Efficient Technology and the Conservation of Natural Forests: Evidence from Sri Lanka

8/22/2019 Efficient Technology and the Conservation of Natural Forests: Evidence from Sri Lanka

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Economics and REsEaRch dEpaRtmEnt

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e cerv

f nurl Fre:

Evee fr sr Lk

Herath Gunatilake

October 2007

RD WoRking PaPER SERiES no. 105


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ERD Wrking Paper N. 105

EfficiEnttEchnologyandthE consErvationof natural forEsts:

EvidEncEfrom sri lanka

hErath gunatilakE

octobEr 2007

Herath Gunatilake is a Senior Economist at the Economic Analysis and Operations Support Division, Economics and

Research Department, Asian Development Bank. This research was carried out with fnancial assistance rom theEconomy and Environment Program or South East Asia (EEPSEA). The author acknowledges comments received rom

Nancy Olewiler, Department o Economics, Simon Fraser University during the design and feld research phases o

this work. The author also acknowledges valuable comments by William F. Hyde, Senior Scientist, Forest Economicsand Policy Analysis Research Center, University o British Columbia, who helped in reorganizing the original version

o the paper. The author is, however, solely responsible or any errors contained in the paper.


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2007 b Asian Deveopment BankOctober 2007

ISSN 1655-5252

Te views expressed in tis paper

are tose o te autor(s) and do notnecessari refect te views or poicies

o te Asian Deveopment Bank.


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FoREWoRD

Te ERD Working Paper Series is a orum or ongoing and recent competedresearc and poic studies undertaken in te Asian Deveopment Bank or onits bea. Te Series is a quick-disseminating, inorma pubication meant tostimuate discussion and eicit eedback. Papers pubised under tis Series

coud subsequent be revised or pubication as artices in proessiona journasor capters in books.


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CoNtENts

Abstract vii

I. INTRODCTIONI. INTRODCTION 1

II. BACRONDII. BACROND 2

III.III. METhODOlOy OR CAlClATIN TEChNICAl EICIENCy 5

I. SAMPlE, DATA, AND hyPOThESESI. SAMPlE, DATA, AND hyPOThESES 7

. RESlTS 1. RESlTS 10

A. Ecienc Improvements and orest Conservation 1A. Ecienc Improvements and orest Conservation 12 B. Ecienc Improvement versus Oter Poicies 14

I. CONClDIN COMMENTS 1I. CONClDIN COMMENTS 16

Appendix Distribution o te Sampe and Descriptive Statistics o te Data 1Appendix Distribution o te Sampe and Descriptive Statistics o te Data 18

Reerences 2Reerences 20


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AbstRACt

Existing poic instruments or conserving tropica orests ave sownimited success. Tis paper investigates te easibiit o improving te tecnicaecienc o te wood processing industr as an aternative approac to orestconservation, using sawmis in Sri lanka as a case stud. Improved wood processing

ecienc decreases te voume o raw materia (ogs) required to produce agiven quantit o processed wood products and, tereore, decreases te pressureon natura orests. A stocastic rontier production unction was estimated to

assess te tecnica ecienc o sawmiing in Sri lanka. iven te considerabeinecienc ound in sawmiing operations, current sawn wood output can beobtained wit 28% ess inputs. Compared wit oter poic measures, tecnicaecienc improvement as a potentia to pa a notewort roe in conserving

natura orests. Tecnoogica improvements, as a too or conservation, deservete attention o researcers and poicmakers.


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I. INtRoDUCtIoN

Te rapid decine in te words orest cover is a tangibe measure o a number o critica

goba environmenta poic interests (i) te decine in natura abitat and biodiversit; (ii) carbonsequestration to mitigate cimate cange; (iii) watersed management and erosion contro;(iv) iveioods o indigenous peope and te rura poor; and (v) genera protection o aestetic

vaues. Poic diaogue or eac o tese concerns as ocused primari on (i) direct egisativeinstruments to contro orest destruction suc as restrictions on timber arvest eves and/or totaogging ban, (ii) repanting and improving orest management, (iii) certication o good management,(iv) incentives or good management, (v) taxes on orest products, and (vi) improvements in propert

rigts o orest ands.

Te success o tese instruments in protecting remaining tropica natura orests as been imitedand poicmakers continue to searc or aternative means. Tis paper examines te easibiit o

tecnica ecienc improvement in te wood processing industr as a means to conserve naturaorests.Te orest-conserving eect o tecnica ecienc improvement coud be substantia in mancases. Tis paper uses inecienc in sawmis in Sri lanka to iustrate te impact o tecnoogica

improvements on orest conservation. Sri lanka as a and area o 6.56 miion ectares, o wic80% was covered b cosed-canop natura orests in te beginning o te ast centur. Tis orestcover as dwinded to about 18% b 1992 (ME 1995).

Economics examines two measures o ecienc aocative and tecnica ecienc. Improvementsin aocative ecienc require te rm to cange te combination o inputs in order to aign wit

input price canges. hde (1980) sows tat improved aocative ecienc in timber management inte Pacic Nortwest o te nited States (S) woud sarp increase production or, aternative,

maintain timber production wie sucient reducing and input to tripe te area o protectednatura orests. Te goba or regiona impact o simiar aocative ecienc improvements is unknown.however, exampes o poicies tat create uncertaint and tereb imit orest production or constraincapita investment in orestr and wood processing are widespread. yin and Newman (1996) as we

as liu et a. (2001), and hde et a. (1997) discuss suc poicies in orce in te Peopes Repubico Cina, and te Piippines, respective. Deacon (1994) anazes te eect o a more generaevent o widespread socia disruption on orestr. Poicies tat restrict arvests and sipment are

just as common (Sedjo and Wiseman 1983, Bod and rutia 1987, Zang et a. 1998).

Improvements in tecnica ecienc reer to increased output rom te same eve o inputsor obtaining te same output rom ewer inputs. hde (1997) suggests tat improved tecnica

ecienc in te S wood processing industr woud aso ave a orest-conserving eect. Industriaresearc and support rom agencies suc as te S orest Product laborator ave ed to useutecnoogica innovations,1 wic increased te ratio o umber to roundwood rom 33% in 1970 to1 Tese innovations incude (i) best open ace tecnoog, wic optimizes te initia ine or sawing; (ii) edge-gue andTese innovations incude (i) best open ace tecnoog, wic optimizes te initia ine or sawing; (ii) edge-gue and

rip metod, wic reduces te wood ost in edging; (iii) saw-dr-rip metod, wic increases te deect-ree umber

avaiabe rom ardwoods; and (iv) use o sarper and more stabe bades, wic can increase umber recover romogs b 5% to 10%.


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efficient technOlOgyandthecOnservatiOnOfnatural fOrests: evidencefrOm sri lanka

herath gunatilake

42% in 1993 (rantam and howard 1980 and Ince 1994, as cited b Wernick et a. 1997). ictor

and Ausube (2000) simiar contend tat urter improvements in management and tecnoogwi generate iger vaue out o products and save more virgin orests. or exampe, re-engineeringwooden I-beams or foor sstems to use ess ber tan traditiona construction, and making oriented

strand board as a substitute or pwood, coud ep curb demand or wood. Togeter wit itingcrop ieds and concentrating orestr in ast-growing wood arms, tecnoogica improvementsare estimated to increase te area et or nature to 3 biion ectares. Tis paper sstematicameasures tecnica ecienc o wood processing and assesses te possibiit o using tecnica

ecienc improvements as a too or orest conservation in Sri lanka.

Te genera objectives o tis paper are to trace te eect o ecienc improvement on naturaorests in terms o reduction o arvest o ogs, and to assess te reative merits o tis approac

in comparison to oter poic instruments. Te rest o te paper is organized as oows. SectionII describes te orestr situation in Sri lanka. Section III presents te teor in reation to teestimation o tecnica ecienc using te stocastic rontier production unctions. Section I

describes te sampe, data, and poteses, oowed b an anasis o te researc ndings. Tena section discusses te poic impications.

II. bACKGRoUND

Sri lankas contribution to te goba weat o genetic materias and biodiversit is notewort(otagama et a. 1997). hence, te deorestation in te countrmore tan 40,000 ectares rom

1956 to 2000is aarming, given te average annua repanting during te same period o on2,000 ectares. Te actors tat contributed to deorestation and orest degradation in Sri lankaare extensive and compex; some are even outside te orestr sector. Tese actors incude argeagricutura and uman settement projects suc as te Maawei deveopment project, siting

cutivation, excessive arvesting o timber, and sometimes, arvesting nontimber orest products.

Tere is a strong ink between popuation growt and deorestation in man deveoping

countries. More ood is needed to eed/support te increasing popuation. Over te ears, agricuturaproduction as increased in Sri lanka main b expanding te area under cutivation (ME 1995).In addition to te demand or ood, demand or ue-wood, construction wood, and oter wood-based products suc as paper, pup, etc. are aso increasing wit popuation growt. Te resource

base tat suppies orest products in Sri lanka as decined remarkab; per capita orest area asdecined rom about 1.3 in 1900 to ess tan 0.1 ectare in 2000. Te remaining natura orestsace mounting pressure as te popuation keeps increasing; popuation in Sri lanka is sti growingat a rate o 1.16% (Centra Bank 2006).

rom a conservation point o view, tis situation as been aggravated due to unequa distributiono te existing tpes o natura orests. O te remaining natura ig canop orests, about 85%are dr-zone orest tpes. Ecoogica more important owand rainorests and montagne orests are

conned to sma patces (unatieke and unatieke 1991). Ric bioogica diversit and igereve o endemism ound in te atter categor o orests ave made teir protection a priorit.having recognized te importance o tese orests or biodiversit protection, te government o

Sri lanka as decared most o te remaining owand rainorests and montagne orests as protectedareas.


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sectiOn ii

backgrOund

erd WOrkingPaPer seriesnO. 105

Since natura orests supp a range o mutipe products and environmenta services, te

consequences o rapid deorestation can be ar reacing. According to te ME (1995), annua sawnwood consumption per 1,000 persons in Sri lanka in 1993 was estimated at 31 cubic meters (m3),wic is comparative ess tan in oter countries Maasia 216.9m3, Taiand 67.4m3, Repubic

o orea 112m3

, India 20.5m3

, and S 485m3

. Sawn wood demand in Sri lanka is projected to growrom 0.544 miion cubic meters (m3)in 1993 to 0.885 miion cubic meters in 2020, at a rate o12,600m3/ear. Demand or pwood and oter wood-based panes, respective, are predicted toincrease at rates o 2.8% and 3.5% per ear (ME 1995). Predicted supp and demand or sawn wood

is depicted in igure 1. I current trends continue uncecked and wood imports are not promoted,tere woud be a sortage o sawn wood in te countr.

900

800

700

600

500

FIGURE 1

PREDICTED SAWNWOOD PRODUCTION AND CONSUMPTION FOR SRI LANKA

95 0 5 10 15 20

Year

Sawnwood,

(000m3)

Production Consumption

Source: MFE (1995).

Beore te 1970s, te countrs timber requirement was arvested rom natura orests. Excessive

arvesting o timber and cearing orests or agricutura expansion et on a sma proportiono natura orests, wic were aso ig degraded. having recognized te need or conservationo te remaining orests, te government decared some o te natura orests as protected areas.

harvesting timber rom unprotected natura orests was aso banned. As a resut o te ban, peopestarted to substitute ess preerred tree species tat grow in ome gardens and oter private ands, inpace o te ig-vaue tropica timber species. Private ands were supping te timber requiremento te countr or some time wie ver restrictive reguations or eing and transport o timber

were enacted (Senaviratne and unatiake 2001). Tese reguations created an articia scarcit otimber. however, due to te uncertaint o getting timber transport permits to se timber, privatesector investments in te orestr sector as been acking. Tis urter aggravated timber scarcitin te countr and raised timber prices (Senaviratne and unatiake 2001).

Te iger prices o timber unortunate provide incentives or iega ogging rom naturaorests. or exampe, i a rura dai wageworker can arvest a mature satin tree (a ig-quait

tropica ardwood tree) rom a natura orest, e can make more mone tan rom working te woeear. iven suc incentives, iega ogging as become widespread; te number o orest oencesrecorded in 1997 increased b 3% to 5,158 against 5,014 in 1996, wie te vaue o iega timberconscated was Rupees 35.7 miion in 1997 (Centra Bank 1997). Tese records represent on a

raction o te iega activities. iven te tedious procedures and toug reguations, obtaining atimber permit as become an extreme dicut task witout specia support rom government


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ocers. having reaized te potentia mutua benets, timber traders and government ocers

invoved in issuing timber permits ave ormed a carte, wic aciitates issuance o permits totimber traders. Since tree owners know tat te are unabe to get permits easi, timber traders inte carte ave excessive bargaining power against timber owners in deciding stumpage prices. Tus,

te prevaiing situation as provided opportunities or timber traders to make excessive prots. orexampe, Senaviratne and unatiake (2001) sow tat te prot margin in timber trading is about60%. Tree owners on get about 22% o te tota vaue. In return or te support o governmentocias, timber traders pa tem bribes. Tus, a part o te vaue o timber ends up as income

or government ocias. er ow prices received b tree owners and ack o cear propert rigts(existing reguations take part o te ownersip rigts awa rom tree owners) discourage cutivationo trees b smaoders.

Initia, tis cooperative arrangement between timber traders and government ocers workedin arvesting timber rom private ands. Since tere were minimum eorts b private andowners togrow timber trees, most o te mutipurpose trees avaiabe in ome gardens were arvested witout

proper regeneration. Tereore, timber scarcit worsened during te ast two decades. As timberbecame scarce, te carte o timber traders and government ocers extended teir activities tonatura orests. Current, it seems tat wit te connivance o government ocers, timber iegaarvested rom natura orests is sent to te market as i te were arvested rom private ands.

Because o tis invovement o corrupt government ocers in te carte, it is near impossibeto stop iega ogging. iven te above background, one o te major caenges Sri lanka woudbe acing in te immediate uture is supping orest-based products, especia timber, witoutcompromising te et need o conserving remaining natura orests wit ig biodiversit vaue.

Conventiona, steps taken to resove tis tpe o situation incude (i) estabisment o orestpantations b te government; (ii) enactment o more stringent reguations; and (iii) timber tradeiberaization. however, estabisment o orest pantations b te government is proibitive, cost,

and inecient in Sri lanka (ME 1995). Te orestr sector master pan as tereore rued out tispossibiit as a soution to te probem. On te oter and, more egisation ma not ied positiveresuts as existing restrictive reguation itse as aied to do so. Te private sectors invovement in

timber cutivation is critica to augment timber supp in te countr. however, as described, privatetimber production as been severe discouraged b existing eav reguator measures. Timber tradeiberaization is a possibiit, wic is deat wit b Weeraewa and unatiake (2007). Apart romte possibiit o increasing wood production and trade iberaization, ecient utiization o ogs

produced in te countr ma be an aternative means to reieve te pressure on natura orests.

Tere seems to be a signicant wastage in te sawmiing industr at present. Te orest/woodindustr in Sri lanka is dominated b sawmis producing sawn timber or domestic markets and or

subsequent processing suc as conversion into urniture and oter wood products. Previous recordso te sawmiing sector consisted o more tan 4,000 sawmis, incuding pit-sawing units. Tisstud, owever, nds tat pit-sawing units are no onger in operation due to iger abor costs.

Sawmis in Sri lanka are, in genera, sma and abor-intensive. Te ave od and most worn-out maciner. Tota output o sawn wood in 1993 is estimated at 515,000m 3. Te capacit osawmis ranges rom a ew cubic meters a ear to 7,000m3/ear. Te average output o te major


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sectiOn iii

methOdOlOgyfOr calculatingtechnical efficiency

erd WOrkingPaPer seriesnO. 105 5

sawmis2 is about 750m3/ear. Sawmis in Sri lanka are od, wit te average age o surveed

mis at about 18 ears (ME 1995). Te odest mis were estabised in te ear 1950s and manave not gone troug an major improvements. Te od mis empo simpe and abor-intensivetecnoog and sti use origina imported equipment, wie some o te new mis ave oca

made repicas o te od imported maciner (ME 1995). Primar cutting macines are dominatedb circuar saws, and some arger mis ave band saws (wit orizonta reciprocating ead rings)tat aow or iger recover o wood due to teir reative narrow saw bades. Sma size, aborintensiveness, od and most worn-out maciner, poor aout, and poor saw-doctoring and eeding

sstems ave resuted in eav osses during miing. Te average recover rate is on about 40%(compared to 55% and 50% in Maasia and Indonesia, respective).

Tis picture o te sawmiing industr in Sri lanka impies an ongoing wastage and ack o

ecienc. Tere ma be possibiities or improving ecienc in tis sector to make sawmiingmore protabe. Consumers ma be abe to purcase sawn timber at a ower price i ecienc isimproved. More important, improving te ecienc o tis sector ma pa a vita roe in te

conservation o natura orests. Reduction o wastage in sawmiing woud reieve extra pressure ontree arvesting and reduce te ongoing destruction o natura orests in Sri lanka. Tis wi ave asignicant positive impact on orest conservation in Sri lanka, in addition to direct producer andconsumer benets.

III. MEthoDoloGy FoR CAlCUlAtING tEChNICAl EFFICIENCy

Traditiona, economic ecienc at te rm eve is measured b singe actor productivit.Tis approac is, owever, not ver accurate as oter actors soud be ed constant in measuringactor productivit. arre (1957) deveoped better and simpe two measures o ecienc tecnicaecienc and aocative ecienc. O tese, tecnica ecienc refects te abiit o a rm to

obtain maximum output rom a given set o inputs, or to obtain a given eve o output rom aminimum eve o inputs. Aocative ecienc refects te abiit o a rm to use inputs in optima

proportions, given teir prices (Coei 1995). Tese two ecienc measures are combined to estimateeconomic ecienc.

arres tecnica, aocative, and economic ecienc can be urter eaborated on using teconcept o unit isoquants (igure 2). Consider a rm producing output y rom inputs X1 and X2 wit

te production unction, y = (X1, X2). Assuming constant return to scae, te rontier tecnoogcan be represented b te unit isoquant, 1 = (X1/y, X2/y), QQ. let WW represent te ratio o inputprices. arre denes a rm producing at point A as tecnica inecient and te ratio OB/OAgives arres measure o tecnica ecienc. I te rm is operating at point B, it is considered

tecnica ecient but aocative inecient; te ratio OD/OB gives arres measure o aocativeecienc. ina, te ratio OD/OA measures tota ecienc. Economic ecienc is measured bcombining bot ratios and is equa to te product o tecnica and aocative eciencies.

2 In Taiand, te average is 7,000mIn Taiand, te average is 7,000m3/ear and in Indonesia it is 30,000 m3/ear. Tus, te average output o a sawmiin Sri lanka is ower tan tat o oter Asian countries.


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herath gunatilake

FIGURE 2

EFFICIENCY MEASUREMENTS

X2/Y Q

C

B

Q

A

D

O X1/Y

Source: Gunatilake and Gunaratne (2002).

W

W

Oten, rm eve inputoutput reationsips are examined wit production unctions estimatedusing regression anasis. Since te regression ine is tted troug te means o te data set,suc anasis provides on an average reationsip (Aauddin et a. 1993). In contrast, te rontierproduction unction corresponds to te orma denition o a production unction, wic reers to

te maximum output obtainabe rom a given set o inputs and tecnoog. Te basic dierenceo a stocastic rontier, compared to an average production unction, ies in te ormuation ote residua term o te regression equation. here te error term is separated into smmetricand asmmetric components. Te smmetric component represents te usua random variations,

measurement errors, and statistica noise. Te asmmetric (one-sided) term captures te tecnicainecienc o te rm (umbakar et a. 1991, Bravo-reta and Pineiro 1993, Coei 1995). Te

major weaknesses o te stocastic rontier metod incude arbitrar specication o te distributionaorm o te one-sided error term, seection o te unctiona orm, and dicuties invoved wenmutipe outputs are present.3

oowing te standard assumption o Zener et a. (1966), te above teor can be used to

speci a rontier production unction or sawmis. Assuming tat mi owners maximize expectedprots, te singe equation Cobb-Dougas stocastic production mode (Aigner et a. 1977, Meeusenand van den Broeck 1977) can be specied as

Lny Ln Lnx v uik

ik ik i i = + + =

01

5

were

i is te index o sawn wood output, cubic eet/mont

x1 iste index o og inputs, cubic eet/mont

x2 isunits o energ used, kiowatt ours/mont

3 Tecnica ecienc o a mutipe product rm can be measured using te matematica programming metod knownTecnica ecienc o a mutipe product rm can be measured using te matematica programming metod known

as data enveopment anasis.


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sectiOn iv

samPle, data, and hyPOtheses


x3 iscapita expenditure o te mi

x4 isskied abor, person das/mont

x5 is unskied abor, person das/mont

k (k =1,2,5) are te parameters

vi is a random variabe, iid N(0, 2

v)

ui is a non-negative random variabe tat represents tecnica inecienc

Te two error terms make te dierence between an average production unction and a rontierproduction unction. sing Battese and Coeis (1992) parametric specication, te maximum

ikeiood estimation o te equation provides estimators or , 2 = 2v + 2u and =

2u +

2.Prediction o tecnica ecienc o a rm is based on conditiona expectation o u i (exp(-ui)),given te vaue o random variabe i = vi - ui. Subtracting exp(-vi) rom bot sides o te aboveequation

Lnyi* = Lnyi - u iwere i* = is te it rms observed output, adjusted or statistica noise. Te above equation orms

te basis or te measurement o te tecnica ecienc o te rm.

IV. sAMPlE, DAtA, AND hyPothEsEs

Primar data or estimating te above production unction was coected using a structuredquestionnaire. A stratied random sampe was drawn rom te popuation, based on te geograpiczones in Sri lanka. rom eac zone, a number o mis to be incuded in te sampe were decided

based on te proportion o te mis in te zone. Ten random number tabes were used to seectte predetermined number o mis. Te origina samping ramework and te distribution o tena sampe are given in te Appendix (Tabe A1). Te surve was conducted in two stages. In

te rst stage o te surve, inormation on genera aspects o te sawmis was coected and aninputoutput seet was given to te mi manager. At te rst stage, most o te managers agreedto out te inputoutput seet. however, at te time o coection, amost a managers did not out te inputoutput seets. Wit tis disappointing experience, a second visit to te mis

was arranged to te orms using person-to-person interviews. Te data gatered are based onte memor o te mi manager in most cases, as te do not keep proper records. Data woudave been more accurate ad te mi managers ed out te orm as inputs came in and soonater miing te ogs.

In te origina samping ramework, te sampe size was 180 mis. Tirteen mis were aocatedor Ampara and Batticaoa districts. Due to securit reasons, te researc assistants were not abeto make te second visit to tese 13 mis. About eigt questionnaires were excuded rom te

sampe rom dierent districts due to inconsistencies ound in te answers. Anoter 11 mis wereexcuded rom te sampe due to mi owners reuctance to provide inormation on og inputs andoutputs. Tus, a compete set o data was avaiabe or on 148 sawmis.

Anoter probem encountered in estimating te equation was te presence o a number odierent outputs. As mentioned earier, te stocastic rontier tecnique can be used on or


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singe-output rms. Tereore, te dierent outputs were aggregated to a singe output index using

te oowing ormua

y

p q

Pn

j

rj rj

r

s

j

j

n

= =

=

1

1

_

wereyjis te normaized output or te jt rm,s denotes te number o dierentiated products,

prjdenotes te price o te rt product or te jt rm, qrjdenotes te amount o rt product ortejt rm and, n is te number o rms. Te average price in te denominator is dened as

p p q q q qj rj rj r

s

j j rj

r

s

= =

= = 1 1

/ ,

A simiar probem was encountered in measuring og inputs. Te og inputs were broadcategorized into sotwood and ardwood, disregarding te species, and were aso aggregated using

te above ormua. Te number o units o energ used during te mont under consideration wasobtained rom te mont eectricit bis. An attempt was made to get accurate inormation on

capita expenditure o te sawmis. however, during te pre-testing stage it was et tat miowners/managers were not wiing to revea true inormation on capita expenditures, probabdue to tax evasive strategies. Tereore, a proxmi capacitwas used in pace o capita

expenditure.

Man tecnica ecienc studies ave estimated a second regression equation4 to identi tedeterminants o tecnica ecienc. Te stud oowed tis approac to identi te determinants

o tecnica ecienc o sawmiing. Since tere are no previous studies on te tecnica ecienco sawmiing, te variabes were identied based on te surve ndings, inorma discussions witte mi managers, and scatter pots o ecienc scores and reated variabes. Te variabes and

te postuated poteses are given in Tabe 1.

4 Te rst regression equation estimates te production unction to cacuate ecienc scores.


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sectiOn iv

samPle, data, and hyPOtheses


tablE 1dEtErminantsof tEchnical EfficiEncy

variablE dEscriptionhypothEsizEd rElationship

to tEchnical EfficiEncyX1 Age o te manager/owner Positive

X2 Quait o og inputs Positive

X3 Carges based on og input =1, Oters = 0 Negative

X4 Owner-managed mis = 1, Oters = 0 Positive

X5 Education o te manager/owner Positive

X6 Entrepreneursip Positive

X7 Capacit o te mi Negative

X8 Source o energ, on pubic eectricit =1, pubic eectricit

and oter = 0

Negative

X9 Age o te macines Negative

As to age o te manager/owner, age is assumed to infuence tecnica ecienc positive,since age refects te experience o te manager in te sawmiing industr.

Regarding quait o og inputs, given te scarcit o wood, man immature trees are arvested,

resuting in ver ow recover rates. Moreover, since te ogs are not suppied b we-managedorestands, man ogs are not straigt. hig-quait ogs (mature straigt ogs) are assumed toprovide iger tecnica ecienc. or carges based on og input, certain mis on ease teirmacines or miing, wit carges based on og inputs. Te oter mis purcase ogs, mi tem,

and se te sawn wood. Since te ormer tpe o mis ave no incentives to improve tecnicaecienc, it was assumed tat suc mis are tecnica inecient.

or te variabe mi ownersip, te surve reveaed tat wen ired managers manage temis, te are paid a xed mont saar. Tere are no incentive paments based on prots or an

oter measure o perormance (unatiake and unaratne 2002). Tereore, owner-managed mis areassumed to be more ecient. or te issue on education o te manager/owner, orma education

ma enance te management abiit o managers. Tereore, it is assumed tat a iger eve oorma education positive aects tecnica ecienc. Meanwie, on te variabe entrepreneursip,managers wit iger entrepreneursip abiit ma conscious take steps to increase tecnicaecienc to increase prots. Tereore entrepreneursip is assumed to aect tecnica ecienc

positive.

On mi capacit, given og sortages, arge mis ma not be abe to u utiize teirxed production actors. Tereore, it is assumed tat mi capacit negative aects tecnica

ecienc.

As to source o energ, Sri lanka as a ver irreguar supp o power because te countr

depends main on dropower. Power cuts are requent and, as mi owners expain, tese powercuts ma be one reason or ower ecienc. Tereore, it is assumed tat mis wit on pubiceectricit supp are inecient compared to tose wit pubic as we as teir own means o powersupp (generators).

ina, on age o macines, od and worn-out macines ead to ow recover and are tereoreassumed to aect tecnica ecienc negative.


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Te age o te owner (X1) was considered wen te owner imse managed te mi. Oterwise,

te managers age was considered. log quait (X2) was ranked rom 1 to 5; 1 representing tepoorest quait and 5 representing te best quait. Te tpe o miing (X3) variabe was measuredas a dumm 1 or te mis tat eased teir macines, 0 oterwise. Owner-managed mis (X4) were

assigned 1 wie te mis managed b ired managers were given 0. Education (X5) was ranked 1troug 6 or no scooing, up to grade 5, up to grade 10, rst government examination passed,universit entrance passed, and degree or dipoma, respective. Six entrepreneursip caracteristicswere quaitative assessed to rank te entrepreneursip (X6) o te mi manager. Tese caracteristics

incude risk perception, empoee weare tecnoog adoption, pura-activit or diversication,deveopment o contacts and networks, and sustainabiit/environmenta awareness. Managers/miowners were asked a ew questions on eac o tese aspects. Based on te answers, te wereassigned a rank rom 1 troug 5, 1 representing ver poor entrepreneursip and 5 representing

ver good entrepreneursip. Capacit o te mi (X7) was measured as potentia to produce sawnwood per mont i te mi operated or eigt ours at u capacit or 22 das. I te source oenerg (X8) in a mi is on eectricit, tat mi was assigned 1, and mis wit diese-operated

macines or combination o eectricit and diese were assigned 0.

In ear studies o tecnica ecienc, a two-stage procedure was oowed in anazing tedeterminants o tecnica ecienc. In te rst stage, tecnica ecienc scores were estimated,

and ten a second-stage regression was estimated to nd te determinants o tecnica ecienc.As sown b umbakar et a. (1991), tis procedure as two probems. irst, tecnica eciencma be correated wit inputs causing inconsistent estimates o te parameters and tecnicaecienc scores. Second, te standard ordinar east squares estimators are inappropriate because

te tecnica ecienc scoreste dependent variabe in te second stage regressionare one-sided. umbakar et a (1991) suggest a one-step ormuation in order to overcome tese probems.Te present stud used tis one-step procedure to obtain tecnica ecienc scores and teir

determinants simutaneous using te rontier econometric sotware (ersion 4.1) program.

V. REsUlts

Appendix Tabe A2 sows te descriptive statistics o te variabes used in te estimation ote rontier production unction. On te og input is signicant in te production unction. Energinputs and bot abor inputs are insignicant (see Appendix Tabe 3). Te resuts revea tat te

og input is te imiting actor o production in sawmiing. Most o te mis are operating undercapacit due to a severe sortage o ogs. Te poor resuts o te production unction anasis mabe due to measurement errors. had te inputoutput seets been ed out soon ater miing wasundertaken, as origina panned, better resuts woud ave been obtained.

Te distribution o te tecnica ecienc scores is given in Tabe 2. Te average tecnicaecienc is 0.7219. rom an input perspective, tis indicates tat on average te sawmis can save

about 28% o a inputs wie producing te same output i te production process is reorganizedin an appropriate manner. rom an output perspective, te resuts suggest tat on average 28%more sawn wood can be produced wit te current eve o inputs. Tus, te overa resuts indicatetat tere is considerabe inecienc in te sawmiing industr.


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tablE 2distributionof tEchnical EfficiEncy scorEs

EfficiEncy scorE (pErcEnt) numbErof mills pErcEntagEof mills

< 10 1 0.6811 20 1 0.68

21 30 8 5.41

31 40 10 6.76

41 50 12 8.11

51 60 3 2.03

61 70 6 4.05

71 80 23 15.54

81 90 41 27.70

91 100 43 29.05

Average ecienc score 0.7219

Standard deviation 0.229

Tabe 3 sows te actors infuencing tecnica ecienc in te sawmiing industr. Asmentioned earier, te equation to anaze te determinants o tecnica ecienc was estimated

using te maximum ikeiood metod, wic does not estimate coecient o determination (R2).Neverteess, te correation between actua and predicted vaues is 0.68, and seven o te ninevariabes used are statistica signicant. Te age o te manager/owner and te source o energ

do not sow a statistica signicant impact on tecnica ecienc. Since tere are requent powercuts, it was potesized tat mis tat compete depend on pubic power supp are tecnicainecient. however, resuts indicate tat tere is no statistica signicant reationsip betweensource o energ and tecnica ecienc.

tablE 3

factors affEcting tEchnical EfficiEncy

variablE coEfficiEnt standard Error t- ratio

Intercept 0.40366 1.58370 0.2549

Age (X1) 0.03787 0.05036 0.7518

Quait o ogs (X2) 0.35137 0.03369 10.4302**

Tpe o mi (X3) 0.47824 0.06415 7.4540**

Owner management (X4) 0.20986 0.02942 7.1326**

Education (X5) 0.22210 0.02816 7.8855**

Entrepreneursip (X6) 0.10627 0.02891 3.6756**

Capacit (X7) 0.08626 0.01516 5.6894**

Source o energ (X8) 0.16516 0.11648 1.4179Age o macine (X9) 0.28842 0.07388 3.9040**

** Signicant at 0.05 eve.


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Quait o te og input sows a statistica signicant positive impact on tecnica ecienc,

as expected. Te mis tat are on miing and carging based on te og input are inecientbecause tere is no incentive or suc mis to improve tecnica ecienc. As discussed earier,mi managers are not provided an incentives based on te perormance o te mi. Tereore, it

is expected tat owner-managed mis are tecnica more ecient. Te expected reationsip wasobserved wit statistica signicance. Education o te owner/manager was expected to positiveaect tecnica ecienc. Tis reationsip was not observed, wic ma be due to ack o ocuso orma education in business management. Entrepreneursip was expected to positive aect

tecnica ecienc. Te resuts sow te expected impact wit statistica signicance. As expected,tere is a negative reationsip between capacit o te mi and tecnica ecienc. As indicatedearier, most o te maciner in te sawmiing industr are od, and as macines get oder teirperormance becomes poor, eading to tecnica inecienc. As potesized, te age o te macine

negative infuences tecnica ecienc.

A. Efcienc Imprvemen and Fre Cnervain

Tecnica ecienc measures te maximum rate at wic te use o a inputs can be reducedwitout reducing outputs. It can aso be measured as te rate at wic te outputs can be increased

wit te same eve o inputs (umbakar 1996 and Seiord 1996). As te resuts sow, tere issignicant inecienc in te sawmiing industr in Sri lanka. A data enveopment anasis wasaso carried out wit te same data and it was ound tat ecienc scores were simiar to tosedescribed above (unatiake and unaratne 2002). Te resuts tus suggest tat te current sawn

wood output can be obtained wit about a 28% cut in a inputs. Suc an improvement wi reievepressure on te overa wood supp sector. however, protected orests wi receive te greatestimpact rom te og inputs savings. As basic orest economics suggests, tere is a cost gradientor iega arvesting rom dierent tpes o orests (Carke et a. 1993). Te east-cost tpes wi

awas be arvested rst and te igest-cost tpes wi be arvested ast. Private ands suc asome gardens are te east-cost wood sources wie protected orests are te igest-cost sources.5nprotected natura orests ma be in between tese two categories. I current trends continue,

scarcit wi raise prices, providing te incentive or iega timber extraction even rom igest-cost protected orests.

In order to igigt te magnitude o orest savings due to ecienc improvements, saved

ogs can be converted to an area o natura orests wit some pausibe assumptions, as oows.Te data used in tis cacuation were taken rom ME (1995).

(i) On average te dierent tpes o mature natura orests provide te oowing wood

voumes

lowand rain orests 126 m3/a

Dr monsoon orests 21 m3

/aMoist monsoon orests 39 m3/a

O tese orest tpes, owand rainorests are conned to a ew patces. Wood arvestrom tis tpe is not possibe because te are protected. Moist monsoon orests are

5 In genera, protected natura orests are te east disturbed orests and istorica remained intact due to ig cost o timberextraction. In addition to te ocation and reated ig cost o arvesting protected orests, tere are additiona costs o beingcaugt and punised or iega ogging. Suc costs are igest or te protected orests.


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aso imited to sma areas. On dr monsoon orests remain in arge areas. Tereore,

te saved orests are cacuated, assuming a weigted average o 25.5 m3 o wood canbe arvested rom one ectare o orests. In cacuating te weigts, te dr monsoonorests were assigned a weigt o 3 and te moist monsoon orests were assigned 1 based

on te avaiabe orest areas.(ii) As tecnica ecienc improves, te timber supp curve sits to te rigt. Assuming

tat te demand curve does not sit, te sit in te supp curve resuts in a ower

price and a iger equiibrium quantit o sawn wood. Tus, te tecnica eciencimprovement aows production o te extra quantit witout extra og inputs. Tis astwo eects. irst, te price decrease improves socia weare because ower prices increaseconsumer surpus. lower prices aso reduce te incentives or iega ogging. Second,

producing te extra sawn wood output wit te same inputs eads to saving te sourceo ogsand consequent te orest ands.

(iii) Tota round wood consumption in Sri lanka is 1,396,000m3 in 2000. O tis voume

o ogs, it was assumed tat 28% coud be saved annua i tecnica inecienc is

compete eiminated. however, compete eimination o tecnica inecienc is anunreaistic assumption. Tereore, te avoided deorestation was cacuated assuming tat

tecnica ecienc improvement are 25%, 50% and 75% o te existing inecienc o28%.

tablE 5EfficiEncy improvEmEntsand prEvEntEd dEforEstation

EfficiEncy improvEmEnt(pErcEnt)

prEvEntEd annual dEforEstation(hEctarEs)

25 3,695.29

50 7,390.58

75 1,1085.88

Tabe 5 sows te extent o prevented deorestation under dierent eves o tecnicaecienc improvements. Te assessment o te determinants o tecnica ecienc provides someavenues or tecnica ecienc improvements. Enancing te supp o quait ogs, investing in

new maciner, providing ired managers incentives tat are inked to ecienc improvements, andimproving entrepreneursip abiities can be used to improve tecnica ecienc.

Tis stud anazed tecnica ecienc improvements on at one stage o orestrsawmiing.

Te anasis sows tat tecnica ecienc improvement on at te miing stage as a potentia roein preventing deorestation in Sri lanka. Tecnica ecienc improvements over te entire orestrie cce (starting rom tree panting up to end uses suc as construction/urniture industries)

ma provide muc iger conservation impacts. I suc tecnica ecienc improvements canbe reaized at te regiona or goba eves, tere woud be proound positive impacts on orest

conservation. Te vaue o te ndings o tis stud is imited b te sma sampe size and quaito data. Moreover, tecnica ecienc in tis tpe o studies is dened taking te best mis in te

sampe as te bencmark. I te sampe is cross-countr, incuding countries wit better miingtecnoog, muc bigger inecienc ma be discovered. Tereore, more cross-countr researc ontecnoogica improvements on orestr covering te entire ie cce coud provide more vauabepoic directions.


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b. Efcienc Imprvemen veru oer Picie

Te resuts sow tat tecnica improvement in te sawmiing industr as a potentia roe topa in protecting natura orests in Sri lanka. however, to better appreciate its vaue, comparisonwit oter poic toos is needed. Suc an anasis soud answer te oowing questions (i)

how eective is te poic to acieve conservation objectives? (ii) how ong wi te poic taketo be eective?6 (iii) Is te poic measure poitica easibe? (iv) Does te poic acieve teconservation objective witout compromising economic ecienc? unatiake and unaratne (2002)

undertook suc a comparative anasis considering timber trade iberaization, and remova otimber permit sstem in comparison to tecnica ecienc improvement. Te oowing provides asummar o teir ndings.

Te eect o timber market iberaization on orest protection was anazed using a staticmarket simuation mode (see Weeraewa and unatiake 2007 or detais). lack o estimateddemand easticit or timber products in Sri lanka was a constraint in tis anasis. Te anasiswas undertaken wit pausibe assumption on price easticit. Remova o existing distortions suc

as tari, goods and service tax, deense ev, and oter border carges can cut down te oca

supp o sawn ogs signicant. Te supp woud be reduced due to te impact o sawn woodprices remova o a border carges reduce timber price b about 25%. Te decine in timber pricereduces te incentives or iega ogging and enances orest conservation in Sri lanka. Te price

reduction aso resuts in an increase in consumer surpus o about S$40 miion per ear. Timbertrade iberaization reduces oca supp b about 12% to 31% depending on te easticit o suppand demand. Timber market iberaization is a sort-run measure tat can eective reduce sawn

wood prices and consequent decrease te incentives or iega ogging. Aso, it wi reduce teoca sawn og supp and eective essen te pressure on natura orests. Simiar to te anasison te eimination o tecnica inecienc, te annua savings o equivaent natura orest wereestimated using pausibe assumptions. Wit te more conservative assumption o ineastic demand,

timber market iberaization can save about 6,985 ectares o orest annua. I te demand is

eastic, tese savings can increase up to 17,469 ectares per annum.Compared to te tecnica ecienc improvement, timber market iberaization seems to ave

a quicker eect on natura orests. As sown in te anasis, timber market iberaization improvesovera socia weare, and tus economic ecienc. enera, open market poicies benet certaingroups in te societ and adverse aect certain oter groups. In tis case, te consumers are

gainers and te producers are osers. One unique caracteristic o te current orestr sector in Srilanka is tat tere is no organized timber supp sector. Part o te timber is suppied rom omegardens and oter nonorest ands as a b-product. Te rest is iega extracted rom natura orests.Timber traders and government ocers, in bot cases, appropriate most o te rents. Tereore, te

actua producer surpus osses can be ver ow and tere are no true osers in te case o timbermarket iberaization. however, poitica easibiit o timber trade iberaization is moderate. More

important, depending on te orest management practices o te timber exporters, tis poic maead to destruction o orests esewere. In particuar, i te timber is exported rom an unsustainabe

source, tere woud be no conservation impact at te goba or regiona eve. Tis seems to be temajor drawback7 o te timber trade iberaization poic as a too or conservation.6 Tis requirement is unique in orestr because orestr cces are ong and te resuts o man poic canges are reaizedTis requirement is unique in orestr because orestr cces are ong and te resuts o man poic canges are reaized

ater 2040 ears depending on te orest species. or exampe, te eect o an incentive program or smaoder

tree growers wi be observed on ater 2040 ears.7 Timber certication sstem can be impemented to prevent deorestation in te exporting countr. however, costs andTimber certication sstem can be impemented to prevent deorestation in te exporting countr. however, costs and


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tablE 6summaryof policy altErnativEs

policy

EFFECt

EffEctivEnEss

political

fEasibility

Economic

EfficiEncyshortrun long runRemova o

permit sstem

low sawn wood

price

hig Moderate Economica

ecient

Incentives or

tree growing

Supp o ig-

quait ogs

No osers

Conducive business

environment ormiing

Incentives or

investment inmis

Tecnicaecienc

improvement

Moderate Moderate Tecnica ecienc

improvementmeasures

soud besubject tocostbenet

anasis

1) Investment

on maciner

Saw ogs

savings

Saw ogs savings

2) Supp o

quait ogs

Saw ogs

savings

Saw ogs savings

3) Mi evemeasures

Saw ogssavings

Saw ogs savings

Timber marketiberaization

low sawn woodprices

Potentiadeorestation in

exportingcountries

hig Moderate Economicaecient

Reduction ooca supp

No osers

Source Adapted rom unatiake and unaratne (2002).

As discussed in te background section, te existing timber permit sstem provides perverseincentives or conservation. It keeps timber prices iger and provides incentives or iega ogging.On te oter and, te vaue o timber is arge extracted b timber traders and government ocias

so tat tere are ard an incentives or smaoders to grow timber trees. Remova o te timberpermit sstem or tree species grown in private ands suc as jack, teak, and maogan wi reducetimber prices and consequent reduce incentives or iega ogging. In addition, it wi provide aconducive business environment or miing and ma promote investments in te sawmiing industr.

Tis measure wi aso provide incentives or te private sector and smaoders to grow timbertrees. Tus, it wi enance te ong-term supp o quait saw ogs, wic is necessar or tecnica

benets and existing institutiona capacit wi determine te success o te certication sstem.


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ecienc improvement. Tis poic wi be ig eective as sown b te case studies presented

in unatiake and unaratne (2002). however, its poitica easibiit is ranked ow because tebeneciaries o te existing sstem are poitica poweru. Te donor communit as been tringto impement tis poic or some ears witout success. Tis incident cear sows te strengt

o te groups backing te status quo. Because te unnecessar interventions are removed and temarket is aowed to pa its roe, tis poic is potentia economica ecient. Tere are notrue osers in tis case because current a sma group o timber traders and government ocersappropriate most o te rents in te timber sector.

Tecnica ecienc improvement wi ave bot sort- and ong-term eects. Repacing odwit new maciner is a measure tat can be taken in te sort term, subject to capita avaiabiit.ninterrupted supp o quait ogs is required to improve tecnica ecienc. Tis is, owever,

a ong-term measure tat can be acieved troug remova o restrictive reguations and provisiono necessar incentives. In addition, certain canges can be made at te mi eve to improveecienc. Tese measures incude converting te iring-tpe mis to miing businesses, providing

perormance-based incentives or mi managers, and making te mi managers aware o teir owntecnica ecienc eves and te possibe was to improve tecnica ecienc. Te eectivenesso improvement o tecnica ecienc is ranked as moderate because canging te determinantsto improve tecnica ecienc is not eas. Deveoping entrepreneuria abiit o mi managers or

provision o ow-interest oans to purcase new macines is not expected to generate oppositionrom societ, unike in te case o trade iberaization. Tereore, tecnica ecienc measures arepoitica more easibe in comparison to trade iberaization. Te eects o tecnica eciencimprovement on socia weare are not ver cear as most o te ecienc improvement interventions

incur costs. Tereore, te measures soud be subjected to costbenet anasis.

Since certain eects are reaized in te ong run, te above-described tree major poicmeasures soud be considered or simutaneous impementation. In apping a number o poic

measures, te adverse impact o one measure vis--vis te oters needs urter consideration. orexampe, timber market iberaization wi reduce oca timber supp and ma negative aect tesawmiing sector. Consequent, it ma negative aect certain restructuring required to improve

tecnica ecienc in te sawmiing industr. In te ace o decining oca production due tomarket iberaization, mi owners ma esitate to invest in new macines, etc.

VI. CoNClUDING CoMMENts

Poicmakers continue to ook or aternative poic instruments to conserve tropica naturaorests, since avaiabe instruments ave sown imited success. Tis stud examined te easibiit

o a new approac to orest conservation troug improvement o tecnica ecienc in sawmiing.Te paper iustrates te merits o tis approac based on sawmiing operations in Sri lanka.

Anases sow tat tere is considerabe inecienc in sawmiing in Sri lanka. Wit tecnica

ecienc improvements, te current sawn wood output can be produced wit 28% ess inputs.Conversion o te og input savings to natura orest area saved sows reasonab ig conservationimpacts.

Te ndings o te stud are, owever, preiminar in nature. Te stud anazes tecnicaecienc on at one stage in te ie cce o orest products, sawmiing. Moreover, tecnica


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cOncluding cOmments


ecienc in tis tpe o studies is dened b taking te best mis in te sampe as te bencmark.

I te sampe is cross-countr, muc bigger opportunities ma be ound or tecnica eciencimprovements. Suc improvements ma provide better aternative means or natura orest conservation.Tereore, more cross-countr researc on te eect o tecnoogica improvements on orestr

covering te entire ie cce o orest products is recommended. Tis wi strengten te basisor using tecnoogica improvement as a too or conservation o natura orests, and tereoredeserves te attention o poicmakers.


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APPENDIxDIstRIbUtIoN oF thE sAMPlE AND DEsCRIPtIVE stAtIstICs oF thE DAtA

appEndix tablE 1sampling framEwork

TotalSample

Size

=

200

climatic zonEs gEographical zonEs district

climatic

zonEs

numbEr

of

millErs

samplE

sizE

gEographical

zonEs

numbEr

of

millErs

samplE

sizE

district

numbEr

of

millErs

samplE

sizE

actual

samplE

WetZone

846 100

Nort

Wet Zonelowand

366 37

ampaa 209 16 14

egae 23 5 5

uruneagae 113 11 9

Matae 21 5 4

SoutWet Zone

lowand353 33

autara 117 11 10

ae 164 15 14

Matara 39 4 4

Ratnapura 33 3 3

pand 127 30

and 117 23 20

N. Eia 4 3 2

Badua 6 4 4

Dr Zone 203 50

Sout EasternDr Zone 110 29

hambantota 32 14 12

Moneragaa 4 2 2

Ampara 51 11 -

Batticaoa 23 2 -

CentraDr Zone 93 21

Anuradapura 13 11 9

Trincomaee 8 - -

Puttaam 72 10 10

higrban

198 50 Coombo 198 50 Coombo 198 50 47


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aPPendix


appEndix tablE 2dEscriptivE statisticsofthE variablEs

outputindEx indExinput EnErgy (kW)

mill capacity

(/month)

labor 1,

pErson-days/month

labor 2,

pErson-days/month

Mean 2832.761 4031.898 1581.446 3626.689 90.081 61.986

Median 1104.939 1806.832 1165 2875 88 44

Mode 2626.441 2427.381 1000 1500 88 44

StandardDeviation 6650.399 8814.211 1427.866 3838.604 53.047 35.653

Range 43771.11 60544.83 8820 29775 264 154

Minimum 2.8974 139.6878 180 225 22 22

Maximum 43774.01 60684.52 9000 30000 286 176

Count 148 148 148 148 148 148

appEndix tablE 3EstimatEd production functionforthE sawmilling industry

variablE coEfficiEnt standard Error t-ratio

Intercept 0.4988 0.2254 2.2135**

log input 1.0191 0.0259 39.4843**

Energ 0.0099 0.0289 0.3445

Capacit o te mi 0.0204 0.0208 0.9846nskied abor 0.0347 0.0323 1.0780

Skied abor 0.0473 0.0293 1.6142

** Signicant at 0.05 eve.


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P i d i h Phili i

abu e per

Herath Gunatilake examines the feasibility of technical efficiency improvement asan approach for forest conservation using a case study of saw milling in Sri Lanka.The paper shows that reduction of existing inefficiency helps prevent deforestation.Having compared the merits of this approach with other policy options, the paperasserts that technological improvements as a means of forest conservation deservethe attention of policymakers.

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ADB aims to improve the welfare of the people in the Asia and Pacific region,particularly the nearly 1.9 billion who live on less than $2 a day. Despite manysuccess stories, the region remains home to two thirds of the worlds poor. ADB isa multilateral development finance institution owned by 67 members, 48 from theregion and 19 from other parts of the globe. ADBs vision is a region free of poverty.Its mission is to help its developing member countries reduce poverty and improvetheir quality of life.

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Documents

Efficient Technology and the Conservation of Natural Forests: Evidence from Sri Lanka