




































African Journal of Environmental Economics and Management Vol. 1 (5), pp. 153-166, December, 
2013. Available online at www.internationalscholarsjournals.org © International Scholars Journals 

 

 

Full Length Research Paper 
 

Market and welfare economic impacts of sustainable 
forest management practices: An empirical analysis 

of timber market in Peninsular Malaysia 
 

AS Abdul-Rahim
1
*, HO Mohd-Shahwahid

1
, S. Mad-Nasir

2
 and AG Awang-Noor

3
 

 
1
Faculty of Economics and Management, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia. 

2
Faculty of Agriculture, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia.  
3
Faculty of Forestry, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia. 

 
Accepted 13 April, 2013 

 
The main objective of this study is to analyze the impact of sustainable forest management (SFM) 
practices on the timber market in Peninsular Malaysia. A partial equilibrium model was applied in this 
study covering domestic timber market namely supply and domestic demand of timber. It was analyzed 
by using a system of equations approach. All data were compiled from published sources of Malaysian 
Government publications namely from the Department of Statistics and Annual Report of the Forestry 
Department of Peninsular Malaysia. All of the data are annual time series basis from 1970 to 2008. 
Impact analysis was conducted based on three scenarios that arise from SFM practices (that is (1) 
reduced by 24% in harvested area, (2) increased by 74% in external cost of timber harvesting and (3) 
increased by 47% in the cost of internalization the externalities). These scenarios will be incorporated in 
the timber market model. Results show that changing from the conventional logging (CL) practices to 
SFM practices reduce the equilibrium quantity of timber and increase the price level. The welfare 
economic impacts of SFM provide empirical evidence that there is a loss in welfare economic impacts 
on the timber industry in Peninsular Malaysia. However, an increase in the domestic price of timber 
would help to compensate for the loss volume of timber. The state government and any related 
agencies should be able to use these results as a reference to come out with good mechanisms in 
strengthening the effectiveness of SFM policy. Hence, they should be able to assist domestic timber 
industry by supporting them to fetch various potential incentives such as price premium, carbon credit 
and market access for timber produced from sustainably managed forest. 

 
Key words: Consumer surplus, producer surplus, equilibrium price, equilibrium quantity. 

 
 
INTRODUCTION 
 
According to Kumari (1995), when we are discussing 
about sustainable forest management (SFM), it should 
cover all mechanisms of allocation and not focused on 
market only. However, there are many situations and 
resources which are not and cannot be allocated by 
market mechanism. For example, many cultures, inclu-
ding indigenous people, use non-market mechanism for 
resource allocation. This does not mean that their 
resource allocation is not at optimal level. Similarly, with 

 
 
 

 
regards to carbon sequestration, nationally or globally 
would enjoy the benefit of clear atmosphere received 
from the carbon storage which cannot traded in the 
market. However, nowadays, there is a term known as 
carbon credit created by economists assigning values on 
carbon for trading in the market.  

In Malaysia, Kumari (1995, 1996) conducted a study of 
total economics valuation (TEV) approach in the context 
of conventional logging (CL) and SFM practices. The 

 
*Corresponding author. E-mail: abrahim@econ.upm.edu.my. Tel: +6019-2090970.  Fax: +603-89486188.  



Abdul-Rahim  et al.              153 
 
 
 

Table 1. Forest of goods and services valuation under CL and SFM practices. 
 

 
Goods/Services 

Method/variable 
Location 

Value estimated (RM/ha) 
Source  

 

analysis CL SFM  

    
 

 Total social benefitsa TEV Malaysia 627 1,118  
 

 Total global benefitsb TEV Peninsular Malaysia 8,389 9,146 Kumari, 1996 
 

 Carbon Storage TEV Peninsular Malaysia 8,049 8,677  
 

 Water Cost of water treatment Peninsular Malaysia 704 1,477 Mohd Shahwahid et al., 1999 
 

 Timber and non-timber Cost-benefit (NPV) Sarawak 9100 9905 Dagang et al., 2005 
 

 Watershed protection NPV Peninsular Malaysia 1,019 1,060 Mohd Rusli, 2002 
 

 Forested catchment NPV Peninsular Malaysia 1,006.1 740.7 Mohd Rusli, 2002 
  

a
Hydrological, rattan, bamboo, recreation, domestic water and fish; 

b
Endanger species and carbon stock. 

 

 
TEV involves use value, non-use value, direct use value, 
indirect use value, option value, existence value and 
quasi-option value. In general, Editorial (2007) mentioned 
that the concept of SFM in the context of economics is 
the study of the socially optimal allocation of scarce 
resources. This means the economics study is not limited 
to the study of markets, marketed resources, market 
signals of scarcity, and market mechanisms of resource 
allocation but it also includes the study of all resources, 
marketed and non-marketed; all categories (Aboriginal, 
ecological, environmental, legal, social and market) of 
resource scarcity signals; all mechanisms, including 
market, social, legal, and political, of resource allocation; 
and intra and inter-generational equity as part of social 
optimality.  

Table 1 indicates several goods and services with res-
pect to the economic value estimated from the two types 
of forest management practices namely conventional 
logging (CL) and reduced impact logging (RIL) practices 
where RIL is also represent the implementation of SFM 
practices. Both CL and RIL deal with the impacts of the 
forest management practices on goods and service of the 
forest multiple functions through economic analysis. 
Economic analysis is referring to the social effects or 
externality effects that might occurred due to timber 
harvesting operations. For example, some of these 
include hydrological, rattan, bamboo, recreation, dome-
stic water, fish, endanger species and carbon storage. 
The full valuation of forest goods and services would yield 
surpluses for countries to invest in and achieve SFM. 
 

Owing to the externality effects, SFM policy is in favor 
to provide greater positive externality effects compared to 
CL practices. For example, in Table 1, Kumari (1996) 
found that at national benefit, the total social benefits 
under CL and SFM are RM627/ha and RM1,118/ha 
respectively. This has also increased the global benefits 
from RM8,389/ha to RM9,146/ha under CL and SFM 
respectively. In addition, Mohd Shahwahid et al. (1999) 
revealed that the cost of treating the water is lower under 
SFM practices with less externality effects.  

This  study will  not  only  analyze  the  determinant  of 

 

 
Peninsular Malaysia timber market, but also internalise 
the externality effects in the systems analysis. For 
example, to minimizing the externality effects from timber 
harvesting operations, the additional activities and 
procurement are really needed. This will lead to increase 
in the operational cost. A study by Abdul Rahim et al. 
(2009b) revealed that the operational cost has increased 
by 47% due to additional activities that may minimise the 
externality effects. In addition, the incremental cost of 
treating water due to timber harvesting will also incur-
porate in this analysis. This is because it could consider 
as externality effects as the third party namely water 
treatment plant has to bear higher cost in treating the 
water resulting from timber harvesting. One recent study 
by Abdul-Rahim and Mohd-Shahwahid (2010) showed 
that the cost of water treatment has increased by 74% 
due to timber harvesting activities. This is crucial issues 
need to be analyze and discuss because if there is a 
significant distortion in the market, government inter-
vention is one of the solution to easy the problem.  

To make it clear, timber market in this study is also 
known as log market. Most of previous studies on timber 
market analysis typically deal with the prices, supply and 
demand in domestic and international market. However, 
to the best of authors’ knowledge, none of the study 
analyzes timber market that internalizes the value of price 
and quantity as the value that already incorporated the 
externality effects. For example, a current domestic 
timber prices in Peninsular Malaysia is just determined by 
the market driven. It is expected that by internalizing the 
externalities, the price is potentially higher than the 
current prices. Hence, government intervention is really 
needed to correct the distortion. In this context, this 
present study will provide some output of analysis that 
could be used by the government for policy decision 
making. Therefore, the optimum level of output and price 
at externality level will be quantified because the net 
benefit is maximized when it takes into account the 
negative externality effects as well (Tietenberg, 2003).  

In a view of Malaysian case, Malaysian Government 
has given its priority to manage the forest with sustain-
able manner which refer to SFM practices. In recognition 



154       Afr. J. Environ. Econ. Manage. 
 
 

 
to the need of strengthening SFM, Malaysia has under-
taken a critical step to reduce the annual coupe or AAC in 
the country (Woon and Tong, 2004). Consequently, the 
AAC has been reduced from 52,250 ha per annum for 
Peninsular Malaysia during the Sixth Malaysia Plan (1991 
to 1995) to 46,040 ha per annum during the Seventh 
Malaysia Plan (1995 to 2000). This reduction continues 
during the Eight Malaysia Plan (2001 to 2005) and Ninth 
Malaysia Plan (2006 to 2010) to 42,870 ha and 36,940 ha 
respectively. Looking at the actual number of timber that 
has been extracted, it is shown that the total volume of 
timber extracted is lower than the AAC approved during 
Eight Malaysia Plan at 37,326 ha instead of 42,870 ha. 
Furthermore, on the marketing front, the supply of 
Malaysian timber has been declining; mainly due to the 
Malaysian commitment to SFM practices (Jamal and 
Mohd Shahwahid, 1996; Tan et al., 2003).  

This planned reduction in logging rate helps to ensure 
the extraction of forest resource is in line with the 
sustainable capacity of the forests. A downward trend in 
available supply which referred to AAC has put 
considerable pressures to the local production of timber 
as well as other wood products. As mentioned by Lim et 
al. (2002), the declined in timber production was mainly 
due to the reduction of annual coupes resulting from the  
Rio Convention and Malaysia’s need to achieve ITTO 
objectives 2000 and international certification standard in 
attaining SFM. Therefore, if all of these conditions are 
followed successfully, it would further reduce the supply 
for domestic consumption. It will be even more worrying, 
when the accessible forestland in Malaysia is slowly 
given a way to agriculture especially in oil palm, new 
satellite towns and other forms of land use, creating a 
conflict between agriculture production and forest 
management (Ahmad Fauzi, 2005).  

Beside the AAC has been reduced, the stringent criteria 
of SFM on harvesting operation has affected the timber 
volume that can be extracted from forests. Consequently, 
Malaysian timber supply has been continuously 
diminished. For example, timber production from 
Peninsular Malaysia natural forests has been decreasing 
steadily. According to Forestry Department of Peninsular 
Malaysia (2008), the statistic shows that timber 

production decreased from 12.8 million m
3
 in 1990 to 4.0 

million m
3
 in 2008.  

Most of the studies conducted either locally or abroad 
revealed that there is incremental cost in operating SFM 
other than the reduction in timber production 
(Schwarzbauer and Rametsteiner, 2001; Ahmad Fauzi et 
al., 2002; Linden and Uusivuori, 2002; Woon and Tong, 
2004; Abdul Rahim and Mohd Shahwahid, 2009a). All of 
these possible changes are directly related on harvesting 
regulations and additional guidelines on timber harvesting 
activities. Hence, this will reduce the volume of timber 
which can be extracted from forest as well as incurred 
higher cost. In other words, in the short run, it may reduce 
potential harvesting volumes and producers may 

 

  
 
 
 
have to bear higher cost in implementing SFM. However, 
in the long run, this may support a sustainable level of 
production that will exceed of what would be possible in 
later years if environmentally harvesting systems were to 
be continued (Thang, 2007). Beside the issues of 
operation cost and timber production, several other 
elements in SFM that potentially give direct impact to the 
timber market are also identified; such as price premium 
and market access. With regard to the economic reasons, 
timber producers must acknowledge that there are some 
economic advantages to participate in SFM.  

With the above issues rose relating to the Malaysian 
timber industry, it is paramount that the market is to be 
understood in term of the relationship of its major 
parameters. It has become essential to know the various 
impacts of SFM practices on timber market in Peninsular 
Malaysia. This is where we have to come out with several 
scenarios of SFM practices and carry out simulations 
analysis for examining the market and welfare economic 
impacts. 

 
METHODOLOGY AND DATA 
 
While there are different issues in forest sector policies analysis, the 
analytical framework is quite similar. The common approach is to 
develop a forest sector model and to simulate the impacts of the 
policy on the timber and product markets for domestic or 
international markets. A typical model building involves the 
estimation of output consumption, price and trade of the timber 
products. The impacts of the policies were evaluated by comparing 
the simulated results for with and without policy scenarios.  

Studies on forest related policies such as Kallio et al. (1986), 
Menurung (1995), Schwarzbauer and Rametsteiner (2001), Barbier 
et al. (1995), Ismariah (2001), Mohd Shahwahid (1993, 1995), Mad 
Nasir and Mohd Shawahid (1995) and Ahmad Fauzi (2005) have 
used such framework. A review on their analytical framework is 
useful, as this study will address most likely similar policy questions 
relating to certain policy approach. However, this paper differs as it 
takes into account the SFM policy by incorporating with several 
scenarios of SFM practices namely (1) reduced by 24% in 
harvested area, (2) increased by 74% in external cost of timber 
harvesting and (3) increased by 47% in the cost of internalization 
the externalities. In other words, the current input cost of timber 
harvesting operation has to incorporate together with the cost that is 
related to the externalities. This is where most of the prior studies 
have ignored the externality effects in their econometric modeling. 

 
Overview of the model structure 
 
The underlying objectives of this study as discussed earlier focused 
on the internalization of externality effects on the analysis of timber 
market in Peninsular Malaysia. Figure 1, illustrates the flow of the 
economic impact analysis with respect to the objectives of study 
and the analysis approach. In this study, there are two major steps 
of impact analysis. The first step is to estimate the Peninsular 
Malaysia timber market model. The second step is to analyze the 
market and welfare economic impacts by incorporating several 
scenarios under SFM practices. In sum, both analyses are 
important to investigate the impact of the implementation of SFM 
practices on the timber industry.  

The logic of the economic analysis is rather simple. If the forested 
area is manage according to the SFM practices, it will 



Abdul-Rahim  et al.              155 
 
 

 
Economic impact analysis 

 
 

 
Market effects Welfare effects  

  

 
 

 
Incorporating with several scenarios under SFM; 

 
1. Reduction in harvested area  
2. Incremental cost of internalization the externalities  
3. External cost of timber harvesting (externalities)  
4. Market access  

 

 
System of equations  

Approach 
 

 
Simulation analysis 

 
      

 

 Baseline scenario   SFM scenario   

    

      
 

       

 
Figure 1. Economic impact analysis schematic diagram. 

 
 
 
 

 Harvesting from natural forest   

  Timber   

 Total timber Supply   

Domestic industrial Domestic Export International industrial  
needs demand demand needs from less forest  

   endowed countries  

     
     

 
Figure 2. Schematic diagram of timber supply. 

 
 
 
 
affect several economic elements such as harvested area, 
operational costs, price and market. Changes in these elements 
influence the economics of timber supply and demand. The model 
analyzes the impact of these shifts in timber supply and demand on 
key variable such as the production and consumption of timber 
market. Several impacts under SFM scenarios are simulated by 
linking them into Peninsular Malaysia timber market model. 

 
Peninsular Malaysia timber market model 
 
This study adopted and modified  the  model  developed  by  Kumar 

 
 
 
 
(1981, 1983), Kinus (1992), Mohd Shahwahid (1993, 1995), Mad 

Nasir and Mohd Shahwahid (1995), Ismariah (2002), Ahmad Fauzi 
(2005) and Abdul Rahim and Mohd Shahwahid (2009a). Timber 
that comes from natural forests will be analyzed in this study.  

The schematic diagram (Figure 2) not only shows the flow of 
production of timber but also insist on developing the model. There 
are timber supply, domestic demand and export demand in the 
diagram.  

However, import demand export demand was not considered in 
this study. This is because Malaysia is not fully relying on imported 
timber particularly for Peninsular Malaysia and its export of timber 
has been banned since 1990s. The detailed justifications will be 



156       Afr. J. Environ. Econ. Manage. 
 
 

 
explained in the next section. 

 
Supply of timber from natural forest 
 
The timber supply from natural forest is given by the equation: 
 

lnTS t = 0 + 1 lnP t + 2 lnAH t + 3 lnIC t + 4 lnTS t 1  + t  (1) 
 

where: 
 

TS t = Supply of natural forest timber 
 

P t = Price of timber 
 

AH t = Harvested area in natural forest 
 

IC t = Total salaries and wages paid in logging industry 
 

TS
 t 1 = Lag supply of timber supply by one year 

 

t  = Years 
 

 t = Error term 
 

   

ln  = natural logarithm 
 

 
Equation 1 estimates the total supply of timber from natural forest, 
which should be positively related to the natural forest timber prices 
and harvested area in natural forest. TSt is the supply of natural 
forest timber as endogenous or dependent variable; Pt is the price 
of natural forest timber, which is an important variable in 
determining the quantity of natural forest timber supply; AHt is the 
natural forested area open for harvesting; ICt is total salaries and 
wages paid in logging industry represents to the production cost;  
TS t 1 is previous year natural forest timber supply, which have 

influenced the natural forest timber supply. 

 
Incorporation the cost of internalization the externalities and 
external cost 
 
Input  cost  under  the  scenario  of  SFM  =  input  cost  +  cost  of  
Internalization the externalities (2) 
 
Input cost under the scenario of SFM = input cost + external cost of  
timber harvesting (3) 
 
Equations 2 and 3 explain the situation where the timber market 
model is incorporated with the cost of internalization the 
externalities and external cost. Incorporation those elements are 
crucial, otherwise it can lead to market failure. Market failure 
associated with the externality effects resulting from timber 
harvesting activities in forest. Without taking into account the 
externality effects, the timber production from natural forest could 
be considered as being managed without sustainably produced. In 
other words, it cannot achieve the optimum level of quantity and 
price of timber. Most of previous studies especially studies using 
econometric modeling had ignored the external cost in their 
research. Therefore, this study tries to incorporate with that element 
so that the research outcome could represent the optimal level 
estimation of quantity and price in timber market. 

 
Demand of timber from timber processing mills  

lnDD 
*
t =  0 +  1 lnP t +  2 lnIPI t +  3 lnWMP t + 4   lnDD t 1 

+ t (4) 

 

    
 

where;  
 

DD 
*

t = Domestic demand for timber  
 

P t = Domestic price for timber  
 

IPI t = Industrial production index  
 

WMP t = World import price of timber  
 

DD t 1  = Lag of domestic demand for timber for by one year  
 

t  = Years  
 

    

 t = Error term  
 

    

ln  = natural logarithm  
 

 
Equation 4 describes the estimated total domestic demand for 
timber from natural forests. It suggests that the lower the price offer, 
the higher the volume of forest timber demanded domestically. On 
the other hand, the higher world import price of timbers would 
encourage further consumption of domestic timbers. Similarly, the 
higher industrial production index (IPI) would promote timber 
processing mills (that is sawmills, plywood and veneer mills) to 
demand more domestic timbers.  

Instead of using Malaysian income, IPI will be used in this study 
because the timber demand is considered as intermediate goods. 
IPI is also used to measure the economic growth of the timber-
based manufacturing industries and it should therefore be positively 
related to the timber demand. When there is a growth in timber 
processing mills, demand for timbers would rise but domestic 
demand would have to compete with other substitute such import of 
timber. Hence, we used world import price of timber (WMP) which 
represents substitute good. It suggests that the higher the WMP,  
the higher the volume of domestic demand of timbers. lnDD 

*
t is the 

dependent variable for domestic demand for timber, which is 

influenced by the domestic price of timber (P t ), industrial 
 
production index (IPI t ), world import price of timber (WMP t ) and 

the previous year’s domestic demand of timber (DD t 1 ). 
 
 
Closing identities (total supply of timber) 
 
The above timber market model has two main equations. To close 
the system, an identity equating timber availability with domestic 
demand of forest timbers is postulated as follows: 
 
TSt=DDt (5) 
 
To analyze the timber market model, this study estimates timber 
supply and demand for domestic market. Then, re-estimate the 
supply and demand simultaneously followed by simulation analysis 
of several scenarios under the SFM practices. The domestic supply 
and domestic demand equations will be estimated by system of 
equations approach.  

From Equation 5, a partial equilibrium of quantity and price of 
timber can be generated.  
The details calculation can be seen in Appendix A. In addition, the 
producer and consumer’s surplus that represents welfare economic 
impacts are also being quantified. 

 
Welfare economic impact analysis 
 
The  effects on the timber sector from several scenarios under SFM 



Abdul-Rahim  et al.              157 
 
 

 
Price 

 
P2  S1 

  S0 

C   
P1   

  B 
P   

E   

F   

0  D0 
Q1 Q Quantity 

 
Figure 3. Change in consumer and producer surplus from shift of 
timber supply in domestic market. 

 
 

 
practices namely reduction in harvested area, incremental cost of 
internalization the externalities and external cost of timber 
harvesting operations can be explained by the changes in the 
aggregate consumer and producer’s surplus. Consider the timber 
market in Figure 3, the market demand curve for timber is simply 
the horizontal summation (that is, summation n along the quantity 
axis) of the demand curves of each individual timber processing 
mills (sawmills, veneer and plywood mills).  

The aggregate price value of a given quantity of timber will be 
equal to the area under the market demand curve and the height of 
the market demand curve is equal to the price value of each unit of 
timber. For example, the total value of Q units of timber is equal the 
area OP2BQ. But, if the commodity could be purchased at price P, 
the total cost of Q units to the consumer would be only the area 
OPBQ.  

Since the total cost would be less than the total value to the 
consumer, timber processing mills would realize a net gain referred 
to as consumer’s surplus equal to the difference area PP2B. 
Similarly, the market supply curve for timber is the horizontal 
summation of the supply curve for all mills in the industry. The 
height of the supply curve for timber is equal to the opportunity cost 
of each unit of timber, since the height of a firm’s supply curve 
indicates the price value of the marginal opportunity cost of each 
unit of the commodity.  

The price paid for inputs by the industry reflects the opportunity 
cost of the last unit purchased. The area under the market supply 
curve for timber will therefore be equal to the total opportunity cost 
of the inputs used by the industry to produce timber. Then, the 
difference between the total revenue received by an industry and 
the area under the market supply curve for timber is equal to the 
total producer’s surplus received by the timber supplies in that 
industry. In summary, the aggregate consumer’s surplus is equal to 
the area under the market demand curve and above the market 
price line, area PP2B. In turn, aggregate producer’s surplus is equal 
to the area above the market supply curve and below the price line, 
area PBF.  

The price value of the benefits and costs resulting from the shift 
of the supply curve for timber in the domestic market can be 
calculated using the concepts of consumers and producer’s surplus 

 
 

 
discussed previously. As illustrated in Figure 3, the reduction in 
available cut and increases in cost of internalization the externalities 
and external cost of timber harvest would reduce timber supply. 
 

The supply curve before the policy is labeled S0, and the total 
consumer and producer’s surplus is equal to the area FBP2. Hence, 
the supply curve shifted to S1, and the total consumers and 
producer’s surplus is equal to the area ECP2. Therefore, the shift in 
the supply curve for timber from S0 to S1 would result in a decrease 
in total consumers’ and producers’ surplus equal to the area BCEF.  
The total sum of the consumer and the producer surplus is the 
social surplus. At this level, the value of consumer and the producer 
surplus were represented the value after taking into account several 
scenarios under SFM practices. 

 
Evaluating the time series properties 
 
It has become a standard practice to begin the analysis by 
examining the time series properties of the data. Any time series 
data can be thought of as being generated by a stochastic or 
random prices and a concrete set of data. A stochastic process is 
said to be stationary if its mean and variance over time and the 
value of covariance between two time periods depends only on the 
distance or lag between the two time periods and not on the actual 
time at which the covariance is computed. With these particular 
characteristics, shocks to a stationary time series would be; over 
time, the effect of the shocks will dissipate and the series will revert 
to its long run mean level. Consequently, long-term forecasts of a 
stationary series will converge to unconditional mean of the series. 
In contrast, a non-stationary series process has a permanent 
component. Its mean variance is time independent. For a non-
stationary series, there is no long-run mean to which the series 
returns.  

We start the analysis by examining the time series properties of 
the data used in the supply and demand equations. However, 
depending on the power unit root tests, deferent tests might yield 
different results which eventually lead to certain degree of 
uncertainty in the analysis of level relationships. Therefore, this 



      

Table 2. Results of timber market.     
      

 Supply function     

 ∆lnTS =  - 1.7281 + 0.1497∆lnP - 0.0828∆lnIC  + 0.2076∆lnAH + 0.9531∆lnTSt-1   

(0.05)* (0.07)* (0.00)*** (0.00)***  

 R
2
  = 0.93 Adj. R

2
  = 0.92 DW = 1.93 Ramsey RESET Test = (0.33)  

 Heteroscedasticity Test = (0.63)  Wald Test = (0.00)***   

      

 Demand function     

 ∆lnDD =  4.2010 - 0.3687∆lnP + 0.2792∆lnIPI + 0.3216∆lnWMP + 0.6758∆lnDD t-1   

(0.05)* (0.20) (0.12) (0.00)***  

 R
2
  = 0.73 Adj. R

2
  = 0.69 DW = 1.88 Ramsey RESET Test = (0.61)  

 Heteroscedasticity Test = (0.73);  Wald Test = (0.00)***   

 
 

 
study utilize two different unit root testing procedures in examining 
the stationary properties of the data to provide a robust test result 
on the information of the order of integration of the data used. The 
use of alternative unit root testing procedures is very important in 
dealing with anomalies that arise when the data are not very 
informative about whether or not there is a unit root. These two unit 
root tests used are the non-stationary test of Augmented Dickey-
Fuller (ADF) and Philips-Perron (PP) unit root test. 

 
Data description 
 
The data used in this analysis is time series data. With regards to 
the time series data analysis, this study intends to evaluate the 
empirical performance of SFM practices in Peninsular Malaysia 
domestic market using annual data from 1970 to 2008. Published 
data on all variables in this study were available from the Forestry 
Department of Peninsular Malaysia, Department of Statistics, 
Malaysia and Ministry of Plantation Industries and Commodities, 
Malaysia. 
 
 
EMPIRICAL RESULTS 
 
Econometric analysis is capable of providing a 
quantitative analysis of the actual economic phenomenon 
based on the concurrent development of theory and 
observation, related by an appropriate method of 
inference (Gujarati, 2003). Since this analysis uses time 
series data, it is necessary to find out whether the data 
are stationary or otherwise. For this reason, unit root test 
has been conducted using the ADF and PP unit root test. 

 
Unit root test on time series data 
 
It is necessary to test the order of integration of each 
variable in a model. This is to determine how many times 
the variables need to differently produce a stationary 
series. It is essential to note that testing for stationary 
condition for a single variable is very similar to testing 
whether a linear combination of variable cointegration to 
form a stationary and equilibrium relationship (Harris, 
1995). 

 
 

 
Since the unit root test results are sensitive to different 
values of the autoregressive lag lengths, the selection 
rule of the truncation lag parameter is crucial in 
determining the order of integration of the data. In this 
study, the optimal lag length of the ADF test is chosen 
based on automatic selection by Schwartz information 
criterion (SIC), while Newey-West Bandwidth criterion is 
used for the optimal lag length selection in the PP test to 
ensure the errors are white noise. All the unit root tests 
are carried out using E-views 6.0 software.  

All the variables are non-stationary in levels. Thus, we 
cannot reject the null hypotheses of a unit root in both the 
ADF and PP tests. On the other hand, all series appear to 
be stationary after first differencing that is I (1). This result 
is consistent for both ADF and PP tests used in this 
study. Therefore, higher order of differencing is not 
required to make the data into stationary process. The 
results imply that there is I (1) variables in the Peninsular 
Malaysia data, and no existence of I (2) variable.  

There is a concrete support for the existence of a unit 
root stationary at I (1) by ADF and PP unit root tests in 
Peninsular Malaysia. The result of I (2) is automatically 
do not need to carry out because all the variables are 
integrated at I (1). If, there are not integrated at I (0) and I 
(1), then it is necessary to analyze the unit root test at I  
(2) level. 

 
Estimated coefficients of timber market 
 
Table 2 provided the empirical result of the estimated 
equations. As mentioned earlier, the supply and demand 
models for the timber industry were estimated using the 
system of equations approach as endogenous variable 
exists in each of the equation. Based on the result of unit 
root tests, all parameters used in the model are stationary 
at first difference. Therefore, the data are not stationary at 
level form; it should be transformed to the first difference 
before importing those variables in the model. In general, 
the estimated equations in the model have reasonable 
goodness-of-fit. All of the variables 

158       Afr. J. Environ. Econ. 

Manage. 

 



Abdul-Rahim  et al.              159 
 
 

 
coefficients in the model were as expected and consistent 
with the theory of supply and demand.  

Based on the empirical result of timber supply function, 
the estimated coefficients of P and IC were statistically 
significant at the level of 10%. This means that, they are 
the significant determinants of timber supply. For P, the 
result suggested that for every 10% growth in average P, 
ceteris paribus, timber supply would increase by 1.5%. 
The significant coefficient of P verified the priori 
assumption that price is an incentive for timber 
production.  

On the other hand, IC has a negative coefficient. Based 
on the estimation, a growth of 10% in IC, ceteris paribus, 
the timber supply would decrease by 0.8%. In other 
words, larger value in IC will then reduce the volume of 
timber produced. AH on the other hand appeared to be 
highly significant at the level of 1%. This is believed to be 
due to the direct impact of timber harvesting activities on 
timber supply. Thus, a 10% reduction in AH led to 
approximately 2% decrease in timber supply. This is 
where the Malaysian Government has taken a proactive 
action when the rate of AAC shows declination since 
early 1990s. This to a certain extent may pull down the 
timber supply to a sustainable level. This result is similar 
with the study conducted by Jamal and Mohd Shahwahid 
(1997) and Lim et al. (2002) which concluded that the 
Malaysian strategy to reduce AAC in the natural forest is 
in preparation towards SFM practices. For example, 
Jamal and Mohd Shahwahid (1997) mentioned that 
timber supply started declining from 1992 onwards due to 
the practice of sustainable forest management.  

The estimates obtained for the domestic demand 
equation were as expected. The coefficients for own price 
and lagged one year dependent variable were significant 
at the level of 5% and one percent respectively. The own 
price elasticity is -0.389. This result confirmed the 
findings of previous studies (Mohd Shahwahid, 1995; 
Abdul Rahim; Mohd Shahwahid, 2009e) that the domestic 
demand and supply for timber price is inelastic. A 10% 
growth in the price of timber decreases the domestic 
demand for timber by 3.8%. Similarly, Daniels and Hyde 
(1986) reported that both supply and demand price were 
fairly inelastic and suggested that price changes will not 
result in dramatic harvest fluctuation. Conversely, the 
coefficients for substitute price and industrial production 
index were not significant. The industrial production index 
does not influence the demand for timber (Mohd 
Shahwahid, 1995). The insignificant result of the 
substitute price (that is, world import price) implied that 
the domestic timber market in Peninsular Malaysia do not 
really rely on imported timber.  

In the case of Peninsular Malaysia, there was no export 
market for timber since early 1990s. According to FDPM 
(2005), Peninsular Malaysia has imposed a ban on timber 
export since the 1990s. This action was taken to give 
local timber processing mills priority in getting their raw 
materials and also to meet the domestic demand. 

 
 
 

 
Any export has to be processed timber. In addition, 

Peninsular Malaysia has marginally imported timber from 
abroad. For example, in 2007, Peninsular Malaysia has 

imported 70,704 m
3
 of timber or 1.6% out of the total 

supplied. Hence, the total quantity supplied and 
demanded can be solved within the domestic market as a 
large portion of these quantities were not from the foreign 
market.  

This is a reasonable explanation for the exclusion of 
international timber market in the partial market 
equilibrium analysis. In other words, this study will focus 
on the impact of domestic market and economic welfare, 
for the case of Peninsular Malaysia. 
 
 
Validation of timber market model 
 
The overall fit of the equation between the explanatory 
variables and dependent variable could be explained by 
the value of R-square. This is an important criterion in 
evaluating the quality of regression. For example, the 
value of R-square obtained from the estimated supply 
equation is 0.93. This implied that 93% of the variation in 
timber supply can be explained by the explanatory 
variables in the model.  

Other diagnostic tests that have been carried out for 
timber supply and demand equations were serial 
correlation of Durbin-Watson (DW) test, heterosce-
dasticity, Ramsey RESET test and Wald test (Table 2). 
The results of DW and Heteroscedasticity tests have 
shown no evidence of serial correlation and hetero-
scedasticity problems. The Ramsey RESET test has 
proven that the equation is stable and has no functional 
misspecification. The Wald test is important to test 
whether the estimated equations have a long run 
relationship between independent and all explanatory 
variables. The result showed that the model is 
cointegrated at the significant level of 1%. The root mean 
square error and Theil inequality test demonstrated that 
the deviation of simulated variables is quite close to the 
average size of the variable in the equation.  

A historical simulation has been carried out in the 
sample throughout the period of this study. This is where 
the adequacy of the model in forecasting and policy 
analysis. The detailed tests and results were depicted in 
Table 3.  

The root mean square error (RMSE) and Theil’s 
inequality coefficient were found to be relatively small for 
timber supply (TS) and domestic demand (DD). This 
result suggested that the forecasting and policy analyses 
can be considered as accurate.  

The value of bias proportion is equal to zero, indicating 
the non-existence of a systematic bias for TS and DD. 
Figure 4a and b showed the actual, fitted and residual 
graphs of the timber supply and demand equations. This 
result provides strong evidence that the equation is stable 
between the dependent and all independent variables. 



  
 
 
 

Table 3. Historical simulation of timber model. 
 
    TS  DD 

 

Root mean square error  0.08  0.10 
 

Theil’s inequality coefficient 0.002  0.003 
 

Bias proportion   0.000  0.000 
 

Variance proportion  0.03  0.019 
 

Covariance proportion  0.96  0.98 
 

      16.4 
 

      16.0 
 

      15.6 
 

.2       
 

      15.2 
 

.1       
 

.0      14.8 
 

      
 

-.1       
 

-.2       
 

-.3       
 

1975 1980 1985 1990 1995 2000 2005 
 

 Residual Actual Fitted  
 

   a    
 

      16.4 
 

      16.2 
 

      16.0 
 

      15.8 
 

.4      
15.6         

.2      15.4 
 

       

      15.2 
 

.0       
 

-.2       
 

-.4       
 

1975 1980 1985 1990 1995 2000 2005 
 

 Residual Actual Fitted  
 

   b    
 

Figure 4. Simulation of timber supply and demand.   
 

 
 
 
Results of price and quantity equilibrium 
 
Table 4 presents the empirical results of the average 
simulated value calculated from the timber partial market 
equilibrium model for the period of 1995 to 2008. During 
this period and thereafter, the SFM/RIL has been 
implemented in the Malaysian forest management. Since 
this study examined the economic impact of SFM 

 
 

 
practices, this study will only averaged out the data for 
the period of 1995 to 2008 from the simulated output for 
further analysis. As mentioned earlier, the impact analysis 
comprised of three scenarios; (1) reduced by 24% in 
harvested area, (2) increased by 74% in external cost of 
timber harvesting, and (3) increased by 47% in the cost of 
internalization the externalities. The percentage of the 
reduction in harvested area was 

160       Afr. J. Environ. Econ. Manage. 



    
 

 Table 4. Average simulated values due to SFM practices.   
 

    
 

 

Parameter 
Equilibrium quantity Equilibrium price 

 

 (m
3
) (RM/m

3
) 

  
Baseline scenario 
 
 
 
Scenarios % changes 
under SFM practices 

 

 
Reduced by 24% in harvested area  
Rise by 74% in external cost 
of timber harvesting  
Rise by 47% in the cost of 
internalization the externalities 

 
 

6,655,871 514 

6,392,684 573 

6,442,272 561 

6,506,564 546 

 
 

 
adopted from the study conducted by Ahmad Fauzi et al. 
(2002). Whereas, the remaining two scenarios (that is, 
incremental cost of internalization the externalities and 
incremental cost of external cost of timber harvesting 
activities) were borrowed from the study conducted by 
Abdul Rahim et al. (2009) and Abdul Rahim and Mohd 
Shahwahid (2010) respectively. The incremental external 
cost of timber harvesting activities and the cost of 
internalization the externalities by minimizing damages 
from timber harvesting activities will result in optimum 
level of quantity and price level.  

In this impact analysis, the equilibrium price was 
calculated from the estimation of timber market model, 
where the market equilibrium was set-up. By definition, 
the equilibrium price is the price at which the supply of 
timber equals the demand for timber (Equation 5). After 
substituting the equilibrium price into the supply or 
demand model, the equilibrium quantity was obtained. In 
other words, from the estimated coefficient, the 
equilibrium price and quantity of timber could be 
quantified. The detailed processes are available in 
Appendix A. The average timber market equilibrium point 

for price and quantity was RM514/m
3
 and 6.65 millions 

m
3
 respectively. This point corresponds with the baseline 

scenario.  
The incorporation of the three impacts of SFM prac-

tices; (1) reduction in harvested area, (2) incremental 
external cost of timber harvesting activities and (3) 
incremental cost of internalization the externalities by 
minimizing forest damages from timber harvesting 
activities through simulation analysis, showed negative 
effect upon equilibrium quantity. On the other hand, the 
price of timber showed positive effect as it increased 
under the three impact scenarios from SFM practices. As 
shown in Table 4, the price of timber increased by 12, 9 

and 6% to RM573/m
3
, RM561/m

3
 and RM546/m

3
 

respectively under the three scenarios of SFM practices. 
This reflected the domestic timber market in Peninsular 
Malaysia that potentially may fetch price premium 
averaging from 6 to 12% if the three potential impacts 
were imposed on timber producers. In other words, these 
simulated prices were the price of timber when best 
practice environmental resource management was 

 
 

 
adopted and when price distortion was remedied. This 
finding is consistent with the result obtained from the 
previous studies. Some authors claimed evidence that 
consumer in Europe and USA were willing to pay 
between 2 to 30% more for sustainably produced certified 
tropical timber (Baharuddin, 1995; Baharuddin and 
Simula, 1996; Simula and Baharuddin, 1996; Oliver, 
2005). In addition, Kollert and Lagan (2007) carried out 
their study in selected forest management units (FMUs) 
in Sabah, Malaysia and found that Sabah timber 
achieved a price premium averaging from 2 to 56%.  

Based on this empirical analysis, the advantage of 
complying with SFM practices in Peninsular Malaysia is 
the increase of domestic price of timber, averaging from 6 
to 12%. This is where Malaysian Government inter-
vention is needed to ensure that the advantages of price 
premium in the domestic market can be realized; 
particularly, the timber produced from sustainably 
managed forest. As seen in Table 4, the equilibrium 
quantity of timber has decreased by 4, 3 and 2% to 6.39 

m
3
, 6.44 m

3
 and 6.51 m

3
 respectively under the three 

scenarios of SFM practices. This finding is consistent with 
the study conducted by Schwarzbauer and Rametsteiner 
(2001) which revealed that the timber production will 
decrease in the long run due to SFM practices. This 
implied that the domestic timber processing mills might 
rationalize their consumption of timber as raw material 
from natural forest by being more efficient processors. 
Those who could not upgrade or switch towards the more 
efficient production practices may have to close down, 
while those who can may expand their production base. 
In addition, Woon (2001) revealed that the total number 
of timber processing mills (that is, sawmills, plywood and 
veneer mills) were expected to be drastically reduced due 
to SFM practices. The result of this study provides an 
empirical evidence of the implication under SFM 
scenarios on timber market in Peninsular Malaysia. The 
percentage of decreases in equilibrium quantity of timber 
in the long run provided an explanation that the 
Malaysian timber production was managed not only for 
present needs but also for the benefits of the future 
generation as well. Furthermore, the timber harvesting 
technique in SFM practices that gave 

   

Abdul-Rahim  et al.              161 



162       Afr. J. Environ. Econ. Manage. 
 
 
 
Table 5. Average welfare impacts due to SFM practices. 

 
Item Producer surplus Consumer surplus Total Social benefits 
Baseline scenario 88,225 118,224,286 118,312,541 
 

Reduced by 24% in  
harvested area 

 
Scenarios % Rise by 74% in external  
changes under SFM cost of timber harvesting 
practices  

Rise by 47% in the cost  
of internalization the 
externalities 

 
 

67,347 118,122,972 118,190,319 

68,364 118,143,237 118,211,601 

75,799 118,168,669 118,244,468 

 
 

 
priority in curbing externality effects and logging damages 
enhanced the process of regeneration of timber tree in 
the next cutting cycle. In this context, Thang (2007) 
revealed that the Malaysian timber production would 
increase in the long run due to the implementation of 
SFM. 
 
 
Results of welfare economic impacts 
 
Based on the simulated value calculated earlier as given 
in Table 4, the average annual estimated values of 
welfare economic impacts were further calculated (Table 
5). The similar scenarios as what in the market impact 
analysis were adopted and simulated in this welfare 
economic impacts analysis. The simulation results 
showed that the calculated value of producer surplus and 
consumer surplus changes when incorporating the three 
scenarios under SFM practices. The detail process can 
be seen in Appendix B.  

Under scenario one, where HA reduced by 24%, the 
producer surplus reduced from RM88,255, under the 
baseline case to RM67,347. Similarly, the consumer 
surplus also decreases from RM118.22 million, under the 
baseline scenario, to RM118.12 million. Under scenario 
two, where external cost of timber harvesting increased 
by 74%, the producer surplus reduced from RM88,255, 
under the baseline case, to RM68,364. Similarly, the 
consumer surplus also decreased from RM118.22 million, 
under the baseline scenario, to RM118.14 million. Under 
scenarios three, where the cost of internalization the 
externalities went up by 47%, the producer surplus 
reduced from RM88,255, under the baseline case, to 
RM75,799. Similarly, the consumer surplus also 
decreases from RM118.22 million, under the baseline 
scenario, to RM118.17 million.  

This result indicated that the variation in the HA is the 
main cause of reduction in the calculated value of the 
producer and consumer surplus. This is because the 
elasticity of HA was relatively higher than the other policy 
variables. This situation would bring towards loss in the 

 
 

 
economic welfare on timber market in Peninsular 
Malaysia. The economic welfare in this study referred to 
the calculated value of total social benefit, which is the 
summation of the value of producer and consumer 
surplus. Hence, this finding implied that when the timber 
industry complies with the SFM practices, the economic 
welfare of the stakeholders in the timber sector will 
decline.  

As noted by Wells and Wall (2005), there is an element 
of trade-offs between environmental protection and 
timber from forests. However, with SFM practices, the 
source of timber supply from natural forest could be 
sustained and the externality effects from timber 
harvesting activities could be minimized. Otherwise, the 
regeneration of timber from the natural forests would be 
affected. In general, the nation would also lose the 
valuable non-timber forest products (NTFPs) and 
environmental services that could potentially generate 
income for the society and government in the future. In 
addition, Kotwal et al. (2008) claimed that SFM practices 
could enhanced the growing stock of timber and forest 
productivity of timber and non-timber forest produce. 
 
 
CONCLUSIONS 
 
The above findings showed that such HA and IC 
behaviors may have significant impact on the future 
equilibrium price and quantity process, which in turn 
affects the welfare of producers and stakeholders in the 
timber-based industry. On the supply side, the results 
showed that compliance with SFM practices will reduce 
the supply of timber to a sustainable level. However, the 
level of price was pushed up in the partial equilibrium 
process. Hence, the equilibrium price and quantity of 
timber have increased and decreased respectively, 
representing the optimum level in internalizing the 
externalities from timber harvesting activities.  

For the case of Peninsular Malaysia, the simulation 
showed that the market and welfare economic impacts 
arising from SFM practices were small. Based on those 



Abdul Rahim  et al.              163 
  

 

scenarios, a decrease in harvested levels were likely to context, the common method that has typically been used 
 

affect the market and economic welfare more than an is an input-output model. The coefficients estimated in 
 

increase in input costs (direct and indirect) owing to SFM the econometric model could be used in the input-output 
 

practices. This result is similar with the study conducted (I-O) model to measure the total economic impact for the 
 

by Schwarzbauer and Rametsteiner (2001). They found whole  economy.  In  addition,  the  I-O  model  is  also 
 

that any decrease in harvested levels gave an immense capable  to  take  into  account  the  importance  of  inter- 
 

impact on forest products market than any increase in the dependencies   that   exists   between   sectors   in   an 
 

operational costs due to SFM practices.  economy. Then, the direct and indirect impacts of SFM 
 

The simulation results of partial market equilibrium pre- practices could be highlighted. 
 

sented above revealed that producers could potentially (2) This study only analyzes the economic impact of SFM 
 

fetch  price  premium  in  the  domestic  timber  market in practices on timber market as it gave direct impact to the 
 

Peninsular Malaysia. In this context, one should expect timber harvesting activities. However, it would be wise for 
 

that timber producers will choose to comply with the SFM decision  makers  to  further  conduct  the  economic  impact 
 

practices if the price is an incentive. Therefore, the price analysis of SFM practices on timber-based industries such as 
 

premium is required to offset the foregone value of two sawntimber, plywood, pulp and paper, veneer and moulding. 
 

elements considered in this study; (1) incremental cost of This  could  be  done  through  individual  analysis  which 
 

internalization the externalities by minimizing the environ- analyzes the types of timber-based industries by using 
 

econometric model. Alternatively, this could be analyzed 
 

mental damage from timber harvesting activities, and (2) 
 

external cost of timber harvesting operations which refers by  using  a  system  dynamic  (SD)  approach.  This 
 

to  cost  of  water  treatment.  Ignoring  the  externalities approach is very comprehensive. It covers forest sector 
 

would lead to market failure or distortion in equilibrium aspects from timber up to paper consumption, which is 
 

price  and  quantity.  In  this  context,  government  inter- the main strength of this approach compared to other 
 

approaches in the econometric models with less scope 
 

vention  is  needed  to  alter  the  distortion  of  market 
 

equilibrium.  but more detail. 
 

This  is  due  to  the  timber  prices  used  in  the  timber (3)  In  this  study,  the  timber  market  analysis  for  SFM 
 

market  does  not  reflect  the  price  of  environmental practices refers to the timber that were produced from 
 

resources. Government could built-in the mechanism of natural forests. For the extension of this study, timber 
 

forest taxation rates which are in line with changes to produced from the forest plantation establishment is also 
 

needed to be taken into account in the analysis. This is 
 

market  timber  prices.  In  this  context,  Majawat  (2010) 
 

mentioned that there is a need to place monetary value to because  forest  plantations  plays  an  important  role  in 
 

environmental services.  supplying timber to the timber processing mills and ease 
 

The policy variables used in Peninsular Malaysia timber the pressure of natural forest which related to the timber 
 

market model (that is HA and IC) were significant and production.  Therefore,  new  timber  market  model  for 
 

inelastic.  Exogenous  shocks  in  those  policy  variables timber  produced  from  forest  plantation  need  to  be 
 

developed. 
 

would have small impact on the equilibrium  price and 
 

quantity of timber, and eventually impact on the economic (4) In the context of SFM, future research on integration 
 

welfare  of  timber  industry.  The  result  indicated  that of  all  aspects  related  to  sustainably  managed  forests 
 

stakeholders  in  timber  industry  experienced  a small such as environment, economic and social is vital as the 
 

reduction  in  economic  welfare  due  to  SFM  practices. result of the integration approach of these aspects would 
 

be more compatible. Hence, future work needs to focus 
 

However,  if  the  government  could  impose some good 
 

mechanisms, this could offset their losses. As a result, on developing sufficient approaches and methodologies 
 

this  could  encourage  more  stakeholders  in  the  timber for better integration approach. 
 

industry to comply with SFM policy and minimized the (5) Only the stakeholders in the timber industry for the 
 

externality effects from timber harvesting activities. This welfare economic impact analysis due to SFM practices 
 

could be materialized when timber producers include the were being evaluated in this study. 
 

Hence, the gain and loss of the economic welfare is 
 

external  cost  of  externalities  in  their  total  operational 
 

costs, or known as full economic costs.  limited to the stakeholders in the timber industry. In fact, 
 

   SFM practices affect other stakeholders (that is, society) 
 

   as well apart from the stakeholders in the timber industry. 
 

Future research direction  In this respect, new research should be carried out in 
 

   measuring the welfare economic impact of SFM practices 
 

Based on this study, several elements of limitations are on other stakeholders that are believed to be related to 
 

captured. The potential future research directions are as the forests particularly on the NTFPs and environmental 
 

follows:   services. 
 

   Thus, the welfare economic impact of SFM practices 
 

(1) The extension of this study should be carried out in could be evaluated comprehensively and a better picture 
 

order  to  identify  the  total  economic  impact  of  SFM of  the  total  gains  or  losses  pertaining  to  the  SFM 
 

practices to  the  rest  of  the  economic  sectors.  In this practices could be drawn. 
 



164       Afr. J. Environ. Econ. Manage. 
 
 

 
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Abdul-Rahim  et al.              165 
 
 
 
APPENDIX A. Market equilibrium process 
 
Domestic markets 
 
In order to obtain the equilibrium condition, we have to equate the supply and demand equations as can be seen in 
Equation 6. As there is only domestic market in the Peninsular Malaysia timber market model, only domestic supply and 
domestic demand for timber were required to obtain the market equilibrium. Then, we are able to calculate the 
equilibrium price. To find the equilibrium quantity, we can substitute the equilibrium price into either the supply or  
demand equation. Equation A.1 was derived from the estimated result of Equation 1 and 4. Note that the value of 1 lnP 

and 0 were the summation of coefficient of price and intercept that have been estimated in Equation 1 and 4 

respectively. The rest of the coefficients correspond to the parameters in the model. 
 

1 lnP = 0 - 2 lnAH + 3 lnIC +  4 lnIPI +  5 lnWMP -  6 lnTSt-1 + 7 lnDD t-1 (A.1) 
 

In order to solve lnP, we have to divide the estimated coefficient in Equation A.1 with  1  

               

lnP = 


0  - 


 
2
  lnAH +  3

  lnIC + 
 

4 lnIPI + 
 

5 lnWMP - 
 6

  lnTSt-1 + 
 7

  lnDD t-1 (A.2)       
 


1 1 1 1  1  1 1  

  
By substituting all of the parameters used in Equation A.2 with the average data of time series, then we will be able to 
find the equilibrium price for Peninsular Malaysia’s timber market. To find the equilibrium quantity, we substitute the 
equilibrium price into either Equation A.3 or A.4. 
 

lnTS = 0 + 1 lnP - 2 lnIC + 3 lnAH  + 4 lnTS t-1 (A.3) 

lnDD = 0 - 1 lnP + 2 lnIPI + 3 lnMP + 4 lnDD t-1 (A.4) 

 
Note that the calculated value of equilibrium price and quantity are in natural logarithm form. Hence, we have to convert 
the equilibrium price and quantity to a real value. 

 
APPENDIX B. Welfare economic impact process 
 
Using partial equilibrium consumer surplus (CS) and producer surplus (PS) concepts, it is possible to analyze the 
economic gains and losses in the domestic economy from the implementation of SFM practices. CS refers to the area 
above the equilibrium price line but below the demand curve (Figure 3). It represents the difference between the 
amounts that consumers are willing to pay for a given quantity. PS refers to the area below the equilibrium price line but 
above the supply curve (Figure 3). It represents the difference between the total revenue received by producers for 
producing a given quantity. It is typical for economist to measure CS and PS in order to assess the impacts on 
consumers and producers of given policies.  

In this study, we used integral calculus to find the areas of CS and PS that we adopted from Hess (2002). From 
Equation 6, we could further find CS and PS. To find CS we need to subtract the total expenditures of consumers 

(P0*Q0) from the area under the demand curve up to the quantity transacted (Figure 3). According to Hess (2002), if the 
calculation is integrated with respect to the quantity variable, the Marshallian formulation must be used.  

 
Q

0    
 

CS = area PP2B =  d 
1

 (Q)dQ  (P Q ) (B.1) 
 

 0 0   

    
 

 0    
 

Alternatively, we could find CS by integrating with respect to the price variable.  
 

 P2    
 

CS = area FP2B = d (P)dP  (B.2) 
 

 P0    
 



166       Afr. J. Environ. Econ. Manage. 
 
 

Here the interval of interest is along the price axis from the equilibrium price P0 to the maximum demand price of P2.  
On the other hand, to find PS we need to subtract from the total revenues received, (P0*Q0), the area under the supply 

curve up to the quantity transacted Q0. 
 

PS = area FP0B = 
  Q0  

(B.3) 
 

(P *Q )   s
1 (Q)dQ 

 

 0 0     

     
 

   0   
 

Alternatively, we could find PS directly by integrating with respect to the price variable.  
 

 
P

0     
 

PS = area FP0B = s(P)dP  (B.4) 
 

F 
 
Here the interval of interest is along the price axis from the minimum supply price of F up to the market equilibrium price 

of P0. 
 


