Economic Impacts of Closing National Forests for Commercial Timber Production in Florida and Liberty County

Transcription

1 Economc Impacts of Closng Natonal Forests for Commercal Tmber Producton n Florda and Lberty County Abstract: The paper assesses the mpacts of a proposed polcy, whch suggests a ban on commercal tmber harvest n the U.. natonal forests. pecfcally, ths study examnes the effect of ths polcy on a small forest dependent county (Lberty County) n Florda and Florda tate by applyng a computable general equlbrum (CGE) model. The results ndcate that the proposed polcy would decrease overall economc output by $5 mllon n Lberty County. The decrease n economc output at the state level n response to ths polcy s only $ mllon. Results suggest that the welfare ndex n response to the proposed polcy wll drop by 2.9% n Lberty County whle the change at the state level s neglgble. At the county level, where lmted alternate opportuntes for labor and captal moblty, the negatve effect of the proposed polcy s shown to have a multplyng effect. Key words: Computable General Equlbrum Model, commercal tmber harvest, regonal economc mpacts, U.. natonal forest. Jan Zhang *, Janak R.R. Alavalapat *, Ram K. hrestha, and Alan W. Hodges 2 chool of Forest Resources and Conservaton, Insttute of Food and Agrcultural cences, Unversty of Florda, PO Box 040, Ganesvlle, FL 326, UA. 2 Department of Food and Resource Economcs, Insttute of Food and Agrcultural cences, Unversty of Florda, PO Box 0240, Ganesvlle, FL 326, UA.

2 2 Introducton Natonal forests n the U.. serve many socal, economc, and envronmental needs of Amercans and people around the world. A proper management of these forests has a profound mpact on local economes and the envronment (Danels et al. 99, UDA Forest ervce 2000). However, changes n publc preferences towards the use of these forests contnue to generate new forest management ssues, whch often translate nto new polces or nduce changes n exstng polces. nce the Organc Admnstraton Act of June 4, 897, wheren the creaton of the natonal forest system to mprove and protect publc forestlands was authorzed, numerous laws, Clean Water Act and Endangered peces Act for exa mple, have been enforced n the U.. (UDA Forest ervce 2000). These federal polces have been nfluencng the structure and functon of the UDA Forest ervce and management of natonal forests ether drectly or ndrectly. In recent years, there has been an ncreasng attenton towards the envronmental conservaton, outdoor recreaton use, and non-tmber values of natonal forests n the U.. (Chamberlan et al. 2002, Cordel et al. 999, Looms and Walsh 997, Wear and Gres 200). These motves have caused more pressure on changes n polces relatng to the management of our natonal forests. One such polcy proposal s HR 494: Natonal Forest Protecton and Restoraton Act 200. In essence, the bll purports to: ave taxpayers money, reduce the defct, cut corporate welfare, protect communtes from wldfres, and restore Amerca s natural hertage by elmnatng the fscally wasteful and ecologcally destructve commercal loggng program on Federal publc lands, restorng natve bodversty n our Federal publc forests, and facltatng the

3 3 economc recovery and dversfcaton of communtes affected by the Federal loggng program (U.. Congress 200, HR 494). The proposal manly reflects the publc demand for alternatve use of publc land, perceved net economc gan n such alternatve uses, and apparent need for protecton of ecosystems and bologcal dversty. Ths bll s causng ntense dscussons among forest dependent communtes, forestry professonals, and polcy makers across the naton. Although the bll needs the majorty support n the House and the enate to become law, t would be useful to gan nsghts about the economc mpacts of ths bll, at least n selected areas. Apparently, the proposal may have ecologcal economc benefts but t could also mpose certan opportunty costs, at least n the short-run, n the form of forgone tmber revenues. More mportantly, the opportunty costs may not be unform across regons. The role of tmber recepts and ncome from forest sector n some regons may be more crtcal than n other regons. As such, the economc mpact can be much more ntense n forest dependent communtes thereby mpactng ther stablty (Clary 986, Danels et al. 99). In the context of Florda, t s expected that economc mpacts of the HR 494 n Lberty County may be more serous than those n overall Florda, as forestry s a key component n the county s economy. In ths study we examne economc mpacts of the HR 494: Natonal Forest Protecton and Restoraton Act 200 on both Lberty County and the state of Florda. pecfcally we evaluate the effects of elmnatng commercal loggng actvty on natonal forests n Florda on ncome, output, and welfare. A computable general equlbrum (CGE) model s appled to acheve ths task. The rest of the paper s organzed as follows. In the followng secton, techncal features of the CGE model and detals of data are dscussed. The detals of tmber harvest n Apalachcola Natonal Forest and other natonal forests n Florda are also dscussed to defne the

4 4 polcy shocks. Model results are then presented and dscussed n ecton three. The fnal secton provdes a bref summary, conclusons, lmtatons of the study, and suggestons for further research. Model specfcaton The three Natonal Forests, Ocala, Apalachcola, and Oceola, n Florda occupy approxmately.25 mllon acres of land. The Ocala Natonal Forest offers unque ecologcal stes, trals, and natural sprngs along wth tmber harvestng areas. The Apalachcola Natonal Forest conssts of flat to gently rollng terran and most lowlands where cypress, longleaf pne/wregrass, and savannas provde habtat for an unusual combnaton of vertebrates and wldflowers. In the Osceola Natonal Forest, vstors wll hke, fsh and camp on a regular bass. Consstent wth management gudelnes stpulated n the Natonal Forest Management Act 976, the U.. Forest ervce manages these areas for multple uses, provdng many economc and envronmental benefts to local communtes. In all these forests tmber s harvested as a part of the overall management strategy to support local communtes va a contnuous flow of forest products. Fgure presents the annual tmber recepts of the Apalachcola and all Natonal Forests n Florda from 986 to 997 (UDA Forest ervce 998). The tmber recepts trend ndcates that over tme there has been a sgnfcant declne n tmber recepts n both Apalachcola and all Natonal Forests n Florda.

5 Florda Apalachcola Fgure. Annual Tmber Recepts from Apalachcola Natonal Forest and Natonal Forests of Florda from 986 to 997 (Values are n $000s) Table. Average Annual Tmber Recepts ( ) from Florda Natonal Forests (U $000s) Natonal Forest Mean td Dev Mn Max Apalachcola (Lberty County), , Ocala 2, , , Oceola, ,42.00 Florda Total 4,44.58,597.63, , The average annual tmber recept from Apalachcola Natonal Forest s $.22 mllon, 27% of the total recept from natonal forests n Florda (Table ). If HR 494 becomes a law, t s expected that there wll be a drect reducton n the economc actvty by $.22 and $4.44 mllon, respectvely, n Lberty County and the state of Florda. Although the forest sector may

6 6 be a small porton of the overall economy, t may have lnkages wth the rest of the economy. In order to capture these ntersectoral lnkages, a CGE analyss may be an approprate approach (Alavalapat et al.998). Many researchers have appled computable general equlbrum (CGE) models to analyze regonal forestry ssues. Danels et al. (99) have appled ths approach to assess the dstrbutve mpacts of Forest ervce attempts to mantan stablty n forest dependent communtes. Alavalapat et al. (997) have appled a CGE model to assess economc mpacts of stumpage prce ncrease n Brtsh Columba. Pohjola (999) has appled ths approach to assess economy-wde effects of reducng CO2 emssons. Patrqun et al. (2003) have recently appled ths model to estmate the mpacts of resource management polces n a forest dependent communty n Canada. nce H.R. 494 s expected to restrct the use of forestland for commercal loggng, ths would reflect as an ncrease n the cost of captal (ncludes both land and captal), whch causes a decrease n the loggng output. Accordngly we ntroduced a cost parameter and calbrated the model such that an ncrease n the cost of captal reduced the output n the forest sector by $.22 mllon and $4.44 mllon, respectvely, n Lberty County and Florda. We used 999 IMPLAN data as the bass for calbratng the benchmark equlbrum. The model was solved usng the PATH solver n General Algebrac Modelng ystem (GAM). Our model aggregates Lberty County economy nto eght sectors (Dary and lvestock products; Agrculture products, Processed food products; Forest products and loggng; awmll products; Wood products; Pulp and paper; Utltes and servces) and Florda economy nto nne sectors (Agrculture, food and lvestock; Forest products and loggng; aw mll products; Wood products; Offce furnture and fxtures; Pulp and paper products; Non-renewable natural resources; Manufacturng; Utltes and servces). alent features of our model are descrbed

7 7 below n sx parts. The notatons used n the mathematcal model and the equatons are presented n Table 2 and 3, respectvely. Table 2 Model Parameters and Varables Parameters δ A substtuton elastctes of Armngton functon δ substtuton elastctes of CET functon T δ CE captal-labor substtuton elastctes of frms F t tax rate on consumer commodtes C t tax rate on captal use K t tax rate on labor use L t tarff rate on mports t M y margnal propensty to save γ F CE share parameter n the producton functon of frm α effcency parameter of CE producton functon of frm F γ CE share parameter n the producton functon of commodty A β effcency parameter of CE producton functon of commodty γ η θ A T CET share parameter regardng destnaton of domestc output shft parameter n the CET functon of frm power n nested-ele household utlty functon µ subsstence household consumpton quanttes ψ household s margnal propensty to save ϑ replacement rate ξ Phllps curve parameter IO j α I CG ntermedate demand Cobb-Douglas power n the bank s utlty functon α Cobb-Douglas power n government utlty functon (commodtes) α Cobb-Douglas power n government utlty functon (captal) KG α Cobb-Douglas power n government utlty functon (labor) LG Varables P K prce of prmary factor (captal)

8 8 P P L K L D prce of prmary factor (labor) prces of domestc output prmary factor (captal) endowments prmary factor (labor) endowments supply of domestc output of frms domestc output of frms delvered to home market P X P D ndex domestc output prce delvered to home country domestc sales of composte commodty sales prce of composte commodty P prce ndex of domestc commodty P world market prces of exports n terms of foregn currency WXZ WMZ P world market prces of mports n terms of foregn currency ε exchange rate DM P mport prces n natonal currency DX P export prces n natonal currency E exports M K L C U B H G I F T C E T E L B u G mports captal demand labor demand consumer demand Y household s ncome utlty levels household savng consumer expendture government savng foregn savng total domestc and foregn savngs nvestment lesure demand extended consumer expendture tme endowment unemployment C government demand for commodtes K government demand for captal L T T G G R F government demand for labor tax revenues tax transfer

9 9 T other transfer OF T tax revenue on use of captal T T K L C M tax revenue on use of labor tax revenue on consumer commodtes T tax revenue on mports T Y ncome taxes Consumer Expendtures 9 j= Table 3 Model Descrpton. C = µ + θ[( + tc ) P ] ( B ( + tc j ) Pjµ ) 2. =ψ ( t Y H y ) 9 θ 0 3. L = ( T µ 0 ) [( t y ) PL ] B ( + tc ) P j j µ j ( θ0 ) j= P 4. L / PC E = U / L ξ PL / PC EU / L 5. P 9 = ndex = 9 = ( + t ( + t C 0 C Investment Demand 6. T = H + G + εf 7. I = α I P T Frms ) PC 0 0 ) P C 0 δ F δf ( δ F ( ) ( / α ) F δf δ F δ F δf 8. K = γ [ + t ) P ] γ [( + t ) P ] + ( γ ) [( + t ) P ] 9. F F ) ( K K F K K F L L δ F δ F ( δf ( ) ( / α ) δf δ FI δ F δ F [( + t ) P ] γ [( + t ) P ] + ( γ ) [( + t ) P ] δ ) L = ( γ ) F Foregn Demand K D L A F M 0. ( ) [ ( ) ] A A A A A A A A = γ P γ P + γ P ( X / β ) D A A M A M K K A D D A A A A A A A. M = γ P [ P ( ) P ] A γ + γ ( X / β ) D T M A D F ( ) ( ( ) 2. ( ) [ ( ) ] T T T T T T T T = γ P γ P + γ P ( X / η ) D T T ) L A L A F F

10 0 T X T DM WMZ 4. P = ( + t M ) εp M D ( 3. E [ ] T T T T T T T T = γ P γ P + ( γ ) P ( X / η ) 5. P DX = εp WXZ Balance of Payment 9 DM 6. P M = = = Government 9 P DX E + 7. C = α P ( T T ) G 8. K = α P ( T T ) G CG R KG K R PL ( LG R 9. L = α T T ) G 20. TR ( tc PC + t K PK K + t PL L + t L M ε P = 9 = 2. T F = ϑ PL EU + PndexTOF Market Clearng K = 9 = + K 23. L + L G G 9 = K = L E 24. X IO + C + C + I ( =...9) = = j= j U F F G F F G G G T DM M ) + t Y Income Equatons 25. Y = PK K + PL ( L EU ) + TF 26. B = ( ty ) Y H 27. P ( + t ) P K + ( + t ) P L + P IO ( =...9) = K K L L WMZ 28. P X = P M + P D D WXZ 29. P = P E + P D D Macroeconomc Closures K = K = 3. F = = 0 G 33. T OF = TOF 9 = j= j Y )

11 Expendture Equatons and Investment Demand The model assumes that consumers seek to maxmze utlty as characterzed by a nested Lnear Expendture ystem (LE) based on a tone-geary utlty functon. Total consumpton s splt nto two components consumpton goods and lesure component (equaton ). The model apportons the overall consumpton of a commodty across the two components by usng expendture elastctes and a Frsch parameter. Under the tone-geary functon, household utlty s derved only from the lesure component of consumpton. Lesure demand s determned by relatve prces and the sze of the overall budget for lesure, whch s descrbed n Equaton [3]. The sourcng of the commodty s determned from a two-level optmzaton process. In the frst stage, consumer chooses between lesure and a composte consumpton good and maxmzes tone-geary utlty functon subject to a budget constrant. In the second LE nest, the consumer chooses between domestc and mport goods n each sector assumng that mported and domestc commodtes are mperfect substtutes. Household savng s descrbed n equaton [2] and Phllps curve s ntroduced to capture the negatve relatonshp between real wages and the unemployment rate and s llustrated n equaton [4]. The prce ndex s defned n Equaton [5] and we selected wage as the numerare. The representatve agent receves ncome from prmary factors and net transfers from the government and uses ths ncome to purchase all the products n the market. Domestc fnal demands are composed of prvate consumpton, government consumpton, and nvestment. Changes n aggregate consumpton are a drect measure of the equvalent varaton of polcy changes, whch s the ndex of welfare effect n our model. Total savng s the sum of household savng, government savng and foregn nvestment savng (Equaton 6).

12 2 Frm Producton Equatons and Foregn Demand Producton n the economy s specfed by CE technologes. Producton exhbts constant returns to scale and frms are perfectly compettve, whch mples that prces equal margnal costs of producton. Producers are constraned n ther choce of nputs by a three-level nested producton technology. At the top level, ndvdual ntermedate goods and the bundle of prmary factors are used n fxed proportons reflectng the Leontef type of technology. These proportons are derved from nput-output coeffcents n the model s database. At the second level, each sector has a constant elastcty of substtuton (CE) aggregator of producton labor and captal. Value added s produced wth a CE functon of aggregate labor and captal (equaton [8] and equaton [9]). At the thrd level, the frms have the choce of buyng ntermedate nputs from the domestc market or the foregn market accordng to the constant elastcty of transformaton functon (CET). The second and thrd level of producton modelng requres a number of sets of elastctes. We have chosen elastcty values from the prevous lterature and based on our knowledge of the study regons (hoven and Whalley, 992). Equaton [0] s Armngton functon, whch shows how mports and domestc output are used to generate the composte commodtes. Equaton [] expresses mport demand as a functon of the relatve prces of mports and domestc commodtes. It s derved from a cost-mnmzaton approach subject to equaton [0] and a fxed level of composte commodty demand. Equaton [2] provdes the Constant Elastcty of Transformaton (CET) functon that transforms domestc output to commodtes to exports and domestc sales. Equaton [3] s derved from proft maxmzaton subject to equaton [2] and a fxed level of domestc output; t defnes export supply as a functon of relatve prces. Frms pay ndrect taxes and other costs ncludng workng captal costs and wages. Fnally, each CE and Leontef functon carres a techncal change

13 3 parameter whch can be set exogenously to shft the share of a gven tem n the relevant aggregate. We consdered labor supply endogenous and assumed that labor s moble across sectors. Captal (a composte of captal and land) s consdered moble among sectors and assumed fxed n each regon. Proft maxmzaton mples that the value of margnal rate of transformaton of the domestc good for an aggregate export wll equal the relatve domestc good prce n terms of an aggregate export ndex. Equaton [3] and Equaton [4] are the prce of mport and export equatons respectvely. Balance of payment s descrbed n equaton [6]. Government Equatons The government maxmzes a Cobb-Douglas utlty functon under a balanced budget (Equaton [7], [8], [9]). Government obtans ts revenue from collectng ncome taxes, ndrect taxes, and tarffs leved on mported goods. Tax revenues from consumpton goods, captal and labor use, and from the household s ncome, are made nomnal by usng the Laspeyres consumer prce ndex (Equaton [20]). The government pays unemployment benefts to the household at the replacement rate (Equaton [2]). Government total payment equals to the payment benefts to unemployment and other lump sum transfers. Income Equatons The model nsttutons are households, government, frms, and the rest of the world. Factor ncome s channeled completely to the household. The household receved part of ts ncome from government transfer (Equaton [25]). Equaton [26] descrbes the net ncome after tax plus savng equals consumer s total expendture. Equaton [27] s a zero proft condton, where the total supply of domestc output of frms equals to the value added and ntermedate demand. Equatons [28] and [29] are zero proft condton for mport and export accordng to Armngton assumpton.

14 4 Macroeconomc Closure and Market Clearng The equlbrum condtons for factor markets are defned n equatons [30-33]. Two market clearance rules follow from our statc equlbrum assumpton. Both captal and labor markets clearng condtons hold n the model (Equaton [22-24]). Whle most of the equatons are self-explanatory, an addtonal explanaton s n order. Frst, the model descrpton presented n Table 3 reflects Florda model wth 9 sectors and 9 commodtes. The correspondng model for Lberty County wll have only 8 sectors and 8 commodtes. econd, all tax rates are zero n the benchmark equlbrum. Thrd, n order to capture of the lmted moblty of labor across sectors n Lberty County relatve to Florda, we set the elastcty of labor supply and CE captal-labor substtuton-elastctes low. Model Results and Dscusson Table 4 descrbes the mpacts of a $.22 mllon reducton n the Forest products and loggng sector output n Lberty County. For each sector, changes n the return on captal, labor, domestc prce of output, and output are presented along wth benchmark values. As explaned earler, the polcy shock enters the Forest products and loggng sector by reducng ts output by $.2 mllon or by 0%. Results ndcate that the overall output n Lberty County wll decrease by about $5. mllon or by 4% n response to the proposed polcy. Although we notce a sgnfcant drop n the returns to captal and labor n the Forest and loggng sector, the overall decrease n the returns for these factors s mnmal. Results suggest that the returns to captal would slghtly ncrease n all sectors except n the Forest and loggng, Pulp and paper products, and Utltes and servces sectors. On the other hand, the returns to labor are shown to decrease n all the sectors, except Processed food products sector n the economy (Table 4). Commodty prces are shown to ncrease sgnfcantly n the Forest products and loggng sector due to a

15 5 Table 4 Economc Impacts of a $.22 mllon Reducton n the Loggng ector, Lberty County Returns on captal ($000) Returns on labor ($000) Domestc output Prce ndex (%) Output ($000) ectors Bench Mark After Polcy Change (%) Bench Mark After Polcy Change (%) Bench Mark After Polcy Change (%) Bench Mark After Polcy Change (%) Dary and lvestock products Agrculture products Processed food products Forest products and loggng awmll products Wood products Pulp and paper products Utltes and servces Total

16 6 decrease n the output whle the prces of outputs n other sectors dropped slghtly. The welfare ndex, as measured by changes n aggregate consumpton, wll decrease n Lberty County by 2.9% n response to $.22 mllon reducton n the Forest and loggng sector. Overall, the results ndcate that the Lberty County s economy wll experence a sgnfcant decrease n response to the reducton n the loggng sector. Ths s a common result n most of the forest resource dependent communtes (Alavalapat et al. 997). Forest resource dependent communtes do not provde many alternatve economc opportuntes for captal and labor to engage n other sectors of the economy. Table 5 presents economc mpacts of a tmber harvest reducton by $4.44 mllon n Florda. Unlke the case of Lberty County, the mpact of HR 494 on the overall economy of Florda s very mnmal. Results ndcate that the overall output wll drop by about $ mllon n response to a $4.4 mllon drop n the forest and loggng sector. We notce a slght ncrease n the overall returns for captal and labor. These results should not be surprsng because the Forest and loggng sector s very small relatve to the overall sze of the Florda economy (0.2%). Furthermore, n a larger economy, factors of producton wll have greater opportuntes to move across sectors. As a result t may be even possble to see an overall ncrease n the economy n response to a contracton n a partcular sector caused by a shock.

17 7 Table 5 Economc Impacts of a $4.4 mllon Reducton n the Loggng ector, Florda ( U $mllons) Returns on captal ($000) Returns on labor ($000) Domestc Output Prce Index Output ($000) Bench Mark After Polcy Change (%) Bench Mark After Polcy Chang e Bench Mark After Polcy Change (%) Bench Mark After Polcy Change (%) ectors Agrculture, food, & lvestock Forest products & loggng aw mll products Wood products Offce furnture & fxtures Pulp and paper products Non-renewable resources Manufacturng Utltes and servces Total

18 8 ummary and conclusons The HR 494 Natonal Forest Protecton and Restoraton Act 200 proposes a ban on commercal tmber harvest on all natonal forests n the U.. In ths study, we examne economywde mpacts of ths proposal on Lberty County (a small forest dependent county) and on the state of Florda. Based on the hstorcal harvest data, we estmated that the bll would reduce the average annual tmber harvest by $4.44 mllon n Florda and by $.22 mllon n Lberty County alone. In order to capture the ntersectoral lnkages and assocated multpler and trade off mpacts, we employed a computatonal general equlbrum (CGE) approach. Analyses were conducted separately for Florda and Lberty County snce sgnfcant structural dfferences exst between these two economes. For example, the share all forestry related sectors n the Florda economy s only.9% whle the correspondng share n Lberty County s about 7%. The results reveal that the mpact of HR 494 ($4.44 mllon) n Florda would have mnmal mpact on the economy. However, the magntude of the mpact of HR 494 on the economy of Lberty County appears to be hgh. Results of ths study provde mportant nsghts to polcy makers and mplementng agences. Frst, the mpact of ths proposal s not unform across the state. In Lberty County, wth lmted alternate employment opportuntes and less scope n the expanson n other sectors, ths proposal causes a sgnfcant reducton n the welfare of households. The UDA Forest ervce s requred, by law, to return 25% of gross tmber recepts from the Natonal Forests drectly to the countes located wthn the Natonal Forests n addton to annual payments n leu of taxes. Although a new law, the Rural chools tablzaton Act, decouples the county recepts from the tmber harvest level and replaces the 25% forest payments, the elmnaton of loggng actvty would certanly compound the on-gong socoeconomc crss. Ths suggests that wthout approprate compensaton schemes to offset the

19 9 negatve mpacts, the socal acceptablty of the proposed polcy s doubtful n Lberty County. At the state level, where people are less dependent on the forest sector, HR 494 may have a greater appeal. It s mportant that polcy makers consder these regonal dfferences and address equty ssues n makng decsons. Fnally we would to pont out the lmtatons assocated wth our study. Frst, the model does not consder the envronmental benefts or ncreased opportuntes n recreaton, f any, assocated wth HR 494 proposal. It s qute possble that the utlty of resdents of Lberty County and Florda may ncrease from mproved envronmental servces assocated wth the proposal. econd, the models used n smulated the polcy shocks are senstve to the parameters used n the model. Although we used the best nformaton that s avalable for us, there s sgnfcant scope to refne the parameters. Thrd, t would be nterestng to dsaggregate the land from captal and to consder t as an exogenous varable. Ths would allow to smulate the polcy shock by reducng the forest land avalable for the Forest and loggng sector. Acknowledgement Fnancal support from the UDA Forest ervce and the Florda Agrcultural Experment taton s greatly apprecated. We also thank for the help from Crstna Mohora. References Alavalapat, J.R.R., M.B. Percy, and M.K. Luckert A computable general equlbrum analyss of a stumpage prce ncrease polcy n Brtsh Columba. Journal of Forest Economcs 3(2): Alavalapat, J.R.R., W.L.Adamowcz, and W.A.Whte A comparson of economc mpact assessment methods: The case of forestry developments n Alberta. Canadan Journal of Forest Research 28(5): 7-79.

20 20 Champerlan JL, Bush RJ, Hammett AL, Araman PA (2002) Eastern Natonal Forests: Managng for Nontmber Products. Journal of Forestry : 8-4. Clary D., 986. Tmber and the Forest ervce. Unversty Press of Kansas, Lawrence. Cordell HK, Betz CJ, Bowker JM, Englsh DBK, Mou H, Bergstrom JC, Teasley RJ, Tarrant MA, Looms JB (eds) (999) Outdoor Recreaton n Amercan Lfe: An Natonal Assessment of Demand and upply Trends. Champagn, IL: agamore Publshng. Danels E, Hyde WF, Wear DN, 99. Dstrbutve Effects of Forest ervce Attempt to Mantan Communty tablty. Forest cence 37: Looms JB, Walsh RG, 997. Recreaton Economc Decsons: Comparng Benefts and Costs, 2 nd Ed. Venture Publshng, Inc., tate College, Pennsylvana. MIG, Inc., Economc Impact Assessment Modelng ystem. Mnnesota IMPLAN Group, Inc., tllwater, Mnnesota, lcensed to the Unversty of Florda, Department of Food and Resource Economcs. Patrqun, M., J.R.R. Alavalapat, A. Wellstead, W. Adamowcz, and W. Whte Estmatng mpacts of resource management polces n the Foothlls Model Forest Economy. Canadan Journal of Forest Research 33: Pohjola, J Economywde effects of reducng CO2 emssons: a comparson between net and gross emssons. Journal of Forest Economcs 5(): hoven, JB and Whalley, J., 992. Applyng General Equlbrum, Cambrdge Unversty Press. U.. Congress, 200. Catalog of Congressonal Blls. 03 rd 07 th Congress, HR UDA Forest ervce, UDA Forest ervce trategc Plan. Washngton D.C.

21 2 UDA Forest ervce, 998 Natonal Forest n Florda Recepts. UDA Forest ervce, Tallahassee, Florda. UDA Florda Dvson of Forestry, Florda Forest Forever. Florda Department of Agrculture and Consumer ervce, Tallahassee, Florda. Wear DN, Gres JG, 200. The outhern Forest Resource Assessment ummary Report. UDA Forest ervce, outhern Research taton, Ashevlle, North Carolna, (