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Energy Policy 35 (2007) 6036–6045

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Impacts of biodiesel production on Croatian economy

Biljana Kulisica,b,�, Efstratios Loizouc, Stelios Rozakisd, Velimir Segona

aDepartment for Renewable Energy Sources and Energy Efficiency, Energy Institute Hrvoje Pozar, Savska 163, HR-10000 Zagreb, CroatiabMediterranean Agronomic Institute Chania—MAICh, CIHEAM—International Centre for Advanced Mediterranean Agronomic Studies, GreececDepartment of Agricultural Products Marketing and Quality Control, Technological Education Institute (TEI) of Western Macedonia, Greece

dDepartment of Agricultural Economics and Rural Development, Agricultural University of Athens, Greece

Available online 4 October 2007

Abstract

The aim of this paper is to assess the direct and indirect impacts on a national economy from biodiesel (rapeseed methyl ester (RME))

production using input–output (I–O) analysis. Biodiesel development in Croatia is used as a case study. For Croatia, as for many other

countries in Europe, biodiesel is a new activity not included in the existing I–O sectoral accounts. For this reason the I–O table has to be

modified accordingly before being able to quantify the effect of an exogenous demand for biodiesel. Impacts in terms of output, income

and employment lead to the conclusion that biodiesel production could have significant positive net impact on the Croatian economy

despite the high level of subsidies for rapeseed growing.

r 2007 Published by Elsevier Ltd.

Keywords: Biodiesel; Input–output analysis; Biodiesel production block

1. Introduction

Recent trends in the oil market are obliging nationaleconomies to consider alternative energy sources in orderto increase energy security and also mitigate the effects ofoil rising prices. The transport sector, particularly passen-ger cars, is directly exposed to changes in oil prices. Inaddition, there is growing concern with respect to globalenvironmental threats causing governments to committhemselves to international agreements and implementnational environmental laws, especially in Europe. EUmembers as well as candidate countries are eitherconsidering or already involved in production of liquidfuels from biomass, such as oilseeds, waste oil (biodiesel)and sugar, starch and cellulose crops (ethanol), conformingto EU directives.

The option of biodiesel production in Croatia has beenunder consideration since 1997 (Domac et al., 1998).Namely, according to the optimistic scenario (Domac

e front matter r 2007 Published by Elsevier Ltd.

pol.2007.08.025

ing author. Department for Renewable Energy Sources

ciency, Energy Institute Hrvoje Pozar, Savska 163, HR-

Croatia. Tel.: +385 1 6326169, fax: +385 1 6040599.

ess: bkulisic@eihp.hr (B. Kulisic).

et al., 2001), which assumes that Croatia will join theEuropean Union by 2007, Croatia should use approxi-mately 40 000 tons of biodiesel by then. The projectionsstate that at least 15% of Croatian energy needs will bedelivered from biomass and waste by 2030 (Domac et al.,1998). Accession negotiations between the Republic ofCroatia and the European Union opened on 3 October2005.However, all studies related to biodiesel project feasi-

bility in Croatia until now have been carried out fromeither a technical (i.e. Kricka et al., 2001b) or investors’(Kricka et al., 2001a) point of view. Biodiesel projects werenot seen as competitive—the price of biodiesel, at aminimum forecast, was 10% higher than the price ofpetroleum diesel, which is significant in terms of Croatianconsumers’ purchasing power. Nevertheless, those calcula-tions were made at the time when the oil price was $28 perbarrel, not exceeding $70 as it is in the time of writing ($60average Brent price is expected in 2006).In order to make biofuels competitive, subsidies at a

significant level are required. Minimal subsidy level mayvary depending on the type of biofuel, but, in general, taxexemption from petroleum products’ special excise taxsuffices to compensate excessive cost of biofuels compared

ARTICLE IN PRESSB. Kulisic et al. / Energy Policy 35 (2007) 6036–6045 6037

with fossil fuels (Rozakis and Sourie, 2005). In otherwords, a new economic activity may be undertaken thanksto subsidization as elsewhere in Europe, but estimatesreport that agents’ economic surplus is less than thebudgetary amount earmarked for biofuels (Sourie et al.,2005). These estimates usually take into account only directimpacts, thus underestimating social gain in terms ofsurplus, income and job creation. For this reason, weattempt to assess direct and indirect impacts on thenational economy from biofuel production using inpu-t–output (I–O) analysis.

As a matter of fact, in 2004, the Croatian Governmentaddressed the United Nations Industry DevelopmentOrganisation (UNIDO) for funding and technical assis-tance for a feasibility study on biodiesel productionnationwide. The UNIDO suggested, among other things,the use of an I–O analysis as the methodology for assessingthe macroeconomic impact of biodiesel production. Thisresearch was mainly based on the data used for theUNIDO study.

In order to implement a preliminary I–O analysis of theCroatian economy, we proceed to construct a biodieselsector I–O block and then to integrate it in the nationalI–O table. Finally we use this table to assess the impacts onthe economy assuming that Croatia will comply with theEU ‘‘Biofuels Directive’’—Directive 2003/30/EC, whichrecommends proportions of biofuels and other renewablefuels placed on the national market (2% and 5.75%calculated on the basis of the energy content, of all petroland diesel for transport purposes placed on their marketsby 31 December 2005 and 2010, respectively). Resultspresented in this paper should be seen with caution as theyonly approximate real impacts as the latest national I–Otable available for this exercise is dated in 1997.1 For thisreason, special attention is given in the detailed representa-tion of biodiesel production so that this exercise can bereplicated after updating the national I–O table to reflectmajor structural changes that happened during the lastdecade in the Croatian economy.

The next section outlines the basic principles of I–Oimpact analysis. Section 3 details the so-called biodieselproduction block construction (OUN, 1999), that is a self-sufficient biodiesel-only producing economy, tracing downinter-industry transactions in the entire production chain(rapeseed growing, storage, oil pressing, trans-esterifica-tion, blending, wholesale and retail sale). The impact onthe Croatian economy will be assessed after the aggrega-

1It is actually an experimental I–O table where 1987’s I–O table was

updated with the RAS method and, as the authors stress themselves,

should be used as guideline only (Gorjan et al., 2001). In early 2003, The

Central Bureau of Statistics of the Republic of Croatia delivered Statistical

Standards for Structural-Business Research of Industry (IND-21/SPS)

based on the Law on Official Statistics (Gazette, No. 52/94) upon which

data collection became harmonized with those of the EU and OUN. The

Croatian Statistical Bureau is currently in the phase of data collection for

building an I–O table for 2004 whose completion is expected to be no

sooner than the year 2006 (Gorjan, 2005).

tion of the biodiesel block in the national I–O table aspresented in Section 4. Results quantify the impact on theeconomy and allow guidelines and recommendations togovernmental policies regarding biodiesel production inCroatia, provided in the conclusions.

2. I–O analysis: methodological overview

Attempting to assess possible impacts from the use ofbiodiesel in the Croatian economy, I–O analysis wasemployed. By exploiting the I–O methodology, integratedanalysis can be performed by assessing the impacts on thewhole economy; that is, to estimate the direct and indirectinterrelationships and impacts of the biodiesel sector on allother sectors. I–O analysis framework was introduced byWassily Leontief in the late 1930s (Leontief, 1986).The basic Leontief I–O model is a systematic method

that quantifies and records the productive relations amongthe different sectors of economic activity, in the frameworkof a complicated economy. Apart from the relative size ofthe economic system, which can vary from a nationaleconomy to regional or urban economies (regionalmodels), the methodological approach remains the same.In its most basic form, an I–O model consists of a system oflinear equations containing productive coefficients whichdescribe the relation between inputs used by the sector andthe final product. Its specific structural characteristics arethus reflected in the numerical magnitude of the coefficientsof these equations.I–O analysis is offered as a quantitative tool to analysts

and can contribute substantially to the understanding of thenature of a national or regional economy. It traces out thesources of each sector’s inputs, whether they are purchasedfrom other firms in the economy, imported or contributed bylabour (wages and salaries). It also provides a breakdown ofeach sector’s output, with sales to other industries and offinal demand (consumption, gross fixed capital formationand exports). Thus, portraying the total economy by anumber of sectors, I–O models assess the effects of changesin one sector on all other sectors of the economy, both thedirect and indirect impacts. I–O analysis can capture theindirect effects and the impacts due to general structuralchanges. Therefore, this approach will provide evidence onthe size of the effect on total employment, income and grossoutput, by employing a final demand-based approach. Theflexibility of the I–O model makes it ideally suited forprojections of economic activity, impact analysis or structur-al and technical change trace.2

Utilizing the information from an I–O table, the well-known Leontief model in its general form can be derived asshown below in matrix form:

X ¼ AX þ Y , (1)

2Detailed presentation of the I–O analysis can be found, among others,

at Richardson (1972), Mattas et al. (1984), Miller and Blair (1985) and

Leontief (1986).

ARTICLE IN PRESSB. Kulisic et al. / Energy Policy 35 (2007) 6036–60456038

where A is the matrix of technical coefficients, X the vectorof sectoral output and Y the vector of sectoral finaldemand components. Eq. (1) can be rewritten as

X ¼ ðI � AÞ�1Y , (2)

where I is an identity matrix. The solution of system 2constitutes the basic solution of the Leontief’s I–O system3,where any exogenous changes in the final demand vector Y

induce changes in the total gross output X of the economy.Matrix (I–A)�1 is the so-called matrix of interdependencecoefficients or the Leontief inverse. Each element of thatmatrix indicates the total (direct and indirect) requirementsof sector i per unit of final demand for the output of sectorj. With the use of Leontief inverse and direct coefficientsfor employment and household income, the employment,income and output multipliers can be estimated (see Millerand Blair, 1985).

3. Building the biodiesel production block

Introduction of a new industry can change the existingtechnical structure and transaction flow among otherindustries. There are two approaches (Miller and Blair,1985, p. 333) of introducing a new production activity intoan economic area: (a) through a new final-demand vectoronly and (b) through the addition of new elements intothe technical coefficient table for the economy. Althoughthe approaches differ in specification for influencing themagnitude of the new economic activity on the wholeeconomy, they both assume already existing technicalcoefficients. For the sake of this analysis, given thereliability of the structure of the existing I–O table andno real production of biodiesel, the biodiesel productionblock served as a platform for the first approach as it gavemore conservative results.

In the absence of a reliable I–O table and official datacollection for Croatia as well as the non-existence of abiodiesel sector, the most appropriate approach to estimatethe effects of biodiesel production is to create a biodieselproduction block based on the expert data (Appendix B:Model assumptions). SNA (OUN, 1999, p. 186) recom-mends ‘‘to make the adjustments more systematic (i.e. totake into account inter-industrial relationships), compilersshould set up the most clearly separable blocks of sectorsand assign them to separate groups of I–O statisticiansresponsible for balancing’’. By having a separate biodieselproduction block, it would be possible to use it foraggregation in both an existing and new I–O table or,when the real data become available, it can be corrected

3This model, the standard I-O model, is often referred to as the demand-

driven model since it relates gross sectoral output with final demand

changes (for any new sectoral final demand, the new total output can be

estimated). Contrary to the demand-driven model, the supply-driven

model relates sectoral gross output with primary inputs, with which,

instead of estimating direct input coefficients, one can estimate direct-

output coefficients.

and aggregated into the real I–O table. Moreover, theblock has flexibility towards changes in the productionflow (i.e. importing rapeseed oil instead of domesticproduction).The cornerstone of compiling the biodiesel production

block is the commodity-flow approach (OUN, 1999),which allows applying engineering information to estimateinput flows and, subsequently, intermediate consumption,for establishments of which only their outputs are knowndue to the properties of linear production function withconstant input coefficients. The biodiesel production blockfollows the basic methodology of SNA (Stone’s model(OUN, 2000)) as it is not certain what would be thenational adjustments of the methodology for constructingthe future Croatian I–O table. Additional assumptionswere also necessary. Whatever the magnitude or geogra-phical boundary of the economy in question, the compilingprinciples stay the same. Thus, it has been assumed that thebiodiesel production block represents a self-sufficienteconomy that produces only biodiesel. This means thatthe total supply at purchasers’ prices is equal to the totaloutput of industries (total product supply at basic prices)plus trade, transport margins and taxes, less subsidies onproduct (VAT).The outline of the methodology sequence for building

the biodiesel production block to reach the productivecoefficients contains the following three basic steps.Firstly, the biodiesel production chain with its outputs is

identified and broken down into the production stages andestablishments, the smaller statistical unit of SNA (Fig. 1)followed by categorizing the inputs necessary for produ-cing each output of the establishment. Inputs of thebiodiesel processing chain flow through the block, butthere are also other inputs required to produce those basicoutputs of each establishment. All inputs are organizedaccording to the group they affect—either inter-industry orvalue added group. Since the data were collected top down,market distortions (i.e. trade and transport margins, fiscalburdens) had to be removed in order to obtain productiveflow as pure as possible. Thus, each input’s price is levelledto its basic price by removing trade and transport marginsand taxes less subsidies on product (VAT of 22%). Totaluse equals the sum of intermediate consumption, finalconsumption expenditure and gross capital formation.Secondly, since there is no actual local production of

biodiesel (considering Croatian conditions detailed inAppendix B), it has been assumed that the factory isvertically integrated, rapeseed growing in a neighbouringarea, no profit from by-products (Stone’s negative transfermethod), all fixed assets were newly purchased andcalculated with the perpetuary inventory method (QuangViet., 2000). The main target while setting up theassumptions was to make the block maximally adjustablefor the national peculiarities.Thirdly, the commodity flow table was created to ensure

balanced supply and use of the inputs and/or outputs ofthe biodiesel production block. The conventional form of

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Fig. 1. Biodiesel production chain according to the establishments, outputs and by-products (BD05: mix biodiesel 5%–fossil diesel 95%).

Table 1

Biodiesel production block properties of the adjusted conventional form of I–O model

Products at purchasers’ prices Intermediate

consumption of

industries

Final

expenditures

Gross capital

formation

Total use of

domestic products

at basic prices

Total

economy

(1) (2) (3) (4) (5) (6) (7)

(1) Product 1

(2) Product 2

(3) Trade and transport margins

(4) Payable VAT

(5) Total uses at purchasers’ prices

(6) Total gross value added/GDP

(7) Gross value added at basic prices

(8) Taxes less subsidies on production

(9) Total industry output at producers

prices

B. Kulisic et al. / Energy Policy 35 (2007) 6036–6045 6039

the I–O model (OUN, 1999) was adjusted for assumptionsof the block (Table 1).

The existing fiscal system was applied (subsidies fromagricultural policy, excise on mineral fuels, HAC fee,4 22%of VAT, etc.) and, for the trade and transport margins, alump sum of 15% was used as a best estimate.

The final outcome was the biodiesel production block,an asymmetric 20� 7 matrix where the seven establish-ments represent the biodiesel production chain and 14industries are supporting its production (Appendix A,Table A1). To reach the basic property of an I–O table—symmetry—the self-sufficient biodiesel-only producingeconomy has to open to imports of the supportingindustries. Thus, the difference between the biodieselproduction block’s input and output sums represents thenew demand for inputs of RME production. The new finaldemand vector is extracted from the biodiesel productionblock and adjusted for prices (2004 into 1997 price index).It is important to point out that, at that time, fossil diesel’sbasic price was 35% of the 2004 price (1997: 1.27HRK5/land 2004: 3.66 /l).

The last step was classification of establishmentsaccording to the International System of Industry Classi-fication (ISIC) and inputs according to the Commodity byProduction Classification (CPC) and extraction of the finaldemand vector (Appendix A, Table A2). The new demand

4HAC fee: Croatian Highways fee that pays off the constructions of

highways.5The average exchange rate for years 1997 and 2004: 1h: 6.9607HRK

and 1h: 7.4967HRK, respectively.

vector represents RME production whose output is fullysold to the mineral diesel sector for blending. Biodieselconsumption has the same pattern as the consumption ofthe mineral diesel; thus, 5% of fossil diesel is disaggregatedand attributed to biodiesel. As the Stone’s model does notexplicitly state employment, the data for employment wererecalculated separately.

4. Aggregation of biodiesel block to the I–O table

The latest available published national I–O table forCroatia (1997) was used for the impact measurement; itconsists of by 60 sectors of economic activity and wascompiled according to the Standard Industrial Classifica-tion (SIC) system. For the needs of the analysis, small andless important (in terms of output and employmentcontribution) sectors of the economy were aggregatedand the 60 sectors scheme converted to 40 sectors. For thecalculation of the income multipliers, the compensation ofemployees’ vector was used from the I–O table, and for theemployment multipliers sectoral employment data wereobtained from the statistical office.The identification and construction of the Biodiesel

sector was one of the main objectives of the study.Biodiesel sector did not exist in the available I–O table aspreviously mentioned, nor was it included in the existingpetroleum sector. Thus, a case-specific survey was sched-uled and conducted for this purpose; the transactions (rowand column) with all other sectors in the economy wereidentified according to the current national situation andthe EU regulations. The survey and the compilation of the

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Table 2

Important sectors of the Croatian economy according to I–O multipliers

Sector OM R Type I

EM

R Type I

IM

R

Agriculture 1.7819 20 3.0518 3 3.3186 1

Food and

beverages

2.0810 8 2.1497 8 1.9902 8

Coke, refined

petroleum

2.1565 5 3.7546 1 2.5740 3

Biodiesel 2.4897 2 3.3255 2 1.6134 25

Electricity, gas,

water,

recycling

2.1468 6 2.1802 7 1.9384 12

Construction 2.2450 3 2.4354 5 2.4211 4

B. Kulisic et al. / Energy Policy 35 (2007) 6036–60456040

biodiesel sector followed the methodology described in theUnited Nations I–O manual (OUN, 1999) as explained inSection 2.

The next two important objectives were the identificationof the important sectors of the Croatian economy, and thenthe assessment of possible impacts due to the introductionof biodiesel. In order to identify the importance of abiodiesel sector, the I–O linkage coefficients were used.Furthermore, in assessing possible impacts on the Croatianeconomy from the introduction and further use ofbiodiesel, the multipliers were used along with a scenarioanalysis formed following national and EU discussions forthe use of biodiesel.

Financial

intermediation

3.0399 1 3.0399 4 3.0399 2

Services 2.1268 7 2.0569 10 2.0589 6

*OM ¼ output multiplier; EM ¼ employment multiplier; IM ¼ income

multiplier; R ¼ ranking.

Table 3

Total impacts due to a hypothetical increase in the use of biodiesel from

5% to 10%

Positive

impacts

Negative

impacts

Net

impacts

Output (in million HRK) 1225.7 159.3 1066.5

Income (in million HRK) 251.9 26.0 225.9

Employment (in

employees)

2329 382 1947

5. Impact assessment

Having estimated the I–O linkage, coefficients becomeobtainable to estimate any output, income and employ-ment impacts (both direct and indirect) on the economydue to an expansion in the use of biodiesel, either fordomestic consumption or for export. The computationalmethod of assessing the impacts is shown in Appendix C. Ahypothetical scenario assumes an increase in the produc-tion and use of biodiesel from the base-case 5% to 10% ofthe fossil diesel—that is, the current level is doubled. Usingthe Croatian I–O table as finalized, after making theadjustments, the relative linkage coefficients were esti-mated6. The classification scheme of the used I–O consistedof 40 sectors of economic activity. The results of themultipliers analysis, for all sectors, are shown in Table A3(Appendix A); Table 2 presents the most important sectorsof the Croatian economy according to their multipliermagnitude.

In terms of output effect, Financial Intermediationpresents the highest backward linkage relationships. Witha multiplier7 (3.0399) ranking in the first place, thisindicates that an exogenous change in the final demandof the specific sector has the ability to induce multipleimpacts in the output of all sectors in the Croatianeconomy. Specifically, a monetary unit exogenous changein the final demand of Financial Intermediation will inducean increase in the total output of the whole economy(all sectors) by 3.099 monetary units.

The Biodiesel sector as it can be seen presents the secondhighest multiplier in the economy, despite its relatively lowtotal output. The high multiplier (2.4897) indicates theinterrelationships of the sector with all other sectors and itsability to induce direct and indirect mainly economicactivity. Thus, any investments in the Biodiesel sector willproduce about twice and a half output in the wholeeconomy. Construction and coke-petroleum sectors alsopresent high output multipliers. As it can be seen, the

6Computations were performed using the GAUSS software package.7For the suitability and advantages of using I–O multipliers as well as

possible problems and drawbacks where their use should be seen with

caution, see among others Hughes (2003).

biodiesel sector presents higher linkages than the regularpetroleum sector. The influential transactions of thebiodiesel sector with agriculture—it is used as input forbiodiesel—might explain the strongest linkages of biodieselcompared with regular diesel.In terms of employment, petroleum and biodiesel sectors

present the highest type I multipliers8; that is, an increaseby one person in the current employment level of the twosectors will increase the employment of the whole economyby 3.7 and 3.3 persons, respectively. However, in terms ofsimple multipliers, the two sectors do not present highmultipliers. Considering income multipliers, it can be seenthat the ability of the biodiesel sector to generate house-hold income in the economy is not very important, whereasthe petroleum sector’s ability is much higher. Agricultureand financial intermediation are the sectors with thehighest income multipliers.The results of the scenario analysis are shown in Table 3.

In order to examine the ability of the biodiesel sector togenerate economic activity in the economy, it was assumedthat the use of biodiesel will be increased to 10% of fossildiesel use—that is, a 100% increase of the current level.Results indicate that the economy will benefit from such a

8See, among others, in Miller and Blair (1985) the computation and

interpretation difference between type I and simple multipliers.

ARTICLE IN PRESSB. Kulisic et al. / Energy Policy 35 (2007) 6036–6045 6041

case, because a considerable increase in terms of output,income and employment will be observed. For example,the application of such a case will generate 2 329 newjobs in the biodiesel sector and all others related to it.However, due to the shift in biodiesel use, the economy willface some negative impacts; this will happen because anumber of people, income and output will be shifted fromthe regular petroleum sector. These results are shown inTable 3, as well as the net impact on the Croatianeconomy.

6. Conclusions

Considering the deficiencies of the available CroatianI–O table and the lack of a biodiesel sector, the presentstudy attempted to integrate biodiesel information in theI–O table, and then to assess impacts of a biodiesel largescale project to the economy. This analysis points out whatwould be the possible direct impact of the biodieselproduction on the Croatian economy given certainassumptions and data availability. Overall, the directcontribution from the biodiesel production to the GDPamounts to 304 million HRK, taking into account thedecrease of 112 million HRK due to the currentagricultural policy. This maximal contribution of havingthe whole production process from domestic sources couldbe lowered for imports or/and substitution effect in the realworld circumstances. However, given the existing I–Otable, this analysis has shown that impacts of biodieselproject development of 50 000 t in size are not only thosepotential 304 million HRK of gross value added, but alsoin positive net impacts due to its high multiplier effect of2.4897. The new final demand originated from biodieselproduction created an additional 610 million HRK, out ofwhich 239 million HRK is allocated among industrysectors and 371 million HRK among trade and transportmargins and taxes, less subsidies on production.

For this reason, biodiesel production is worthwhile tosubsidize as it seems to be beneficial in terms of industrydevelopment, income and labour direct and indirect effects,despite the significant amount of funding given throughagricultural subsidies. However, one should be careful ininterpreting the results as, in reality, the Croatian economymight not meet the net final demand from its own sourcesand the multiplier effect could be outsourced to theexporting economies. Nevertheless, the availability of asocial accounting matrix in order to perform a SAMimpact analysis instead of an I–O could give more detailedresults for the role of biodiesel sector. Future researchshould pursue possible impacts in terms of employment,household income or net tax benefits for the economy inorder to further clarify the economic and social role ofbiodiesel production. The methodology of constructing abiodiesel production block for the purposes of I–O andSAM impact analysis may be applicable to any countrywhere biodiesel is a new activity.

Appendix A

See Tables A1–A3.

Appendix B

Model assumptions based on the expert guidelines ofbiodiesel production to satisfy the EU Biodiesel Directivewere

�

Quantity: 50 000 t. � Origin: rapeseed. � The rapeseed growing occurs on neglected agricultural

land, and thus no substitution effect with competitioncrops.

� All existing Eurodiesel will be blended with 5% of

biodiesel and it will not be specially labelled.

� The production will be vertically integrated and it will

occur in an existing oil-processing plant (buildings andland existing).

� The gas station price of biodiesel blend BD05 has to be

the same as the one of Eurodiesel.

� The Government will not set an excise tax and HAC

(Croatian Highway Fee) fee on the biodiesel and it willsubsidize the price difference, if existing.

� The guidelines point out important information: there is

actually no change in the final demand since the totalEurodiesel final consumption will be replaced withBD95 at the same final price. However, this reasoningwill be ignored for the time being.

Appendix C

The methodology to assess the impacts in terms ofoutput, household income and employment is describedbelow. The total change in the output of the regionaleconomy due to a given change in the final demand ofsector j is estimated using the following equation:

DX ¼ OMj � DFDj, (3)

where X is the total output of the regional economy, OM isthe output multiplier and FD is the final demand (D is thechange). The total change in the output of the economy inthe case where the final demand of n sectors changes isestimated by the following equation:

DXð1�1Þ¼ eð1�40Þ

� OMð40�1Þ

�DFDð40�1Þ

� �. (4)

In terms of household income, the total income changein the regional economy due to a given change in the finaldemand of sector j is estimated as

DH ¼ HDIEj � DFDj (5)

where H is the household income and HDIE is thehousehold direct and indirect (total) coefficient or simpleincome multiplier of sector j. The total change in the

ARTIC

LEIN

PRES

S

Table A1

Biodiesel production block: I–O model (in million HRK)

Products at

purchasers’ prices

Intermediate consumption of industries Total

economy

Final

expenditures

Gross capital formation Total industry output

at basic pricesRapeseed

growing

Storage Oil

pressing

Cake

production

Esterification Glycerin DBlendingand sale

Rapeseed

growing

Storage Oil

pressing

Esterification

Seeds 6 0 0 0 0 0 0 6 0 0 0 0 0 6

Fertilizers 36 0 0 0 0 0 0 36 0 0 0 0 0 36

Pest agents 19 0 0 0 0 0 0 19 0 0 0 0 0 19

Fuel 76 4 0 0 0 0 0 80 0 0 0 0 0 80

Rapeseed 0 0 196 0 0 0 0 196 0 0 0 0 0 196

Overhead 0 1 2 0 7 0 0 10 0 0 0 0 0 10

Storage 0 0 7 0 0 0 0 7 0 0 0 0 0 7

Rapeseed oil 0 0 0 0 206 0 0 206 0 0 0 0 0 206

Methanol 0 0 0 0 30 0 0 30 0 0 0 0 0 30

KOH 0 0 0 0 5 0 0 5 0 0 0 0 0 5

Wooden flour 0 0 0 0 0 0 0 0 0 0 0 0 0 0

DRME 0 0 0 0 0 0 364 364 0 0 0 0 0 364

DBD05 0 0 0 0 0 0 0 0 727 0 0 0 0 727

Cake 0 0 0 0 0 0 0 0 97 0 0 0 0 97

Glycerin 0 0 0 0 0 0 0 0 10 0 0 0 0 10

Agricultural

mechanisation

0 0 0 0 0 0 0 0 0 1 0 0 0 1

Transport

mechanisation

0 0 0 0 0 0 0 0 0 0 1 0 0 1

Mechanisation 0 0 0 0 0 0 0 0 0 0 0 0 51 51

Trade and

transport margins

24 1 0 0 5 0 34 64 16 0 0 0 4 85

Taxes—subsidies

on products

11 0 0 0 70 0 87 168 104 0 0 0 14 286

Total uses at

producers’ price

171 7 206 0 323 0 485 1192 954 1 2 0 69 2218

Total GVA/GDP 0 0 0 0 0 0 0 304

GVA at basic

prices

25 0 0 97 41 10 242 416

Taxes—subsidies

on production

0 0 0 0 0 0 0 �112

Total output at

basic prices

196 7 206 97 364 10 727 1608

Bold italic number represent the direct influence of biodiesel production on GDP.

B.

Ku

lisicet

al.

/E

nerg

yP

olicy

35

(2

00

7)

60

36

–6

04

56042

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Table A2

New demand vector by CPC (in million HRK)

CPC division Description Goods and services Total industry output at basic

prices

01 Products of agriculture, horticulture and market gardening Seeds 6

23 Coke oven products; refined petroleum products; nuclear fuel Fuel 80

24 Other chemical products; man-made fibres Fertilizers 36

24 Other chemical products; man-made fibres Pest agents 19

24 Other chemical products; man-made fibres Methanol 30

24 Other chemical products; man-made fibres KOH 5

24 Other chemical products; man-made fibres Wooden flour 0

29 General purpose machinery Mechanisation 51

34+35 Special purpose machinery Agricultural

mechanisation

1

34+35 Transport equipment Transport

Mechanisation

1

50+52+60+61+62+63 Wholesale trade services Trade and 85

Retail trade services Transport

Land transport services

37+40+41+90 Electricity distribution services; gas and water distribution services

through mains

Overhead 10

Sewage and refuse disposal, sanitation and other environmental

protection services

Recycling

Table A3

Output, income and employment multipliers of the Croatian economy

SIC Sector OM R Type I

EM

R Simple

EM

R Type

I IM

R Simple

IM

Rank

1 1 Agriculture 1.7819 20 3.0518 3 2.7526 32 3.3186 1 0.1483 33

2 2 Forestry 1.8748 16 1.5822 27 8.4572 7 1.4832 31 0.5552 7

3 5 Fishing 1.7923 19 1.6074 24 5.1278 24 1.8782 16 0.2307 27

4 10–14 Mining 1.1719 40 1.3871 35 0.9599 38 1.2606 39 0.0816 38

5 15 Food and beverages 2.0810 8 2.1497 8 4.8534 27 1.9902 8 0.2916 23

6 16 Tobacco 1.3388 37 1.4656 32 0.8527 39 1.4107 33 0.0698 39

7 17 Textiles 1.4663 32 1.3171 37 5.3920 22 1.3993 34 0.1809 30

8 18+19 Apparel and leather 1.4725 31 1.3096 38 9.5981 4 1.3946 35 0.3313 21

9 20 Wood products 1.6925 22 1.7272 19 5.7661 20 2.0376 7 0.2699 25

10 21 Paper and paper

products

1.5344 27 1.5255 30 3.0963 30 1.5639 28 0.1584 31

11 22 Publishing, printing 1.9681 11 2.3002 6 6.1562 16 2.0708 5 0.3653 18

12 23 Coke, refined

petroleum

2.1565 5 3.7546 1 5.1743 23 2.5740 3 0.3521 20

13 23a Biodiesel 2.4897 2 3.3255 2 4.7314 28 1.6134 25 0.5116 9

14 24 Chemicals 1.6087 23 2.1489 9 2.5799 34 1.8278 19 0.1858 29

15 25 Rubber and plastics 1.5049 29 1.6054 25 3.0767 31 1.6614 23 0.1562 32

16 26 Non-metallic mineral

products

1.8160 18 1.8788 17 5.0109 26 1.8820 15 0.2847 24

17 27 Basic metals 1.5021 30 1.5347 29 2.7405 33 1.6507 24 0.1285 35

18 28 Metal products 1.7002 21 1.6202 23 5.4673 21 1.7011 22 0.2667 26

19 29 Machinery and

equipment

1.2132 39 1.2952 39 1.6292 37 1.3022 37 0.0833 37

20 30–33 Electrical machinery 1.3879 34 1.6213 22 2.3545 35 1.5372 30 0.1417 34

21 34+35 Motor vehicles, 1.3396 36 1.8343 18 2.1273 36 1.7346 21 0.1196 36

22 36 Furniture 1.5975 24 1.6516 20 5.0306 25 1.8474 18 0.2157 28

23 37+40+41+90 Electricity, gas,

water, recycling

2.1468 6 2.1802 7 6.7616 14 1.9384 12 0.4416 14

24 45 Construction 2.2450 3 2.4354 5 6.6857 15 2.4211 4 0.3553 19

25 50–52 Trade 2.0721 9 1.6372 21 8.8091 5 1.7845 20 0.4337 15

26 55 Hotels and

restaurants

1.8809 15 1.4799 31 8.2454 10 1.6059 26 0.3898 17

27 60–63 Transport 1.8265 17 1.9754 12 5.8328 19 1.8678 17 0.3309 22

B. Kulisic et al. / Energy Policy 35 (2007) 6036–6045 6043

ARTICLE IN PRESS

Table A3 (continued )

SIC Sector OM R Type I

EM

R Simple

EM

R Type

I IM

R Simple

IM

Rank

28 64 Post and

telecommunications

1.5072 28 1.3930 34 5.9686 17 1.2452 40 0.4695 11

29 65 Financial

intermediation

3.0399 1 3.0399 4 6.9574 13 3.0399 2 0.6507 6

30 66 Insurance and

pension funding

1.3455 35 1.3455 36 5.8782 18 1.3455 36 0.7073 4

31 67 Financial

intermediation

activities

1.9682 10 1.9682 13 7.6815 11 1.9682 10 0.4904 10

32 70 Real estate 1.4224 33 1.4224 33 0.2056 40 1.4224 32 0.0143 40

33 71 Renting 1.9394 12 1.9394 14 8.7879 6 1.9394 11 0.4167 16

34 72 Computer and

related activities

1.9053 14 1.9053 16 7.2288 12 1.9053 14 0.4576 13

35 73 Research and

development

1.5903 25 1.5903 26 8.3193 9 1.5903 27 0.6526 5

36 74 Other business

activities

2.2224 4 1.9775 11 8.4386 8 1.9822 9 0.4688 12

37 75 Public

administration and

defense

1.9298 13 1.9298 15 3.8744 29 1.9298 13 0.7811 3

38 80 Education 1.2945 38 1.2945 40 17.6175 1 1.2945 38 0.9490 2

39 85 Health and social

work

1.5632 26 1.5632 28 14.2373 2 1.5632 29 0.9529 1

40 91–99 Services 2.1268 7 2.0569 10 10.2358 3 2.0589 6 0.5307 8

*OM ¼ output multiplier; EM ¼ employment multiplier; IM ¼ income multiplier; R ¼ ranking.

B. Kulisic et al. / Energy Policy 35 (2007) 6036–60456044

household income of the economy in the case where thefinal demand of n sectors (and not only one) changes isestimated by

DHð1�1Þ¼ eð1�40Þ

� HDIEð40�1Þ

�DFDð40�1Þ

� �. (6)

Finally, the employment change in the economy due to agiven change in the final demand of a sector j is estimatedby

DE ¼ EDIEj � DFDj, (7)

where E is the sectoral employment and EDIE is theemployment direct and indirect (total) coefficient or simpleemployment multiplier of sector j. The total change in theemployment of the economy in the case where the finaldemand of n sectors (and not only one) changes isestimated by

DEð1�1Þ¼ eð1�40Þ

� EDIEð40�1Þ

�DFDð40�1Þ

� �. (8)

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