Armington elasticities Estimates for Uruguayan manufacturing sectors

Transcription

1 Armngton elastctes Estmates for Uruguayan manufacturng sectors Manuel Flores Adrana Casson December, 2008 Introducton The hgh degree of openness of the Uruguayan economy and the fact that the country s charactersed by beng constantly subject to shocks, strongly suggest the use of smulaton tools that allow for predctng ts future evoluton under dfferent scenaros. Currently, Computable General Equlbrum Models (CGEMs) appled to trade are one of the most potentally powerful nstruments for dong such analyses. Although there exsts some research performed usng ths methodology for Uruguay, accumulaton n the area s stll scarce (the earlest reference s Laens and Terra, 2000, whle latests contrbutons are Terra, 2003; Terra et al., 2005; Laens and Terra, 2008). As t s well known, operatonal CGEMs crtcally rely on the avalablty of many parameters, especally related to elastctes, among whch Armngton elastctes of substtuton are crucal when the models are appled to trade. In the case of Uruguay, these parameters have been mposed n order to have coherent smulatons and/or usng avalable estmates for other economes. Hence, n order to obtan more robust results, t s of upmost nterest to specfy and estmate Armngton models that would provde estmators of the elastctes usng Uruguayan data. The work here summarzed ntends to start fllng n ths gap. In the followng secton the theoretcal framework chosen s exposed. In Secton 3 we brefly sketch the econometrc models to be estmated, the results of whch are detaled n Secton 4. Conclusons and future suggested lnes of research are summarsed n the last secton. Armngton Elastctes The falure of tradtonal nternatonal trade theores n explanng several of the trade patterns observed n the 60s gave rase to new developments that n the 80s were known as New Trade Theores (NTT). One key assumpton that s questoned by these new approaches s the complete specalzaton of each country n those goods n whch they have comparatve advantages, an assumpton crucal for the valdty of the Law of One Prce. Further, the tradtonal theores look only at the supply sde, whle dsregardng the possblty of ncreasng returns to scale. Another man contrbuton of the NTT relates to them hghlghtng that the homogenety of goods may not be lnked exclusvely to the techncal characterstcs of producton but also to secondary attrbutes such as commercalzaton practces or brands. Further, heterogenety n qualty and hence prces was also ntroduced n the models.

2 These novel contrbutons were related also to the supply sde of the market, beng the demand relatvely dsregarded. However, t was long before that P.S. Armngton (1969) had analysed the possblty of dfferentaton of goods stemmng from the percepton of consumers on them beng heterogeneous dependng on the natonal orgn of producton, although keepng the assumptons of perfect competton and constant returns to scale. Ths dstnctve feature of otherwse homogeneous goods need not be objectve or even related to the actual exstence of dfferences but n beng so perceved by consumers they do alter the relatve demand of the varous natonal varetes 1. As a consequence, goods prevously treated as homogeneous n trade models had to be consdered heterogeneous accordng to ths new dmenson, determnng that consumers would not perfectly substtute one varety for the other. Thus, the degree of substtutablty between natonal varetes of a good, known n the lterature as the Armngton elastcty, started havng a man role n trade models. An Armngton structure mples that consumpton decsons nclude at least two stages. Frst, gven the budget constrant consumers decde upon the quantty demanded of each good. Afterwards, the proporton of natonal versus foregn varetes of each good s decded. Some extensons of the model nspred n the orgnal paper ncorporate a thrd stage n whch the mported share of each good s further dstrbuted among the dverse foregn countres offerng the merchandse. Each natonal varety of a good s denomnated by Armngton as a product. Markets are thus defned dependng on the defnton of homogeneous goods except for ther orgn of producton, so that many products are traded wthn each market. Trade models along the last decades have ncreasngly ncorporated the natonal dfferentaton of goods as proposed by Armngton. In dong so, they also assume the exstence of market rgdtes and that natonal/foregn ndustres may exert a certan degree of market power. Armngton elastctes have also acqured a starrng role among most researchers advocated to buldng Computable General Equlbrum Models (CGEM), both multregonal and mult-country, partly due to them allowng for a better approxmaton of the specalsaton patterns observed especally durng and after a trade lberalsaton process 2. As such, ts magntude becomes crucal for a correct quantfcaton of the overall effects of any change n trade polces, whle smulatons performed usng CGEMs may even lack any sense for certan range of values of these parameters. The fact that relable CGEMs smulatons depend crtcally on Armngton elastctes forced researchers n the past to use arbtrary calbrated values, at tmes makng use of values provded by other exstng models. However, the strategy casted doubts on the approprateness of the mputed parameters for the partcular economy under study, whle at tmes the CGEM n need of Armngton elastctes had a level of dsaggregaton 1 No matter ts specfctes, the natonal dfferentaton of goods overlaps horzontal and vertcal dfferentaton as defned n the NTTs. 2 GTAP, MONASH, models developed by The World Bank, the Internatonal Monetary Fund, the World Trade Organzaton, among others. 2

3 nconsstent wth respect to the one gvng rse to the avalable parameters. The above stated shortcomngs motvated an upsurge of econometrc analyses focusng on the estmaton of Armngton models for dverse ndvdual economes as well as for sets of countres/regons, usng dfferent levels of aggregaton for defnng goods and markets. The avalablty of estmated elastctes of substtuton for the countres for whch smulatons are beng performed should guarantee that a more accurate and relable result s obtaned from smulatons, as they would presumably ncorporate the specfctes of the partcular economy under analyss. However, the current econometrc lterature focused on Armngton elastctes has not yet provded wth estmates that fulfl the CGEMs needs, a fact that has n turn trggered a profuse nterest on studyng varous theoretcal and methodologcal ssues, some of whch were prevously unforeseen. Among the topcs currently under debate t s worth mentonng the consequences of relaxng theoretcal assumptons such as the separablty of preferences that lmt the feasble utlty functons; the consderatons that have to be taken nto account for defnng homogeneous goods; or the mplcatons of usng a two or three stages decson process. Methodologcal ssues are concerned wth the consequences of usng dfferent sorts of nformaton sets; the correct specfcaton of models; the choce of estmaton methods; or the qualty of avalable data; among many others 3. No matter the obstacles that have stll to be surmounted, the accessblty to estmated values that are obtaned for the specfc economy under study s the only means by whch smulatons can be consdered relable, snce t s well known that the mpact of polces cannot be expected to be ndependent of the specfctes of each spatal/temporal case study, whle consumpton preferences may substantally dffer between economes. The Model The Armngton model proposes mechansms explanng an underlyng structure that ntends to reflect actual nternatonal trade patterns. Perfect competton and constant returns to scale are assumed, whle goods are consdered homogenous except for the natonal orgn of producton. Consumers are expected to decde on the bundles of goods that report them the maxmum utlty level attanable gven prces and subject to ther budget constrant. As preferences are assumed to be separable, after decdng on the quantty to be purchase of each good, t s possble to ndependently decde on the foregn/natonal composton of the demand for each good. In dong so they take nto account the relatve prces local to mport prces beng the relatve quanttes demanded of the products determned dependng on the ease wth whch they substtute varetes once relatve prces vary the magntude of the Armngton elastcty of substtuton. In order to solve the resultng optmsaton programme, t s further assumed that consumers get more satsfacton whenever they are able to 3 For a dscusson on the topc, see Casson and Flores (2009) and Flores (2008). 3

4 ncrease the quanttes consumed (non-sataton), whle the utlty level ncreases proportonally when equally augmentng the quanttes consumed of all goods (homothetcty of the utlty functon). The above assumptons mply that the demand for each good and product s ndependent of what happens n all other markets. The margnal rate of substtuton s not a functon of the absolute quanttes consumed or the absolute level of ncome. Thus, the demand for each good/product depends only on the level of expendture assgned exclusvely to ts consumpton and not on what s devoted to the demand of other goods/varetes, whle the relevant prces are only those operatng n each specfc market. The model and the derved soluton of the assocated optmsaton programmes can be stated as follows: Stage 1: Max X U U (X 1,, X n ) s.t. D = (P X ) X * = X ( D, P 1,, P n ) Stage 2: Mn NM PN N + PM M s.t. X * = Φ (N,M ) for each = 1,,n N * = N (X *,PN /PM ) M * = M (X *,PN /PM ) for each = 1,,n Where U s the utlty of consumpton; X and P are the quanttes demanded and the prces of good, respectvely; D s the level of expendture; N and M are the quanttes demanded of domestc and foregn varetes of good, respectvely; PN and PM the correspondng prces. An aster n varables refers to ts optmum value. Further, as the prce of each good should be equal to the weghted average of the prces of ts varetes, the followng dentty should also be verfed: P P 1 Φ... X 1. Φ P m X m P = j (P j X j )/X ; P = P j (X /X j ) 1/σ = 1,,n j= 1,,m A wdely used functonal form that has the above stated propertes s the Constant Elastcty of Substtuton (CES). As ts name ndcates, the ease of substtutablty of goods s constant all along the ndfference curves, whle the elastcty of substtuton s dentcal between all pars of goods/products. A CES utlty functon n the case of two goods can be denoted as: U(X 1,X 2 ) = A*[ βx 1 -γ + (1-β)X 2 - γ ] -1/ γ Where A s a scale parameter; β s a dstrbuton parameter; and λ= 1/(1+ γ) s the elastcty of substtuton. The relatve demand for goods after solvng the optmsaton programme s: 4

5 (X 1 / X 2 ) * = [(1-β)/ β] -1/(1+γ) -1/(1+ γ) * (P X1 /P X2 ) Assumng that there are n goods, the optmum level of demand for each good s: X * = Φ (N,M ) = [b N -ρ + (1-b )M -ρ ] -1/ρ = 1,..., n Once all X * are determned, the second optmsaton programme has to be solved, yeldng: (N /M ) * = [(1-b )/b ] -1/(1+ρ) * (PM /PN ) -1/(1+ρ) where N and M are the natonal and foregn varetes of each good, respectvely. Takng logs, the model to be estmated s: N ln M 1 b ln b PM ln PN for each = 1,,n (1) Data and methodologcal ssues We estmate models bascally specfed as (1) at a 4-dgt level of dsaggregaton (ISIC, Rev.2) for 32 manufacturng sectors along 1989 to 2001, usng monthly and quarterly data. The dfferent frequency of the data s due to the fact that although we estmated the models wth quarterly nformaton so as to avod the excessve and non nformatve volatlty of monthly observatons, we consdered that the analyses of the order of ntegraton and the exstence of contegraton ganed robustness by usng larger tme seres. Although data was avalable untl 2004 by the tme ths study had started, we consdered that observatons were not enough to properly model the changes occurrng after the huge shock to the economy that took place n Further, by md-2002 there was a change n the methodology used to construct prce ndexes, so that compatblsng the seres would have mpled an extensve addtonal work on the data exceedng the goal of ths frst approach to the subject. We chose to work wth a subset of the 57 sectors for whch data was avalable as a frst step n the research. The chosen ndustres belong to three broad categores referrng to Food, Beverages and Tobacco, tradtonally net exportng sectors; Chemcal Products, whch are manly net mportng ndustres; and Textles, a sector gatherng both types of ndustres. The strategy was adopted so as to control for the eventual 5

6 role that the ndustres nternatonal nserton may play n the specfcaton of the models. We approxmate relatve demands of varetes by the value of sales and mports, thus assumng no effectve supply restrctons are present, nether nternatonally nor domestcally. The assumpton has to be tested for n the case of local supply, beng Uruguay a small economy. Data on local sales and prces stem from the Natonal Statstcs Insttute (INE) whle those referrng to mports are obtaned from the Customs Offce and the Central Bank of Uruguay (BCU). Quanttes mported are not the best proxy for the demand of foregn varetes snce they refer to the entrance of products and not to ther effectve sale n the local market. The consequent asynchroncty between entry and consumpton of mported goods - especally when usng monthly data - forces the use of many bnary varables to account for atypcal observatons. Exchange rates data are provded by the BCU whle tarffs stem from the Latn Amerca Integraton Assocaton (ALADI). As tarffs are reported at a 6-dgt level of dsaggregaton, they had to be aggregated to match the prce varables. A seasonal pattern was ncluded n all models as well as a determnstc trend whenever the analyss of the order of ntegraton of varables or the contegraton results mposed such a strategy. Econometrc results Specfcaton, estmaton and statstcal analyss of the models As a frst step n the econometrc analyss, we studed the statstcal propertes of the stochastc processes nvolved ntegraton order; balance of proposed estmable models; and exstence of contegraton relatons when pertnent. We used ADF tests, wth an ntally hgh number of lags that were afterwards sequentally reduced and Engle and Granger s (1987) procedure for testng contegraton 4. A hypothess of nterest n our research relates to the possblty of changes n tarffs and/or exchange rates havng overshootng effects on relatve demands. The dea stems from the fact that these varables have been hstorcally used as antnflatonary polcy nstruments n Uruguay, so that agents may perceve ther varatons n a dstnctve way than prce movements. We tested for the hypothess by addng these two varables n the standard Armngton model and afterwards tested for the statstcal sgnfcance of ther assocated coeffcents. Consequently, we also performed the order of ntegraton and contegraton analyses ncludng these varables. 4 The econometrc software used was EVews. 6

7 The ADF tests on the order of ntegraton of tme seres were performed usng the three versons orgnally proposed by Dckey and Fuller (1979), so as to jontly study the outcomes and decde on the statonarty of processes 5. Our results on the order of ntegraton of the tme seres nvolved sgnal at relatve prces and quanttes beng mostly I(1) and rarely I(2). A non neglgble number of relatve prces are found to be statonary processes, as t s also the case for the exchange rate (Table 1). The statonarty of the exchange rate s not rejected when the model ncludes a determnstc tme trend. The result s consstent wth the prefxed exchange rate polcy exerted by the monetary authortes along most of the perod, although most probably not sustanable f analysed n a longer perod of tme. Tarffs are mostly ntegrated processes, hence of nfnte memory. The result supports the hypothess of permanent effects of polcy changes and partcularly of structural nsttutonal changes - such as the Mercosur formaton - on ether ther level when t s I(1) - or both on ther level and ther rate of change when I(2) as s the case for a thrd part of the sectors analysed. The result suggests that care should be posed when usng tarffs as short run polcy nstruments, snce the effects would anyway persst for a long tme. Order of Integraton Table 1: Order of Integraton - Summary of results Relatve demands - Relatve prces Tarffs Exchange rate Food Beverage & Tobacco Textles Chemcal Products (4-dgt ISIC ndustres) Number of ndustres (monthly data) q p t e % Number of ndustres % Number of ndustres % Number of ndustres I(0) 2 6, ,3 9 28, ,0 (1) 26 81, , ,4 0,0 I(2) 4 12,5 4 12,5 4 12,5 0,0 Total Note: q s the log of the rato of mported to domestcally produced quanttes sold; p s the log of the relatve prce of goods local to mported; t s the log of 1 plus the tarff rate; and e s the log of the exchange rate. % It s thus possble to state that n many markets shocks do have permanent effects on the temporal evoluton of relatve demands, relatve prces and tarffs, ether on ther mean value and/or ther varance. Ths property should be kept n mnd when nstrumentng polces but also when faced to exogeneous events, such as an ncrease n the level of nternatonal supply that n turn reduces prces, or a lberalsaton 5 Although the wdespread practce regardng the decson on the order of ntegraton of processes usng ADF tests s to dscard the trend and constant ncluded and/or the constant ncluded versons of the AR(p) model proposed for proxyng the DGP, we beleve that t s better to jontly analyse the results for all models, usng the hghest order dynamc structure allowed for by the data (for a dscusson of the topc, see for example Banerjee et al., 1993). Consequently, we decded wthout takng as fully proven the non rejecton of the exstence of constant and/or trend n the Dckey-Fuller models. 7

8 process that results n a reducton of tarffs, or even when an dosyncratc change n tastes that may ncrease the demand of goods of a partcular orgn of producton s verfed. In cases n whch statonarty of relatve quanttes or prces s not rejected, on the contrary, the processes are charactersed by havng short memory, so that the effect of exogeneous shocks dsappears as tme goes by. A most lkely underlyng cause s that the components of relatve quanttes and/or prces have a common stochastcs trend so that shocks have long lastng effects on the ndvdual components wthout generatng changes n ther relatonshp n the long run. In Table 2 below the frequency of the dverse possble outcomes s summarsed. Table 2: Order of Integraton - Summary of results Import demand Local demand - Internatonal prces Local prces Food Beverage & Tobacco Textles Chemcal Products (4-dgt ISIC ndustres monthly data) OI M N PM PN I(0) I(1) I(2) Total Note: M s the log of the ndex of the real value of mported goods; N s the log of the ndex of the real value of domestcally produced goods; PM s the log of the mports prce ndex; PN s the log of the domestc prce ndex. In the partcular case of relatve prces beng statonary and gven the exchange rate s I(0), the evdence would support the valdty of the Law of One Prce (LOP) n those markets, at least along the perod under analyss. Analogously, f the order of ntegraton of local and nternatonal prces are I(2) and the relatve prce s I(1), then there exsts one common unt root, thus sgnallng at the valdty of the relatve verson of the LOP. On the contrary, f non contegraton among domestc and nternatonal prces exsts, that s, when the order of ntegraton of these seres s dfferent or whenever the order of ntegraton of relatve prces s equal to that of both of ts components, the evdence s nconsstent wth the valdty of the LOP n any of ts versons. A second step nvolved analysng f the models were balanced and hence allow for analysng the exstence of contegraton 6. Ths was verfed n all cases at a 90% level of confdence, as shown n Table 3. 6 In a balanced model the rght hand sde varables should have an order of ntegraton such t s possble that a lnear combnaton of them has the same order of ntegraton of the varable n the left hand sde. Contegraton exsts when ths lnear combnaton does exst. Obvously, the exstence of contegraton among varables of an unbalanced model s not possble. 8

9 Table 3: Balance of models Food Beverage & Tobacco Textles Chemcal Products (4-dgt ISIC ndustres monthly data) Industres q p t 3111 I(2) I(2) I(2) 3112 I(1) I(0) I(1) 3113 I(1) I(0) I(1) 3115 I(1) I(0) I(1) 3116 I(1) I(0) I(1) 3117 I(1) I(1) I(1) 3118 I(0) I(1) I(1) 3119 I(1) I(1) I(1) 3121 I(1) I(2) I(2) 3122 I(1) I(1) I(1) 3131 I(1) I(1) I(0) 3132 I(0) I(0) I(0) 3133 I(1) I(1) I(1) 3134 I(1) I(1) I(1) 3140 I(1) I(1) I(0) 3211 I(1) I(0) I(1) 3212 I(1) I(1) I(0) 3213 I(1) I(1) I(0) 3214 I(2) I(2) I(0) 3215 I(1) I(0) I(1) 3219 I(1) I(1) I(0) 3220 I(1) I(1) I(0) 3240 I(1) I(1) I(0) 3511 I(1) I(0) I(1) 3512 I(1) I(1) I(1) 3521 I(1) I(0) I(1) 3522 I(2) I(2) I(2) 3523 I(2) I(0) I(2) 3529 I(1) I(1) I(1) 3530 I(1) I(1) I(1) 3551 I(1) I(1) I(1) 3560 I(1) I(1) I(1) The jont analyss of the order of ntegraton of the processes n each sector merts further attenton, although exceedng the purposes of ths research, as t may suggest sectoral specfctes that n turn result nformatve n terms of mprovng the specfcaton of models and hence the accuracy of estmates. 9

10 Once verfed the emprcal consstency of the relatons as stated n the models, contegraton analyses were performed. At a 90% confdence level, contegraton was rejected only n one ndustry, for whch the confdence level for non rejecton was 82%. However, the sector s Petroleum Refneres, ts prce beng set by the government and frequently used as an antnflatonary nstrument so that t s most lkely that the equlbrum relaton s not observed as t s beng exogenously dstorted (Table 4). Table 4: Contegraton Analyses Order of Integraton of resduals of statc regressons Models wth and wthout determnstc trend Food Beverage & Tobacco Textles Chemcal Products (4-dgt ISIC ndustres monthly data) Industres Statc regresson wth trend Statc regresson wthout trend Lags ADF OI Lags ADF OI ,426 *** I(0) 10-5,374 *** I(0) ,947 *** I(0) 2-7,900 *** I(0) ,439 *** I(0) 0-5,413 *** I(0) ,598 *** I(0) 1-5,197 *** I(0) ,950 *** I(0) 6-4,976 *** I(0) ,545 *** I(0) 0-5,651 *** I(0) ,103 ** I(0) 9-5,317 *** I(0) ,468 * I(0) 13-4,443 ** I(0) ,427 *** I(0) 1-4,570 ** I(0) ,754 ** I(0) 4-2,845 No I(0) ,582 ** I(0) 3-4,590 ** I(0) ,599 *** I(0) 0-8,063 *** I(0) ,664 *** I(0) 1-5,312 *** I(0) ,110 *** I(0) 3-3,879 * I(0) ,659 *** I(0) 1-4,828 *** I(0) ,020 *** I(0) 7-2,268 No I(0) ,809 *** I(0) 1-3,749 No I(0) ,756 *** I(0) 0-7,595 *** I(0) ,380 *** I(0) 1-5,870 *** I(0) ,698 *** I(0) 0-8,407 *** I(0) ,194 *** I(0) 1-4,837 *** I(0) ,741 *** I(0) 0-7,636 *** I(0) ,550 *** I(0) 0-7,239 *** I(0) ,977 *** I(0) 0-9,370 *** I(0) ,574 *** I(0) 0-8,420 *** I(0) ,800 *** I(0) 0-6,686 *** I(0) ,273 *** I(0) 4-1,929 No I(0) ,618 *** I(0) 0-4,448 ** I(0) ,703 ** I(0) 2-4,705 ** I(0) ,986 No I(0) 2-2,196 No I(0) ,914 *** I(0) 0-9,602 *** I(0) ,216 No I(0) 1-4,220 ** I(0) Notes: Lags refers to the maxmum number of lags ncluded n the model for performng the ADF test; ADF s the value of the statstc; ***/**/* refer to the sgnfcance level of the tests beng 1%/5%/10% accordng to Macknnon response surfaces; OI s the order of ntegraton of resduals. 10

11 In spte of the evdence supportng relatons are not spurous, we beleve that n some cases the low level of confdence necessary for not rejectng contegraton sgnals at the need of ncludng addtonal varables accountng for the role of other phenomena. We thus proceed to estmatng the Armngton models n ts dynamc versons due to the data frequency used. Models were estmated for all 32 sectors ndvdually usng Least Squares. We performed an n depth evaluaton of the valdty of all statstcal assumptons underlyng the orgnal specfcaton, ts results beng taken nto account for respecfyng the orgnal versons of the models. The ntal dynamc structure of order 5 mposed to all models was afterwards modfed by sequentally dscardng non sgnfcant lags. Normalty tests were ntensvely used as a means of dentfyng outlers that were thus modelled by means of bnary varables. Heteroskedastcty was not an ssue whle changes n parameters were found n a few cases and thus ncluded n the models. Exogenety of prces, only credble f there were no restrctons from the supply sde, was n most cases rejected usng Hausman s test (1978). When strong exogenety was rejected, the models were re-estmated by Instrumental Varables Methods, usng lags of the prce varable as nstruments. The dfferences between the estmated values of the Armngton elastctes usng both estmaton methods were not large n absolute terms, although statstcally sgnfcant. It s worth notng that the LS endogenety bases found were both postve and negatve dependng on the ndustry, so that no unque effect on the estmated value of the elastcty can be stated n terms of gnorng endogenety of prces. In many models we ncluded a tme trend, ether followng the contegraton relaton specfcaton or as the result of statstcal tests sgnallng at ts ncorrect omsson. These trends mght be capturng factors lnked to techncal progress, dfferentated by orgn of producton, or else revealng changes n the composton of demand. Further, the hypothess of an exstng overshootng mpact of tarffs was not rejected n a non neglgble number of cases when performng the contegraton analyses wth monthly data. However, when swtchng to quarterly data the effect dsappeared n most markets. The result may be read as a quarter beng the necessary tme perod for a reversal of the ntal overreacton of agents to changes n tarffs 7. The estmated value of the Armngton Elastcty The estmated values of the long-run Armngton elastctes vary n a range of 0.5 to 4.3 dependng on the good/ndustry (see Table 5 below). No estmated elastctes are nl, so that the evdence supports that there exst a degree of substtutablty between mported and domestc varetes of all the analysed goods. The pont estmates of the elastcty are greater than 1 n almost 60% of the cases, although the nterval 7 The full estmaton results are avalable upon request. 11

12 estmaton excludes the unty only n half of those cases. On the opposte, elastctes are statstcally lower than 1 just n 4 economc sectors. Table 5: Long-run Armngton Elastctes Unequatonal Models Food Beverage & Tobacco Textles Chemcal Products (4-dgt ISIC ndustres monthly data) Armngton Confdence Interval Industry Startng date Elastcty SD. Lower Bound Upper Bound Further, f lookng at the value of the upper bound of the nterval estmates, the estmated elastcty ranges from 0.68 to 6.35, beng over 1.5 n 55% of the cases, of whch two thrds are over 2. These fgures, as well as the pont estmated although at a lesser extent, are qute n lne wth those reported n Donnelly, Johnson and Tsgas 12

13 (2004), who perform a matchng of the USITC elastctes wth those of the default GTAP-41 commodty model. The fgures there reported range from 1.0 to 5.2, the mnmum value beng lower that that used n GTAP (1.8). Consstent wth the assumpton of separablty of preferences, the estmated models were specfed sectorally, guaranteeng that no nformaton relatve to what happens n any other market was taken nto account. The assumpton mples that when decdng relatve demands of the varetes of a partcular good condtonal on the prevalng relatve prce, consumers do not take nto account any nformaton assocated to the relatve demand or prce of other goods nor on the share of ncome devoted to ther consumpton. Statstcally, the assumpton undoubtedly mples that no smultanety exsts among the systematc components of the condtonal relatve demands for goods, so that no causalty lnks are to be found between the relatve demands of each good and hence smultaneous equatons econometrc models are to be dscarded. However, the assumpton would not be volated f the non systematc components of the processes are contemporaneously correlated as the assocaton s just the result of exogenous shocks affectng many markets and/or phenomena at the same tme, even those that are completely unrelated. Ths would be the case, e.g., for exogenous shocks affectng the nternatonal arbtrage mechansms. Includng such nformaton n the models have no consequence n the value of estmates but do mprove the level of accuracy of the nference. We thus specfy multvarate models that nclude seemngly unrelated equatons for all ndustres wthn each 3-dgt groupngs and also for the 2-dgt ISIC dvsons that were estmated by Generalsed Least Squares. It may also occur that the relatve prces are also subject to these same effects, so that ther non systematc components may also be correlated. Further stll, contemporaneous correlaton may also exst among prces and quanttes. In order to account for ths addtonal possblty the multvarate models were specfed ncludng autoregressons for all the prces that were prevously found as not weakly exogenous to the relatve demand processes. We report the results on the estmated elastctes n Table 6. As expected, the value of the pont estmates of the Armngton elastcty do not vary sgnfcantly wth respect to the unequatonal models but gans n precson are ndeed remarkable, attanng an average reducton of almost 20%. The hgher accuracy of results may or may have not sgnfcant consequence on the absolñute magntude of the estmates, buty t certanly determnes that the accuracy and consequent relablty of hypothess testng and nference n general are mproved. 13

14 Table 6: Long-run Armngton Elastctes Unequatonal and Multvarate Models Food Beverage & Tobacco Textles Chemcal Products (4-dgt ISIC ndustres monthly data) Industry Armngton Elastcty SD Lower Bound Upper Bound Percentage decrease n SD % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % Average: 19.3% Concludng remarks The econometrc analyses above summarsed provde wth the frst set of estmated Armngton elastctes for several Uruguayan manufacturng ndustres. As such, they 14

15 consttute the only locally avalable set of parameters that may be used n CGEMs smulatons. The thorough statstcal evaluaton performed to the estmated models allows us to guarantee that the results obtaned are robust. However, we do beleve many of the statstcal analyses suggest that the models may be mproved by consderng addtonal varables. Further, extendng the sample perod may provde nformaton that s most lkely that s not beng here captured gven the specfctes of the tme perod consdered. Compared to nternatonal estmates, the magntude of the long-run Armngton elastctes obtaned seems qute adequate. However, they may stll be consdered low n terms of the operatonal needs of CGEMs. We suggest the use of nterval estmaton n order to have an objectve range of values for performng senstvty analyses. More work should be done n the future so as to account for some of the suggested shortcomngs of ths frst approach to the topc. A major ssue s that of the ncorrect omsson of eventually key varables related to modellng the supply sde of the markets as well as to the assumptons related to the ncome elastcty beng unty. The above may be also related to the need of further studyng how to relax the assumptons underlyng the separablty of consumers preferences and the homothetcty of the utlty functon that would n turn allow for the use of alternatve functonal forms. 15

16 References Armngton P. S., (1969). A theory for demand for products dstngushed by place of producton. IMF Staff Papers, Vol. 16(1): Banerjee A., Juan J. Dolado, John W. Galbrath, Davd F. Hendry (1993). Co- Integraton, Error Correcton, and The Econometrc Analyss of Non-Statonaty Data. Oxford Unv. Press. Casson, A. and M. Flores M. (2009). «Methodologcal Shortcomngs n Estmatng Armngton Elastctes, Workng paper, Departamento de Economía, Facultad de Cencas Socales, Unversdad de la Repúblca, Uruguay. Dckey D. A. and W.A. Fuller, (1979). Dstrbuton of the Estmators for Autoregressve Tme Seres wth a Unt Root, Journal of the Amercan Statstcal Assocaton, Vol. 74, pp. Donnelly,W.A., K. Johnson and M. Tsgas, (2004). Revsed Armngton Elastctes of Substtuton for the USITC Model and the Concordance for Constructng a Consstent Set for the GTAP Model, U.S. Internatonal Trade Commsson. Research Note No A. Engle R. y G. Granger (1987). Contegraton and Error Correcton: Representaton, Estmaton and Testng. Econometrca, Vol. 55, pp Flores M., (2008). Elastcdades de Armngton. Dscusón teórco-metodológca y estmacones para Uruguay. Monographc work, Facultad de Cencas Económcas y de Admnstracón, Unversdad de la Repúblca, Uruguay. Hausman, J.A., (1978). Specfcaton tests n econometrcs, Econometrca, 46. Laens, S. and M.I.Terra, (2000). Efectos del perfecconamento sobre el Mercado de trabajo de Uruguay. Un ejercco de smulacón usando un modelo CGE, Revsta de Economía, Banco Central del Uruguay, Vol.7/2, Segunda Época. Laens, S. and M.I.Terra, (2008). Asymmetres and straghtenng the customs unons. Optons for the common external tarff. In Deepenng ntegraton n Mercosur. Dealng wth dspartes. (Chapter 5), J. S. Blyde, E. Fernández Aras, P. Gordano (Eds.), IADB. MacKnnon, J.G., (1991). Crtcal values for contegraton tests., Ch. 13 n Long-run Economc Relatonshps: Readngs n Contegraton, eds. R. F. Engle and C. W. J. Granger, Oxford, Oxford Unversty Press, M.I.Terra, M.I., (2003). Trade lberalzaton n Latn Amerca countres and the agreement textles and clothng n the WTO, Econome Internatonale 2003/3, nº 94-95, pp Terra, M.I., A. Forteza, G. Katz and A. Pereyra, (2005). Macroeconomc Impacts of the Reform of Publc Servces n Uruguay A CGE Analyss, Workng paper 21/05, Departamento de Economía, Facultad de Cencas Socales, Unversdad de la Repúblca, Uruguay. 16