. Despte the same ndustry-level trade shock, demands for dfferent occupatons may respond dfferentally. Ths channel engenders dfferent gans 18 Smlarly to the equlbrum condtons n levels, two market clearng condtons mply the trade balance condton at the counterfactual equlbrum. j N =1 λ j n X j n D n = j N =1 λ j n X j. 19 Accordng to the Walras law, one market clearng condton becomes redundant wthout addtonal normalzaton. Normalzng the sum of per-unt occupatonal prces s one way to add an ndependent equaton to the system. Alternatvely, we can assume that the world total output s kept constant as a normalzaton:,j E j =,j E j = E. The man results of ths paper are very robust to ths alternatve normalzaton. 20 Ossa (2015) ponts out that ndustry-specfc trade elastctes magnfy the aggregate welfare effect of trade. I focus on the relatonshp between ndustry-specfc trade elastctes and the dstrbutonal effect of trade. 14

16 from trade dependng on workers ntal occupaton afflaton. The second channel s the labor supply channel through whch trade mpacts the labor supply decsons of heterogeneous workers. Ths channel has not been wdely studed n the lterature. If workers of the same type are all homogeneous, p j,o entrely decdes the labor allocaton whch should be same for all workers wth the same type. In contrast, ths model s based on workers comparatve advantage whch generates a dfferental pattern of labor reallocaton. The elastcty of ndustry- and occupaton-level labor supply wth respect to p j,o s θ,τ (1 π j,o,τ ). The parameter θ,τ governs the responsveness of type τ workers to changes n p j,o. The self-selecton of workers and compostonal shft wthn worker types thus affect the dstrbuton of gans from trade. Ths model nests exstng models by consderng dfferent values of θ,τ. In the extreme case when θ,τ and T j,o,τ = 1 for all (, τ, j, o), workers are homogeneous n ther productvtes wthn a type. If there s only one occupaton, then ths case collapses to the mult-ndustry EK model. If t s assumed that θ,τ ; = 1 for all (, τ, j, o); µj,o = µ j,o for all ; and z (e j ) = z for all and e j, then ths model s equvalent to the mult-ndustry Heckscher-Ohln model wth CES T j,o,τ producton technology. In both mult-ndustry EK and mult-ndustry Heckscher- Ohln cases, the labor demand sde s a domnatng factor determnng ndustrylevel labor reallocaton. Another extreme case s where θ,τ s equal to 1, and workers are extremely heterogeneous n ther productvtes. Ths case corresponds to the ntuton of the specfc factors model. Instead of assgnng a specfc value for the parameter θ,τ ex ante, I estmate ths parameter n the next secton n order to take the model most closely to the data. Ths model can also nest models that allow for worker heterogenety only across ndustres; e.g., Galle et al. (2015). By assumng that there s only one occupaton, thus T j,o,τ = Tj,τ, workers of dfferent types have dfferent dstrbutons for ther ndustry-specfc productvtes, but each effcency unt of labor that they supply s treated as equal wthn each ndustry. In the quanttatve analyss, I compare ths lmtng case to the baselne case wth both ndustry and occupaton dmensons. 15

17 2.6 Aggregate and Type-level Welfare Effect The model delvers both aggregate gans and type-level gans from trade. Gven the same homothetc preference for workers, the proportonal change n country s welfare s Ŵ = Î /[ j 1 λ j Âj (ĉj ( ˆλ j ) 1 ν j ) 1 η 1 1 η ] 1, (21) where ˆλ j s the change n domestc absorpton, and Î s the change n total ncome, as prevously derved. Once the model s solved for the counterfactual equlbrum ˆp j,o, welfare changes are calculated accordngly. Ths formula for welfare changes nests prevous works wth several smplfyng restrctons to my model. If trade s balanced n all countres (D = D = 0 for all ), and there s only one ndustry (J = 1), a sngle type of labor (T = 1) wth a perfectly nelastc supply, and one occupaton, then equaton (21) exactly matches the welfare formula derved by Arkolaks et al. (2012) (ACR, hereafter): Ŵ = ˆλ ν 1 for the EK model wth a trade elastcty ν. If we consder a mult-ndustry EK model wth ACR restrctons as well as the Cobb-Douglas structure across ndustres, but wthout the endogenous labor allocaton, equaton (21) collapses to Ŵ = j ( ˆλ j λj ) ν j, where λ j s a Cobb-Douglas share of ndustry j. As the man focus of my paper, I now derve the welfare effect for each worker type to dscuss the dstrbuton of trade-nduced welfare changes. Assumng that each worker type shares the aggregate trade defct based on the rato of ther total labor ncome, the change n type-level welfare s Ŵ,τ = Î,τ /[ j 1 λ j Âj (ĉj ( ˆλ j ) 1 ν j ) 1 η 1 1 η ] 1, (22) where Î,τ s the counterfactual change of type-level ncome I,τ = w,τ L,τ + D,τ, and D,τ s type τ s share of the aggregate trade defct. 21 The change n aggregate welfare (21) s then a smple weghted average of the change n type-level welfare (22), where the weght s type-level ncome share n the base year. Changes n between-type-nequalty are dscussed by comparng ths type-level welfare change 21 Galle et al. (2015) derve a smlar formula for changes n type-level welfare. If I assume that there s only one occupaton and that the preference follows a Cobb-Douglas, equaton (22) matches ther formula. 16

18 across worker types n counterfactual analyses. Between-type-nequalty can be also measured by the skll premum. I defne the skll premum by the wage premum of college graduates over non-college graduates, where ts proportonal change depends on equaton (14). 2.7 Labor Reallocaton and Average Wages of Industry and Occupaton The model shows the endogenous pattern of workers sortng nto ndustry and occupaton. Based on the model-predcted ˆπ j,o,τ and the data on πj,o,τ, I calculate π j,o,τ π j,o,τ πj,o,τ to capture the employment response wthn a type, snce πj,o,τ s defned as a share whch s summed to 1 for each type. The employment shfts can be further aggregated up to the ndustry or the occupaton level wth the data on L,τ n order to quantfy the aggregate patterns of labor reallocaton nduced by trade across ndustres and occupatons, respectvely. Industry- and occupatonlevel employment shfts can be compared to the macro data n order to quantfy how much of actual ndustry- and occupaton-level employment shfts can be explaned by trade shocks of nterest. In addton, ths model also predcts changes n ndustry- and occupaton-level average real wages after takng compostonal shfts nto account. Those changes are defned by ŵ j / ˆP and ŵ o / ˆP, respectvely, where ŵ j = [ τ,o ŵ o = [ τ,j w,τ L,τ π j,o,τ ( τ,o w,τ L )ŵ,τ ˆπ j,o,τ ]/[ L,τ π j,o,τ ( ) ˆπ j,o,τ πj,o,τ τ,o τ,o L,τ ] (23),τ πj,o,τ w,τ L,τ π j,o,τ ( τ,j w,τ L )ŵ,o,τ ˆπ j,o,τ ]/[ L,τ π j,o,τ ( ) ˆπ j,o,τ πj,τ τ,j τ,j L,o,τ ]. (24),τ πj,τ These results are structural counterparts to the trade-nduced change n the ndustry and the occupaton wage prema studed n many reduced-form analyses. 17

19 3 Quanttatve Analyss In ths secton, I dscuss the data, the estmaton of parameters, the calbraton of changes n blateral trade costs, and the algorthm to solve the model. I quantfy the dstrbutonal effects of changes n the trade envronment between 2000 and 2007, wth 2000 as the base year. From an nternatonal trade perspectve, ths tme perod s nterestng, especally because Chna joned the WTO n Data I consder N = 33 countres whch consst of 32 countres and a constructed rest of the world. These 32 countres account for 76.19% of the world total trade volumes n I also consder T = 5 worker types, J = 4 ndustres, and O = 5 occupatons. Worker types are defned by educatonal attanment: hgh school dropouts (HD), hgh school graduates (HG), workers wth some college educaton (SC), college graduates (CG), and workers wth advanced degrees (AD). 22 I assume that there are 4 ndustres: agrculture (AGR), mnng (MIN), manufacturng (MFG), and servce (SVC). Table 1 gves the occupaton categores defned by aggregatng the occupaton classfcaton by Dorn (2009) and the Internatonal Standard Classfcaton of Occupatons (ISCO) classfcaton. The fve categores are based both on the level of requred sklls and on the routneness of the occupatonal task, as used n Autor and Dorn (2013). 23 More detals are descrbed n the Appendx. Table 1: Lst of Occupaton Categores 1. Low skll Occupatons (LSO) 2. Assemblers and Machne Operators (AMO) 3. Precson Producton and Crafts Occupatons (PPC) 4. Admnstratve, Clercal, and Sales Occupatons (ACS) 5. Managers, Professonals, and Techncans (MPT) 22 The defnton of educatonal attanment vares by household survey n dfferent countres. As summarzed n the Appendx, I make the defnton consstent wthn each country. 23 In hs most aggregate categorzaton, Dorn (2009) dstngushes between transportaton, constructon, and agrcultural occupatons and low-skll servce occupatons for the U.S. However, the ISCO codes nclude agrcultural laborers n low-skll (elementary) occupatons. I thus aggregate all agrcultural occupatons and low-skll servce occupatons nto low-skll occupatons. 18

20 The Integrated Publc Use Mcrodata Seres (IPUMS) Internatonal database provdes labor market nformaton from household survey for the 22 countres n the sample for For the remanng countres, I proxy ther labor market allocaton wth the lagged survey data or the data from other countres wth a smlar ncome level and adjust them wth the data from ILOSTAT and LABORSTA. 24 As descrbed n Fgure A1, the household-level survey data show that patterns of labor allocaton vary sgnfcantly by worker type and country. Whle many exstng works n the lterature focus only on the ndustry dmenson, the data show that t s also mportant to consder occupatons to explan the full scope of the dstrbutonal effect of trade. In fact the ndustry-level pattern of labor allocaton does not vary much by worker type. By contrast, dfferent worker types show very dfferent patterns of occupaton-level labor allocaton, whch suggests that workers sklls have hgher complementarty wth occupaton-specfc tasks than wth ndustry-specfc tasks. As t can be seen from equaton (14), dfferental patterns of ntal labor allocaton across occupatons are mportant for relatve gans from trade between worker types. I obtan blateral trade flows for agrculture, mnng, and manufacturng ndustres from the UN Commodty Trade (COMTRADE) database. In addton, the Trade n Servces Database of the World Bank provdes blateral trade flows n the servce ndustry. Aggregate varables are obtaned from varous sources: UN Statstcal Dvson (UNSD) natonal accounts, OECD STructural ANalyss (STAN), World Input-Output Database (WIOD), KLEMS, ILOSTAT and LABORSTA from the Internatonal Labor Organzaton (ILO), and the Occupatonal Wage around the World (OWW.) 25 Detaled descrptons can be found n the Appendx. 3.2 Parameters The model parameters are ether estmated, calbrated to the base year, or based on prevous work. The key parameter, the labor supply elastcty θ,τ, s estmated usng data from base year The occupaton ntensty parameter µ j,o s calbrated to match the share of occupaton wthn each ndustry n the base year. 24 I also use the Barro and Lee (2013) dataset to supplement the nformaton on the labor supply wth workers educatonal type. Detaled strategy s summarzed n the Appendx. 25 The basc methodology used to obtan the nput-output table n the WIOD s summarzed by Tmmer (2012). The OWW database are made publcly avalable by Oostendorp (2012). 19

21 Estmaton of labor supply elastcty θ,τ For notatonal smplcty, I denote T j,o,τ Tj,o,τ (pj,o ) θ,τ for the estmaton of parameters. The Fréchet scale parameter j,o T j,o,τ and the shape parameter θ,τ of the dstrbuton of the equlbrum wage n (4) are jontly estmated usng the maxmum lkelhood (ML) method. 26 Denotng ndvdual worker ω s equlbrum wage by w ω condtonal on the choce of (j, o), then the log-lkelhood functon for worker type τ n country s: ln L(θ,τ, T j,o,τ w 1,... w L ) = L(ln θ,τ + ln( T j,o,τ )) (θ,τ + 1) j,o j,o L ω=1 where L s the number of workers n the sample out of the total L,τ workers wth type τ n country. The baselne estmaton s done for countres wth avalable ndvdual wage profles for the base year: Brazl, Inda, Mexco, and the U.S. Table A1 summarzes the estmaton result. The ML estmates of θ,τ vary from 1.48 to 1.97 for the U.S., and better-educated workers have smaller estmates. 27 The result mples that better-educated workers are more dspersed n ther productvtes and wages wthn the type, whch s consstent wth the evdence n wage data. The result also shows that less sklled workers have a larger labor supply elastcty generatng dfferental mpacts of trade across worker types. In addton, the estmated θ,τ s larger n the U.S. on average. Ths result s consstent wth the exstng research pontng out the role of labor market rgdty n developng countres: e.g., Goldberg and Pavcnk (2003; 2005) and Topalova (2007). The baselne counterfactual result n the next secton s derved wth the actual estmates of θ,τ for the U.S., Brazl, Inda, and Mexco. For the other OECD (non-oecd) countres, the average of the estmates for the U.S. and Mexco (Brazl and Inda) s used, respectvely. 28 As shown n Fgure A2, the predcted wage dstrbuton fts the dstrbuton of the actual wage data very well. L ln w ω ( T j,o,τ ) w θ,τ ω, j,o ω=1 Other parameters Type-level labor supply L,τ and occupaton ntensty µ j,o are 26 Ths method assumes that there s no correlaton between dosyncratc productvty draws. Wth correlaton allowed, a further normalzaton s requred to dentfy the scale parameter. 27 Usng GMM, I get larger estmates of θ,τ wth an average of approxmately 2.5 for the U.S. Compared to recent works by Lagakos and Waugh (2013), Hseh et al. (2013), and Bursten et al. (2015), I get smlar or slghtly lower estmates. Ths s related to the defnton of worker types and the ndependence assumpton across productvty draws. 28 For the other countres where the wage data are avalable n dfferent years from the base year, I estmate ths parameter for avalable years, and the man counterfactual result s very robust. 20

22 calbrated to mach the 2000 data. The trade elastcty ν j s taken from the estmates n Calendo and Parro (2015) for the agrculture, mnng, and manufacturng ndustres (9.59, 14.83, and 5.5, respectvely.) 29 I use Eaton and Kortum (2002) s man estmate, 8.28, for the servce ndustry. The elastcty of substtuton across occupatons n producton γ s set to 0.90 from Goos et al. (2014), whch allows complementarty between occupatons. The elastcty of substtuton η 1 across ndustres n preference s set to 0.75 followng Comn et al. (2015). 30 Results wth dfferent values of ν j, γ and η 1 are dscussed n the robustness secton. 3.3 Measurng Trade Shocks I examne the effect of two exogenous shocks: changes n blateral trade costs ( ˆ d j n ) and changes n productvty n Chna (Â j CHN ) between 2000 and Frst, I calbrate changes n blateral trade costs to match changes n ndustry-level blateral trade flows n the data. Two standard assumptons are requred for dentfcaton: 1) symmetry,.e., d j n = dj n for all and n, and 2) no domestc trade cost,.e., dj = 1 for all and j. Wth these two dentfyng assumptons, I follow the Head and Res (2001) approach to back out changes n trade costs from blateral trade flow data see also Parro (2013). The gravty equaton from the model results n the followng relatonshp between trade flows and trade costs: ˆλ j n ˆλ j ˆλ j n ˆλ j nn = ( ˆ d j n ) 2νj. (25) The change n trade costs d ˆj n s calbrated to exactly match equaton (25) gven νj from Calendo and Parro (2015) and Eaton and Kortum (2002). Table A2 and Fgure A3 llustrate the results, showng blateral trade costs decreasng most n the manufacturng ndustry between 2000 and Blateral trade costs declned by 12.4% on average n the manufacturng ndustry, whle calbrated declnes are 7.24%, 6.75%, and 6.57% n the agrculture, mnng, and servce 29 Calendo and Parro (2015) estmate the sector-level trade elastctes for 20 sectors ncludng agrculture, mnng, and 18 2-dgt Internatonal Standard Industral Classfcaton (ISIC) manufacturng sectors. I take an average of ther estmates across 18 manufacturng ndustres. 30 Ths value s the estmate when consderng three ndustres (agrculture, manufacturng, and servces) and trade controls n Comn et al. (2015). Buera et al. (2015) and Cravno and Sotelo (2016) consder a much lower elastcty of 0.2 between the two aggregate sectors of goods and servces. 21

23 ndustry, respectvely. Changes n trade costs depend on a partner country as well. For nstance, trade costs wth Chna have decreased by 23.5% on average across all ndustres, whch s the largest declne among all countres n the sample as trade partners. In a relaton to ths observaton, trade costs have fallen more wth low-ncome trade partners. For example, manufacturng trade costs wth OECD partners have declned by 15.35% on average, whle they have fallen by 18.87% wth non-oecd partners. Ths based trade lberalzaton pattern between 2000 and 2007 s expected to have nduced a major structural change n all countres engaged n nternatonal trade. I then use the result n Hseh and Ossa (2016) for changes n productvty n Chna. The baselne shock I use for counterfactual smulaton s an 11.2% ncrease of A j CHN durng the tme perod of nterest, whch s the medan result of Hseh and Ossa (2016). 3.4 Solvng for the World Equlbrum Wth the model n proportonal changes, I only need to obtan the data on E j, λj, λ j n, Dj j,o, and ξ for the base year To take the model to the data, E j s frst measured by the value of gross output by ndustry and country. Blateral trade flows X j n are then used to calculate the domestc absorpton Xj = E j n = X j n, blateral trade shares λ j n, and trade defcts Dj. After that, I compute the total expendture X j = n = X j n + Xj to construct the expendture share λj j,o. Lastly, ξ s measured by the share of hourly wage pad to a certan occupaton relatve to the hourly wage pad to all occupatons n ndustry j. The computaton strategy to solve the model for the equlbrum ˆp j,o s based on Calendo and Parro (2015) and the step-wse method of Alvarez and Lucas (2007). I and then solve for the change n the ndustry-level prce ˆP j. frst guess the ntal ˆp j,o After that, I calculate correspondng equlbrum quanttes derved n the model. The counterfactual equlbrum s ˆp j,o whch elmnates excess demands of occupatons for both base and counterfactual years. I repeat these steps wth the updated untl the system of equatons (19) s satsfed. The techncal ntal guess of ˆp j,o detals of the soluton strategy are descrbed n the Appendx. 22

24 4 Counterfactuals The man advantage of ths model s to be able to quantfy the nterplay of trade lberalzaton, nequalty, and labor reallocaton for a large number of countres. Another advantage of ths model s the ablty to easly test any specfc counterfactual trade shocks. In ths paper, I consder d ˆj n for j = AGR, MIN, MFG and  j CHN as two separate types of trade shocks.31 Parameters outsde these two are assumed to be tme-nvarant. The baselne counterfactual results are derved wth the prevously estmated θ,τ. Then, the mportance of havng a correct specfcaton for the degree of worker heterogenety s argued by comparng results wth dfferent values of θ,τ. Gven ˆp j,o solved at the counterfactual equlbrum, correspondng equlbrum quanttes of nterest are derved: changes n aggregate welfare, type-level welfare, skll premum, wthn-type labor reallocaton patterns, ndustry- and occupaton-level real wages, as well as employment shares across ndustres and occupatons. 4.1 Effect of Changes n Blateral Trade Costs Calbrated changes of blateral trade costs n three goods ndustres between 2000 and 2007 are frst ntroduced holdng other parameters fxed. The calbraton shows that the declne of trade costs s twce as large n the manufacturng ndustry as n agrculture or mnng ndustres. Thus, ths exercse nvestgates the effect of an actual but based trade lberalzaton especally toward manufacturng. Fgure 1 descrbes the counterfactual changes n aggregate welfare of each country aganst average declnes of blateral trade costs between 2000 and 2007 for each country. Numbers are provded n Table A3. Aggregate welfare ncreases n all countres n the sample, and countres wth a larger declne of trade costs gan more on average. Changes n between-type nequalty The model predcts an unequal dstrbuton of those aggregate welfare gans across worker types, whch s the man focus 31 Changes n blateral trade costs n the servce ndustry are also calbrated n the prevous secton, but for the counterfactual exercse, I focus only on the effects of trade lberalzaton n goods ndustres. 23