Are There Price Premiums for Certiﬁed Wood?
Empirical Evidence from Log Auction Data in Japan
Yuki Yamamoto
Graduate School of Economics, Kobe University
yuuki00007@hotmail.com

Kenji Takeuchi
Graduate School of Economics, Kobe University
takeuchi@econ.kobe-u.ac.jp

Takayoshi Shinkuma
Faculty of Economics, Kansai University
shinkuma@ipcku.kansai-u.ac.jp

Abstract
By using data on more than 38,000 log auction transactions frommarket in Shizuoka Prefecture, Japan, we estimate whether there is a
price premium for certiﬁcation of sustainable forest management. We
found a positive and signiﬁcant eﬀect of certiﬁcation for logs, especially in the smaller diameter category. The reason for the diﬀerence
between diameter size can be attributed to demand from pulp andpaper manufacturers. The premium found was 1.8% of the price of
conventional logs, in the lower range of additional willingness to pay
found in previous studies that used stated preference techniques. An
analysis that includes a pre-certiﬁcation equilibrium price suggeststhat Japanese certiﬁcation is unsuccessful despite the existence of aprice premium.

Keywords: Forest certiﬁcation, Price premium, Log auction, Japan1

1

Introduction

Certiﬁcation of sustainable forest management has been increasingly promoted throughout the world over the last two decades. According to UNECE/FAO (2011), as of May 2011, the total area of forests certiﬁed worldwide
was approximately 375 million hectares, or about 9.3% of the world’s forests.
The area above has been those endorsed by one or other of the two dominant international organizations: the Forest Stewardship Council (FSC), or
the Programme for the Endorsement of Forest Certiﬁcation (PEFC), which
evaluate both forest management activities (forest certiﬁcation) and tracking of forest products (chain-of-custody certiﬁcation). There is a considerable
variety of certiﬁed forest products on the market, from papers to furniture
items. Certiﬁed products often bear labels declaring that they come fromforests that meet the standard of sustainable forest management. Throughsuch labeling, forest certiﬁcation acts as a tool for producers to be able totransfer information on sustainability to consumers.
Haener and Luckert (1998) raise the existence of a green price premium as
one of the contentious issues with regard to the impact of forest certiﬁcation.
Since additional willingness to pay for certiﬁed wood products is an importantfactor in the existence of a price premium, many studies have estimated it
by using stated preference surveys (Ozanne and Vlosky, 1997; 2003; Ozanneand Smith, 1998; Forsyth et al., 1999; Grönroos and Bowyer, 1999; Pajari
et al., 1999, Veisten, 2002; 2007; Kozak et al., 2004; O’Brien and Teisl,
2004; Aguilar and Vlosky, 2007; Aguilar and Cai, 2010). Table 1 is a briefsummary of ﬁndings by these studies. Most of them found there is a positive
willingness to pay among consumers in North America and Europe, andestimates of a willingness to pay more than the price of conventional forest
products have ranged from 1.4% to 18.7%. Other studies (Vlosky et al., 1999;
Bigsby and Ozanne, 2002; Teisl et al., 2002a; Anderson and Hansen, 2004a;
Thompson et al.,2010) also attempted to investigate the preference structure2and motivation for willingness to pay by using a similar technique.

Table 1: Estimated willingness to pay in stated preference studies
Authors

Area

Results

Ozanne and Vlosky (1997)

US

18.7% for a $1 stud
4.4% for a $100,000 new home

Ozanne and Smith (1998)

US

18% of homeowners prefer certiﬁed wood products

Forsyth et al. (1999)

Canada5% (67.3% of sample)
10% (28.3% of sample)
more than 10% (13% of sample)

Grönroos and Bowyer (1999)

US$2500 per home built

Pajari et al. (1999)EU

1.4% - 4.9%

Veisten (2002)

UK, Norway

5% or less
(32% - 39% of sample)

Ozanne and Vlosky (2003)

US

11.7%

Kozak et al. (2004)

Canada

5.6% - 14%

O’Brien and Teisl (2004)

US

positive

Aguilar and Vlosky (2007)

UK

at least 10%

Veisten (2007)

UK, Norway

2% - 16% (median)Aguilar and Cai (2010)

US, UK

5% higher price can capture 34 to 50% of the market

Note: Additional willingness to pay is indicated by the ratio to the price for conventional
products.

While the willingness to pay on the part of environmentally conscious
consumers plays a key role in the existence of a price premium, it also depends
on the supply side. By using a qualitative survey for suppliers in Finland,
Owari et al. (2006) conﬁrmed that it was not possible for most of the surveyed
Finnish companies to charge a price premium. Certiﬁcation has not helped
them improve their ﬁnancial performance but was positively evaluated bycustomers, and, as such, was a tool to enhance reputation. For suppliers incountries like Finland and Austria, where all forests are certiﬁed and therefore
all forest products could bear a label, there is little incentive to use this tool tosignal a diﬀerence from competitor’s products (UNECE/FAO, 2005). Hence,3

if we want to know what sort of premium exists in the market, we need totake into account the interaction of supply and demand, as we shall see inthe theoretical review in the next section.
This study investigates the dimensions of a price premium by using market data on log auctions in Shizuoka Prefecture in Japan. While there areplenty of studies that have estimated willingness to pay for certiﬁed wood
products by using a stated preference survey, as far as we know, there havebeen no attempts to use actual price data to investigate the size of a pricepremium. Two exceptions to the stated-preference-survey method are experimental studies by Anderson and Hansen (2004b) and Anderson et al. (2005),
in which consumer behavior was studied at two home improvement retailers and two university bookstores in the US. The ﬁndings of these studies,
however, rely on the observation of behavior in an artiﬁcial situation, andthe number of observations and period of experiment were relatively limited.
Since there is a diﬀerence between stated intention to pay and actual behavior (List and Gallet, 2001; Murphy et al., 2005) and possibly between
behavior in an artiﬁcial situation and that in a real situation, using the datafrom a real market would be valuable to understand the proﬁtability of forest
certiﬁcation.
This study relates to a body of empirical analyses that have investigatedthe existence of price premiums for eco-labeled goods (Henion, 1972; Teisl
et al., 1999; Blamey and Bennett, 2001; Bennett et al., 2001; Nimon andBeghin, 1999; Roe et al., 2001; Teisl et al., 2002b; Bjørner et al., 2004).
For example, Teisl et al. (1999) investigated the eﬀect of the dolphin-safelabel on the overall market share of canned tuna by using aggregated sales
data. As another example, Bjørner et al. (2004) used a large body of Danish
consumer panel data to estimate the impact of the Nordic Swan eco-label
on consumers’ shopping behavior. While these studies focus mainly on ﬁnal
consumer goods sold in retail shops, we focus on the premium for certiﬁed
logs, which are used as primary inputs or intermediate goods. The existence4

of price premium at the earlier stage of the supply chain has an important
implication for the economic viability of sustainable resource management,
since it is more directly relevant to the decision making of resource managers.
The rest of this paper is structured as follows. Section 2 summarizes
ﬁndings from theoretical studies on the price premium of forest certiﬁcation. Section 3 presents statistical details of our data and the results of an
econometric analysis. Section 4 discusses the implication of our results incomparison with those of previous analyses and theoretical prediction. Section 5 presents our brief concluding remarks.

2

Theoretical Findings

Consumers often have a willingness to pay more for goods that are made byenvironmentally friendly processes or methods. When there is an information
asymmetry between producers and consumers, an eco-labeling scheme canhelp consumers identify environmentally friendly products in markets. It
would provide an incentive for producers to supply these products in the
expectation of gaining an additional beneﬁt (a price premium) attributable
to consumers’ willingness to pay.
A few studies have attempted a theoretical analysis of the roles of ecolabeling and its impact on markets. One of the earliest study is that of Mattoo and Singh (1994), who considered the conditions under which eco-labelingwould lead to a reduction in the supply of conventional (environmentally unfriendly) products in a competitive market. They assumed that there are two
types of consumers: eco-consumers and non-eco-consumers. Eco-consumers
prefer environmentally friendly products to environmentally unfriendly products, regardless of price. Non-eco-consumers prefer products that have lower
prices. There are also two types of suppliers: one that supplies eco-products
and one that supplies non-eco-products and cannot choose which products
to supply. Mattoo and Singh found that the existence of a price premium,5

i.e., additional willingness to pay, for environmentally friendly products is anecessary condition for the functioning of eco-labeling schemes. They also
pointed out that implementation of an eco-labeling scheme might increase
the supply of environmentally unfriendly products by increasing the prices
of both types of product.
Sedjo and Swallow (2002) analyzed the necessary condition for a successful certiﬁcation scheme with a more reasonable assumption than that ofMatoo and Singh: they assumed that a supplier can choose a producing technique that is either environmentally friendly or not. They attended to thefact that the existence of additional willingness to pay for environmentallyfriendly products does not necessarily mean that a price premium arises in
the actual market. They found that the existence of a willingness to pay a
premium is not a suﬃcient condition for a price premium. They found thata certiﬁcation scheme can fail even when there is a price premium between
certiﬁed and non-certiﬁed products. For a successful eco-labeling scheme,
the equilibrium price of certiﬁed products should be higher than that ofnon-certiﬁed products, and both prices should be above the pre-certiﬁcation
equilibrium price.
To summarize these two contributions, eco-labeling schemes can be regarded as successful in competitive markets when the following conditions
are satisﬁed: a) there is a price premium on certiﬁed goods compared to
non-certiﬁed goods; b) the prices of goods of both certiﬁed and non-certiﬁed
goods under the certiﬁcation scheme are higher than the pre-certiﬁcation
equilibrium price. We examine these conditions for competitive markets inthe following section, using market data on log auctions in Japan.
Although we focus on the question of whether eco-labeling can work wellin competitive markets, several studies have examined it in a duopolistic market structure. In their duopoly models of vertical product diﬀerentiation bothAmacher et al. (2004) and Ibanez and Grolleau (2008) show that eco-labelingcan be used as a means of increasing environmental quality that is too low.

6

On the other hand, there are several theoretical studies that examine theeﬀectiveness of eco-labeling under asymmetric information (Kirchhoﬀ, 2000;
Baksi and Bose, 2007; Hamilton and Zilberman, 2006). When consumers areheterogeneous, although a self-policing scheme is the ﬁrst best when ﬁrms
are honest, third-party certiﬁcation should be implemented when ﬁrms cancheat with the labeling process (Baksi and Bose, 2007). In the case of voluntary certiﬁcation in a monopoly, Kirchhoﬀ (2000) argued that cheating canbe prevented by an exogenous labeling system enforced with an appropriate
ﬁne. Forest certiﬁcation schemes can be considered a kind of eco-labelingpolicy with both the voluntary and third-party certiﬁcation.

3

Empirical Investigation

3.1

Data

Two forest certiﬁcation schemes are dominant in Japan; Sustainable Green
Ecosystem Council (SGEC) and the Forest Stewardship Council (FSC). The
SGEC is a Japan-originated certiﬁcation scheme and has certiﬁed more than
0.86 million hectares or 3.5% of the total forest area in Japan, while the FSC
has certiﬁed more than 0.35 million hectares or 1.5% of that area. With regard to the CoC (chain-of-custody) certiﬁcation, Japan has the third-largest
number of companies in the world, after Europe and North America (UNECE/FAO, 2005). As of 2011, more than 1,500 Japanese companies had
acquired CoC certiﬁcation that 402 under the SGEC, and 1,107 under the
FSC.
Our empirical study uses more than 38,000 log auction transactions in2011 at three markets in Shizuoka Prefecture. The Shizuoka Forest Owners’
Association has been actively involved in sustainable forest management andforest certiﬁcation. Out of the 899,000 hectares of forest area of Shizuoka Prefecture, 8,169 hectares (0.9%) and 37,966 hectares (4.2%) have been certiﬁed7

as sustainable forest by the SGEC and the FSC, respectively. Furthermore,
32 companies have acquired CoC certiﬁcation from the SGEC and 63 fromthe FSC.
Log auction markets emerged in the ﬁrst half of the 1960s throughout
Japan and played the role of distribution centers, given the existence ofsmall-scale and scattered forest stands and log suppliers (Ito, 2002). Logs
produced by suppliers are trucked to the auction market and sorted into
selling units (hai ) by species, diameter, length, quality, and shipper. Buyers
create a price for each hai by auction or bidding and then purchase their logs.
Auction markets generally are ﬁnanced and managed by sales commissions
from buyers and sorting charges from shippers. The number of log auction
markets in Japan was 516 as of 2006 and the log volume they handled was
7.11 million cubic meters, approximately 51.4% of the total domestic log
supply for sawn timber (Ministry of Agriculture, Forestry and Fisheries ofJapan, 2007).
Our data on the timber trade in Shizuoka Prefecture include the clearing price per cubic meter, diameter, length, information on defects (such as
crooks, knots, and scars), and forest certiﬁcation. The Shizuoka Forest Owners’ Association consists of three oﬃces: the Shizuoka Oﬃce, the Fuji TimberCenter and the Tenryu Oﬃce. Each oﬃce holds log auction markets typically
twice a month by a ﬁrst-price sealed-bid auction. On the day of the auction,logs sorted into hai are set out in the yard of the market. Buyers put cards
with bids written on them into a box in front of each hai. Bidding closes
at noon and each hai goes to the highest bidder. Sellers can tell the reserve
price to the auctioneer, but it is not announced to bidders. Since information on reserve prices was unavailable, they are not included in our analysis.
Timbers is sold to industrial sectors such as paper and pulp manufacturers,
the construction sector, and furniture manufacturing companies. Table 2 isa summary of descriptive statistics. The timber in our data mostly consistsof Japanese cedar (Cryptomeria japonica), Japanese cypress (Chamaecyparis

8

obtusa), and Japanese pine (Pinus thunbergii ). We found that 29.8% of thetimber is certiﬁcated but we could not identify which institution (the SGEC
or the FSC) issued each certiﬁcation.

Table 2: Descriptive statistics of data
Variable name

Explanation

Mean

S.D.

y

Sale price (yen) per cubic meters of log

15930.56

9787.98

LengthLength of the log (m)

3.808

0.802

Diameter

Diameter of the log (cm)26.602

9.384

Certiﬁed

Certiﬁed log =1; otherwise =0

0.295

0.456

Defects

Defects =1; otherwise =0

0.172

0..378

Cedar

Cedar =1; otherwise =0

0.520

0.500

Cypress

Cypress =1; otherwise =0

0.448

0.497

Pine

Pine =1; otherwise =0

0.004

0.0611

Fuji

Fuji Timber Center =1; otherwise =0

0.152

0.359

TenryuTenryu Oﬃce =1; otherwise =0

0.590

0.492

Shizuoka

Shizuoka Oﬃce =1; otherwise =0

0.258

0.438

House

Number of new homes built per month

2075.19381.00

NBidders

Estimated number of potential bidders

444.68229.43

Note: 100 Japanese yen were worth approximately 1.21 US dollars as of January 2011.

3.2

Price premium of certiﬁed logs

This section estimates the impact of forest certiﬁcation on log price. We include length, diameter, certiﬁcation, defects, and dummy variables for species(cedar, cypress and pine), markets (Fuji, Tenryu and Shizuoka), and months
to explain the variation in the prices of logs. The certiﬁcation variable is adummy variable that takes one when the log is produced in a certiﬁcatedforest, and zero otherwise. The defects variable is a dummy variable thattakes one when the log has defects such as crooks, knots and scars and zero9otherwise. We regress the sale prices of logs on these various factors. Since
our data contains zero price when the logs have not been sold, we use a Tobit
model for estimation (Huang and Buongiorno, 1986; Boltz, 2002).

M Vi∗ = β ′ Xi + ϵiyi = M Vi∗ if M Vi∗ > RPi
yi = 0 if M Vi∗ < RPi(1)where M Vi is the latent market value per cubic meters of log i, yi is thesale price per cubic meters of log i, Xi is a vector of exogenous variables
for log sales i, β is a vector of coeﬃcients corresponding to the variables X,
ϵi is the error term, and RPi is the reserve price for log i. In our analysis,
we excluded the top one percent of data to remove outliers. Prices in the
top one percent are more than several ten times higher than the median log
price; these extremely high prices are mainly due to trades of old-growth or
high-quality logs for special events. The estimated model is as follows:

M Vi∗ = f (Lengthi , Diameteri , Certif iedi , Def ectsi , Cedari , P inei
Shizuokai , F ujii , M onthij , Housej−1 , N Bidderst ),(2)

where Lengthi denotes the length of log i, Diameteri denotes the diameter oflog i, Certif iedi denotes whether log i has been certiﬁed for sustainable forest
management, Def ectsi denotes whether log i has defects, Cedari and P inei
are dummy variables for wood species, Shizuokai and F ujii are dummy
variables for market i, M onthij denotes dummy variables for the month jthat the auction was held, Housej−1 denotes the number of new homes built
in Shizuoka Prefecture in the month j−1, N Bidderst is the estimated numberof potential bidders, and ϵi is the error term. N Bidderst is included becausea larger number of bidders in an auction would result in higher bids (Boltz

102002). However, we could not directly observe the potential bidders in ourdata, so we estimated their number by using the number of sales held on thesame day in the same market.

The estimation results by OLS and Tobit are summarized in Table 3.
Heteroskedasticity-robust standard errors are given in parentheses under estimated coeﬃcients. Most of the coeﬃcients have the expected sign and arestatistically signiﬁcant in the models 1 and 2. The coeﬃcients of cedar andpine are negative and statistically signiﬁcant at the 1 % level, indicating thatthe price of cypress is higher than the prices of cedar and pine. The coeﬃcients of length and diameter are positive and statistically signiﬁcant at the
1% level, as expected. The signs of the coeﬃcient of forest certiﬁcation are
positive and statistically signiﬁcant, indicating that there are price premiums
for certiﬁed timbers. The coeﬃcients of certiﬁcation are 280.96 and 284.66;
this means that certiﬁcation adds only 1.8% to the average price. The estimated number of bidders has a positive eﬀect on the sale price, and this
supports the theoretical prediction that prices might increase because of thecompetition eﬀect. The sign of the coeﬃcient of Fuji is negative and statistically signiﬁcant, while that of Shizuoka is statistically insigniﬁcant, indicatingthat logs traded in the Fuji market are cheaper than those traded in the othertwo markets. With January taken as a base category, the months dummiesof February and March are positive and statistically signiﬁcant, while thoseof all the other months except April are negative and statistically signiﬁcant.
There is little diﬀerence in coeﬃcients between model 1 and model 2; thismight be because our data contain only a small number of failed trades.
The diameter of a log can be regarded as an important indicator of theintended use of the log. Thus, timber of a larger diameter is mainly used forconstruction material and timber of a smaller diameter tends to be in demandby paper and pulp manufacturers. Since this suggests that the price premium11

of certiﬁcation might vary for diﬀerent ﬁnal wood products, we then estimate
the impact of certiﬁcation on timber price for diﬀerent sizes of diameter.
The estimated model is basically the same as above, except that we divided
the whole sample according to diameter size into three categories: under
20 centimeters, from 20 to 28 centimeters, and over 28 centimeters. These
categories are typically used for classiﬁcation in the Japanese log market.
The estimation results by OLS and Tobit are summarized in Table 4. Although most coeﬃcients are much the same as in the results discussed above,
there are diﬀerences for some coeﬃcients. The coeﬃcients of certiﬁcation inmodels 3, 4, 6, and 7 are positive and statistically signiﬁcant at the 5% level.
It means that certiﬁcation has a positive eﬀect for logs of a smaller diameter. On the other hand, the coeﬃcients of the certiﬁcation for the largest
diameter category are statistically insigniﬁcant.
Our estimation results show that there is a price premium for certiﬁed
timber of a smaller diameter. The reason for a diﬀerence with respect todiameter size can be attributed to demand structure for timber. In Japan,
timber whose diameter is larger than 26 centimeters is mainly used for construction material. Since paper and pulp manufacturers can use any size oftimber for their products, timber of smaller diameter tends to be in demand
among them. Furthermore, paper and pulp manufacturers are the principal
holders of CoC certiﬁcation in Japan, while the construction sector is stillat the beginning stage in this regard (Owari and Sawanobori 2007). Hencedemand for certiﬁed timber might be mainly driven by paper and pulp manufacturers, and a price premium is found especially for timber with smaller
diameters. The coeﬃcient of Houset−1 also supports this, for it is positiveand statistically signiﬁcant only in the model for the category of largest diameter, which would be used in the construction sector.

12

Table 3: Estimation results on the price premium
OLS
model

Constant

1−9868.89∗∗∗(92.43)−19153.39∗∗∗(329.86)2728.54∗∗∗(55.27)361.76∗∗∗(5.58)
280.96∗∗∗(91.29)−6153.71∗∗∗(71.69)32.12(157.89)−1672.88∗∗∗(169.65)−0.01(0.33)
2.28∗∗∗(0.35)
501.18∗∗(252.10)790.92∗∗∗(235.10)186.22(175.76)−1175.47∗∗∗(245.63)−2841.07∗∗∗(213.48)−3204.48∗∗∗(186.56)−3253.92∗∗∗(184.96)−1336.58∗∗∗(353.04)−1034.44∗∗∗(208.76)−407.03∗∗(185.32)−1007.69∗∗∗(199.02)2604.79∗∗∗(829.41)

R2

0.442

Cedar
P ine
LengthDiameter
Certif ied
Def ects
Shizuoka
F uji
Houset−1
N Bidders
F eb
M ar
Apr
M ay
Jun
Jul
Aug
Sep
Oct
N ov
Dec

P seudoR2
N

Tobit
2
−9927.12∗∗∗(93.99)−19204.01∗∗∗(331.43)2721.39∗∗∗(56.06)365.22∗∗∗(5.66)
284.66∗∗∗(92.09)−6176.60∗∗∗(74.63)−85.56(159.52)−1818.21∗∗∗(172.01)
0.04(0.34)
2.28∗∗∗(0.35)
475.08∗(252.44)811.85∗∗∗(235.42)190.95(175.99)−1160.26∗∗∗(246.43)−2838.43∗∗∗(214.54)−3406.83∗∗∗(193.61)−3478.68∗∗∗(190.57)−1429.87∗∗∗(354.25)−1037.45∗∗∗(209.21)−499.14∗∗∗(187.43)−1025.91∗∗∗(200.83)2512.92∗∗∗(831.53)

0.028
38,00438,004∗ ∗ ∗, ∗∗, and ∗=statistically signiﬁcant at 1, 5, and 10%. Heteroskedasticity-robust standard errors are given in parentheses under estimated coeﬃcients.

13

14

N BiddersHouset−1

F uji

ShizuokaDef ects

Certif ied

Diameter

Length

P ine

Cedar

model

3
diameter < 20−6055.56∗∗∗(88.61)−13328.89∗∗∗(667.97)
1766.61∗∗∗(87.85)849.39∗∗∗(23.30)362.62∗∗∗(116.15)−6659.50∗∗∗(99.79)1030.13∗∗∗(179.66)−126.50(204.10)−0.71(0.44)
0.89∗∗(0.38)OLS
4
20 ≤ diameter ≤ 28
−8184.87∗∗∗(101.76)−17144.24∗∗∗(430.75)
3168.97∗∗∗(75.86)417.97∗∗∗(20.64)276.17∗∗(126.17)−5714.01∗∗∗(103.95)−499.01∗∗(228.94)−1225.28∗∗∗(244.91)0.01(0.55)
1.48∗∗∗(0.51)
5
diameter > 28−14140.03∗∗∗(216.86)−24455.83∗∗∗(560.76)3242.35∗∗∗(102.72)
329.63∗∗∗(16.07)226.40(175.09)−6625.63∗∗∗(162.22)−431.02(279.25)−2931.19∗∗∗(306.25)
1.34∗∗(0.56)
3.04∗∗∗(0.60)

6
diameter < 20−6105.61∗∗∗(91.65)−13377.96∗∗∗(669.47)
1756.49∗∗∗(88.55)854.25∗∗∗(23.75)358.40∗∗∗(118.61)−6675.62∗∗∗(102.59)971.25∗∗∗(182.33)−238.46(208.20)−0.72(0.44)
0.91∗∗(0.38)

Tobit
7
20 ≤ diameter ≤ 28
−8235.87∗∗∗(104.18)−17175.67∗∗∗(431.54)3162.21∗∗∗(77.13)419.29∗∗∗(21.00)286.68∗∗(127.03)−5740.72∗∗∗(107.90)−637.40∗∗∗(232.03)−1300.55∗∗∗(247.42)0.05(0.55)
1.49∗∗∗(0.52)

Table 4: Estimation results for diﬀerent diameters8
diameter > 28−14156.31∗∗∗(217.81)−24478.61∗∗∗(560.74)
3238.61∗∗∗(103.99)330.78∗∗∗(16.13)229.61(175.58)−6694.71∗∗∗(166.96)−490.37∗(280.63)−3045.35∗∗∗(309.56)
1.41∗∗(0.56)
3.01∗∗∗(0.60)

15

0.604

Constant

R2

14,6580.028

519.03(377.34)
598.12∗(348.52)
189.66(253.52)−1338.76∗∗∗(372.53)−2994.38∗∗∗(329.42)−3784.87∗∗∗(281.82)−3490.96∗∗∗(285.41)−1337.81∗∗(563.98)−1118.17∗∗∗(318.26)−1252.17∗∗∗(278.26)−757.87∗∗∗(291.09)−1271.12(1410.36)

15,5760.026−190.08(453.06)
1552.34∗∗∗(407.94)168.41(317.72)−372.54(428.36)−2362.62∗∗∗(369.81)−2988.44∗∗∗(365.57)−2758.01∗∗∗(348.69)−2450.59∗∗∗(595.25)−843.71∗∗(363.46)−30.22(322.23)−1188.44∗∗∗(358.14)
1901.23(1514.51)∗ ∗ ∗, ∗∗, and ∗=statistically signiﬁcant at 1, 5, and 10%. Heteroskedasticity-robust standard errors are given in parentheses under
estimated coeﬃcients.

15,576

7,770

14,658487.93(305.47)211.12(296.52)
378.99∗(225.10)−1236.63∗∗∗(323.21)−2747.43∗∗∗(275.16)−3515.23∗∗∗(266.52)−4478.82∗∗∗(268.33)−1536.93∗∗∗(447.78)−1356.95∗∗∗(246.76)−825.45∗∗∗(222.34)−1084.94∗∗∗(237.60)−713.20(1129.92)

N

0.423

−149.13(452.95)
1528.96∗∗∗(407.80)
165.69(317.70)−406.37(428.00)−2388.71∗∗∗(369.48)−2890.76∗∗∗(360.10)−2667.62∗∗∗(343.80)−2352.36∗∗∗(594.05)−846.85∗∗(363.24)72.63(319.15)−1151.17∗∗∗(355.06)
2027.15(1512.04)

0.045

0.448

534.50(376.86)572.61∗(348.08)
184.33(253.36)−1350.44∗∗∗(371.43)−2995.74∗∗∗(328.01)−3567.77∗∗∗(270.33)−3349.45∗∗∗(279.14)−1261.95∗∗(562.11)−1123.44∗∗∗(317.64)−1175.98∗∗∗(274.87)−743.40∗∗∗(288.37)−1245.06(1404.48)

P seudoR2

Dec

N ov

Oct

Sep

Aug

Jul

Jun

M ay

Apr

M ar

7,770

488.98(304.88)212.25(295.83)
380.99∗(224.64)−1227.08∗∗∗(321.44)−2735.04∗∗∗(272.25)−3428.34∗∗∗(257.15)−4295.99∗∗∗(258.28)−1517.32∗∗∗(446.02)−1347.99∗∗∗(245.85)−798.24∗∗∗(219.37)−1107.70∗∗∗(236.61)−722.37(1123.81)

F eb

4

Discussion

4.1

Implication of Results

Existence of a price premium is important for an eﬀective forest certiﬁcation
system. On the demand side, it is a precondition for a price premium that
customers have a willingness to pay more for certiﬁed wood products thanfor conventional products. Most previous studies have found that there isa positive willingness to pay more by using stated preference surveys. As
the summary in Section 1 shows, previous estimates of a willingness to pay
more than the price of conventional forest products have ranged from 1.4%
to 18.7%.
Our estimation results show that there is a price premium of 1.8% forcertiﬁed timber in the Japanese market. This is in the lower range of theadditional WTP found in other studies. This can be attributed to institutional diﬀerence between Japan and other countries, the eﬀect of supply
volume, or overestimation resulting from use of the stated preference technique. Forsyth et al.(1999), for example, found that the important factors
taken in to account when consumers purchase wood products are quality
and price, and certiﬁcation has less of an impact on their decision making. By focusing on forest certiﬁcation, the stated preference techniques(especially contingent valuation) might put undue emphasis on the issue andmake respondents to pay too much attention to the certiﬁcation. Furthermore, respondents might answer questions in a socially desirable manner,
thereby overstating the importance of a product’s environmental attributes(Anderson and Hansen 2004b).
Our estimation results do not coincide with those of Owari and Sawanobori (2007), who implemented a mail survey of 132 Japanese companies that
had been given a chain-of-custody certiﬁcate and found that they cannot receive a price premium. This can be attributed to two factors. The ﬁrst factor

16

is the delayed growth of a certiﬁcation scheme in Japan. Certiﬁed forest areas in Japan have increased from 179 hectares in 2005 to 1,006 hectares in2010 under the FSC and the SGEC. So in 2005, when Owari and Sawanobori
conducted their survey, there might not have been enough recognition of,and a reputation for, certiﬁed products. The second factor is the diﬀerencein the recipient of the price premium. The premium found in our study is
on logs to be used as a primary input or for intermediate goods, whereas
the premium discussed by Owari and Sawanobori is mainly on ﬁnal wood
products such as paper and furniture. There is a possibility that demand for
certiﬁed timber by manufacturers of ﬁnal wood products would be motivated
not by a price premium but by the goal of communicating with customers to
improve the latter’s perceptions about forest-related industries. While thiswould be a reasonable interpretation, considering the higher level of information asymmetry in the market of ﬁnal goods, one might intuitively expect
a higher level of price diﬀerentiation to be realized in a market closer to theﬁnal consumer. Further investigation of diﬀerent price premiums at diﬀerent
stages of the supply chain is a subject for future studies.

4.2

Post-certiﬁcation Equilibrium

According to Sedjo and Swallow (2002), there are three possibilities in regard
to equilibrium prices under a forest certiﬁcation scheme:

1)P C > P N C > P 0 ;2)P C > P 0 > P N C ;3)P C = P N C > P 0 ,where P C denotes the price of certiﬁed wood, P N C denotes the price of
non-certiﬁed wood, and P 0 denotes the equilibrium price under the precertiﬁcation scheme. Sedjo and Swallow (2002) deﬁne a decrease in the supply

17

of non-certiﬁed wood as the success of the certiﬁcation scheme. It is assumed
that producers can choose to produce their products either eco-friendly or
eco-unfriendly products (woods). Producers make their decision on the basisof their proﬁt calculations in comparing the two options, either eco-friendly
or eco-unfriendly woods. If certiﬁcation is costly to individual producers, a
price premium of eco-friendly woods over eco-unfriendly woods is assured inmarket equilibrium or P C > P N C . Suppose the certiﬁcation cost is so lowthat the higher price in the certiﬁed markets can generate suﬃcient revenues
to cover the higher costs. Then some producers will exit the non-certiﬁed
market and enter the certiﬁed market. The decrease of supply in the noncertiﬁed market also pushes the price P N C up. This case describes the ﬁrst
possibility, P C > P N C > P 0 .
Alternatively, suppose the certiﬁcation cost is rather high. The pricepremium is insuﬃcient to compensate the marginal producer of certiﬁedwood. As a result, certiﬁcation can induce some producers to return tonon-certiﬁed production. The increase of supply in the non-certiﬁed market
also depresses the price P N C . This case corresponds to the second possibility,
P C > P 0 > P NC.
If certiﬁcation is not costly and the supply of eco-friendly woods is suﬃciently large relative to demand from eco-consumers, then certiﬁcation may
fail to generate a price premium and both eco-friendly and eco-unfriendly
woods are sold at a common price. In addition, if eco-consumers reveal
a willingness to pay a premium for eco-friendly woods, the common pricewould become higher than the initial price. Under this situation, the third
possibility, P C = P N C > P 0 , can arise.
To make a comparison with the theoretical predictions by Sedjo and Swallow possible, we must consider the relationships that exist among the pricesof certiﬁed wood (P C ), of non-certiﬁed wood (P N C ), and of pre-certiﬁcation
equilibrium (P 0 ). The estimation result in Section 3.2 suggests that certiﬁed
wood has a price premium: (P C > P N C ). What we need to do next is to in-18

vestigate the relationship between P 0 and P N C . If we ﬁnd that P N C is higher
than P 0 , then the Japanese forest certiﬁcation scheme can be regarded as
successful.

We estimated a model to clarify the relationships among P C , P N C , andP 0 . The data used is from the log auctions of the Tenryu market from Julyto December in 2009, 2010, and 2011. The Tenryu market did not trade any
certiﬁed logs in 2009; assuming that the price levels of the Tenryu market are
not aﬀected by prices in the other markets, we can consider the 2009 dataas that of the pre-certiﬁcation equilibrium. Due to the limited availabilityof data for 2009, we are restricted to using only data for the second half ofthe years 2009 to 2011. The estimation model is basically the same as in theprevious section, except for the inclusion of dummy variables for sale pricesof certiﬁed and non-certiﬁed logs in the post-certiﬁcation period (2010 and2011). The prices were adjusted to 2010 prices by using the average consumer
price index.
The estimation result by OLS is summarized in Table 5 (dummy variables
for months were omitted). The coeﬃcient of P C is positive and statisticallysigniﬁcant at the 5% level. The coeﬃcient of P N C is negative and statisticallysigniﬁcant at the 1% level. This indicates that the price of non-certiﬁed wood
P N C is lower than the pre-certiﬁcation equilibrium price P 0 , while the priceof certiﬁed wood P C is higher than P 0 . Our estimation result indicatesthat the Japanese certiﬁcation system can be regarded as belonging to thesecond case (P C > P 0 > P N C ). It means that certiﬁcation does not leadto a decrease in non-certiﬁed logs, even though there is a price premium forcertiﬁed logs.
The second possibility presented by Sedjo and Swallow corresponds tosituations where the cost of certiﬁcation is high. Although we cannot obtainenough detailed information about the cost of forest certiﬁcation in Japan,

19

Table 5: Comparing P 0 , P N C and P C
OLS
model

Constant

9−11272.62∗∗∗(112.85)−15711.98∗∗∗(596.30)
2500.03∗∗∗(60.56)511.37∗∗∗(7.33)−5571.36∗∗∗(107.07)281.66∗∗(132.01)−346.20∗∗∗(123.60)
1.00∗∗∗(0.18)−0.25(0.29)
785.67∗∗∗(196.44)690.66∗∗∗(168.75)
1816.48∗∗∗(192.83)1346.33∗∗∗(173.19)1214.92∗∗∗(197.48)−2218.28∗∗∗(550.27)

R2

0.374

Cedar
P ine
LengthDiameter
Def ects
PC
P NC
Houset−1
N Bidders
Aug
Sep
Oct
N ov
Dec

P seudoR2
N

Tobit
10
−11270.85∗∗∗(112.86)−15720.33∗∗∗(597.69)
2500.97∗∗∗(60.57)511.64∗∗∗(7.34)−5569.48∗∗∗(107.11)279.27∗∗(132.03)−353.66∗∗∗(123.69)1.01∗∗∗(0.18)−0.25(0.29)
782.82∗∗∗(196.50)689.75∗∗∗(168.72)
1819.55∗∗∗(192.83)1345.21∗∗∗(173.20)1207.40∗∗∗(197.53)−2244.26∗∗∗(550.83)

0.022
34,88034,880∗ ∗ ∗, ∗∗, and ∗=statistically signiﬁcant at 1, 5, and 10%. Heteroskedasticity-robust standard errors are given in parentheses under estimated coeﬃcients.

20

some anecdotal evidence suggests that it is considerably high. As a rough estimate, FSC Japan states that the cost of certiﬁcation for forest management
is 1,500 to 4,000 yen (approximately 18.15 to 48.4 US dollars) per hectare
at the initial process and 500 yen to 1000 yen (6.05 to 12.1 US dollars) per
hectare as an annual charge. These ﬁgures are several times higher than
the average cost of initial certiﬁcation (4.975 US dollar for FSC and 2.17 US
dollars for Sustainable Forestry Initiative) reported by Cubbage et al. (2003)
for forest land in North Carolina.

5

Conclusion

This paper investigates the impact of forest certiﬁcation on log prices in a
Japanese market. On the basis of the results of our estimation, which used
real auction market data, we can conclude that forest certiﬁcation has apositive price premium on logs of small diameter. However, this does notmean that forest certiﬁcation provides enough of a premium for sustainable
forest management, because the estimated impact is relatively low comparedto other factors.
As a major importer of timber from the South-East Asia region, Japan
has a signiﬁcant inﬂuence on the development of forest certiﬁcation systems
in Asia. The existence of a price premium found in this study provides goodprospects for certiﬁed wood products to be imported from other regions toJapan. Consider what has happened in Finland: although there is no strong
demand for certiﬁed timber in that country, Finnish companies trading intimber have turned to certiﬁed timber, so that they can export to the United
Kingdom or Germany, where there is a strong demand for certiﬁed products.
This means that whether companies will take the trouble to be a certiﬁed
company, or not, depends entirely on the preferences of their customers, suchas importers or ﬁnal consumers (Owari et al., 2006). Stimulating the demandfor certiﬁed products would be a key element for the diﬀusion of certiﬁcation

21

systems throughout the Asian region.

Acknowledgement
We gratefully acknowledge the cooperation of the Shizuoka Forest Owners’
Association in providing us data for its log auction markets. Helpful comments from Yasushi Shoji is also acknowledged. Kenji Takeuchi would liketo thank the Department of Economics at the University of Gothenburg for
giving him the opportunity to conduct research as a visiting researcher.

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27