1

InternationalPriceTransmissioninCGEModels:HowtoReconcileEconometricEvidenceandEndogenousModelResponse?

KhalidSiddig

AgriculturalandFoodPolicyGroupUniversityofHohenheim

Stuttgart70593Germany

PhoneNumber:(+49)711459‐22643Email:khalidhasiddig@yahoo.com

and

HaraldGrethe

AgriculturalandFoodPolicyGroupUniversityofHohenheim

Hohenheim70593Germany

PhoneNumber:(+49)711459‐22631Email:grethe@uni‐hohenheim.de

Contributed Paper at the 15th Annual Conference on Global Economic Analysis

"New Challenges for Global Trade and Sustainable Development"

June 27 to 29 2012, Geneva

Copyright 2011 by the authors. All rights reserved. Readers may make verbatim copies of thisdocumentfornon‐commercialpurposesbyanymeans,providedthatthiscopyrightnoticeappearsonall such copies. The authors acknowledge the generous support of the DeutscheForschungsgemeinschaft(DFG)forthisresearchprojecton“TheEconomicIntegrationofAgricultureinIsraelandPalestine”.

2

InternationalPriceTransmissioninCGEModels:HowtoReconcileEconometricEvidenceandEndogenousModelResponse?

Abstract

The importanceofempiricallyanalyzing thetransmissiontoand impactsof international

pricesondomesticmarketsisgrowing,particularlysincethe2006–2008foodpricehike.

However, the field is dominated by econometric time‐series analysis (PTA) and rather

disconnected from analyses based on simulation models such as computable general

equilibrium(CGE)models.Themissingreconciliationamongthesetoolscouldbedueto:

PTAoftenbeingconcernedwithhighfrequencydataandshorttermadjustmentprocesses,

whichdoesnotreconcilewellwiththeannualdataofCGEanalyses;typicallylittleoverlap

between research teams ineconometric time series analysis and those inCGEmodeling;

and the endogeneity of price transmission in CGEmodels. Due to this endogeneity, the

calibration of CGE models to empirically observed price transmission is not

straightforward,asaninfinitecombinationofmodelparametersandspecificationsallows

forreachingacertainlevelofpricetransmission.Thispaperaimstoaddressthequestion

of how a certain degree of price transmission from the international to the domestic

market,whichmaybedeterminedempiricallysuchasbasedonavectorerrorcorrection

model, can be met in a single country CGE model. We examine and validate seven

hypothetical determinants including structural characteristics of the model, the

parameterization of behavioral functions, and properties of the sectors concerned. The

findingsofthispapersupportcontrollingthepass‐throughofpricesfromtheinternational

tothedomesticmarketinCGEmodels.

Keywords: Price transmission, sensitivity analysis, CGE models, parameterization,

internationaltrade.

JELClassification:C13,C68,D58,F17,F31,J60.

3

1 Introduction

The literature on the empirical analysis of the transmission of international prices to

domestic markets is dominated by specific analytical methods such as cointegration

analysisandtheestimationoferrorcorrectionmodels.However,connectiontotheworld

ofComputableGeneralEquilibrium(CGE)modeling,despitetheirpowerfulnessinshowing

the economy‐wide implications of price changes, is limited. At most, prior studies have

includedexogenousassumptionsonpricetransmissionwhicharepluggedintoCGEmodels

by fixingdomesticprice levels(see, forexample,MundlakandLarson(1992),Baffesand

Gardner(2003),Delgadoetal.(2004),andHabermeieretal.(2009)).1

Adam (2011) illustrates the realmacroeconomic and distributional effects of alternative

fiscalandtradepolicyresponsestofoodpriceshocksandhowthesearedeterminedbythe

structural characteristics of low‐income economies. He also investigates impacts of food

price shocks on the aggregate price level and the implications of increased food price

volatility on the design and conduct of monetary policy in low‐income economies.

However,despitetheconsiderationofmanystructuralcomponentsthatmightimpactthe

transmission process. For example, the elasticity of substitution between imports and

domesticgoodsandtheelasticityoftransformationbetweenproductionforthedomestic

and the export market are both set to 0.5 without considering the impact of these

parametersonpricetransmission.Indoingso,thecommonapproachofselectingelasticity

values based on educated guesses and knowledge about particular countries without

takingpricetransmissionimplicationsintoaccountisfollowed.

Themissing reconciliation among the research fields of econometric price transmission

analysis(PTA)andCGEanalysiscouldbeduetoseveralreasons,suchas:(1)EmpiricalPTA

being often more concerned with high frequency data and short term adjustment

processes,whichdoesnotreconcilewellwiththetypicalsolutionperiod(annualaverages)

and simulation horizon (medium to long term) of CGE analyses; (2) Different research

teamsforeconometrictimeseriesanalysisandCGEmodelingwithtypicallylittleoverlap;

and(3)PricetransmissionisendogenoustoCGEmodelsandisdeterminedbyawiderange

1SeeAdam(2011)foracomprehensivesurveyandcomparisons.

4

ofmodelparametersandspecifications,suchastradeshares,shareofthesectorconcerned

intheeconomy,Armingtonelasticities,elasticitiesofsubstitutionamongvalueaddedand

intermediateinputs,andelasticitiesofsubstitutionswithinintermediateinputcategories,

factormarket closures in general, and their complex interactions. As a consequence, the

calibration of CGE models to empirically observed price transmission is not

straightforward;aninfinitecombinationofmodelparametersandspecificationsallowsfor

reachingagivenlevelofpricetransmission.

Thispaperaddressesthequestionofhowacertaindegreeofpricetransmissionfromthe

internationaltothedomesticmarket,whichmaybedeterminedempirically(e.g.,basedon

a vector error correction model), can be met in a single country CGE model. To this

purpose,weemployas “laboratory”a single countryCGEmodeldevelopedbyMcDonald

(2009)andadjustedtoasocialaccountingmatrix for Israel(Siddigetal.,2011).Wefirst

formulateaprioriassumptionsonwhichmodelspecificationsandparametersinaCGEare

themain determinants of the resulting degree of price transmission. Subsequently, in a

systematic sensitivity analysis we analyze the impact of these determinants and their

interactionaswell as showhowexogenouslygivendegreesofprice transmissioncanbe

met endogenously in a CGEmodel based on the calibration of various parameters. As a

simple and significant shock,we apply a doubling of international cereal andother crop

prices, which is not far from what was observed during the years 2007 and 2008, and

investigatehowthisshockimpactsdomesticpricesintheIsraelieconomy,whichhashigh

importsharesoftheseproducts.

Thepaperisorganizedasfollows:inSection2wedescribethemodelincludingitsclosure

rulesandthepricesystem; inSection3wehighlightthedatabaseincludingtheSAMand

behavioralelasticitiesandalsodescribetheselectedfoodsectorsinIsrael;inSection4we

formulate a priori expectations about the main determinants of price transmission; we

presentresultsofasystematicsensitivityanalysisinSection5;andSection6containsthe

conclusion.

5

2 TheModel2.1 OverviewThesinglecountryComputableGeneralEquilibrium(CGE)modelSTAGE(McDonald,2009)

is used as a basis of our experiments. STAGE is a Social AccountingMatrix (SAM) based

model with amix of non‐linear and linear relationships that depict the behavior of the

economy’sagents.Itisastaticmodelwithhouseholdsmaximizingtheirutilityaccordingto

preferences represented by Stone‐Geary utility functions. Households consume

commoditiesavailableinthedomesticmarketfrombothdomesticproductionandimports.

The substitution between domestic and imported goods is governed by the Constant

ElasticityofSubstitution(CES)specification(Armington,1969).Israelisasmallcountryin

theworldmarketofwheat,othercerealswhichcompriseofall cerealsother thanwheat

suchasrice,corn,barley,rye,andoats,andothercrops(thecropswhicharethefocusof

thisstudy);hence,worldmarketpricesforimportsandexportsarefixedinthemodel.

Domesticproductionismodeledasatwo‐stageproductionprocesswithaCESfunctionon

top, where intermediate inputs and production factors are combined to generate the

outputofeachactivity.Atthesecondstage,intermediateinputsarecombinedaccordingto

Leontief technology, while production factors (land, labor, and capital) are combined

accordingtoCEStechnology,withtheoptimalratioofproductionfactorsbeingdetermined

byrelativeprices.Thedomesticproductionofcommoditiesissoldinthedomesticorthe

exportmarket based on a Constant Elasticity of Transformation (CET) specification and

dependent on relative prices in these markets. The model is implemented in General

AlgebraicModelingSystem(GAMS)softwareandadaptedtoanIsraeliSAM(Siddigetal.,

2011).

TheIsraeli2004SAMisadetailedSAMthatcomprisesoneaccountforcapital,oneforland,

and36forlabor.Forthepurposeofthispaper,neitherthedifferentlaboraccountsnorthe

accounts of taxeson labor are at the focus; hence, they are discussed as one aggregated

laboraccount.

2.2 PricesystemFigure(1)showstheinterrelationshipsbetweenthepricesforcommoditiesandactivities

as depicted by the model. The supply prices of the composite commodities (PQSc) are

defined as the weighted averages of the domestically produced commodities that are

6

consumed domestically (PDDc) and the domestic prices of imported commodities (PMc).

The domestic prices of imported commodities are defined as the product of the world

prices of commodities (PWMc) multiplied by the exchange rate (ER) plus ad valorem

importduties(TMc).Weightsofthedomesticandtheimportedpricesinthedetermination

of theaveragepricesaredeterminedbyaCES function.Theaveragepricesexcludesales

taxes,andhencemustbeupliftedby(advalorem)salestaxes(TSc)andexcisetaxes(TEXc)

toreflectthecompositeconsumerprice(PQDc).

Figure(1):PriceRelationshipsfortheSTAGEModel

Source:ModifiedandextendedfromMcDonald(2009).

Theproducerpricesofcommodities(PXCc)aresimilarlydefinedastheweightedaverages

ofthepricesreceivedfordomesticallyproducedcommoditiessoldondomestic(PDDc)and

export (PEc)markets.Weights adjust endogenously based on a CET function. The prices

receivedontheexportmarketaredefinedastheproductofworldpriceofexports(PWEc)

and theexchange rate (ER) lessanyexportdutiesdue,whicharedefinedbyadvalorem

exportdutyrates(TEc).

PWEc

PWMc

PEc

PMc

PXCc

PQSc

PXa1...

PXan

PQDc

PINTa

PVAa

PDDc

Exporttax(TEc)

PWMc*ER*(1–TM)

PWEc*ER*(1‐TEc)

Productiontaxes(TXa)

Importtarifff(TM)

SIGMA

OMEGA

SIGMAac SIGMAx

SIGMAva

w‐land

w‐labor

w‐cap

Sales,excise,andother

domestictaxes

PQSc*(1+TSc)

7

Thisstudyfocussesonasampleofselectedpricestoinvestigatethedeterminantsofprice

transmission from the rest of theworld to thedomesticmarket. The selectedprices are

producer prices of commodities (PXCc), supply prices of domestically produced

commodities on the domestic market (PDDc), supply prices of composite commodities

(PQSc),valueaddedpricesofproductionactivities(PVAa),andintermediateinputpricesof

production activities(PINTa). Elasticities are also shown in the figure as the trade CES

(SIGMA), production CES at the top level (SIGMAx), production CES at the second level

(SIGMAva),andtradeCET(OMEGA).

2.3 ClosurerulesForouranalysisweapplythefollowingstandardclosure:themodel isinvestmentdriven

with the share of investment in domestic final demand being fixed. The government

account,alltaxrates,governmentconsumptionexpendituresandtransfersareassumedas

fixed,whilegovernmentsavingsarea freevariable.For the factormarket,allproduction

factorsareassumedfullyemployedandmobileacrosssectorsinthedefaultclosure,which

reflects a long term adjustment period.We also employ amodified factor closurewhich

reflects a more medium term adjustment period and considers the amount of capital,

skilledlabor,andlandtobefixedandactivityspecific,whileonlyunskilledandsemi‐skilled

laborare fullymobileand fullyemployed.Thecurrentaccountbalance isassumed tobe

fixed,whiletheexchangerateisthefreevariabletheindefaultclosure.Importandexport

pricesarealwaysfixed.

3 TheDatabase3.1 SocialAccountingMatrixTheIsraeliSAMthatrepresentstheIsraelieconomyintheyear2004isthemaindatabase

usedinthisstudy.Itincorporates43sectors,36laboraccounts,10householdgroups,and

18taxcategoriesotherthantaxesonproductionfactors(Siddigetal.,2011).TheSAMwas

developed based on data obtained from different official sources in Israel including the

IsraeliCentralBureauofStatistics(ICBS),theCentralBankofIsrael(BOI),andtheIsraeli

TaxAuthority(ITA). Inaddition,non‐Israelisourceswereusedtofill‐ingaps indomestic

reportssuchastheWorldTradeOrganization(WTO), theOrganizationforEconomicCo‐

operationandDevelopment(OECD),andtheWorldBank.

8

For this study, details pertaining to production factors, households, or taxes are not

relevant; therefore, they will be treated as aggregates throughout the discussion. What

matters from theviewpoint and for theobjectivesof this study ishow the selected food

sectors are represented in the SAM and what weight they have in the entire Israeli

economy.

3.2 SelectedfoodsectorsandpricetrendsDespitetheirimportanceinmeetingdomesticfooddemandinIsrael,wheat,othercereals,

and other crops do not represent big shares in aggregated economic variables such as

exports, imports, andproduction. Table (1), shows thepercentage share of each in total

Israeli imports, exports, production, and factor use. The three commodities together

representonly1.7%of total Israeli imports, 0.8%ofexports, andonly0.4%ofdomestic

production; however, their share in the total cultivated land is 33.1%with other crops

aloneoccupying23.4%.Thisimpliesthatthesethreecropswillbesensitivetolandmarket

closure, while changes in the three crops are expected to have a minor influence on

economicvariablesatthemacro‐level.

Table1:Sharesofthethreecommoditiesinselectedvariablesoftheeconomy(%)

Import Export Production Landuse Labouruse CapitaluseWheat 0.37 0.00 0.03 6.97 0.03 0.01Othercereals 0.59 0.01 0.03 2.87 0.01 0.07Othercrops 0.72 0.75 0.31 23.35 0.25 0.34

Total 1.68 0.76 0.36 33.18 0.29 0.42

Sources:Siddig,etal.(2011),owncalculations.

Thesizeof thesesectorsmeasuredby theircontributions to thecountry’s totaldomestic

productionshowsthatothercropshavethelargestshareofthethreesectorswitha0.31%

contribution, followed by wheat with 0.029%, and other cereals with 0.026%. Similar

ranking isalsoachievedwhenconsidering theshareof thesesectors in theiruseof total

agriculturallandandlabor.Accordingtotheircontributionstothecountry’stotalexports

andimports,thesectorothercropshasthelargestsharefollowedbyothercerealsandthen

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12

elasticities on the transmission of the world price of imports and exports to domestic

markets,whiletheresultssectionwillassessandvalidatetheseassumptionsbasedonour

empiricalfindings.

For thedefault version of ourmodel analysis (pre‐sensitivity analysis), the valuesof the

fourelasticitiesareassumedtobe2.0forthetradeelasticities(CESandCET)and0.8for

production CESs at top and second levels. The selection of these values is based on

educatedguessesgovernedbyourknowledgeabouttheIsraelieconomyandguidedbythe

elasticityrangesrecommendedbySadoulet&deJanvry(1995).

4 APrioriAssumptionsonDriversofPriceTransmission

Apriori,wehypothesizethefollowingmodelcomponents,parameters,andspecifications

tobecrucialinthedeterminationofthedegreeofpricetransmissionbetweeninternational

anddomesticprices:

1. The trade shares (import and export): the higher the trade shares of the sector, thehigherthetransmissionofworldmarketpricechangestothedomesticmarket.Importsand exports are imperfect substitutes for domestic products. Therefore, if the initialtrade share is very small, it cannot become large (Hanslow, 2001; Kuiper and vanTongeren,2006).

2. The value share in the domestic economy: the higher the share of the sector in thedomestic economy, the higher the impact created by changes in world price on thedomestic market price. This is because the domestic price increase is dampened bymore production, which happens more easily with smaller sectors. Therefore, if thesector is large, price increases can be dampened by domestic production to a lesserextentonly.

3. Theshareindomesticfactoruse:sectorscouldbedifferentiatedaccordingtotheiruseof different factors of production with different implicit price elasticities of factorsupply.Incaseasectorreliesheavilyonaninelasticfactor,pricetransmissionislikelyto be higher. This is because with increasing domestic production, the cost ofproduction would increase more than it would if there were a higher factor supplyelasticity.

4. Thedegreeof factormobilityamongsectors: thehigherthefactormobility, the lowerthepricetransmission.Thisisbecauseincreasingdomesticsupplyincaseofincreasing

13

international prices dampens the increase in domestic prices; however, the moreimmobilethefactorsare,thelessthismechanismcanwork.

5. ArmingtonelasticitiesandCETelasticitiesbetweendomesticdemand/importdemandand domestic supply/export supply: the higher the trade elasticities, the higher theprice transmission. This is because higher elasticities allow for higher degrees ofsubstitution, resulting inmore demand for the domestically produced product in thecaseofanincreasingworldmarketprice.

6. Elasticitiesofsubstitutionamongvalueaddedandintermediateinputs:thehighertheelasticities, the more options producers have to substitute primary factors byintermediatesandviceversa.Therefore,thehighertheelasticities,thelessofanimpactworldmarket price changes will have on domestic prices. In addition, elasticities ofsubstitutionwithin input categoriesmatter because higher elasticities of substitutionenableproducerstoadjustproductionandthusdampenthepriceshockdomestically.

7. Theprevailingexchangeratepolicy:thedomesticcurrencytendstoappreciateifworldpricesofcommoditieswhicharepredominantlyexportedincrease,whilethedomesticcurrency tends to depreciate if there are rising prices for predominantly importedproducts.3 Fromaprice transmissionperspective, an increasingworldprice togetherwithaflexibleexchangeratewouldreducethepass‐throughofthatincreaseincaseofacurrencyappreciationandincreasethepass‐throughincaseofacurrencydepreciation.

Thefollowingsectiontriestoempiricallyassessandvalidatethedescribedhypotheses.

5 ResultsandSensitivityAnalysis

Asafirststep,weapplyashockofa100%increaseinworldpricesforwheat,othercereals,

and other crops to the model with standard parameterization and model closures as

described in Section 2. Thismodel is found to transmit the 100% increase in theworld

pricetothedomesticpricesofthethreecommoditiesatverydifferentmagnitudes(Figure

5). Theprices shown inFigure5 include thedomesticpriceof imports (PM), the supply

priceof the composite commodity (PQS), the supplypriceof thedomestic commodity in

the domesticmarket (PDD), the composite producer price (PXC), the value added price

(PVAa),andtheintermediateinputprice(PINTa).

3 The effects of international price shocks on the exchange rate in CGE models depend on the complexinterplayofvariousfactors(Devarajanetal.,1993)andarenotdiscussedinthisarticle.

14

Asafirstobservation,thepercentageincreaseinPMandPEis96%,ratherthanthe100%

increase in theworldmarketprice.The increase isnotby the full amountbecauseofan

appreciationofthedomesticcurrencyagainstthedollarbyabout1.8%.Whilethechange

of thepricesof importsandexports isequaloverallproducts, the transmission toother

domestic prices differs heavily among products. For example, producer prices of wheat,

other cereals and other crops increase by 25%, 32%, and 74%, respectively, due to the

100% increase in their world market prices (Figure 5). We make an effort to explain

differences among products in Section (5.1) based on sectoral shares in the domestic

economyaswellastradesharesintotalproduction/use.

Given the high level of observed correlation between the world market price and food

prices in Israel (Figure 4), we find that domestic price changes in the standard model

specificationaretoolow.Therefore,wecarryoutasensitivityanalysisinSections5.2to5.4

to investigateoptionsneeded to reachahigher level ofprice transmissionand to assess

andvalidatethehypotheticalassumptionsmadeinSection4.

5.1 SectorsharesThefirstapriorihypothesisassumesthatthehigherthetradeshare,thehighertheprice

transmission.Thereactionoftheselectedsectorstotheworldpriceincreasemeasuredat

thedomesticsupplyprice(PQS)ranksthesectorsaccordingtotheirimportsharesasother

cereals,wheat,andothercropshave73%,69%,and65%increasesinPQS(Figure5)and

importsharesare74%,71%,and30%(Figure2),respectively.Forothercrops, the65%

increase inPQSseemshigh ifoneconsiders thesubstantially lower importshare for this

product group. The impact on PQS for other crops, however, also stems from a strong

increaseintheexportprice.

Toconfirmourinterpretationregardingthecausesofpricechangesandparticularlythose

onPQS,wesimulatedasituationwheretheshocksareintroducedinseparateexperiments,

once from the export side alone and once from the import side alone. In case we only

increaseimportprices,butnotexportprices,theshareincreaseinPQSforothercropsis

indeed significantly lower: only 54%. On the other hand, wheat and other cereals are

virtuallynotexportedandtheeffectonPQSstemsalmostexclusivelyfromtheimportprice

shock.Ifweapplythepriceshockontheexportsideonly,effectsonPQSareclearlyranked

accordi

third.

Figur

Foroth

isstron

impact

forothe

price in

product

increas

pricesf

strictly

Inconc

trade s

shares

respect

termso

theresu

5

10

15

20

25

30

%changeinprices

ingtoexpo

re(5):Chan

herprices,t

ngestforoth

oftheexpo

ercropsmo

ncrease an

ts. Value a

es in produ

forinterme

followthei

clusion,we

hares. Base

of sectors

tand theo

ofitssector

ults.

96 96

0

0

0

0

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0

0

PM

rtshares,w

ngesindomwithdefau

thepicture

hercrops,w

ortpriceon

otivatesdom

d results i

added and

uction,wh

ediates.The

irPXCcoun

canattribu

ed on this

in domest

thercrops

ralsize,bu

69

6 96

M

Wheat

withother

mesticpricesultmodelp

islesshom

whichcanb

nPXC(see

mesticprod

in a higher

aggregate

ich transla

erefore,the

nterpartsan

utethesize

single exp

tic product

sectordiff

utalsointe

73 65

PQS

t

15

cropsrank

sfollowingarameteriz

mogeneous.

beexplaine

Figure1).T

ducerstop

r increase

e intermedi

ates intohi

resultsfor

ndrankthe

eofthedom

periment, w

ion, aswh

fersheavily

ermsofits

24 2845

PDD

Otherce

kingfirst,ot

a100%inczationandc

.ForbothP

edbythehi

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producemo

in its valu

iate input

gherwage

rPVAandP

ethreesect

mesticpric

we cannot

eat and ot

y fromthe

tradestruc

25 32

7

PXC

ereals

thercereals

creaseininclosures(%

PDDandPX

ighexport

increasein

ore.Thisda

ue added p

demand is

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PINTareno

torssimilar

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conclude t

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other two

cture,both

89

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PV

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price than

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the relevan

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osectorsno

ofwhichi

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24

253

VA

hercrops

ndwheat

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thedirect

ucerprice

domestic

for other

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5.2 FacToanal

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Figure(

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price(P

worldm

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7

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0

50

100

150

200

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ctormobilyzetherel

priceshock

obtained in

f price tran

edbyourr

eecommod

cropsandc

themobilit

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ropsandce

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(6):Change

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portpricefo

would be a

increase in

7469

57

57

256

‐1

Mobile

Wh

ilityevanceoff

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amodel c

nsmission i

esults,show

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cerealsinp

tyandimm

alueaddedp

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velyunder

esinprices

composite

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able to attr

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97

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108

Immobile

heat

factormobi

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losurewith

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wninFigur

rtheassum

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mobilityass

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ertheimmo

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ract produc

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74

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en there is

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97

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74

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obile Mo

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ity.Ourexp

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obile Im

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pectation is

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angesinthe

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greeoftran

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267%and

,compared

umptions(%

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causethein

ositeprodu

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mmobile

ps

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ctation is

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%)

uct supply

aseinthe

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ucerprice,

rfold.The

esult ina

PM

PQS

PDD

PXC

PVA

PINT

17

fallofPDDby27%.PQSwouldbeaffectedbyboththisdeclineinPDDandtheincreasein

PM,withaslightlynegativenetresultof‐1%.

Someofthewheatpricesbehavecontrarytoexpectations;namelyforPVA,PXC,andPDD,

the pass‐through from the international to the domestic market is less under the

immobilityassumption than it isunder themobilityassumptionbecauseof crosseffects.

With mobile factors, the production of other crops increases heavily and replaces land

whichhadpreviouslygrownwheat:landuseforwheatdeclinesby81.4%.Thisresultsina

scarcedomesticsupplyofwheatandthushigherdomesticwheatpricesthanwouldoccur

undertheassumptionoffactorimmobility.

5.3 SubstitutionelasticitiesToanalyzetheimpactoftheproclaimeddeterminants(5)and(6),weperformasensitivity

analysis with several values for the following major related elasticities: the trade

elasticities (the CES between imports anddomestic goods and the CETbetween exports

anddomesticgoods)andtheproductionCESs(theCESbetweenaggregateprimaryfactors

andaggregateintermediateinputsandtheCESbetweenthedisaggregatedprimaryfactors

ofproduction).

Toenhancethelevelofpricetransmission,thedefaultfactormarketclosureisadjustedfor

thissensitivityanalysis.Weconsidertheamountofcapital,skilledlabor,andlandusedto

be fixedandactivity specific,whileunskilledand semi‐skilled labor are fullymobile and

fullyemployed.

Dependingonthesensitivityofthemodeltothefourelasticitiesanditsabilitytoconverge,

tendifferentvaluesareselectedforthetradeCESsandCETscoveringarangebetweenT1

(0.5) and T10 (9.5), while assuming similarity between both of them at each stage. In

addition, another ten values are selected for the production CESs assuming similarity

between both of them in each stage. The range for the production CESs is between P1

(0.05)andP10(3.0).Theexactvaluesofthetradeandproductionelasticitiesaswellasthe

defaultlevelsusedinpreviousexperimentsareshowninTable(2).

18

Table(2):Therangesofelasticityvaluesconsideredinthesensitivityanalysis

Codes ProductionCESs Codes TradeCESandCETP1 0.05 T1 0.50P2 0.38 T2 1.50P3 0.71 T3 2.50Defaultversion 0.80 2.00P4 1.03 T4 3.50P5 1.36 T5 4.50P6 1.69 T6 5.50P7 2.02 T7 6.50P8 2.35 T8 7.50P9 2.67 T9 8.50P10 3.00 T10 9.50

Figure(7)showstheresultsobtainedfromthedescribedcombinationofelasticities.Trade

CES and CET are presented at the horizontal axis, while the vertical axis shows the

percentagechangeinprices.ProductionCESsareidentifiedbydifferentcolors.

Theresultsofthesensitivityanalysisconfirmourfifthassumptionwithrespecttothetrade

elasticitiesasshowninFigure(7):allthelinesslopeupasTvaluesmovefromT1toT10.

Theexceptionsarethecompositesupplypricesofwheatandothercereals,whereprices

increasewith increasing tradeelasticitiesonly if theproductionelasticity isunityor less

(levels P1 to P4). With higher production elasticities (levels P5 to P10), higher trade

elasticities result in less price transmission. This can be explained by considering two

differenteffectswithoppositedirectionscausedbyhigherimportCESelasticitiesincaseof

increasingimportprices:

Effect1:Ahigherelasticityresultsinmoresubstitutionofthedomesticcommodityfortheimportedcommodity,whichraisesPDDandthusPQS.Effect2:AhigherelasticityresultsinahigherweightofPDDandalowerweightofPMintheformationofPQS,whichdepressesPQS.

Thelowertheproductionelasticities,thestrongereffect1(increasingPQS),andthelesser

effect2(depressingPQS).Forwheatandothercereals,effect1dominatesthetotaleffect

on PQS up to a production elasticity of up to unity, whereas effect 2 dominates with

productionelasticities aboveunity. In contrast, forother crops theeffectofhigher trade

elasticities on the price transmission from trade prices to PQS is always positive. This

19

results from the fact that PQS is also impacted by the export price due to a significant

exportshareinthisproductgroup.

The sixth a priori assumption – the lower the production elasticities are, the higher the

pass‐through is – is also validated according to our results. According to Figure (7), the

percentagechangeinthepriceseriesincreasesasproductionelasticitiesmovetowardT1

whichhasthesmallestTvalueof0.05.Thiscanbeobservedfromthewideverticalspaces

between P values, which become even wider as the elasticity is closer to P1 (see, for

instance,PXCforwheatandcereals).

Thisbeingsaid,thestrengthofpass‐throughalsodiffersamongthedifferentcommodities.

Figure (7) shows wheat prices reacting stronger to the production elasticities, which is

reflected in thewider spaces between the different lines compared to cereals and other

crops. On the contrary, other crops show the lowest reaction among the three selected

commoditiesasthelinesareclosertooneotherforallofothercrops’priceseries.Thisis

explainedbythesizeoftheothercrops’sector,ingeneral,andtheamountofresources(VA

and intermediates)needed tobringclear increases in itsdomesticproduction.Theother

cropssectoristhethirdbiggestagriculturalsector inIsraelafterthefruitandvegetables

sectorandother theanimal farmingsector,while thewheatandothercerealsectorsare

smaller.

Despitethedifferencesamongthethreecommoditiesintheirsize,coststructure,demand

components, and factor demand, their overall reaction to the elasticity combinations is

foundtobeconsistentwiththeelasticity‐relatedaprioriassumptions.Thejustificationfor

increasesinthepass‐throughastradeelasticities(CESandCET)increaseisthatdomestic

producerswould realize higher demand for their products due to domestic supply cuts

causedbyhigherworldpricesasimportsdeclineandexportsexpand.Ifdomesticgoodsin

this case are not good substitutes for imported ones, the reduction in imports and the

increaseinexportswouldhardlyhappen.

ThehighertheproductionCESis, thestrongerthereallocationamongproductionfactors

andintermediatesarewhichallowsforastrongerresponsetohigherworldprices.Thus,

thehighertheproductionCESis,thegreatertheabilityofproducerstoreactanddampen

thedomesticpriceincreaseisbyadditionalsupplyandviceversa.

ProdPercentagechangeinpricesfrom

thebase

Wheat

Othercereals

Othercrops

Figu

ducerprice(PXC)

ure7:Percenta

) Value

ageincreasein

eaddedprice(PV

TradeE

20

pricesaccordin

VA) Composi

lasticities(CES&

ngtoelasticityc

itesupplyprice(

&CET)

combinations

(PQS) Domestticsupplyprice((PDD) Productionelasticities(top&secondlevels)

21

Figure(8)helpsdetermine theobtainablerangesofprice transmissionusingdifferent

combinations of trade and production elasticities. For simplicity, only prices of other

cropsaredepicted,wheretheselectionofothercropsisrelatedtothesizeofthesector

in the economy: the other crops sector represents the largest food crop sector, with

about70%of its supplyproduceddomestically.Moreover, it couldbeconsideredasa

typical sector with substantial amounts imported, produced domestically, exported,

consumedbyhouseholds, invested,andusedas intermediate inputs.Thefigureshows

thedifferentrangesofpriceschanges indifferentcolorswhilecombiningthedifferent

trade and production elasticity values. The highest changes are always shown in red,

followedbypurple,lightgreen,orange,whilethelowestpricerangesarealwaysinblue.

Looking at the domestic prices of imports and exports, which represent the bridge

between the domestic market and the rest of the world, we find only two possible

ranges of changes in prices. The highest obtainable price change for both is 98% by

combining P1 and T10, while the lowest obtainable price change is 65% at the

combination of P10 and T10. The differences between changes in PWM and PM and

changes in PWE and PE are driven by the exchange rate, which appreciatesmore in

thesescenarioswhentradeelasticitiesarehigher.Thiswayofpresentingpricechanges

allowsfordeterminingvariouscombinationsoftradeandproductionelasticities,which

resultinthedesiredlevelofpricetransmission.

If, for example, the time series analysis confirms that a 100% increase in the world

market price of other cropswould transmit fully to the producer price, then the CGE

modelshouldbeabletogenerateanincreaseintheproducerpricecloseto100%.The

requiredelasticitylevelscanbefoundbasedonthegraphatthetoprightpartofFigure

(8),whichshows that tradeelasticitiesatT10andproductionelasticitiesatP1would

resultinthedesiredresult.However,theselectedvaluesoftradeelasticitiesarehigher

than the recommended range of elasticities that CGE modelers tends to rely upon

(Sadoulet and de Janvry, 1995).4 Thus, these results indicate the importance of

considering the specifics of individual countries and commodities in judgingplausible

4 Experience has shown that the empirical results obtained from simulations with CGEs are quiteinsensitive to specific values of elasticities, while, instead, they crucially depend upon their order ofmagnitude.Thepossiblerangeofsubstitutabilityisrelativelywellrepresentedbyfourvalues:0.3forverylow substitutability, 0.8 formedium‐low, 1.2 formedium‐high, and 3.0 for very high (Sadoulet and deJanvry,1995).

elasticit

typicall

Fig

Ifweco

rangeo

100%.T

becom

thepro

tyvalues.F

lybeonlyo

gure8:Pric

onsiderthe

ofprices is

Thelowest

mbinedwith

oducer pric

Furthermo

oneofmany

cerangesfo

eproducer

sreflected

ttradeelas

hP1(thelo

ce.On the

re,calibrat

yobjective

orothercro

rpriceofo

by thered

sticitythat

owestprod

other hand

22

tingacerta

esinthepar

opswithdi

othercrops

dcolorand

couldbec

ductionCES

d, thehigh

aindegree

rameteriza

fferentcom

sasanexa

dcomprises

onsidered

Ss)onlyto

hest produc

ofpricetr

ationofaCG

mbinations

mple,theh

schangesb

hereisT1;

generatea

ction elasti

ransmission

GE.

ofelasticit

highestobt

between8

;however,

achangeof

icity that c

nwould

ties

tainable

0%and

itcould

f84%in

couldbe

23

considered to obtain changeswithin the same range is P5, which could be combined

with T10 (the highest trade elasticities) only to generate an 80% increase in the

producerpriceofothercrops.

The second obtainable range of producer prices (60% to 80%), which is colored in

purple, couldbeachievedbycombining theproductionCESsbetweenP2andP8with

trade elasticities at different levels. As a general rule, the higher the value of the

production CESs, the higher the trade elasticitiesmust be to remainwithin the same

range of price pass through. The lowest obtainable level of pass‐through within this

range(60.8%)canbeachievedbycombingP8andT8,whilethehighest levelofpass‐

through(79.7%)canbeachievedbycombingP5andT9.

Asimilarapproachcouldbefollowedtoidentifydifferentrangesfordifferentpricesand

commoditiesinlightofthelevelsofcorrelationsbetweentheworldmarketpricesand

thedomesticpricesthroughoutthepricetransmissiontreeshowninFigure(1).Forthe

valueaddedpriceofFigure (8) (righthandmiddlepanel), forexample, thereare four

possible ranges of price pass‐through, there are three for the composite supply price

(right hand lower panel)and three for the intermediate input price (left handmiddle

panel).

These results confirm and validate our fifth and sixth hypotheses,which assume that

trade and production elasticities have significant influences on the degree of price

transmission from theworld to the domesticmarketwithin the CGE framework. It is

alsoshownthatthetransmissionishigherifweincreasethevalueoftradeelasticities,

while it is lower if we increase the value of production elasticities. Therefore, the

elasticitycombinationthatallowstheCGEmodeltogeneratethehighest levelofpass‐

through is always the one that considers high trade elasticities together with low

productionelasticities.

5.4 ExchangerateregimeToexaminetheinfluenceoftheprevailingexchangerate(EXR)regimeofthepricepass‐

through,anupdatedmodelclosureisappliedwithafixedEXR.Asdiscussedabove,the

domesticcurrencyappreciatesunderour100%worldmarketpriceshock.Thisimplies

that domestic import and export price changes would be smaller than worldmarket

pricechanges.A fixedexchangerateregime, incontrast,wouldassure thatchanges in

thedomesticpricesof importsandexportswould remain similar to changes inworld

prices as the EXRwould remain fixed at a value of 1. Figure (9) compares the pass‐

through

commo

Figur

Figure

ahighe

appreci

thepas

6 Co

Despite

prices t

empiric

cointeg

powerf

compar

regardi

actorso

Itthere

harmon

attracti

empiric

0

20

40

60

80

100

120

Changeinprices(%

)hofa50%

odities.

re9:Thepa

(9)confirm

rpass‐thro

iationand

s‐throughw

nclusion

e the grow

to domesti

calmethod

grationana

ful method

red to eco

ing implica

oftheecon

eforeseem

nizes their

iveapproa

callydeterm

49

37

1314

46

Flexible

W

increasein

ass‐through

msourseve

oughofwo

anincrease

wouldbeh

ns

wing numb

icmarkets

dsapplieda

alysisandt

ds to desc

onomy‐wid

ations a ce

omy.

sadequate

linkages in

ch is to ca

minedbyt

50

38

14

15

6 4

0

e Fixed

Wheat

nworldpr

hofa50%iex

enthaprior

rldpricein

einworld

higherinth

ber of stud

, particula

areconcent

theestimat

cribe and

e models

ertain leve

etouseav

naway th

librateCGE

imeseries

4939

15

17

47

1

d Flexib

Ot

24

ricesofexp

increaseinxchangerat

riassumpt

ncreasesto

marketpri

hecaseofa

dies analyz

rly after th

tratedone

tionofvec

forecast p

such as C

l of price

varietyofto

hat capture

Emodels t

analyses,w

50

40

16

7 1

60

2

ble Fix

thercereals

portsandim

nworldpricteregimes

tionthataf

domesticm

ices.Howe

fixedEXR

zing the pa

he 2006‐20

conometric

torerrorc

price relat

GE models

transmissi

oolsthatco

esandrefle

tomeet the

whichisou

49

33

22

18

62

2

ed Flex

mportsfor

cesunderfl

fixedexcha

marketsin

ver,ifworl

compared

ass‐through

008 food p

ctimeserie

correctionm

tionships t

s, they are

ion might

onnectsbo

ects thestr

e levelofp

urmotivati

50

34

2 2

36

108

4

xible F

Othercrop

thethrees

lexibleand

angeratere

caseofac

ldpricesd

toaflexibl

h of intern

price incre

esanalysis

models.Th

through ti

e less info

have on d

othtechniq

rengthofe

pricepass‐t

iontocond

4

23

37

110

5

Fixed

ps

selected

dfixed

esultsin

urrency

ecrease,

eEXR.

national

ase, the

suchas

heseare

me, yet

rmative

different

quesand

each.An

through

ductthis

PM

PQS

PDD

PXC

PVA

PINT

25

study.Wehypothesizesevendifferentdeterminants,basedongeneraleconomicsense

andtradetheory,ofthepass‐throughofinternationalpricestodomesticmarkets.They

aregrouped in fourmajorcategories: (1)structuralcharacteristics, suchas thesizeof

the concerned commodity in the domestic economy in terms of supply, demand,

production,andtrade,aswellasitsshareintheuseofdomesticfactorsofproduction;

(2)modelclosureandbasicassumptionsrelatedtothemobilityofproductionfactors;

(3) model parameterization, including assumptions related to the substitution

possibilities among domestic and traded goods, as well as producers’ options to

substitute primary factors by intermediate inputs or to substitute different primary

factorsforoneother;and(4)theprevailingexchangerateregime.

We use a single country CGE model developed by McDonald (2009) together with a

detailedIsraeliSAMfor2004(Siddigetal.,2011)asthebasisforourexperiments.Our

findingsconfirmthatthepricepass‐throughfrominternationaltothedomesticmarkets

in CGEs can be controlled for by configuring its closure rules, production and trade

elasticities, factor market closures, and exchange rate regime. General conclusions

includethefollowing:(1)highertradesharesofthesectorresultingreatertransmission

oftheworldmarketpricetothedomesticmarket;(2)increasingexportpricestogether

with lowCET elasticities and high production elasticitiesmay even result in negative

effectsondomesticconsumerprices; (3)greater factormobility results in lowerprice

transmission;(4)highertradeelasticitiesresultingreaterpricetransmission;(5)higher

production elasticities (top and second level) result in more substitution options for

producersandlesspricetransmission;and(6)thepass‐throughofanincreasingworld

price is higher under a fixed exchange rate regime compared to a flexible one if the

domesticcurrencyappreciatesduetotheworldmarketpriceshock.

Thedescribedapproachtodepicttheobservedtransmissionofinternationalcommodity

pricestodomesticmarketsmaybehelpfulinconsideringacombinationofPTAandCGE

modeling. The possibilities of combining the different assumptions of the model

structure,elasticities,andclosurerules tomeetacertaindegreeofprice transmission

are manifold. The modeler therefore has considerable freedom to choose a model

formulation which targets a certain degree of price transmission. This freedom is

helpful, as achieving a certain degree of price transmission will typically be just one

target among others, such as capturing the real economy accurately in the choice of

factormarketclosuresorbasingbehavioralparametersonempiricalanalysis.

26

7 References

Adam, C. (2011). On the Macroeconomic Management of Food Price Shocks in Low‐incomeCountries.JournalofAfricanEconomies,Vol.20,AERCSupplement1:63–99.

Baffes, J. and B. Gardner (2003). The Transmission of World Commodity Prices toDomestic Markets under Policy Reforms in Developing Countries. The Journal ofEconomicPolicyReform,6(3):159–80.

Delgado, C., N. Minot and M. Tiongco (2004). Evidence and Implications of Non‐tradability of Food Staples in Tanzania, 1983–1998. MTID Discussion Paper 72.Washington,DC:InternationalFoodPolicyResearchInstitute.

Devarajan, S., Lewis, J. D. and S. Robinson (1993). External Shocks, Purchasing PowerParity,andtheEquilibriumRealExchangeRate.TheWorldBankEconomicReview,7(1):45‐63.

Habermeier,K.,I.Otker‐Robe,L.Jacome,A.Giustiniani,L.Ishi,D.Vavra,T.KisinbayandF.Vazquez(2009).InflationPressuresandMonetaryPolicyOptionsinEmergingandDevelopingCountries:ACross‐regionalPerspective.IMFWorkingPaper09/1.

Hanslow,K.(2001).TheApplicationofCRESH‐BasedFunctionalFormsinCGEModels.ResearchMemorandumCatNo.:GA506,Melbourne.

ICBS(TheIsraeliCentralBureauofStatistics)(2011).Unpublishedtimeseriesdataonthepriceofcerealsandexchangerate(2001–2010).

Kuiper,M.and.vanTongeren(2006).UsinggravitytomoveArmington‐anempiricalapproach to the small initial trade share problem in general equilibrium models.Paperpreparedfor theNinthAnnualConferenceonGlobalEconomicAnalysis, June15‐17,2006inAddisAbaba,Ethiopia(Version0.3,3May2006).

McDonald,S.(2009).Astaticappliedgeneralequilibriummodel(STAGE).Version1:July2007.DepartmentofEconomics&Strategy,OxfordBrookesUniversity,UK.

Mundlak, Y. and D. Larson (1992). On the transmission of world agriculture prices.WorldBankEconomicReview,6(3):399–422.

Nicita,A.(2006).MultilateralTradeLiberalizationandMexicanHouseholds:TheEffectof theDohaDevelopmentAgenda. In:Hertel,T.andL.A.Winters(eds.):PovertyandtheWTO:ImpactsoftheDohaDevelopmentAgenda.TheWorldBank:107‐128.

27

Sadoulet, E. and A. de Janvry (1995). Quantitative Development Policy Analysis. TheJohnsHopkinsUniversity Press, Baltimore and London, 1995.Manuscript availableat:Are.berkeley.edu/~sadoulet.

Siddig,K.,Flaig,D.,Luckman,J.andH.Grethe(2011).A2004SocialAccountingMatrixfor Israel. Agricultural Economics Working Paper Series (HohenheimerAgrarökonomischeArbeitsberichte),No.20.

28

8 Appendix:Descriptionoftheagriculturalsectorsofthe2004SAM

SAM2004sectors DetaileddescriptionbasedonIOT1995

Cereal:Growingofrice(non‐husked),corn,barley,rye,oats,andothercereals

Growingofothercerealsandpulses

Growingofwheat Growingofwheat

Fruitandvegetablesincludingmateandspices,excludingotherfruitdried

Growingofcitrus

Growingofpomefruits

Growingofstonefruits

Growingofnuts

Growingofgrapes

Growingofbananas

Growingofolives

Growingofsubtropicalandothertreecrops

Growingofvegetables(includingmelonsandpumpkins)

Growingofpotatoes

Othercrops:Growingofroughfodder,cotton,otherplantbasedfibers,oilseeds,soyabeans,groundnuts,tobacco.Growingofflowers,seeds,andnurseryproducts.Importsofgreencoffee,cocoabeans,andbulktea

Growingofroughfodder

Growingofcotton

Growingofotherfieldcrops(includinggroundnuts)

Bovinecattle,horses,asses,mules,andhinnies,live,bovinesemen,sheep,livegoatsshornwool,greasy,andfleece‐washedshornwool

Cattlefarmingformeat

Sheepfarming(milk,meat,andwool)

Otheranimal:Layinghens,poultryfarming,andturkeyfarming.Farmingofotheranimalsincludingfineanimalhair,notcardedorcombedandsilk‐wormcocoonssuitableforreeling

Raisingoflayinghens

Poultryfarmingformeat

Poultryhatcheries

Raisingofturkeysandotherpoultryfarming

Farmingofotheranimals

Meat:Processingofmeatandpoultry,includingCPCSubclass02962(pulledwool,greasy,includingfleece‐washedpulledwool;coarseanimalhair)andCPCSubclass02971(rawhidesandskinsofbovineorequineanimals,sheeporlambs,goatsorkids)

Processingofmeatandpoultry

Manufactureofedibleoils,margarine,andoilproductsexcludingCPCSubclass21660(maize(corn)oilanditsfractions,notchemicallymodified)

Manufactureofedibleoils,margarine,andoilproducts

29

SAM2004sectors DetaileddescriptionbasedonIOT1995

Milk:Milkofcattle,sheep,andgoats Cattlefarmingformilk

Forestry,fruittrees(investmenttobearing),andimportsofnaturalrubber

Forestry

Fruittrees(investmenttobearing)

Naturalrubber(imports)

Fishing:Pond‐culturefisheries.shoreandlakefisheries

Pond‐culturefisheries

Shoreandlakefisheries