NBER WORKING PAPER SERIES THE CONTRIBUTION OF TRADE TO WAGE INEQUALITY: THE ROLE OF SKILL, GENDER, AND NATIONALITY

Transcription

1 NBER WORKING PAPER SERIES THE CONTRIBUTION OF TRADE TO WAGE INEQUALITY: THE ROLE OF SKILL, GENDER, AND NATIONALITY Michael W. Klein Chrisoph Moser Dieer M. Urban Working Paper hp:// NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachuses Avenue Cambridge, MA May 2010 We hank Pol Anras, Rene Böheim, Axel Dreher, Pierre-Olivier Gourinchas, Marin Halla, Elhanan Helpman, Peer Scho, Enrico Spoloare, Rudolf Winer-Ebmer and seminar paricipans a Tufs Universiy, Johannes Kepler Universiy Linz, 3rd BBQ Conference in Aarhus, he Volkswirschaflicher Workshop in Tuebingen and RWTH Aachen Universiy for heir commens. We are very graeful o he Insiue for Employmen Research (IAB) for heir hospialiy and, especially Peer Jakobebbinghaus and Dana Müller, for suppor wih he LIAB daa and IAB esablishmen panel. The usual disclaimer applies. The views expressed herein are hose of he auhors and do no necessarily reflec he views of he Naional Bureau of Economic Research by Michael W. Klein, Chrisoph Moser, and Dieer M. Urban. All righs reserved. Shor secions of ex, no o exceed wo paragraphs, may be quoed wihou explici permission provided ha full credi, including noice, is given o he source.

2 The Conribuion of Trade o Wage Inequaliy: The Role of Skill, Gender, and Naionaliy Michael W. Klein, Chrisoph Moser, and Dieer M. Urban NBER Working Paper No May 2010 JEL No. F16,J31 ABSTRACT Inernaional rade has been cied as a source of widening wage inequaliy in indusrial naions. Consisen wih his claim, we find a significan expor wage premium for high-skilled workers in German manufacuring and an expor wage discoun for lower skilled workers, using mached employer-employee daa. Esimaes sugges ha he expor wage premium o high-skilled workers represens up o one hird of heir overall skill premium. Bu, while an increase in expors increases wage inequaliy along he dimension of skill, i diminishes he wage inequaliy associaed wih boh gender and naionaliy. In his way, rade conribues o narrowing wage gaps and miigaing wage inequaliy in German manufacuring. Michael W. Klein Flecher School Tufs Universiy Medford, MA and NBER michael.klein@ufs.edu Dieer M. Urban Faculy of Business and Economics RWTH Aachen Universiy Templergraben Aachen, Germany dieer.urban@wiwi.rwh-aachen.de Chrisoph Moser ETH Zurich KOF Swiss Economic Insiue 8092 Zurich, Swizerland moser@kof.ehz.ch

3 1. Inroducion Manufacuring plans ha expor differ from hose ha do no along a variey of dimensions; hey are larger, more producive, more capial inensive, and, of paricular ineres, pay higher wages. In an influenial analysis of Unied Saes manufacuring plans, Bernard and Jensen (1995) found a wage premium of beween 7 and 11 percen in exporing plans, conrolling for a number of observable plan-level characerisics. Subsequen work by hese auhors (1999, 2004) and Bernard e al. (2007) have confirmed he exporer wage premium in he Unied Saes, while ohers have found evidence of an exporer wage premium in oher indusrial counries, including Denmark (Munch and Skaksen, 2008), Germany (Bernard and Wagner, 1997, who sudy he German Federal Sae of Lower Saxony, as well as Arnold and Hussinger, 2005, and Schank, Schnabel and Wagner, 2007), Korea (Hahn 2004), Porugal (Marins and Opromolla, 2009), Spain (Farinas and Marin-Marcos, 2007), Sweden (Hansson and Lundin, 2004), and he Unied Kingdom (Greenaway and Yu, 2004). 1 A key source of he ineres in he wage differenial beween exporers and oher firms is ha his could conribue o rising inequaliy in indusrial counries (Krugman, 2008, Helpman, Iskhoki and Redding, 2009). Bernard and Jensen (1997) argue ha much of he rise in wage inequaliy in Unied Saes manufacuring in he 1980s can be accouned for by an increase in relaive labor demand by exporers, who, as compared o non-exporing firms, employ relaively more highly skilled, non-producion-line workers as compared o lower skilled producion-line workers. 2 This argumen urns on he difference in he demand for skilled labor beween exporing plans and hose ha do no expor, raher han differences in he exporer wage premia across skill levels. 3 These disribuional effecs are magnified if he expor wage premium is more pronounced for higher-skilled workers han for lower-skilled workers. For example, he Bernard and Jensen (1997) inequaliy effec ha occurs hrough an expansion of he 1 Schank, Schnabel and Wagner (2007) survey hese resuls. Ineresingly, o he bes of our knowledge here is no evidence for an expor wage premium in France (see for insance Kramarz, 2008, p. 25). 2 Blum (2008) argues ha rade played a role in rising Unied Saes wage inequaliy in he 1970s, bu no subsequenly. 3 Bernard and Jensen (1995) find ha boh producion-line workers and non-producion-line workers enjoy a wage premium in plans ha expor as compared o hose ha do no expor. 2

4 expor secor is bolsered if he expor wage premium for high-skilled workers exceeds ha of heir lower skilled co-workers. There are heoreical reasons o believe ha his migh, in fac, be he case. 4 Thus, an invesigaion of he skill srucure of he expor wage premium has poenially imporan implicaions for he disribuional effecs of rade. Mos exising sudies canno speak o he skill srucure of he exporer wage premium, however, because of daa limiaions. Sudies using plan-level daa can, a bes, differeniae producion-line workers from non-producion-line workers. Some of hese sudies find posiive and significan wage premia for boh non-producion-line workers and producion-line workers (e.g. Bernard and Jensen 1995, 1999, 2004, Hahn 2004, Hansson and Lundin 2004 for 1990 observaions), while ohers find a premium for non-producion-line workers only (e.g. Bernard and Wagner 1997, and Hansson and Lundin 2004, for 1999 observaions). Oher, more recen, analyses use linked employeremployee daa ses. Munch and Skaksen (2008) use a Danish mached worker-firm longiudinal daa se and find ha wages are higher in firms wih high expor inensiy and highly educaed workers, bu here is a lower wage premium in high-expor-inensiy firms wih workers who have lower levels of educaion. Schank, Schnabel and Wagner (2007) use he German LIAB daa se which links employee saisics o he IAB Esablishmen Panel o esimae separae regressions for blue-collar and whie-collar workers while conrolling for a range of individual characerisics including age, gender, level of educaion, and naionaliy. In conras wih much of he oher lieraure, hey find a higher expor wage premium for blue collar workers han for whie collar workers. In his paper, we invesigae he skill srucure of he wage premia (or discouns) over he period for workers employed by wesern German manufacuring plans ha expor, using he linked employer-employee LIAB daa se. This panel daa se provides us wih informaion ha enables us o characerize boh workers and plans a a level of deail ha conribues imporanly o he analysis. The daa enables us o consruc four skill caegories for workers by using informaion on heir educaional aainmen, heir occupaion, and he manner in which hey are classified by he German 4 See Yeaple (2005), Busos (2007), Helpman, Iskhoki and Redding (2009, 2010), Felbermayr, Pra and Schmerer (2010), Amii and Davis (2008), Egger and Kreickemeier (2009), and Davis and Harrigan (2007). 3

5 social securiy sysem. We find ha here is a significan expor wage premium for workers in he wo highes skill caegories, and evidence of an expor wage discoun for lower-skilled workers. These resuls are confirmed when esimaing he expor wage premium across he 340 occupaions defined in he daa se raher han he four skill caegories we have consruced. The expor wage premium for higher-skilled workers combined wih he wage discoun for lower-skilled workers implies an increase in manufacuring wage dispariies wih an expansion in he number of plans ha expor, or wih an increase in he share of expors relaive o oal manufacuring oupu. Bu while an expansion in exporing may widen inequaliy across skill levels, anoher se of resuls presened in his paper shows ha an increase in expors diminishes manufacuring wage gaps due o gender or naionaliy. Higher-skilled women, who are paid less han men wih comparable personal characerisics in comparable plans, enjoy a higher expor wage premium han men, and here is no evidence of an expor wage discoun for medium-skilled and lower-skilled women. Likewise, higher-skilled manufacuring workers who are no German ciizens enjoy an expor wage premium and here is no a significan expor wage discoun for hese workers eiher. One conjecure is ha exporing firms exhibi less wage discriminaion han non-exporing firms because hey face siffer compeiion, which would be consisen wih Becker (1957). Thus, while an increase in he average expor share of he German economy raises wage inequaliy along he dimension of skill, i lowers wage inequaliy along he dimensions of gender and ciizenship, and hence reduces condiional wage inequaliy. The nex secion of his paper inroduces he mached employer-employee daa se we use and provides some saisics on workers skill levels and firms expor saus. Secion 3 presens esimaes of he skill srucure of he expor wage premium. Differences in he skill srucure of he expor wage premium beween men and women, and beween German ciizens and workers who are no ciizens, are shown by he esimaes in Secion 4. Secion 5 offers some concluding commens. 4

6 2. Skills and Expors The mached employee-employer daase on German esablishmens used in his analysis combines he IAB esablishmen panel from he German Labor Agency wih is LIAB employee panel. 5 The maching of workers wih he firms ha employ hem enables us o use deailed informaion on workers skills and aribues as well as informaion abou firms inernaional exposure. Our sample is represenaive for wesern German manufacuring plans for he period However, plans are drawn randomly from sraa of differen drawing probabiliies. These sraa are formed along he dimensions of region, indusry and plan size class. Hence, all repored means and esimaes in his paper will be inversely weighed by heir drawing probabiliies. Our daase does no comprehensively follow individuals over ime, since workers ha leave sampled plans drop ou of he daase. Sill, here are a large number of individuals who swich from one plan in he sample o anoher also included in he sample in our daa se. A complee daa descripion is given in he appendix. In his secion we describe hese wo dimensions of he daa, and provide some saisics for boh skill levels and expor share. Oher variables used in he analysis are described in Secion Workers Skill Levels A worker s skill is posiively associaed wih educaional aainmen, and is also refleced by his or her occupaion. The LIAB daa se includes employee informaion along boh of hese dimensions. The educaional aainmen variable for each employee differeniaes among 6 caegories: up o 10 years of schooling and no vocaional raining; up o 10 years of schooling and vocaional raining; high-school degree wihou vocaional raining; high-school degree wih vocaional raining; college degree; and universiy degree. The LIAB also idenifies 340 occupaions. The division of his wide se of occupaions ino a much smaller se of higher-skilled and lower-skilled jobs is no sraighforward in he absence of oher informaion. Forunaely, here is an official German governmen classificaion sysem ha places each occupaion ino one of wo job 5 Appendices A2 and A3 provide all variable definiions and includes deailed informaion on he daa se. 6 This is he area of he former Federal Republic of Germany. 5

7 caegories based on he asks required by ha job; he lower-skilled caegory of Arbeier which includes occupaions ha employ unskilled, blue-collar workers who migh have some vocaional raining, and he higher-skilled caegory of Angeseller ha includes occupaions employing maser crafsmen and whie-collar workers. 7 The Figure in Appendix A1 demonsraes he high correspondence beween a worker s occupaion and wheher he or she is classified as an Arbeier or an Angeseller. For example, more han 90 percen of he workers in more han 200 of he 340 occupaions are classified as eiher Arbeier or an Angeseller. In conras, fewer han 20 occupaions have no more han wo-hirds of heir workers in eiher he Arbeier or an Angeseller caegory. Thus, he Arbeier / Angeseller disincion is largely, hough no exclusively, a caegorizaion by occupaional caegory. We use he Arbeier / Angeseller disincion, along wih educaional aainmen, o consruc four caegories of workplace skill level; low-skilled workers, medium-skilled workers; high-skilled workers, and workers wih college or universiy degrees (which we call universiy-educaed ). The use of four skill caegories, raher han he 340 occupaions, allows for racable resuls concerning he skill ineracion wih expor saus. 8 These four caegories provide a more accurae indicaor of workplace skill level han one based solely on educaional aainmen. In paricular, he medium-skill and highskill caegories have he same educaional aainmen, bu differen levels of job-relaed skills. These caegories are also more refined han hose based on he producion / nonproducion disincion ypically used in sudies based on plan-level daa. We summarize our caegorizaion in Table 1, and show he proporion of each group in he sample. Low-skilled workers make up 34 percen of he sample. They have, a mos, 10 years of schooling and no vocaional raining, and heir occupaion does no require more educaion han his. Workers in he medium-skilled caegory (35 percen of he sample) and high-skilled caegory (24 percen of he sample) have a high school degree and may have vocaional raining. 7 More informaion on he Arbeier and Angeseller caegories is included in he daa appendix. 8 The occupaion informaion is used in he regression analysis, however, by including he 340 occupaions as fixed effecs. We also presen some corroboraing evidence for our skill-based findings by lising occupaions wih he lowes and highes esimaed condiional expor wage premia. 6

8 Table 1: Skill Levels by Educaion / Occupaion Occupaion Classificaion (Prop. Of Sample) Educaion Arbeier Angeseller 10 years, no vocaional raining Low-skilled (0.34) No observaions 10 years, vocaional raining High School degree, no voc. raining High School degree, vocaional raining College Degree Medium-skilled (0.35) High-skilled (0.24) Univ. Educaed No observaions Universiy Degree (0.07) Source: LIAB, Insiue for Employmen Research; Means are drawing probabiliy weighed. Alhough workers in he las wo caegories may have he same level of formal educaion, hey are disinguished by wheher heir occupaion is lised in he Arbeier or Angeseller caegories. A chef, for example, could be included in he high-skilled caegory if his occupaion is in he Angeseller caegory, while a less-skilled cook would be included in he Arbeier caegory. Also, an occupaion in he Angeseller caegory may require more supervisory obligaions han a somewha similar occupaion lised in he Arbeier caegory. Our highes skill caegory includes workers wih college or universiy degrees whose occupaion is always in he Angeseller caegory. This caegory represens 7 percen of he sample. To see ha he disincions among he 4 skill groups make sense, we calculae mean daily gross wages (in consan 2005 euros) for 340 occupaion groups, order hese occupaion groups according o heir mean wage from lowes o highes and plo he share of each skill group by occupaion group. The resuls are shown in Figure 1. Unsurprisingly, he occupaions wih he highes average wages are hose ha have he larges share in he wo caegories wih he highes skills, and occupaions dominaed by low-skilled workers have lower average wages. Neverheless, here is subsanial wage variaion wihin he four skill caegories, and his jusifies he use of occupaion-level conrols in he regression esimaes. 7

9 Figure 1: Proporion of Skills by Occupaion Ordered By Mean Wage Share of Skill Group by Occupaion Kernel smoohing applied Share of skill group by occupaion Share of medium-skilled Share of low-skilled Share of high-skilled (uni) Share of highskilled (no uni) Occupaions ordered by median real wage Source: LIAB, Insiue for Employmen Research 2.2 Plan Expor Share Characerisics of Exporing Firms Our daase is represenaive for manufacuring plans in wesern Germany and is from he IAB esablishmen panel. All fullime workers a hese plans are mached o heir place of employmen in he LIAB daase. The employer daa provides informaion abou he inernaional ransacions for each plan, including he share of expors in is oal sales. The proporion of plans by heir expor share class is presened in Figure 2. This figure shows ha abou 75 percen of plans do no expor. However, he proporion of employees in plans ha do no expor is less han 30 percen, indicaing ha, on average, exporing plans have many more employees han non-exporing plans (see Figure 3). For hose 25 percen of plans ha expor, he expor shares for he 25 h, 50 h, and 75 h perceniles over he sample period are presened in Figure 4. For example, he 75 h percenile expor share among all exporing plans was 20 percen in 1993 and rose o over 50 percen in The 50 h and 25 h percenile expor shares grew as well, roughly doubling heir values over his period. 8

10 Figure 2: Proporion of Plans by Openness Class Disribuion of Expor Share - Plan Daa Proporion of plans by openness class Noe: LIAB, Insiue for Employmen Research. Proporions are weighed by inverse drawing probabiliies. Figure 3: Proporion of Employees by Openness Class Disribuion of Expor Share - Employee Daa Proporion of employees by openness class Noe: LIAB, Insiue for Employmen Research. Proporions are weighed by inverse drawing probabiliies. 9

11 Figure 4: Time pah of expor share by exporing plan perceniles Evoluion of Expor Share Share of expors by openness class from 1993 o h, 50h, 75h percenile expor share year expor share, 25h percenile expor share, 75h percenile expor share, 50h percenile Noe: LIAB, Insiue for Employmen Research. Proporions are weighed by inverse drawing probabiliies. Exporing plans differ from hose ha do no expor along a number of dimensions; hey have more employees, pay higher wages, and have differen skill composiions. Somewha surprisingly, no only is he share of employees wih college or universiy degree larger in exporing plans, bu so is he share of low-skilled employees. Table 2: Composiion of Employees All Plans Exporers Non-Exporers No. Obs. (worker-year) 8,041,676 7,227, ,666 Skill Composiion Low-skilled Medium-skilled High-skilled Univ./College Educaed Proporion Women Proporion Foreigner Noe: LIAB, Insiue for Employmen Research; worker-year observaions unweighed; Proporions are weighed by inverse drawing probabiliies. 10

12 Thus, he share of medium skilled employees is smaller in exporing plans han in non-exporing plans, as shown by he saisics in Table 2. 9 The focus of his paper is he deerminaion of wage differenials by skill caegory, beween plans ha expor and hose ha do no. The regressions in Par 3 use he wages o deermine he expor premium, condiional on a number of facors. Table 3 provides some iniial saisics on uncondiional wage differences across caegories. The wage variable represens he logarihm of average daily gross wage of individual fullime workers in base year 2005 Euros. 10 All worker caegories obain larger wages on average in exporing plans, albei he differences across groups are considerable, ranging from 8% for medium skilled woman o 37% for high-skilled woman. Table 3: Wage by Worker Caegories (logarihm, consan 2005 Euros) All Exporers Non-Exporers Exp Non.Exp All Workers ln Wages by Skill Level Low-skilled Medium-skilled High-skilled Univ./College Educaed ln Wages of Women Low-skilled Medium-skilled High-skilled Univ./College Educaed ln Wages of Non-Ciizens Low-skilled Medium-skilled High-skilled Univ./College Educaed Noe: LIAB, Insiue for Employmen Research; means are weighed by inverse drawing probabiliies. 9 This could indicae ha exporing migh be relaed o job polarizaion, which refers a decrease in relaive demand for medium-skilled jobs (e.g. Goos and Manning, 2007, and Auor e al., 2006). To anicipae one robusness check, our resuls on expor wage premia are no sensiive o he inclusion of occupaional ime rends ha can be expeced o encompass relaive demand-shifs beween skill-caegories over ime. 10 The wage daa of he mos highly compensaed employees are censored above a cerain value. We follow he mehodology employed by ohers in impuing hese wage values (e.g. Schank e al., 2007, Dusmann e al., 2009). See he appendix for deails. 11

13 3. The Skill Srucure of he Trade Wage Premium The saisics in Table 3 indicae a subsanial uncondiional expor wage premium for wesern German manufacuring plans, a resul consisen wih hose presened in he published research discussed in he inroducion. Of course, ha research focuses on he condiional, raher han he uncondiional, expor wage premium. In his secion we exend ha research wih our esimaes of differences in he condiional wage premium across skill levels. Before urning o he empirical mehodology, i is worhwhile o consider he heoreical predicions concerning he expor wage premium. In many models of inernaional rade, exporers are disinguished from non-exporers because hey have higher levels of exogenous produciviy (e.g. Dornbusch, Fischer and Samuelson 1977, Meliz 2003). Models ha seek o explain differences in wages beween exporing and non-exporing firms mus also offer reasons for a lack of full labor mobiliy beween exporing and non-exporing firms, and reasons why exporing (i.e. higher produciviy) firms pay higher wages. Helpman, Iskhoki and Redding (2009) presen a model in which a firms producion funcion includes an exogenous produciviy indicaor, he number of employed workers, and he average skill level of is workforce. The inclusion of he average skill level of he workforce in he producion funcion resuls in complemenariies ha are sronges for he mos producive firms. Poenial employees skills can only be gleaned hrough cosly screening. The incenive o screen workers, and incur he cos of doing so, is sronges among highes produciviy firms because producion complemenariies rise wih he produciviy of he firm. Thus, more producive firms, he ones ha find i profiable o pay a fixed price in order o expor, have workforces wih he highes average abiliy. These workers are also more cosly o replace han lower-abiliy workers in less producive firm, so, hrough sraegic bargaining, here is an expor wage premium across firms in his model. Exensions of his model allow for differen expor wage premium for workers in differen occupaions wihin a firm. 11 In one exension of he model ha allows for 11 The expor wage premium can be jusified by oher models ha combine Meliz (2003) wih some labor marke fricion. We can disinguish beween wo srands: Firs, search and maching models of 12

14 differen available echnologies, more producive firms choose skill-inensive echnologies ha would conribue o increasing wage inequaliy as an economy moves from auarky o rade. In anoher exension, he presence of capial ha is a complemen o skilled workers, bu a subsiue for unskilled workers, could lead o an expor wage premium for skilled workers and an expor wage discoun for unskilled workers. In hese cases, an expansion of rade (in his model, he move from he auarky equilibrium o he rade equilibrium) affecs overall inequaliy hrough boh changes in wihin-occupaion inequaliy and changes in beween-occupaion inequaliy. Wihin-occupaion inequaliy rises wih a move from auarky o rade, while beween-occupaion inequaliy may rise or fall. Thus, wihin his framework, he overall link beween expanding rade and beweenoccupaion inequaliy becomes an empirical quesion. Our mehod for addressing his empirical quesion using he daa se ha includes linked employer-employee daa augmens a regression specificaion ha esimaes he effec of rade saus on wages by disinguishing his effec by skill level. Before considering esimaes based on ha approach, i is useful o firs consider he simpler specificaion ha esimaes he overall expor wage premium, ln 4 W i, j, X j, ZSi Z, Ii, Pj, Fi, j i, j, Z 2 [1] where he dependen variable is he logarihm of W i,j,, which is inroduced in Table 3 and represens he average daily gross wage of worker i who is employed a plan j in year. The expor wage premium in his specificaion is, which shows he effec on wages of he share of expors in oal revenue of plan j in year, Xj, 0,1 (X j, = 0 if plan j does no expor in year ). An individual s skill level is capured by he dummy variables in he hree elemen vecor S i Z,, where Z = 2 for medium-skilled, 3 for high-skilled, and 4 unemploymen wih individual or collecive wage bargaining are proposed for insance by Felbermayr, Pra and Schmerer (2010) and - as discussed above - by Helpman, Iskhoki and Redding (2009). The second srand of he lieraure argues ha firms are willing o pay higher han marke-clearing wages, i.e. efficiency wages, for one of wo reasons. On he one hand, any wage ha falls shor of being perceived as fair would reduce a worker s effor. In his spiri, Amii and Davis (2008) and Egger and Kreickemeier (2009) explain he expor wage premium wih a fair-wage model, whereby he fair wage level depends on firm profiabiliy and is expor saus. On he oher hand, if a worker has disase for effor and firms imperfecly monior workers effors, higher wages make he hrea of being fired when caugh shirking more credible. Davis and Harrigan (2007) offer a shirking model, where he coss of monioring he workers effors differ across firms. If a worker s effor is more valuable o or less perfecly moniored by an exporing firm, his model will also offer an underlying mechanism for an expor wage premium. 13

15 for universiy educaed (low-skilled is he omied dummy). Oher individual characerisics are represened by he vecor I j, and include he logarihm of experience, he logarihm of enure, and dummy variables for gender and German ciizenship. 12 Plan-level characerisics oher han expor share, represened by he vecor P j,, include he logarihm of number of employees as well as furher characerisics of he esablishmen. 13 Time fixed effecs are represened by. A lis of variable definiions of firm and employee conrol variables is given in Appendix A2. The regression specificaion includes oher fixed effecs as well, as represened by F i,j. Tables 4 and 5 offer esimaes based on differen ypes of fixed effecs specificaions. Plan fixed effecs, denoed P in he ables below, conrol for unobserved, non-imevarying differences in exporing plans as compared o non-exporing plans (his is equivalen o including J-1 plan-specific dummy variables if here are J plans). 14 These fixed effecs do no conrol for ime-varying differences in occupaional composiion beween exporing plans and oher plans. We can conrol for occupaion fixed effecs, and allow for he possibiliy ha occupaions affec wages differenly across plans, hrough he inclusion of plan-occupaion fixed effecs (which, wih 340 occupaion caegories, effecively inroduces a possible maximum of [(J 340) 1] dummy variables, alhough he acual number used will be many fewer because each firm does no have he full se of all possible occupaions). This specificaion is denoed as P O. 15 A hird 12 Experience is measured as he number of days since he worker s enry ino employmen, and enure is measured as he number of days since he worker s enry ino his or her curren posiion. 13 The vecor P j, includes a number of dummy variables. One indicaes he presence of a work council a a plan; workers a plans wih more han 20 employees have he righ o esablish a work council o represen heir ineress, alhough hey are no obliged o do so. Two oher dummy variables indicae wheher a plan represens he enire company (Single Plan Company), and anoher indicaing wheher he plan belongs o a Holding Company hus, he omied caegory is a headquarer plan in a muli-plan company. In addiion, some regressions also include a dummy variable ha equals 1 if managers self-assess heir plan as operaing a he echnological fronier for is indusry. 14 Idenificaion of he expor wage premium in a regression ha includes some ype of plan-level fixed effec is hrough changes in he expor share for individuals across ime, including changes in he expor share for workers in a paricular plan as well as movemens of workers from a plan wih one value of he expor share o anoher plan wih a differen value. In conras, in an OLS regression wih no plan-level fixed effecs, unobserved plan differences ha are associaed wih boh higher produciviy and a propensiy o expor will appear as an expor wage premium. Thus, we would expec a higher esimaed expor wage premium in esimaes ha do no conrol for unobserved plan-level effecs since exporing is correlaed wih higher produciviy. Likewise, we would expec a higher esimaed expor wage premium in regressions using esablishmen-level daa. Resuls presened below sugges his is, in fac, he case. 15 The use of 340 narrowly-defined occupaions as conrols is one way in which his analysis is disinguished from ohers who use much broader occupaion classificaions, such as Munch and Skaksen 14

16 opion would be o conrol for individual fixed effecs and plan fixed effecs. Abowd, Kramarz and Margolis (1999) show ha he failure o conrol for unobserved individual and firm heerogeneiy can lead o a subsanial esimaion bias. I is well known ha he underlying assumpion apar from he usual exogeneiy of explanaory variables is random soring condiional on ime-invarian person and firm effecs. 16 An even more general specificaion is one ha includes person-firm spell-effecs, which conrols addiionally for unobservable mach-specific produciviy effec. 17 This is denoed P I, and is equivalen o including a full se of ineracion erms beween plan and individual dummy variables. Wih spell-fixed effecs P I, he expor wage premia are idenified exclusively from workers changing heir wages over ime while saying in one and he same plan ha changes is expor share over ime. Insead, when conrolling for personand firm-specific effecs such as in Abowd, Kramarz and Margolis (1999), he wage premia of exporing may addiionally be idenified hrough workers swiching from plans wih low expor share o plans wih high expor share or vice versa. For example, if here is self-soring such ha workers who learned a lo in heir previous job moved o firms wih larger expor share, hen he wage premia would be overesimaed, picking up unobservable learning somehing ha does no affec he esimaes if using worker-firm spell effecs P I. For his reason, we will repor resuls from worker-firm spell effecs 18, 19 raher han firm- and worker-fixed effecs. (2008) who have 9 occupaional dummy variables, and Schank e al. (2007) who include a single dummy variable o disinguish maser crafsmen or foremen from oher blue-collar workers. 16 Solon (1988), Gibbons and Kaz (1992), and Winer-Ebmer and Zweimüller (1999), among ohers, sress ha random soring condiional on observables and ime-invarian fixed effecs migh be oo srong an assumpion and self-selecion of workers leads o inconsisen esimaes. Frias, Kaplan and Verhoogen (2009) aemp o conrol for ime-varian individual effecs and do no find evidence for soring on individual abiliy playing a significan role in explaining he expor wage premium of Mexico (when also relaxing he assumpion ha he explanaory variable of ineres is exogenous allowing i o be predeermined). 17 Woodcock (2008) derives mach-specific wage componens in a wage regression on employee-employer mached daa from a ren-sharing model wih mach-specific produciviy and discusses he idenificaion condiions of he spell esimaor. Andrews e al. (2008) discussed worker-firm spell-effecs before, which were also applied in Schank, Schnabel, and Wagner (2007) and Munch and Skaksen (2008) in he conex of esimaing he average expor wage premium. 18 However, we have also esimaed a specificaion wih worker- and firm-fixed effecs along he lines of Abowd, Creecy and Kramarz (2002), where sandard errors were calculaed by a plan-clusered boosrap, and resuls urned ou o be very similar o he esimaes wih firm- and worker-spell effecs. The same is rue for a specificaion using individual bu no plan fixed effecs. 19 Esimaes may sill be asympoically biased if here is self-soring of workers such ha worker-specific unobservable wage componens grow faser in firms he expor shares of which grow faser. This may be 15

17 Table 4 presens esimaes of, as well as he oher coefficiens in Equaion 1, for four specificaions ha differ in heir reamen of fixed effecs. In each case, he expor wage premium coefficien is significan a beer han he 99 percen level of confidence. This coefficien is when no fixed effecs are included, which yields an expor wage premium of 3.2 percen a he median value of expor share of 0.5 (his median is based only on he se of firms ha expor). This is less han half he value ha has been repored in work based on plan-level daa. One explanaion for his discrepancy is ha hese regressions, unlike hose based on plan-level observaions, conrol for individual characerisics. This explanaion is suppored by an esimae from a regression using he same se of observaions bu only including he logarihm of plan employmen and year dummy variables as addiional regressors (no shown in Table 4). In his regression, he coefficien on expor share is (wih a sandard error of 0.016), so he esimaed expor wage premium for a firm wih he median level of expors is nearly 8 percen. This value is wihin he range repored in Bernard and Jensen (1996). The fixed effecs esimaes of he expor wage premium presened in columns 2 hrough 4 of Table 4 are sriking for wo reasons. Firs, hey are all much smaller han he esimae obained wih OLS, wih values abou one-fourh as big. This is consisen wih an imporan role played by unobserved plan-level fixed effecs linked o boh produciviy and exporing. Second, once we conrol for unobserved plan-level effecs, here is lile marginal effec on esimaed values of obained by conrolling for eiher unobserved occupaional effecs or unobserved individual effecs. Each of he coefficiens in he second hrough fourh columns of he able is beween and This suggess ha i is unobserved plan level effecs, raher han unobserved occupaion effecs or unobserved individual effecs, which are correlaed wih characerisics ha affec boh he expor share of a plan and he overall wage premium o workers in plans ha expor. he case, for example, if workers increase heir produciviy hrough learning or invenions, rendering he firm more compeiive inernaionally, he rens from which are shared wih he workers. While we are no aware of any mehodology ha allows circumven his poenial source of bias, i may be limied in pracice. To see his, learning effecs are monoonically increasing produciviy of workers while he expor share of single firms flucuaes considerably over ime, such ha he correlaion beween hem is probably quie small. 16

18 Table 4: Effec of Expor Share on Wages, No Differeniaing by Skill level Variable OLS P P O P I Expor Share (j) 0.064** (0.010) 0.018** (0.007) 0.018** (0.007) 0.016* (0.007) Medium-skilled (i) 0.133** (0.004) 0.118** (0.003) 0.063** (0.003) 0.019** (0.005) High-skilled (i) 0.387** (0.005) 0.367** (0.004) 0.197** (0.005) 0.104** (0.006) Univ. Educaed (i) 0.752** (0.006) 0.706** (0.005) 0.398** (0.007) 0.256** (0.018) Woman (i) ** (0.006) ** (0.004) ** (0.003) Foreigner (i) (0.004) ** (0.002) ** (0.001) (0.004) ln(tenure) (i) 0.025** (0.002) 0.037** (0.001) 0.036** (0.001) 0.016** (0.002) ln(experience) (i) 0.085** (0.002) 0.072** (0.001) 0.062** (0.001) 0.042** (0.002) ln(employmen) (j) 0.045** (0.002) (0.007) 0.016* (0.007) 0.046** (0.007) Single Plan Co. (j) (0.006) (0.002) (0.002) (0.003) In a Holding Co. (j) 0.033** (0.006) (0.003) (0.003) (0.004) Work Council (j) 0.075** (0.008) (0.005) (0.006) (0.006) R² No. of Observaions 8,041,676 8,041,676 8,041,676 8,041,676 = sig. a 90% o 95% level of confidence * = sig. a 95% o 99% level of confidence. ** = significan a 99% level of confidence Fixed Effecs year in all specificaions. Oher fixed effecs include plan (P), planoccupaion (P O), and plan-individual (P I). Esimaes weigh observaions by inverse drawing probabiliy weighs. The overall expor wage premia repored in Table 4 could be masking differences in wage premia across skill levels indeed, he exisence of hese differences is he focus of his paper. To invesigae his possibiliy, we esimae a modified version of Equaion [1] 17

19 ha includes ineracions beween each of he four skill levels and expor share, raher han a single expor share variable. 20 The specificaion we use is 4 4 Si z, X j, ZSiz, Ii, Pj, Fi, j i, j, ln Wi, j, Z, [2] Z 1 Z 2 where all variables are defined as above. The four esimaed skill-specific expor wage premium in his equaion are L (low-skilled), M (medium-skilled), H (high-skilled) and U (universiy educaed). The hree skill coefficiens, M, H and U, represen he skill premia relaive o he low-skilled group ha are no associaed wih exporing. As wih he esimaion of Equaion [1], we allow for differen ypes of fixed effecs esimaion of Equaion [2]. 21 The hree panels of Table 5 correspond o esimaes using he plan (P), plan-occupaion (P O), and plan-individual (P I) fixed effecs, respecively. Esimaes of Equaion [2] coefficiens L, M, H and U, as well as M, H and U, are repored in Table 5. In addiion, he able includes ess of he pairwise differences among all four expor wage premium coefficiens. These are presened as he difference of he higher-skilled caegory minus he lower-skilled caegory, so a posiive value indicaes an increasing wage gap wih an expansion of expors. These differences can be inerpreed as expor-induced skill premia. Resuls presened in Table 5 show ha, wih each of he hree fixed effecs specificaions, each of he hree coefficiens are significan a beer han he 99 percen level of confidence, wih values rising wih skill level. Three of he four coefficiens are significan wih each fixed effecs specificaion a beer han he 99 percen level of confidence, wih H and U significan in all hree cases, M significan wih plan fixed effecs and plan-occupaion fixed effecs, and L significan wih plan-individual fixed effecs. Also, in all hree ses of esimaes, U > H and boh are greaer han L and M, alhough M > L wih plan-individual fixed effecs only. The righ side of each panel shows ha five of he six differences beween pairs of he coefficiens are significan a beer han he 95 percen level of confidence. The linear combinaion U H is no 20 Schank, Schnabel and Wagner (2007) ake a differen approach and esimae separae regressions for each of heir wo caegories of workers. 21 While resuls presened in Table 4 may be viewed as indicaing he use of occupaion or individual fixed effecs is unimporan, given heir marginal role in alering esimaes of, here could be an imporan difference beween he effec of occupaion and individual fixed effecs on esimaes of he overall expor premium, in Equaion [1], and heir effecs on he four skill-specific expor wage premia in Equaion [2]. 18

20 significan wih plan fixed effecs, bu significan a he 99 and 90 percen level of confidence for he plan-occupaion and plan-individual fixed effecs, respecively. Table 5: Effec of Expor Share on Wages, By Skill Level A: P, Plan FE R 2 = 0.67 n = 8,041,676 Skill Level Z (Skill) Z (Skill Exp) Medium Z High Z Univ. Z Low-skilled (0.009) ** (0.009) 0.138** (0.013) 0.147** (0.017) Medium-skilled 0.133** (0.004) ** (0.009) 0.191** (0.014) 0.200** (0.018) High-skilled 0.327** (0.006) 0.123** (0.013) (0.015) Univ. Educaed 0.651** (0.009) 0.132** (0.018) B: P O, Plan-Occupaion FE R 2 = 0.77 n = 8,041,676 Skill Level Z (Skill) Z (Skill Exp) Medium Z High Z Univ. Z Low-skilled (0.008) ** (0.009) 0.044** (0.019) 0.094** (0.012) Medium-skilled 0.073** (0.004) ** (0.008) 0.081** (0.013) 0.127** (0.020) High-skilled 0.185** (0.007) 0.051** (0.011) 0.050** (0.014) Univ. Educaed 0.366** (0.010) 0.101** (0.020) C: P I, Plan-Individual FE R 2 = 0.93 n = 8,041,676 Skill Level Z (Skill) Z (Skill Exp) Medium Z High Z Univ. Z Low-skilled ** (0.008) 0.016* (0.007) 0.073** (0.013) 0.129** (0.037) Medium-skilled 0.015** (0.006) (0.007) 0.057** (0.011) 0.113** (0.037) High-skilled 0.081** (0.007) 0.052** (0.012) (0.029) Univ. Educaed 0.210** (0.021) 0.108** (0.037) = sig. a 90% o 95% level of confidence * = sig. a 95% o 99% level of confidence. ** = significan a 99% level of confidence Fixed Effecs year in all specificaions. See Table 5 for lis of oher regressors. Esimaes weigh observaions by inverse drawing probabiliy weighs. The inerpreaion of he esimaes presened in Table 5 is faciliaed by Figure 5. This figure plos he expor wage premium for each of he four groups of workers as a funcion of he expor share. The inercep of each line represens he respecive coefficiens 19

21 (wih L = 0 since he low-skill dummy is omied in his specificaion). Differences in he values of he inercep show he skill wage premium, relaive o low-skilled workers, for firms ha do no expor. The slope of each line represens he respecive semielasiciy of wages wih respec o he expor share in oal revenue, ha is, where Z=L, M, H, or U. These semi-elasiciies may be posiive or negaive. lnw X i, j, j, Z As drawn, he figure presens an expor wage discoun, raher han an expor wage premium, for medium-skilled workers and low-skilled workers which, as will be shown, is consisen wih mos of he esimaes presened in his paper. Table 6 includes five ses of relevan resuls ha can be calculaed from he esimaes in Table Panel I presens he expor wage premium a various values of he expor share. This is represened in Figure 5 as, for example, he verical disance beween he poin E and he line denoed U represening he wage premium for universiy educaed workers in a plan ha is in he 75 h percenile of he expor share disribuion. The value associaed wih his based on he regression esimaes is. U X 75 h 22 These esimaes are based on he resuls from he specificaion wih firm-worker spell effecs in Table 5. 20

22 Table 6: Esimaes of Expor Wage Premia and Skill Premia I. Expor Wage Premia (percen) Z X 100% i Skill Caegory Expor Share 25 h Percenile 50 h Percenile 75 h Percenile Low-Skilled -0.63** -1.05** -1.40** Medium-Skilled High-Skilled 1.56** 2.60** 3.40** Univ. Educaed 3.24** 5.40** 7.02** II. Percen of Wage Premium Due o Expor Wage Premium Z Xi 100% Z Z Xi Skill Caegory Expor Share 25 h Percenile 50 h Percenile 75 h Percenile Medium-Skilled High-Skilled 16.2** 24.4** 29.6** Univ. Educaed 13.3** 20.4** 25.0** III. Differences in Expor Wage Premia by Expor Share - Expor-induced Skill Premia X 100 % Z Z i Medium Z High Z Univ. Z Percenile 25 h 50 h 75 h 25 h 50 h 75 h 25 h 50 h 75 h Low-Skilled 0.5* 0.8* 1.0* 2.2** 3.6** 4.8** 3.9** 6.4** 8.4** Medium-Skilled 1.7** 2.9** 3.7** 3.4** 5.6** 7.3** High-Skilled IV. Percen of Overall Skill Premia Due o Expor-induced Skill Premia Z ZX i 100% Z ZZ ZX i 21 High Z Univ. Z Percenile 25 h 50 h 75 h 25 h 50 h 75 h 25 h 50 h 75 h Medium-Skilled 21** 30** 36** 15** 22** 27** High-Skilled 11 18* 22* V. Differences in Expor-induced Skill Premia wih Increasing Expor Share X X 100 % Z Z 75h 25h Medium Z High Z Univ. Z 75 h 25 h 75 h 25 h 75 h 25 h Low-Skilled 0.56* 2.56** 4.50** Medium-Skilled 2.00** 3.94** High-Skilled 1.94 Noe: Calculaions based on esimaes for plan-individual fixed effecs regressions in Table 5, sandard errors are available from he auhors upon reques. Sraa drawing probabiliies are aken ino accoun.

23 Panel I of Table 6 shows ha he expor wage premium is negaive for low-skilled and medium-skilled workers (alhough i is no saisically significan for medium-skilled workers he saisical significance of he resuls in Panel I depend upon he saisical significance of each of he four respecive coefficiens). The esimaed expor wage premia are posiive for high-skilled and universiy-educaed workers. The expor wage premia for universiy-educaed workers, which range from 3.24 percen for workers in firms a he 25 h percenile of expor share o 7.02 percen for workers in firms a he 75 h percenile of expor share, are more han double ha of high-skilled workers a respecive perceniles of expor share. Panel II of Table 6 repors he proporion of he overall wage premium for a given skill group ha is due o he expor wage premium a he 25 h, 50 h, and 75 h percenile values of expor share. 23 As an example of his from Figure 5, consider he expor wage premium relaive o he overall wage premium for universiy-rained workers in he 75 h percenile of expor shares. This is represened by he verical disance beween he poin E and he line denoed U relaive o he verical disance from he horizonal axis o poin E. In erms of he regression coefficiens, his is X U 75h U X U 75h. The saisics presened in Panel II show ha he expor wage premium is an imporan componen of he overall wage premium. For example, i is a fifh of he wage premium for universiy-educaed workers in firms a he 50 h percenile of expor share, and onequarer for hese workers who are employed in firms a he 75 h percenile of expor share. The comparable values for high-skilled workers are 24.4 percen and 29.6 percen. The expor wage premium miigaes he overall premium for medium-skilled workers, reducing i by up o 27.2 percen for workers in firms a he 75 h percenile of expor share. The calculaions in he firs wo panels of Table 6 reflec wage premia relaive o low-skilled workers a firms ha do no expor. Panels III, IV, and V offer pairwise differences across all four caegories of workers a firms wih comparable levels of 23 These premia are relaive o low-skilled workers a firms ha do no expor. Thus, he only premium for low-skilled workers is hrough he expor wage premium and, for ha reason, he expor wage premium represens 100 percen of heir wage premium for his reason, calculaions for low-skilled workers are no included in his panel. 22

24 expors. Panel III presens he pairwise differences in expor wage premia a he 25 h, 50 h, and 75 h percenile values of expor share. 24 These can be illusraed by considering Figure 5 where, for example, he difference in he expor wage premium for universiyeducaed workers as compared o medium-skilled workers a he 75 h percenile of expor share is ((E U ) (G M )). The corresponding value from he regression coefficiens is. The resuls in his panel exhibi subsanial skill premia wihin U M X 75 h plans due o exporing. For example, he expor wage premium of universiy-educaed workers relaive o low-skilled workers, medium-skilled workers, and high-skilled workers a a plan a he 75 h percenile of expor share is 8.4 percen, 7.3 percen, and 3.6 percen, respecively, and high-skilled workers have a premium of 4.8 percen over lowskilled workers and 3.7 percen over medium-skilled workers. Panel IV shows ha he values in Panel III, which represen he wage premia associaed wih exporing, represen subsanial proporions of he pairwise differences in he respecive overall wage premia across skill levels. The resuls in his panel are comparable o hose in Panel II, alhough here he comparison group is exclusively lowskilled workers in firms ha do no expor and, in Panel IV, comparisons are made across skill groups in plans wih a common level of expor share. For example, a represenaive saisics in Panel IV is ha of high-skilled workers as compared o medium-skilled workers a he 75 h percenile of expor share. The difference in he expor wage premium, relaive o he difference in he overall wage premium, for his pair is U M X 75h 100% X U M As shown in his panel, he differences in he expor wage premia represen a subsanial proporion of he pairwise differences in he overall wage premia. A he median value of expor share, he expor-induced skill premia represens abou one-hird of he overall skill premia of high-skilled workers and universiy-educaed workers relaive o mediumskilled workers, and almos one-quarer of he overall skill premium of universiyeducaed workers o high-skilled workers. U M 75h 24 The saisics in his able are expor wage premia of workers of one skill-level versus anoher where boh skill levels are a a plan wih a common expor share. Thus, he expor wage premium relaive o low skilled workers exceeds ha in Panel I since hose saisics are for low-skilled workers in a plan ha does no expor and here is a negaive expor wage premium for low-skilled workers. 23

25 The final panel of Table 6 shows how a change in expor share affecs he wage gap beween workers a wo differen skill levels. These saisics represen he percenage poin change in expor-induced skill premia due o a change in he expor share from he 25 h percenile level o he 75 h percenile level. As shown in Panel V, a change of his magniude increases he difference beween universiy-educaed workers and low-skilled workers by 4.5 percenage poins, and beween medium-skilled workers and low-skilled workers by 4.0 percenage poins. The effecs are smaller for he difference in wages beween high-skilled workers and medium-skilled workers (2.0 percenage poins) or low-skilled workers (2.6 percenage poins). Each of he esimaes in Panel V are saisically significan a beer han he 95 percen level of confidence bu for ha beween high-skilled and universiy-educaed workers, which is significan a beer han he 90 percen level of confidence. We nex provide a furher disaggregaion of he expor wage premia by moving beyond an analysis based on 4 differen skill groups o one in which we inerac each of 340 occupaion dummies wih he expor share, obaining a differen esimaed expor wage premium for each of hese occupaions, as shown in 'O i o X j, Z Siz, Ii, Pj, Fi, j i, j, ln Wi, j, o, [3] o1 Z 2 where O i is a dummy variable vecor conaining he 340 occupaion dummies and conains he occupaion-specific expor share wage premium. To display he resuls, we form wage ceniles c k, k=1,,100, separaely for each year wih k=1 he lowes wage cenile. Then, we calculae he average wage premium of exporing by wage cenile k in year : E Exporpremium i p i 1 I i c k ; X k j, X 0 j, i o1 ' o O X p I i c ; X 0 io where I[.] is he indicaor funcion and p i he inverse drawing probabiliy of an observaion. If he condiional mean independence assumpion and he sable uni reamen value assumpion hold, hen his condiional expecaion has he inerpreaion j, i k j,, [4] o 24