Pertanika J. Soc. Sci. & Hum. 7(2): 91- 95 (1999) ISSN: 0128-7702© Universiti Putra Malaysia Press

Factors Influencing the Occurrence of Forest Offenses m aPeninsular Malaysia State

RUSLI MOHDDepartment ofForest Management

Faculty ofForestryUniversiti Putra Malaysia, 43400 UPM Serdang,

Selangor, Malaysia

Keywords: forest law enforcement, forest offenses, illegal logging, economics of crime

ABSTRAK

Satu kajian telah dibuat disalah sebuah negeri di Semenajung Malaysia untuk melihat tren danmengenalpasti faktor yang mempengaruhi kesalahan hutan yang berlaku untukjangkamasa daritahun 1981 hingga 1992. Data serta maklumat tentang kesalahan hutan, harga balak, keluasankawasan hutan, dan bilangan pegawai penguatkuasa telah dikumpul dari pelbagai sumbertermasuklah rekod serta laporan tahunan Jabatan Hutan Negeri berkenaan, dan buletinMASKAYU yang dikeluarkan oleh Lembaga Industri Perkayuan Malaysia. Analisis korelasi danregressi telah dilakukan untuk melihat kaitan diantara kesalahan hutan dengan harga balak,bilangan pegawai penguatkuasa dan keluasan kawasan hutan. Jumlah kesalahan hutan di negerikoJian menunjukkan tren yang menurun. Pembalakan haram yang merupakan satu darikesalahan hutan membentuk peratusan yang tinggi pada setiap tahun dalam jangkamasa kajian.Dari tiga faktor yang dikaji, cuma harga balak sahaja mempunyai korelasi yang bermaknaterhadap kesalahan hutan. Harga balak berkadar songsang dengan bilangan kesalahan hutan.Model regresi yang terbentuk yang mengkaitkan kesalahan hutan dengan harga balak adalah:

Bil. kesalahan hutan = 393.94 - 0.53 harga balak (p = 0.02)Bilangan pembalakan haram = 264.69 - 0.37 harga balak (p = 0.03)

Kajian yang lebih terperinci perlu dijalankan dimasa akan datang untuk memahami dengan lebihlanjut faktor lain, seperti denda, yang mempengaruhi kesalahan hutan.

ABSTRACT

A study was conducted in one of the states of Peninsular Malaysia to observe the trends andidentity factors associated with the occurrence of forest offenses during the period from 1981 to1992. Data and information on forest offenses, price of logs, size of forest areas, and number ofenforcement officers were collected from various sources including the records and annualreports of the State Forestry Department, and MASKAYU bulletin published by the MalaysianTimber Industry Board. Correlation and regression analyses were carried out to determine therelationships between forest offenses and price of logs, size of forest area and number ofenforcement officers. The number of forest offenses in the state shows a decreasing trend. Illegallogging which is a form of forest offense constitutes the highest percentage in all the years duringthe study period. Of the three factors investigated, only the price of logs correlated significantlywith forest offenses. The price of logs is inversely correlated with forest offenses. The regressionmodels developed show the relationships between the number of offenses and the price of logsas follows:

For number of forest offenses p = 0.02 andFor number of illegal logging cases p = 0.03

Further studies should be conducted to better understand other factors like penalties thatinfluence forest offenses.

Rusli Mohd

INTRODUCTION

The government of Malaysia, like many otherproducers of tropical wood products, has pledgedits commitment to manage the forests in asustainable manner, in line with the InternationalTropical Timber Organization (ITTO) year 2000objective which states that all wood productstraded in international market must be producedfrom sustainably managed forests. A number ofstrategies and programmes have beenimplemented by the government, including theestablishment of National Timber CertificationCouncil as well as the formulation and testing ofMalaysia's criteria and indicators (MC&I) forsustainable forest management. Recently, fundscollected through timber export cess amountingto more than RM 350 million have been allocatedby the government to finance forest developmentand research projects in an effort to speed upthe attainment of the sustainable forestmanagement objective.

While commendable efforts are ongoing insome aspects, the government should alsoexamine other important aspects of forest policyto make sure that they complement one another.One of these aspects is related to forest lawenforcement. Forest law enforcement is a criticalaspect of forest management because it regulatesthe relationship between many parties,particularly timber companies, with the forestresource. Illegal and uncontrolled harvestingactivities, for example, may cause irreparabledamage to the forest which subsequentlyinfluences its long-term productivity andsustainability. Generally, forest authority shouldtry to keep forest offenses to a minimum level,particularly those that cause great harm to theforest and the environment.

In spite of the fact that forest offenses poseobstacles to sustainable forest management, littlehas been studied about them. Little, if any, hasbeen published on the extent of the problem aswell as factors influencing their occurrence. Thispaper highlights the trends in the occurrence offorest offenses in one state of Peninsular Malaysiaand identifies factors associated with theiroccurrence. These offenses are only thoseprovided for in the National Forestl1' Act, 1984.No attempt is made to look at the nature ofthese offenses under the general law of crime,namely the Penal Code.

Factors Influencing Forest Offences

Forest offenses can be defined as the conduct ofany activity, or its omission, which is illegalunder the existing forest law of the countI-y.The main piece of legislation governing theconduct of such activities in Peninsular Malaysiais the National Forestry Act, 1984 and itsamendments of 1993. Forest offenses arecriminal acts because they violate the law of thestate and the person committing them are liableto legal punishment. According to Curzon(1979), crime is "an unlawful act or defaultwhich is an offense against the public and rendersthe person guilty of the act liable to legalpunishment." Forest offenses have impact onthe State which, in turn, has the responsibility tobring the guilty person to justice. Theories onthe economics of crime, therefore should shedlight on factors which influence the occurrenceof forest offenses.

The body of literature on the economics ofcrime focuses on two main issues. The first issueis on individualis decision about criminal activitywhile the second is on criminal justice policy(Hirsch 1979). The concern of the first issue ison the factors that influence an individualisdecision whether or not he or she commits acrime. Studies done on this first issue try todevelop the supply function for crimes or alsoknown as the deterrence function. The objectof studies on the second issue, on the otherhand, is to determine the optimal probability ofpunishment and the optimal type and severity ofpunishment. Such studies entail, among otherthings, the determination of the loss to societyas a result of crimes.

Economists argue that criminals are rationalindividuals who respond in a natural way to theincentives provided by the environment in whichthey operate. Rational individuals balance thecosts and benefits of their possible actions andallocate their time to legal and illegal activitiesaccordingly. These individuals will take an actionif the benefits obtained outweigh the costs.Following such argument, rational individualswould commit crimes if the expected benefitsgained outweigh the expected costs incurred.

What are the benefits and costs associatedwith committing a crime? The benefit that theindividual stands to gain as a result of crime canbe measured by establishing the amount that

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Factors Influencing Forest Offenses in a Malaysian State

Punishment XProbability of ArrestX Probability ofConviction

the offender, in a market-like setting, wouldhave to be offered in order to pursuade himagainst committing the crime. Inferences aboutthese benefits can be made by measuring theextent of change in the volume of crimes thatresult from a given change in costs.

The expected costs (or expectedpunishment) to the individual comprise of severalparts. These are the size of punishment,probability of arrest and probability of conviction.Expected punishment is given by the followingformula (Reynolds 1996):

Expectedpunishment (E.P.)

where:punishment =jail sentenceprobability of arrest = number of arrests/total number of offensesprobability of conviction = number ofconvictions/number of arrests

The discussions on benefits and costs ofcommitting crimes presented above can suggestfactors that influence forest offenses. Thebenefits that an offender stands to gain fromcommitting forest offenses should be related tothe revenue that he expects to obtain from thesale or processing of stolen logs. Therefore, thesale price of logs should influence the occurrenceof forest offenses. It is expected that the higherthe price of logs the higher will be the occurrenceof forest offenses, if other factors remainconstant.

Costs associated with forest offenses arerelated to the chances that an offender will beapprehended and later convicted and the penaltythat he pays if he is convicted. The number ofenforcement officers and the size of forest areasshould influence the chances of arrest and,hence, the occurrence of forest offenses. Themore the enforcement officers, the greater thelikelihood for inspection activities to be carriedout, and therefore, the higher probability ofarrest. Consequently, the more the enforcementofficers, the lesser the chances of forest offensesoccurring. Therefore, it is expected that thenumber of enforcement officers is inverselyrelated with forest offenses.

The size of forest area should also influencethe probability of arrest. The bigger the forestarea, the more time needed for inspection and

patrol, and the lower will be the chances fordetection of forest offenses. Therefore, the sizeof forest area should be inversely related withthe occurrence of forest offenses. In this study,the number of forest offenses will be correlatedwith the sale price of logs, the size of forest areaand number of enforcement officers in the stateforestry department.

METHODThis study was conducted in one of the states inPeninsular Malaysia and it was chosen for reasonof convenience. The total forest area of thestate is about 260,000 ha. and this representsabout 23 percent of the total land area of thestate. Income from forestry activities, particularlylogging, contributes significantly to the state'seconomy. For the purpose of administration,the state is divided into three forest districts.

Two categories of data were collected forthe study. The first category is related to theoccurrence of forest offenses in the state whilethe second is on factors that are predicted toinfluence these offenses. For the first category,data on the number and types of forest offensesfor each year during the 1981 to 1992 periodwere gathered from the records kept by theState Forestry Department. Data on log pricesdelivered at mill gate, number of enforcementofficers in the state and size of productive forestsbelong to the second category and these werecollected from various sources including therecords kept by the Malaysian Timber IndustryBoard and the State Forestry Department itself.

For purposes of analysis, forest offenses weredivided into six categories based on the provisionsof the National Forestry Act, 1984. Thesecategories were: a) illegal cutting and removingof forest produce from a permanent reserveforest or state land, b) illegal searching,collecting, removing, or manufacturing of anynon-wood forest produce, c) illegal clearing forpurpose of cultivation, d) trespassing, e) illegalpossession of forest produce for conversion, andf) violating license conditions. Graphical analysiswill be done in order to observe the trends inthe occurrence of the various offenses over thestudy period.

Models will be developed to relate theoccurrence of forest offenses with log prices,number of enforcement officers and size offorest area by means of linear regression whichcan be mathematically expressed as:

PertanikaJ. Soc. Sci. & Hum. Vol. 7 No. 21999 93

Rusli Mohd

price of logsnumber of officerssize of forest area

Offenses = a + I3lL + 132F + 133

AWhere:

p =L

FA =

every year are illegal logging cases. This confirmsclaims often made that illegal logging occurswidely in the states, including in the State beingstudied.

(0.03)

TABLE 2Correlation between total number of offences

per year and type A offenses per year withindependent variables

DISCUSSION AND CONCLUSIONForest offenses, particularly illegal logging, willhinder the attainment of sustainable forestmanagement in this country. Widespread

Factors Correlated with Occurrence of Forest Offense

Results of correlation analysis between thenumber of offenses and type A offenses with theindependent variables are shown in Table 2.0.

r = 0.0571P = 0.86

r = 0.1492P = 0.644

r = 0.2345P = 0.46

r = 0.1909P = 0.552

r = - 0.6456P = 0.02*

r = - 0.6209P = 0.03*

* significant at 5 percent level

As can be seen from the table, only logprice correlated significantly with the number ofoffenses. Both the total number of offenses andtype A offenses are inversely correlated with logprice which means that there will be fewer ofthese offenses in times when the price for logs ishigh than when the price is low.

Subsequent analysis results in the followingsimple regression models relating forest offenseswith log price:

Number of offenses = 393.94 - 0.53 log price(0.02)

Number of type A offenses = 264.69 - 0.37log price

The models developed show that for every unitincrease in log price, there is a correspondingdecrease in about half unit of all types of offenses.Similarly, when the price of logs increases by aunit, the number of type A offenses decreases byabout 0.4 unit.

Type Aoffences

Offense Independent variables

Log price Number of Total area(RM/cu.um) officers of

productionforest

Alloffences

Data in the table show that forest offensesin the State are on a declining trend. Thenumber of offenses was highest in 1981, graduallydecreases from then on until 1988, increasesslightly in 1989 before leveling off in early 1990's.The median number of offenses per year is 69which means that one offense in every four tofive days. Information contained in columnthree of the table indicate that, on the average,almost two offenses occurred for every 10,000cU.m of logs harvested or one offense per 5000cu.m of log produced.

It is also shown that in almost every year,offenses that can be classified as "illegal logging"constitute the biggest proportion of all thecategories of offenses. On the average, nearly74 percent of all the offenses that occurred

median = 69 median = 0.17 median = 74

TABLE 1Occurance of forest offenses, 1981-1992

Year Total No. of % of categorynumber of offenses/1000 a offences

offences cU.m of log (i.e. illegalproduction logging)

1981 150 0.44 751982 129 0.39 711983 91 0.15 881984 84 0.28 731985 80 0.28 831986 68 0.23 701987 47 0.18 481988 47 0.10 891989 70 0.16 671990 31 0.06 901991 31 0.09 801992 45 0.17 73

RESULTS

Occurrence ofForest Offenses

Table 1.0 provides information on the occurrenceof forest offenses in the State during the studyperiod. It gives the actual number of offenses,the number of offenses per 1000 cU.m of woodproduction and the percentage of category Aoffenses.

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Factors Influencing Forest Offenses in a Malaysian State

occurrence of these offenses means that theeffective size of productive forest areas isdecreased and this can upset the planning forsustainable harvest. In addition, a large sum ofmoney in the form of premium is not collectedby the government when the forest areas areillegally logged. Such money could have beeninvested in development projects that wouldenhance the productivity and, subsequently, thesustainability of the forest. Due to these reasons,the authority concerned should regularly inspectlogging activities to ensure that the loggers abideby the rules and regulations stipulated for them.

The results presented in the earlier part ofthis paper should be much awaited by theauthority. In terms of number of offenses, atleast, the trend is declining. However, numberof offenses alone do not truly reflect theseriousness of the problem. There can be fewincidence of illegal logging activities but theamount of logs removed or the areas cut in eachof the incidence can be huge. The state forestauthority, therefore, should not be complacentin its enforcement activities once they found outthat the number of offenses is declining over theyears. It should be a cause for concern in thestate being studied as it was shown that illegallogging cases constitute a big proportion of thetotal number of offenses in the state.

The results of regression analysis do notsupport the hypotheses made earlier on therelationships between number of offenses andlog price, size of forest area and number ofenforcement officers. It was expected that forestoffenses would increase with increase in logprice, and that it would decrease with decreasein forest area and increase in enforcementofficers. However, only log price was correlatedsignificantly with number of offenses. It wasfound that the higher the log price the lowerwill be the number of offenses. This resultshows that loggers will not be motivated to stealmore logs when the price of logs increases. Itcan be argued that an increase in log pricealready provides enough incentives for theloggers to cut their own forest concession areas.There is no necessity to log other areas in orderto obtain a comparable margin of profit.

AE far as inspection activities are concerned,the [mdings indicate that these should be carriedmore often in times when the prices of logs arelow than in times when the prices of logs arehigh. Inspection activities should be planned

taking into consideration the projections madefor log prices. The authority should monitorthe development in log prices and planinspection activities accordingly.

The above findings, however, should betreated as very preliminary and more studiesshould be carried out in other states to confirmthem. Future studies may want to use a moredisaggregated data for log price, for example,price for different groups of commercial species.Such studies should also try to determine theprobability of arrests and probability of convictionfor forest offenses and, consequently, analysetheir influence on these offenses. More detaildata will have to be collected for such studies.The ultimate aim of such studies is to find outwhether or not increasing penalties deter theoccurrence of forest offenses.

In conclusion, achieving sustainable forestmanagement requires congruent and balancedefforts in many facets of forest policy. Thegovernment should not only focus on certainprogrammes or projects to enhance theproductivity and sustainability of the forests butignore other aspects which may be equallyimportant in achieving sustainable forestmanagement. One important facet of forestpolicy is its enforcement. Lack of enforcementcan lead to widespread occurrence of illegalactivities. The occurrence of forest offenses,such as illegal logging and encroachment, cansignificantly hinder the attainment of sustainableforest management. AE little is known on theoccurrence of forest offenses in this country,more research should be carried out in thefuture. Comprehensive research programmescan lead to the formulation of improvedstrategies to control the occurrence of forestoffenses.

REFERENCES

CURZON, L.B. 1989. Dictionary ofLaw. Third Edition.Kuala Lumpur: International Law BookServices.

HIRSCH, Z.H. 1979. Law and Economics: An IntroductoryAnalysis. New York: Academic Press.

REYNOLDS, M.O. 1996. Crime and Punishment inTexas: Update. National Centerfor Public AnalysisPolicy Report No. 202.

(Received: 23 February 1999)

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