Analysing the economic impacts of a plant disease incusion using a geneal equilibium appoach Glyn Wittwe, Simon McKidy and Ryan Wilson 1 Abstact This study uses a dynamic multi-egional computable geneal equilibium (CGE) model to estimate the mico- and macoeconomic effects of a hypothetical disease outbeak. The extent of the incusion, the impact of the disease on plant yields, the esponse of buyes, the costs of eadication and the time path of the scenaio contibute to outcomes at the industy, egional, state and national levels. We also decompose the contibution of these individual diect effects to the oveall impact of the disease. This may povide some guidance as to aeas fo pioity in attempting to eadicate o minimise the impacts of a disease. The study also intoduces a theoy of dynamic egional labou adjustment in which economic events may lead to both eal wage diffeentials and woke migation between egions. 1 Glyn Wittwe, Cente of Policy Studies, Monash Univesity; Simon McKidy and Ryan Wilson, Plant Health Austalia, Deakin ACT. We would like to thank Ross Adams, John Bennan, Nicole McCoy and David Cook fo assistance with this poject and fo poviding helpful comments on the manuscipt. The Austalian Govenment povided financial suppot fo this eseach. 1
1. Intoduction This study examines the egional and national economic impacts of a hypothetical outbeak of the fungus Tilletia indica (the causal agent of Kanal bunt) in wheat cops in the wheat belt of Westen Austalia. The wok was initiated to povide a geneic model to assist in analysing the egional economic impact of any exotic plant pest incusion unde new plant industy cost shaing aangements being developed fo Austalia. A key diffeence between plant and animal industies in elation to the impact of exotic pests is that plant industies ae often highly egionally localised. To fully assess the impact of an exotic pest on a plant industy it is theefoe impotant to have a clea undestanding of the potential egional economic impacts of an exotic pest incusion. Kanal bunt was used as the case study pest on which to develop the geneic model to assess the egional and national economic impacts of a hypothetical exotic pest incusion. Kanal bunt has minimal impact on cop yield but is consideed a disease of political and quaantine impotance (Stansbuy et al. 2001). Fist descibed in Kanal, Hayana, India in 1930, it spead to Afghanistan, Ian, Iaq, Lebanon, Nepal and Pakistan. Subsequently, it has been detected on continents othe than Asia, fist in Noth Ameica, in Mexico in 1972. Moe ecently, it was detected in the USA in 1996 (Ykema 1996) and South Afica in 2000 (Cous et al. 2001; Stansbuy and Petoius, 2001). A numbe of nations have esponded to the theat of disease since 1983 with planting and seed industy quaantines and estictions. The impact of Kanal bunt on yields is minimal. Since only a small popotion of gains ae infected, the main poblem is with the peceived quality athe than quantity of output. It is likely theefoe that seed infected by the fungus will be downgaded o ejected by buyes. Thee have been a limited numbe of estimates of the potential economic effects of Kanal bunt. Stansbuy et al. (2002) modelled the isk of T. indica impacting on the wheat industy in Westen Austalia. This suggested that fist detection of the pathogen could ange fom 4 to 11 yeas, with an economic impact on between 8 and 24 pe cent of the value of poduction in WA. Bennan et al. (2004) classified the costs associated with an outbeak of Kanal bunt as diect costs, eaction costs and contol costs, and estimated the elative impotance of each cost fo a hypothetical outbeak in the Euopean Union. We use the dynamic, computable geneal equilibium (CGE) Monash Multi-Regional Foecasting (MMRF) model fo this task. The methodology has been applied to a numbe of othe hypothetical incusions affecting othe cops in vaious egions. Ou inputs into the model include the initial impacts of the incusion on output and access to expot makets, the timeline of fighting and ovecoming the disease, and the associated diect costs. In the geneal equilibium appoach, the loss of jobs and declining investment in a paticula industy following a disease outbeak may be compensated to some extent by the movement of labou and capital into othe sectos ove time. In this espect, the pespective offeed by ou dynamic CGE modelling diffes fom that of othe appoaches such as equilibium displacement modelling (EDM). In EDM o othe patial equilibium famewoks, the distibution of gains between poduces and othe agents fom given supply o demand shifts is estimated fo a specific set of industies (see Zhao et al. 2003, 1
James and Andeson 1998). Ou CGE famewok diffes by examining impacts beyond the industy-specific level: it pojects yea-to-yea impacts on national and egional aggegate consumption, and on othe maco- and micoeconomic measues. The CGE appoach uses an input-output database with a egional disaggegation that includes compehensive costs and sales stuctues. These ae impotant in estimating the contibution of diffeent consequences of the disease (i.e., lost poductivity, quaantine estictions, additional cop spaying) to the oveall outcome, and, togethe with the sales stuctue of the industy, may be useful in devising stategies fo dealing with disease outbeaks. We also weigh the contibutions of diffeent diect effects on the oveall outcome. Given the egional and sectoal detail in the maste database, we can apply the methodology to vaious plant disease outbeaks aising in paticula cops and egions. 2. The model MMRF is a dynamic, multi-egional CGE model of Austalia (Naqvi and Pete 1996; Adams et al. 2002). In a specific application, it is computationally convenient to aggegate the model with the choice of aggegation detemined by the focus of the study. This aggegation is pepaed fom the maste database, discussed in section 2.2. Fo the application epoted hee, we use a two- aggegation of the maste database egion, with Westen Austalia (WA) and the est of Austalia (ROA) epesented sepaately. In the sectoal dimension, we aggegate to 27 industies. One of these industies is the gains industy, which we assume uses the same inputs to poduce eithe wheat o baley following a constant elasticity of tansfomation (CET) fom. In total, thee ae 28 commodities, with the emaining 26 industies each poducing a unique commodity. In the egional dimension, the model also includes top-down detail of the statistical divisions of the state in which the outbeak occus. A specific modification fo this poject allows us to ascibe poductivity shocks at the level of statistical divisions. This is useful, given that a specific sub-state egion (the wheat belt) is affected by the disease outbeak. The theoy of MMRF is simila to that in national dynamic CGE models such as MONASH (Dixon and Rimme 2002). Each industy in MMRF selects inputs of labou, capital and mateials to minimise the costs of poducing its output. The levels of output ae chosen to satisfy demands and demands eflect pices and incomes. Investment in each industy eflects ates of etun and capital eflects past investments and depeciation. The main diffeence is in the egional dimension. In MMRF, thee is a given industy in each of two egions, instead of a single national industy. Commodity uses in MMRF have in this specific aggegation thee souces of supply (Westen Austalia, the est of Austalia and impots) instead of two (domestic and impoted) as in MONASH. And MMRF has a national govenment, and a govenment and household in each egion instead of having a single govenment and a single household. Regions in MMRF ae specified as sepaate economies, linked by tade. MMRF imposes a fixed exchange ate and fee tade between egions, and common extenal taiffs. In this sense, MMRF emains a national model, athe than intenational. This means that 2
behaviou in foeign makets is detemined outside the model (i.e. exogenously). In dynamic analysis, MMRF is un in two modes: foecasting and policy. In foecasting mode, it takes as inputs foecasts of maco and tade vaiables fom oganisations such as Access Economics (2003) and ABARE (2003), togethe with tend foecasts of demogaphic, technology and consume-pefeence vaiables. It then poduces detailed foecasts fo industies, egions and occupations. In policy mode, it poduces deviations fom foecast paths in esponse to shocks elevant to the hypothesis being exploed, such as changes in taxes, taiffs, technologies, wold commodity pices and, in agicultue, disease outbeaks. 2.1 The key assumptions CGE models such as MMRF can be un unde many diffeent sets of assumptions concening maco- and mico-economic behaviou. The key geneal assumptions undelying ou simulation follow. In unning the model in dynamic mode, we compae yea-by-yea a deviation simulation containing the scenaio being studied with a business-as-usual foecast simulation. Public expenditue and taxes We assume that the disease outbeak makes no diffeence to the path of eal public consumption. Howeve, adjustments in income tax ates compensate fo changes in govenment evenue and outlays associated with changes in the level of economic activity. Labou maket Equation Section (Next)The egional labou maket adjustment mechanism, in levels, is given by : W t W 1 1 t 1 EMP t LS α = + t Wf t Wf t 1 EMPf t LSf (1) t The intepetation of (1) is that if the deviation shock weakens the labou maket in egion and peiod t elative to foecast, eal wages in deviation will fall elative to foecast Wf t W t. In addition, thee will be an initial enlaged gap between labou maket demand LS t EMPf t LSf t the gap between demand and supply will gadually etun to foecast though a futhe decline in eal wages. The speed of labou maket adjustment is govened by α, a positive 2 paamete. The egional labou supply equation is: EMP t and supply, elative to foecast levels and. In successive yeas, ( W t ) ( ) ( Wf t ) ( ) γ γ t = q γ q q q t t t t t q q LS (2) γ LSf W S Wf Sf 2 Pete Dixon of the Cente of Policy Studies devised the egional labou maket adjustment theoy. 3
The deviation in egional labou supply fom foecast depends on the deviation in q q S t is a measue of egional elative to national eal wages fom foecast. In (2), ( ) q W γ t labou esponsiveness to eal wages summed acoss all egions, whee γ is a positive paamete and S q t the shae of egion q in national employment. This equation implies that should the deviation in eal wages in a egion fall elative to the deviation in national eal wages fom foecast, its labou supply will fall, while that in othe egions will ise. Combining (1) and (2), adjustment in the labou maket in a given egion will initially occu via a combination of additional unemployment and lowe eal wages. Unemployment will eventually etun to foecast ates, with lowe eal wages. As eal wages fall elative to contol, the egion s labou supply will also fall. Within this theoy, long un labou maket adjustment occus as a combination of inte-egional labou migation and changes in egional eal wage diffeentials. Rates of etun on industy capital stocks In simulations of the effects of shocks, MMRF allows fo shot-un divegences in the atios of actual to equied ates of etun fom thei levels in the base case foecasts. Shot-un inceases/deceases in these atios cause inceases/deceases in investment. Movements in investment ae eflected with a lag in capital stocks. These adjustments in capital stocks gadually eode initial divegences in the ate of etun atios. Poduction technologies MMRF contains vaiables descibing pimay-facto and intemediate-input-saving technical change in cuent poduction, input-saving technical change in capital ceation, and input-saving technical change in the povision of magin sevices (e.g. tanspot and etail tade). In ou simulation, all these vaiables ae held on thei base case foecast paths except fo the specific shocks concening wheat in Westen Austalia elevant to the scenaio. 2.2 The database A significant pat of using a CGE appoach to examine diffeent hypothetical disease incusions at the egional and national level is to have at ou disposal highly disaggegated egional input-output databases. The maste database used to pepae egional aggegations fo specific pojects is based on the national published input-output table (ABS 2001). This has been disaggegated in both the sectoal and egional dimensions. The sectoal detail now includes many agicultual commodities not available in published ABS data. The egional dimension includes input-output tables fo each of 57 statistical divisions in Austalia. Hoidge et al. (2003) detail the souces of the maste database, an outline of its pepaation, and the methodology used to devise inte-egional tade matices to connect the input-output databases of each egion. 4
3. The impacts of a Kanal bunt outbeak In estimating economic effects, we conside how widespead the disease is on detection. Muay and Bennan (1996) have outlined fou diffeent outbeak cases. In case 1, the outbeak is small and isolated, with the likelihood of disease containment being achieved though pohibition of wheat gowing on affected fams fo seveal yeas. Case 2 concens a moe scatteed outbeak that potentially may be contained. In case 3, thee is a wide distibution of disease in a egion o distict. In case 4, the disease is widely distibuted thoughout Austalia. Thee ae many aeas of Austalia s wheat gowing egions whee Kanal bunt would establish and spead and the climate suitability fo this pathogen in Austalia has been detemined by Muay and Bennan (1998) and Stansbuy and McKidy (2002). 3.1 Assumptions concening diect impacts Ou scenaio is quite pessimistic, in so fa as we assume a elatively widespead outbeak. In eality, we might expect an outbeak to be detected in isolation, and theefoe elatively easy to manage. Howeve, as is evident in what follows, economic losses though quaantine measues ae likely to be much geate than disease management and eadication costs. We need to assume the diect yea-to-yea impacts of a hypothetical incusion in ode to un the dynamic CGE model. These include additional eseach and administation costs aising fom fighting the disease and spaying costs incued by the industy and public bodies. In addition, we need to estimate the impact of the incusion in tems of lost poductivity o downgading (actual o peceived) of quality. Quaantine estictions in oveseas makets ae paticulaly impotant fo cops that ae lagely expoted. And finally, thee is the question of how many yeas it takes to eadicate a disease and estoe lost makets. We assume that the disease is scatteed acoss the wheat belt egion, a case 3 scenaio unde the classification outlined by Muay and Bennan (1996). Fighting the disease aises the input costs fo vitually all Westen Austalian wheat fames, as we assume that the scatteed natue of the incusion put all wheat fams in the state at isk, and theefoe in need of fungicide applications. The supply side of the model contains shiftes that allow us to shock diffeent pats of the cost stuctue, including intemediate inputs and pimay inputs. We incease specific intemediate-input equiements to depict the effect of additional fungicide equiements, which cost $9 million. We also assume that thee is a yield loss of 0.1 pe cent within the wheat belt, ascibed via a pimay facto technology shock. On the demand side, we assume two diffeent advese effects. The fist is the peceived eduction in the quality of wheat, which lowes the pice. The second effect is that of lost expot makets. We assume that following the initial outbeak in 2005, all Austalia s wheat pots ae affected: those foeign nations who pohibit the impots of wheat affected by Kanal bunt will tempoaily ban all Austalian wheat. This blanket ban lasts fo thee months. We assume thee is little scope fo catch-up sales in the emainde of the yea, so that outside Westen Austalia, expot demand shinks by 10 pe cent. This is based on 40 pe cent of total expots being sold to nations who ban wheat fom souces with Kanal 5
bunt outbeaks, with the ban on wheat poduced outside Westen Austalia lasting fo one quate of a yea. 3 In Westen Austalia, we assume that makets banning wheat fom egions with Kanal bunt outbeaks will maintain the ban until the disease has been eadicated in the state. In 2006, expot demand fo wheat shipped fom Austalian pots outside Westen Austalia is fully estoed. The ban on Westen Austalian wheat continues. Even if Kanal bunt is confined to the wheat belt, the ban effectively extends to the entie state, because wheat oiginating in the wheat belt may be shipped out though any of the state s gain pots, given geogaphic consideations. Since wheat vaieties diffe between states, we allow impefect substitution of wheat between easten states and Westen Austalia, fo domestic uses. In ou hypothetical scenaio, quaantine estictions, educed yields and additional poduction costs continue in Westen Austalia until 2010, and expot demand is not fully estoed until the following yea. 3.2 The disease outbeak and quaantine phase: 2005 to 2009 The labou maket theoy of this vesion of MMRF opeates at the egional level. Theefoe, we begin with the impact of the scenaio at the state macoeconomic level. Figues 1 shows the impact of the scenaio on the labou maket vaiables explained in equations (1) and (2). Initially, the advese shock of the Kanal bunt scenaio dives down both employment and egional wages in Westen Austalia. Employment falls by 0.22 pe cent (as measued by industy wage-bill weights) o 2,200 jobs in 2005 elative to contol. 4 In yeas subsequent to 2005, eal WA wages decline futhe. This povides a stimulus fo WA sectos othe than gains, and educes the gap between WA s labou supply and demand. The eduction in employment is explained by two factos. Fist, WA s aggegate expenditue moves away fom investment (due to a decline in ates of etun on capital following the disease outbeak and esultant loss of expot makets) and consumption towads expots and impot eplacement (figues 2 and 3). Second, thee is a eduction in WA s tems-of-tade (ie, the pice of expots divided by the pice of impots, fo both intestate and intenational tade) (figue 4). The switch in the composition of WA s expenditue educes employment in the shot un at any given wage because expot and impot eplacement activities ae less labouintensive than investment and consumption activities. The tems-of-tade eduction educes employment in the shot-un via the maginal poduct/wage elationship: 3 This assumption of the duation of bans on wheat fom Austalia is suppoted by an incident in Febuay 2004 in which an impoting county ejected wheat fom Austalia, asseting that it was infected with Kanal bunt. A numbe of makets subsequently questioned the status of all Austalian wheat, iespective of state boundaies. Tende negotiations wee suspended fo two weeks in the case of one county. These did not esume until extensive tests confimed that Kanal bunt was not pesent anywhee in Austalia. 4 As many fames ae owne-opeatos, they will suffe a dop in imputed wages that fa exceeds the 0.14 pe cent decline in eal WA wages oveall. Theefoe, initial job losses in agicultue will be smalle than implied by ou assumption that all wages in WA deviate fom foecast by an equal pecentage. 6
MP L (K/L) = (W/P c )x( P c /P g ) (3) In (3), the value of the maginal poduct of labou to employes, that is MP L times the pice of GDP (P g ), is equated to the wage ate (W). In (3), we wite this elationship as the poduct of two atios. The fist is the eal wage as seen by wokes and the second is the consume pice index (P c ) divided by the pice deflato fo GDP (P g ). With a temsof-tade decline, P c /P g inceases because P c includes the pices of impots but not expots, wheeas P g includes the pices of expots but not impots. Unde ou assumption of sluggish adjustment in the eal wage (that is, little shot-un change in W/P c ), an incease in P c /P g causes an incease in MP L, equiing an incease in the capital/labou atio (K/L). Because K (ie., capital plus land) is fixed in the shot un, L must fall. As it weakens the tems of tade, the diect loss of expot makets educes domestic absoption within Westen Austalia. The effect (eflected in WA s eal exchange ate shown in figue 4) facilitates an incease in expots fo commodities othe than wheat, and inhibits impots (figue 3). Oveall, the changes in expot and impot volumes ae sufficient fo the tade balance to move towads suplus, by $1.3 billion (figue 3). This seemingly paadoxical esult aises because expot volumes of all commodities othe than wheat incease duing the peiod when at least some Austalian wheat is banned in some expot destinations. Figue 1: Effects of disease outbeak on Westen Austalia s labou maket (% deviation fom baseline) 0. 05 0-0.05-0.1 Employment 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 Labou supply Real wage -0.15-0.2-0.25 Fo seveal yeas fom 2005, WA s investment slowly ecoves elative to contol, as esouces move to othe sectos. At the same time, the tems of tade gadually impove (figue 4). This is patly because investment and consumption move back towads 7
contol, inceasing WA s domestic absoption and theeby deceasing the volume of commodities available fo expot. As expot volumes decease, expot pices incease, eflecting finite expot demand elasticities (i.e., an elasticity of 4 indicates that fo each 4 pe cent decease in expot volumes, thee is a 1 pe cent incease in expot pices). Figue 2: Effects of disease outbeak on WA s investment and consumption: (% deviation fom baseline) 1.0 0.5 National eal consumption 0.0-0.5 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022-1.0-1.5 WA eal investment WA eal consumption -2.0-2.5 Figue 3: Effects of disease outbeak on WA s tade balance and volumes: (% deviation fo expots and impots; $bn deviation fo balance of tade) 1.5 Balance of tade ($ billion) 1 0.5 Expot volume 0-0.5-1 2004 2007 2010 2013 2016 2019 2022 Impot volume -1.5 8
Figue 4: Effects of disease outbeak on eal exchange ates and tems of tade (% deviation fom baseline) 3 2.5 WA eal depeciation 2 1.5 1 0.5 0-0.5-1 -1.5-2 Nat. eal depeciation 2004 2007 2010 2013 2016 2019 2022 Nat. tems of tade WA tems of tade Figue 5: Effects of disease outbeak on WA s income, employment and capital stocks (% deviation fom baseline) 0.2 0.15 0.1 0.05 0-0.05 Real GSP Capital stocks 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022-0.1-0.15-0.2-0.25 Employment Pivate consumption is educed in 2005 by 2.0 pe cent (about $1.1 billion), consideably lage than the loss in eal GDP of 0.14 pe cent (figue 5). This gap between lost income and lost consumption is explained mostly by the tems-of-tade decline. As is shown in 9
figue 4, WA s tems of tade fall in 2005 by 1.5 pe cent. The Austalia-wide tems of tade ae also shown, with the WA contibution accounting fo vitually all the decline. With WA s intenational plus intestate expots in 2005 being foecast at $53 billion, a tems-of-tade fall of 1.5 pe cent is equivalent to a loss in disposable income (and theefoe consumption) of $800 million (=53x0.015x1000). Afte 2005, eal wages continue to fall, allowing the gap between employment and labou supply to close, so that by 2008, with no emaining gap elative to foecast, thee is no futhe downwad pessue on WA s eal wages (figue 1). Without elimination of the disease outbeak, and emoval of associated oveseas quaantine estictions, we would expect WA s eal wages to emain below contol, but without futhe decline. The state s shae of national labou supply would also stabilise below contol, dagged down by the eal wage. Figue 6: Effects of disease outbeak on WA s wheat output, expot volumes and expot pices (% deviation fom baseline) 5 0-5 Expot pice 2004 2007 2010 2013 2016 2019 2022-10 Output -15-20 -25 Expot quantity Figue 6 shows the impact of the disease outbeak on WA s wheat output and expots. The gain gowing egions of Westen Austalia ae dominated by mixed fam entepises. Theefoe, scope exists fo switching fom one cop to anothe o moving poduction away fom gains into livestock. Figue 7 shows that thee is a small degee of switching fom gain poduction to othe boadace activities between 2005 and 2008. The switching only patly compensates fo lost incomes in gain poduction. Within gains poduction, baley s value-shae of output in Westen Austalia in 2006 is 20 pe cent in the base foecast, ising to 27 pe cent in the deviation scenaio in 2006. We assume within the model that the tansfomation paamete is 2, so that fo each 1 10
pe cent ise in the output pice of baley elative to the composite gains pice, output of baley ises by 2 pe cent moe than composite gains output. Figue 7: Effects of disease outbeak on Westen Austalia s agicultual outputs (% deviation fom baseline) 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0-0.2-0.4 Othe agicultue Sheep Othe cops 2004 2007 2010 2013 2016 2019 2022 Figue 8: Effects of disease outbeak on eal incomes of main WA wheat-gowing egions (% deviation fom baseline) 0.5 0-0.5-1 -1.5-2 -2.5-3 -3.5-4 -4.5-5 2004 2007 2010 2013 2016 2019 2022 South east/goldfields Mid West Geat Southen Wheat belt 11
At the statistical division level, the disease outbeak has a sevee effect on the wheat gowing egions of Westen Austalia. Figue 8 shows the wheat belt s eal output (eal goss egional poduct o eal GRP) dopping by between 3 and 4 pe cent until the disease is eadicated. The impact of the disease outbeak on the eal disposable income of these egions is lage than the impact on eal GRP, due to the advese tems-of-tade effect. In the wheat belt, wheat accounts fo aound 25 pe cent of eal income. In the scenaio, the expot pice of wheat in WA falls by aound 15 pe cent (figue 6). This fall is equivalent to a cut in eal disposable income of 3.75 pe cent (=0.25 x 15%). This compaes with a statewide decline in the tems of tade in 2005 of 1.5 pe cent. Combining the decease in eal output with the tems-of-tade decline, the wheat belt s spending powe deceases by aound 7 pe cent until eadication of the disease. Ou model allows fo the movement of output fom wheat to baley without changes in inputs, some divesion of gains into livestock inputs in esponse to changing elative pices and eallocation of poductive esouces to othe activities ove time. But such measues can only patly alleviate the negative impact of the disease on the egion. The othe egions shown in figue 10 ae not quite as seveely affected, because wheat s contibution to local income is less: 12.5 pe cent in the Mid West, 5.7 pe cent in Geat Southen and 2.0 pe cent in South East/Goldfields. 3.3 Decomposition of diect impacts Table 1: A decomposition of the impacts of the Kanal bunt outbeak in 2005, % change fom 2005 baseline Total Spay/ Quality WA quaantine ROA quaantine yield downgade National Real GDP -0.02 0.00-0.01-0.01 0.00 Employment -0.02 0.00-0.01-0.01 0.00 Capital stocks 0.00 0.00 0.00 0.00 0.00 Aggegate consumption -0.18 0.00-0.08-0.08-0.02 Aggegate investment -0.13 0.00-0.04-0.04-0.03 Westen Austalia Real GSP -0.14 0.00-0.07-0.08 0.00 Employment -0.23 0.00-0.11-0.12 0.01 Capital stocks 0.00 0.00 0.00 0.00 0.00 Aggegate consumption -2.12 0.00-1.05-1.12 0.05 Aggegate investment -1.16 0.00-0.59-0.60 0.03 Wheat output -12.9-0.1-5.9-7.0 0.1 Wheat expot volume -17.6-0.1-8.4-9.5 0.4 Wheat output pice -17.2-0.1-8.5-8.7 0.1 One way of assessing the impact of each of ou assumptions on the simulated outcome is to decompose the shocks to evaluate each contibution to the oveall esult. We do this fo a single yea, 2005, in which the geatest losses occu. The columns in table 1 decompose individual effects. Fo example, the column labelled spay/yield shows the impact of additional spaying costs and educed yields. Ou database shows that ove 95 12
pe cent of Westen Austalia s wheat is expoted. Hence, quality downgades and quaantine estictions on Westen Austalian wheat in foeign makets dominate economic losses. Fo example, these two columns account entiely fo the decline in WA s aggegate consumption and investment elative to foecast, with a small positive effect fom the tempoay quaantine estictions on intestate wheat expots. 3.4 Disease elimination and maket estoation phase: 2010 onwads The elimination of the disease in 2010 bings small intemediate and pimay input poductivity impovements and, moe impotantly, a patial estoation of expot makets that is completed in 2011. Investment in Westen Austalia suges above contol in 2010, and ises futhe with additional favouable demand shocks in the following yea (figue 2). The jump in investment induces a ise in employment well above labou supply in the state, so that unemployment is educed elative to foecast (figue 1). Figue 3 shows the tems of tade impovement aising in 2011. Fom 2012 onwads, investment dampens and employment falls slightly. As long as employment emains above labou supply, thee is upwad pessue on egional wages, so that by 2022, eal wages ae moving eve close to foecast. Aggegate consumption jumps above contol with full estoation in 2011 and emains thee fo the est of the simulated time hoizon. This is due to the balance of tade suplus un fom 2005, in which WA has a compensating accumulation of foeign financial capital (elative to contol). With employment and eal wages in Westen Austalia meging towads contol afte 2013, aggegate consumption pesists above foecast, eflecting educed debt-sevicing payments to foeignes. As an indicato of the national welfae loss aising fom the disease outbeak, the pesent value of the deviation in national eal aggegate consumption (as shown in figue 2, discounted at 6 pe cent) is - $1,280 million (including all yeas to 2022). Figue 5 shows the impact of the scenaio on WA s aggegate factos of poduction and eal goss state poduct (GSP). Industies not affected the diect advese effects of the scenaio in Westen Austalia benefit fom a polonged peiod of lowe eal wages befoe and afte the estoation. This induces additional investment in these industies, so that eal GSP and capital ise above contol. This in pat esults fom compositional change, with esouces moving to elatively capital-intensive mining. 4. Conclusion This analysis of the economic impacts of a plant disease incusion indicates the potential of a dynamic CGE model as an analytical tool in assisting with categoising of exotic plant pests as pat of a plant industies cost shaing ageement. CGE modelling pesents a numbe of aspects elevant to the issue of public vesus industy funding; these ae not necessaily available in a compaative static and/o patial equilibium appoach. In the case of a hypothetical Kanal bunt outbeak, expected foeign quaantine estictions dominate economic losses. Theefoe, isolation of the disease, if possible, and estictions on movements of machiney and wheat within the affected aea may be moe cost 13
effective than elimination of the disease. In the scenaio descibed in this pape, this may be impactical when the disease is scatteed ove a wide aea on detection. Geneally, the need to eadicate athe than confine the disease becomes stonge as poductivity losses incease elative to quaantine losses. Fo example, the impacts of foeign quaantine measues against gape expots would be small compaed with poductivity losses in the event of an outbeak of Piece s disease that led to the widespead emoval of vine stock in a wine-poducing egion. At the egional level, the dynamic CGE appoach povides new insights. Fo example, we can eadily distinguish between eal output and eal disposable income, because we captue the impacts of changes in the tems of tade. As pat of this study, we intoduced a egional labou maket adjustment theoy with the effect that pesistent disease in an industy would esult in long-un lowe egional eal wages in the advesely affected aea, combined with lowe labou supply. That is, the negative impact would esult eventually in inte-egional movements of labou. In addition, adjustments to capital stocks ove time estoe ates of etun on capital to baseline levels. Consequently, welfae effects aising fom an incusion ae spead via lowe wages beyond the industy of oigin, and via inte-egional migation and eallocation of investment beyond the egion of the outbeak. While this povides a theoetical basis fo some public funding of plant disease management, leaving aside souces of maket failue, it does not pescibe the exact contibutions that industies and govenment should make in cost shaing ageements. Ou assumptions concening facto mobility imply that we cannot use diect impacts on individual industies and egions as indicatos of welfae. Even statewide measues of welfae need qualification. While we could calculate the net pesent value of aggegate consumption elative to foecast in a egion as a measue of welfae, this is confounded by inte-egional migation. The net pesent value measued at the national level emains the pefeed welfae indicato. In the case of any hypothetical incusion, we ae able to vay the assumptions concening the timeline of an outbeak, and associated costs aising fom fighting the disease, and damage to the industy though lost output o lost makets. Whethe losses occu via damage to poductivity o damage to sales, the dynamic CGE appoach povides a method of estimating industy, egional and national impacts. 14
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