Freight transport and economic growth : an empirical explanation of the coupling in the EU using panel data

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1 Freght transport and economc growth : an emprcal explanaton of the couplng n the EU usng panel data Julen Brunel To ce ths verson: Julen Brunel. Freght transport and economc growth : an emprcal explanaton of the couplng n the EU usng panel data <halshs > HAL Id: halshs Submted on 4 Oct 2005 HAL s a mult-dscplnary open access archve for the depos and dssemnaton of scentfc research documents, whether they are publshed or not. The documents may come from teachng and research nstutons n France or abroad, or from publc or prvate research centers. L archve ouverte plurdscplnare HAL, est destnée au dépôt et à la dffuson de documents scentfques de nveau recherche, publés ou non, émanant des établssements d ensegnement et de recherche franças ou étrangers, des laboratores publcs ou prvés.

2 Freght transport and economc growth : an emprcal explanaton of the couplng n the EU usng panel data. BRUNEL Julen, Transport Economcs Laboratory (UMR-CNRS 5593), Unversty Lumère Lyon 2, France. Abstract: The lnk between transport and economc growth s nowadays understood behnd the so-called ssue of couplng. Transport ntensy or transport elastcy to economc producton are generally used to assess the lnk. In ths paper, road freght ntensy s decomposed nto four factors. A European panel data estmaton of these four factors solates levels of couplng and levels of decouplng. We observe two factors of couplng (. e. the rse of the average dstance of transport and the ncreasng market share of road transport) and two factors of decouplng (the decreasng share of the ndustry n the economc producton and the decreasng weght of ndustral producton). Date verson: 26/09/05 15:59. Classfcaton: JEL R41, Q01 Contact : julen.brunel@let.sh-lyon.cnrs.fr 1

3 Introducton The lnk between transport and economc growth has always been an ssue for transport economsts. The lerature was orgnally nterested to know the contrbuton of transport nfrastructures to economc growth. The semnal paper of Fogel (1962) shows that ral transport was a source of the Amercan surge at the end of the nneteenth century. Later, the development of endogenous growth models gave up a new nsght to ths ssue lke n Aschauer's paper (1989). Another set of papers has emphassed the lnk between transport and economc growth n order to forecast transport demand. Most of these papers estmates transport or traffc elastces to economc producton. Ths lerature corroborates the dea of a strong relaton between transport and economc growth. Recently, a growng concern for envronmental matters have changed the regard on ths relaton. Experts of the Intergovernmental Panel on Clmate Change (IPCC) assume n ther thrd report that the global average surface temperature has ncreases by 0.6 C durng the twenteth century (IPCC, 2001). Ths report also underlnes the growng concentraton of Greenhouse Gazes (GHG) due to human actvy and forecasts a global warmng comprsed between two and sx degrees Celsus for the twenty-frst century. One can observe that transport sector plays a great role n global warmng. For nstance, French data form CITEPA (2005) shows that transports generate 28% of total CO 2 emssons n Ths share s hgher than ndustres or resdental and servce actves ones snce these sectors are respectvely responsble of 21 and 22% of CO 2 emssons. Another matter of concern for CO 2 emssons caused by transportaton s s hgh level of growth. From 1960 to 2003, s volume ncreased by more than 500% n France. Ths statement s true for other developed countres (Schäfer, 2005). The growng concern for global warmng has gven a new sense to the lnk between transport and the economc growth. Nowadays, ths ssue s not only devoted to determne the role of economc growth n transport growth but s also consderng f ths lnk between transport and economc growth can be broken. Ths ssue, also called the couplng, has been an extensve ssue for the lerature. It has even been an ssue for nstutonal lerature. It was for nstance the focus of a report of the Standng Advsory Commtee on Trunk Road 2

4 Assessment (SACTRA, 1999) n the Uned Kngdom. European research programs were fulflled on ths topc lke REDEFINE (1999) or SPRITE (2000). The European Conference of Mnsters of Transports also organzed a conference on ths matter (ECMT, 2002). Ths ssue s astonshngly even dscussed n polcal documents lke the European Whe Paper on transport polcy (European Commsson, 2001) n whch the European Commsson supports a decouplng strategy. In the frst secton of ths artcle, the man drectons of the lerature are revewed. Then, ths paper purposed an orgnal assessment of the couplng usng panel data econometrcs. The second secton of the paper presents a decomposon of the couplng n four factors. The thrd secton estmates the four factors evolutons along wh natonal ncome level usng a European panel data sample. The fourth secton nterprets these evolutons n term of elastcy. It gves two factors of couplng (the average dstance of transport and the modal spl of transport) and two factors of decouplng (the share of the ndustry n the economy and the average densy n value of the ndustral producton). Secton fve fnally concludes. The lerature The lnk between transport and the economy has been the object of a huge lerature. Ths secton presents the two man drectons of ths lerature. The frst drecton deals wh the assessment of the aggregate transport demand sensbly to economc producton. Elastcy estmatons are one of the most commonly used tool to assess ths knd of relaton. For nstance, Meersman and Van de Voorde (1999) estmates the elastcy of freght transport to the ndustral producton n Belgum usng an Error Correcton Model. In France, Gabella- Latrelle (1997) estmates natonal transport demand elastcy to the ndustral producton. More recently, ths relaton has been estmated usng the contegraton (Meyer, 1998 ; Lenormand, 2002). It s also the ssue of a paper of Kulshreshtha and Nag (2000) where a contegratng VAR model s estmated for nter-urban ralway passenger transports n Inda. For freght transport, Kulshreshtha et al. (2001) also uses the contegraton to estmate the relatonshp between economc growth and ralway transport n Inda. Yao (2005) realzes a Granger causaly test for the relaton between transport and the producton or frms nventory. It shows sgnfcant feedback effects between these varables. Elsewhere, Lahr and Yao (2004) observe that transport actvy related ndexes are strongly synchronzed wh NBER-defned economc cycles. 3

5 Another mean to assess the lnk between aggregate transport demand and economc producton s the transport ntensy. Ths ndex s the rato between transport demand (. e. tons-mles or tons-klometers for freght demand) and the value of the GDP. It represents the numbers of transport uns necessary to produce one dollar or one euro of GDP. Ths aggregate ndcator has been used by Baum (2000) and Baum and Kurte (2002). These papers conclude n a decreasng trend for transport ntensy n Germany. They however observe that transport ntensy s ncreasng f only takes nto account road transports and the ndustral producton. The aggregate approach gves several estmatons of the sensbly of transport demand to the economc producton. However, these papers do not provde any explanaton of the phenomenon. Explanatons are gven by a second a set of papers. The man purpose of ths second set of papers s to decompose the aggregate transport demand n dfferent levels of couplng or decouplng. Ths methodology was nally developed by energy economcs. Ang and Zhang (2000) offers a comprehensve revew of these papers. Dfferent knds of decomposons are purposed to adapt to transport economcs. Kwon (2005) adapts the IPAT denty to the transportaton sector. Ths denty s suggested by the smple equaton Impact=Populaton Affluence Technology that Kwon (2005) transforms for the transportaton sector n ( D ) ( C ) C = P P D (1) where C s the level of CO 2 emssons from car travels and D total car drvng dstance n vehcle-km. Accordng the equaton (1), the amount of CO 2 emssons produced by the transport sector s equal to a product of three factors. The frst one (P) s the populaton. The second factor ( D ) represents the car travel dstance per person. It s also the affluence factor P of the IPAT equaton. Fnally, the technology factor s gven by the thrd factor ( C ) that D represents the amount of CO 2 emssons by un of car traffc. An emprcal estmaton of equaton (1) factors for Great-Bran between 1970 and 2000 shows that the better fuel effcency of cars s offset by larger dstances of travel. 4

6 Kang and Shpper (1996) or Schpper, Scholl and Prce (1997) decompose a transport energy use ndex nto three factors. They are the actvy (volume of transport realzed), the structure of the actvy (the modal share) and the ntensy (energy used per loaded transport actvy). These papers show the lms of technologcal mprovements of the transport energy effcency because such gans were untl now always offset by an ncreasng volume of transport or a rse of road modal share. In the transportaton feld, some papers leave the energy effcency and focus on the lnk between transport actvy and the economc growth. For nstance, Redefne (1999) decomposes the lnk between transport and the economc growth nto seven relatons that are dfferent levels of couplng or decouplng. In the same van, a paper of Jognaux and Verny (2003) explans that the couplng between freght transport and the economy s manly explaned by the growng dstance of transport n France. McKnnon and Woodburn (1996) nsst on the mpact of logstcal decsons such as warehousng to explan the lnk between transport and the economy. Fosgerau and Kveborg (2004) or Kveborg and Fosgerau (2004) analyses Dansh hstorcal trends of several couplng factors. Steer Daves Gleaves (2003) offers such a descrpton for a set of European countres. Ths knd of papers affords some explanatons of the couplng thanks to a decomposon of ths ssue n a set of factors. It shows some factors of couplng lke the ncreasng dstance of transport and some other factors of decouplng lke the densy n value of the producton or the average load factor of trucks. In ths paper, a decomposon s also purposed as one can see n the followng secton. The model Transport ntensy s often used to assess the couplng n transportaton economcs (Baum, 2000). Ths ndex of couplng s nspred by the energy ntensy, a common ndcator n energy economcs (Martn, 1988). Transport ntensy s by defnon the rato between the number of tons-klometers realzed n a country and the value of the GDP of ths country or TK TI = (2) GDP 5

7 where TI s the transport ntensy, TK s the number of tons-klometers made n country and GDP s the value of the GDP of the country n dollars or n euros. Transport ntensy represents the number of transport uns (ton-klometers) necessary to produce one un of GDP (one euro or one dollar). If transport ntensy ncreases or s constant, corresponds to a case of couplng. In the oppose, a case of a decreasng transport ntensy corresponds to a suaton of decouplng. Other uns can be used rather than the global number of ton-klometers for the assessment of the couplng. It was precsely the focus of Stead (2001) n whch a varety of ndcators s dscussed. The use of the volume of CO 2 emssons caused by transport gves the CO 2 ntensy of transports. One can also dstngush between freght and passenger transport. The freght transport ntensy s the number of ton-klometers made by freght vehcles necessary to produce one un of GDP. As road transport s the man source of CO 2 emssons, s then better to assess a road freght ntensy (notced RFI ) gven by RFI road _ TK GDP = (3) where road_tk s the number of ton-klometers made by road freght vehcles n the country. The use of the vehcle-klometers would even be better because the vehcle s the source of polluton. Vehcle-klometer s nevertheless a varable que dffcult to fnd n nternatonal statstcal database. It s why the road freght ntensy s used rather than the road traffc ntensy. Fgure 1 represents the evoluton of RFI for a European panel of countres from It shows that the road freght ntensy s ncreasng or constant for ths sample. It then says that these countres are cases of couplng. 6

8 Fgure 1 Evoluton of RFI for a European panel of countres (Eurostat, 2002 ; PWT, 2002). Followng the equaton (3), the road freght ntensy s decomposed nto a product of four ratos gvng the followng denty RFI = road _ TK TK TK T T IND IND GDP (4) where TK s the number of ton-klometers made by freght transport n country whatever the mode of transport, IND the ndustral producton of the country and T the number of transported tons. Therefore, accordng to equaton (4), RFI s a product of four factors. These factors are the followngs. The frst factor s the rato between the number of tons-klometers of freght made by road n a gven country and the number of tons-klometers made n the same country by all modes of freght transport. It s the modal share of road transport. The second factor corresponds to the number of transported tons n a country by un of ndustral producton. It could be nterpreted as the average weght of one un of ndustral producton or as the nverse of the densy n value of the ndustral producton. 7

9 The thrd factor corresponds to the average dstance made by a transported ton whatever s mode of transport. The fourth factor s equal to the rato between the ndustral producton and the GDP of a country. It s the share of the ndustry n the economy. Equaton (4) then yelds Raod freght ntensy = Road modal share. Average dstance. Average weght of $1 of ndustral producton. Share of the ndustry n GDP (5) Road freght ntensy was decomposed nto a product of four factors. These factors are dfferent levels of couplng or decouplng. The followng secton then nvestgates the evoluton of these four factors. Estmaton Ths secton estmates the evoluton of these four factors along wh the level of natonal ncome. In the frst sub-secton, the model specfcaton s presented. Next, a second subsecton provdes the results of econometrc estmatons. Model specfcaton The emprcal estmaton of the model s nspred by prevous papers on envronmental economcs made upon the lnk between pollutes and the economc growth. Ths set of papers concludes n the exstence of an nverted-u shape curve between polluton and the economc ncome (Holtz-Eakn and Selden, 1992 ; Shafk, 1994 ; Grossman and Krueger, 1995). Ths curve s also called the Envronmental Kuznets Curve (EKC). In the current case, ths paper estmates the relaton between natonal level of economc ncome and the four factors of couplng defned above. A quadratc model specfcaton s estmated. Ths model specfcaton s smlar to Shafk (1994) or Holtz-Eakn and Selden (1992). Estmated models are then the followngs. msh = α + β y + γ ysq + ε (6) msh msh msh 8

10 dst wgh = α + β y + γ ysq + ε (7) dst wgh dst wgh dst wgh = α + β y + γ ysq + ε (8) nd = α + β y + γ ysq + ε (9) nd nd where msh s the logarhm of the road modal share, wgh the logarhm of the average weght of the ndustral producton, dst the logarhm of the average dstance of transport, nd the logarhm of the share of the ndustry n the GDP, y the per capa ncome taken n logarhm and ysq the square of the logarhm of the per capa ncome. nd The data set s detaled n the appendx. For (6), (7) and (8), the sample s composed by the ffteen older European Unon member countres from 1982 to Model (9) also uses a panel data sample but has been enlarged to all OECD member countres and the perod. The panel nature of the sample mples pecular econometrc estmatons. Two model estmatons are performed. The frst one s a Fxed Effect Model (FEM) estmaton. Ths model ntroduces an ndvdual country-specfc constant term. The second one s a Random Effect Model (REM) estmaton. In ths model, the error-term s assumed to be the sum of two elements ε = µ + λ where the frst term s a country-specfc error-term and the second term a whe-nose. It s estmated by feasble, two steps generalzed least squares (GLS). Two statstcs are then computed to assess these models. The frst one s the Breusch and Pagan's Lagrange multpler statstc to test the presence of ndvdual specfc-effects. Ths statstc follows a 2 γ law at one degree of freedom. The null-hypothess of no-specfc-effect s rejected when ths statstc s superor to 3.84 (at 95% level). The second statstc s the Hausman statstc to test REM aganst FEM. The Hausman statstc (H) also follows γ 2 law at k-1 degrees of freedom wh k the number of regressors. Hgh values of H argues n favor of FEM. In the followng subsecton, the results of the two prevous tests are presented. Then, FEM or REM estmatons results are gven. 9

11 Results The results of both LM and Hausman tests fgure n table 1. The Lagrangan Multpler test shows that the four models present country-specfc effects. It then argues n favor of a FEM or a REM rather than for a classcal regresson whout group dummes. Furthermore, the Hausman test reveals that a fxed-effects model s more sgnfcant than a random-effect model for all the models except for model (9). The share of the ndustry among the GDP s the only model where a random effect model s estmated. Table 1 LM and Hausman Tests LM-Test Hausman Test LM-stat. Prob. H-stat. Prob. model (6) (modal spl) model (7) (average dstance) model (8) (average weght) model (9) (ndustry share) The followng table presents the results of the fxed effect models estmatons of models (6) to (8). The results are statstcally sgnfcant. Standard-errors of the estmated parameters are always sgnfcant. The Fsher statstc and the correlaton coeffcent also shows sgnfcant values. Table 2 FEM estmatons (standard-errors n parentheses) Varables modal spl average weght average dstance y (1.50) (21.56) (15.61) ysq (.08) (1.10) (.80) F R² Sample sze A REM s estmated for model (8). Results fgure n table 3. The estmaton s also hghly 10

12 sgnfcant as one could observe wh standard-errors. It confrms the correlaton between the level of natonal ncome and the levels of couplng. The followng subsecton gves an nterpretaton of these regressons. Table 3 REM estmatons (standard-errors n parentheses) Varables ndustry share y 5.76 (.20) ysq -.30 (.01) Intercept (.96) Sample sze 783 Interpretaton The results of above estmatons are nterpreted n term of elastces. One can get the elastcy thanks to the dervatve of the quadratc, estmated relaton between economc ncome and the factors of couplng. It gves that ξ n = ˆ β + ˆ γ y (10) n n where n ξ s the estmated ncome-elastcy of the factor of couplng n and prevously estmated parameters. βˆ n and γˆ n are the Fgure 2 presents the ncome-elastcy of the four factors of couplng along wh the level of natonal ncome. The frst factor of couplng corresponds to the share of the ndustry n the GDP (varable nd ). It frst presents a posve, decreasng elastcy untl the GDP per capa level of $15,000. Then, the ncome-elastcy becomes negatve. Ths graph llustrates a wellknown phenomenon that was ever ponted by Kuznets (1955) n s paper on ncome nequales. It shows that the ndustral sector share among the GDP of a country draws an nverted-u shape along wh the level of ncome. European Unon countres are then n a suaton where the ndustry accounts for a decreasng share of the GDP. e. n a suaton of 11

13 negatve ncome-elastcy of the ndustry share. It therefore corresponds to a level of decouplng. For varable msh, fgure 2 reveals a posve and slghtly ncreasng ncome-elastcy. Negatve values are observable for very low levels of ncome. One cannot nterpret such values because they correspond to ncome levels that are not sgnfcant n the sample. The man pont of the graph s the fact that the ncome-elastcy of road modal share s posve. It nduces that a rse of natonal ncome level nvolves a rse of the road modal share. European ndustry has known crucal changes these last twenty years among them a structural modfcaton of the producton. Heavy goods productons such as coal or steel productons were often left for lghter ndustral productons. Ths modfcaton of the ndustral producton structure produced a structural effect over the modal spl of the transport market because heavy products are more lkely to be transported by ral than lghter products. Furthermore, the development of the Just-n-Tme manufacturng organzaton nduced a hgh demand for quck, relable transports. At the same tme, road transport experenced a lberalzaton of s ndustry. These two facts produce an ncrease of the road transport competveness n comparson to the ralway alternatve that s stll a publc monopolstc ndustry n a large majory of European countres. Structural changes of European ndustry and the worsenng competveness of ralway transport explans that the road-modal share factor s a level of couplng. Fgure 2 also represents the ncome-elastcy of the ndustral producton weght (varable wgh ). One should frst observe a negatve and hghly ncreasng ncome-elastcy. Then, the ncome-elastcy becomes posve snce a level of per capa ncome of $20,000. The man pont of ths graph s the negatve but ncreasng ncome-elastcy. It says that the average weght of the ndustral producton decreases along wh the rse of the natonal ncome. Ths rse goes on untl a progressve level of saturaton where the average weght does not change anymore. Actually, the rght-sde of the graph s not very sgnfcant. One should get n mnd that the most representatve part of these graphs s roughly comprsed between ncome values of $12,000 and $20,000. It s why the average weght of the ndustral producton has to be understood as a factor of decouplng. Ths factor has to be lnked wh the restructuraton of European ndustry prevously mentoned to explan changes of road modal share. 12

14 Fgure 2 Estmated ncome-elastces of the factors of couplng Varable: nd Varable: msh 0,3 0,2 0, , ,2-0,3-0,4 0,5 0,4 0,3 0,2 0, ,1-0,2 Varable: wgh Varable: dst ,5 3 2,5 2 1,5 1 0, , Fnally, fgure 2 represents the ncome-elastcy of the average dstance of transport (varable dst ). Ths fgure ponts out a posve, decreasng ncome-elastcy. It states that the rse of the natonal ncome goes wh an ncrease of the average dstance of transport. Another pont s that the ncome-elastcy s negatve beyond the value of $23,000. It means that the average dstance of transport reaches a maxmum for the value of $23,000. Actually, one should frst get n mnd the low sgnfcance of ncome values after $20,000. Furthermore, one can nterpret ths phenomenon n term of geographc constrant. It does not mean that the average dstance of transport wll decrease beyond ths value. The average dstance of domestc 13

15 transport does not grow anymore because cannot grow anymore nsde a natonal, physcally constraned terrory. The sample s made by the ffteen older European Unon countres among whch many small countres can be found. It s then not surprsng to reach such a saturaton pont. Therefore, one should nterpret the average dstance as a factor of couplng. The ncluson of nternatonal transport n the analyss would even more clearly makes as a factor of couplng. The nterpretaton of these regressons reveals two levels of couplng and two levels of decouplng. Factors of couplng are the rse of the average dstance of transport and the ncreasng modal share of the road n domestc transports. The two factors of decouplng are the decrease to the average weght of the ndustral producton and the declne of the ndustry share n the GDP. Concluson Ths paper nvestgates the lnk between transport and the economc growth. Road freght transport ntensy s decomposed nto four levels of couplng. A European panel data estmaton of ths decomposon reveals two factors of couplng and two factors of decouplng. Factors of couplng are the ncreasng dstance of transport and the growng modal share of road transport. Inversely, the declnng share of the ndustry n the GDP and the decreasng weght of the ndustral producton are two factors of decouplng. These conclusons are consstent wh most of the results found n the lerature. For nstance, the rse of the average dstance of transport has often been dentfed as an explanaton of the couplng. The decreasng weght of the ndustry n the economy has also been observed n a many papers. Otherwse, ths paper s consstent wh the dea accordng whch the elastcy of transport wh respect to the economc producton s not constant. These results should however be completed by further works. One of these can be the ncluson of nternatonal transport n the analyss. It has ever been mentoned that the average dstance of transport would certanly be a stronger factor of couplng. Another drecton that future researches can follow s n the enlargement of ths analyss to other contexts. Ths paper deals wh European countres from 1982 to It should be nterestng to apply ths model to other countres from other contnents to nvestgate the evoluton of these factors. A temporal enlargement can also be useful and would certanly gves more consstent results. 14

16 References Ang, B. W. Zhang, F. Q "A Survey of ndex decomposon analyss and envronmental studes", Energy, 25: Aschauer, D. A "Is publc expendure productve?", Journal of Monetary Economcs, 23(2): Baum, H "Decouplng transport ntensy form economc growth" n ECMT, Key ssues for transport beyond th nternatonal symposum on theory and practce n transport economcs. Pars: OECD, pp Baum, H. Kurte, J "Transport and economc development" n ECMT, Transport and economc development. Pars: OECD, pp CITEPA, Emssons dans l'ar en France: Substances mplquées dans le phénomène d'accrossement de l'effet de serre. Pars: CITEPA, 24 p. Eurostat, Everythng on transports. Data CD-ROM. Brussels: European Commsson. European Commsson, European Transport polcy for 2010: tme to decde. Brussels: European Commsson, 124 p. Fogel, R. W "A quantatve approach to the study of ralroads n Amercan economc growth: A report of some prelmnary fndngs", The Journal of Economc Hstory, 22(2): Fosgerau, M. Kveborg, O "A revew of some crcal assumptons n the relatonshp between economc actvy and freght transport", Internatonal Journal of Transports Economcs, 31(2): Gabella-Latrelle, C Le modèle qunqun fret, un modèle de smulaton à l'horzon 2015 des flux de transport de marchandses. Tome 1 : Le modèle qunqun fret, un nstrument d'ade à la décson. Thèse de doctorat de scences économques. Lyon: Unversé Lumère Lyon 2, 280 p. + app. 15

17 Grossman, G. M. Krueger, A. B "Economc growth and the envronment", Quarterly Journal of Economcs, 110(2): Heston, A. Summers, R. Aten, B Penn World Table Verson 6.1. Phladelpha: Center for Internatonal Comparsons at the Unversy of Pennsylvana. Holtz-Eakn, D. Selden, T. M "Stokng the fres? CO 2 emssons and economc growth", NBER Workng paper #4248, Washngton: NBER Workng paper seres, 38 p. Intergovernmental Panel on Clmate Change, Clmate Change 2001: The Scentfc Bass. Cambrdge: Cambrdge Unversy Press, 881 p. Jognaux, G. Verny, J "Le découplage entre transport de marchandses et crossance: organsatons productves, localsatons et demande de transport", XXXIXth ASRDL Conference, Lyon, 1-3 September. Kang, N. Shpper L "Energy trends n the Japanese transportaton sector", Transport Polcy, 3(1/2): Kulshreshtha, M. Nag, B "Strucuture and demand of non-suburban passenger travel demand n Indan ralways", Transportaton, 27: Kulshreshtha, M. Nag, B. Kulshrestha, M "A multvarate contegratng vector auto regressve model of freght transport demand: evdence from Indan ralways", Transportaton research, 35A(1): Kuznets, S "Economc growth and ncome nequaly", The Amercan Economc Revew, 45(1): Kveborg, M. Fosgerau, M "Explanng the decouplng of freght traffc growth and economc growth", European Transport Conference, Strasbourg, 4-6 October. Kwon, T.-H "Decomposon of factors determnng the trend of CO 2 emssons from car travel n Great-Bran", Ecologcal Economcs, 53: Lahr, K. Yao, W "The predctve power of an expermental transportaton output ndex", Appled Economcs Letters, 11:

18 Lenormand, A Prévsons dans les modèles contégrés avec rupture: Applcaton à la demande de transports terrestres de marchandses et de voyageurs. Thèse pour le doctorat en scences-économques. Pars: Unversé Pars 1 Panthéon-Sorbonne, 583 p. Martn, J.-M "L'ntensé énergétque de l'actvé économque dans les pays ndustralsés: les évolutons de très longue pérode lvrent-elles des ensegnements utles?", Econome et Socété, 3-EN: McKnnon, A. Woodburn, A "Logstcal restructurng and road freght growth : An emprcal assessment", Transportaton, 23(2): Meersman, H. Van de Voorde, E "Is Freght Transport Growth Inevable?" n ECMT, Whch changes for transport n the next century. 14th nternatonal synosum of theory and practce. Pars: OECD, pp Meyer, F La concurrence ral-route: Analyse économétrque des trafcs de marchandses et des perspectves du transport combné. Thèse pour le doctorat en scenceséconomques. Pars: Unversé Pars 1 Panthéon-Sorbonne, 515 p. OECD, Annual Natonal Accounts for OECD Member Countres - Data from 1970 onwards: GDP by output at constant prces. Pars: OECD. REDEFINE, Relatonshp between Demand for Freght-transport and Industral Effects. Summary Report. Rotterdam: NEI. SACTRA, Transport and the economy: full report. London: SACTRA, 282 p. Schäfer, A "Structural change n energy use", Energy Polcy, 33: Schäfer, A. Vctor, D. G "The future mobly of the world populaton", Transportaton research, Vol. 34A(3) : Schpper, L. Scholl, L. Prce, L "Energy use and carbon emssons from freght n 10 ndustralzed countres: an anlyss of trends from 1973 to 1992", Transportaton Research, 2D(1):

19 Shafk, N "Economc development and envronmental qualy: An econometrc analyss", Oxford Economc Papers, 46: Stead, D "Transport ntensy n Europe - ndcators and trends", Transport Polcy, 8: SPRITE, Separatng the Intensy of Transport from Economc Growth. Fnal Publshng Report. Leeds: ITS, 42 p. Steer Daves Gleaves, Freght transport ntensy of producton and consumpton. London : Steer Daves Gleaves, 144 p. Yao, V. W "The causal lnkages between freght transport and economc fluctuatons", Internatonal Journal of Transport Economcs, 32(2): Appendx: The data set The panel data sample s composed by economc data and by transport data. Transport data are gven by Eurostat (2002) NewCronos database. More precsely, the varable road_tk s gven by the table B-Road Transport V3-09. Natonal annual transport by dstance class and type of carrage (Mo Tkm). It s composed by the ffteen older European Unon member countres from 1982 to One should nevertheless remark several blanks. Data are only avalable snce the country adheson to the Unon. Furthermore, some countres present several mssng data. The ralway varable s gven by the table A-Ral Transport V3-05. Natonal annual transport by dstance class and group of goods (1000 T, Mo Tkm). The varable TK s gven by the sum of the prevous varables. The varable T s also gven by the sum of road and ral transport seres. The road transport seres s presented n the table B- Road Transport V3-08. Natonal annual transport by dstance class, type of carrage and group of goods (1000T) whereas table A-Ral Transport V3-05. Natonal annual transport by dstance class and group of goods (1000 T, Mo Tkm) gves data for ralways volume of transport. It the excludes from the analyss nland water-ways domestc transport even f ths mode of transport s not nsgnfcant for countres lke Germany, Netherlands or Belgum. Its share s however declnng n comparson wh road transport. The analyss s not based by nland-water ways transport omsson: road modal share s a factor of couplng. Furthermore, n a majory of countres of the sample, ths mode of transport s nsgnfcant. 18

20 Economc data are gven by other database. The share of the ndustry n the GDP s gven by the OECD table Annual Natonal Accounts for OECD Member Countres - Data from 1970 onwards: GDP by output at constant prces (OECD, 2004). OECD database presents several blanks. For nstance, data for Swzerland or Ireland are always mssng. Furthermore, data are not gven before the adheson to the organzaton. Fnally, ncome data have been taken n Purchasng Power Pary (PPP). PPP ncome data are provded by the Penn World Tables of the Center for Internatonal Comparsons of the Unversy of Pennsylvana. Actually, we use the latest verson of ths database or the PWT Verson 6.1 (Heston, Summers and Aten, 2002). These data are taken for all OECD countres from 1970 to