a comparison of three economic impact models

Tourism Economics 2008 14 (4) 769ndash789

A comparison of three economic impactmodels for applied hospitality and

tourism research

MARK A BONN

Dedman School of Hospitality College of Business Florida State University 1 ChampionsWay UCB Room 4104 Tallahassee FL 32306-2543 USA E-mail mbonncobfsuedu

JULIE HARRINGTON

Center for Economic Forecasting and Analysis Florida State University TallahasseeFL USA

This study examines the differences between three economic impactmodels the capacity utilization model (CUM) Regional EconomicModels Inc (REMI) and the impact analysis for planning (IMPLAN)model with a view to providing insights into their applicability forhospitality and tourism educators and researchers Four databaseshave been used to compare the results concerning total outputincome and employment The results were most dissimilar for thelsquoincomersquo variable The difference in income lies in the fact that thethree models estimated income in three different ways The CUMestimated lsquopayrollrsquo REMI estimated lsquodisposable personal incomersquo andIMPLAN estimated lsquovalue addedrsquo Due to the different incomemeasurements REMIrsquos income estimates were the highest while theCUMrsquos were the lowest This study does not strive to recommend oneeconomic impact model over another however it does examine thebehaviour of the respective models concerning various data sets anddescribes the underlying characteristics of the models

Keywords economic impact tourism models IMPLAN REMIcapacity utilization model (CUM)

Tourism contributes significantly to the US economy as it impacts a wide rangeof business sectors and augments employment and payroll income During2003 total tourism-related direct and indirect employment was 54 million and25 million respectively (Kuhbach and Herauf 2005) The tourism industryrsquos

The authors would like to thank the Apalachee Regional Planning Council and the Tampa RegionalPlanning Council for providing the opportunity to use the region-specific REMI software for theirrespective counties

TOURISM ECONOMICS770

value added grew 45 to US$285 billion which represented 26 of the GDPfor the period 2001ndash2003 (Kuhbach and Herauf 2005) Moreover tourismprovides tremendous benefits for federal state and local governments in theform of taxes (for example excise sales income and property taxes) In 2004the industry generated an estimated US$100 billion in taxes based on US$5464billion of direct sales from tourism (Travel Industry Association of America2005 ndash personal communication with Dr Tien Tian)

The economic impacts of tourism are frequently analysed using economicimpact modelling software The objective of this paper is to compare threeeconomic impact models (the capacity utilization model (CUM) RegionalEconomic Models Inc (REMI) and the impact analysis for planning (IMPLAN)model) using four visitor survey expenditure databases The study also examinesprevious tourism economic impact studies (from 1990 to current) to determinemethodologies pertaining to CUM REMI and IMPLAN

In doing so the State of Florida was selected to provide data sets for analysisof the economic impact models Florida was selected because tourism is thenumber one industry due primarily to its natural resources a favourableclimate an immense shoreline theme parks professional and major universitysports major airports and cruise industry ports cultural events and retirementcommunities The number of Florida tourists reached a record 768 million in2004 and is projected to grow to 89 million by 2010 (Visit Florida 2006)Currently 13 million Florida jobs are related directly or indirectly to tourismand are projected to grow to between 15 and 18 million by 2010 The 2005Florida Visitor Study reported that the state collected US$37 billion intourismrecreation sales taxes in 2005 that is US$62 billion was infused intothe statersquos economy during the year through tourist expenditures The studyalso noted that tourism expenditures supported 948700 jobs in 2005 (VisitFlorida 2005) Tax revenues accounted for about 20 of the total tax revenues(in sales and use taxes) collected (Baker and Aydin 2005)

Literature review of economic impact models

There have been various studies relating to the economic impact estimation oftourism spanning the past 20 years however few articles exist that comparethe performance of those models Following is a literature review of several ofthe studies that have examined economic impact modelling and performancewith respect to the tourism industry Stynes (1999) conducted numerous studiesthat focused on the economic impacts of tourism He outlined severalapproaches that researchers might employ including four typical approaches(a) subjective estimates that rely on expert opinion (b) secondary data inaggregate form using existing estimates tailored to the situation (c) secondarydata in disaggregate form allowing a finer resolution to fit the situation and(d) primary data andor formal models usually involving visitor surveys andregional economic models It is the latter issue of economic impact modellingthat this paper will address Archer (1984) described the sources available toacquire data and the necessary processes to adapt these data for use in inputndashoutput (IO) modelling He noted that a local or regional consumer expendituresurvey was rarely available and was both expensive and time-consuming However

771Three economic impact models

this study was able to utilize those lsquoexpensive and time-consumingrsquo data setssince the local verifiable survey data was collected based on a series of personalinterviews using the randomized sampling design Hence this would serve tostrengthen the ability of this paper to allow more accurate comparisons of CUMREMI and IMPLAN

Ryan (2003) discussed the economic impacts of tourism and economic impactmodels He pointed out that while IO analysis further refined the basicmultiplier processes the transference to service (in particular tourism sectors)was hampered by the lack of definition with regards to the tourism industryThere are no SIC or NAICS codes assigned solely to the tourism sectorCurrently there are only two NAICS codes pertaining to two tourism-relatedsectors1 Convention and Visitorrsquos Bureau and Administration of GeneralEconomic Programmes As can be surmised the tourism sector is still not fullydefined by NAICS

A seminal work and highly quoted tourism economics text Economics ofOutdoor Recreation (Clawson and Knetsch 1971) discussed the economic impactof outdoor recreation including tourism on local areas Although the book didnot cover economic impact modelling per se it provided an economic impactfoundation for the calculation of multipliers and procedures regardingexpenditure surveys

In Travel Tourism and Hospitality Research A Handbook for Managers andResearchers (1994abc) Frechtling provided an overview of Archer and Owensrsquosad hoc model (developed individually for each area studied) He recommendedusing the ad hoc model and the IO approach depending on the budget availableand the expertise of the researchers Frechtling suggested that IMPLAN wasa cost-effective way to measure total tourism impacts on an arearsquos economy Inconclusion he advocated that the time had come to progress beyond measure-ment issues and begin to draw conclusions that could be applied broadly topublic marketing planning and development decision making

In 2001 The Connecticut Center for Economic Analysis (CCEA) performedan economic impact study of Connecticutrsquos travel and tourism industry usingREMI They employed a mix of survey methods to calculate a reliable estimateof total tourism-related economic activities in Connecticut They examined 8counties and 11 tourism lsquodistrictsrsquo Their results revealed that in relative termsConnecticutrsquos travel and tourism industry employed a larger fraction of workersthan manufacturing or financial insurance and real estate (FIRE)

Rickman and Schwer compared the REMI and IMPLAN economic modelsin 1993 and 1995ab To date their studies are the only ones that exist theexception being a paper by Perlich (2005) that describe the differences betweenREMI and IO Crihfield and Campbell (1992) and Deller (1992) ultimatelyfound that based on the structural differences in the REMI and IMPLANmodels differences did not affect the multiplier estimates significantly In their1995b study Rickman and Schwer examined how multipliers compared amongvarious versions of the models They found that there was a tendency forIMPLAN to overestimate the regional purchase coefficients (RPCs) in theservice sectors such as in resource-based and tourist-based economies It wasdiscussed however that this would be easy to remedy based on the userrsquos abilityin IMPLAN to alter or adjust RPCs However this limitation could result inunintentional underestimation because it is arbitrary and non-scientific


Description of models

The capacity utilization model (CUM)

The capacity utilization model (CUM) was developed originally in 1990 byHenry Fishkind for economic analysis of tourism in the State of Florida Fishkindand Associates conducted numerous tourism studies in Florida and other statesOne of those studies was summarized in the Central Florida Visitor IndustryReport in 1989 With respect to tourism the CUM quantifies the economicimpact (labour and fiscal) that tourism has on the local economy The basicassumption of CUM is that it uses the hotelmotel industry as a baseline In orderto measure the capacity of the tourism sector the model uses the hotelmotelindustry as a baseline and obtains total numbers of rooms available and occupancyrate information from a national industry reporting service Smith Travel Re-search2 Additionally surveys of local lodging properties for each of the fourstudies were conducted to determine occupancy rate average daily rate andhistorical occupancy during the specific time of the event and estimates of totalnumbers of rooms sold to event attendees This information was compared withthe Smith Travel information to provide an increased accuracy The models alsoused the following information based on survey instruments estimates of averageparty size for those using hotel and motel accommodations the average triplength in nights for those staying in hotelsmotels and the proportion of visitorswho stay in hotelmotels versus those staying with friends and relatives incampgrounds condominiums as well as visitors coming just for the event andspending no evenings in the area Visitor expenditures (hotels transportationentertainment and food etc) were also obtained through the survey

Using the CUM to estimate the total number of visitors is especially valuablewhen the event is open access and visitor numbers cannot be obtained by thetotal number of tickets sold The CUM has been used by Bonn and Bell (1998and 2003) to estimate economic impact recreational (use) value and visitornumbers associated with natural springs and artificial and natural reefs Thesestudies involved 21 Florida counties over a six-year period Economic impactis measured by the direct and indirect output and employment created byvisitors as well as total wages paid to visitor industry employees and thegeographic distribution of the paid salaries The CUM does not address inducedimpacts Multipliers in this model for Tampa Florida and Tallahassee Floridawere obtained using the US Department of Commerce database on countymultiplier statistics A multiplier of 15 was provided and used to estimate thetotal output (that is direct expenditures (Table 1) times 15 = total output)3 Directemployment and wages were estimated using the latest statistics published byEconomic Census the US Census Bureau (Economic Census 2002) For the twoevents and two quarterly databases studied in this article the 1997 EconomicCensus was used and updated using the Consumer Price Index (that is CPI)for inflation Figure 1 outlines the theoretical framework for the calculation ofeconomic impact estimates in the CUM

The REMI model

REMI 2002 is a widely used dynamic integrated IO and econometric modelREMI is based on neoclassical theory and was founded in 1980 The modelrsquos


Figure 1 CUM economic impact analysis framework

structure incorporates inter-industry transactions and endogenous final demandfeedbacks The basic assumption of REMI is that the model is based ontheoretical structural restrictions rather than individual econometric estimatesbased on single time-series observations for each region It has much in commonwith the computable general equilibrium (CGE) models It does however differfrom the CGE models in that the REMI model does not require markets toclear continuously (Treyz 1993) REMI is used extensively to measure proposedlegislative and other programme and policy economic impacts across the privateand public sectors of the state by the Florida Joint Legislative ManagementCommittee Division of Economic and Demographic Research the FloridaDepartment of Labor and other state and local government agencies In addition itis the chosen tool to measure these impacts by a number of universities andprivate research groups that evaluate economic impacts across the state andnation Figure 2 provides a baseline for the calculation of economic impactestimates in REMI

REMI shares two underlying assumptions with mainstream economic theoryhouseholds maximize their utility and producers maximize their profits Itincludes hundreds of equations that describe cause-and-effect relationships inthe economy extending beyond an IO model

The REMI used for this analysis (version 80) was developed specifically bycounty for the state of Florida and included 23 sectors For the Tallahassee areathe county model comprised Leon Jefferson Gadsden and Wakulla countiesFor the Tampa area Hillsborough Pinellas Pasco and Manatee counties wereexamined REMIrsquos principal advantage is that it is a dynamic IO econometric

On site visitor surveydata collection

Smith Travel Researchhotelmotel occupancydate

Direct employmentcreated by visitors

Economic census lateststatistics

Direct wages paid tovisitor industry employees

CUM developmentpercentage of hotelmotel visitors party sizelength of stay per party spendingoccupancy data

Total visitorestimate

Total direct visitorspending estimate

Total visitor direct economic impact

Multipliers

Total visitor direct amp indirect economicimpact


Figure 2 REMI economic impact analysis framework

model and can be used to forecast both direct and indirect economic effects overmultiple-year time frames However the model is not county specific whichcould lead to unnecessarily inflated results Other IO models are used primarilyfor static or single-year analysis REMI uses three sources of employment wageand salary data the Bureau of Economic Analysis (BEA) employment wage andpersonal income series ES 202 establishment employment and wage and salarydata and county business patterns (CBPs) data published by the Bureau of theCensus The industries are based on the North American IndustrialClassification System (NAICS)

IMPLAN model

The impact analysis for planning or IMPLAN model in contrast to REMIis solely an IO model The theoretical framework is inputndashoutput developedby Wassily Leontief for which he received the Nobel Prize in 1973 The basicassumption of the IMPLAN model is that the fundamental information inIO analysis involves the flow of products from each industrial sector (producer)to each of the industrial sectors considered as consumers This information iscontained in an inter-industry transactions table The rows of the table representthe distribution of the producerrsquos output throughout the economy The columnsrepresent the composition of inputs required by an industry to produce itsoutput There are additional columns that depict lsquofinal demandrsquo or sales by

State and local governmentspending

Investment

Output

Consumption

Real disposable incomeExports

(1) Output

(2) Labour amp CapitalDemand

(3) Demographic (5) Market Shares

(4) Wages Prices amp Costs

Domesticmarketshare

Internationalmarket share

Employment

Labouroutputratio

Optimalcapitalstock

Population

Labourforce

Participationrate

Migration

Employment opportunity

Housing price

CompensationComposite

compensation rate Production costs

Composite pricesReal compensation

rate

Consumer pricedeflator


Figure 3 IMPLAN economic impact analysis frameworkSource IMPLAN Central NRCS Economists Workshop (MIG Inc 1997)

each sector to final markets for their production The additional rows are termedlsquovalue addedrsquo which comprise the other non-industrial inputs to productionsuch as labour IMPLAN was founded in 1993 as an extension of tworesearchersrsquo work at the University of Minnesota and involving collaborativework with the US Forest Service Land Use Planning Unit in Colorado It isnon-survey based and its structure illustrates that of IO models found in theregional science literature Figure 3 provides a baseline for the calculation ofthe economic impact estimates in IMPLAN

Key IO assumptions used in IMPLAN

(1) Constant returns to scale production function (that is linear)(2) Homogeneous sector output(3) No input substitution(4) No supply constraints(5) Other IMPLAN considerations

(a) Technology and trade relations are assumed(b) Need to account for price changes(c) Need to account for structural changes(d) Employment increase or decrease causes immediate in or out

migration (that is full employment)

Similar to REMI IMPLAN assumes a uniform national production technologyand uses the RPC approach to regionalize the technical coefficients IMPLAN2002 Florida county-level was used for the economic analysis for this researchThis newer version now has 509 sectors instead of 528 and includes theconversion from SIC to NAICS codes The primary sources of employment andearnings data are CBPs data and BEA data

Table 1 provides a summary of the three economic impact models

Use matrix

(Absorption matrix)

Make matrix

(By-product matrix)(Market share matrix)

Totalcommodity

output

Final

Commodities

Competitive imports matrix

Non-competitive imports matrix

Total industry outlay

Final payments

Industries

Employee compensationIndirect business taxProprietary incomeOther property type income

Totalindustryoutput

PCE low incomePCE medium incomePCE high income

SampL govrsquot purnon-edSampL govrsquot pured

Fed govrsquot purnon-milFed govrsquot purmil

Inventory purchasesCapital formationForeign exportsDomestic exports

SampL govrsquot salesFed govrsquot salesInventory sales

Total commoditysupply



Final demand totals


Table 1 Comparison of the three modelsa

Characteristics REMI IMPLAN CUM

I Type Conjoined inputndashoutput Regional inputndash Derived from labourand behaviour model output force economics

linear equationIndividual tourismarrivals

II General modelcharacteristicsBase year 1980 1993 1975 updated in 1990sReference model National A matrix National A matrixOpenclosed Open Both

III Sector schemeDisaggregated 493 509 Unlimited and

dependent on surveyvariable numbers

Aggregated 23 (county) or 70 sector User choice User choice(state) or 169 (state)

IV RegionalizationtechniqueProduct mix Keep at a disaggregated Keep at a dis- Keep at a disaggregated

level aggregated level levelConsumption BLS Regional Consumer Adjusted using Adjusted using

Expenditure Surveys RPCs multipliersTrade patterns Regional purchase Regional purchase Multipliers can be

coefficients coefficients input into the model(from other source)

V Impacts measuredOutput Yes Yes YesEmployment Yes Yes YesIncome Yes Yes Yes

VI Special features Economic Geography County Data Tourism andTransight Zip Code hospitality industry2020 Policy Insight Level Data specificBizDev

VII Computerrequirements IBM PC or mainframe IBM PC or IBM PC

mainframeVIII Costs

Purchase model Variable many options US$540 software Freeand pricing schemes State totalsavailable (for example packages US$500ndashUS$46000) for primary US$2650 statelicence (70 sector state (including counties)of Florida and Individual stateUS$69000 169 sector) US$350and US$6900 for Zip Code Levelsecondary licence for File US$425state of Florida model


Table 1 continued


Customizedsimulation Available Available Available on requestOther options Leasing models are Customized models

availableIX Data Secondary Secondary PrimaryX Time period Dynamic 50 years or Static one year Static

moreXI Website httpwwwremicom httpwww httpwww

implancom fishkindcom

Note aExcerpted from lsquoAnalyzing the economic impact of transportation projects using RIMS IIIMPLAN and REMIrsquo Dr Tim Lynch Director Center for Economic Forecasting and Analysis (2000)Prepared for Office of Research and Special Programs US Department of Transportation WashingtonDC Supported by a grant from the US Department of Transportation University Research InstituteProgramme

Overview of Florida tourism expenditures databases

During 2003ndash2004 researchers based in Florida collected survey data duringtwo special events the Southwest Airlines Gasparilla Pirate Fest (Gasparilla)and the University of Miami versus Florida State University Football GameWeekend (Miami vs FSU) Also data were collected for two quarterly researchprojects involving visitors to Florida destinations within specific countiesTampa (Hillsborough County) and Tallahassee (Leon County) Florida Datawere collected based on a series of personal interviews for each of the two eventsencompassing three days Additionally data were collected over the course ofthree months for each of the two quarterly databases The following discussionis a detailed explanation on methodologies for each of the two events and thetwo quarterly databases that were used in the economic impact analysiscomparisons

Gasparilla 2004

The Southwest Airlines Gasparilla Pirate Fest is an open access mega-event thatis held in Tampa Florida The annual event consists of a day parade thattraverses an eight-mile route along what may be the longest contiguous sidewalkin the USA On-site surveys were conducted based on a randomized samplingdesign Surveyors were stationed at specific points on both sides of the paraderoute Every third adult was approached for qualification as a non-resident Ifthe third adult was a local resident then the next adult was approached fornon-resident qualification purposes This process continued until non-residentparade attendees were identified In this study Gasparilla visitors were definedas those who were non-Hillsborough County residents Ultimately 300 Gasparillavisitors provided data suitable for this analysis


University of Miami versus Florida State University Football Weekend

During the weekend of 11 October 2003 the University of Miami versusFlorida State University Football Game attracted approximately 82000individuals to the Doak Campbell Stadium through ticket sales A significantnumber of tickets were purchased by local residents including students andwere therefore omitted from the analysis On-site surveys were conducted basedon a randomized sampling design Surveyors were stationed at specific datacollection points around the stadium Additionally surveys were conducted atrandomly selected lodging properties within the county Every third adult wasapproached for qualification as a non-resident If the third adult was a localresident then the next adult was approached for non-resident qualificationpurposes This process continued until non-resident attendees were identifiedIn this study visitors were defined as those who were non-Leon Countyresidents A total of 284 usable data were collected during the eventweekend

Tallahassee Florida Q1 2004

Visitors to Tallahassee (Leon County Florida) were interviewed personally aspart of a comprehensive destination marketing research project During randomdays sites and times visitors were screened randomly using random numbersto qualify them as non-residents Once qualified as non-residents of LeonCounty visitors were asked to respond to a survey related to their on-site (mostrecent) travel experience Information pertaining to economic expendituresparty size length of stay demographics activities pursued during this tripprimary destination for this visit and many other dimensions were representedon the survey instrument More than 500 (N = 515) usable surveys werecollected for the analysis

Tampa Florida Q1 2004

Visitors to Tampa (Hillsborough County Florida) were interviewed personallyas part of a comprehensive destination marketing research project The surveymethodology was identical to the Tallahassee Q1 study A total of 1538 surveyswere identified as suitable for the analysis

Economic impact methodology

This paper describes the impact of tourism on the economy of Florida countiesusing three economic impact models (CUM REMI and IMPLAN)Comparisons were conducted using the results from these three economic impactmodels and examined the increase in employment and economic outputgenerated by tourism activities specific to the countiesrsquo economies The neteconomic stimulus from tourism was estimated by summing tourismexpenditures based on survey data for four economic activities and events


Gasparilla Miami vs FSU Football Game the Tallahassee quarterly and theTampa quarterly visitor survey Direct expenditures were divided into thefollowing for each of the four databases lodging event admission feesrestaurants evening entertainment shopping ground transportation groceriesand all other These expenditures were then used as inputs for the three Floridaregional IO models which included cross-linkages among every sector of theFlorida economy As touristsvisitors expend dollars further demand for goodsand services across other sectors of the Florida economy are generated Directtourism spending creates a secondary lsquomultiplierrsquo cycle of spending that furtherincreases income jobs and total state economic activities referred to as stateoutput This analysis measures those direct and indirect economic increasesflowing from tourism dollars based on the four expenditure databases Itdoes not quantify the intangible benefits generated by the presence oftourism to the local economy for issues such as improved transportation healthcare historical environment or cultural amenities among others

Measured economic impacts include increases in (a) total output (b) incomeand (c) employment Short-term economic impacts are the net changes inregional output earnings and employment that are due to new dollars enteringa region from a given enterprise or economic event In this study the enterpriseis tourism and the region is specific Florida counties The effects of expendituresexternal to Florida (termed leakages) were not included in the impactestimates

As part of our modelling strategy actual tourism expenditures were used tocalculate the economic impact (Table 2) The various tourism directexpenditures (for example lodging event admission fees restaurants shoppingground transportation groceries and all other) were disaggregated by specificeconomic sectors to calculate the economic impacts (Figure 4)

Table 2 Amount of tourism expenditure by economic databaseevent for GasparillaMiami versus FSU Football Weekend Tallahassee Q1 and Tampa Q1

Spending category Gasparilla Miami Tallahassee Tampaby value vs FSU Q1 Q1(US$ million)

Attraction fees 049 000 179 0a

Evening entertainment 199 103 1753 2658Event admission fees 336 201 292 19638Groceries 158 062 1007 3154Ground transportation 088 076 949 5430Lodging 291 261 5247 14500Other items 181 023 782 2018Restaurants 637 179 5897 16247Shopping 223 101 5816 9580Sports activities 021 000 523 2200Total expenditure 2183 1007 22445 75425

Note aEvents (US$228 was included with admission fees)


Figure 4 Percentage of tourism expenditures by economic databaseevent forGasparilla the Miami versus FSU Home Football Game Weekend TallahasseeQ1 and Tampa Q1


Model assumptions

This paper provides estimates of the direct indirect and induced effects oftourism expenditures on the economies of two Florida counties The modelassumptions are

(1) The base model assumes a constant rate of growth for the economy(2) The expenditure approach model uses actual tourism expenditures (by

category lodging shopping etc) multiplied by total estimated number ofvisitors

(3) The total number of visitors estimated by the CUM is valid and is usedin the REMI and IMPLAN models

(4) The total tourism expenditures by database are Gasparilla ndash US$2183million FSUndashMiami Game ndash US$1007 million Tallahassee Q1 ndashUS$22445 million and Tampa Q1 ndash US$75425 million Results areexpressed in terms of impact on total output income and employment

Model limitations

(1) A limitation of the base model assuming a constant rate of growth for theeconomy is that there are multipliers associated with each sector forexample if one sector grows by X amount then the whole economy growsby X times the sector multiplier Hence theoretically growth in any sectorcan result in an arbitrary high level of growth in the corresponding wholeeconomy which may not be the case REMI has three options forsimulating the growth rate of an economy historical observed (the defaultchoice) anticipatory fed and Keynesian approaches

(2) The expenditure approach model uses actual tourism expenditures (bycategory lodging shopping etc) multiplied by total estimated number ofvisitors Spending estimates are based on a representative sample of thetourist population which encompass a wide array of tourist type locationand seasonal variations

(3) The total number of visitors estimated by the CUM is valid and is usedin REMI and IMPLAN models

(4) The total tourism expenditures by database are Gasparilla ndash US$2183million MiamindashFSU Game ndash US$1007 million Tallahassee Q1 ndashUS$22445 million and Tampa Q1 ndash US$75425 million Results areexpressed in terms of impact on total output income and employmentEconomic impact estimates are based on solid numbers and types ofvisitors which is not the authors contend a limitation of this studyHowever the economic impact results are generalized to these specificeventsdatabases

Strengths and weaknesses of the three models

One major strength of the CUM is that it is industry specific and does notrequire an expensive software program It provides detailed estimates of county-


level sectors based on primary data The model can be distributed freely Themajor strengths of REMI and IMPLAN are that they can provide detailedestimates of sectors at the county level REMI is capable of providing a finerresolution than at the county level (for example city) however both REMI (bycounty) and REMI customized (for example a metropolitan area) are far costlieroptions than county-level IMPLAN REMI uses several economic impactmethodologies (IO econometric equations economic-base and some aspects ofCGE) over multiple years (to 2050) and IMPLAN employs solely an IOmodelling methodology with a one-year (static) forecast horizon Hencedepending on the modellerrsquos needs REMI would be advantageous for short- andlong-term analysis The REMI model is able to simulate how long-run impactsmay differ from short-run impacts due to changes in competition inoutmigration rates labourcapital substitution and inflation among others Inaddition the REMI model estimates the future economic profile of a regionbased on national forecasts of industry growth changing technology and its ownestimates of the shifting competitive position of each industry in a given regioncompared to that industry elsewhere in the country (Weisbrod 1990) IMPLANdoes not have this capability

IMPLAN allows internal customization that is by developing multipliertables changing components of the systems such as production functions andaltering trade flows generating Type I II or any true social account matrix(SAM) multiplier internalizing household government andor investmentactivities and creating custom impact analysis by entering final demand changesamong others (IMPLAN 1999) REMI provides a dynamic perspective (fore-casting capabilities up to year 2050) and year-to-year effects for over 6000variables The REMI model does not allow users to change the IO or developnew multipliers It can be run as a simple IO model by turning off economicmigration endogenous consumption and certain price responses The usercannot alter RPCs directly in the regional model (REMI 2005) It is beneficialto be able to alter RPCs if the modellers are aware of information specific toa good or service that is not captured by the current model

Although the CUM can produce estimates similar to the other two modelson total output and number of jobs created the model has its limitations Firstit can estimate only the direct and indirect impacts (that is not inducedimpacts) It does not present results as separate categories (direct and indirect)but rather as total impacts The model does not provide detailed informationlike total value added employee compensation proprietorrsquos income etc Secondthe CUMrsquos only resource is Economic Census reports from the US CensusBureau Since the Economic Census is updated every five years the key statisticsused in the model remain the same for five years and are adjusted for inflationonly Some general weaknesses of IMPLAN are that it is inappropriate to usewith large impacts (Kraybill 1993) According to Miller and Blair (1985) theIO model (including IMPLAN) assumes a linear production function whichtranslates to constant returns to scale and constant production function for eachfirm in an industry It also assumes there are no constraints to the supply ofany commodity and that full employment is the norm IMPLAN assumesnational average production coefficients and margins and uses a set ofeconometric equations to predict interregional trade flows If one doesnot accept these assumptions users as mentioned earlier have the ability


to input their own data to improve the accuracy of the impact estimates (thatis internal customization or hybrid approach)

There is another method called tourism satellite account (TSA) which canbe used to estimate the economic impact of tourism activities like the onediscussed in this paper lsquoSatellite accountrsquo is a concept developed by the UNto measure the size of economic sectors that are not defined as industries inthe system of national accounts (SNA) TSA is the outcome of the collaborativework of multiple national governments as well as international institutions likethe World Tourism Organization (WTO) the Organization for EconomicCooperation and Development (OECD) and the United Nations (UN) to createa comprehensive and consistent measure of the economic impact of tourism As earlyas 1983 the WTO called for the creation of lsquoa uniform and comprehensivemeans of measurement [of tourism] and comparison with other sectors of theeconomyrsquo (Smith and Wilton 1997) In 1994 the WTO started designing aTSA with the objective of presenting a comprehensive and integratedframework for estimating production consumption capital investmentemployment and other variables related to tourism activity There are currently70 countries or territories around the world implementing a TSA (Libreros etal 2006)

The term lsquosatellitersquo refers to the fact that a TSA is based on the IOframework of a stateregional economy It is a subset of general IO accountingSince tourism is a conglomeration of industries it is not possible to identifya set of industries add up their outputemployment and use the result to gaugethe impact of tourism in a country or region TSAs offer a solution to thisproblem by weighing the outputemployment of all tourism-related industriesby the ratio of tourism expenditures to total expenditures for each industry(Smeral 2006)

TSAs start with a solid definition of tourism and delineation of lsquocorersquo tourismindustry As accepted by the UN and WTO TSAs define tourism as lsquoactivitiesof persons travelling to and staying in places outside their usual environmentfor not more than one consecutive year for leisure business and other purposesrsquo(United Nations 1994) TSAsrsquo core tourism industries consist of five broadindustries lodging restaurants entertainment transportation and retail TSAsfirst measure tourismrsquos impact on these industries They also extend beyond coretourism industries and measure tourismrsquos indirect effect on other industriessuch as printingpublishing concrete utilities financial services furnishing andequipment suppliers food security administration and so forth Thus TSAscapture the impact of tourism on industries that benefit directly or indirectlyfrom travel and tourism expenditures

The TSA model was not used in this study for three reasons First unlikeREMI and IMPLAN a TSA model measures only direct and indirect impactsof tourism expenditures not induced impacts Second since a TSA model isderived from an IO model such as REMI and IMPLAN direct and indirectimpacts from a TSA model likely will not be different Third and mostimportant currently we do not have a TSA model developed for the state ofFlorida While the US BEA and several other states currently use a TSA modelto estimate the economic impact of tourism expenditures Florida uses only atourismrecreational sales category as a proxy to estimate direct visitorexpenditures A recent study strongly recommended that the state develop a


TSA model in order to capture the economic impact of visitor expenditures fully(Aydin 2007)

Economic analysis results of the three models

The following results present the economic impact of tourism expenditures forthe four specific databases regarding their respective counties Table 3summarizes the total economic impact of tourism on the economy of the Floridacounties The table depicts the economic impacts of tourism on employmenttotal output and income from the tourism expenditures based on the fourspecific databases Output is the amount of production including allintermediate goods purchased as well as value added Increases in personal (ordisposable) income translate into more economic activities and local and statetax revenues In addition to total output and income tourism generates asignificant amount of employment across the state REMI assumes that changesin employment affect wages These changes in wages affect in-migration (thatis population) and labour supply which in turn affects employment levels Theemployment results are expressed in terms of jobs Total output and realdisposable income results are expressed in terms of 2005 US$

This tourism-generated rise in state output created considerable direct andindirect increases in employment across the state Table 3 indicates thatadditional jobs are created from these spending increases In turn thisemployment increase also generates higher wage and salary earnings for FloridiansTable 3 illustrates the direct and indirect personal (or disposable) incomeincreases Structural differences were revealed through examination of thedocumentation for both the IMPLAN and REMI models The authors wereunable to obtain any documentation associated with the CUM developed byHank Fishkind (personal communication with Fishkind and AssociatesSeptember 2005)

In REMI and IMPLAN total output measures the sum of the direct indirectand induced effects of changes in the economies of Tallahassee and TampaFlorida It refers to the amount of productionservice including all intermediategoods purchased as well as value added (compensation and profit) Regardingoutput measures in the CUM only direct and indirect impacts are providedWith respect to employment the CUM uses county Economic Census reportsto estimate the number of paid employees created The county REMI gives BEAemployment estimates as a count of the number of jobs It incorporates theCBPs provided in an annual series that includes employment during this studyperiod (not including proprietors and partners of unincorporated businesses)The series excludes data on self-employed individuals employees of privatehouseholds railroad employees agricultural production employees and mostgovernment employees However REMI is able to estimate self-employment byincorporating data from the BLS Current Employment Survey (for wage andsalary jobs and average weekly hours) the Current Population Survey (for self-employed and unpaid family worker jobs agricultural employmentemployment and private household employment except logging) and ES-202employment and wages data collected from the unemployment insuranceprogramme (for industries unpublished in the CES)4 Similar to REMI IMPLAN


Table 3 Comparison of IMPLAN REMI and CUM models in 2005 US$

Miami vs FSU Football Game Leon Gadsden Jefferson and Wakulla CountiesOutput (US$) Employment Income (US$)

IMPLAN results 14242929 312 9497102REMI results 16377711 271 13071023CUM results 16131938 315 3122453

Tallahassee Q1 Leon Gadsden Jefferson and Wakulla CountiesOutput (US$) Employment Income (US$)


Gasparilla Hillsborough Pinellas Manatee and Pasco CountiesOutput (US$) Employment Income (US$)


Tampa Q1 Hillsborough Pinellas Manatee and Pasco CountiesOutput (US$) Employment Income (US$)


bases its employment estimates on unemployment insurance (ES-202) data orlsquocovered employmentrsquo and since the early 1990s has been providing estimatesof self-employed railroad or any other firms that do not pay unemploymentinsurance using a combination of ES-202 and BEA Regional EconomicInformation System (REIS) data5 Self-employment data are important sincethey include those employees that typically are not surveyed but are stillintegral to tourism industries such as taxis micro-accommodations etc Wagesor income for the CUM are based on the county Economic Census reports fromthe US Census Bureau Both REMI and IMPLAN are based on CBPs the USDepartment of Laborrsquos Unemployment Insurance CEW ndash Covered Employmentand Wages Program ndash and BEA REIS databases It should be emphasized thatthe use of primarily national industry structures to represent local productionespecially in more rural areas can be problematic

Discussion of results

The economic impact results pertain specifically to the four economic activityand event databases An assumption is made (and limitation) in this study thatthe economic impact estimates are applicable for the entire year The results


were variable between the models particularly the lsquoincomersquo result comparisonsThe difference in income lies in the fact that both IMPLAN and REMI includemultiple counties (three for each study area) within their model The CUMincludes only county-specific information This is one of the main reasons thatthe CUM appears to offer very conservative outputs pertaining to income

The CUM estimated the lsquopayrollrsquo (but uses only county-specific information)REMI estimated the lsquodisposable personal incomersquo and IMPLAN estimated thelsquovalue addedrsquo The major differences between the income definitions are

bull GVA or gross value added ndash composed of the value of final demand createdby consumer spending investment net exports and government spendingexcluding intermediate inputs

bull Personal income ndash consists of total increases in payroll costs paid by localindustries plus income from self-employment other property income andtransfer payments

bull Disposable income ndash a measure of after-tax buying power of the community(income less taxes) It reflects increased government spending and consumeractivity

Both REMI and IMPLAN incorporate three additional counties in each studyarea which could lead to over-inflation of income In REMI the disposableincome variable (personal income minus taxes) was used to represent the incomeimpact The REMI income determinants included total labour and proprietorrsquosincome personal contributions to social insurance the net residence adjust-ment dividends interest and rent and transfer payments In IMPLAN howeverthe value-added impact was determined to resemble most closely REMIrsquosdefinition of personal income Value added consists of employee compensationproprietor income other property income and indirect business taxes Due tothe different income measurements REMIrsquos income estimates are the highestwhile the CUMrsquos are the most conservative again due to the fact that the CUMis county specific and the other two models use multiple counties (that isregions) to generate output In comparing both REMI and IMPLAN theIMPLAN output results were consistently lower in three databases The Tampaquarterly database however demonstrated higher output estimates withIMPLAN This could possibly be due to the IMPLAN model whichincorporates four counties (representing the Tampa region) and correspondinglevel of disaggregation (509 sectors) The interregional effect among countiesis not taken into account with IMPLAN6 however it is accounted for inREMI7

The CUM ranged from the highest output results (Tallahassee Q1) to thelowest output results (Tampa Q1) This could be a result of the fact that theCUM model is constructed specifically for the tourism lodging and hospitalityindustries Interestingly in comparing the two models (REMI and IMPLAN)regarding employment REMI was lower in all four databases This could bedue to the ratio between output and employment impacts being affected byREMIrsquos inclusion of pricewage effects County level IMPLAN uses a nationalaverage for output per worker (and adjusts to the regional level using the BEAREIS data) and REMI uses regional productivity values Hence given a uniformshock in each of the models it is possible that REMI has a higher labourproductivity rate and demand for labour to produce the same level of output


is lower hence employment is lower Thus although REMIrsquos output resultsare greater in terms of output in two databases the employment results areconsistently lower Income level results are significantly greater with REMI inthree of the four databases The CUM model consistently tracks significantlymore conservatively in terms of personal income Again this may be due tothe fact that the CUM model is specific to the tourism lodging and hospitalityindustry It uses only data from visitor spending whereas the other two modelsdo not Furthermore it uses only county-specific information The other twomodels use four counties for each of the two study samples

A possible explanation for the total output employment and incomedifferences (since the data sources are comparable) between REMI and IMPLANcould be that the REMI county-specific model is working from a highlyaggregated regional IO table (23 sectors) and the corresponding RPC valuesyield different results than the IMPLAN model which is working from a highlyspecified county IO table (509 sectors) A fundamental difference as outlinedby Perlich (2005) between IMPLAN and REMI is that IMPLAN accounts foreconomic variables only (production spending employment) whereas REMIaccounts for economic labour force population (migration births deaths) andfiscal impacts In addition market dynamics and relative regional competitive-ness across time are also included

Prior to selecting one economic impact model over another decision makersshould consider the following primary factors as outlined previously in Table3 (a) cost of the economic impact software (b) time period of the analysismulti-year or static and (c) level of detail with respect to multipliers andindirect and induced effects REMI is highly complex built on an IO econo-metric framework however it is also the costliest software IMPLAN is widelyaccepted by many organizations (public and private) in terms of analysis andeconomic impact results over a one-year time horizon and is not costprohibitive (less than US$3000 for an individual state with associatedcounties) The CUM is suitable for specific hospitality and tourism-relatedanalyses and is free of charge The authors examine the overall structure of theseeconomic impact models but do not strive to recommend one economic impactmodel over another given their multifaceted use by economic modellersHowever this paper does examine the behaviour of the economic impact modelsregarding various data sets and describes the underlying characteristics of themodels

Endnotes

1 httpwwwcensusgovepcdwwwnaicshtml2 httpwwwsmithtravelresearchcomsmithtravelresearch3 RIMS II multiplier of 15 used for the CUM in this study based on previous research for these

regions (personal communication with Frederick Bell 2006)4 REMI Policy Insight Documentation on County Business Patterns and Current Population

Survey Data on self-employment5 IMPLAN personal communication with Scott Lindall 20076 In order to construct a working multi-regional IO model however a set of interregional trade

flows (or coefficients) has to be estimated using the Commodity Flow Survey (Census Bureauand Transportation Statistics) httpwwwimplancomlibrarydocuments2006pdfs33_interregional_trade_flow_robinsonpdf

7 REMI personal communication with Adam Cooper 2007


References

Archer BH (1984) lsquoEconomic impact misleading multiplierrsquo Annals of Tourism Research Vol 11No 3 pp 517ndash518

Aydin N (2007) lsquoFlorida needs a better method to estimate tourismrsquos economic impactrsquo FloridaTaxWatch Report Tallahassee FL pp 1ndash59

Baker K and Aydin N (2005) lsquoSpecial report by the Florida TaxWatch Center for Tourismrsquo inThe Impact of Tourism on Floridarsquos Economy Telling a More Complete Story Florida TaxWatch ReportTallahassee FL

Bell Frederick W (2006) personal communication JanuaryBonn MA and Bell FW (1998) lsquoThe economic value of artificial reefs in northwest Floridarsquo

Technical Report Florida Department of Environmental Protection Tallahassee FLBonn MA and Bell FW (2003) lsquoFlorida natural springs and their economic valuersquo Florida

Department of Environmental Protection Tallahassee FLClawson M and Knetsch J (1971) Economics of Outdoor Recreation Resources for the Future The John

Hopkins Press Baltimore MDConnecticut Center for Economic Analysis (CCEA) (2003) lsquoThe 2001 economic impact of Connecti-

cutrsquos travel and tourism industryrsquo Report Connecticut Center for Economic Analysis Universityof Connecticut Storrs CT

Crihfield JB and Campbell HS Jr (1992) lsquoEvaluating alternative regional planning modelsrsquoGrowth and Change Vol 23 pp 521ndash530

Deller SC (1992) lsquoA consistent cross-analysis of two regional economic modeling systems acomparison of REMI and IMPLANrsquo Working Paper Department of Agricultural and ResourceEconomics University of Maine Orono ME

Economic Census US Census Bureau (2002) lsquo2002 Economic Census Geographic Area SeriesFloridarsquo last revised 3 January 2006 httpwwwcensusgoveconcensus02guide02EC_FLHTM

Fishkind and Associates Inc (1989) lsquoCentral Florida tourism industry descriptionrsquo TechnicalReport prepared for the Greater OrlandoOrange County Convention and Visitors Bureau andthe Kissimmee-St Cloud Convention and Visitor Bureau

Fishkind H and Associates Inc (2005) personal communication SeptemberFrechtling DC (1994a) lsquoAssessing the economic impacts of travel and tourism ndash introduction to

travel economic impact estimationrsquo in Brent Ritchie JR and Goeldner CR eds TravelTourism and Hospitality Research Second Edition John Wiley and Sons New York pp 359ndash366

Frechtling DC (1994b) lsquoAssessing the economic impacts of travel and tourism ndash measuringeconomic benefitsrsquo in Brent Ritchie JR and Goeldner CR eds Travel Tourism and HospitalityResearch Second Edition John Wiley and Sons New York pp 367ndash392

Frechtling DC (1994c) lsquoAssessing the economic impacts of travel and tourism ndash measuringeconomic costsrsquo in Brent Ritchie JR and Goeldner CR eds Travel Tourism and HospitalityResearch Second Edition John Wiley and Sons New York pp 393ndash402

IMPLAN (1997) Central NRCS Economists Workshop Minnesota IMPLAN Group Inc StillwaterMN

IMPLAN (1999) IMPLAN Professional Version 20 Minnesota IMPLAN Group Inc StillwaterMN

IMPLAN (2007) personal communication with Scott Lindall 7 MayKraybill DS (1993) lsquoComputable general equilibrium analysis at the regional levelrsquo in Microcom-

puter-Based InputndashOutput Modeling Applications to Economic Development Westview Press BoulderCO pp 125ndash148

Kuhbach P and Herauf BA (2005) lsquoUS travel and tourism satellite accounts for 2001ndash2004rsquoBureau of Economic Analysis Washington DC

Libreros M Massieu A and Meis S (2006) lsquoProgress in tourism satellite account implementationand developmentrsquo Journal of Travel Research Vol 45 August pp 83ndash91

Lynch T (2000) lsquoAnalyzing the economic impact of transportation projects using RIMS II IMPLANand REMIrsquo prepared for Office of Research and Special Programs US Department of Transpor-tation Washington DC

Miller RE and Blair PD (1985) InputndashOutput Analysis Foundations and Extensions Prentice-HallInc Englewood Cliff NY

Perlich P (2005) Regional Economic Analysis and Impact Models Bureau of Economic and BusinessResearch David S Eccles School of Business University of Utah Salt Lake City UT


Regional Economic Models Inc (2005) lsquoModel documentationrsquo Frederick Treyz and George TreyzRegional Economic Models Inc Amherst MA (httpwwwremicom)

REMI (Regional Economic Models Inc) (2007) personal communication with Adam Cooper 7 MayRickman DS and Schwer RK (1993) lsquoA systematic comparison of the REMI and IMPLAN

models the case of Southern Nevadarsquo Review of Regional Studies Vol 23 pp 143ndash161Rickman DS and Schwer RK (1995a) lsquoMultiplier comparisons of IMPLAN and REMI across

versions illuminating black boxesrsquo Environment and Planning A Vol 26 pp 143ndash151Rickman DS and Schwer RK (1995b) lsquoA comparison of the multipliers of IMPLAN REMI

and RIMS II benchmarking ready-made models for comparisonrsquo The Annals of Regional ScienceVol 29 pp 363ndash374

Ryan C (2003) lsquoThe economic impacts of tourismrsquo in Recreational Tourism Demand and ImpactsAspects of Tourism Second Edition Multilingual MattersChannel View Publications Clevedonpp 148ndash196

Smeral E (2006) lsquoTourism satellite accounts a critical assessmentrsquo Journal of Travel Research Vol45 August pp 92ndash98

Smith SLJ and Wilton D (1997) lsquoTSAs and the WTTCWEFA methodology different satellitesor different planetsrsquo Tourism Economics Vol 3 No 3 p 250

Stynes DJ (1999) Guidelines for Measuring Visitor Spending Michigan Tourism Economic ImpactModel httpweb4canrmsueduMGM2econpdfecimpvol3pdf

Travel Industry Association of America (2005) personal communication with Dr Tien Tian Decem-ber

Treyz GI (1993) Regional Economic Modeling A Systematic Approach to Economic Forecasting and PolicyAnalysis Kluwer Academic Publishers Norwell MA

United Nations (1994) lsquoRecommendations on tourism statisticsrsquo Department for Economic andSocial Information and Policy Analysis and World Tourism Organization United Nations NewYork p 9

Visit Florida Inc (2005 2006) Department of Marketing and Statistics Tallahassee FLWeisbrod G (1990) lsquoREMI and I-O models comparedrsquo Cambridge Systematics wwwedrgroupcom

pagespdfREMI-IOpdf http


value added grew 45 to US$285 billion which represented 26 of the GDPfor the period 2001ndash2003 (Kuhbach and Herauf 2005) Moreover tourismprovides tremendous benefits for federal state and local governments in theform of taxes (for example excise sales income and property taxes) In 2004the industry generated an estimated US$100 billion in taxes based on US$5464billion of direct sales from tourism (Travel Industry Association of America2005 ndash personal communication with Dr Tien Tian)

The economic impacts of tourism are frequently analysed using economicimpact modelling software The objective of this paper is to compare threeeconomic impact models (the capacity utilization model (CUM) RegionalEconomic Models Inc (REMI) and the impact analysis for planning (IMPLAN)model) using four visitor survey expenditure databases The study also examinesprevious tourism economic impact studies (from 1990 to current) to determinemethodologies pertaining to CUM REMI and IMPLAN

In doing so the State of Florida was selected to provide data sets for analysisof the economic impact models Florida was selected because tourism is thenumber one industry due primarily to its natural resources a favourableclimate an immense shoreline theme parks professional and major universitysports major airports and cruise industry ports cultural events and retirementcommunities The number of Florida tourists reached a record 768 million in2004 and is projected to grow to 89 million by 2010 (Visit Florida 2006)Currently 13 million Florida jobs are related directly or indirectly to tourismand are projected to grow to between 15 and 18 million by 2010 The 2005Florida Visitor Study reported that the state collected US$37 billion intourismrecreation sales taxes in 2005 that is US$62 billion was infused intothe statersquos economy during the year through tourist expenditures The studyalso noted that tourism expenditures supported 948700 jobs in 2005 (VisitFlorida 2005) Tax revenues accounted for about 20 of the total tax revenues(in sales and use taxes) collected (Baker and Aydin 2005)

Literature review of economic impact models

There have been various studies relating to the economic impact estimation oftourism spanning the past 20 years however few articles exist that comparethe performance of those models Following is a literature review of several ofthe studies that have examined economic impact modelling and performancewith respect to the tourism industry Stynes (1999) conducted numerous studiesthat focused on the economic impacts of tourism He outlined severalapproaches that researchers might employ including four typical approaches(a) subjective estimates that rely on expert opinion (b) secondary data inaggregate form using existing estimates tailored to the situation (c) secondarydata in disaggregate form allowing a finer resolution to fit the situation and(d) primary data andor formal models usually involving visitor surveys andregional economic models It is the latter issue of economic impact modellingthat this paper will address Archer (1984) described the sources available toacquire data and the necessary processes to adapt these data for use in inputndashoutput (IO) modelling He noted that a local or regional consumer expendituresurvey was rarely available and was both expensive and time-consuming However













The REMI model
















Multipliers





IMPLAN model



Investment

Output

Consumption


(1) Output




Domesticmarketshare


Employment

Labouroutputratio

Optimalcapitalstock

Population

Labourforce

Participationrate

Migration


Housing price




rate











Use matrix

(Absorption matrix)

Make matrix


Totalcommodity

output

Final

Commodities




Final payments

Industries


Totalindustryoutput









Final demand totals

















mainframeVIII Costs



Table 1 continued









Gasparilla 2004























Model assumptions






Model limitations
















































Endnotes







References





















































The REMI model
















Multipliers





IMPLAN model



Investment

Output

Consumption


(1) Output




Domesticmarketshare


Employment

Labouroutputratio

Optimalcapitalstock

Population

Labourforce

Participationrate

Migration


Housing price




rate











Use matrix

(Absorption matrix)

Make matrix


Totalcommodity

output

Final

Commodities




Final payments

Industries


Totalindustryoutput









Final demand totals

















mainframeVIII Costs



Table 1 continued









Gasparilla 2004























Model assumptions






Model limitations
















































Endnotes







References























































Multipliers





IMPLAN model



Investment

Output

Consumption


(1) Output




Domesticmarketshare


Employment

Labouroutputratio

Optimalcapitalstock

Population

Labourforce

Participationrate

Migration


Housing price




rate











Use matrix

(Absorption matrix)

Make matrix


Totalcommodity

output

Final

Commodities




Final payments

Industries


Totalindustryoutput









Final demand totals

















mainframeVIII Costs



Table 1 continued









Gasparilla 2004























Model assumptions






Model limitations
















































Endnotes







References












































IMPLAN model



Investment

Output

Consumption


(1) Output




Domesticmarketshare


Employment

Labouroutputratio

Optimalcapitalstock

Population

Labourforce

Participationrate

Migration


Housing price




rate











Use matrix

(Absorption matrix)

Make matrix


Totalcommodity

output

Final

Commodities




Final payments

Industries


Totalindustryoutput









Final demand totals

















mainframeVIII Costs



Table 1 continued









Gasparilla 2004























Model assumptions






Model limitations
















































Endnotes







References


















































Use matrix

(Absorption matrix)

Make matrix


Totalcommodity

output

Final

Commodities




Final payments

Industries


Totalindustryoutput









Final demand totals

















mainframeVIII Costs



Table 1 continued









Gasparilla 2004























Model assumptions






Model limitations
















































Endnotes







References

























































mainframeVIII Costs



Table 1 continued









Gasparilla 2004























Model assumptions






Model limitations
















































Endnotes







References










































Table 1 continued









Gasparilla 2004























Model assumptions






Model limitations
















































Endnotes







References






























































Model assumptions






Model limitations
















































Endnotes







References


















































































Endnotes







References










































References









































a comparison of three economic impact models

Documents

economic impacts of

tourism economics770value

tourism educators

threeeconomic impact

impact analysis

economic impactmodels

payroll income

respective models