Service Sector Productivity and Economic Growth in Asia *

Servce Sector Productvty and Economc Growth n Asa * Jong-Wha Lee + Korea Unversty and Warwck J. McKbbn The Australan Natonal Unversty and The Brookngs Insttuton September 2013 * Prepared for the IMF conference, Asa: Challenges of Stablty and Growth, on September 26-27, 2013. We thank Perre-lver Gournchas and Ayhan Kose for very useful suggestons, Kwanho Shn for helpful dscusson and data, and Hanol Lee and Chul Jong Song for research assstance. + Correspondng Author: Economcs Department, Korea Unversty, Sungbuk-Ku, Anam-dong 5-1, Seoul 136-701, Korea. Tel.: +82-2-33202216, fax: +82-2-9284948, E-mal: jongwha@korea.ac.kr. 0

Abstract Ths paper nvestgates the role of an expandng servce sector for structural adjustment and economc growth n Asa. There have been major employment shfts toward the servce sector n 11 Asan economes snce 1990. Despte strong convergence of labor productvty at both the aggregate economy level and sectoral levels, there reman sgnfcant dfferences n labor productvty across economes and across sectors. Lower labor productvty n the servce sector relatve to the manufacturng sector has n general hampered overall economc growth n Asa. Nevertheless, modern servces ncludng the transportaton, storage, and communcatons and the fnancal ntermedaton and busness servces, have experenced hgher productvty growth, playng a role of a second growth engne n Asa. A shft-share analyss shows that the servce sector has made a sgnfcantly postve contrbuton to aggregate labor productvty growth, both through wthn- and structural change- effects, exceedng the net contrbuton of manufacturng sector. Servce sector growth tends to be hgher when qualtes of human resources and nsttutons mprove, the level of democracy ncreases, and the level of trade openness s lower. The paper explores the mpact of more rapd growth n labor productvty growth n the servce sector n Asa based on an emprcal general equlbrum model. The model allows for nputoutput lnkages and captal movements across ndustres and economes, and consumpton and nvestment dynamcs. We fnd that faster productvty growth n the servce sector n Asa benefts all sectors eventually, contrbutng to the sustaned and balanced growth of Asan economes, but the dynamc adjustment s dfferent across economes. Ths adjustment depends on the sectoral composton of each economy, the captal ntensty of each sector and the openness of each sector to nternatonal trade. In partcular, durng the adjustment to hgher servces productvty growth, there s a sgnfcant expanson of the durable manufacturng sector that s requred to provde the capta stock that accompanes the hgher aggregate economc growth rate. Ths s partcularly mportant for the aggregate adjustment n captal goods exportng economes such as Korea and Japan. 1

I. Introducton The purpose of ths paper s to analyze the role of the servce sector n structural adjustment and economc growth n Asa. The paper emprcally nvestgates the hstorcal experence of Asan economes and explores a scenaro of more rapd catch-up of servce sector productvty growth over comng decades for Asan economes. In the era of ndustralzaton snce World War II, major Asan economes ncludng Japan, the Republc of Korea (Korea henceforth) and the People s Republc of Chna (PRC) have undergone spectacular economc transformatons fast economc growth and major employment shfts from the agrculture sector toward the manufacturng sector. The manufacturng sector has been a key engne of growth over ths perod. Ths rapd ndustralzaton has been supported by hgh savng and nvestment rates and an export-orented polcy. In recent decades, however, the pace of output growth n the ndustralzed East Asan economes has slowed down sgnfcantly. Japan and Asan Newly Industralzed Economes (ANIEs) that had experenced fast growth began to grow less rapdly over tme as ther per capta ncome gap wth that of the US narrowed. A number of factors ncludng slower labor force growth, lower nvestment rates, declnng rates of return to nvestment and sluggsh technology advancement have been hghlghted as the major causes of the growth deceleraton. Another salent feature n East Asa s growth s the rse of servce ndustres wth major employment shfts toward the servce sector. The well-establshed emprcal stylzed fact shows that there s a postve relatonshp between the share of servces n GDP (or total employment) and GDP per capta (Clark, 1957 and Chenery, 1960). More recently, Echengreen and Gupta (2012) argue that the relatonshp s not lnear, followng two dstnct wave patterns of servce 2

sector growth. In the frst wave, the servce share n output and employment rse wth GDP per capta at a deceleratng rate. The servce share rses agan n the second wave at a hgher ncome level. They argue that the frst wave features the rse of tradtonal servces whle ncomes are stll low, whle the second wave features modern servces ncludng post and communcaton, fnancal ntermedaton, computer, and busness servces. How does the rse n the servce sector contrbute to overall growth n Asan economes? As an economy grows, the servce sector becomes larger and hence the overall growth depends more on the performance of the servce sector. Thus, the servce sector s contrbuton to the overall growth tends to become proportonally bgger wth economc development and an expanson of the servce sector. However, f the labor productvty growth of the servce sector s lower than that of ndustral sector, the ncrease n the sze of the servce sector wth dendustralzaton can have a harmful effect on overall output growth. The lterature presents a number of theores that attempt to explan the change n the servce sector share and ts mplcaton to overall economc growth. Structural change can be drven by both demand and supply-sde factors. The semnal paper by Baumol (1967) presents a model of unbalanced growth, n whch the hgher productvty growth n the progressve (manufacturng) sector than n the stagnant (servce) sector causes shfts of labor from manufacturng to servce ndustres and shows aggregate output growth slows down over tme as the sector wth the lower productvty growth expands. Recent papers by Nga and Pssardes (2007) and Acemoglu and Guerrer (2008) develop multsector growth models motvated by Baumol. In ther models, total factor productvty or factor proporton dfferences generate employment shfts to the stagnant servce sector over the 3

(non)-balanced growth path. Another strand of lterature ncludng Latner (2000), Kogsamut, Rebelo and Xe (2001), and Foellm and Zwemuller (2008) rely on a demand-sde explanaton for structural change. 1 In secton V of the paper usng an emprcally based global ntertemporal mult-sector general equlbrum model (a large scale DSGE model), we explore what happens f labor productvty rses n the servce sector n ndvdual Asan economes and then across all of Asan economes at the same tme. The model allows for consderaton of nter-ndustry nput-output lnkages, factor movements, and consumpton and nvestment dynamcs. The model also ncorporates spllovers across the border through trade and fnancal lnkages. The results show that enhancng productvty n the servce sector can play a major role as a new growth engne leadng to Asa s strong and sustanable growth n the long-run. Labor moves out of the servce sector n the longer run but the adjustment across the other non- servce sectors n the short run depends on a range of factors ncludng: the characterstcs of each sector (n terms of factor nputs and demand bundles), and what happens to aggregate nvestment and consumpton n an economy and the sectoral composton of that spendng and the effects of productvty growth on the real exchange rate through nflows of global captal whch temporally hurts the compettveness of trade exposed sectors. The story s qute complex n the decades followng a new productvty surge but n the longer term the outcome s broadly smlar to the Nga and Pssardes (2007) and Acemoglu and Guerrer (2008) adjustment story. A number of recent papers focus on analyzng the patterns of structural change and economc growth experences of the major East Asan economes such as Japan and the emergng 1 See Herrendorf, Rogerson and Valentny (2013) for lterature survey. 4

Asan economes (ADB, 2012, Buera and Kabosk, 2012, and Uy, Y and Zhang, 2013). However, as far as we are aware, no paper has explctly focuses on nvestgatng the short run adjustment and the long run mplcatons of expandng servce sector productvty growth on overall economc growth n Asa. Ths paper proceeds as follows. Secton II descrbes the data and analyzes the stylzed patterns n structural change and convergence of labor productvty n the Asan economes. Secton III uses the technque of shft-share analyss to nvestgate the role of servce sector productvty growth n overall economc growth. Ths secton also dscusses the estmates of total factor productvty growth rates at the detaled servce ndustres n Japan and Korea and compares them to those n the Unted States. Secton IV uses cross-country panel data sets to examne the determnants of servce sector productvty growth. Secton V uses the emprcal results on hstorcal productvty experence n Asa as exogenous nputs nto a large scale ntertemporal general equlbrum model of the global economy. Gven ths future baselne, we then explore dfferent future scenaros of servce sector productvty growth n Asa and how ths affects Asan economes ndvdually and the spllovers wthn Asa and throughout the world. Secton VI provdes some concludng observatons. II. Structural Transformaton and Economc Growth n Asa In ths secton, we document the patterns of structural transformaton, focusng on change n the share of servces n total output and employment, n major Asan economes. A. Data and sample: 5

ur data are from the Gronngen Growth Developng Centre (GGDC) 10-sector database, whch provdes annual data on value added (at both current and constant prces) and employment data from 1970 to 2005 (Tmmer and de Vres, 2007). The GGDC data provdes dsaggregated data consstng of ten sectors, as defned by the ISIC Revson 2. The data covers ten Asan economes Japan, four Asan NIES (Korea, Tawan, Sngapore, and Hong Kong), ASEAN-4 (Indonesa, Malaysa, Phlppnes, and Thaland), and Inda. We have expanded the sample by addng Chna, compled by McMllan and Rodrk (2011). We have also added the Unted States for the reference country, for whch data s avalable from the GGDC 10-sector database. We aggregate the orgnal data nto 9 sectors by combnng communty, socal and personal servces wth government servces. The servce sector conssts of four servce branches wholesale and retal trade; hotels and restaurants; transport, storage and communcatons; fnance, nsurance, real estate and busness servces; and communty, socal, personal and government servces. We focus on the sample perod from 1990 to 2005 because data on Chnese ndustres are avalable from 1990. B. Pattern of structural change Fgure 1 summarzes the change n sectoral employment shares for agrculture, manufacturng, and servce sectors. The vertcal axs s the share of employment n 1990, 1995, 2000 and 2005 n 11 major Asan economes and the U.S. The horzontal axs s the log of GDP per worker n 2000 nternatonal dollars. Fgure 2 summarzes the change n sectoral value added 6

n current prces. 2 The fgures confrm the stylzed patterns of structural change n the prevous studes (and the survey by Herrendorf, Rogerson and Valentny (2013)). Increase n GDP per capta s assocated wth the decreases n employment and value added shares for agrculture and the ncreases n employment and value added shares for servces. The manufacturng employment and value added shares show hump-shaped changes. 3 It s clear that there has been major employment shfts toward the servce sector n 11 major Asan economes over the perod, 1990-2005. In Japan, the share of employment n the servce sector ncreased from 57.4% n 1990 to 67.1% n 2000, whle t ncreased more dramatcally n Korea from 46.2% to 64.4% over the same perod. The employment share of the servce sector n Chna has also ncreased steadly over the perod from 19.9% to 32.6%. The fgures for the employment share and value added share of servces suggest that there s an acceleraton n the rate of ncrease at around 9.5 n the log of GDP per worker, consstent wth the evdences n Buera and Kabosk (2012) and Echengreen and Gupta (2012). C. Convergence of sectoral labor productvty We assess f convergence n labor productvty at the aggregate economy and sectoral levels has occurred n the sample of 11 Asan economes. Labor productvty s computed by dvdng real value added by the number of all employed persons. For the purpose of comparablty, we use the real valued added at 2000 PPP prces. 2 The patterns are smlar for the value added shares wth real values. 3 Uy, Y and Zhang (2013) present an open economy model n whch the declnng porton of the hump s not well explaned. 7

Fgure 3 shows the change of the average labor productvty levels for aggregate economy over the perod from 1990 to 2005. The fgure shows a clear pattern of convergence n labor productvty levels for the aggregate economy. There s tendency of convergence at the sectoral level as well. The convergence s stronger n the manufacturng and servce sectors, compared to the agrculture sector. 4 But, there are some outler economes whch have not shown a clear convergence. For example, Japan s a clear outler n the agrculture sector. In the servce sector, Korea s an outler. By contrast, Inda has made rapd catch-up n the servce labor productvty, whle t has not been convergng n labor productvty n manufacturng. Despte sgnfcant convergence of sectoral labor productvty over tme, there reman sgnfcant dfferences n sectoral labor productvty. The productvty gap between sectors wthn an economy s also very dverse. Table 1 shows the rato of each sector s labor productvty to manufacturng labor productvty n 2005. In Hong Kong, Inda and Tawan, the labor productvty n the servce sector s hgher than that n manufacturng, whle t s far lower than the manufacturng labor productvty n Korea, the Phlppnes and Thaland (Fgure 4). Wthn the servce sector, for most economes, the levels of labor productvty across servce branches are also qute dverse. In general the labor productvty s relatvely hgh n the transport, storage and communcatons and the fnance, nsurance, real estate and busness servces branches (see Table 1). 4 We test convergence n labor productvty at the aggregate economy and sectoral levels usng panel data for 11 Asan economes. The estmaton results from panel estmaton wth country fxed effects support convergence across aggregate economy, manufacturng and servce sectors. No convergence occurs n agrcultural labor productvty of Asan economes. The results can be provded upon request. The convergence n servce sector labor productvty n a broad sample of countres s dscussed n detals n Secton V. 8

Table 2 shows labor productvty growth by sector, for the overall perod, 1990-2005. Labor productvty growth of the servce sector for the 1990-2005 perod was relatvely low, compared to that of manufacturng sector for most of the major Asan economes. III. Role of Expandng Servce sector on Productvty Growth We nvestgate the contrbuton that the growth of servce sector has made to overall productvty growth n Asan economes. We also assess the dfferences n productvty growth across servce branches. A. Patterns of structural change and economc growth Broadly speakng, the low labor productvty of the servce sector relatve to the manufacturng sector tends to hamper overall productvty growth. Fgure 5 shows the relatonshp between the share of servce sector employment and aggregate labor productvty growth over the three sub-perods, 1990-95, 1995-2000, and 2000-05. Aggregate evdence from 11 Asan economes and the US shows that there s negatve relatonshp between the overall labor productvty growth rate of the economy and the employment share of the servce sector n terms of employment. Ths affrms the relatvely low productvty growth n the servce sector. Nevertheless, tertalzaton s not necessarly an obstacle to overall labor productvty growth n an economy. In Inda and Malaysa, for example, labor productvty n the servce sector grew faster than that n manufacturng. Table 2 shows the labor productvty growth by four servce branches. The transport, storage and communcatons branch presents labor productvty growth rates smlar to or even 9

hgher than those of manufacturng sector n most of the 11 Asan economes (and the US). Here, Indonesa s one notable excepton n that the labor productvty growth n the transport, storage and communcatons branch was even lower than the average growth rate n the servce sector. Note that ths analyss does not take nto account the ndrect effects of these servces actvtes on the productvty n the other sectors. ther servce actvtes also show dynamc productvty growth n a number of countres. For example, the wholesale and retal trade and the hotels and restaurants servce branches n Inda and Sngapore experenced very hgh labor productvty growth. In Japan and Malaysa, the fnance, nsurance, real estate and busness servces had hgh labor productvty growth. In contrast, Indonesa, Korea, and Thaland, the fnance, nsurance, real estate and busness servces sector showed negatve labor productvty growth rates. Ths reflects the mpacts of Asan fnancal crss n 1997-98. B. Shft-share analyss In ths secton we adopt the technque of 'shft-share analyss' to examne the mpact of tertarzaton on aggregate productvty growth emprcally. The shft-share analyss shows how the aggregate labor productvty growth s lnked to the dfferental growth of labor productvty n ndvdual sectors and the reallocaton of labor between sectors. It uses an accountng technque to decompose aggregate labor productvty growth over a perod of tme nto a wthn effect (labor productvty growth wthn each ndustry), and a shft-effect or structural-change effect (labor productvty growth due to employment shfts toward more productve ndustres). 10

Recent papers such as Maudos et al. (2008), Maroto-Sánchez and Cuadrado-Roura (2009), Tmmer and de Vres (2009), McMllan and Rodrk (2011), and de Vres et al. (2012) have used 'shft-share analyss' to examne the mpact of structural change on economc growth. We adopt the same technque to analyze the role of tertarzaton for aggregate productvty growth n the Asan economes. Y = ( s, y, )+ ( y, s, ) The equaton shows that the overall growth of labor productvty n an economy s dvded nto two components. The frst s the contrbuton from productvty growth wthn ndvdual sectors weghted by the share of employment n each sector ( wthn effect ). The second s the contrbuton from labor reallocaton across dfferent sectors ( structural change effect ). The second term s the change of employment shares multpled by productvty levels at the end of the tme perod across sectors. 5 The contrbuton of each sector n the structural change effect can be ether postve or negatve, dependng on whether a sector s expandng or shrnkng. When the contrbutons from ndvdual sectors s aggregated, the structural change term becomes negatve, lowerng economy-wde productvty growth, f the labor dsplaced from hgh-productvty growth sector moves to low-productvty growth sectors. Table 3 presents the results of the shft-share analyss usng the data from 1990 to 2005, 5 The structural change term s agan dvded nto two components: the change of employment shares multpled by productvty levels at the begnnng end of the tme perod ( statc structural change ) and the nteracton between the change n employment shares and the productvty growth n ndvdual sectors ( dynamc structural change ). The results of shft-share analyss wth statc and dynamc structural change terms are avalable from the correspondng author upon request. 11

constructed from the data of nne sectors for the major Asan economes and the US. The results show that the wthn-effect domnates the effects of structural changes n most of the Asan economes. Nevertheless, the structural change has made sgnfcant contrbuton to the overall growth of labor productvty n several Asan economes ncludng Hong Kong, Indonesa, and Thaland. McMllan and Rodrk (2011) argue that Asa s outstandng not so much n productvty growth wthn ndvdual sectors, but n the broad pattern of structural change. But, clearly the strong labor productvty growth n ndvdual ndustres has been a salent feature of Asan economc growth, whle structural change has also contrbuted postvely to labor productvty growth n many Asan economes. Table 3 demonstrates the mportance of the servce sector n structural change and aggregate productvty growth. In the ndustralzed Asan economes ncludng Hong Kong, Japan, Korea, Sngapore and Tawan, the structural change effect of the manufacturng sector was negatve because they experenced shft of employment from manufacturng to servce sector. Nevertheless, because the servce sector contrbuted postvely to the overall structural change effect due to the ncrease n servce sector employment, the overall structural change effect becomes ether small or postve. In the late comers ncludng Chna, Inda, Indonesa, Malaysa and Thaland, both the manufacturng and servce sector contrbuted postvely to aggregate growth n terms of the structural change effect because these economes experence ncrease n the employment of both manufacturng and servce sectors durng the perod. For some economes, the servce sector domnates the manufacturng sector n terms of contrbuton to aggregate labor productvty growth due to the strong postve wthn and 12

structural-change effect of the servce sector. In Hong Kong, Inda, Malaysa and Tawan, the servce sector contrbuted more to the overall wthn-effect aggregate growth than the manufacturng sector. In these economes, the strong postve wthn- and structural-change effect of the servce sector contrbuted sgnfcantly to aggregate productvty growth. C. TFP growth n the servce sector The contrbuton of the servce sector to aggregate productvty growth s determned manly by two components: the change n employment share and productvty growth n the servce sector. The share of employment n the servce sector n Asa s expected to contnue to rse. Theoretcal models provde both demand- and supply-sde explanatons for structural change towards servce sector. Servces can expand due to dfferences n sectoral factor proporton, skllbased technology change, and non-homothetc preference. 6 As the theoretcal lterature and the shft-share analyss show, the contrbuton of expandng servce sector on the labor productvty growth of an overall economy depends on the labor productvty growth of servce sector relatve to those of other sectors. If labor moves to the servce sector from other sectors wth hgher levels and growth rates of labor productvty, the net effect on economy-wde labor productvty growth can be negatve. n the other hand, f the servce sector can have hgher labor productvty growth relatve to other sectors, the employment reallocaton to the servce sector can contrbute postvely to aggregate labor productvty growth. Ths s the result that we fnd n the follow secton. 6 See Herrendorf, Rogerson and Valentny (2013). 13

The crtcal factor for a sustaned contrbuton of the servce sector to overall economc growth s how to ncrease total factor productvty growth n servce sector. The reallocaton of productve factors such as labor and captal between sectors s eventually subject to dmnshng productvty unless total factor productvty ncreases. We look at avalable estmates of total factor productvty growth at the detaled sectoral levels. We have data for only two Asan countres ncludng Japan and Korea. The data for Japan are from the EUKLEMS database, whle Korean data s from the KIP (Korea Industral Productvty) database. Table 4 present the TFP growth estmates data for Japanese and Korean ndustres. For comparson, t also presents estmates for the US ndustres, sourced from the EUKLEMS database. The estmate show that a number of modern servces such as the transportaton, storage, and communcatons and the fnancal ntermedaton branches have experenced hgher total factor productvty growth rates n all three countres. ver the perod 1990-2006, the TFP growth rates n the transportaton, storage, and telecommuncaton servce branch were about 6.0% n Korea, exceedng 3.6% n the manufacturng sector. TFP has also ncreased rapdly n some tradtonal servces, such as wholesale and retal trade, partly due to extensve use of new nformaton technologes. ver the same perod, the TFP growth rates n the wholesale and retal trade branch reached about 2.0% n Japan and 2.9% n the U.S. IV. Determnants of Labor Productvty Growth n Servce Sector For Asa s more balanced and sustaned growth, how quckly the regonal economes can 14

close the gap n labor productvty n the servce sector wth advanced economes s a crtcal queston. Thus, we want to nvestgate the determnants of labor productvty growth n servces. The neoclasscal growth model predcts convergence of output per labor (labor productvty). The model predcts that an economy that s poorer and has hgher margnal productvty of captal grows faster, closng the gap n output per labor wth that of advanced economes quckly. But as an economy grows, t tends to grow slower as they are lkely to have already acheved faster rate of factor accumulaton and greater technologcal progress, leavng them wth lttle room for further growth. The convergence phenomenon can be condtonal on external envronmental and polcy varables facng ndvdual economes (Barro and Xala--Martn, 2004). Each country s convergng to ts own steady-state level of output per labor. The long-term level depends on polces, nsttutons, and other country specfc crcumstances. An economy wth favorable economc polces and structure tends to have a hgher steady-state level of labor productvty, and therefore faster growth at any gven ntal level of labor productvty. In the cross-country context, condtonal convergence mples that poorer countres would grow faster than rcher countres, when controllng for the varables nfluencng the steady-state level of output per labor. Emprcal studes provde evdence supportng ether uncondtonal or condtonal convergence of labor productvty dependng on the sample of countres. Most studes have tested the convergence hypothess usng data at the aggregate economy level, but very lmted numbers of studes have explored the convergence of labor productvty at sectoral levels. 7 7 A recent paper by Rodrk (2012) fnds uncondtonal convergence n labor productvty across manufacturng ndustres for recent decades n 118 economes. No paper has explctly focused on convergence n labor productvty across servce sectors. Echengreen and Gupta (2009) and Park and Shn (2013) use cross-country data 15

In ths secton, we set up a reduced-form equaton for servce sector labor productvty growth based on condtonal convergence framework. The model can be represented by (1) log( y / y ) / T log( y Z g yt T 0 0 2 0 ) 3 where the dependent varable s the growth rate of labor productvty n servce sector for the perod T for country, log(y 0 ) s a log value of the ntal level of labor productvty for country, and Z denotes an array of the varables that nfluence the country 's steady-state level of labor productvty n servce sector. The condtonal convergence mples a negatve coeffcent on the ntal labor productvty. A wde varety of external envronment and polcy varables wll affect growth rates by nfluencng the long-run potental level of labor productvty. The extended neoclasscal growth model emphaszes nvestment rate, populaton growth, and human captal as mportant factors that determne the steady-state level of output per labor. ur regresson ncludes three varables that represent these fundamental growth factors. The measure of human captal stock s the average years of schoolng for populaton aged 15 and over (Barro and Lee, 2013). Fertlty rate s ncluded to representl populaton growth. Prevous emprcal research also consders nsttutons and polcy factors as the mportant determnants of long-run output per labor. We nclude four varables to control for nsttuton and to explore the man factors that nfluence growth of servce sector labor productvty. Ther specfcatons are not bult on convergence framework. 16

polcy varables. 8 The frst varable s government consumpton, defned as the average of government consumpton n fnal goods to GDP. The second varable s the overall mantenance of the rule of law for the protecton of property and contractual rghts n the economy. The thrd polcy varable s nternatonal openness. The openness measure used n ths analyss s the rato of trade to GDP. Fnally, we nclude an ndex of democracy, whch as dscussed n Barro (1999), may have non-lnear effects n growth. We also add two addtonal varables, whch can nfluence the long-run potental level of labor productvty n the servce sector. They nclude the share of trade servces n total nternatonal trade and the share of urban populaton n total populaton. Echengreen and Gupta (2009) consder these two varables as well as overall trade openness and democracy as mportant factors that determne servce share growth as GDP per capta rses. 9 Another exogenous factor we consder n our regressons s a terms-of-trade shock, measured as the change n the rato of export to mport prces. ur regresson of specfcaton (1) apples to a panel set of cross-country data over fve 5- year perods from 1985 to 2009, correspondng to the perods 1985-90, 1990-95, 1995-2000, 2000-2005, and 2005-2009. The overall sample conssts of 270 observatons for 83 countres when the regresson ncludes only the ntal level of labor productvty and the common sample that nclude all explanatory varables has 208 observatons for 63 countres. The dependent varable s the growth rate of 5-year average labor productvty n the servce sector over the fve 8 ur emprcal framework ncludes a representatve set of the explanatory varables that have been wdely used n prevous work. See Barro and Sala--Martn (2004, Ch. 12) for detals. 9 Echengreen and Gupta (2009) also consder some geographcal varables (lattude, share of land area n tropcs, and proxmty to the major fnancal centers). It turns out they enter statstcally nsgnfcant n our regresson wthout country fxed effects. Because they are tme-nvarant, the coeffcents on these varables cannot be estmated n the regresson wth country fxed effects. 17

5-year ncrements between 1985 and 2010. ne concern n the emprcal specfcaton s that any effect from contemporaneous explanatory varables may reflect reverse causaton from labor productvty growth to the explanatory varables. For example, the relatonshp between contemporaneous nvestment and growth may reflect hgh growth causng hgh nvestment. Ths problem, however, can be solved by adoptng the nstrumental-varables (IV) estmaton technque. We estmate ths system of the fve equatons by panel IV estmaton technque. The nstrumental-varable technque controls for the possble smultanety problem when Z --the external envronment and polcy varables-- are endogenously determned. Instruments are mostly lagged values of the explanatory varables (see the notes to Table 5). For example, n consderng growth rate of labor productvty from 2000 to 2005, the average rato of nvestment n GDP over 2000-2004 enters n the regresson but nvestment rato for 2000 s used as ts nstrument. In addton, any measurement error n the lagged dependent varable the ntal level of labor productvty can have a drect nfluence on the growth rate, whch s the log dfference between the current and 5-year lagged labor productvty n each fve year nterval, and thus cause bas downward (or strengthen convergence) the estmated effect of lagged labor productvty on labor productvty growth. To reduce ths potental bas, we use 5-year lagged value of servce sector productvty as an ndependent varable. That s, the value of servce sector labor productvty n 1995 s used n the regresson for growth rate of labor productvty from 2000 to 2005. Ths use of lagged values of explanatory varables can control for the possble endogenety and measurement problems, but may not be entrely successful f there exsts seral correlaton n explanatory varables. 18

Some studes suggest estmatng panel growth regressons by the fxed-effects estmaton technque, consderng that unobserved, persstent country characterstcs nfluence labor productvty growth and are also correlated wth explanatory varables. The excluson of country fxed effects cause bases on the estmated effects of explanatory varables on labor productvty growth n servce sector. However, the fxed-effects technque elmnates nformaton from cross-secton varatons and does not allow estmaton of the effects of varables that have lttle wthn-country tme varaton (Barro, 2013). For the dscusson below, we wll use the results from the IV panel estmaton both wth and wthout country fxed-effects. Table 5 contans emprcal results for the cross-country panel regressons. Columns (1) and (2) of Table 5 nclude only tme effects and the 5-year lag of the log of lagged labor productvty. The regresson n column (1) s estmated by adoptng a panel GLS technque wthout country-fxed effects. 10 We fnd strong uncondtonal convergence n labor productvty across servce sectors. The estmated coeffcents on the ntal labor productvty are negatve and statstcally sgnfcantly dfferent from zero. The estmated coeffcent of uncondtonal convergence s about 0.6 percent per year. Column (2) of Table 5 shows the results of panel regresson wth country fxed effects. The estmated convergence coeffcents ncrease n sze and reman statstcally sgnfcant. The estmated convergence speed ncreases to 4.4% per year. Thus, cross-country data confrms that developng countres can catch up wth advanced countres n the labor productvty of servce ndustres over tme. 10 The estmaton weghts countres equally but allows for dfferent error varances n each perod and for correlaton of these errors over tme. 19

Columns 3 and 4 of Table 5 present the regresson results ncludng the set of explanatory varables. Column 3 presents results of regresson wthout country fxed effects. The estmated effects of average years of schoolng and the mantenance of rule of law are strong postve and statstcally sgnfcant. Ths result ndcates that countres wth better qualty of human resources and better qualty of nsttutons tend to have hgher growth rates of labor productvty n servce sector. n the other hand, the estmated coeffcents on many explanatory varables ncludng nvestment rate, government consumpton, and terms-of-trade varables enter wth expected sgns but not statstcally sgnfcant. The servce trade and urban populaton varables also enter statstcally nsgnfcantly. The estmated coeffcent on the overall trade openness varable s negatve but not statstcally sgnfcant. The regresson result confrms the non-lnear relatonshp between democracy and growth. The coeffcents on the ndcator of democracy and ts square terms are jontly statstcally sgnfcant (p=0.001). The fertlty rate varable appears to be negatvely assocated wth labor productvty growth rate n servces. Column 4 of Table 5 presents the result of regresson wth the ncluson of country fxed effects. The regresson result shows sgnfcant effects of human captal and the mantenance of rule of law varables on servce sector labor productvty growth. The pont estmate on human captal varable mples that an ncrease n the average years of schoolng by one year ncreases growth rate of servce sector labor productvty by about 1.3 percentage ponts a year, wth other varables constant. An ncrease n the rule-of-raw ndex by one standard devaton (0.25) has an effect of a smlar sze, by ncreasng labor productvty growth rate by about 1.3 percentage pont. 20

The regresson result confrms the non-lnear relatonshp between democracy and servce sector growth. Echengreen and Gupta (2009) argue that the second wave of servce sector growth s observed n countres wth hgh values of democracy. The coeffcents on the ndcator of democracy and ts square terms are postve and negatve respectvely and both of them are jontly statstcally sgnfcant (p=0.02). Democracy tends ntally to retard labor productvty growth of servce sector but later stmulates growth. The pont estmates mply that f the democracy ndex ncreases by one standard devaton of 0.24 (startng from the sample mean of 0.82) ncreases the growth rate of labor productvty by about 0.4 percentage pont, The regresson wth country fxed effect shows a sgnfcantly negatve effect of overall trade openness on servce sector labor productvty growth. Ths mples that ncrease n trade openness s more benefcal to more tradeable agrculture and manufacturng sectors, but hurts labor productvty growth n servce ndustres that are less tradable. The estmated coeffcent ndcates that f the share of trade n GDP ncreases by about 0.3, the growth rate of servce sector labor productvty decreases by about 1.1 percentage pont, wth other varables held constant. We fnd clear evdence that the external envronment and polcy varables can play a sgnfcant role n determnng productvty growth n the servce sector. Servce sector growth tends to be hgher when the ntal level of servce labor productvty s lower.. the qualty of human resources s hgher, the mantenance of the rule of law s mproved, the level of overall trade openness s reduced and the level of democracy ncreases. V. Smulatons for the Effects of Servce Sector Productvty Growth 21

Ths secton nvestgates the effects of servce sector productvty growth on structural change and economc growth n Asan economes. The emprcal results n the prevous sectons show that servce sector productvty growth can be an engne of economc growth n Asan economes. However, faster productvty growth n the servce sector can have sgnfcant spllovers to other sectors through nter-ndustry nput-output lnkages, factor movements, and consumpton and nvestment dynamcs. It can also have spllovers across the border through trade and fnancal lnkages. The complete analyss requres an emprcally based global ntertemporal mult-sector general equlbrum model (a large scale DSGE model). We adopt a model, called the G-Cubed model, to explore what happens f labor productvty rses n the servce sector n ndvdual Asan economes and then across all of Asan economes at the same tme. A. The Model The model used n ths paper s the G-Cubed model whch s an ntertemporal general equlbrum model of the world economy. The theoretcal structure s outlned n McKbbn and Wlcoxen (2013) and more detals can be found n the Appendx. A number of studes summarzed n McKbbn and Vnes (2000) show that the G-Cubed modellng approach has been useful n assessng a range of ssues across a number of countres snce the md-1980s.11. Some of the prncpal features of the model are as follows. The model s based on explct ntertemporal optmzaton by the agents (consumers and 11 These ssues nclude: German unfcaton n the early 1990s; fscal consoldaton n Europe n the md-1990s; the formaton of NAFTA; the Asan crss; and the productvty boom n the US. 22

frms) n each economy. In contrast to statc CGE models, tme and dynamcs are of fundamental mportance n the G-Cubed model. The G-Cubed model s known as a DSGE (Dynamc Stochastc General Equlbrum) model n the macroeconomcs lterature and as an Intertemporal General Equlbrum (IGE) model n the computable general equlbrum lterature. The man dfference to small scale DSGE models now popular at central banks s the large amount of sectoral dsaggregaton and consderable degree of country dsaggregaton. In order to track the macro tme seres, the behavour of agents s modfed to allow for short run devatons from optmal behavour ether due to myopa or to restrctons on the ablty of households and frms to borrow at the rsk free bond rate on government debt. Thus, aggregate consumpton s a weghted average of consumpton based on wealth (current asset valuaton and expected future after-tax labour ncome) and consumpton based on current dsposable ncome. Smlarly, aggregate nvestment s a weghted average of nvestment based on Tobn s Q (a market valuaton of the expected future change n the margnal product of captal relatve to the cost) and nvestment based on a backward lookng verson of Q. In the model software, t s possble to change the nformaton set of forward lookng agents after a scenaro begns to unfold. The model allows for short run nomnal wage rgdty (by dfferent degrees n dfferent countres) and, therefore, allows for sgnfcant perods of unemployment dependng on the labour market nsttutons n each country. Equlbrum between aggregate demand and aggregate output s mantaned by flexble prces, whch causes demand to adjust as well as short term supply. There s an explct treatment of the holdng of fnancal assets, ncludng money. Money s ntroduced nto the model through a restrcton that households requre money to purchase goods. 23

Global accountng denttes are mposed on the model so, for example, for every borrower there s a lender thereby avodng the fallacy of composton. Lkewse, the model gves a careful treatment of stock-flow relatons such as the accumulaton of current account defcts nto foregn clams on domestc output, whch has to be servced by future trade surpluses. n the fscal sde, whch s the focus of ths study, the accumulaton of fscal defcts nto government debt has to be servced from future revenues though t does not have to be completely pad off. The model dstngushes between the stckness of physcal captal wthn sectors and wthn countres and the flexblty of fnancal captal, whch mmedately flows to where expected returns are hghest. Ths mportant dstncton leads to a crtcal dfference between the quantty of physcal captal that s avalable at any tme to produce goods and servces, and the valuaton of that captal as a result of decsons about the allocaton of fnancal captal. As a result of ths structure, the G-Cubed model contans rch dynamc behavour, drven on the one hand by asset accumulaton and, on the other, by wage adjustment to a neoclasscal steady state. It embodes a wde range of assumptons about ndvdual behavour and emprcal regulartes n a general equlbrum framework. The nterdependences are solved out usng a computer algorthm that solves for the ratonal expectatons equlbrum of the global economy. In the verson of the model used here there are sx sectors (energy, mnng, agrculture, manufacturng durables, manufacturng non-durables and servces) as well as a generc captal producng sector n each country that draws largely on the durable manufacturng sector for nputs. There are 17 countres/regons as set out n table 6. For Asa, Japan, Korea, Chna, Inda, and Indonesa are ncluded as ndvdual economes and the other economes are ncluded as rest 24

of Asa. In ths model, each of the sx sectors s represented by a prce-takng frm whch chooses varable nputs and ts level of nvestment n order to maxmze ts stock market value. Each frm s producton technology s represented by a ter-structured constant elastcty of substtuton (CES) functon. At the top ter, output s a functon of captal, labor, energy and materals: (2) Q = A X 1 1 1 j j j=k,l,e,m where Q s the output of ndustry, X j s ndustry 's use of nput j, and A, j, and are parameters. A reflects the level of technology, s the elastcty of substtuton, and the j parameters reflect the weghts of dfferent nputs n producton; the superscrpt o ndcates that the parameters apply to the top, or output, ter. Wthout loss of generalty, we constran the δ's to sum to one. At the second ter, nputs of energy and materals, X E and X M, are themselves CES aggregates of goods and servces. Energy s a sngle good 1 and materals s an aggregate of goods 2 through 6 (mnng through servces). The functonal form used for these ters s dentcal to (14) except that the parameters of the energy ter are A E, E j, and E, and those of the materals ter are A M, M j, and M. The goods and servces purchased by frms are, n turn, aggregates of mported and domestc commodtes whch are taken to be mperfect substtutes. We assume that all agents n 25

the economy have dentcal preferences over foregn and domestc varetes of each commodty. We represent these preferences by defnng twelve composte commodtes that are produced from mported and domestc goods. Each of these commodtes, Y, s a CES functon of nputs domestc output, Q, and mported goods, M. 12 For example, the mnng products purchased by agents n the model are a composte of mported and domestc mnng. By constranng all agents n the model to have the same preferences over the orgn of goods we requre that, for example, the agrcultural and servce sectors have the dentcal preferences over domestc energy and energy mported from the Mddle East. 13 Ths accords wth the nput-output data we use and allows a very convenent nestng of producton, nvestment and consumpton decsons. In each sector the captal stock changes accordng to the rate of fxed captal formaton (J ) and the rate of geometrc deprecaton (δ ): (3) K = J K We assume that the nvestment process s subject to rsng margnal costs of nstallaton. To formalze ths we adopt Uzawa's approach by assumng that n order to nstall J unts of captal a frm must buy a larger quantty, I, that depends on ts rate of nvestment (J/K): (4) J I = 1+ J 2 K where s a non-negatve parameter. The dfference between J and I may be nterpreted varous ways; we wll vew t as nstallaton servces provded by the captal-goods vendor The goal of each frm s to choose ts nvestment and nputs of labor, materals and 12 The elastcty of substtuton n ths functon s the Armngton elastcty. 13 Ths does not requre that both sectors purchase the same amount of energy, or even that they purchase energy at all; only that they both feel the same way about the orgns of energy they buy. 26

energy to maxmze ntertemporal rsk-adjusted net-of-tax profts. For analytcal tractablty, we assume that ths problem s determnstc (equvalently, the frm could be assumed to beleve ts estmates of future varables wth subjectve certanty). Thus, the frm wll maxmze: 14 I ( R( s ) e n) ( st) (5) ( (1 4) P I ) e t ds where e s a sector and regon-specfc equty rsk premum all varables are mplctly subscrpted by tme. The frm s profts,, are gven by: * E M (6) = ( 1 2 )( P Q W L P X E P X M) where τ 2 s the corporate ncome tax, τ 4 s an nvestment tax credt, and P * s the producer prce of the frm s output. R(s) s the long-term nterest rate between perods t and s: 1 (7) R( s) = r( v) dv s t Because all real varables are normalzed by the economy's endowment of effectve labor unts, profts are dscounted adjustng for the rate of growth of populaton plus productvty growth, n. Solvng the top ter optmzaton problem gves the followng equatons characterzng the frm s behavor: 1 (8) X A Q j {L,E, M} j j s t * P P j J (9) ( 1 )(1 4) P K = I 14 The rate of growth of the economy's endowment of effectve labor unts, n, appears n the dscount factor because the quantty and value varables n the model have been scaled by the number of effectve labor unts. These varables must be multpled by exp(nt) to convert them back to ther orgnal form. 27

(10) d * dq I J = ( r e + ) (1 2) P (1 4) P ds dk 2 K 2 where λ s the shadow value of an addtonal unt of nvestment n ndustry. Equaton (20) gves the frm s factor demands for labor, energy and materals, and equatons (21) and (22) descrbe the optmal evoluton of the captal stock. By ntegratng (22) along the optmum path of captal accumulaton, t s straghtforward to show that λ s the ncrement to the value of the frm from a unt ncrease n ts nvestment at tme t. It s related to q, the after-tax margnal verson of Tobn's Q (Abel, 1979), as follows: (11) = q 1 P 4 I Thus we can rewrte (21) as: J K 1 (12) = q 1 Insertng ths nto (16) gves total purchases of new captal goods: 1 I q 2 1 K 2 (13) To estmate G-Cubed s parameters we began by constructng a consstent tme seres of nput-output tables for the Unted States. The procedure s descrbed n detal n McKbbn and Wlcoxen (1999a). The dataset we constructed allowed us to estmate the model s parameters for the Unted States. To estmate the producton sde of the model, we began wth the energy and materals ters because they have constant returns to scale and all nputs are varable. We estmate the elastcty of substtuton by sector and by level of nestng on the US data and apply ths to all countres. We calbrate the delta share parameters usng country specfc nput output data from 28

GTAP. Tables 8 and 9 presents the values of the elastctes of substtuton, E, M, and the E M,, and parameters that appear on the producton sde of the model (as well as the j j j substtuton between domestc and foregn goods and between countres of orgn of foregn goods). The sgma s are common across countres n the same sectors but the deltas are calculated from the country specfc nput/output tables for each country. The factor shares wll be mportant n the results below. B. Smulaton results We consder three man scenaros n ths secton. ne s where all Asan economes (Chna, Inda, Indonesa, Japan, Korea and other Asa) experence a rse n labor productvty growth of 1 percent pont per year startng n 2014 and persstng untl 2053 after whch the shock n the growth rate of labor productvty growth rate decays by 4% per year untl returnng to baselne n 2100 15. We then compare the case where all Asan economes successfully rase productvty growth n servces to the case where each country n Asa experences productvty growth of the same magntude but each ndvdually. For the non-asan results we only explore the spllovers from the aggregate Asan growth experence. As shown n Secton IV, servce sector productvty growth can be ncreased by mprovng qualty of human resources, mantenance rule of law and level of democracy, and lowerng overall trade openness level. Here, we consder the productvty shock only n servce sector. As a comparson we also present 15 The reason for the partcular tme path s to ensure the long run steady state of the model s preserved but to enable a long perod of more rapd growth n servce sector productvty to occur untl around 2050. 29

results at the sectoral level for the same labor productvty shock across Asan economes, but appled to manufacturng sectors (both durable and non-durable goods) rather than servces. The results are presented n Tables 10 through 13. Each table shows the devaton from the baselne of a range of varables at dfferent ponts nto the future. GDP, consumpton, and nvestment are expressed percent devaton from baselne. The trade balance s percent of baselne GDP devaton from baselne. Table 12 contans results for the percentage devaton n sectoral output by country over tme. Table 13 shows the results for the sectoral percentage devaton from baselne n employment by sector over tme. These results are also presented n a seres of graphs n Fgure 6 through 9. At the macro level n Table 10 and 12 (and Fgures 6 through 8), the results are clear. nce the surprse rse n labor productvty of the servce sector occurs, there s a reallocaton of nputs wthn each economy. Hgher productvty n one sector eventually rases GDP across the economy although the presents of adjustment costs mples that ntally GDP can fall as nputs are reallocated. wn productvty growth overwhelmngly benefts the country experencng the productvty surge however over tme all countres benefts from servce sector productvty growth n another economy through the ncrease n natonal wealth that s spread globally. The extent of the gan depends on the lnkage between economes outsde of Asa and economes experencng the productvty surge, For example Australa gans far more than the Euro area because of strong trade lnkage, especally for ntermedate nputs n Asa. Germany gans more than the rest of the Euro zone because of the exports of durable goods for captal nvestment purposes from Germany to Asa (partcularly Chna). In an ndvdual economy, hgher labor productvty rases the return to captal n the servce sector. Ths nduces an ncrease n 30

nvestment n that sector. It also causes an ncrease n demand and therefore output n all sectors that feed nto that sector (see Table 12 and Fgure 9). In the model, nvestment goods are produced by a captal producng sector that draws largely on the output of the durable manufacturng sector so the demand for durable manufacturng goods rses as part of the nvestment boom. Ths s true for the domestcally produced goods as well as for mports. In all economes that experence the productvty ncrease nvestment rses. Ths s ntally funded by a rse n aggregate savngs (or a fall n consumpton) as backward lookng agents do not fully ncorporate hgher wealth nto ther consumpton decsons n the short term. The hgher nvestment s also partly funded by a captal nflow wth fnancal captal attracted to the hgher return on captal n growng economes. Ths captal nflow apprecates the exchange rate n each Asan economy and worsens the trade balance (whch s the counterpart of the captal nflow). The balance between fnancng domestcally and through foregn captal vares across Asan economes dependng on the scale of captal nflow requred to buld the new captal stock. It ranges from very large n Japan to less n Korea and Chna (where captal controls lessen the avalable nflow). We see that GDP rses n all Asan economes after the frst year and n the long run (Table 10 and Fgure 6)). In non-asan economes such as the Unted States and Australa the results vary over tme. The ntal relocaton of captal from the US lowers US GDP below baselne for 20 years but eventually the hgher demand from Asa through hgh wealth rases the demand for US goods. Australa s dfferent because t s more hghly ntegrated nto Asan producton partcularly through the supply of mnng and energy goods whch s very dfferent to the US. Australa n more ntegrated nto the Asan producton flows and the trade benefts of 31

hgh growth n Asan domnate the captal outflow from Australa. Ths llustrates that the spllover between countres outsde Asa and Asa depend very much on trade patterns and the nature of the goods traded. In partcular Australa experences a surge n mnng and energy exports that feed nto the faster growng Asan captal stocks. Thus Australa s GDP rse contnuously from the productvty surge n Asa whereas US GDP s below baselne for more than 20 years because the captal relocaton effect outweghs the postve trade effects. Returnng to the sectoral level (Tables 12-13 and Fgure 9), the results dffer substantally across the Asan countres. Because the shock s a rse n labor augmentng techncal change n the servce sector, fewer workers are needs to produce the same level of output. Labor demand tends to fall n all servce sectors experencng the productvty surge, thus freeng up labor to flow nto other parts of the economy. Ths tends to rase the margnal product of captal n these sectors. In partcular the demand for captal goods that are needed to buld the captal stock for the expandng servce sector rases the demand for durable manufacturng goods well n excess of other sectors. Ths result s found n each Asan economy although to a dfferent extent dependng on the captal ntensty of the servce sector relatve to other sectors. The fact that the durable goods manufacturng sector s very dfferent to the non-durable goods manufacturng sector (whch responds more lke agrculture) s an mportant result and suggests that an aggregate manufacturng sector mght mask an mportant adjustment process especally when the captal accumulaton process s endogenous as t s n G-Cubed. Lookng more closely at ndvdual country results across the major sectors we see that n Table 12 for Chna there s ntally a rse n the output of the durable manufacturng sector as new captal goods are bult for the expandng servces sectors. The expanson of captal goods s 32

front loaded compared to the persstence rse n labor productvty n the servce sector. The employment effects n durable manufacturng are even larger than for other sectors as workers move out of servces nto the expandng durable manufacturng sector. Japan (Table 12 and Fgure 9) shows an even larger flow of workers out of the servce sector nto the other sectors and partcularly nto the durable goods sector. Snce durable goods s a sector wth a large comparatve advantage n Japan, beng a major exporter of durable goods throughout Asa and globally. Japan s also much more labor ntensve n servces than the other Asa economes (see Table 9 - parameter delta_k), hence nput costs fall by more n Japanese servces and more labor flows nto other sectors whch are more captal ntensve than n other Asan economes. Thus the demand for durable goods for nvestment purposes ncreases sgnfcantly. Korea also experences a large rse n durables output for smlar reasons to Japan but other countres wth less domestc captal producton such as Chna, Inda and Indonesa have a much smaller expanson of durable goods producton than Japan or Korea wth some of the expanson spllng over nto non-durable goods n Chna. In Tables 12 and 13 we also present results for the Asa wde rse n productvty n the two manufacturng sectors n the model durable and non-durable goods. Labor productvty growth n durable goods reduces the costs of purchasng captal goods throughout Asa because ths sector largely produces the captal goods each sector purchases for nvestment. As the cost of captal goods fall, nvestment rses and GDP rse. Captal ntensve sectors (especally mnng) gan most from ths reducton n captal goods prces. In addton there s the relocaton effect of labor from the manufacturng sectors nto the rest of the economy that parallels the adjustment for the shock to servce sector productvty. In the longer run, manufacturng productvty growth 33

ncreases employment n the servce ndustry but reduces employment growth n Agrculture n all countres. VI. Concludng Remarks Ths paper has emprcally explored the hstorcal experence of sectoral growth n major Asan economes wth a focus on the performance of the servce sector relatve to the manufacturng sector and the mplcaton for overall economc growth. It has found the evdence of sgnfcant catch-up n a number of sectors ncludng the servce sector but a wde varety of experences n each economy. It has also found a substantal gap stll remans n labor productvty between the servce sectors n Asa and the Unted States. Although lower labor productvty n the servce sector relatve to the manufacturng sector has n general hampered overall economc growth n Asa, the evdence shows that, n several Asan economes, the servce sector has made a sgnfcantly postve contrbuton to aggregate labor productvty growth, both through own productvty growth and structural change effects, exceedng the net contrbuton of manufacturng sector. In addton, some modern servces ndustres such as the transportaton, storage, and communcatons and the fnancal ntermedaton and busness servces have experenced hgher productvty growth. We have also found that servce sector growth tends to be hgher when the qualty of human resources s hgher, the mantenance of the rule of law mproves, the level of democracy ncreases, and the level of trade openness s lower. Ths evdence suggests that the external envronment and polcy varables can play a sgnfcant role n mprovng servce sector productvty growth. Especally, mprovng qualty of human resources and nsttutons would be 34

mportant for the productvty growth of both overall economy and servce sector. In addton, reducng dependency on trade contrbutes to promotng servce sector productvty growth. verall, the emprcal evdence from the hstorcal data suggests there s an enormous potental for servce sector productvty growth n Asa f polces could be adopted to enhance the catch-up n the servces to be more lke the experence wth the manufacturng sector. ver the last three decades, ncreased economc and trade ntegraton has bolstered the regon s growth. For example, segmented producton for global supply chans has stmulated trade n ntermedate goods and promoted foregn drect nvestment. However, facng the prospect of a global growth slowdown and sgnfcant downsde rsks n the post-crss perod, the Asan economes must move away from an over-relance on export-orented development strateges. For sustanable growth, t s necessary for Asa to rebalance two growth engnes own domestc demand and external demand. Reducng dependence on external demand for example, by promotng prvate-sector nvestment and encouragng household expendture s crucal. Supply-sde polces that promote small and medum-sze enterprses and servce ndustres accommodatng domestc demand are also crtcal to ensurng more balanced and sustanable growth n Asan economes. ne crtcal queston s whether enhancng productvty n the servce sector can play a role of a second growth engne leadng Asa s strong and sustanable growth n the future. We have addressed ths queston by explorng smulatons of a mult-sectoral general equlbrum model. We fnd that faster productvty growth n the servce sector n Asa can sgnfcantly beneft all sectors, contrbutng to more balanced and sustanable growth of Asan economes. The smulatons show dverse dynamc adjustment across economes. We fnd that, n contrast to 35

the smpler models of economc growth, a key part of the structural adjustment story n the freeng up of labor from the servce sector and a rse n the demand for durable manufacturng goods requred buldng the physcal captal stock that s nduced by the productvty surge. Thus both the servce and durable good sectors experence rapd growth n output but employment shfts manly toward the durable goods sector durng the adjustment process. Ths s partcularly mportant n countres such as Korea and Japan who have a hgh productvty n the durable manufacturng sector due to ther comparatve advantage and openness to nternatonal trade n that sector. The results of ths paper suggest that the smple aggregate models and the models of lmted sectoral nteractons may mss an mportant dynamc story of productvty growth n the servce sector and captal accumulaton n an ntegrated global economy. Further work, both smulaton analyss and emprcal work would further mprove our understandng of the nteracton of sectoral productvty growth, captal accumulaton and overall economc growth n the Asan economes. 36

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Table 1, Rato of Each Sector s Labor Productvty to Manufacturng Labor Productvty n 2005 Agrculture, Huntng, Forestry and Fshng CHN HKG IDN IND JPN KR MYS PHL SGP THA TWN USA 0.12 0.44 0.18 0.20 0.19 0.28 0.44 0.20 0.22 0.11 0.26 0.57 Manufacturng 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Servces 0.54 2.08 0.49 1.41 0.64 0.29 0.73 0.34 0.74 0.43 1.10 0.57 Wholesale and Retal Trade, and Restaurants Transport, Storage and Communcatons Fnance, Real Estate and Busness Servces Communty and Government Servces 0.50 1.79 0.41 1.24 0.54 0.22 0.58 0.31 0.69 0.31 0.86 0.43 0.73 2.05 0.44 2.17 0.83 0.87 1.21 0.43 0.84 1.36 1.51 0.88 4.84 4.02 3.43 2.59 0.46 0.13 1.95 0.66 1.21 0.49 1.50 1.05 0.33 1.34 0.36 1.03 0.71 0.28 0.43 0.27 0.40 0.40 1.13 0.38 thers 0.79 1.39 0.92 1.52 0.62 0.68 0.99 0.60 0.46 0.53 0.55 0.54 Mnng and Quarryng Electrcty, Gas, and Water 2.56 1.90 3.66 1.87 0.76 1.61 11.2 1.80 0.38 3.23 3.64 0.91 2.77 12.01 1.13 3.74 2.38 4.70 3.69 3.22 2.36 4.72 6.01 3.42 Constructon 0.36 0.78 0.42 1.17 0.46 0.51 0.23 0.32 0.34 0.18 0.29 0.34 All Economy 0.44 1.95 0.48 0.60 0.67 0.46 0.78 0.36 0.77 0.40 0.98 0.61 40

Table 2. Labor Productvty Growth by Sector, 1990-2005. Agrculture, Huntng, Forestry and Fshng CHN HKG IDN IND JPN KR MYS PHL SGP THA TWN USA 4.6-3.8 2.6 1.3 0.1 5.5 3.1 1.0 0.3 3.9 3.1 3.4 Manufacturng 10.7 5.9 3.3 3.8 3.7 8.1 4.1 0.9 5.5 2.6 4.4 4.5 Servces 5.6 2.0 1.8 5.5 1.0 1.1 4.2 0.8 3.1-0.7 3.2 1.5 Wholesale and Retal Trade, and Restaurants Transport, Storage and Communcatons Fnance, Real Estate and Busness Servces Communty and Government Servces 4.0 2.3 1.0 4.6 1.1 1.8 4.0 0.4 5.1-2.5 3.9 3.2 6.8 3.5 0.7 6.2 1.3 6.0 4.1 0.9 3.1 3.9 6.4 3.2 5.8 0.0 1.3-2.9 2.5-5.2 5.0 0.7 1.1-2.9 0.3 1.3 7.3 1.4 2.0 6.4 0.2-0.8 2.7 0.7 2.5 0.6 2.6-0.2 thers 9.6 0.7-1.3 1.3-1.0 2.3 0.7-0.2 2.0-0.1 1.3-0.2 Mnng and Quarryng Electrcty, Gas, and Water 16.7 0.2-0.6 1.5-0.1 9.1 2.7 4.6-7.9 6.4 3.5 0.5 13.8 7.9 6.5 2.8 2.0 8.3 5.3 2.9 5.0 5.9 5.3 3.7 Constructon 5.5-2.0-0.3 1.2-2.1 1.0-0.4-2.0 1.7-4.8 0.2-0.7 All Economy 8.4 3.2 2.7 4.1 1.4 3.8 4.0 0.9 3.6 3.0 3.9 1.8 41

Table 3. Decomposton of Labor Productvty Growth over 1990-2005 Country Sector Total Wthn Structural change Chna All Economy 8.42 7.46 0.95 Manufacturng 3.04 3.21-0.17 Servces 3.46 1.8 1.66 Hong Kong All Economy 3.22 1.99 1.23 Manufacturng -0.2 0.7-0.91 Servces 3.43 1.14 2.28 Indonesa All Economy 2.74 1.7 1.04 Manufacturng 1.1 0.76 0.33 Servces 1.23 0.46 0.77 Inda All Economy 4.14 3.17 0.97 Manufacturng 0.8 0.63 0.17 Servces 2.68 2.05 0.62 Japan All Economy 1.4 1.41-0.01 Manufacturng 0.38 1.08-0.71 Servces 1.23 0.46 0.77 Korea All Economy 3.82 5.19-1.37 Manufacturng 2.07 3.69-1.62 Servces 1.41 0.51 0.9 Malaysa All Economy 4 3.52 0.48 Manufacturng 1.43 1.05 0.39 Servces 2.31 1.6 0.72 The Phlppnes All Economy 0.94 0.81 0.14 Manufacturng 0.15 0.24-0.09 Servces 0.79 0.23 0.56 Sngapore All Economy 3.64 3.72-0.08 Manufacturng 1 1.8-0.81 Servces 2.53 1.75 0.78 Thaland All Economy 3.01 1.36 1.64 Manufacturng 1.74 0.72 1.01 Servces 0.97-0.11 1.07 Tawan All Economy 3.91 3.38 0.53 Manufacturng 0.99 1.4-0.42 Servces 2.92 1.7 1.22 USA All Economy 1.78 2.07-0.29 Manufacturng 0.34 0.93-0.59 Servces 1.42 1.01 0.42 42

Table 4. Comparson of TFP Growth by Sector between Japan, Korea, and the USA, 1990-2006. Annual average growth rate (%) INDUSTRY JAPAN KREA USA Total Economy 0.05 0.58 0.54 Agrculture, Huntng, Forestry and Fshng -0.64 1.10 2.21 Total Manufacturng 0.63 3.61 2.87 Servces 0.00-0.87 0.11 Wholesale and Retal Trade 2.02-1.89 2.89 Hotels and Restaurants -0.29-4.97 0.13 Transport, Storage and Communcaton 0.64 5.98 1.51 Fnancal Intermedaton 0.95 2.43 0.37 Real Estate, Rentng and Busness Actvtes -0.63-2.28-0.66 Publc Admn and Defense; Compulsory Socal securty -0.24-1.82-1 Educaton -0.36-1.23-1.41 Health and Socal Work 0.06-3.3-1.32 ther Communty, Socal and Personal Servces -2.29-2.31 0.62 thers -1.50-0.27-1.41 Mnng and Quarryng -0.22-2.77-0.53 Electrcty, Gas and Water Supply 0.08 1.92 0.69 Constructon -2.12-2.76-2.34 Source: Author s calculaton usng EU KLEMS Database and KIP Database 43

Table 5. Determnants of Labor Productvty Growth n the Servce Sector Dependent Varable: Average Fve-Year Growth Rate of Servce Sector Labor Productvty Log (Lagged Servce Labor Productvty) Log (Fertlty Rate) ⑴ ⑵ ⑶ ⑷ Panel GLS -0.0058 *** (0.0018) Panel GLS Fxed Effects -0.0440 *** (0.0133) Panel IV -0.0118 *** (0.0029) -0.0117 * (0.0071) Panel IV Fxed Effects -0.0495 *** (0.0172) 0.0426 * (0.0254) Investment Rato Average School Years Government Consumpton Rato Rule of Law Index Share of Trade n GDP Terms-of-Trade Change Share of Servces Trade n Total Trade Urban Populaton (Rato to Total Populaton) Democracy 0.0440 (0.0350) 0.0024 ** (0.0011) 0.0117 (0.0439) 0.0260 ** (0.0120) -0.0024 (0.0038) 0.0218 (0.0618) 0.0099 (0.0205) 0.0139 (0.0119) -0.0853 ** (0.0429) 0.0396 (0.0946) 0.0126 ** (0.0062) -0.0810 (0.2727) 0.0595 *** (0.0234) -0.0389 ** (0.0168) 0.0226 (0.0840) 0.0032 (0.0567) 0.1347 (0.0873) -0.1296 * (0.0736) Democracy Squared 0.0416 (0.0348) 0.0780 (0.0681) bservatons 270 270 208 208 Number of Countres 83 83 63 63 R-squared 0.07 0.07 0.20 0.04 44

Notes to Table 5 The panel specfcaton uses pooled data for 1985-90, 1990-95, 1995-2000, 2000-2005 and 2005-2009 for 83 economes n columns 1 and 2 and 63 economes n columns 3 and 4. Perod dummes are ncluded. Standard errors are n parenthess. Astersks denote the followng sgnfcance levels: *** p<0.01, ** p<0.05, * p<0.1. The dependent varable s the growth rate of 5-year average labor productvty n the servce sector over the fve 5-year ncrements between 1985 and 2009. Intal servce labor productvty varable uses 5-year lagged values (1980, 1985,, and 2000). The share of trade servces n total trade and the share of urban populaton n total populaton are the values at the ntal year of each 5-year perod. ther regressors are averages over perods, wth lagged values used as nstruments. The data on servce sector labor productvty, trade servces share, urban populaton share, fertlty, and terms-of-trade are from the World Bank, World Development Indcators. The nvestment and government consumpton ratos to GDP are from Penn World Tables, verson 7.0. Average years of schoolng data are from Barro and Lee (2013). The mantenance of law-andorder ndcator (converted from seven categores to a 0-1 scale, wth 1 representng hghest level) s from Poltcal Rsk Servces, Internatonal Country Rsk Gude. The democracy ndcator (converted from seven categores to a 0-1 scale, wth 1 representng hghest rghts) s the poltcal-rghts varable from Freedom House. 45

Table 6: Countres/regons n the G-cubed Model Unted States Japan Unted Kngdom Germany Rest of Euro Zone Canada Australa Korea RECD Chna Inda Indonesa ther Asa Latn Amerca ther emergng countres Eastern Europe & former S U l-exportng & Mddle East Table 7: Sectors of Producton n Each Country Energy Mnng Agrculture Durable Manufacturng Non-Durable manufacturng Servces Table 8: Elastctes of Substtuton (Sgma) n Producton Foregn and Inputs (, E, M) domestc goods sgma_o sgma_e sgma_m sgma_df sgma_ff 1. Energy 0.746 0.192 0.725 3.000 2.000 2. Mnng 0.500 1.147 2.765 0.900 2.000 3. Agrculture 1.235 0.671 1.516 0.900 2.000 4. Durable man 0.410 0.805 0.200 0.900 2.000 5. NonDurable man 1.004 1.100 0.057 0.900 2.000 6. Servces 0.333 0.288 2.236 0.900 2.000 Note: Sgma parameter ( ) represents s the elastcty of substtuton between nputs n sectoral fnal goods (o), energy (E) and materals (M),, Sgma_df s the elastcty of substtuton between domestc and foregn goods Sgma_ff s the elastcty of substtuton between foregn goods from dfferent countres. 46

Table 9: Delta Parameters n Producton functons USA 1. Energy 2. Mnng 3. Agr 4. Durable man 5. NDurable man 6. Servces delta_k 0.259 0.228 0.187 0.075 0.132 0.117 delta_l 0.114 0.314 0.246 0.274 0.242 0.486 delta_e 0.457 0.078 0.022 0.018 0.054 0.029 delta_m 0.171 0.380 0.545 0.634 0.572 0.368 delta_m_2 0.005 0.232 0.001 0.008 0.005 0.000 delta_m_3 0.022 0.007 0.321 0.009 0.119 0.010 delta_m_4 0.173 0.295 0.078 0.580 0.050 0.091 delta_m_5 0.059 0.108 0.226 0.084 0.497 0.105 delta_m_6 0.742 0.357 0.374 0.319 0.329 0.794 Japan 1. Energy 2. Mnng 3. Agr 4. Durable man 5. NDurable man 6. Servces delta_k 0.263 0.217 0.263 0.105 0.144 0.206 delta_l 0.087 0.143 0.246 0.195 0.171 0.368 delta_e 0.440 0.086 0.038 0.027 0.056 0.023 delta_m 0.211 0.555 0.453 0.673 0.628 0.403 delta_m_2 0.003 0.005 0.000 0.014 0.001 0.000 delta_m_3 0.006 0.003 0.307 0.007 0.116 0.010 delta_m_4 0.123 0.133 0.028 0.609 0.037 0.066 delta_m_5 0.036 0.056 0.306 0.072 0.498 0.127 delta_m_6 0.831 0.803 0.359 0.299 0.348 0.797 Korea 1. Energy 2. Mnng 3. Agr 4. Durable man 5. NDurable man 6. Servces delta_k 0.168 0.530 0.346 0.144 0.113 0.241 delta_l 0.042 0.172 0.221 0.110 0.105 0.288 delta_e 0.721 0.048 0.069 0.023 0.142 0.059 delta_m 0.069 0.250 0.364 0.724 0.640 0.412 delta_m_2 0.001 0.001 0.000 0.018 0.004 0.000 delta_m_3 0.008 0.017 0.319 0.005 0.144 0.016 delta_m_4 0.240 0.151 0.029 0.714 0.037 0.094 delta_m_5 0.189 0.071 0.383 0.085 0.608 0.154 delta_m_6 0.561 0.760 0.268 0.177 0.207 0.736 47

Table 9: Delta Parameters n Producton Functon (contnued) Chna 1. Energy 2. Mnng 3. Agr 4. Durable man 5. NDurable man 6. Servces delta_k 0.208 0.209 0.211 0.106 0.107 0.244 delta_l 0.080 0.212 0.302 0.104 0.100 0.229 delta_e 0.531 0.068 0.029 0.045 0.056 0.045 delta_m 0.182 0.511 0.458 0.745 0.736 0.482 delta_m_2 0.002 0.152 0.001 0.039 0.009 0.001 delta_m_3 0.014 0.011 0.423 0.014 0.171 0.055 delta_m_4 0.420 0.279 0.062 0.669 0.056 0.263 delta_m_5 0.093 0.209 0.297 0.113 0.591 0.214 delta_m_6 0.470 0.349 0.217 0.164 0.172 0.467 Inda 1. Energy 2. Mnng 3. Agr 4. Durable man 5. NDurable man 6. Servces delta_k 0.214 0.456 0.430 0.156 0.153 0.327 delta_l 0.089 0.225 0.273 0.090 0.168 0.282 delta_e 0.518 0.205 0.053 0.089 0.117 0.084 delta_m 0.179 0.114 0.244 0.665 0.563 0.307 delta_m_2 0.009 0.007 0.002 0.038 0.008 0.007 delta_m_3 0.010 0.016 0.556 0.016 0.262 0.076 delta_m_4 0.199 0.191 0.023 0.604 0.030 0.171 delta_m_5 0.078 0.321 0.192 0.081 0.411 0.156 delta_m_6 0.704 0.466 0.228 0.261 0.290 0.591 Indonesa 1. Energy 2. Mnng 3. Agr 4. Durable man 5. NDurable man 6. Servces delta_k 0.497 0.478 0.416 0.166 0.155 0.237 delta_l 0.046 0.240 0.293 0.115 0.156 0.294 delta_e 0.387 0.062 0.017 0.051 0.037 0.078 delta_m 0.071 0.220 0.274 0.667 0.652 0.390 delta_m_2 0.009 0.174 0.517 0.001 0.099 0.001 delta_m_3 0.010 0.002 0.008 0.446 0.007 0.265 delta_m_4 0.199 0.208 0.108 0.020 0.471 0.014 delta_m_5 0.078 0.020 0.061 0.294 0.169 0.515 delta_m_6 0.704 0.596 0.306 0.239 0.254 0.205 Notes: Sectoral output s a functon of captal, labor, energy and materals as follows: Q = A X 1 1 1 j j j=k,l,e,m where Q s the output of ndustry, X j s ndustry 's use of nput j, and A,, and are parameters. The delata parameters ( ) parameters reflect the weghts of dfferent nputs n producton; j j 48

Table 10: Effects Rse n Labor Productvty n the Servce Sector (%) Real GDP Investment 2014 2020 2040 2014 2020 2040 Japan Asa wde 1.24 5.32 12.78 18.87 40.45 54.06 wn 1.05 4.98 12.27 16.57 38.56 52.24 Korea Asa wde 0.30 3.23 7.82 5.00 15.16 17.01 wn 0.11 2.67 6.87 3.57 13.28 15.35 Chna Asa wde -0.02 0.91 2.24 0.97 3.01 3.90 wn 0.00 0.83 1.96 0.87 2.75 3.48 Inda Asa wde -0.19 0.89 2.37 0.20 3.44 3.95 wn -0.07 1.09 2.42 0.73 3.81 4.02 Indonesa Asa wde -0.07 1.30 3.77 0.92 6.02 7.15 wn -0.10 1.18 3.50 0.72 5.54 6.81 AS Asa wde -0.35 1.22 5.17-0.35 8.04 12.16 wn -0.29 1.19 4.69 0.18 7.53 11.05 USA Asa wde -0.21-0.12 0.04-1.95-0.80-0.09 Australa Asa wde -0.01 0.08 0.22 0.19 0.49 0.55 REUR Asa wde -0.15-0.19 0.01-1.32-1.05-0.28 Germany Asa wde -0.03-0.04 0.15-0.42-0.70 0.17 Table 11: Effects Rse n Labor Productvty n the Servce Sector (%) Consumpton Trade Balance 2014 2020 2040 2014 2020 2040 Japan Asa wde 0.53 1.52 5.14-1.61-1.81-1.32 wn 0.36 1.14 4.52-1.36-1.68-1.25 Korea Asa wde -0.41-1.13 3.45-0.42-0.62-0.29 wn -0.69-1.42 2.63-0.10-0.55-0.38 Chna Asa wde -0.44-0.85 1.71-0.18-0.16-0.02 wn -0.47-0.77 1.37-0.09-0.16-0.07 Inda Asa wde -0.77-1.05 1.12 0.20 0.07 0.00 wn -0.54-0.60 1.26 0.08-0.07-0.09 Indonesa Asa wde -0.31-0.70 2.09-0.01 0.02 0.20 wn -0.40-0.61 1.90 0.08-0.06 0.06 AS Asa wde -0.98-2.29 0.83 0.43 0.24 0.29 wn -1.06-2.17 0.38 0.50 0.21 0.24 USA Asa wde -0.22-0.31-0.09 0.19 0.20 0.15 Australa Asa wde 0.03-0.11 0.02-0.04 0.08 0.14 REUR Asa wde -0.28-0.43-0.13 0.21 0.23 0.17 Germany Asa wde -0.11-0.25 0.07 0.11 0.22 0.14 49

Table 12: Sectoral utput Change (%) for Asa Wde Labor Productvty Shocks Servces Productvty Shock Manufacturng Productvty Shock 2014 2020 2030 2040 2014 2040 Japan Agrculture 1.06 4.19 6.20 7.48 0.43 3.46 Man - D 1.04 10.52 14.72 21.86 0.43 13.81 Man - ND -0.54 0.67 2.11 2.96 0.12 5.93 Servce 0.19 5.22 10.70 15.95 0.02 1.51 Korea Agrculture -0.43 0.72 3.25 4.38-0.02 3.11 Man - D 0.48 6.51 8.40 10.71 0.32 7.82 Man - ND -0.64 0.49 2.80 3.92-0.02 4.86 Servce 0.00 3.78 9.07 12.18-0.05 1.84 Chna Agrculture -0.13 0.50 1.33 1.71-0.07 1.50 Man - D 0.21 2.16 2.71 3.35 0.21 3.75 Man - ND -0.21 0.53 1.53 2.04-0.03 2.72 Servce 0.01 1.53 3.23 4.34-0.04 1.80 Inda Agrculture -0.41-0.42 0.72 0.84-0.13 0.55 Man - D 0.19 2.94 3.45 3.80 0.14 2.36 Man - ND -0.32 0.12 1.28 1.63 0.00 2.16 Servce -0.03 1.80 3.74 4.66-0.05 1.03 Indonesa Agrculture -0.28 0.19 1.41 1.63-0.09 1.20 Man - D 0.44 4.59 5.70 6.50 0.30 4.54 Man - ND -0.31 0.29 1.70 2.27 0.00 3.34 Servce -0.03 2.03 4.99 6.96-0.04 1.58 Table 13: Sectoral Employment Change (%) for Asa Wde Labor Productvty Shocks Servces Productvty Shock Manufacturng Productvty Shock 2014 2020 2030 2040 2014 2040 Japan Agrculture -0.97-0.28-2.01-3.30-0.20-0.76 Man - D 0.29 9.59 13.80 21.49-0.51-2.64 Man - ND -3.23-4.04-6.85-9.70-0.88-2.56 Servce -0.87-0.86-3.52-6.17-0.09 0.51 Korea Agrculture -1.76-1.12-2.13-3.76-0.55-2.40 Man - D 0.51 7.75 10.12 12.98-0.35-3.22 Man - ND -1.83-1.25-1.34-1.77-0.71-1.74 Servce -1.09-2.54-5.49-9.76-0.16 1.39 Chna Agrculture -0.29 0.20 0.48 0.69-0.21-0.02 Man - D 0.29 2.71 3.85 5.54-0.13-3.10 Man - ND -0.43 0.17 0.59 1.01-0.28-0.19 Servce -0.44-1.23-2.57-4.11-0.09 2.10 Inda Agrculture -0.75-0.37-0.22-0.24-0.26-0.41 Man - D 0.38 3.59 4.43 5.53-0.24-3.51 Man - ND -0.42 0.11 0.56 0.87-0.17-0.50 Servce -0.55-1.22-2.13-3.33-0.07 1.28 Indonesa Agrculture -0.68-0.20-0.48-0.74-0.29-1.19 Man - D 0.57 4.98 6.15 7.42 0.01-0.96 Man - ND -0.66-0.18-0.16-0.25-0.33-1.28 Servce -0.56-1.07-2.04-3.26-0.09 1.14 50

Fgure 1: Sectoral shares of employment- 11 Asan economes and the US, 1990-2005 5 51

Fgure 2: Sectoral shares of value added- 11 Asan economes and the US, 1990-2005 52

Fgure 3. Labor productvty n manufacturng sector for 11 Asan economes and the US 53

Fgure 4. The rato of servce to manufacturng labor productvty n 2005 54

Fgure 5. Servce sector employment and aggregate labor productvty growth for 11 Asan economes and the US 55

Fgure 6. GDP Effects of Servces Productvty Shock Chna GDP Japan GDP % Devaton 3.0 2.5 2.0 1.5 1.0 0.5 0.0-0.5 % Devaton 18.0 16.0 14.0 12.0 10.0 8.0 6.0 4.0 2.0 0.0 Chna All Asa Japan All Asa Korea GDP Inda GDP % Devaton 10.0 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0 % Devaton 3.0 2.5 2.0 1.5 1.0 0.5 0.0-0.5 Korea All Asa Inda All Asa USA GDP Australa GDP % Devaton 0.15 0.10 0.05 0.00-0.05-0.10-0.15-0.20-0.25 % Devaton 0.30 0.25 0.20 0.15 0.10 0.05 0.00-0.05 All Asa All Asa 56

Fgure 7. Investment Effects of Servces Productvty Shock g y Chna Investment Japan Investment % Devaton 5.0 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 % Devaton 70.0 60.0 50.0 40.0 30.0 20.0 10.0 0.0 Chna All Asa Japan All Asa Korea Investment Inda Investment % Devaton 25.0 20.0 15.0 10.0 5.0 0.0 % Devaton 5.0 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 Korea All Asa Inda All Asa USA Investment Australa Investment % Devaton 0.5 0.0-0.5-1.0-1.5-2.0-2.5-3.0-3.5 % Devaton 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 All Asa All Asa 57

Fgure 8. Consumpton Effects of Servces Productvty Shock Chna Consumpton Japan Consumpton % Devaton 2.5 2.0 1.5 1.0 0.5 0.0-0.5-1.0-1.5 % Devaton 6.0 5.0 4.0 3.0 2.0 1.0 0.0 Chna All Asa Japan All Asa Korea Consumpton Inda Consumpton % Devaton 5.0 4.0 3.0 2.0 1.0 0.0-1.0-2.0 % Devaton 2.0 1.5 1.0 0.5 0.0-0.5-1.0-1.5 Korea All Asa Inda All Asa USA Consumpton Australa Consumpton % Devaton 0.10 0.05 0.00-0.05-0.10-0.15-0.20-0.25-0.30-0.35 % Devaton 0.20 0.15 0.10 0.05 0.00-0.05-0.10-0.15 All Asa All Asa 58

Fgure 9. Sectoral utput and Employment Effects of Servces Productvty Shock A. Chna g 3.0 utput Effects of 1% Servce Productvty Growth Employment Effects of 1% Servce Productvty Growth 2.5 3.0 2.5 2.0 1.5 1.0 0.5 2.0 1.5 1.0 0.5 0.0 0.5 1.0 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 0.0 0.5 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 1.5 2.0 2.5 Chna Agrculture utput Chna Non Durable Manutput Chna Durable Man utput Chna Servces utput Chna Agrculture Labor Chna Non Durable ManLabor Chna Durable Man Labor Chna Servces Labor B. Japan 12.0 utput Effects of 1% Servce Productvty Growth Employment Effects of 1% Servce Productvty Growth 10.0 8.0 12.0 10.0 8.0 6.0 6.0 4.0 4.0 2.0 2.0 0.0 2.0 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 0.0 2.0 4.0 6.0 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 Japan Agrculture utput Japan Durable Man utput Japan Agrculture Labor Japan Durable Man Labor Japan Non Durable Manutput Japan Servces utput Japan Non Durable ManLabor Japan Servces Labor C. Korea g 7.0 utput Effects of 1% Servce Productvty Growth Employment Effects of 1% Servce Productvty Growth 6.0 10.0 5.0 8.0 4.0 3.0 2.0 1.0 6.0 4.0 2.0 0.0 2.0 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 0.0 1.0 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 4.0 6.0 Korea Agrculture utput Korea Non Durable Manutput Korea Durable Man utput Korea Servces utput Korea Agrculture Labor Korea Non Durable ManLabor Korea Durable Man Labor Korea Servces Labor 59

Appendx: The G-Cubed Model The reader s referred to the complete documentaton of the model n the Handbook of CGE Modelng. Ths Appendx draws heavly on the exposton n McKbbn and Wlcoxen (2013). The verson of the model used n ths paper s the sx sector model wth country and sectoral coverage set out n Tables 7 and 8. Each economy or regon n the model conssts of several economc agents: households, the government, the fnancal sector and the sx producton sectors lsted above. The theoretcal structure s outlned below. To keep the notaton as smple as possble varables are not subscrpted by country except where needed for clarty. Throughout the dscusson all quantty varables wll be normalzed by the economy's endowment of effectve labor unts. Thus, the model's long run steady state wll represent an economy n a balanced growth equlbrum. The soluton software lnearzes around the ntal condtons n 2010 rather than the steady state. Frms Each of the sx sectors s represented by a prce-takng frm whch chooses varable nputs and ts level of nvestment n order to maxmze ts stock market value. Each frm s producton technology s represented by a ter-structured constant elastcty of substtuton (CES) functon. At the top ter, output s a functon of captal, labor, energy and materals: (14) 1 1 1 Q = A j X j j=k,l,e,m where Q s the output of ndustry, X j s ndustry 's use of nput j, and A, 60 j, and are parameters. A reflects the level of technology, s the elastcty of substtuton, and the parameters reflect the weghts of dfferent nputs n producton; the superscrpt o ndcates that the parameters apply to the top, or output, ter. Wthout loss of generalty, we constran the δ's to sum to one. At the second ter, nputs of energy and materals, X E and X M, are themselves CES aggregates of goods and servces. Energy s a sngle good 1 and materals s an aggregate of goods 2 through 6 (mnng through servces). The functonal form used for these ters s dentcal to (14) except that the parameters of the energy ter are A E E, j, and E, and those of the materals ter are A M, M j, and M. j

The goods and servces purchased by frms are, n turn, aggregates of mported and domestc commodtes whch are taken to be mperfect substtutes. We assume that all agents n the economy have dentcal preferences over foregn and domestc varetes of each commodty. We represent these preferences by defnng twelve composte commodtes that are produced from mported and domestc goods. Each of these commodtes, Y, s a CES functon of nputs domestc output, Q, and mported goods, M. 16 For example, the mnng products purchased by agents n the model are a composte of mported and domestc mnng. By constranng all agents n the model to have the same preferences over the orgn of goods we requre that, for example, the agrcultural and servce sectors have the dentcal preferences over domestc energy and energy mported from the Mddle East. 17 Ths accords wth the nput-output data we use and allows a very convenent nestng of producton, nvestment and consumpton decsons. In each sector the captal stock changes accordng to the rate of fxed captal formaton (J ) and the rate of geometrc deprecaton (δ ): (15) K = J K Followng the cost of adjustment models of Lucas (1967), Treadway (1969) and Uzawa (1969) we assume that the nvestment process s subject to rsng margnal costs of nstallaton. To formalze ths we adopt Uzawa's approach by assumng that n order to nstall J unts of captal a frm must buy a larger quantty, I, that depends on ts rate of nvestment (J/K): J (16) I = 1+ J 2 K where s a non-negatve parameter. The dfference between J and I may be nterpreted varous ways; we wll vew t as nstallaton servces provded by the captal-goods vendor The goal of each frm s to choose ts nvestment and nputs of labor, materals and energy to maxmze ntertemporal rsk-adjusted net-of-tax profts. For analytcal tractablty, we assume that ths problem s determnstc (equvalently, the frm could be assumed to beleve ts estmates of future varables wth subjectve certanty). Thus, the frm wll maxmze: 18 16 The elastcty of substtuton n ths functon s the Armngton elastcty. 17 Ths does not requre that both sectors purchase the same amount of energy, or even that they purchase energy at all; only that they both feel the same way about the orgns of energy they buy. 18 The rate of growth of the economy's endowment of effectve labor unts, n, appears n the dscount factor because the quantty and value varables n the model have been scaled by the number of effectve labor unts. These varables must be multpled by exp(nt) to convert them back to ther orgnal form. 61

I ( R( s ) e n) ( st) (17) ( (1 4) P I ) e t ds where e s a sector and regon-specfc equty rsk premum all varables are mplctly subscrpted by tme. The frm s profts,, are gven by: * E M (18) = ( 1 2 )( P Q W L P X E P X M) where τ 2 s the corporate ncome tax, τ 4 s an nvestment tax credt, and P * s the producer prce of the frm s output. R(s) s the long-term nterest rate between perods t and s: 1 (19) R( s) = r( v) dv s t Because all real varables are normalzed by the economy's endowment of effectve labor unts, profts are dscounted adjustng for the rate of growth of populaton plus productvty growth, n. Solvng the top ter optmzaton problem gves the followng equatons characterzng the frm s behavor: (20) X A Q j {L,E, M} j j 1 s t * P P j J (21) ( 1 )(1 4) P K = I (22) d * dq I J = ( r e + ) (1 2) P (1 4) P ds dk 2 K 2 where λ s the shadow value of an addtonal unt of nvestment n ndustry. Equaton (20) gves the frm s factor demands for labor, energy and materals, and equatons (21) and (22) descrbe the optmal evoluton of the captal stock. By ntegratng (22) along the optmum path of captal accumulaton, t s straghtforward to show that λ s the ncrement to the value of the frm from a unt ncrease n ts nvestment at tme t. It s related to q, the after-tax margnal verson of Tobn's Q (Abel, 1979), as follows: 62

(23) = q 1 P 4 I Thus we can rewrte (21) as: 1 (24) = q 1 Insertng ths nto (16) gves total purchases of new captal goods: (25) J K 1 I q 2 1 K 2 In order to capture the nerta often observed n emprcal nvestment studes we assume that only fracton 2 (for_ n the parameter fle) of frms makng nvestment decson use the fully forward-lookng Tobn s q descrbed above. The remanng (1 2) use a slowly-adjustng verson, Q, drven by a partal adjustment model. In each perod, the gap between Q and q closes by fracton 3 : (26) Q ( ) t 1 Q t 3 q t Qt As a result, we modfy (25) by wrtng I as a functon not only of q, but also the slowly adjustng Q: 2 (27) 2 1 1 q 1 K 1 Q 2 2 2 2 I 1 K Ths creates nerta n prvate nvestment, whch mproves the model s ablty to mmc hstorcal data and s consstent wth the exstence of frms that are unable to borrow. The weght on unconstraned behavor, 2, s taken to be 0.3 based on a range of emprcal estmates reported by McKbbn and Sachs (1991). So far we have descrbed the demand for nvestment goods by each sector. Investment goods are suppled, n turn, by a thrteenth ndustry that combnes labor and the outputs of other ndustres to produce raw captal goods. We assume that ths frm faces an optmzaton problem dentcal to those of the other twelve ndustres: t has a nested CES producton functon, uses nputs of captal, labor, energy and materals n the top ter, ncurs adjustment costs when changng ts captal stock, and earns zero profts. The key dfference between t and the other sectors s that 63

we use the nvestment column of the nput-output table to estmate ts producton parameters. Households Households have three dstnct actvtes n the model: they supply labor, they save, and they consume goods and servces. Wthn each regon we assume household behavor can be modeled by a representatve agent wth an ntertemporal utlty functon of the form: - ( s-t ) (28) U t = (ln C( s) + ln G( s)) e ds t where C(s) s the household's aggregate consumpton of goods and servces at tme s, G(s) s government consumpton at s, whch we take to be a measure of publc goods provded, and θ s the rate of tme preference. 19 The household maxmzes (28) subject to the constrant that the present value of consumpton (potentally adjusted by rsk premum h ) be equal to the sum of human wealth, H, and ntal fnancal assets, F: 20 (29) c ( ( ) h )( ) () () R s P scse n s t Ht Ft t Human wealth s defned as the expected present value of the future stream of after-tax labor ncome plus transfers: (30) ( ) ( ) (1 1)( ( G C I ) ) R s h H t = - W L + L + L + L TR e n s t ds t where 1 s the tax rate on labor ncome, TR s the level of government transfers, L C s the quantty of labor used drectly n fnal consumpton, L I s labor used n producng the nvestment good, L G s government employment, and L s employment n sector. Fnancal wealth s the sum of real money balances, MN/P, real government bonds n the hand of the publc, B, net holdng of clams aganst foregn resdents, A, the value of captal n each sector, and holdngs of emssons permts, Q P : 12 1 (31) MN F = P + B + A+ q I K I + q C K C + 12 12 q K = 1 = 1 P P Q P 19 Ths specfcaton mposes the restrcton that household decsons on the allocatons of expendture among dfferent goods at dfferent ponts n tme be separable. 20 As before, n appears n (29) because the model's scaled varables must be converted back to ther orgnal bass. 64

Solvng ths maxmzaton problem gves the famlar result that aggregate consumpton spendng s equal to a constant proporton of prvate wealth, where prvate wealth s defned as fnancal wealth plus human wealth: C (32) PC = ( )( F+H) However, based on the evdence cted by Campbell and Mankw (1990) and Hayash (1982) we assume some consumers are lqudty-constraned and consume a fxed fracton γ of ther aftertax ncome (INC). 21 Denotng the share of consumers who are not constraned and choose consumpton n accordance wth (32) by 8, total consumpton expendture s gven by: C (33) P C = 8( h )( F t + H t) + (1 8) INC The share of households consumng a fxed fracton of ther ncome could also be nterpreted as permanent ncome behavor n whch household expectatons about ncome are myopc. nce the level of overall consumpton has been determned, spendng s allocated among goods and servces accordng to a two-ter CES utlty functon. 22 At the top ter, the demand equatons for captal, labor, energy and materals can be shown to be: C C 1 C C, P P C (34) P X P C, K, L, E M where X C s household demand for good, C s the top-ter elastcty of substtuton and the are C are the nput-specfc parameters of the utlty functon. The prce ndex for consumpton, P C, s gven by: h (35) P C Cj jk, L, E, M P C 1 j 1 C 1 The demand equatons and prce ndces for the energy and materals ters are smlar. 21 There has been consderable debate about the emprcal valdty of the permanent ncome hypothess. In addton the work of Campbell, Mankw and Hayash, other key papers nclude Hall (1978), and Flavn (1981). ne sde effect of ths specfcaton s that t prevents us from computng equvalent varaton. Snce the behavor of some of the households s nconsstent wth (32), ether because the households are at corner solutons or for some other reason, aggregate behavor s nconsstent wth the expendture functon derved from our utlty functon. 22 The use of the CES functon has the undesrable effect of mposng untary ncome elastctes, a restrcton usually rejected by data. An alternatve would be to replace ths specfcaton wth one derved from the lnear expendture system. 65

Household captal servces consst of the servce flows of consumer durables plus resdental housng. The supply of household captal servces s determned by consumers themselves who nvest n household captal, K C, n order to generate a desred flow of captal servces, C K, accordng to the followng producton functon: K (36) C = K where s a constant. Accumulaton of household captal s subject to the condton: C C C (37) K = J K We assume that changng the household captal stock s subject to adjustment costs so household spendng on nvestment, I C, s related to J C by: C C C (38) J I = 1+ C J 2 K Thus the household's nvestment decson s to choose I C to maxmze: CK c I C (39) ( ) z R s P K P I e n s t t where P CK s the mputed rental prce of household captal and z s a rsk premum on household captal (possbly zero). Ths problem s nearly dentcal to the nvestment problem faced by frms, ncludng the partal adjustment mechansm outlned n equatons (26) and (27), and the results are very smlar. The only mportant dfference s that no varable factors are used n producng household captal servces. The Labor Market We assume that labor s perfectly moble among sectors wthn each regon but s mmoble between regons. Thus, wages wll be equal across sectors wthn each regon, but wll generally not be equal between regons. In the long run, labor supply s completely nelastc and s determned by the exogenous rate of populaton growth. Long run wages adjust to move each regon to full employment. In the short run, however, nomnal wages are assumed to adjust slowly accordng to an overlappng contracts model where wages are set based on current and expected nflaton and on labor demand relatve to labor supply. Ths can lead to short-run unemployment f unexpected shocks cause the real wage to be too hgh to clear the labor market. 66 C C C ds

At the same tme, employment can temporarly exceed ts long run level f unexpected events cause the real wage to be below ts long run equlbrum. Government We take each regon's real government spendng on goods and servces to be exogenous and assume that t s allocated among nputs n fxed proportons, whch we set to 2006 values. Total government outlays nclude purchases of goods and servces plus nterest payments on government debt, nvestment tax credts and transfers to households. Government revenue comes from sales taxes, corporate and personal ncome taxes, and from sales of new government bonds. In addton, there can be taxes on externaltes such as carbon doxde emssons. The government budget constrant may be wrtten n terms of the accumulaton of publc debt as follows: (40) B t = D t = rt Bt +G t +TRt T where B s the stock of debt, D s the budget defct, G s total government spendng on goods and servces, TR s transfer payments to households, and T s total tax revenue net of any nvestment tax credt. We assume that agents wll not hold government bonds unless they expect the bonds to be pad off eventually and accordngly mpose the followng transversalty condton: (41) R ( s ) n s lm B( s) e = 0 s Ths prevents per capta government debt from growng faster than the nterest rate forever. If the government s fully leveraged at all tmes, (41) allows (40) to be ntegrated to gve: (42) R( s) nst B = (T G TR)e t ds t Thus, the current level of debt wll always be exactly equal to the present value of future budget surpluses. 23 The mplcaton of (42) s that a government runnng a budget defct today must run an approprate budget surplus as some pont n the future. therwse, the government would be unable to pay nterest on the debt and agents would not be wllng to hold t. To ensure that (42) t 23 Strctly speakng, publc debt must be less than or equal to the present value of future budget surpluses. For tractablty we assume that the government s ntally fully leveraged so that ths constrant holds wth equalty. 67

holds at all ponts n tme we assume that the government leves a lump sum tax n each perod equal to the value of nterest payments on the outstandng debt. 24 In effect, therefore, any ncrease n government debt s fnanced by consols, and future taxes are rased enough to accommodate the ncreased nterest costs. ther fscal closure rules are possble, such as requrng the rato of government debt to GDP to be unchanged n the long run or that the fscal defct be exogenous wth a lump sum tax ensurng ths holds. These closures have nterestng mplcatons but are beyond the scope of ths paper. Fnancal Markets and the Balance of Payments The seventeen regons n the model are lnked by flows of goods and assets. Flows of goods are determned by the mport demands descrbed above. These demands can be summarzed n a set of blateral trade matrces whch gve the flows of each good between exportng and mportng countres. There s one nne by nne trade matrx for each of the twelve goods. Trade mbalances are fnanced by flows of assets between countres. Each regon wth a current account defct wll have a matchng captal account surplus, and vce versa. 25 We assume asset markets are perfectly ntegrated across regons. Wth free moblty of captal, expected returns on loans denomnated n the currences of the varous regons must be equalzed perod to perod accordng to a set of nterest arbtrage relatons of the followng form: (43) k E k = j j + E j k j k where k and j are the nterest rates n countres k and j, k and j are exogenous rsk premums demanded by nvestors (possbly zero), and E j k s the exchange rate between the currences of the two countres. 26 However, n cases where there are nsttutonal rgdtes to captal flows, the arbtrage condton does not hold and we replace t wth an explct model of the relevant restrctons (such as captal controls). Captal flows may take the form of portfolo nvestment or drect nvestment but we assume these are perfectly substtutable ex ante, adjustng to the expected rates of return across 24 In the model the tax s actually leved on the dfference between nterest payments on the debt and what nterest payments would have been f the debt had remaned at ts base case level. The remander, nterest payments on the base case debt, s fnanced by ordnary taxes. 25 Global net flows of prvate captal are constraned to be zero at all tmes the total of all funds borrowed exactly equals the total funds lent. As a theoretcal matter ths may seem obvous, but t s often volated n nternatonal fnancal data. 26 The one excepton to ths s the ol exportng regon, whch we treat as choosng ts foregn lendng n order to mantan a desred rato of ncome to wealth. 68

economes and across sectors. Wthn each economy, the expected returns to each type of asset are equated by arbtrage, takng nto account the costs of adjustng physcal captal stock and allowng for exogenous rsk premums. However, because physcal captal s costly to adjust, any nflow of fnancal captal that s nvested n physcal captal wll also be costly to shft once t s n place. Ths means that unexpected events can cause wndfall gans and losses to owners of physcal captal and ex post returns can vary substantally across countres and sectors. For example, f a shock lowers profts n a partcular ndustry, the physcal captal stock n the sector wll ntally be unchanged but ts fnancal value wll drop mmedately. Money and Monetary Rules We assume that money enters the model va a constrant on transactons. 27 We use a money demand functon n whch the demand for real money balances s a functon of the value of aggregate output and short-term nomnal nterest rates: (44) MN= PY where Y s aggregate output, P s a prce ndex for Y, s the nterest rate, and ε s the nterest elastcty of money demand. Followng McKbbn and Sachs (1991) we take ε to be -0.6. n the supply sde, the model ncludes an endogenous monetary response functon for each regon. Each regon s central bank s assumed to adjust short term nomnal nterest rates followng a modfed Henderson-McKbbn-Taylor rule made up of two equatons. The frst s a desred nterest rate ( d ) and the second s the actual polcy nterest rate ( t ) whch adjusts to the desred rate over tme. The two equatons follow: (31a) = + ( ) + ( ) + ( ) + ( ) (31b) = + + The desred nterest rate ( d ) evolves as a functon of actual nflaton (π) relatve to target T T nflaton ( ), output growth (Δy) relatve to growth of potental output ( y ), nomnal ncome (ny) relatve to target nomnal ncome (ny T )and the change n the exchange rate (Δe) relatve to T the bank s target change ( e ). The actual polcy nterest rate ( t ) adjusts gradually to the desred polcy rate ( d ) and can be shfted exogenously n the short term by changng the exogenous component ( x ). 27 Unlke other components of the model we smply assume ths rather than dervng t from optmzng behavor. Money demand can be derved from optmzaton under varous assumptons: money gves drect utlty; t s a factor of producton; or t must be used to conduct transactons. The dstnctons are unmportant for our purposes. 69

The parameters n monetary response functon vary across countre.. For example, countres that peg ther exchange rate to the US Dollar have a very large value for β4. In the current model we assume that nomnal ncome targetng s the major polcy rule gven the results are forward lookng and most countres wll move over tme to ths type of rule. The rule also need to be able to model unconventonal monetary polces n some advanced economes through adjustment to the exogenous part of the rule ( x ). Parameterzaton To estmate G-Cubed s parameters we began by constructng a consstent tme seres of nputoutput tables for the Unted States. The procedure s descrbed n detal n McKbbn and Wlcoxen (1999a) and can be summarzed as follows. We started wth the detaled benchmark U.S. nput-output transactons tables produced by the Bureau of Economc Analyss (BEA) and converted them to a standard set of ndustral classfcatons and then aggregate them to twelve sectors. 28 Second, we corrected the treatment of consumer durables, whch are ncluded n consumpton rather than nvestment n the U.S. Natonal Income and Product Accounts and the benchmark nput-output tables. Thrd, we supplemented the value added rows of the tables usng a detaled dataset on captal and labor nput by ndustry constructed by Dale Jorgenson and hs colleagues. 29 Fnally, we obtaned prces for each good n each benchmark year from the output and employment data set constructed by the ffce of Employment Projectons at the Bureau of Labor Statstcs (BLS). Ths dataset allowed us to estmate the model s parameters for the Unted States. To estmate the producton sde of the model, we began wth the energy and materals ters because they have constant returns to scale and all nputs are varable. In ths case t s convenent to replace the producton functon wth ts dual unt cost functon. For ndustry, the unt cost functon for energy s: 28 Convertng the data to a standard bass was necessary because the sector defntons and accountng conventons used by the BEA have changed over tme. 29 Prmary factors often account for half or more of ndustry costs so t s partcularly mportant that ths part of the data set be constructed as carefully as possble. From the standpont of estmatng cost and producton functons, however, value added s the least satsfactory part of the benchmark nput-output tables. In the early tables, labor and captal are not dsaggregated. In all years, the technques used by the BEA to construct mplct prce deflators for labor and captal are subject to varous methodologcal problems. ne example s that the ncome of propretors s not splt between captal and mputed labor ncome correctly. The Jorgenson dataset corrects these problems and s the work of several people over many years. In addton to Dale Jorgenson, some of the contrbutors were L. Chrstensen, Barbara Fraumen, Mun Sng Ho and Dae Keun Park. The orgnal source of the data s the Fourteen Components of Income tape produced by the Bureau of Economc Analyss. See Ho (1989) for more nformaton. 70

(45) E 1 c = E A 5 E E 1 k pk 1 k= 1 1 E The cost functon for materals has a smlar form. Assumng that the energy and materals nodes earn zero profts, c wll be equal to the prce of the node's output. Usng Shepard's Lemma to derve demand equatons for ndvdual commodtes and then convertng these demands to cost shares gves expressons of the form: E 1 P E E j (46) s j j, j 1,, 5 E A P E where s j s the share of ndustry s spendng on energy that s devoted to purchasng nput j. 30 A E, E, and E j were found by estmatng (45) and (46) as a system of equatons. 31 Estmates of the parameters n the materals ter were found by an analogous approach. The output node must be treated dfferently because t ncludes captal, whch s not varable n the short run. We assume that the frm chooses output, Q, and ts top-ter varable nputs (L, E and M) to maxmze ts restrcted proft functon, π: (47) = p Q p X j jl, E, M where the summaton s taken over all nputs other than captal. Insertng the producton functon nto (47) and rewrtng gves: 1 1 1 1 1 (48) P A k K j X j Pj X jl, E, M jl, E, M where K s the quantty of captal owned by the frm, δ k s the dstrbutonal parameter assocated wth captal, and j ranges over nputs other than captal. Maxmzng (48) wth respect to varable nputs produces the followng factor demand equatons for ndustry : j j 30 When E s unty, ths collapses to the famlar Cobb-Douglas result that s= and s ndependent of prces. 31 For factors for whch the value of s was consstently very small, we set the correspondng nput to zero and estmated the producton functon over the remanng nputs. 71

1 1 1 1 1 (49) X = P j j j k K P A k Pk, j { L, E, M} Ths system of equatons can be used to estmate the top-ter producton parameters. The results are lsted n McKbbn and Wlcoxen (1999a). Much of the emprcal lterature on cost and producton functons fals to account for the fact that captal s fxed n the short run. Rather than usng (49), a common approach s to use factor demands of the form: k (50) X j = j P Q A P k kk, L, E, M 1 k 1 Ths expresson s correct only f all nputs are varable n the short run. In McKbbn and Wlcoxen (1999a) we show that usng equaton (50) bases the estmated elastcty of substtuton toward unty for many sectors n the model In petroleum refnng, for example, the fxed-captal estmate for the top ter elastcty, 3, s 0.54 whle n the varable elastcty case t s 1.04. The treatment of captal thus has a very sgnfcant effect on the estmated elastctes of substtuton. Estmatng parameters for regons other than the Unted States s more dffcult because tmeseres nput-output data s often unavalable. In part ths s because some countres do not collect the data regularly and n part because many of G-Cubed s geographc enttes are regons rather than ndvdual countres. As a result, we mpose the restrcton that substtuton elastctes wthn ndvdual ndustres are equal across regons. 32 By dong so, we are able to use the U.S. elastcty estmates everywhere. The share parameters (the δ's n the equatons above), however, are derved from regonal nput-output data taken from the GTAP 7 database and dffer from one regon to another. In effect, we are assumng that all regons share a smlar but not dentcal producton technology. Ths s ntermedate between one extreme of assumng that the regons share common technologes and the other extreme of allowng the technologes to dffer n arbtrary ways. The regons also dffer n ther endowments of prmary factors, ther government polces, and patterns of fnal demands. Fnal demand parameters, such as those n the utlty functon or n the producton functon of new nvestment goods were estmated by a smlar procedure: elastctes were estmated from 32 For example, the top ter elastcty of substtuton s dentcal n the durable goods ndustres of Japan and the Unted States. Ths approach s consstent wth the econometrc evdence of Km and Lau (1994). Ths specfcaton does not mean, however, that the elastctes are the same across ndustres wthn a country. 72

U.S. data and share parameters were obtaned from regonal nput-output tables. Trade shares were obtaned from 2009 Unted Natons Standard Industry Trade Classfcaton (SITC) data aggregated up from the four-dgt level. 33 The trade elastctes are based on a survey of the lterature and vary between 1 and 3. 34 Table A1 contans some key parameters for The Asan economes n the model. Table A1 : Key Macro parameters adapt 0.35 nt_elast -0.6 labgrow 0.018 ph_1 4 ph_2 15 ph_3 4 ph_4 4 ph_5 4 ph_6 4 ph_y 4 ph_z 4 tmepref 0.022 wage_p 0.4 wage_q 0.35 delta 0.1 fore_ 0.3 fore_c 0.3 mpc 1 r0 0.04 33 A full mappng of SITC codes nto G-Cubed ndustres s contaned n McKbbn and Wlcoxen (1994). 34 For a senstvty analyss examnng the role of the trade elastctes and several other key parameters, see McKbbn, Ross, Shackleton and Wlcoxen (1999). 73