Interindustry Wage Differentials, Technology. Adoption, and Job Polarization

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1 Inteindusty Wage Diffeentials, Technology Adoption, and Myungkyu Shim Hee-Seung Yang Abstact Using data on the U.S., we find that high-wage industies in 1980 expeienced (1) moe evident job polaization and (2) highe gowth ate of infomation and communication technology (ICT) capital pe woke between 1980 and These findings ae consistent with the hypothesis that fims optimally espond to inteindusty wage diffeentials, which (at least patly) aise fom exogenous factos at the fim level. As the elative pice of ICT capital declines, the pesistent stuctue of inteindusty wage diffeentials pushes high-wage industies to eplace outine wokes with ICT capital moe intensively than low-wage industies. As a esult, those industies exhibit slowe employment gowth of outine wokes than low-wage industies, which led to heteogeneity in job polaization acoss industies. Fist Daft: Decembe This Daft: May 18, We would like to thank Valeie Ramey, Giacomo Rondina, and Iina Telyukova fo thei insightful comments and invaluable suppot. We ae also gateful to Paul Chen, Tiffany Chou, Julie Cullen, Steven Davis, Davide Debotoli, Roge Godon, Youjin Hahn, Kwang Hwan Kim, Godon Hanson, John List, Bienda Rai, Yixiao Sun, and Johannes Wieland fo thei helpful comments and suggestions. We would also like to thank the semina and confeence paticipants at UC San Diego, Monash Univesity, Yonsei Univesity, Sogang Univesity, Austalian National Univesity, Shanghai Univesity of Finance and Economics, Koea Univesity, Univesity of Nebaska- Lincoln, 2013 Sping Midwest Maco Meeting, 2013 SED annual meeting, and 2014 SOLE annual meeting fo thei feedback. Hee-Seung Yang gatefully acknowledges financial suppot fom Monash Univesity. School of Economics, Shanghai Univesity of Finance and Economics, mkshim@mail.shufe.edu.cn Depatment of Economics, Monash Univesity, heeseung.yang@monash.edu

2 1 Intoduction The stuctue of the labo maket in the U.S. has changed damatically ove the past 30 yeas. One of the most pevalent aspects of the change is job polaization: employment has become inceasingly concentated at the tails of the skill distibution, while thee has been a decease in employment in the middle of the distibution. This hollowing out of the middle has been linked to the disappeaance of outine occupations that can be easily eplaced by machines. 1 In the U.S., outine occupations accounted fo aound 60 pecent of total employment in 1981, while this shae fell to 44 pecent in While many pevious studies have examined job polaization at the aggegate level (see Goos, Manning, and Salomons(2009); Acemoglu and Auto(2011); Cotes(2016); and Jaimovich and Siu (2014)), the extent of job polaization diffes acoss industies (see Auto, Levy, and Munane (2003); Goos, Manning, and Salomons (2014); and Michaels, Nataj, and Reenen (2014)). Figue 1.1 shows changes in employment shae by industy between 1980 and This figue demonstates that job polaization is moe ponounced in some industies than in othes. Fo instance, the decease in the employment shae of outine occupations is lage in manufactuing, communication, and business-elated sevices, while the decease is much smalle in tanspotation and etail tade. 1 As emphasized by Auto (2010), Goos, Manning, and Salomons (2009), and Michaels, Nataj, and Reenen (2014), job polaization is not esticted to the U.S.; seveal Euopean counties have expeienced job polaization as well. 2 Numbes ae calculated fom the Mach Cuent Population Suvey (CPS).

3 2 Changes in Employment Shae Mining Constuction Manufactuing nonduable goods Manufactuing duable goods Tanspotation Communication Utilities and Sanitay Sevices Duable goods Wholesale Tade Nonduable goods Wholesale Tade Retail Tade Finance, Insuance, and Real Estate Business and Repai Sevices Pesonal Sevices Entetainment and Receation Sevices Pofessional and Related Sevices Public Administation Aggegate Non Routine Cognitive Routine Non Routine Manual Figue 1.1: Changes in Employment Shae by Industy between 1980 and 2009 Note: The hoizontal axis denotes thee occupational goups (each occupational goup includes 16 industies and one aggegate vaiable) and the vetical axis denotes the change in employment shae of a specific occupational goup in each industy between 1980 and Souce: The U.S. Census. Shim & Yang: Inteindusty Wage Diffeentials, Technology Adoption, and

4 This pape povides a new pespective to undestand heteogeneity in job polaization acoss industies. In paticula, we find that inteindusty wage diffeentials, the phenomenon that obsevationally equivalent wokes ean diffeently when employed in diffeent industies, ae closely elated to the heteogeneous job polaization acoss industies; the annualized gowth ate of outine employment between 1980 and 2009 deceased by 0.42 pecent when the initial industy wage pemium in 1980 ose by 10 pecent, which is stictly geate than the estimates fo non-outine occupations in absolute tems. In othe wods, job polaization between 1980 and 2009 was moe appaent in the high-wage industies in We futhe find that the annualized gowth ate of infomation and communication technology (ICT, hencefoth) capital pe woke between 1980 and 2007 inceased by 0.35 pecent when the initial (i.e., 1980) industy wage pemium inceased by 10 pecent. On the othe hand, the annualized gowth ate of non-ict capital pe woke is not associated with the initial industy wage pemium. To undestand the empiical elationship between the inteindusty wage diffeentials and the degee of job polaization, we pesent seveal hypotheses that can potentially explain ou findings. In paticula, we examine whethe the elative pice of outine to othe occupations, initial shae of outine wokes, o capital-labo atio can pedict ou esults, and show that these hypotheses ae not suppoted by data. We then intoduce ou theoy, which is consistent with empiical evidence. In the theoy, inteindusty wage diffeentials aise fom exogenous factos that ae beyond fims contol. As a esult, high-wage fims seek altenative ways to educe poduction costs instead of loweing wages. The fim s esponse to the industy wage pemium would thus change employment towad othe poduction factos as in Bojas and Ramey (2000). Fim s adjustment of its employment, howeve, is not even acoss wokes; outine wokes ae moe easily eplaced by ICT capital. As the pice of ICT capital has substantially declined since the 1980s, fims in a high-wage industy ae moe likely to substitute ICT capital fo outine wokes than fims in a low-wage industy, which esults in diffeent degees of job polaization acoss industies. This pape has thee majo contibutions. Fist, ou study contibutes to the existing liteatue on job polaization by aiding undestanding of heteogeneity in job polaization acoss 3

5 industies. In paticula, we povide the fist evidence that polaized employment is connected with inteindusty wage diffeentials. Second, ou esults highlight the impotance of consideing exogenous factos in explaining the industy wage pemium, adding to the liteatue and discussion on inteindusty wage diffeentials. Lastly, this pape povides additional evidence to the liteatue on fims optimal esponses to the labo maket stuctue (Acemoglu (2002) and Caballeo and Hammou (1998)). The pape is oganized as follows. Section 2 intoduces two key concepts, inteindusty wage diffeentials and job polaization, with eviews of elated liteatue. Section 3 descibes the data, and Section 4 pesents main esults and intoduces hypotheses that can potentially justify ou findings. Afte we show that these hypotheses ae not suppoted by data, we intoduce ou theoy to explain empiical findings in Section 5. Section 6 concludes. 2 Liteatue Review In this section, we intoduce key concepts that ae impotant to undestand ou pape and discuss the elated liteatue. 2.1 Inteindusty Wage Diffeentials Pesistent dispesion in wages acoss industies (i.e., the existence of inteindusty wage diffeentials) has been one of the most challenging subjects in labo economics. In ode to undestand why it is so puzzling fom the pespective of the competitive labo maket equilibium theoy, it is useful to conside two wokes with the same obsevable socioeconomic chaacteistics (including education, age, gende, ace, egion, and occupation) but who wok in diffeent industies. The competitive labo maket theoy pedicts that the wages should be (at least in the long un) the same between the two wokes in equilibium. If wages diffe, a woke in a low-wage industy will attempt to find a job in a high-wage industy; in equilibium, this inceases (esp. deceases) labo supply to the high- (esp. low-) wage industy, and hence wages will be equalized in a competitive labo maket. This notion of a competitive labo maket, howeve, is not suppoted by data; fo instance, a woke employed in the petoleum-efining industy eaned about 40 pecent moe than a woke 4

6 industy wage pemium industy wage pemium Figue 2.1: Pesistency of Inteindusty Wage Diffeentials: Compaison between 1980 and 2009 Note: We omit the industy of hotels and lodging places, which has the lowest value of estimated coefficients in the wage egession of 1980, so that evey othe coefficient fo industy dummies has a positive sign. Souce: The U.S. Census and Ameican Community Suvey (ACS). in the leathe-tanning and finishing industy in 1984 even afte contolling fo all obsevables (Kuege and Summes (1988)). In addition, the wage dispesion is not a tansitoy petubation fom the competitive equilibium. To demonstate this, we compute the industy wage pemia in 1980 and 2009 sepaately using a typical wage equation, which egesses log wages ove vaious socioeconomic chaacteistics and industy fixed effects, and pesent a scatte plot of the two sets of industy fixed effects in Figue 2.1. It shows that industies that paid elatively high wages in 1980 also paid high wages in 2009, which implies that the stuctue of inteindusty wage diffeentials is highly pesistent. We also find, as Dickens and Katz (1987) show, that an industy vaiable has been a consistently impotant facto in explaining wage diffeentials. 3 Ou pape is unique in this liteatue in the sense that we study how inteindusty wage diffeentials can be associated with stuctual changes in the aggegate labo maket such as job polaization. In this egad, Bojas and Ramey (2000) is the only pape elated to ou study. 3 We un the wage egession (4.1) fo diffeent peiods (1980, 1990, 2000, and 2009) and compute the explanatoy powe of the wage equation with and without industy dummies, following Dickens and Katz (1987). The esults ae epoted in Table A.1. In paticula, 4 to 16 pecent of the wage vaiation is explained by industy. Inteestingly, the explanatoy powe attibutable to the industy is vey stable and substantial ove time, which implies that industy should be consideed as an impotant facto in explaining wages. 5

7 Bojas and Ramey (2000) find that industies that paid elatively high wages to wokes in 1960 expeienced (1) lowe employment gowth and (2) highe capital-labo atio gowth and highe labo poductivity gowth between 1960 and While they focus on the aveage effect of inteindusty wage diffeentials on wokes, ou findings emphasize the impotance of consideing heteogeneity acoss wokes (occupations) in studies of the labo maket. 2.2 We classify occupations into thee goups as follows, to be consistent with the job polaization liteatue including Auto (2010), Acemoglu and Auto (2011), and Cotes (2016): Non-outine cognitive occupations: Manages; Pofessionals; and Technicians Routine occupations: Sales; Office and administation; Poduction, cafts, and epai; and Opeatos, fabicatos, and laboes Non-outine manual occupations: Potective sevices; Food pepaation and building and gounds cleaning; and Pesonal cae and pesonal sevices Using the Mach CPS between 1971 and 2010, 4,5 we plot Figue 2.2 to show job polaization gaphically: while the employment shae of non-outine cognitive (hencefoth, cognitive) and non-outine manual (hencefoth, manual) occupations has gown ove time, that of outine occupations has deceased. One intuitive eason behind job polaization is that the skill (task) content of each occupation is diffeent. Among the thee goups, outine occupations ae most easily eplaced by ICT capital, as demonstated by Auto, Levy, and Munane(2003); the tasks that outine wokes pefom ae easie to codify than othe tasks because the tasks have outine pocedues. Meanwhile, cognitive and manual occupations ae not easily substituted. Fo instance, business decisions of manages (cognitive occupations) cannot be eplaced by technology; intoduction of new technology, such 4 Data wee extacted fom the IPUMS website: (see King, Ruggles, Alexande, Flood, Genadek, Schoede, Tampe, and Vick (2010)). 5 We apply the method of convesion factos to obtain consistent aggegate employment seies. See Shim and Yang (2015) fo a detailed discussion on the method of convesion factos. 6

8 Cognitive Routine Manual 0.45 Employment Shae t Figue 2.2: Note: The shaded egions ae the official NBER ecession dates. Souce: The Mach CPS. as advanced softwae, does not substitute fo these manages; athe, it is a complement to thei tasks. In addition, people involved in cooking o cleaning (manual occupations) cannot be diectly eplaced by machines; these jobs equie humans to pefom non-outine manual tasks. In contast, a geat potion of the tasks that a bank clek pefoms ae easily eplaced by an ATM; deposits and withdawals ae outine tasks, and machines can pefom these tasks moe efficiently than humans. Hence, these jobs have disappeaed ove time, as the economy has expeienced apid technological pogess in ICT capital. 6 Consistent with this stoy, Cummins and Violante (2002) show that investment-specific technological changes have mainly occued fo ICT capital athe than fo othe types of capital so that the elative pice of ICT capital has declined moe apidly since the 1970s. 7 6 Offshoability is also highe fo outine occupations than fo cognitive and manual occupations. Most of the sevice jobs (manual occupations) ae not tadable and occupations that equie cognitive tasks ae not easily offshoed while factoies can be elatively easily elocated to foeign counties. 7 The peiod in which the gowth ate of investment-specific technological changes inceased does not pefectly match the occuence of job polaization, which is usually said to be afte Consistently with this timing poblem, we find that job polaization also occued befoe 1980, while the magnitude was smalle than the one afte

9 A few papes have studied the possibility of heteogeneous job polaization acoss industies. 8 Acemoglu and Auto(2011) show that changes in industial composition do not play an impotant ole in job polaization. Jaimovich and Siu (2014) and Foote and Ryan (2014) note that job polaization may be moe ponounced in the constuction and manufactuing industies. While Auto, Levy, and Munane (2003), Goos, Manning, and Salomons (2014), and Michaels, Nataj, and Reenen (2014) also conside possible diffeences in job polaization acoss industies, they do not connect inteindusty wage diffeentials and heteogeneity in job polaization; howeve, ou findings indicate that they ae closely elated. 3 Data Thee ae two main souces of data fo this pape: (1) the decennial Census and ACS data, 9 and (2) the EU KLEMS data. Following Acemoglu and Auto (2011), we use the 1960, 1970, 1980, 1990, and 2000 Census and the 2006, 2007, and 2009 ACS. As Acemoglu and Auto (2011) note, the elatively lage sample size of the Census data makes fine-gained analysis within detailed demogaphic goups possible. 10 We dop fames (and elated industies) and the amed foces. Age is esticted to yeas and we only conside pesons employed in wage-and-salay sectos. Table B.1 in Supplementay Online Appendix B descibes the industy classification used in the analysis. 11 The second data set, EU KLEMS, has infomation on value added, labo, and capital fo vaious industies in many developed counties, including the U.S. The EU KLEMS is useful since it povides detailed infomation on capital: in the data, capital is divided into two pats, ICTcapitalandnon-ICTcapital,sowecananalyzetheolesofdiffeenttypesofcapitalinafim s behavio. We use U.S. data between 1980 and 2007, whee industies ae defined accoding to the 8 Some ecent papes, including Mazzolai and Ragusa (2013), Auto, Don, and Hanson (2013a), and Auto, Don, and Hanson (2013b), analyze job polaization at the local labo maket level. 9 Data wee extacted fom the Integated Public Use Micodata Seies (hencefoth, IPUMS) website: (Ruggles, Alexande, Genadek, Goeken, Schoede, and Sobek (2010)). 10 In detemining the size of the sample, we follow Acemoglu and Auto (2011): 1 pecent of the U.S. population in 1960 and 1970 and 5 pecent of the population in 1980, 1990, and We followdon (2009)to ovecomethe inconsistencypoblem ofoccupationcodes due to the fequentchanges in occupation coding in the Census and to constuct a consistent occupation seies. 8

10 Noth Ameican Industy Classification System of the United States (hencefoth, NAICS). Since the industy classification of EU KLEMS is diffeent fom the Census data, we eclassify industies to be consistent between the Census and the EU KLEMS data. Table B.2 in Supplementay Online Appendix B descibes the industy classification of EU KLEMS used in the analysis. 4 Empiical Analysis This section pesents ou main empiical findings. We fist estimate industy wage pemia as follows. logw hit = X hit β t +ω it +ε hit (4.1) whee w hit is the wage ate of woke h in industy i in Census yea t; X hit, a vecto of socioeconomic chaacteistics, includes the woke s age (five age goups: 16 24, 25 34, 35 44, 45 54, o yeas), educational attainment (five educational goups: less than 9 yeas, 9 to 11 yeas, 12 yeas, 13 to 15 yeas, o at least 16 yeas of schooling), ace (indicating if the woke is Afican-Ameican), gende, and egion of esidence (indicating in which of the nine Census egions the woke lives). Ou findings ae not sensitive to contolling fo state dummies and vaious inteaction tems of age, gende, ace, and education in the wage egession. We also contol fo thee occupation dummies (cognitive, outine, o manual occupations). ω it, an industy fixed effect, measues the industy wage pemia. The esult of equation (4.1) in 1980 is epoted in Table A Afte we obtain the estimated coefficients fo 60 industy fixed effects, ˆω it, fom equation (4.1), we estimate the second-stage egession as follows: y ijt,t+k = θ jˆω it +η ijt (4.2) whee y ijt is the vaiable of inteest such as employment of occupation goup j in industy 12 The estimated coefficients ae consistent with the usual intuition: (1) wages ae stictly inceasing in education, (2) wages also ise in ages until wokes each thei pime age, and then decease slightly, and (3) Afican-Ameican eans less. 9

11 i. y ijt,t+k is the annualized (aveage) gowth ate of y ijt between peiods t and t + k, and j {cognitive,outine,manual}. 13 We estimate equation (4.2) sepaately fo cognitive, outine, and manual occupations. Note that we use the estimated value, ˆω it, as a egesso in the second-stage egession, which aises a concen about the geneated egesso poblem. In paticula, it is possible that the eo tem in equation (4.2) is heteoscedastic. In ode to addess this issue, we weigh the egession by the initial (i.e., 1980) employment of each industy. In addition, the lage sample size of the Census data weakens the geneated egesso poblem; thee ae at least 1, 000 obsevations in each cell of occupation j in industy i in Census yea t. 14 Futhemoe, in ode to addess the potential endogeneity of the wage pemium, we use the pevious decade s estimated industy wage pemium as an instumental vaiable (IV). 4.1 and Initial Industy Wage Pemia In this section, we empiically test if inteindusty wage diffeentials ae elated to diffeent degees of job polaization acoss industies. If thee is no link between industy wage dispesion and job polaization, the coefficients on ˆω it in equation (4.2) would not diffe acoss occupations; that is, the subsequent employment gowth of each occupational goup does not eact diffeently to industy wage pemia. If they ae elated, howeve, we should obseve θ < θ c, θ m, whee, c, and m indicate outine, cognitive, and manual occupations, espectively. Figues 4.1 to 4.3 show gaphically how initial industy wage pemia ae elated to the subsequent employment gowth of each occupational goup. The hoizontal axis is the industy wage pemia in 1980, which is estimated using equation (4.1). The vetical axis denotes the aveage employment gowth ate of each occupational goup by industy between 1980 and We can obseve that the slope of the fitted line is negative and the steepest in the case of outine occupations (Figue 4.2), which suppots the hypothesis that fims facing high wages educe thei demand fo outine wokes moe. Inteestingly, Figue 4.3 shows that thee is a weake (positive) elationship between initial industy wage pemia and subsequent employment gowth 13 That is, y ijt,t+k = (log(y ij,t+k ) log(y ijt ))/k. 14 Fo a moe detailed discussion on the geneated egesso poblem, see Wooldidge (2001). 10

12 in manual occupations. We will etun to this issue late in Section Employment Gowth of Cognitive Occupation ( ) Industy Wage Pemium (1980) Figue 4.1: Dynamic Responses of Fims to Inteindusty Wage Diffeentials Cognitive Occupations Note: The size of a cicle denotes the employment level of each industy in Souce: The U.S. Census and ACS. Employment Gowth of Routine Occupation ( ) Industy Wage Pemium (1980) Figue 4.2: Dynamic Responses of Fims to Inteindusty Wage Diffeentials Routine Occupations Note: The size of a cicle denotes the employment level of each industy in Souce: The U.S. Census and ACS. 11

13 Employment Gowth of Manual Occupation ( ) Industy Wage Pemium (1980) Figue 4.3: Dynamic Responses of Fims to Inteindusty Wage Diffeentials Manual Occupations Note: The size of a cicle denotes the employment level of each industy in Souce: The U.S. Census and ACS. The main empiical finding based on equation (4.2) is epoted in Table 4.1. The dependent vaiable in the fist ow is the annualized gowth ate of aggegate employment fo industy i. The estimate confims the obustness of the main esult of Bojas and Ramey (2000) in the sense that thei finding is also obseved fo a late peiod; they use Census data between 1960 and In the emaining ows, we epot the estimates of equation(4.2), whee the dependent vaiable is the aveage gowth ate of employment fo occupation j in industy i between 1980 and When estimating equation (4.2) fo each occupation, the initial industy wage pemium (ˆω i,1980 ) does not depend on occupation. In this sense, the esults in Table 4.1 eveal how aveage industy wage pemia affect diffeent occupational goups in a distinct manne. The estimated coefficients epoted in the second to fouth ows in Table 4.1 ae consistent with Figues 4.1 to 4.3. The aveage gowth ate of outine employment between 1980 and 2009 deceased by 0.42 pecent when the initial industy wage pemium in 1980 inceased by 10 pecent, while that of cognitive employment deceased by 0.25 pecent. The initial industy wage pemium has a positive elationship with the subsequent employment gowth ate of the manual 12

14 Table 4.1: Estimates of Employment Gowth by Occupation Goups ( ) OLS IV Occupation Goups Coefficient R-Squaed Coefficient R-Squaed Total (0.0073) (0.0069) 0.24 Cognitive Occupations (0.0071) (0.0066) 0.13 Routine Occupations (0.0090) (0.0086) 0.21 Manual Occupation (0.0137) (0.0114) 0.13 Note: 1. The egessions ae weighted by each industy s initial (i.e., 1980) employment. 2. The instument is the pevious decade s (i.e., 1970) industy wage pemium. 3. The sample size is Robust standad eos ae epoted in paentheses. *** p < 0.01, ** p < 0.05, * p < 0.1. occupation goup and the OLS estimate is not significant. 15 In summay, employment gowth of outine occupations between 1980 and 2009 is negatively coelated with industy wage pemium in The IV estimates ae also epoted in Table 4.1. Both the OLS and IV egessions yield simila coefficients, which implies that measuement eos in the estimated ˆω it and the geneated egesso poblem ae not sevee. One might aise a concen that the esults might be exaggeated by the geat ecession that occued at the end of 2007, which dispopotionately affected the employment of outine occupations (Jaimovich and Siu (2014)). In ode to addess this issue, we estimate the same egession with a sample peiod between 1980 and 2007, which is epoted in Table 4.2. The esults ae simila to those epoted in Table 4.1: the subsequent employment gowth of outine occupations between 1980 and 2007 still deceases in the initial industy wage pemium and its coefficient isthe geatest inabsolute tems. 17 Inaddition, onemight aguethat theheteogeneity in job polaization might be diven by pat-time wokes as they ae moe likely to be affected by fims esponses to wage pessue and moe likely to have outine occupations. In Table A.3, we conduct the same execise with a sample of full-time wokes only and the esults ae lagely 15 We test if these coefficients ae significantly diffeent fom each othe; at the 5 pecent significance level, θ is not equal to eithe θ c o θ m, and hence, the fim s esponse to the initial industy wage pemium is not unifom acoss diffeent occupations. 16 Inteindusty wage diffeentials had been obseved even pio to 1980; fo instance, the estimation of Bojas and Ramey (2000) is based on the industy wage pemium in The magnitude of the esponsiveness is, howeve, much lowe than that of the latte peiod and the explanatoy powe dops by half. This suggests that the heteogeneous aspect of job polaization acoss industies became moe ponounced afte Estimates with a sample peiod between 1980 and 2006 ae also simila to the main esults. 13

15 unaffected. Table 4.2: Estimates of Employment Gowth by Occupation Goups ( ) OLS IV Occupation Goups Coefficient R-Squaed Coefficient R-Squaed Total (0.01) (0.0093) 0.22 Cognitive Occupations (0.0083) (0.0076) 0.11 Routine Occupations (0.0097) (0.0095) 0.18 Manual Occupations (0.0154) (0.0136) 0.00 Note: 1. The egessions ae weighted by each industy s initial (i.e., 1980) employment. 2. The instument is the pevious decade s (i.e., 1970) industy wage pemium. 3. The sample size is Robust standad eos ae epoted in paentheses. *** p < 0.01, ** p < 0.05, * p < 0.1. Anothe possible concen about ou estimates obtained fom equation (4.2) is that thee might be othe industy-specific factos that could affect the subsequent employment gowth of each occupation goup. We test the obustness of ou esults to the inclusion of vaious industyspecific factos: shae of outine wokes in industy i in 1980, capital pe woke and ICT capital pe woke in industy i in , and union membeship ate in industy i in The estimation esults ae epoted in Table Table 4.3: OLS Estimates of Employment Gowth by Occupation Goups ( ): Including Industy-Specific Vaiables Cognitive Routine Manual Industy wage pemium Routine shae Capital pe woke ICT capital pe woke Union membeship (1983) R Note: 1. The egessions ae weighted by each industy s initial (i.e., 1980) employment. 2. The sample size is Robust standad eos ae epoted in paentheses. *** p < 0.01, ** p < 0.05, * p < Infomationoncapitalisonlyavailablefo29industiesinEUKLEMSdata; thus, weassignedtheinfomation fo those industies to the 60 Census industies by matching industy codes. 19 Union data at industy level ae available only fom See Hisch and Macpheson (2003) fo details. 20 We discuss in detail why the fist two vaiables ae included in the egession in Section

16 We find that the inclusion of the vaious industial factos does not alte ou esults in Table 4.1. In fact, it inceases the diffeences between the coefficients of outine wokes and nonoutine wokes. Hence, ou main esults ae obust to the addition of othe industy-specific factos. The esults also show that union membeship seems to affect employment gowth of non-outine occupations only, even though the highe union membeship ate might put moe pessue on fims. This might be because outine wokes wee mostly coveed by unions until the 1990s and unions might pevent fims fom eplacing them with capital. As the last obustness check, we estimate the same second-stage egession with a diffeent dependent vaiable the changes in employment shae of occupation goups between 1980 and As shown in Table 4.1, the employment gowth of outine occupations has been lowe than that of cognitive and manual occupations fo the last 30 yeas. As a esult, the employment shae of outine occupations has declined, while the shae of at least one of eithe cognitive o manual occupations has inceased. Thus, we should obseve that (1) the change in employment shae of outine occupations is negatively elated to the initial industy wage pemium and (2) the change in employment shae of cognitive o manual occupations is (weakly) positively elated to the initial industy wage pemium. Inestimating equation (4.2), we set y ijt,t+k = es ij,t+k es ijt, whee es ijt is the employment shae of occupation j in industy i at Census yea t. Table 4.4 summaizes the esults of the altenative estimation. Table 4.4: Estimates of Employment Shae by Occupation Goups ( ) OLS IV Occupation Goups Coefficient R-Squaed Coefficient R-Squaed Cognitive Occupations (0.0802) (0.0808) 0.00 Routine Occupations (0.0572) (0.0599) 0.16 Manual Occupations (0.0960) (0.0797) 0.11 Note: 1. The egessions ae weighted by each industy s initial (i.e., 1980) employment. 2. The instument is the pevious decade s (i.e., 1970) industy wage pemium. 3. The sample size is Robust standad eos ae epoted in paentheses. *** p < 0.01, ** p < 0.05, * p < 0.1. Fist, the employment shae of outine occupations deceases moe in industies with a high initial wage pemium, which is consistent with the pevious esults in Table 4.1. Second, the 15

17 coefficient fo manual occupations is much geate than zeo in both the OLS and IV egessions, while the coefficient fo cognitive occupations is estimated to be almost zeo. This is because (1) the negative esponsiveness of the employment gowth of cognitive occupations to the initial industy wage pemium is not lage compaed to that of outine occupations and (2) thee is weak coelation between the subsequent employment gowth of manual occupations and the initial industy wage pemium. 4.2 ICT Capital pe Woke and Initial Industy Wage Pemia We now analyze if gowth ate of ICT capital pe woke since 1980 is elated to industy wage pemia in In addition, we also test if the elationship between the gowth ate of ICT capital pe woke and initial industy wage pemia is diffeent fom the elationship between that of non-ict capital pe woke and initial industy wage pemia. If non-ict capital is geneal-pupose capital, the coefficients fom the egession would be lowe in magnitude fo non-ict capital pe woke than fo ICT capital pe woke. Notice that the gowth ate of capital level may be negatively elated to the initial industy wage pemium. If the size of an industy shinks as labo demand deceases, capital demand itself might also decease. If the ate at which the demand fo capital deceases is lowe than the ate at which the demand fo labo deceases, the esulting capital-labo atio gows in the industy wage pemium. Fo the analysis, we use the EU KLEMS database. Since it povides infomation on employment and capital in 29 industies, we ecompute the initial industy wage pemium in 1980 by eclassifying the Census 60 industies into 29 industies. 21 Each capital seies (aggegate capital, ICT capital, and non-ict capital) is eal fixed capital stock based on 1995 pices. In ode to obtain capital pe woke seies, we divide capital by employment fo each industy. We fist show gaphical evidence of ou agument. Fist, Figue 4.4 shows a positive elationship between the industy wage pemium in 1980 and the subsequent annualized gowth ate of ICT capital pe woke between 1980 and Figue 4.5, howeve, suggests that changes in non-ict capital pe woke between 1980 and 2007 may not be pecisely elated to inteindusty wage diffeentials. 21 Details on the classification can be found in Supplementay Online Appendix Table B.2. 16

18 Gowth of ICT Capital pe Woke ( ) Industy Wage Pemium (1980) Figue 4.4: ICT Capital pe Woke to Initial Industy Wage Pemium ( ) Note: The size of a cicle denotes the employment level of each industy in Souce: The EU KLEMS. Gowth of Non ICT Capital pe Woke ( ) Industy Wage Pemium (1980) Figue 4.5: Non-ICT Capital pe Woke to Initial Industy Wage Pemium ( ) Note: The size of a cicle denotes the employment level of each industy in Souce: The EU KLEMS. Fo the complete analysis, we estimate equation (4.3). y it,t+k = θˆω it +η it (4.3) 17

19 whee y it is capital pe woke, capital level, o employment in industy i at time t. The OLS and IV esults, which ae quite simila, ae epoted in Table 4.5. Befoe we discuss the main esult, we focus on the last ow, in which the dependent vaiable is the aveage employment gowth ate. The estimate using the EU KLEMS data is simila to the coefficient obtained fom the Census data (see Table 4.1), which confims the obustness of ou findings. Table 4.5: Estimates of Capital, Poductivity, and Employment Gowth ( ) OLS IV Dependent Coefficient R-Squaed Coefficient R-Squaed Capital/Woke (0.0134) (0.0139) 0.05 ICT Capital/Woke (0.0190) (0.0171) 0.09 Non-ICT Capital/Woke (0.0136) (0.0144) Capital (0.0110) (0.0114) 0.10 ICT Capital (0.0217) (0.0204) Non-ICT Capital (0.0107) (0.0115) 0.25 Output (0.0089) (0.0087) 0.01 Labo Poductivity (0.0089) (0.0091) 0.22 Employment (0.0076) (0.0072) 0.27 Note: 1. Both the EU KLEMS and the Census data ae used fo the estimation. 2. The egessions ae weighted by each industy s initial (i.e., 1980) employment. 3. The instument is the pevious decade s (i.e., 1970) industy wage pemium. 4. The sample size is Robust standad eos ae epoted in paentheses. *** p < 0.01, ** p < 0.05, * p < Labo poductivity is obtained by dividing output by wokes in each industy. 7. Capital and output ae eal vaiables. The elevant coefficients fo diffeent types of capital ae pesented in the fist thee ows. As the initial industy wage pemium inceased by 10 pecent, the annualized gowth ates of aggegate capital pe woke, ICT capital pe woke, and non-ict capital pe woke between 1980 and 2007 inceased by 0.14 pecent, 0.35 pecent, and 0.03 pecent, espectively. That is, θ ICT > θ Aggegate > θ non ICT. Futhemoe, only θ ICT is statistically significant. The fouth to the sixth ows in Table 4.5 ae also notewothy. Fist, both capital and non- ICT capital decease in the initial industy wage pemium. Togethe with the fact that these industies also decease demand fo labo, capital pe woke and non-ict capital pe woke ae not elated to inteindusty wage diffeentials. ICT capital, howeve, is not coelated with the 18

20 initial industy wage pemium; as a esult, ICT capital pe woke ises moe in industies with a high initial industy wage pemium. Finally, we find that the gowth ate of labo poductivity inceases in the initial wage pemium, which is consistent with Bojas and Ramey (2000). 4.3 Possible Explanations In this section, we examine thee hypotheses that might explain ou findings and show that none of them ae consistent with empiical evidence Pice Effect: Ae Routine Wokes Paid the Highest? Note that the main findings in Table 4.1 offe two possible explanations. The fist is the task content explanation: as outine jobs can be easily eplaced by othe poduction factos, demand fo outine occupations is moe sensitive to the initial industy wage pemium. The second agument is the elative pice explanation: if the outine occupations ae paid moe than othe goups, fims would decease thei elative demand fo the outine occupation goup since this goup is actually the most expensive poduction facto (while the popety of tasks equied by outine occupations may enhance the fims dynamic esponses to inteindusty wage diffeentials, it may not be of the fist ode). To check which explanation fits bette, we conside an occupation-specific industy wage pemium, denoted as ω ijt, which is the wage pemium of occupation j in industy i, in the following altenative wage equation: logw hit = X hit β t +ω it ψ }{{ jt } +ε hit (4.4) =ω ijt whee ω it is the industy fixed effect and ψ jt is the occupation fixed effect. Thus, ω it ψ jt is the inteaction of each industy dummy and each occupation dummy. We call this the occupationspecific industy wage pemium. In this altenative wage equation, we do not include the fixed effect tems, ω it and ψ jt. By egessing the above equation, we obtain infomation about the extent to which an occupation goup in a specific industy eans moe than the same occupation goup in othe industies, and this also allows fo within-industy compaisons of the wage pemia. Figue 4.6 depicts occupation-specific industy wage pemia by industy. In ode to see how 19

21 the aveage industy wage pemium (ω it ) and the occupation-specific industy wage pemium (ω ijt ) ae elated, we sot industies by the aveage industy wage pemium in ascending ode. To theleft, theeaelow-wageindusties such ashotels andlodgingplaces, andtotheight, thee ae high-wage industies such as mining and investment. All values ae estimated in Figue 4.6 shows that the elative pice explanation is not suppoted by the data: in any industy, we obseve that ω ict > ω it > ω imt, which means that the cognitive occupations ae paid the most, followed by the outine and manual occupations. Hence, we can exclude the possibility of the elative pice explanation. 22 Figue 4.6 also shows that the occupation-specific industy wage pemium ises almost monotonically in the aveage industy wage pemia fo cognitive and outine occupation goups, while thee is much vaiation in the manual occupation-specific industy wage pemium. This is one of the easons that the effect of the aveage industy wage pemium on the employment gowth of the manual occupations is not negative in Table 4.1; even when fims face elatively highe aveage industy wage pemia, fims may not pay high wages to manual wokes. Fo example, the secuity, commodity bokeage, and investment companies industy (on the ight in Figue 4.6)paidmanual wokes less thanquiteafewothe industies did. Asaesult, thewagepessue fom the manual occupation goup is not as lage as the pessue fom othe occupation goups. Theefoe, fims have less incentive to decease thei labo demand fo manual occupations when facing high wages Level Effect: Heteogeneity in elative impotance of outine wokes We intoduce anothe hypothesis that the initial shae of outine wokes is impotant to undestand the elationship between inteindusty wage diffeentials and job polaization. To test this hypothesis, we pay attention to the fact that the coelation between the employment shae of outine wokes in 1980 and the industy wage pemium in 1980 is stictly positive. Fo instance, 22 One inteesting finding is that the slope of the line in Figue 4.6 is steepe fo outine occupations than fo cognitive occupations. In the end, the gap between the cognitive occupation-specific industy wage pemium and outine occupation-specific industy pemium becomes almost zeo. This fact implies that while cognitive occupations ae paid moe than outine occupations, thee is a tendency fo high-wage industies to actually pay elatively moe fo the outine occupations than low-wage industies. This featue may have a pice effect on ou estimates, but given that the level of the cognitive occupation-specific industy wage pemium is highest fo any industy, we do not analyze this futhe. 20

22 1.4 Occupation Specific Industy Wage Pemium Cognitive Specific Pemium Routine Specific Pemium Manual Specific Pemium 0 Low Wage Industy Industies High Wage Industy Figue 4.6: Occupation-Specific Industy Wage Pemium Note: We ode industy by the industy wage pemium obtained by equation (4.1). Souce: The U.S. Census and ACS. the manufactuing industy had a highe shae of outine wokes than othe industies in 1980 and it paid elatively highe wages to wokes because it faced highe unionization ates. Theefoe, as the elative pice of capital has declined, the high-wage industies would have expeienced moe eplacement of outine wokes because they employed outine wokes moe intensively in 1980; that is, the level effect might be a dominant eason why the job polaization was moe evident in the high-wage industies. In the sense that level effect is the poduct of heteogeneous poduction functions acoss industies, ou analysis in this section can be intepeted as the indiect test of the hypothesis based on poduction functions. We test this hypothesis by eplacing the initial industy wage pemium with the initial employment shae of outine wokes in the main equation (4.2). The esult in Table 4.6 does not suppot the level effect: when we estimate the effect of the initial shae of outine wokes on the employment gowth of each occupation, the coefficient fo outine occupations is athe smalle in absolute value than the coefficient fo cognitive occupations. Theefoe, we ae able to ule out the level effect of the initial shae of outine wokes. 21

23 Table 4.6: OLS Estimates of Employment Gowth by Occupation Goups ( ): Level Effect Occupation Goups Coefficient R-squaed Total (0.0075) 0.30 Cognitive Occupations (0.0071) 0.33 Routine Occupations (0.0116) 0.07 Manual Occupations (0.0103) 0.09 Note: The main egesso is the employment shae of outine wokes in 1980 instead of the initial industy wage pemium Wage pemium as outcome of high capital-labo atio Lastly, we test the hypothesis that the high wage pemium was the consequence of high capital-labo atio in 1980, which is basically based on competitive labo maket theoies. Capital-intensive industies might pay highe wages in 1980 because thei labo poductivity was high. Hence, as the pice of capital declines, those industies might adopt moe capital since they ae moe efficient in using capital by the intinsic natue of the industies. As a esult, moe (outine) wokes might have been eplaced by (ICT) capital in capital-intensive industies. Howeve, this hypothesis is at odds with data in two espects. Fist, it is not consistent with the long-un tend of an industy wage pemium. If this theoy is coect, the dispesion of industy wage pemium should have futhe inceased because the (ICT) capital-labo atio inceased moe in high-wage industies as in Table 4.5. Howeve, industy wage dispesion has slightly deceased (see Bojas and Ramey (2000)). Second, we again estimate the main equation (4.2) by eplacing the initial industy wage pemium with the initial ICT capital-labo atio. 23 The esult in Table 4.7 shows that the last hypothesis is not consistent with the data: the effect of capital-labo atio in 1980 is almost zeo. In addition, the estimation esult in Table 4.3 shows that ou finding is not affected by the factos that we discussed in this section. 23 Results do not change when we use initial (geneal) capital-labo atio. 22

24 Table 4.7: OLS Estimates of Employment Gowth by Occupation Goups ( ): Capital- Labo Ratio Occupation Goups Coefficient R-squaed Total ( ) 0.00 Cognitive Occupations ( ) 0.00 Routine Occupations ( ) 0.00 Manual Occupations ( ) 0.03 Note: The main egesso is the capital-labo atio in 1980 instead of the initial industy wage pemium. 5 Theoetical Consideation: Fims Responses to Pesistent Wage Stuctue acoss Industies In the pevious section, we conside thee possible hypotheses, but none of them ae shown to be fully suppoted by the data. Then, how can inteindusty wage diffeentials be connected to heteogeneity in job polaization? We suggest a plausible hypothesis in this section: it is the fim s optimal esponse to the existing inteindusty wage diffeentials, which aise fom exogenous factos that cannot be contolled by fims, that esults in diffeent degees of job polaization acoss industies. We fist note that thee exist two souces of inteindusty wage diffeentials: (1) woke heteogeneity and(2) exogenous factos to fims. Exogenous factos include diffeent union powe acoss industies, compensating wage diffeentials, seach fiction with positive labo mobility cost, and heteogeneous detection technology fo shiking wokes to geneate inteindusty wage diffeentials. 24 We fist show, in subsection 5.1, that a model assuming woke heteogeneity without exogenous factos does not explain ou findings. Convesely, in subsection 5.2, we show that the pedictions of ou main model (that is, assuming exogenous factos without woke heteogeneity) ae consistent with the data. The intuition of ou theoy is as follows; the cost of labo to poduce the same output, which is the poduct of wage and employment, is diffeent acoss industies. As it is difficult 24 It can be shown that the assumptions made hee yield the same equilibium outcomes. The esults ae available upon equest. 23

25 fo high-wage fims to educe wages elative to low-wage fims, they espond to the high labo cost by adjusting employment ove time. When a fim changes its labo demand, howeve, the effect is not unifom acoss wokes. Since the outine wokes tasks ae moe easily codifiable o computeized, they ae moe affected by a fim s dynamic decision to substitute capital fo labo. 25 In paticula, the elative pice of ICT capital has deceased since the 1980s, and fims with incentives to adjust employment ae moe likely to educe the elative demand fo outine wokes by eplacing them with ICT capital. As a esult, fims in a high-wage industy expeience moe evident job polaization as the demand fo outine wokes declines to a lage extent in these fims. In addition, the ICT capital-labo atio in a high-wage industy ises by a geate amount than in a low-wage industy, since moe ICT capital is intoduced to substitute fo outine wokes. In a simple patial-equilibium fim model, we conside two types of tasks (wokes) nonoutine tasks (non-outine wokes) and outine tasks (outine wokes) in ode to captue the featues of job polaization. 26 As is usually assumed in the job polaization liteatue, capital is a elative substitute fo outine wokes, while it is a elative complement to non-outine wokes. 27 In this sense, the capital consideed in ou model can be intepeted as ICT capital. In ode to geneate inteindusty wage diffeentials, we assume that owing to some exogenous factos, industy 1 pays highe wages than industy 2. The theoetical esults we show in section 5.2 ae peseved even when we conside the geneal equilibium model Model with Woke Heteogeneity We fist examine if the competitive view of the labo maket geneating inteindusty wage diffeentials can explain ou findings. One of the main aguments fo industy wage dispesion is that wokes poductivities ae actually diffeent (due to unobseved heteogeneity). This also nests the case whee a woke is paid moe because 25 Offshoing is anothe possibility, as Goos, Manning, and Salomons (2014) and Oldenski (2014) show. 26 One might futhe decompose non-outine wokes into cognitive and manual wokes; given, howeve, that these wokes have simila oles in the poduction function (both wokes ae elative complements to capital), we choose to use only two types of wokes in the model fo simplicity of discussion. The same stategy is used by Beaudy, Geen, and Sand (2013) and Jaimovich and Siu (2014). 27 See Auto, Levy, and Munane (2003), Auto and Don (2013), and Cotes (2016), fo instance. 28 The esults ae available upon equest. 24

26 she is moe poductive in using capital. Suppose that thee exist the same numbes (measue 1) of wokes and fims in the economy. In the labo maket, each fim that poduces the same consumption goods is matched to one woke. Each woke n is assumed to have diffeent poductivity, and x n denotes the poductivity of a woke whee n [0,1]. Without loss of geneality, x n is assumed to be deceasing in n. The poduction function of a fim is given as y = x n +x k k, whee k is the amount of capital a fim buys fom the intenational maket at unit pice p and x k is the poductivity (efficiency) of the capital measued by the consumption goods. Fo simplicity, the poduction function assumes pefect substitutability between labo and capital. Thus, one implicit assumption hee is that the wokes in this economy ae outine wokes. 29 Note that if thee is no capital, y = x n such that the competitive labo maket implies w n = x n. Hence, the wage diffeentials among wokes ae the diect esult of thei poductivity diffeences. We now intoduce capital into the economy, and the fim minimizes TC = w + pk subject to the poduction function. Suppose that a fim that initially hied woke n poduces 1 unit of consumption goods. Then, the total cost of poducing this 1 unit of consumption goods is equal to 1/x n when the fim employs only labo, and p/x k when it uses only capital. This implies the theshold condition of the fim fo poduction: a fim chooses to use labo (esp. capital) in the poduction if x k /p < x n (esp. x k /p > x n ). Suppose that the pice of capital was initially so high that x k /p < min{x n }, and hence, no fim used capital. The pice of capital deceases owing to the outine-eplacing technology changes. Then, the following poposition holds, which is a natual consequence of the model above. Poposition 5.1 ( when Wokes ae Heteogeneous). Suppose that x k /p < min{x n }; hence, no fim used capital. As p deceases, the (elatively) lowest-wage fim adopts capital at fist. In othe wods, the occuence of job polaization, that is, the eplacement of wokes with capital (othe poduction factos), is fist obseved in the low-wage fims. Theefoe, the pediction of the model that assumes only ex-ante heteogeneous wokes is 29 The key esults ae identical even when we include non-outine wokes in the poduction function. Fo example, y = min{x n h,x +x k k}, whee x n is the poductivity of the non-outine woke, x is the poductivity of the outine woke, and h is the numbe of non-outine wokes that ae employed by a fim. 25