guillotreau-tuna demand 10-05-2011
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8/16/2019 Guillotreau-tuna Demand 10-05-2011
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odéliser le marché mondial duRéunion MACROES, Paris (Jussieu), 9-11
mai !11
Workshop MACROES à Nantes, 14-15 avril2011
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2. Que sait-on du fonctionnement desmarchés thoniers au niveau mondial ?
3. Implications des résultats pour lagestion des pêcheries thonières
"ntroduction1. Worshop ! l"#niversité de $antes les1%-1& avril 2'11 ( un des o)*ectifs+acroes rempli
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# $or%sho& 'antes Modellin* *lo+al tuna
- ,"atelier a reu le soutien du pro*et +/0 et del"I4 et a été organisé sous le la)el I+50-/,I67.
- 18 participants9 dont 6ed :roves ;#/<= et <ale>uires ;$+4-$=9 enn@ un ;#niv. 6aiAan=9 4ransche ;#niv. tavanger=9 +aB $ielsen ;#niv.<anemar=9 0amon iméneC-6ori)io ;#niv. Duelva=9 /.+ullon et /. /ha)oud ;I0<=9 ha))ar aEr@ ;#niv.
7ortsmouth=...- 6hèmes a)ordés ( modèles I< marchés de laconserve en urope - spagne9 0o@aume-#ni-9modèle :I< 5ango ;7-conserve= et 6o@o ;,,-sashimi=9 modélisation de panel ;4rance=9 approche
réseau ;marché mondial=9 approche )ioéco ;Indien=.
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uel.ues &hotos /###
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2. Que sait-on du fonctionnement des
marchés thoniers au niveau mondial ? t0&es o mod2les (
- Mod2les de cointé*ration visant ! vériFer l"eBistence d"un marchéuni>ue horiContalement ;spatialement= et verticalement ;transmission des
changements de priB=. D@p. d"a)sence de coGts de transaction et d"unseul facteur varia)le.;Derric and >uires 1HHJ 5ose and +cIlgorm9 1HH8J :ordon andDannesson9 1HH8J un and Dsu 1HHJ un and /hiang 1HHHJ sche et al.91HHHJ aEr@ et al.9 2'''J sche et al. 1HHH9 2''29 2''%9 2''KJ aEr@ and4ofana9 2''% J :uillotreau et al. 2''&J $ielsen9 2''&J $ielsen et al.9 2''KJ>uires et al. 2''8J eon et al. 2''K9 iméneC-6ori)io et al. 2'1'...=- Mod2les de demande pour représenter les relations priB->uantité;estimation des coef d"élasticité et de LeBi)ilité=;Mitson and +a@nard 1H3J Ming 1H89J Wessels and Wilen 1HH%J Aenand 6roedson 1HH%J ales9 <urham and Wessels 1HHKJ $ielsen 1HHHJ5ertignac et al. 2'''J un and Dsieh 2'''J 6ada 2'''J /hiang et al.2''1J Aen 2''1J <aloonpate 2''2J 0eid et al. 2''3J 5a)ula and/ore@ 2''&J aEr@ and 5roAn 2''J :uillotreau et al. 2''J iméneC-
6ori)io et al. 2''HJ :arcia del Do@o et al 2'1'J un et al. 2'1'...=
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+ultivariate procedure of ohansen )ased on an error correctionmodel ;/+=. ssuming that 7t is a vector Ahich contains prices9 inorder to chec Ahether there are one or several cointegrationrelationships in(
Ahere NiO-I P 1 P...P i9 for i O 19...9 n-19 O -I P 1 P...P n9 Iis a ; B = identit@ matriB9 <t is a vector of dumm@ varia)les;seasonal9 etc.= and R a vector of intercepts
O ST" Where T contains the r cointegration relationships
and S includes the ad*ustment speed parameters ofthe dependent varia)les toAards the long-rune>uili)rium represented )@ T"7t-n
4or the multivariate strateg@9 the ,7 test determines if thecolumns in the matriB sum to Cero9 leading to the conclusion
that the price series are pair-Aise co-integrated.
ointe*ration models(
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Study Model Tuna markets Results
Herrick and Squires1989
Ravallion’s dynamic model(short-run and long-runtests)
Canned tuna in the S!"hailand and #hili$$ines
#rice linkages %et&een S and #hili$$ines markets!%ut not 'or "hailand
ose *c+lgorm 199, ivariate and multi-variatecointegration
ro.en /"! 0 and 2"in 3a$an
Su%stituta%ility %et&een 2" and /"! 2" and 0!not so much %et&een /" and 0
Sun and Hsu 1998
Sun and Chiang 1999
*ultivariate cointegration(/C*)
ro.en /" and 2" in"ai&an! 3a$an and South4orea
2" and /" e5hi%it similar long run $rice changetrends
Sun and 6ang 1999 *ultivariate
0R*0 &ith seasonal
ad7ustment
resh tuna in 3a$an and"ai&an
#rices linkages 'ound
Squires et al ::, ivariate cointegration ;SR <ranger causality
ro.en 2" and S43 in"hailand and S43 in 0mSamoa
Cointegration %et&een "hailand and 0m Samoa 'orS43 (leadershi$ o' angkok)
=o cointegration 'ound %et&een S43 and 2"
3eon et al ::> *ultivariate cointegration ;causality tests
ro.en S43 and 2" 0merican Samoa (#ago-#ago)! /uro$e (+taly!S$ain)! +vory Coast(0%id7ian)! 3a$an ("okyo)!atin 0merica (#uerto Rico
and /cuador)! and "hailand
<ood level o' integration %et&een all S43 markets
2" markets are not s$atially integrated (%et&een
+taly and "hailand)
=o integration %et&een S43 and 2"
3im?ne.-"ori%io et al:1:
*ultivariate cointegration ;
#arity tests ; causality
tests
ro.en 2" and S43 in"hailand! +taly! 3a$an!S$ain! rance! #uerto Ricoand /cuador! 0%id7an
Canned yello&'in in rance
and +taly
Canned ski$7ack in the 4!
<ermany! S0
<ood level o' integration %et&een all S43 marketsand %et&een all 2" markets at the hori.ontal level ;integration %et&een S43 and 2" in "hailand andS$ain or rance
Hori.ontal market integration on the canned tuna
markets 'or S43 (S0 and /uro$e) and $er'ect $ass-
through 'or S43! not 'or 2" in rance or +taly
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3emand models(
- ,inear or logarithmic- rdinar@ or inverse- +arshallian or Dicsian- 0otterdam or I<- tatic or d@namic- 4inal or derived demand- <isaggregated or aggregated data- U0 or #0 stimations-...
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Study Model and market Own-price elasticity Flexibility
4itson and *aynard (198A) 3a$an 1A9 'or high-valued 'ish :>
"aya (1989) 3a$an 1:> 'or tuna home consum$tion :9A
6essels and 6ilen (199@) +nverse demand 3a$an :9A (&hole 3a$an)
1@: (northern 3a$an)
11@ (southern 3a$an)
1:8
:>1
:88
/ales! Burham 6essels (199>) +nverse demand 3a$an(high valued 'ish)
1,> :,:
/ales and 6essels (1999) +nverse demand 3a$an
(high valued 'ish andmedium quality 'ish)
:>A to :818 (high)
:>@, to 1::: (medium)
1 to 1A8
1:: to 1A@
"ada (:::) og ordinary demand(3a$an)
:8 ('ro.en tuna) 1
Sun and Hsieh (:::) "hailandese im$orts 'rom"ai&an 'ro.en tuna
D to : ::D to ::
E&en (::1) "hailandese im$orts 'rom0 - 'ro.en S43
19 :D
Chiang! ee and ro&n (::1) Rotterdam inversedemand system (3a$anauction market)
118 ('ro.en 2")111 ('ro.en /")
D988 ('ro.en ")
:81 ('ro.en 2") (scale elast):8, ('ro.en /")
:1,> ('ro.en ")
Sun and Chiang (:1:) <eneral syntheticinverse demand system(<S+BS) ("hailandcannery-grade and 3a$ansashimi-grade tuna)
1::D (frozen YFT Thailand)
0.979 (frozen SKJ Thailand)
0.778 (frozen YFT Tokyo)
0.833 (frozen BET Tokyo)
1.073 (frozen BFT Tokyo)
:99D (frozen YFT Thailand) (!ale)
1.0"1 (frozen SKJ Thailand)
1."8# (frozen YFT Tokyo)
1."00 (frozen BET Tokyo)
0.93" (frozen BFT Tokyo)
Ja&an and Asia
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Study Model and market Own-price elasticity Flexibility
=ielsen (1999) +nverse demand (S$ain) AAA :A:
3a''ry and ro&n (::8) Bynamic 0+BS (4 Cannedtuna)
:19 to :8: (di''erent $roducts) 1D to D,
<uillotreau et al ::8 Bynamic ordinary *arshalliandemand (rance canned 2")
:1A >,9
3im?ne.-"ori%io et al ::9 "rans'er 'unction model(dynamic ordinary demand)(rance 'ro.en 2")
1@ to 1DD :,D to :8:
3im?ne.-"ori%io and <arcia
del Hoyo :1:
0+BS (canned tuna in S$ain) :A9 D,
Euro&e
Study Model and market Own-price elasticity Flexibility
Cam$%ell (199D) Retail S market 'or cannedtuna
:1, to :: D:: to ,D
ertignac et al (::1) inear demand 'unction &ith$oint elasticities ("hailand-6C#E cannedF 3a$an sashimi
1DD (#S 'leet)
DA ( 'leet)
:,D
:@:
#an and #ooley ::@
(cited in 4om$as et al :1:)
6C#E 'leet e5$orts to"hailand (canning) and 3a$an(sashimi)
1: (/" sashimi market)
,D (2" sashimi market)
19 (S43 can su$$ly increase)
111 (S43 can su$$ly decrease)
:1:
:1D
:D
::9
Baloon$ate (::) 0+BS Retail S market 'orcanned tuna (scan data)
1,> to 8: (%y 'irm 'or the %ig-A) :A, to :,:
4SA
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7rices are not made locall@ )ut glo)all@( no single Leet or
countr@ can aEect the price level and changes in locallandings ma@ have little conse>uences on price levels;correlation )etAeen >uantit@ changes?= price indeB for tuna could )e constructed on that )asis ;isit an o)*ective for the group?=. price indeB )@ species couldserve as a )asis for Fshing agreements largel@ )ased so faron tonnage rather than value ;eBample of the outh 7aciFc
6una 6reat@J >uires et al. 2''8= or for a forAard maret.
:ood pass-through eEects( little maret poAer eBercised at
all stages of the value chain9 Aith some eBceptions ;canned V46 in urope=.
6Ao diEerent value chains ;,,-sashimi and 7-canner@=9maing 546 and somehoA 56 and ,5 separated marets./an Ae imagine more maret connections in the future ;e.g.
V46=?...
3. Implications des résultats5#1 Cointe*ration models
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Can !e "o #$rther a%o$t the &arket inte"rationiss$e an' is it !orth!hile 'oin" it(ome ideas to move toAards eBplanations of the price d@namics(
,ooing for structural )reas matching the implementation of
management or trade polic@ measures ;e.g. glo)al sourcing of 7$:canneries decided )@ the # in 2''9 )an of 4<s hence lesssip*ac- )@ a feA pacers9 6/9...=.
tud@ing as@mmetr@ of price transmission along the chain Aith orAithout thresholds ;ined curve eEects9 menu costs9 60 and +-
60 cointegration modelsJ /han 1HH39 nders-ilos 2''19 aEr@2''%=
valuating maret poAer ;e.g. )@ the retailing industr@= or pricing-to-maret )ehaviour to loo at rent distri)ution eEects.
/onse>uences of too loA prices for primar@ Fsh ;elasticit@ ofsuppl@=?
7rice volatilit@ transmission through :0/D models ;Weaver X$atcher 2'''= or even )rea detection in the transmission of
volatilit@ ;ue9 DYrrman et al. 2''H=. 0ole of inventories ;/hiang etal. 2''1=? Is price sta)ilisation a desira)le o)*ective for the Ahole
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5# 3emand models An-price elasticities have )een found relativel@ loA ;around '.2'=
for canned tuna and relativel@ high ;1.2' to 1.&'= for froCen tunaon average OZ Q-eEect Z 7-eEect at the eB-vessel stage.Bplanations? ;diEerentiation9 maret poAer of retailers9conversion coe[cient9 varia)le mar-up9 menu costs9 maretshares of suppliers?...=
n the sashimi-grade apanese tuna maret9 elasticities Aere
found close to unit@9 or even a )it higher for 546 compared tofroCen 56 and V46 ;un and /hiang 2'1'=. changes in productionlevels Aould have rather neutral eEects on revenues. apanese auction prices of froCen 56 and V46 not aEected )@ apanese import prices of froCen 56 and V469 )ut rather
responded to structural changes in the mareting channels andincreasing suppl@ of farmed 546 ;un and Wu 2''=. 4eA studies looing at cross-price elasticities )etAeen tuna andmeat products. ;e.g. # retail maret of canned tuna \]V O '.33;Ming 1H8= and '.K2 ;Aen and 6roedson 1HH%=9 OZsu)stituta)ilit@ )etAeen product groups=. What a)out other
demand shifters ;green demand9 emerging marets9 health-safet@9eBchan e rate income?...
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)&pli*ations an' #$t$re tasks+ ma@ eBceed the marginal )eneFt of using it in a full maretmodel^^ 4ishing for the maret ma@ increase the rent and modif@the distri)ution of proFts )etAeen Fshers and oAners and alsohave Aelfare conse>uences ;5ertignac et al. 2''1=.
4leBi)ilit@ parameters as price responses to managementmeasures or to other suppl@ shocs ;energ@ cost9 a>uaculture9climate oscillations9 pirac@...= OZ need to com)ine demand modelsAith a more suppl@-side ;)ioeconomic= approach ;/amp)ell 1HH&J5ertignac et al. 2''1J 0eid et al. 2''3J /ha)oud 2'11=
#ncertaint@ also stems from the demand side( a lot to do Aithdemand shifters
,,-sashimi and 7-canner@( tAo independent value chains or one
single tuna maret ;via V46=?...
0esearch Aor to do on the Aa@ suppl@ meet demand ;panel dataanal@sis9 netAor approachJ_ see WolE 2'119 +ullon 2'11=
ther pieces of Aor of interest for +acroes;?=( determinants of4< Fshin ;alladarre :uillotreau <a orn 2'1' WolE uires