St. Gallen, Switzerland, August 22-28, 2010

Transcription

1 Sesson Number: Plenary Sesson 3 Tme: Tuesday, August 23, A Paper Prepared for the 31st General Conference of The Internatonal Assocaton for Research n Income and Wealth St. Gallen, Swtzerland, August 22-28, 2010 World Input-Output Database (WIOD): Constructon, Challenges and Applcatons Abdul Azeez Erumbana Retze Goumaa Bart Losa,b Robert Stehrerc Umed Temurshoevb arcel Tmmer a,b,* Gaatzen de Vresa For addtonal nformaton please contact: Name: arcel Tmmer Afflaton: Unversty of Gronngen Emal addresses: m.p.tmmer@rug.nl Ths paper s posted on the followng webste:

2 Paper prepared for Thrty-frst General IARIW Conference Sankt Gallen, 2010 Plenary Sesson 3: The Impact of Globalzaton World Input-Output Database (WIOD): Constructon, Challenges and Applcatons Abdul Azeez Erumban a Retze Gouma a Bart Los a,b Robert Stehrer c Umed Temurshoev b arcel Tmmer a,b, * Gaatzen de Vres a NB The results n ths paper are prelmnary and should not be quoted Afflatons a Gronngen Growth and Development Centre, Unversty of Gronngen b European Network for Input-Output Studes, Unversty of Gronngen c The Venna Insttute for Internatonal Economc Studes (WIIW) * Correspondng Author arcel P. Tmmer Gronngen Growth and Development Centre Faculty of Economcs and Busness Unversty of Gronngen The Netherlands m.p.tmmer@rug.nl 1

3 Acknowledgements: The constructon of the World Input-Output Database s one of the actvtes n the WIOD-project. Ths project s funded by the European Commsson, Research Drectorate General as part of the 7th Framework Programme, Theme 8: Soco-Economc Scences and Humantes, grant Agreement no: We would lke to thank the other partcpants n the project for ther helpful comments and suggestons. ore nformaton on the WIOD-project can be found at Abstract Ths paper descrbes the contents and constructon of a new database to analyze the effects of globalzaton on soco-economc and envronmental trends at the country and global level. Ths database called WIOD (World Input-Output Database) s constructed by lnkng natonal supply and use tables wth statstcs on nternatonal trade. In ths way t s feasble to estmate e.g. the use of Chnese pant n German cars bought by Japanese consumers. Ths nternatonal nput-output table s frmly grounded n natonal accounts statstcs and complemented wth addtonal soco-economc accounts on the use of varous types of labour (by skll level) and captal (ICT and non-ict assets). It also ncludes varous envronmental ndcators such as energy use and greenhouse-gas emsson. The database wll nclude the major economes n the world coverng 90% of world GDP and provde tme seres from 1995 onwards. We dscuss the methods and datasources used n constructon. In addton we gve llustratve applcatons n the area of outsourcng and ts mpact on global producton networks and emssons of greenhouse gases. The database s currently beng constructed by a consortum of eleven research nsttutes n the WIOD-project ( and the paper reports on the frst phase of ths project. 2

4 1. Introducton The ongong process of globalsaton puts new challenges to the study of economc growth and development around the world. As fnance, people, goods and servces ncreasngly flow from one country to another, nternatonal nterdependences strongly mpact on the development space of ndvdual countres. Changng patterns of world trade drve ncome dstrbutons across and wthn regons, and shft envronmental burdens of producton and consumpton. Ths s manfest n the mushroomng of global producton networks n whch varous stages of the producton process take place at dstant geographcal areas. Intermedate goods and servces are heavly traded across borders, drven by the opportuntes offered by advances n nformaton and communcaton technologes. A hard-dsk drve manufactured n Thaland typcally conssts of nputs sourced from over ffteen dfferent countres. A car n Span s assembled out of mports from all around the world. Ths globalsaton process provdes new opportuntes for a global dvson of labour and producton, ncreasng employment opportuntes and growth. On the other hand, shftng trade and producton patterns mght have adverse effects on local and global dstrbutons of ncome and natural resources. For example, the polluton haven hypothess mantans that rch countres are able to contan the envronmental pressure of domestc producton only by relocatng polluton-ntensve ndustres. Ths would lead to an ncreasng dvergence between the actual use of resources n local producton and the use of resources mplct n local consumpton. Globalsaton also puts new demands on statstcal nformaton for research and polcy analyss. A thorough analyss of globalsaton and ts effects on the economy and envronment reles heavly on extensve montorng of nternatonal trade. Exstng nternatonal trade statstcs provde nformaton on the value of goods and servces traded, but convey lttle about the value added n producton by the exportng country. The latter though s crucal for an analyss of e.g. ncome, employment and envronmental effects of local producton. Ths type of nformaton however s currently not beng collected n statstcal systems and researchers have to rely on datasets constructed outsde the nternatonal statstcal systems. Varous alternatve datasets have been bult n the past of whch the GTAP database s the most wdely known and used. However, all these databases provde only one or a lmted amount of benchmark years and do not offer an analyss of developments over tme. In ths paper we present a new database called the World Input-Output Database (WIOD) that ams to fll ths gap. The WIOD wll provde a tme-seres of world nput-output tables from 1995 onwards. Natonal nput-output tables of forty major countres n the world are lnked through nternatonal trade statstcs. A world nput-output table allows one to study say the use of Chnese chemcals n German automobles bought by Japanese consumers over tme. oreover, the WIOD contans addtonal satellte accounts. A socoeconomc account provdes detaled nformaton on the use of varous type of labour (dstngushed by skll level) and captal (ncludng ICT and non-ict) n producton. The envronmental accounts provde nformaton on energy use, greenhouse-gas emssons and other ar pollutants of producton and fnal consumpton. By standardsng concepts and classfcatons, 3

5 WIOD opens up a new range of feasble studes on the effects of globalsaton. As the WIOD wll be made avalable to the publc for free n due tme, we hope to stmulate new research n ths area. The remander of the paper s organsed as follows. In secton 2 we outlne the conceptual framework of a world nput-output table. ethods of constructon and datasources used are dscussed n Secton 3. Secton 4 ntroduces datasources for the world nput-output table and the soco-economc and envronmental satellte accounts. In Secton 5 we provde two prelmnary applcatons of the WIOD: one on nternatonal trade n value added and another on consumptonbased accountng of greenhouse-gas emssons. Secton 6 concludes. 2. World Input-Output Table (WIOT): Concepts In ths secton we outlne the basc concepts of a world nput-output table (WIOT). A natural startng pont to nvestgate the ncreasng nterdependence of countres s the use of nternatonal trade statstcs. Export and mport statstcs are routnely produced by natonal statstcal nsttutes (NSIs) on the bass of custom declaratons and frm surveys. The complaton of ths data s nternatonally harmonsed and comparable statstcs are frequently publshed by the European Unon, the OECD and the Unted Natons. Exports and mports as a share of GDP are steadly ncreasng n most countres n the world and ths measure s often used to ndcate the ncreasng connecton of natonal economes. An ncreasng share of ths nternatonal exchange s trade n ntermedate products. Rather than goods destned for fnal consumpton, these goods are further used n the producton process of the mportng country. Ths phenomenon s also known as global producton networks. Separate stages of the producton process now take place at dfferent geographcal locatons rather than beng concentrated n a home country. For example, whereas n the past the producton of personal computers took manly place wthn the U.S., now the separate phases of component producton, assembly, testng and packagng are scattered around the world. There s much evdence about the rse of these networks n the past decades but ths conssts mostly of sngle product studes based on frm-level cases (Kaplnsky 2000, Gereff 1999; Sturgeon, van Besebroeck and Gereff 2008) A major bottleneck n the study of global producton networks and ther soco-economc and envronmental effects s the lack of nformaton on cross-country nter-ndustry lnkages. Internatonal trade statstcs ndcate the value of export of say dsk-drves from alaysa to Japan. But they do not convey any nformaton about the value of the product that s actually created n the exportng country. The only nformaton gven n the trade statstcs s the descrpton of the product, followng nternatonal product classfcatons, such as the Harmonsed System (HS). When the components of the dsk-drve, such as optcal devces, sem-conductors and plastcs, are mported by alaysa, rather than produced domestcally, the export value of the dsk-drve wll be a weak ndcator of the value added by the alaysan economy. It may range anywhere between vrtually zero, n case alaysa s merely re-exportng fnshed dsk-drves 4

6 from another country, to the full value n case all stages of producton took place wthn the alaysan economy. As a result, the ncreasng mportance of global producton networks dmnshes the usefulness of nternatonal trade statstcs for country-level analyss. It may lead to relance on msleadng ndcators such as the share of hgh-tech products n total exports. Ths s a popular ndcator of the strength of a natonal economy and nnovaton system. But ths ndcator can be hgh even for a country that s only nvolved n the last stages of producton such as testng and packagng that requre lttle sklls or techncal capabltes. Clearly what s needed for ths type of analyss s nformaton not only on the nternatonal flow of products, but also on the nter-ndustry flows. Ths would enable one to track the orgn of products used as ntermedates, eher beng domestcally produced or mported, and the ndustry from whch t orgnated. Ths type of nformaton s contaned n a so-called nternatonal, or world, nput-output table. To outlne the framework of such a table we start wth the dscusson of a natonal nput-output (IO) table. In Fgure 1 the schematc outlne for a natonal nput-out table (IOT) s presented. For ease of dscusson we assume that each ndustry produces only one (unque) product. 1 The rows n the upper parts ndcate the use of products, beng for ntermedate or fnal use. Each product can be an ntermedate n the producton of other products (ntermedate use). Fnal use ncludes domestc use (prvate or government consumpton and nvestment) and exports. The fnal element n each row ndcates the total use of each product. The ndustry columns n the IOT contan nformaton on the supply of each product. A product can be mported or domestcally produced. The column ndcates the values of all ntermedate, labour and captal nputs used n producton. The vector of nput shares n output s often referred to as the technology for domestc producton. The compensaton for labour and captal servces together make up value added whch ndcates the value added by the use of domestc labour and captal servces to the value of the ntermedate nputs. Total supply of the product n the economy s determned by domestc output plus mports. An mportant accountng dentty n the IOT s that total supply equals total use for each product, such that all flows n the economc system are accounted for. The natonal IOTs are the basc buldng blocks for constructng our World IO table. [Fgure 1 about here] Bascally, a world nput-output table (WIOT) s a combnaton of natonal IOTs n whch the use of products s broken down accordng to ther orgn. Each product s produced ether by a domestc ndustry or by a foregn ndustry. In contrast to the natonal IOT, ths nformaton s made explct n the WIOT. For a country A, flows of products both for ntermedate and fnal use are splt nto domestcally produced or mported. In addton, the WIOT shows for mports n whch foregn ndustry the product was produced. Ths s llustrated by the schematc outlne for a WIOT n Fgure 2. 1 See Blar and ller (2009) for an elaborate ntroducton to nput-output tables and analyss. 5

7 [Fgure 2 about here] Fgure 2 llustrates the smple case of two regons: country A and the rest of the world. In WIOD we wll dstngush 40 countres and the rest of the World, but the basc outlne remans the same. For each country the use rows are splt nto two separate rows, one for domestc orgn and one for foregn orgn. In contrast to the natonal IOT for country A t s now clear from whch foregn ndustry the mports orgnate, and how the exports of country A are beng used by the rest of the world, that s, by whch ndustry or fnal end user. The WIOT contans smlar nformaton for all other countres n the table. Ths combnaton of natonal and nternatonal flows of products provdes a powerful tool for analyss of global producton chans and ther effects on employment, value added and nvestment patterns and on shfts n envronmental pressures. Whle natonal IO tables are routnely produced by NSIs, WIOTs are not as they requre a hgh level of harmonsaton of statstcal practces across countres. In the followng sectons we outlne our constructon of a WIOT. 3. World Input-Output Table (WIOT): Constructon and sources In ths secton we outlne the constructon of the WIOT and dscuss the underlyng data sources. In short, we derve tme seres of natonal supply and use tables (s) and lnk these across countres through detaled nternatonal trade statstcs to crease so-called nternatonal s. These nternatonal s are used to construct the symmetrc world nput-output table whch s product or ndustry based, dependng on the set of alternatve assumptons used. In Secton 3.1 we provde an overvew, whle n secton 3.2 we delve nto methodologes and data sources used. For an elaborate dscusson of constructon methods, practcal mplementaton and detaled sources, see Erumban et al. (2010, forthcomng). 3.1 Bref overvew of WIOT constructon The constructon of our WIOT has two dstnct characterstcs when compared to e.g. the methods used by GTAP, OECD and IDE-JETRO. Frst, we rely on natonal supply and use tables (s) rather than nput-output tables as our basc buldng blocks. Second, to ensure meanngful analyss over tme, we start from output and fnal consumpton seres gven n the natonal accounts and benchmark natonal s to these tme-consstent seres. s are a more natural startng pont for ths type of analyss as they provde nformaton on both products and (usng and producng) ndustres. A supply table provdes nformaton on products produced by each domestc ndustry and a use table ndcates the use of each product by an ndustry or fnal user. The lnkng wth nternatonal trade data, that s product based, and soco-economc and envronmental data, that s manly ndustry-based, can be naturally made n a framework. In contrast, an nput-output table s exclusvely of the product or ndustry type. Often t s constructed on the bass of an underlyng, requrng addtonal assumptons. 6

8 In Fgure 3 a schematc representaton of a natonal s gven. Compared to an IOT, the contans addtonal nformaton on the domestc orgn of products. In addton to the mports, the supply columns n the left-hand sde of the table ndcate the value of each product produced by domestc ndustres. The upper rows of the ndcate the use of each product. A must obey two basc accountng denttes: for each product total supply must equal total use, and for each ndustry the total value of nputs must equal total output value. Let S denote supply and mports, subscrpts and j denote products and ndustres and superscrpts D and denote domestcally produced and mported products respectvely. Then total supply for each product s gven by the summaton of domestc supply and mports: D = S + S (1) j j Total use (U) s gven be the summaton of fnal domestc use (F), exports (E) and ntermedate use (I) such that + U = F + E I, (2) j j The dentty of supply and use s then gven by F D + E + I, j = S + (3) j j j The second accountng dentty can be wrtten as follows D S = VA j + I j j (4) j Ths dentty ndcates that for each ndustry the total value of output s equal to the total value of nputs. The latter s gven by the sum of value added (VA) and ntermedate use of products. [Fgure 3 about here] In the frst step of our constructon process we benchmark the natonal s to tme-seres of ndustral output and fnal use from natonal account statstcs. Typcally, s are only avalable for a lmted set of years (e.g. every 5 year) and once released by the natonal statstcal nsttute revsons are rare. Ths compromses the consstency and comparablty of these tables over tme as statstcal systems develop, new methodologes and accountng rules are used, classfcaton schemes change and new data becomes avalable. These revsons can be substantal especally at a detaled ndustry level. By benchmarkng the s on consstent tmeseres from the NAS, tables can be lnked over tme n a meanngful way. In the next secton we provde further nformaton about the extrapolaton and lnkng procedures. 7

9 8 In a second step, the natonal s are combned wth nformaton from nternatonal trade statstcs to construct what we call nternatonal s. Bascally, a splt s made between use of products that were domestcally produced and those that were mported, such that E E E F F F j I I I D D j D j j + = + = + =,,,, (5) Ths breakdown must be made n such a way that total domestc supply equals use of domestc producton for each product: S E F I j D j D D j D j = + +,, (6) and total mports equal total use of mported products E F I j j = + +, (7) The outlne of an nternatonal s gven n Fgure 4. [Fgure 4 about here] So far we have only consdered mports wthout any geographcal breakdown. To study nternatonal producton lnkages however, the country of orgn of mports s mportant as well. Let k denote the country from whch mports are orgnatng, then an addtonal breakdown of mports s needed such that E F I k k k k k k k j k j = = + +,,,,, (8) As a fnal step the nternatonal s for each country are combned nto a world nput-ouput table, as gven n Fgure 2. Ths transformaton step requres addtonal assumptons that are spelled out n more detal below. 3.2 Implementaton and sources In ths secton we outlne the varous steps taken n the constructon process of the WIOT. These steps are summarsed n Fgure 5 that llustrates the basc data sources used and the varous transformatons appled. Four phases can be dstngushed:

10 A. Raw data collecton and harmonsaton B. Constructon of tme-seres of s C. Breakdown of mport and domestc producton n Use table D. Constructon of WIOT [Fgure 6 about here] A. Raw data collecton and harmonsaton Three types of data are beng used n the process, namely natonal accounts statstcs (NAS), supply-use tables (s) and nternatonal trade statstcs (ITS). Importantly, ths data must be publcly avalable such that users of the WIOT are able to trace the steps made n the constructon process. oreover, offcal publshed data s more relable as checkng and valdaton procedures at NSIs are more thorough than for data that s ad-hoc generated for specfc research purposes. The data s beng harmonsed n terms of ndustry- and product-classfcatons both across tme and across countres. The WIOD classfcaton lst has 59 products and 35 ndustres based on the CPA and NACE rev 1 (ISIC rev 2) classfcatons. The product and ndustry lsts are gven n Appendx Tables 1 and 2. Ths level of detal has been chosen on the bass of ntal dataavalablty exploraton and ensures a maxmum of detal wthout the need for addtonal nformaton that s not generated n the system of natonal accounts. The 35-ndustry lst s dentcal to the lst used n the EUKLES database wth addtonal breakdown of the transport sector as these ndustres are mportant n lnkng trade across countres and n the transformaton to alternatve prce concepts (from purchasers to basc prces, see below). 2 Hence WIOD can be easly lnked to addtonal varables on nvestment, labour and productvty n the EU KLES database (see O ahony and Tmmer 2009). The product lst s based on the level of detal typcally found n s produced by European NSIs, followng Eurostat regulatons. It s more detaled than the ndustry lst to allow for a maxmum lnk wth the very detaled product data from the ITS. It s well-known that non-survey methods to splt up mports such as used n WIOD (see below) are best appled at the lowest level possble. To arrve at a common classfcaton, correspondence tables have been made for each natonal brdgng the level of detal and classfcatons n the country to the WIOD classfcaton. Ths nvolved aggregaton and sometmes dsaggregaton based on addtonal detaled data. Whle for most European countres ths was relatvely straghtforward, tables for non-eu countres proved more dffcult. Natonal s were also checked for consstency and adjusted to common concepts (e.g. regardng the treatment of FISI and purchases abroad). Undsclosed cells due to confdentalty concerns were mputed based on addtonal nformaton. The adjustments and harmonsaton are descrbed n more detal on a country-by-country bass n Erumban et al. (2010). 2 In addton, n WIOD the EUKLES ndustry s splt nto textles and wearng apparel (17-18) and footwear (19) because of the large amount of nternatonal trade n these ndustres. 9

11 B. Constructon of tme-seres of s As dscussed above, natonal s are only nfrequently avalable and are often not harmonsed over tme. Therefore they are benchmarked on consstent tme-seres from the NAS n a second step. From the NAS data tme seres on output and value added by ndustry, total mports and total exports and fnal use by use category are derved. Ths data s used to generate tme seres of s usng the so-called -RAS method (Temurshoev and Tmmer 2009). Ths method s akn to the well-known b-proportonal updatng method for nput-output tables known as the RAS-technque. Ths technque has been adapted for updatng s. Tmeseres of s are derved for two prce concepts: basc prces and purchasers prces. Basc prce tables reflect the costs of all elements nherent n producton borne by the producer, whereas purchasers prce tables reflect the amount pad by the purchaser. The dfference between the two are the trade and transportaton margns and net taxes. Both prce concepts have ther use for analyss dependng on the type of research queston. Supply tables are always at basc prce and often have addtonal nformaton on margns and net taxes by product. The use table s typcally at a purchasers prce bass and hence needs to be transformed to a basc prce table. The dfference between the two tables are gven n the so-called valuaton matrces (Eurostat 2008, Chapter 6). These matrces are typcally not avalable from publc data sources and hence need to be estmated. In WIOD we dstngush 4 types of margns: automotve trade, wholesale trade, retal trade and transport margns. The dstrbuton of each margn type vares wdely over the purchasng users and we use ths nformaton to mprove our estmates of basc prce tables. C. Breakdown of mport and domestc producton n Use table The next step s a breakdown of the use table nto domestc and mported orgn. As margns are only generated by the domestc ndustres, a breakdown of the use table at basc prce s made. Ideally one would lke to have addtonal nformaton based on frm surveys that nventory the orgn of products used, but ths type of nformaton s hard to elct and only rarely avalable. We use a non-survey mputaton method that reles heavly on a classfcaton of detaled products n the ITS nto varous use categores. Our basc data s blateral mport flows between all our countres at a 6-dgt product level from WITS. Based on the detaled product descrpton n the harmonsed system (HS) used n WITS, products are allocated to four use categores: ntermedate, consumpton, nvestment or mx. Ths resembles the well-known Classfcaton by Broad Economc Categores (BEC) but s much more fne-graned as BEC s only based on 3- dgt product groups. oreover, BEC only covers goods and not servces whch have become ncreasngly mportant n nternatonal trade. Based on our alternatve use classfcaton, we allocate mports across use categores n the followng way. Let m, ndcate the share of use categores l (ntermedate, fnal consumpton or l k nvestment) n mports of product by a partcular country from country k defned as 10

12 ~ l, = such that m k 1 (9) l l, k m k ~ where ~ l, k k l, = s the total value from all 6-dgt products that are classfed by use category l and WIOD product group mported from country k, and ~ the total value of WIOD product group mported by a country. These shares are derved from the blateral nternatonal trade statstcs and appled to the total mports of product as gven n the tmeseres to derve mported use categores as follows: I, j, k = m I, k I U, j FC j INV FC INV F, k = m, k + m, k (10) U U where FC denotes fnal consumpton and INV gross fxed captal formaton, together makng up fnal use (F). Note that we use shares derved from the ITS rather than the actual values. There are dscrepances between the mport values recorded n the Natonal Accounts on the one hand, and n nternatonal trade statstcs on the other. Some of them are due to conceptual dfferences, and others due to classfcaton and data collecton procedures (see extensve dscusson n Guo, Web and Yamano 2009). As we rely on NAS as our benchmark tochoose to apply shares from the trade statstcs to the NAS seres. Fnally, we derve the use of domestcally produced products as the resdual by subtractng the mports from total use as follows: I F E D D = I k k I F E, k, k D, j, j, j, k, k = F = E j (11) Note that our approach dffers from the standard proportonalty method popular n the lterature and appled e.g. by GTAP. In those cases, a common mport proporton s used for all cells n a use row, rrespectve the user. Ths common proporton s smply calculated as the share of mports n total supply of a product. We fnd that mport proportons dffer wdely across use categores and mportantly, they dffer also by country of orgn. Our detaled blateral approach ensures that ths type of nformaton s reflected n the nternatonal s and WIOT. D. Constructon of WIOT As a fnal step, nternatonal s are transformed nto a world nput-output table. IO tables are symmetrc and can be of the product-by-product type, descrbng the amount of products needed to produce a partcular good or servce, or of the ndustry-by-ndustry type, descrbng the flow of 11

13 goods and servces from one ndustry to another. In case each product s only produced by one ndustry, the two types of tables wll be the same. But the larger the share of secondary producton, the larger the dfference wll be. The choce for between the two depends on the type of research questons. any foreseen applcatons of the WIOT, such as those descrbed n the next sectons, wll rely heavly on ndustry-type tables as the addtonal data, such as employment or nvestment, s often only avalable on an ndustry bass. oreover, the ndustry-type table retans best the lnks wth natonal account statstcs. An IOT s a construct on the bass of a at basc prces plus addtonal assumptons. We use the so-called fxed product-sales structure assumpton statng that each product has ts own specfc sales structure rrespectve of the ndustry where t s produced. Sales structure here refers to the proportons of the output of the product n whch t s sold to the respectve ntermedate and fnal users. Ths assumpton s most wdely used, not only because t s more realstc than ts alternatves, but also because t s a relatve smple mechancal procedure. It does not generate any negatves n the IOT that would requre manual rebalancng. Applcaton of manual ad-hoc procedures would greatly reduce the tractablty of our methods. Chapter 11 n the Eurostat handbook (Eurostat 2008) provdes a useful and extensve dscusson of the transformaton of s nto IOTs, ncludng a mathematcal treatment. In a frst step the nternatonal s for all countres are combned nto a world. Bascally, the natonal tables are stacked and reordered to resemble a standard supply-use table. The framework for the world s gven n Fgure 6. Subsequently, usng the fxed productsales structure, the world s transformed nto the WIOT gven n Fgure 2. To ensure consstency between blateral flows of mports and exports, exports are defned as mrror flows from mports. ore specfcally, exports of product from say country A to country B are assumed to be equal to the mports of ths product by B from A. [Fgure 6 about here] The full WIOT wll contan data for forty countres covered n the WIOD. Includng the bggest countres n the world, ths set covers about 85 per cent of world GDP. Nevertheless to complete the WIOD and make t nternally consstent, also a regon called the Rest of the World (RoW) needs to be added. Ths regon proxes for all other countres n the world. The RoW needs to be modelled due to a lack of detaled data on nput-output structures. Exports from the RoW are smply the mports by our set of countres not orgnatng from ths set. Imports by the ROW are defned resdually to ensure that exports from all countres equal the mports by all countres. Producton and consumpton n the ROW wll be modelled based on totals for ndustry output and fnal use categores from the UN Natonal Accounts, assumng an nput-output structure equal to that of Inda. Also, at a later stage we wll add n a separate ol-producng regon that wll be useful n partcular n envronmental applcatons. 12

14 4. Basc data sources Sources for WIOT As descrbed n the prevous secton, the constructon of the WIOT requres three type of data: natonal s, Natonal Accounts tmeseres on ndustry output and fnal use, and nternatonal trade data. In Table 1 we provde an overvew of the s used n WIOD. For some countres full tme-seres of s are avalable, but for most countres only some or even one year s avalable. Ths s ndcated n the table. In some cases s for a partuclar year were avalable, but have not been used as they contaned too many errors or nconsstences to be useful. Also, for some non-eu countres s are not avalable, but only IOTs. For these countres a transformaton from IOT to has been made by assumng a dagonal supply table at the product and ndustry level of the orgnal natonal table whch s often more detaled than the WIOD lst. Table 1 provdes detals about the sze of the orgnal s and IOTs and ther prce concept. The tables have been sourced from publcly avalable data from Natonal Statstcal Insttutes and for many EU countres from the Eurostat nput-output database. 3 s mght be avalable for varous years, but that does not mply that they are also comparable over tme as revsons mght have taken place n the Natonal Accounts, whle the hstorcal s have not revsed. Therefore to lnk the s over tme, Natonal Accounts statstcs are used. Data for was collected for the followng seres: total exports, total mports, gross output at basc prces by 35 ndustres, total use of ntermedates by 35 ndustres, fnal expendture at purchasers prces (prvate and government consumpton and nvestment), and total changes n nventores. Ths data s avalable from Natonal Statstcal Insttutes and OECD and UN Natonal Accounts statstcs. Internatonal trade data s derved from the World Integrated Trade Soluton (WITS) database from the Worldbank. Data on export and mport values n ths database are based upon the Unted Naton Statstcal Dvson (UNSD) Commodty Trade (COTRADE) Data Base that contans exports and mports by commodty and partner country. Our basc data are blateral mport flows between all our countres at a 6-dgt product level (Harmonsed System, HS) from WITS. Alternatvely, we could have reled on export flow data. It s well-known that offcal blateral mport and export trade flows are not consstent and hence ths choce would make a dfference. Followng most other studes, we choose to use mports flows as these are generally seen as more relable than export flows. As not all countres report trade at 6-dgt detal, varous cells have been mputed by means of mrror-statstcs on exports and other estmaton technques. Statstcs for trade n goods are well-developed, n contrast to trade n servces. Although servces trade s takng an ncreasng share of global trade flows, statstcs are only rough and hard to reconcle across the varous sources. One partcular challenge s to allocate the statstcs based on Balance of Payments codes to the varous products n the WIOD lst. The approach taken n constructng the blateral trade data for WIOD s extensvely descrbed n Steher et al. (2010). 3 These can be found at 13

15 In addton to a WIOT, the WIOD also ncludes soco-economc and envronmental sattelte accounts. In Fgure 7 the conceptual framework of the extended natonal s gven. Value added s broken down nto the compensaton for the producuton factors labour and captal. 4 In addton statstcs on energy use, greenhouse-gas and other ar emssons, and resource use by ndustry and fnal users are collected. [Fgure 7 about here] Soco-economc accounts The soco-economc accounts contan data on detaled labour and captal nputs for all 35 ndustres. Ths ncludes data on hours worked and compensaton for three labour types (low-, medum- and hgh-sklled labour) and data on captal stocks and compensaton for 8 asset types: 3 ICT assets (software, computer and telecommuncaton equpment) and 5 non-ict assets (resdental buldngs, non-resdental structures, transport equpment, other non-ict machnery and equpment, and other assets). Labour servce nput s based on seres of hours worked and wages of varous types of labour. These seres are not part of the core set of natonal accounts statstcs put out by NSIs; typcally only total hours worked and wages by ndustry are avalable from the Natonal Accounts. For these seres addtonal materal has been collected from employment and labour force statstcs. For each country covered, a choce was made of the best statstcal source for consstent wage and employment data at the ndustry level. In most cases ths was the labour force survey (LFS), whch n some cases was combned wth earnngs surveys when wages were not ncluded n the LFS. In other nstances, an establshment survey, or socalsecurty database was used. Care has been taken to arrve at seres whch are tme consstent, as most employment surveys are not desgned to track developments over tme, and breaks n methodology or coverage frequently occur. Labour compensaton of self-employed s not regstered n the Natonal Accounts, whch as emphassed by Krueger (1999) leads to an understatement of labour s share. We make an mputaton by assumng that the compensaton per hour of self-employed s equal to the compensaton per hour of employees. Ths s especally mportant for ndustres whch have a large share of self-employed workers, such as agrculture, trade, busness and personal servces. Also, we assume the same labour characterstcs for selfemployed as for employees when nformaton on the former s mssng. These assumptons are made at the ndustry level. For the breakdown of value added, compensaton for each captal asset s needed. Captal nput seres by ndustry are generally not avalable from the Natonal Accounts. At best, captal stocks are estmated for aggregate nvestment wthout dstngushng varous asset types. Captal compensaton s gven by multplyng stocks wth rental prces. The rental prce of each asset conssts of a nomnal rate of return, deprecaton and captal gans (Jorgenson and Yp, 1991). 5 4 Currently, we use the expost approach to captal measurement such that labour and captal compensaton wll exhaust value added. In a later stage we wll use the ex-ante or exogenous approach such that a resdual value remans whch s called proft (Schreyer, 2009). 5 Taxes have not been ncluded due to a lack of data. Also, the assets do not cover land and nventores. 14

16 The nomnal rate of return s determned ex-post as t s assumed that the total value of captal servces for each ndustry equals captal compensaton. Captal compensaton s derved as gross value added mnus labour compensaton. Ths procedure yelds an nternal nomnal rate of return that exhausts captal ncome and s consstent wth constant returns to scale. The nomnal rate of return s the same for all assets n an ndustry, but s allowed to vary across ndustres. For each ndvdual asset, stocks have been estmated on the bass of nvestment seres usng the perpetual nventory method (PI) wth geometrc deprecaton profles. Deprecaton rates dffer by asset and ndustry, but have been assumed dentcal across countres. The basc nvestment seres by ndustry and asset have been derved from captal flow matrces and benchmarked to the aggregate nvestment seres from the Natonal Accounts. Although the ESA provdes a classfcaton of captal assets, t s not always detaled enough to back out nvestment n nformaton and communcaton equpment. Addtonal nformaton has been collected to obtan nvestment seres for these assets, or assumptons concernng hardware-software ratos have been employed. When the deflator for computers dd not contan an adjustment for qualty change, a harmonsed deflator based on the Unted States deflator has been used as suggested by Schreyer (2002). The EU KLES database provdes ths data for a large set of OECD countres (see O ahony and Tmmer 2009 provde a more detaled descrpton of the methods used. For non-oecd countres addtonal data has been collected and prepared followng the same harmonsaton and constructon procedures as used n the EU KLES database. Erumban, Gouma, de Vres and Tmmer (2010) provdes addtonal detal. Envronmental accounts 6 The core of the envronmental database conssts of energy and ar emsson accounts. Energyrelated ar emssons s estmated usng energy accounts and technology-specfc emsson factors. A large part of the ar emssons resultng n the mpact categores covered n WIOD (global warmng, acdfcaton and tropospherc ozone formaton) are orgnated from gases emtted n energy-use processes. These emssons are complemented wth non-energy related (process) emssons where approprate, usng nventory data from UNFCCC natonal reports (NIR Natonal Inventory Reports) and CLRTAP (Conventon on Long Range Transboundary Ar Polluton). Energy accounts are compled usng IEA extended energy balances as a startng pont, achevng the specfcaton of energy accounts usng addtonal nformaton to brdge between terrtory and resdence prncples (bunkerng and nternatonal transport, toursm, defence, embasses) and to allocate IEA accounts to the target classfcaton and accountng concepts (dstrbuton of transport actvtes and autoproduced electrcty among ndustres). The very frst step n dervng energy accounts from nternatonal energy balances, as provded by IEA, s to establsh a correspondence-key lnkng energy balance tems and NACE entres plus households. Some of the energy balance tems can be drectly lnked to the producton of certan NACE 6 Ths text s based on the detaled documentaton on the envronmental accounts by Vllaneuva, Genty and Neuwahl (2010) from Insttute for Prospectve Technologcal Studes (IPTS) n Sevlle. IPTS, an EC s jont research center, s responsble for the envronmental accounts n the WIOD project. 15

17 enttes, but n some cases the energy balance tem s related to more than one ndustry. For nstance, the energy balance tem road transport needs to be dstrbuted over all ndustres plus households. Lkewse, the energy balance tem commerce and publc servces needs to be dstrbuted over a number of servces. Losses are also a relevant part of the energy accounts and an mportant element n the assessment of energy effcency. All losses are recorded and allocated to the suppler. Ar emssons are estmated from energy accounts. The general approach mples the use of actvty data and emsson factors, followng the general formula: E = AR EF. The emsson (E) s obtaned by multplyng a certan trggerng actvty (AR: actvty rate) by a certan emsson factor (EF). Such factors embed the concept of a lnear relatonshp between the actvty data and the actual emssons. Several techncal gudance documents provde such emsson factors, n partcular those prepared for the complaton of natonal emsson nventores under nternatonal conventons (UNFCCC, CLRTAP). Addtonally, two very mportant secondary sources of nformaton for emsson factors are used: the results of the FP6 project EXIOPOL and the EDGAR nformaton system. Actvty data wll concern the use of energy, broken down nto energy commodtes and sectors as reported n IEA statstcs. Ar emsson data not related to energy consumpton (e.g. CH4 emssons) wll be collected from nventores to complement the energy-based emssons. The substances ncluded n the database comprse the ar emssons lnked drectly to the three envronmental mpact categores covered, namely: Greenhouse gas emssons to ar (CO2, N2O, CH4, HFCs, PFCs, SF6), needed to derve Global Warmng Potentals Emssons of CFCs, Halons, ethyl Bromde CH3Br, and HCFCs, needed to derve Ozone Depleton Potentals, and Emssons of acdfyng substances to ar (NOx, SOx, NH3), needed to derve Acdfcaton Potentals ore detaled nformaton on the constructon of the envronmental accounts can be found n Vllaneuva, Genty and Neuwahl (2010). 5. Applcatons of the WIOD database Ths secton descrbes two applcatons of the WIOD database. In Secton 5.1, the world nputoutput table s combned wth soco-economc accounts to measure the factor content of trade. In Secton 5.2, the world nput-output table s combned wth envronmental accounts to measure greenhouse gas emssons as a result of producton and consumpton. 5.1 The factor content of trade Trade has become ncreasngly fragmented, wth producton at dfferent stages performed across multple countres. At each stage n the producton process, value s added to a product. The case 16

18 study of the Apple Pod offers an llustratve example of fragmentaton n producton (Dedrck et al. 2008). The Pod s assembled n Chna and sold at the factory gate for $144, whch s reflected n export statstcs from Chna. However, the export of the Pod from Chna ncludes about $100 n mported Japanese value added (e.g. the hard drve, dsplay, and battery), and $15 of mported U.S. value added (e.g. the processor, controller, and memory). Actually, Chna only adds $4 n value added. In addton, the producton factors used n the varous stages of producton dffer across countres. For example, the producton of the processor n the U.S. requres mostly sklled labour, whle assembly of the Pod components n Chna s performed manly by low-sklled workers. So, whle the nternatonal trade statstcs suggest $144 of hgh-tech exports from Chna for each exported I-pod, the value actually added n Chna s only small and contans barely sklls. An analyss of global value chans wuold reveal such nformaton as t ndcates for a product the value added by certan producton factors n varous countres. Ths requres accountng for trade n ntermedate nputs as wll be done n ths secton. Lterature on the factor content of trade s boomng. For example, authors use the GTAP database to test the Heckscher-Ohln-Vanek predctons of comparatve advantage (e.g. Remer (2006); Johnson (2008); Trefler and Zhu (2010)). Other authors am to measure the factor content of trade for specfc countres (e.g. Feenstra and Hong (2007) for Chna, see also de Backer and Yamano (2007). Our applcaton contrbutes to ths lterature, because t uses a tme-seres nputoutput database. Prevous studes examned the factor content for a partcular moment n tme. The tme-seres perspectve n WIOD allows us to examne changes n the factor content due to ncreasng fragmentaton and globalzaton. In addton, the soco-economc accounts allow a rcher characterzaton of the producton factors used by ndustres n creatng value added. Prevous studes dstngushed captal and labor at best. However, as the Pod example llustrates, more detal n labor s needed as well. Assembly actvtes or producton of hgh-tech ntermedate nputs requre very dfferent sklls. Takng these sklls nto account provde a rcher descrpton of the factor content of trade. Data Two datasets are consdered, namely the world nput-output table and the soco-economc accounts as descrbed n the prevous secton. The current provsonal world nput-output table consders Germany, Japan, the Unted States, and the rest of the world for the year Therefore, the frst rows of the table refer to Germany, whereas Japan, the U.S. and the rest of the world follow subsequently. The lay-out of ths table s shown n Fgure 2. The world nput-output table and the soco-economc accounts dstngush 35 ndustres (so the frst 35 rows refer to German ndustres). Values are n euros usng exchange rates for converson of local currences. At a later stage relatve prces (PPPs) wll be used nstead. Producton factors n the socoeconomc accounts are measured as value shares n gross output. In the next verson of ths paper, we plan to ntegrate the other countres covered by WIOD n the world nput-output table and consder the tme perod 1995 to Also, by usng ndustry-level deflators, the tables wll be put n prevous year prces and producton factors wll be measured n volumes. 17

19 ethod The approach follows the methodology outlned n Remer (2006) that closely resembles the technques used n the nput-output lterature. 7 Let n=1,,n ndex goods and servces, and c=1,,c ndex countres. Defne the vector of net output (y C ) as: y C = x C - A x C, (12) where y C s a net output vector (NC x 1), x C s a (NC x 1) gross output vector 8, and A s the world nput-output matrx wth ntermedate nput shares of dmenson (NC x NC). The matrx A descrbes how a gven producte s produced (or delvered) wth dfferent combnatons of factors n dfferent countres, and s used n the producton of tself and other products around the world. The net output measures the amount of products avalable for fnal use n the economy, or for exports. Let t C be a (NC x 1) vector representng the exports and mports of goods and servces by a country for ntermedate or fnal use. Let the (NC x 1) vector d C refer to demand for fnal domestc use. For example, the frst element of d GER ndcates the amount of Agrcultural products produced n Germany and demanded by German fnal users; the 36 th element ndcates the amount of Agrcultural products produced n Japan and demanded by Germany for fnal use and so on.. Trade n goods and servces are measured by: t C = y C - d C. (13) If net output s bgger than domestc demand, the product wll be exported (t s postve for ths product). Conversely, f demand s hgher than net output, the product needs to be mported (the element n t s negatve). To mpute the factor content of trade, consder F, a (F x NC) drect factor nput matrx. Here, F has fve rows, snce fve producton factors are dstngushed. Ths matrx consders country-specfc drect factor nputs. An element n ths matrx ndcates the share n gross output of a producton factor used drectly by the country to produce a gven product. For example, the frst element ndcates the value of ICT-captal used by Germany n producton of one euro of output n the agrcultural sector. The elements are drect factor nputs n the ndustry, because they do not account for producton factors emboded n ntermedate nputs used by ths ndustry. Intermedate nputs are produced as well, requrng captal and labour and other ntermedate nputs. These ntermedate also need to be produced, and so forth. Summng all nputs yelds the total producton that s drectly and ndrectly requred to produce for fnal demand. Ths s gven by multplyng a gven vector of fnal demand wth the so-called Leontef nverse. In matrx notaton, the Leontef nverse s (I A) -1. For ths reason a (F x NC) total factor nput matrx F * s mputed by: 7 See also Detzenbacher and ukhopadhyay (2007). 8 The vector x GER for Germany has postve values of gross output for the frst 35 rows and zeros everywhere else. The vector x JPN for Japan has zeros on the frst 35 rows, postve values of gross output for row 36-70, and zeros everywhere else, and so on. 18

20 F * = F (I - A) -1, (14) where I s an (NC x NC) dentty matrx. A typcal element n F * ndcates the amount of the world producton factor f, emboded n a country s product n. The net factor content of trade (fac C ) for a country (of dmenson F x 1) s then measured by: fac C = F * t C. (15) It gves the dfference between the value of a producton factor both drectly and ndrectly emboded n exports from C and the amount of the same producton factor emboded n the mports from all other countres. By approprate modfcaton of the F* matrx t s possble to dstngush between the regonal orgn of producton factors. E.g. f one s nterested n the emboded German labour and captal, all non-german elements n F* should be set to 0. Results We use equaton (15) to mpute the factor content of trade. It should be stressed that these results are provsonal and subject to change once the world nput-output matrx A s extended wth other countres and the F matrx ncludes more detaled soco-economc nformaton for the remanng countres n WIOD. The rest of the world s large n the current applcaton, and therefore affects the results. The countres n WIOD cover over 90% of world GDP. Therefore, f the full table s consdered, the rest of the world wll shrnk n sze, as wll ts nfluence on the results. 9 Prelmnary results for the Unted States n 1995 are shown n fgure 8. For each producton factor, we dstngush the factor content n total export and n total mports. The net factor content of trade s the factor content of exports mnus mports. Importantly, exports n ths fgure refer to exports of US producton factors, both drectly and ndrectly through the use of ntermedates n the producton for exports. Imports refer to the mports of emboded foregn producton factors and they do not nclude US factors of producton. [nsert fgure 8 about here] The results suggest that the U.S. s a net exporter of ICT captal, but a net mporter of non-ict. The bggest net exports though are n medum- and hgh-sklled labour. Only n low sklledlabour the US s a large net mporter. Summed over all factors, the net factor content of trade s negatve, reflectng the net trade balance n the US n However, the net trade balance s more negatve than the net factor content of trade balance as we move to a value-added measure of trade. A relatvely hgh share of exported value added returns to the US emboded n mported fnal goods (Powers et al. 2010, and the Pod example gven above). Note that our measure of the 9 We plan to use nformaton on world GDP from the UN natonal accounts to construct a table for the rest of the world. 19