INSTITUTE OF BEHAVIORAL SCIENCE! RESEARCH PROGRAM ON POLITICAL and ECONOMIC CHANGE! Unversty of Colorado at Boulder Boulder CO 80309-0484 WORKING PAPER PEC004-0004! The Costs of Complyng wth Foregn Product Standards for Frms n Developng Countres: An Econometrc Study Keth E. Maskus Tsunehro Otsuk John S. Wlson May 19, 004 Research Program on Poltcal and Economc Change Workng Paper PEC004-0004
The Costs of Complyng wth Foregn Product Standards for Frms n Developng Countres: An Econometrc Study Keth E. Maskus, Unversty of Colorado at Boulder Tsunehro Otsuk, The World Bank John S. Wlson, The World Bank Abstract: May 19, 004 Standards and techncal regulatons exst to protect consumer safety or to acheve other goals. However, such regulatons can rase set-up costs and producton costs sgnfcantly. We develop econometrc models to provde the frst estmates of the ncremental producton costs of enterprses n developng natons n conformng to standards mposed by maor mportng countres. We use frm-level data generated from 16 developng countres through the World Bank Techncal Barrers to Trade Survey Database. Our translog cost functon estmaton suggests that standards ncrease short-run producton costs by requrng addtonal labor and captal. A one-percent ncrease n one-tme complance cost n mportng countres rases producton costs by 0.06 percent, a statstcally sgnfcant ncrease. Whle the mpact s small, t does mply that standards and techncal regulatons may consttute non-tarff trade barrers. JEL Codes: F1, L15 Key Words: Standards, regulatons, complance, translog costs Contact Informaton: John S. Wlson, The World Bank, 1818 H Street N.W., Washngton DC 0433, 0-473-065, swlson@worldbank.org; Tsunehro Otsuk, The World Bank, 1818 H Street N.W., Washngton DC 0433, 0-473-8095, totsuk@worldbank.org; Keth E. Maskus, Department of Economcs, UCB 56, Unversty of Colorado, Boulder CO 80309, 303-49-7588, maskus@colorado.edu.
1. Introducton Techncal regulatons, such as product certfcaton requrements, performance mandates, testng procedures, conformty assessments, and labelng standards, exst to ensure consumer safety, network relablty, or other goals. However, such regulatons can sgnfcantly rase setup and producton costs. In consequence, they may act as mpedments to competton by blockng frm entry and expanson wthn a country or, as s frequently alleged by exportng concerns, as barrers to trade. 1 Indeed, there has been a rsng use of techncal regulatons as nstruments of commercal polcy n the unlateral, regonal, and global trade contexts (Maskus and Wlson, 001). As tradtonal barrers to trade have fallen, these non-tarff barrers have become of partcular concern to frms n developng countres, whch may bear relatvely larger costs n meetng ther requrements than ther counterparts n developed natons. Developng countres are typcally standards takers rather than standards makers snce, at the natonal level, developng ther own regulatons tends to be more costly than adoptng those of the maor markets (Stephenson, 1997). At the frm level, complyng wth dfferng standards n such maor export markets as the European Unon (EU), the Unted States, and Japan can add costs and lmt export compettveness. These costs assocated wth foregn standards and techncal regulatons may be borne publcly and prvately. But developng countres typcally have nether the publc resources requred to provde natonal laboratores for testng and certfcaton nor the capablty for collectve acton to rase ther standards. As a result, a sgnfcant porton of meetng the costs of standards may be borne by ndvdual frms. 1 See the case studes n Wlson and Abola (003).
Despte the evdent mportance of ths queston, to date the mpacts of techncal standards mposed by mportng natons on the producton costs of frms n developng countres have not been studed systematcally n an econometrc framework. Quantfcaton of these effects s mportant for several reasons. Frst, t s useful to shed lght on competng clams about the effcency and cost mpacts of foregn standards and regulatons, ncludng how these rules affect labor and captal usage. To the extent that costs are ncreased or nput use s dstorted the prospects for effcent ndustral development could be mpeded. Second, the estmates should be nformatve for governments n settng domestc standards by llustratng ther potental costs. In ths context, harmonzaton wth nternatonal standards may not be optmal. Thrd, a fndng that costs are rased would support the vew that techncal regulatons may be used to lmt market access. In cases where the mportng country s regulatons may not conform to WTO oblgatons, the emprcal results could help assess the damages to the exportng country s trade benefts. Thus, nformaton on the cost mpacts could facltate the resoluton of trade dsputes (Maskus and Wlson, 001). In ths paper we develop econometrc models to estmate the ncremental producton costs of enterprses n several developng natons assocated wth conformng to standards and techncal regulatons mposed by maor mportng countres. We use frm-level data generated through the World Bank Techncal Barrers to Trade Survey Database. Our sample ncludes 159 frms n 1 ndustres located n 16 developng countres n Eastern Europe, Latn Amerca, the Mddle East, South Asa, and Sub-Saharan Afrca. We employ transcendental logarthmc cost functons to separate mpacts of ntal complance cost from tradtonal cost elements n producton. Our results suggest that the need to comply wth foregn techncal standards has a 3
sgnfcantly postve mpact. Specfcally, the elastcty of (varable) producton costs wth respect to standards and techncal regulatons s estmated to be approxmately 0.06. In Secton we provde background nformaton regardng central ssues of techncal standards, costs, and trade. In Secton 3 we specfy the econometrc model for assessng the cost effects of meetng foregn standards and techncal regulatons. In Sectons 4 and 5 we dscuss the survey data and econometrc results, respectvely. In Secton 6 we make concludng observatons.. Background In prncple, product standards play a varety of useful roles n overcomng market falures (Stephenson, 1997). For example, emsson standards oblge frms to nternalze the costs of mantanng an acceptably low degree of envronmental damage. Food safety standards ensure that consumers are protected from health rsks and deceptve practces, nformaton about whch would not ordnarly be avalable n prvate markets. For consumers, effcent and nondscrmnatory standards allow comparson of products on a common bass n terms of regulatory characterstcs, permttng enhanced competton. From the producers pont of vew, producton of goods subect to recognzed standards can acheve economes of scale and reduce overall costs. Snce standards themselves embody nformaton about techncal knowledge, conformty to effcent standards encourages frms to mprove the qualty and relablty of ther products. The terms standards and standards and techncal regulatons are used nterchangeably throughout ths paper. The WTO provdes a clear dstncton between standards and techncal regulatons; the former are voluntary and the latter are mandatory techncal requrements. In many cases standards cover mandatory techncal requrements. 4
Standards also may reduce transacton costs n busness by ncreasng the transparency of product nformaton and compatblty of products and components (Davd and Greensten, 1990). Ths s possble as techncal regulatons can ncrease the flow of nformaton between producers and consumers regardng the nherent characterstcs and qualty of products. In short, consumers can reduce uncertanty n determnng product qualty due to standardzaton of products (Jones and Hudson, 1996). Internatonal standards, n the absence of multlateral consensus on the approprate level or setup of standards, also provde common reference ponts for countres to follow so that transacton costs can be reduced. For example, n 1961 Codex Almentarus was developed as a sngle nternatonal reference pont n order to draw attenton to the feld of food safety and qualty. Smlarly, nternatonal standards developed by the Internatonal Standards Organzaton (ISO) provde a bass especally for the developng countres to choose norms that are recognzed n foregn markets. In ths regard, conformty to global standards can ncrease export opportuntes. Despte ther potental to expand competton and trade, standards may be set to acheve the opposte outcomes. In general, standards selecton could act to rase the complance costs of some frms (e.g., new entrants) relatve to other frms (e.g., ncumbents) thereby restrctng competton (Fscher and Serra, 000). Ths outcome may be most lkely n the context of nternatonal trade, where governments mght choose techncal regulatons to favor domestc frms over foregn rvals, thereby restrctng trade. Ths ssue could be partcularly problematc for small exportng frms from developng countres, for they would need to absorb the fxed costs of meetng multple nternatonal regulatons wthout enoyng domestc scale advantages. 5
Because economc theory suggests that techncal regulatons can ether enhance or mpede trade, t s unsurprsng that emprcal evdence s mxed. Some studes support the clam of an effcency-ncreasng effect. Swann et al (1996) studed the mpacts of standards on Brtsh exports and mports over the perod 1985-1991. Standards data were constructed as a smple count of the number of standards by ndustry. Ther fndngs concluded that adherence to Brtsh natonal standards tended to rase both mports and exports. Moenus (1999) found that standards shared by two countres had a postve and sgnfcant effect on trade volumes n a gravty model. Gasorek et al (199) employed a CGE approach to fnd that harmonzaton of standards n the EU would reduce trade costs by.5 percent. In contrast, the fact that regulatons can act as barrers to trade s evdent n three recent studes. Otsuk, Wlson, and Sewadeh (001) estmated the mpact of changes n the EU standard on maxmum aflatoxn levels n food usng trade and regulatory survey data for 15 European countres and nne Afrcan countres between 1989 and 1998. The results suggested that mplementaton of proposed new aflatoxn standards n the EU would reduce Afrcan exports of cereals, dred fruts, and nuts to Europe by 64% or US$ 670 mllon. Wlson and Otsuk (00) studed the mpact of pestcde standards on banana trade. The authors examned regulatory data from 11 OECD mportng countres and trade data from 19 exportng countres. The results ndcated that a ten-percent ncrease n regulatory strngency tghter restrctons on the pestcde chlorpyrfos would lead to a decrease n banana mports of 14.8 percent. In another paper Wlson, Otsuk and Maumdar (00) addressed the queston of whether crosscountry standards for maxmum tetracyclne (a wdely used antbotc) affected beef trade. They examned the effects of the tetracyclne standard on beef trade between sx mportng and 16 6
exportng countres. The results suggested that a ten-percent more strngent regulaton on tetracyclne use would cause a decrease n beef mports by 6. percent. Survey evdence also ponts to cost-rasng characterstcs of techncal regulatons. A survey by the OECD (1999) as well as the ntervews conducted by the Unted States Internatonal Trade Commsson (1998) shed some lght on the sze of standards-related costs. 3 Accordng to the OECD study, whch was based on 55 frms n three sectors n the Unted States, Japan and the Unted Kngdom, the addtonal costs of complyng wth foregn standards can be as hgh as 10 percent. The Unted States Internatonal Trade Commsson nformally ntervewed representatves of the U.S. nformaton technology ndustry. Intervew responses revealed that standards-related costs are consdered the most sgnfcant trade barrer n that sector. Overall, therefore, theoretcal models and emprcal evdence are mxed on the trade mpacts of foregn standards. However, the emprcal studes undertaken to date take an ndrect, and potentally msleadng, approach to understandng the cost mpacts of regulatory requrements. Specfcally, the econometrc nvestgatons estmate reduced-form or gravty models of blateral trade n whch standards are entered as a determnant of trade flows. The survey evdence s nformatve but fals to ncorporate the responses drectly nto a well-specfed cost functon. Thus, a sgnfcant omsson n ths lterature s that none of these studes has taken a systematc and parametrc approach to estmatng the actual cost mpacts of complyng wth nternatonal standards. It s of consderable nterest to study the extent to whch varable producton costs are rased by these complance needs and whether such complance efforts have mpacts on factor demand wthn frms. Ths s the task to whch we turn next. 3 See the dscusson n Maskus, Wlson, and Otsuk (001). 7
3. Modelng the Cost Effects of Standards A full accountng of the mplcatons of a frm s decson to comply wth standards requres close study of both the costs and benefts of dong so. Our focus here s strctly on the supply sde and we leave asde the demand for complance. Thus, our am s to provde an ntal quantfcaton of the costs ncurred by frms n developng countres as they meet techncal regulatons requred n maor export markets. It s of consderable nterest to determne whether such cost ncreases are sgnfcant. 3.1 Cost Functon Consder a frm exportng a product to a foregn market that mandates conformty wth standard s. We assume that the frm's complance wth any domestc standard s a sunk cost and does not affect ts decson to meet the foregn requrement. In prncple the foregn standard could affect both the frm's fxed costs (e.g., by requrng product redesgn) and ts varable costs (e.g., by devotng more labor to product certfcaton). To capture ths possblty, we model complance wth the standard as a quas-fxed factor and estmate a short-run varable cost functon. 4 In ths vew, fxed costs are ncurred n nvestng n complance whle frms alter ther captal and labor usage to meet recurrng costs. Thus, our cost estmates reflect short-run equlbrum and cannot be consdered estmates of full adustment to the long run. In general, then, the cost functon for the frm s specfed as C = C( w, y; s, z) (1) 4 See Berndt and Hesse (1986), Morrson (1988), and Badulescu (003) for further dscusson. Badulescu sets out a smlar specfcaton n whch R&D s a quas-fxed nput across countres. 8
Here, w refers to a vector of factor prces, y s output, s ndcates the strngency of the foregn standard, and z s a vector of other varables affectng frm-level costs. The frm mnmzes varable costs wx, where x s the vector of varable nputs. The cost functon s assumed to have standard propertes: non-decreasng n w and y, concave n w, and homogeneous of degree one wth respect to w. Ths general cost functon has the strngency of standards and techncal regulatons, s, as an argument because dfferental standards and techncal regulatons should affect the choce of nputs for producng a gven output level. That s, frms are nformed about the techncal regulatons requred to sell ther products n foregn markets. They make nput allocaton decsons between producton actvtes n the tradtonal sense and efforts that are devoted to comply wth the standards and techncal regulatons. 3. Estmaton Models We estmate frm-level parametrc cost functons. Ths approach requres three central assumptons. The frst s that all frms, across ndustres and countres, share the same technology. Applcaton of the transcendental logarthmc (translog) functon to ndustry-level producton data across OECD countres shows that ths assumpton s unlkely to hold (Harrgan, 1997). In the most general case we should estmate frm-level fxed effects and fully flexble quadratc terms between these effects and all cost-related varables n order to permt factor bases n techncal dfferences. Unfortunately, such a specfcaton would more than exhaust the avalable degrees of freedom and s nfeasble. Thus, we nclude n vector z ndustry and country fxed effects n every specfcaton to control for dfferences n technology relatve to the 9
benchmark functon. Nonetheless, ths approach requres makng the resdual assumptons that frms wthn an ndustry wthn each country share the same cost functons and that effcency dfferences by ndustry and country are Hcks-neutral. A second problem s that estmaton of a cost functon ncorporatng ntermedate nputs requres frm-level data on prces of materals and ntermedates, whch our survey data do not provde. Accordngly, we specfy equaton (1) as the cost of producng net output, or value added, ntroducng only labor and captal as varable nputs. Thus, we assume that the valueadded cost functon s weakly separable from the aggregator for raw materals and ntermedate nputs. The weak separablty of the cost functon mples that the choce of relatve labor and captal nputs wll be ndependent of materal and ntermedate nput prces. 5 The cost functon that reflects ths technology s rewrtten as 1 1 C ( w, y; s, z) = ( C ( y, w ; s, z), C ( y, w ; s, z)), () 1 where w = { w L, w K ) and w s the vector of prces for varable nputs other than labor and captal. These subcomponents of the overall cost functon should be homogeneous of degree one n w 1 and w, respectvely, n order to be consstent wth the lnear homogenety of C n w. Thus, ths cost functon allows for each subcomponent to be estmated separately. Our goal s to estmate the elastcty of value-added cost (whch corresponds to C 1 ) wth respect to standards. Ths elastcty may be wrtten as 5 In our partcular case, the separablty condton s wrtten as w C( w, y; s, z) / w C( w, y; s, z) / w L K L( w, y; s, z) = 0, L, K or = 0, L, K. w K( w, y; s, z) 10
1 C s σ s = ln C 1 / ln s (3) 1 s C The thrd assumpton s that factor prces are exogenous to frms, permttng ther nput choces to be made endogenously. However, nspecton of our survey data shows that drect applcaton of ths assumpton to a cross-secton of frms s untenable because frms nevtably report dfferent average wage rates (or annual salares) and returns to captal. Put dfferently, drect constructon of labor and captal prces from the survey data makes use of varables that are endogenous, both n prncple and n fact. Consder, for example, the calculaton of average salary per frm, whch we defne as total payroll dvded by frm employment. Ths computaton generates fgures for annual wage rates that vary across frms wthn each country, as suggested by the summary data n Table 4. Thus, the noton that frms nsde a country, or even wthn an ndustry, face a common wage n a compettve labor market s questonable. Smlarly, we calculate an average captal prce per frm as operatng surplus (value added less payroll), dvded by the value of fxed assets. As may be seen n Table 1, these constructed prces vary across frms as well. One approach to resolvng ths dffculty would be to apply a natonal-average (or ndustry-average) salary and prce of captal to all frms. Such aggregate prces could be ustfed as exogenous to each enterprse. However, to do so would sacrfce the cross-sectonal varaton n factor prces needed to dentfy the cost functon. To cope wth ths problem we employ an nstrumental varables technque n whch we recognze that varatons n factor prces across frms depend on other characterstcs of frms (Roberts and Tybout, 1997; Bernard and Jensen, 000). Specfcally, we estmate frst-stage regressons of constructed labor and captal prces on 11
natonal-average factor prces, country and ndustry dummes, frm age (years snce foundng), and dummy varables ndcatng the structure of frm ownershp. w k L = a 0 + a 1 w k L + a w k K + Σa 3 D + Σa 4k D k + a 5 AGE k + Σa 6m D m (4) w k K = b 0 + b 1 w k L + b w k K + Σb 3 D + Σb 4k D k + b 5 AGE k + Σb 6m D m (5) Here, superscrpts,, and k refer, respectvely, to frm, ndustry, and country, whle superscrpt m refers to type of ownershp. In the data there are four types of ownershp: prvately held domestc frms, publcly traded domestc frms (ncludng domestc subsdares and ont ventures wth domestc frms), subsdares of multnatonal frms (ncludng ont ventures wth multnatonal frms), and state-owned or collectve enterprses. In prncple, age and ownershp are past decsons that should be exogenous to current employment levels. Thus, the nstrumentaton procedure should generate predcted wages that are exogenous to the secondstage cost functon estmaton. Wth these assumptons, we can develop an estmable translog cost functon. Agan, we treat the standard wth whch a frm must comply to be a quas-fxed factor and estmate a shortrun varable cost functon. The noton s that for a frm to export t must meet the requred complance cost and therefore t sets asde that component of cost before allocatng labor and captal to producton actvtes. We specfy the translog form to permt a flexble second-order approxmaton to a cost structure dependng on output, nput prces, and standards. Thus, our central specfcaton of costs for frm s as follows. 1
~ ln C N Ls = β ln y 1 yy (ln y ) ln w + β 0 z L C z n n n= 1 c= 1 y ln s + zc LK Ks β z ln w c L ln w L ln w D K D L ln w ln s dom ln w K + ε K Ly K ln w 1 LL (ln wl ) L ln y Ky ln w 1 ys ln y ln s ss (ln s ) 1 K ln y KK (ln w s K ) ln s (6) where C ~ denotes value-added (cost of labor and captal, referred to as producton cost hereafter), w L denotes the nstrumented wage rate, w K denotes the nstrumented unt prce of captal, y denotes sales as a measure of output, and s denotes the frm-specfc measure of standards. Summary data on these varables are provded n Table 1 for the estmaton sample. The varables z n and z c denote ndustry-specfc and country-specfc factors, respectvely, affectng frm costs. We capture these addtonal factors by means of ndustry and country fxed effects. For ths purpose we use the four-ndustry aggregaton lsted n Table and the 16 countres n Table 3. Our set-up cost for complance s desgned specfcally n the survey to measure cost assocated wth foregn techncal regulatons and standards. Some of the surveyed frms ndcated that t s also necessary to comply wth domestc techncal regulatons and standards n order to sell ther products n the domestc market. Because nformaton s not avalable on the cost of complyng wth domestc techncal regulatons and standards, a dummy varable ( D ) s used to control for the possble cost dfference assocated wth the domestc requrement. It takes the value one f a frm reports that t s requred to comply wth domestc techncal dom 13
regulatons and standards, and the value zero otherwse. The varableε s the error term, whch s assumed normally dstrbuted wth zero mean. Equaton (6) s the translog cost functon, whch we estmate smultaneously wth the followng equaton for the share of labor n varable costs: S = β ln w ln w ln y ln s + µ (7) L L LL L LK K Ly Ls The error term s also assumed normally dstrbuted wth zero mean and t reflects stochastc dsturbances n cost mnmzaton. We elmnate the captal-share equaton from the estmaton because t s fully determned by equatons (6) and (7) and the constrants below. Note that n wrtng these equatons we have mposed the requred symmetry n crossvarable coeffcents. Further, the lnear homogenety condton mposes the followng constrants: β L K = 1 β β = 0 (8) KK + LK β β β LL Ly Ls LK Ky β + Ks = 0 = 0 = 0 Equatons (6) and (7) are estmated ontly n an teratve three-stage least squares procedure (I3SLS), subect to the constrants n equatons (8). When one of the share equatons s dropped, the I3SLS produce s the preferred approach snce the estmators are consstent and asymptotcally effcent (Berndt and Wood 1975). The I3SLS procedure guarantees dentcal translog cost parameters rrespectve of whch share equaton s dropped. The parameters for the 14
dropped equaton can be recovered by usng the symmetry condton and the condtons n equatons (8). From equaton (6) we can determne the drect elastcty of producton costs wth respect to foregn standards as σ = β ln s, whch vares wth the level of standards. We are d s s ss nterested as well n the mpacts of the standards on factor demands. The coeffcent β Ls n the share equaton (7) measures the bas n labor use (mpact on labor share) from an ncrease n the foregn standard ( φ S ln s = β ), and lkewse for the bas n captal use, Ls L Ls ( φ S ln s = β ). In effect, the need to meet ths standard could generate an overall Ks K Ks ncrease n costs, along wth a bas n factor use toward labor or captal. Whle the drect cost elastcty s of some nterest, we can calculate the total elastcty of cost wth respect to a change n the strngency of standards, accountng for mpacts on factor use, as ~ σ S lnc ln s = β s ss ln s Ls ln wl Ks ln wk ys ln y. (9) Ths elastcty wll vary wth dfferent observatons on factor prces and output. Lkewse, we can calculate the total elastcty of scale as ~ σ y lnc ln y = β y yy ln y Ly ln wl Ky ln wk ys ln s. (10) Fnally, the Allen partal elastctes of substtuton between nputs and ( σ ) are: β + S S σ =, = L or K S + SS σ = β, = L, = K. (11) S S 15
4. Data and Varable Constructon The data used for cost estmaton are taken from a new survey undertaken by the World Bank explctly for the purpose of assessng complance costs of frms n developng countres facng techncal standards n ther potental export markets. Because the data are constructed from frm-level surveys we provde an overvew of ther development. 4.1 The World Bank Techncal Barrers to Trade Survey Data The World Bank Techncal Barrers to Trade Survey s the frst comprehensve questonnare desgned to elct nformaton from ndvdual frms n developng countres about how ther operatons are affected by foregn techncal requrements. 6 The survey was admnstered n the year 00 to 689 frms n 17 developng countres. The obectve of the survey s to obtan nformaton on the relevant standards, government regulatons, and techncal barrers to trade (TBTs) confrontng exporters from developng countres seekng to enter maor developed-country markets. The countres cover a range of economc development and export experence yet have suffcently deep agrcultural and ndustral structures to permt sectoral comparsons. Countres were selected for study n fve regons. These nclude Poland, the Czech Republc, and Bulgara (East Europe); Argentna, Chle, Panama, and Honduras (Latn Amerca); Jordan and Iran (Mddle East); Inda and Pakstan (South Asa); and South Afrca, Ngera, Uganda, Mozambque, Kenya, and Senegal (Sub-Saharan Afrca). Informaton on the number of frms ntervewed n each country s lsted n Table 3. 6 Wlson and Otsuk (003) descrbe ths survey n detal. 16
The survey also embodes a dverse sectoral composton. The maorty of frms are categorzed as manufacturng. The largest sngle ndustry s textles and apparel (46 frms) followed by raw agrcultural products (18 frms) and processed food and tobacco (4 frms; see Table ). For analytcal purposes we group the ndustres nto four broad categores, namely raw food; processed food, tobacco, drug and lquor; equpment; textles and materals. Frms were asked to provde nformaton about numerous characterstcs, ncludng product composton, age, form of ownershp, employment, payroll, value of fxed assets, ntermedate nputs, raw materals, and others. Of partcular nterest s the export orentaton of frms. The maorty of the respondent companes n the sample export at least some of ther products. The procedure for selectng frms meant that the sample conssts of frms that are ether currently exportng or are wllng to export but have chosen not to do so for some reason. The number of frms that are currently exportng s 646 or 93.6 percent of the total. The number of frms that are clearly not exportng s 43 or 6.4 percent of the total. Seventy percent of the frms n the total sample face the need to comply wth techncal regulatons (as defned n the survey) n ther export markets. Across all fve regons, 55 percent of the frms may be categorzed as the headquarters locaton of a prvately held, non-lsted company. About 0 percent are the headquarters locaton of a publcly traded or lsted company and 18 percent are subsdares or ont ventures of a domestc enterprse. About 6.5 percent are subsdares of foregn frms or ont ventures wth foregn partners. Only a small porton of frms are state-owned or collectve enterprses. 4. A Measure of Standards 17
A drect measure of the strngency of foregn standards and techncal regulatons facng ths varety of ndustres and mportng partner countres s dffcult to defne. However, the relatve ncrease n set-up cost ncurred for complyng wth these standards s a good proxy for ther strngency. One advantage of usng reported nvestment to represent strngency s that ths measure s expressed n dollar terms and therefore s comparable across ndustres and countres. In practcal terms such an aggregaton s necessary because the precse specfcatons of techncal standards facng frms vary across ndustres and cannot be meanngfully aggregated at that stage. Another advantage s that expendture for complance can be nterpreted as a quas-fxed factor, permttng us to specfy a short-run varable cost functon. Our measure of foregn standards and techncal regulatons s constructed from respondents answers to the queston summarzed n Table 1. Respondents were asked the followng queston: What are the approxmate costs of the tems below as a percentage of your total nvestment costs over the last year? As may be seen, three categores were lsted and respondents ndcated such costs wthn broad ranges. 7 To focus on ncremental nvestment as a measure of quas-fxed costs, we construct a standards-cost aggregate from the frst three categores. Weghted-average set-up costs wth regard to each category were computed by multplyng the mdpont percentage wthn each range by reported nvestment cost of each frm, yeldng a dollar fgure per category per frm. To develop the overall measure per frm we smply added these varous cost categores. Thus, to quantfy the perceved mpact of meetng foregn standards and techncal regulatons we develop a measure of ncremental contrbutons to 7 The survey also asked two questons about measures of recurrent labor costs, whch we do not employ n ths paper. 18
set-up costs arsng from addtonal plant and equpment and product redesgns (n total and for multple markets). Unfortunately, only a small number of frms responded to all three categores. Thus, to nclude only those cases wth responses n all of these categores greatly would reduce the number of observatons avalable for the regresson analyss. We therefore aggregated these standards varables by summng across the three categores, assgnng a category value of zero to frms wth mssng responses, for those frms where at least one category response was postve. Presumably, ths procedure understates the severty of such costs and should result n conservatve cost estmates. 8 Therefore, we use the ncrease n prevous year s reported nvestment cost for complance as a measure of the short-run fxed cost of standards and techncal regulatons. As shown n Table 4, the total standard cost vares from a mnmum of $357 to a maxmum of $1.3 mllon. Reported set-up costs for complance obvously are greater for larger frms. 5. Estmaton Results The frst-stage regressons to develop nstrumented labor and captal prces were run based on equatons (4) and (5). The nstruments used nclude per capta GDP, real nterest rates, frm age, country and ndustry dummes, and dummy varables ndcatng the structure of frm ownershp. Per capta GDP and real nterest rates were used to represent natonal average wage rates, and natonal average prce of captal, respectvely. We used the lendng nterest rate 8 Ths selecton procedure rases a sgnfcant concern about selectvty bas. To control for ths we ncluded n supplemental regressons a dummy varable takng on the value of 1 for frms that answered all fve categores and a value of zero otherwse. Ths made vrtually no dfference n the results. 19
avalable from the World Development Indcators. The nterest rates were adusted for nflaton as measured by the GDP deflator. These two equatons were estmated ontly usng seemngly unrelated regresson (SUR). The nstrumented wage rates and captal prces were then used n the cost functon and share equaton regressons. In the second stage a cost functon was run under alternatve specfcatons. The maxmum number of observatons ncluded n these regressons was 159. As mentoned earler, ths loss n observatons s largely due to the low response to the questons regardng complance wth the foregn standards and techncal regulatons. The translog cost functon was estmated wth the labor share equaton ontly by usng maxmum lkelhood estmaton wth terated three-stage least squares (I3SLS). The I3SLS method was used to obtan consstent estmators by guaranteeng nvarance of the estmated coeffcents of the share equatons rrespectve of whch of the share equatons s dropped (Berndt and Wood, 1975). The parameter estmates wth respect to translog models are presented n Table 5, wth standard errors reported n parentheses. In the frst specfcaton we exclude the quadratc term on standards and the cross-terms on standards, nput prces, and output. Thus, ths model tests for the noton that techncal regulatons affect costs only drectly, wthout secondary mpacts through scale and varable nputs. The second equaton contans the full translog specfcaton and s consstent wth theory. Both of these regressons employ the nstrumented factor prces from the frst stage. The thrd equaton also follows the full specfcaton but for comparson purposes uses the raw (unnstrumented) wage rates and unt prces of captal. Fnally, the fourth model s estmated under the full translog but employs a dfferent defnton of the standards varable, one that only contans the categores for one-tme product redesgn costs (excludng 0
plant and equpment nvestment). In ths case the sample sze falls to 96. Our nterest here s n seeng f the redesgn costs alone have dfferent mpacts on costs. All equatons nclude ndustry and country fxed effects. The ft of each model s good wth adusted R-squared coeffcents of around 0.9. Accordng to the procedures descrbed n Berndt and Wood (1975), we examned local concavty n nput prces and postvty of nput shares for the translog model. Our fully specfed translog cost functons were found to satsfy these condtons. The results of the translog model estmaton suggest that the sgns for the coeffcents for the lnear and quadratc terms of the wage rate and captal prce are all postve and statstcally sgnfcant. However, the sgns and sgnfcance of the coeffcents for the lnear and quadratc terms of the log of standards are mxed. In the restrcted model I, the drect coeffcent β S s postve, suggestng that costs rse wth the relatve severty of foregn standards. However, n the general models II, III, and IV both the lnear and quadratc coeffcents on standards are negatve, suggestng that the drect effect of standards s negatve or cost savng. However, such drect mpacts fal to account for the mpacts of foregn techncal regulatons through factor use and scale. We compute the total elastcty of costs wth respect to standards as n equaton (9), reportng the results n Table 6. We evaluate ths elastcty at the mean and frst and thrd quartles of standards, sales, and nput prces. It may be seen that the total elastcty of domestc costs n producng value added wth respect to varatons n foregn standards ranges from 0.055 to 0.35, dependng on the estmaton approach and sample quartle. Ths estmate s sgnfcantly postve at the mean n Model II and consstently postve and sgnfcant n Models III and IV. 1
These dfferences requre some explanaton. The hghest elastctes are regstered n Model III, n whch the varable factor prces are not nstrumented. Taken lterally, the result would suggest a quanttatvely large mpact of the severty of foregn standards on varable nput costs n exportng frms. That s, havng satsfed the fxed setup costs requred by foregn techncal regulatons, varable costs would ncrease va a large nduced ncrease n labor and captal demand. Indeed, the computed elastctes of labor and captal demand n Table 8 are hghest n ths specfcaton, suggestng that a one-percent rse n foregn standards would nduce an 0.3-percent ncrease n labor and an 0.4-percent ncrease n captal employment. However, these estmates fal to account for the endogenety between producton costs and factor prces n our frm-level data. The nstrumental varables approach n Models II and IV should offer more relable estmates. It may be seen that, usng the fuller specfcaton of standards costs n Model II, ncludng both plant and equpment charges and redesgn costs, the estmated cost elastcty n Table 6 s approxmately 0.06, whch s sgnfcantly postve only at the mean of the sample. Thus, our estmate wth the preferred econometrc approach and the larger sample suggests that ncreases n foregn standards complance costs modestly affect varable cost. Interestngly, however, the estmated total cost elastcty s consderably hgher n Model IV, whch ncorporates only the product-redesgn costs as a fxed factor. In that specfcaton the estmated elastcty s around 0.14 and s hghly sgnfcant at the sample mean. Ths fndng ndcates that the need to reorent product characterstcs to meet foregn standards adds sgnfcantly to short-run varable costs. Whle the results n Models II and IV are not strctly comparable because of the dfferent samples, ths provdes some ndcaton that t s the need to
meet foregn requrements on product characterstcs that matters rather more for sustanng export postons. As may be seen n Table 8, the need for redesgn mples nduced ncreases n demand for labor and captal of perhaps 0.1-0.15 percent. Estmates of the scale elastcty (equaton (10) are also presented n Table 6. Ths parameter measures the percentage change n varable cost wth respect to a one-percentage change n output and may be nterpreted as the rato of margnal cost to average cost. These scale elastctes range between 0.91 and 1.11. It s therefore not clear whether the average frm n our sample exhbts economes of scale or dseconomes of scale. We have assumed so far that the elastcty of costs wth respect to standards s constant across ndustres. Unfortunately, we do not have suffcent numbers of observatons to run a separate cost functon regresson per ndustry even usng the aggregated ndustres. We nstead examne the constancy of the elastcty by lettng the elastcty vary across ndustres n a pooled regresson. That s, we estmate equatons (6) and (7), ncorporatng nteracton terms between the standards varables and four aggregate ndustry dummes. Let denote th ndustry. Equatons (6) and (7) wll be rewrtten as: 3
~ lnc = β ln y 1 yy (ln y ) + + 1 β Ls 0 D ss y ln w L β D (ln s LK ln s ) ln w L ln w + + N L L ln w β β Ks z ln w K D C z n n n= 1 c= 1 K + Ly ln w K zc K ln w β z c 1 LL (ln wl ) L ln s ln y + D D dom Ky β D ys + ε ln w 1 K ln y KK ln y ln s (ln w + K ) β D s ln s (1) = ln ln ln ln (13) S L β L LL wl LK wk Ly y Ls D s + µ r r where D = 1 f = r and D = 0 f r. The ffth constrant n (8) should also be rewrtten accordngly: β = 0 where = 1,.., J (14) Ls Ks Ths revson of the equatons and a constrant permts us to compute elastctes for four aggregated ndustres, ncludng equpment, textles and materals, raw food, and processed food. The th ndustry s total elastcty of cost wth respect to standards s: σ s = β ln s ln w ln w ln y. (15) s ss Ls L Ks K ys The results for each model are presented n Table 7. There appear to be no mpacts on varable costs n processed foods, drugs, and lquors. Estmated cost elastctes are consstently postve n the other sectors and standards seem to affect varable costs especally n equpment (Model II) and textles and materal (Model IV). Table 8 dsplays the elastctes of labor and captal demand wth respect to standards. These may be defned as σ ln L / ln s = lnc / ln s ln S / ln s (16) Ls L 4
σ Ks ln K / ln s = lnc / ln s ln S K / ln s Usng the elastcty of cost wth respect to standards, evaluated at the mean, the full translog model wth nstrumented nput prces (Model II) mples that σ Ls =0.060 and σ Ks =0.056. Ths ndcates that a rse n complance set-up costs ncreases both labor and captal, wth a slghtly greater ncrease n labor demand. As noted above, these effects are larger n Model IV. The Allen partal elastctes of substtuton n Table 9 ndcate a moderate substtutablty between labor and captal ( σ KL ) n the sample. The own-elastcty estmates ndcate that labor s hghly elastc wth respect to ts own prce and that captal s much less elastc. 6. Conclusons Ths paper estmates the mpact on short-run costs of complyng wth standards and techncal regulatons requred by mportng countres by usng frm-level data on techncal barrers to trade for 16 developng countres based on the World Bank Techncal Barrers to Trade Survey Database. The translog model results ndcate that ncremental producton costs are greater for a frm confrontng more strngent standards and techncal regulatons. Usng the broader measure of standards, varable producton costs are 0.058 percent hgher when the ntal set-up cost for complance wth foregn standards s ncreased by one percent. In ths case 0.060 percent addtonal labor and 0.056 percent addtonal captal are employed. Usng the narrower cost defnton, focusng on product redesgn costs, the mpacts on varable costs are consderably hgher, at 0.13-0.14 percent, wth correspondngly hgher mpacts on varable factors. We focus on only labor and captal cost, but other types of nput costs may arse as 5
addtonal plants and producton unts wll requre addtonal raw materal, energy and ntermedate nputs. Our analyss demonstrates the possble supply response n developng country enterprses when changes n foregn standards and techncal regulatons take place. It can also be nferred how much more (less) cost s ncurred when a frm swtches between export markets that vary n the severty of standards and techncal regulatons. It s concevable that frms mght avod hgher-cost markets n lght of the mpacts on producton expendtures. The results may be cautously nterpreted as ndcatons of the extent to whch standards and techncal regulatons consttute non-tarff barrers to trade. Whle the relatve mpact on costs s small n terms of the underlyng elastcty, t could be sgnfcant for partcular frms and countres. In ths context, there s scope for assessng the damages to the exportng country s trade benefts where the mportng country s regulatons may not conform to WTO oblgatons. Polcy solutons then mght be sought by dentfyng the extent to whch subsdes or publc support programs are needed to offset the cost dsadvantage that stems from nternatonal techncal regulatons. 6
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Moenus, Johannes (000). Three Essays on Trade Barrers and Trade Volumes. Ph.D. Dssertaton. Unversty of Calforna, San Dego. Morrson, Catherne J. (1988). Quas-Fxed Inputs n U.S. and Japanese Manufacturng: A Generalzed Leontef Restrcted Cost Functon Approach. Revew of Economcs and Statstcs 70: 75-87. Otsuk, Tsunehro., John S. Wlson and Mrvat Sewadeh. (001) Savng Two n a Bllon: Quantfyng the Trade Effect of European Food Safety Standards on Afrcan Exports, Food Polcy 6: 495-514. Organzaton for Economc Development and Cooperaton. (1999). An Assessment of the Costs for Internatonal Trade n Meetng Regulatory Requrements. TD/TC/WP(99)8/FINAL, Pars: OECD. Stephenson, Sherry M. (1997) Standards, Conformty Assessment and Developng Countres, Polcy Research Workng Paper 186, The World Bank, Washngton DC. Swann, Peter, Paul Temple, and Mark Shurmer. (1996). Standards and Trade Performance: The UK Experence, Economc Journal 106: 197-1313. Unted States Internatonal Trade Commsson. (1998). Global Assessment of Standards Barrers to Trade n the Informaton Technology Industry. Publcaton 3141, Washngton, DC: USITC (November 1998). Wlson, John S. and Vctor Abola (003). Standards & Global Trade: A Voce for AFRICA. The World Bank. Washngton, DC. Wlson, John S. and Tsunehro Otsuk. (00) To Spray or Not to Spray: Pestcdes, Banana Exports, and Food Safety, Polcy Research Workng Paper 805, The World Bank, Washngton DC. Wlson, John S., Tsunehro Otsuk and Bashal Maumdar. (003). Food Safety Scare or Reasonable Rsk: Do Drug Resdue Lmts Affect Internatonal Trade n Beef? Journal of Internatonal Trade and Economc Development, forthcomng. 8
Table 1. Queston on Cost Impact of Complyng wth Foregn Standards as a Share n Total Investment (number of frms) Share of nvestment costs 1-10% 11-6- 51-76- >100% Total 5% 50% 75% 100% Addtonal plant or 6 3 14 6 3 3 10 equpment One-tme product redesgn 70 17 5 3 1 0 96 Product redesgn for each 57 15 4 4 0 0 80 market Table. Industres n the Sample Regon Country Count Raw food Raw agrcultural and meat products 18 Subtotal 18 Processed food, tobacco, Processed food, tobacco, drug and lquor drug and lquor 4 Subtotal 4 Equpment Electroncs 11 Industral equpment 4 Transportaton equpment, and auto parts 10 Other equpment 6 Subtotal 31 Textle and Materal Metal and mneral 15 Chemcal 11 Leather 3 Plastcs materal 9 Textles and apparel 46 Wood product Subtotal 86 Total 159 9
Table 3. Number of Surveys Used for the Analyss by Country Regon Country Count East Europe Bulgara 3 Czech Republc 6 Poland 9 East Europe Total 38 Lat.Amer.&Carbbean Argentna 5 Chle 7 Honduras 3 Panama 6 Lat.Amer.&Carbbean Total 1 Mddle East Iran 14 Jordan 6 Mddle East Total 0 South Asa Inda 33 Pakstan 30 South Asa Total 41 Sub-Sah.Afrca Kenya 8 Ngera 1 Senegal South Afrca 5 Uganda 5 Sub-Sah.Afrca Total 39 16 Country Total 159 Table 4. Data Summary Varable Mean Std. Dev. Mn Max Value Added (US$1,000) 9,087,744 13 189,463 Sales (US$1,000) 1,38 49,97 48 336,16 Wage rate (US$1,000) 3.14 3.14 0.11 15.38 Wage rate nstrumented (US$1,000)*.47 1.78 0.34 8.15 Unt prce of captal (US$1,000) 1.9 4.10 0.00 9.91 Unt prce of captal nstrumented (US$1,000)* 0.8 0.63 0.06 4.01 Per capta GDP (US$1,000). 1.89 0.6 7.47 Real nterest rate (lendng) (%) 9.00 4.78 1.68 9.09 Number of years snce foundaton 7.58 3.71 14 Standards (complance costs of prevous year) (US$1,000) 45 1,441 0.357 1,310 *Please see Secton 5 for the nstruments used for the wage rate and the unt prce of captal. 30
Table 5. Cost Functon Estmaton (Fxed Effects: Industry, Country) Parameters Model I (I3SLS) Model II (I3SLS) Model III (I3SLS) Model IV (I3SLS) β 0-0.810-1.585** 0.031-1.751 (0.660) (0.804) 0.977 (1.146) β y β yy 0.761*** 1.068*** 1.153*** 1.181*** (0.145) (0.19) 0.309 (0.96) 0.019-0.040-0.116** -0.067 (0.018) (0.034) 0.016 (0.041) β L 0.351*** 0.376*** 0.86*** 0.416*** (0.083) (0.087) 0.067 (0.104) β K 0.649*** 0.64*** 0.714*** 0.584*** (0.083) (0.087) 0.067 (0.104) β LL 0.079*** 0.077*** 0.078*** 0.065*** (0.013) (0.013) 0.005 (0.01) β KK 0.079*** 0.077*** 0.078*** 0.065*** (0.013) (0.013) 0.005 (0.01) β LK -0.079*** -0.077*** -0.078*** -0.065*** (0.013) (0.013) 0.005 (0.01) β Ly β Ky -0.011-0.016 0.006-0.016 (0.011) (0.01) 0.51 (0.014) 0.011 0.016-0.006 0.016 (0.011) (0.01) 0.51 (0.014) β s 0.055* -0.54* -0.58** -0.391 (0.031) (0.153) 0.015 (0.57) β ss -0.050** -0.084** -0.079** (0.05) 0.018 (0.037) β Ls -0.00-0.04*** -0.016 (0.010) 0.004 (0.014) β Ks 0.00 0.04*** 0.016 (0.010) 0.004 (0.014) β ys 0.058** 0.133*** 0.090** (0.06) 0.037 (0.036) β D 0.008 0.013-0.355*** 0.00 (0.113) (0.111) 0.05 (0.17) Fxed Effects Industry, Country Industry, Country Industry, Country Industry, Country w L and w k Instrumented yes yes no yes Standards Redesgn and Equpment Redesgn and Equpment Redesgn and Equpment One-tme Redesgn Statstcs N 159 159 159 96 Adusted R-squared 0.93 0.93 0.873 0.94 Log lkelhood -95.435-9.754-108.765-47.915 Note: The adusted R-squared s computed as one mnus the rato of the resdual sum of squares to the total sum of squares, adusted by the degrees of freedom. Fgures n parentheses are standard errors and coeffcents are sgnfcantly dfferent from zero as ndcated by *** (1%), ** (5%) and *(10%). 31
Table 6a: Elastcty of Varable Cost wth respect to Standards and Scale Elastcty wth respect to Standards Scale Elastcty evaluated at Model I Model II Model III Model IV 5 percentle na 0.055 0.07*** 0.14* mean 0.055* (1.760) 75 percentle na 5 percentle mean 75 percentle 0.893*** (1.031) 0.914*** (3.734) 0.939*** (19.446) Note: Numbers n parentheses denote asymptotc t-values. (1.473) 0.058* (1.765) 0.056 (1.436) 0.998*** (1.97) 1.11*** (11.17) 1.4*** (9.609) (4.30) 0.70*** (6.188) 0.35*** (6.177) 0.851*** (7.785) 1.068*** (7.404) 1.96*** (6.945) (1.894) 0.13*** (.619) 0.146*** (.88) 0.876*** (13.705) 1.086*** (17.460) 1.55*** (14.515) Table 6b. Estmated Impact on Mean Dollar Varable Costs of One-Percent ($4,50) Increase n Mean Investment Costs Model I Model II Model III Model IV Mean Impact $4,998 $5,70 $4,535 $1,904 Table 7: Elastcty of Varable Cost wth respect to Standards by Industry Model Model I Model II Model III Model IV Machnary Equpment 0.114** (.000) 0.3*** (3.86) 0.475*** (3.888) 0.5 (1.409) Processed Food, etc. -0.004 (-0.060) Raw Food 0.018 (0.310) Materals and Lght Manufacture 0.058* (1.740) Note: Numbers n parentheses denote asymptotc t-values. -0.053 (-0.633) 0.079 (1.175) 0.033 (0.866) 0.077 (0.667) 0.419*** (4.795) 0.36*** (4.738) -0.06 (-0.148) 0.190 (1.177) 0.14** (.14) 3