Optimum harvesting time and clone choices for eucalyptus growers in Vietnam

Forest Policy and Economics 15 (2012) 60–69

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Optimum harvesting time and clone choices for eucalyptus growers in Vietnam Nguyen Huu-Dung a,⁎, Youn Yeo-Chang b, c a b c

Department of Economics, Vietnam Forestry University, Hanoi, Viet Nam Department of Forest Sciences, Seoul National University, Seoul, Republic of Korea Research Institute for Agriculture and Life Sciences, Seoul National University, Seoul, Republic of Korea

a r t i c l e

i n f o

Article history: Received 19 October 2010 Received in revised form 15 September 2011 Accepted 26 September 2011 Available online 18 November 2011 Keywords: Eucalyptus clone Tree farming Optimal harvesting time Vietnam

a b s t r a c t This paper investigates the productivity and optimal rotation for economic timber management of Eucalyptus urophylla S.T Blake clones being planted in Northeast Vietnam in Fluvic Gleysol and Ferric Acrisol soils. In the first section of the paper, timber yield functions for all eucalyptus monoculture clones and seedlings are identified. Next, the biological optimum rotation period for maximizing sustained yield is calculated based on the yield functions for each soil type. In the last section, the economically optimal rotation (EOR) lengths for all clones and seedlings planted in the two types of soil are calculated using a modified Faustmann model. The results indicate that eucalypts in Fluvic Gleysol will produce larger timber yields than in Ferric Acrisol. Among the clones commonly planted in Northeast Vietnam, eucalyptus clones U16 and PN14 can yield the largest timber volumes in Fluvic Gleysol and Ferric Acrisol, respectively. Our EOR model reveals that EOR lengths of eucalyptus plantations in Northeast Vietnam are longer than the biological rotation time by 1– 3 years under the governmentally subsidized credit scheme for rural households. If growers borrow from commercial and private entities, such rotation period will be substantially shortened and negative site values will appear in a number of cases. Nevertheless, wherever eucalyptus clones are economically qualified, their EOR length is longer than what is currently practiced. To capture the highest profits from eucalypt plantations, growers should extend their current farming business cycle of 7 years to 14–18 years under the subsidized credit scheme and to 10–12 years under the commercial borrowing interest rate. As increasing land use profitability is of great concern across the region, these findings are of practical importance for Vietnamese farmers in choosing clones, land lots, and economic optimal rotation for their farming businesses. © 2011 Elsevier B.V. All rights reserved.

1. Introduction Eucalyptus is one of the most important exotic species for supplying raw wood materials and generating considerable cash incomes for Vietnamese farmers. In some areas, tree growers have earned 3– 4 times more income than with alternative agriculture activities (Midgley et al., 1997). Many Vietnamese farmers, therefore, have invested in eucalyptus plantations in their efforts to maximize their returns of land use (Thiep, 1996). Until 2001, eucalypt plantations increased to 398,000 ha, accounting for 26.5% out of a total 1.5 million ha of plantation forests in Vietnam (MARD, 2005a). This expansion trend of eucalypt plantations is expected to continue in the coming years, as eucalypt has been proposed by the Vietnamese government as one of the main species to be used (MARD, 2005b; Kha et al., 2003a) to achieve 1.8 million tons of cellulose production per year by 2020 (Ministry of Industry, 2007). Despite the increasing reliance on eucalyptus, the Vietnamese grower's decision regarding harvesting time is still largely based on tree ⁎ Corresponding author. Tel.: + 84 433 840894; fax: + 84 433 840063. E-mail addresses: [email protected] (N. Huu-Dung), [email protected] (Y. Yeo-Chang). 1389-9341/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.forpol.2011.09.011

volume in various field trials rather than on economic reasoning. In recent years, some research has focused on timber yield and biological productivity (e.g., Kien et al., 2009; Kha et al., 2003b; Tuan, 2001), while a few other authors (e.g., Midgley et al., 1997) have instead focused on some financial returns, such as net present values and costbenefit ratios, leaving the EOR length unexplored (Bien, 2006). Due to the lack of optimal rotation information, most tree farmers have cut their crops at 7–8 years of age, thus forgoing potential income gains due to premature harvesting. This problem can be even more serious under the high inflation in recent years. As farmers are exposed to complex problems involving not only silviculture, but also many dimensions of managing a farm business, such as cost, capital, and risks over long periods (Pannell, 1996), determining the most efficient time to harvest a crop is becoming an increasingly critical concern for most Vietnamese tree growers. The objective of this paper is to identify the best-performing clones of eucalypt, coupled with their EORs, particularly for new Eucalyptus urophylla S.T Blake clones, namely, PN14 (a hybrid by the Phu Ninh Forest Research Center), U6, GU8, and U16 (imported from China), which are being planted large-scale in various soil types. This paper also compares their timber yields to that of seedlings to ascertain timber yield improvement. In the first section of

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the paper, timber yield functions for all eucalypt monoculture clones and seedlings are presented. Next, the biologically optimum rotation period for maximizing a sustained yield is computed based on the yield functions for each soil type. In the last section, the EOR ages for all clones and seedlings are calculated using a modified Faustmann equation involving exponential constant inflation.

2009). Because eucalypt is a fast-growth species with a fairly short rotation, we used the current annual increment (CAI) instead of the periodic annual increment. The CAI function was developed from the stand yield Eq. (1), which, as will be shown in the empirical result, provides the best predicted statistics. The following CAI function was obtained

2. Theoretical framework

fc ¼ qðt Þ′ ¼

2.1. Timber yield functions In a timber yield function, our concern is mostly total volume and the attenuated speed of the growth rate; therefore, we employed three-parameter growth equations – Korf, Weibull, and an exceptional case of the Mitscherlich function – to preliminarily compare their fitness in modeling eucalyptus growth. The Korf equation processes a sigmoid shape, which was recommended by MARD (2006) for both its simplicity and accuracy in describing stand volume growth of a number of species in Vietnam. Consistent to this finding, several other researchers have also applied this function with success (e.g., Anderson and Luckert, 2007; Remes, 2006). The Mitscherlich function does not have any inflection in the growth process, yet it is a candidate in this study due to the possibility that yield, following Liebig's theory, may be proportionate to the increase in the limiting nutrients available in the soil (e.g., natural organic soil amendments), by which eucalyptus clones may exhibit rapid early growth distinct from the usual S-shaped pattern of the Korf curve under certain soil conditions. The Weibull function is an equation capable of generating curves with diverse unimodal shapes of sampling data distributions (Bailey and Dell, 1973). This function was found to be a good empirical model for stand growth, as in Son et al. (1997). Korf (1939): −a

qðt Þ ¼ ke tb

ð1Þ

Mitscherlich (1919):
 −at qðt Þ ¼ k 1−e

−a

e tb :

ð4Þ

The necessary condition maximizing the CAI is q(t) ″ = 0. Thus, the optimal solution is max

tc

 ¼

1 ab b : bþ1

ð5Þ

Substituting (5) into (4), we have the maximum value of CAI max

fc

 −ðbþ1Þ −ðbþ1Þ b ab ¼ kab e b : bþ1

ð6Þ

The MAI function can be formulated as −a

fm ¼

qðt Þ ke tb ¼ : t t

ð7Þ

The maximization condition for MAI is fm′ = 0. Solving for the optimal solution yields max

tm

1

¼ ðabÞb :

ð8Þ

Substituting (8) into (7) to produces the maximum value of MAI max

fm

¼

k

−1

1 b

ðabÞ

eb :

ð9Þ

The biological optimum rotation period is realized at the intersection of MAI and the current volume increment, which is fc = fm, or −a

ð2Þ

kab −ab k:e tb ; et ¼ bþ1 t t 1

solving for t gives t ¼ ðabÞb :

Weibull (1951):   −at b : qðt Þ ¼ k 1−e

kab t bþ1

ð3Þ

Where: q(t) is volume of tree at age t with t ∈ (1, n); e is the base of natural logarithms (e = 2.718); k is the upper asymptote at which q(t) gets its maximum value; and k, a, b are parameters to be estimated statistically. The selection of a timber yield model is first based on biological evaluation over the parameters of the least square regressions to ensure the estimated parameters fall in a meaningful interval. The fitness (the coefficient of determination, R 2) is then used to evaluate the overall satisfaction of the non-linear model (Ryan, 1997, pp. 419 and 424). Finally, the root mean square error, RMSE, is used to confirm the accuracy of the estimates (see Corral-Rivas et al., 2007). 2.2. Biological optimum rotation Our biological optimization rotation problem is derived from the maximum sustained yield of timber inside the bark (see also Liao et al., 2003; Olschewski and Benitez, 2010). This traditional approach can be achieved by harvesting timber when the mean annual increment (MAI) equals the periodic volume increment (Bettinger et al.,

ð10Þ

Eq. (10) equals Eq. (8), meaning the biological optimum rotation time also occurs at the culmination point of MAI. This optimal condition allows the tree growers to maximize their wood production. It is, however, independent of economic variables and thus does not entail an economic basis for tree growers to optimize their profitability. We now incorporate economic variables into the grower's objective function using the Faustmann framework. 2.3. Economic optimal rotation Traditionally, the Faustmann model (1849) assumes a constant cost and price of timber over the infinite time horizon. The modified model used in this paper, however, allows prices and costs to change over time under the inflation effect (see Pearse, 1990 for a review) because the impacts of inflation on profitability are significant (Howard, 1995), but this is still largely unexplored in case studies in Vietnam. Costs include direct costs (e.g., the costs of planting, silviculture, managing, marketing, and interest forgone) and indirect costs (e.g., the opportunity cost of land). Costs bear an interest rate, i, which is the borrowing interest rate of growers. The volatility of price and cost is internalized into the model by assuming that these variables change along with a consumer price index r. W is the profit of growers from an infinite series

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Current annual increment

of rotation; p is the net stumpage price that equals the selling price minus the harvesting cost measured for 1 m3; and c is the set-up cost of a unit area. We assume that the saplings are grown at the outset of each rotation without significant delay (within one year). The optimization problem can be formulated as

a

kab tb e tb 1

Incremental growth in volume

a

 
 pqðt Þ−ceði−rÞt rt qðt Þ ðr−iÞt 2ðr−iÞt 3ðr−iÞt W ¼ pe : −c 1þ e þ e þ e þ … ¼ eit eði−rÞt −1 ð11Þ

b

ke t t

0

t* '

The first-order necessary condition for the optimal solution is W′ =0, which is rewritten as pqðt Þ′ ¼

Mean annual increment

Year Growth rate of return from delaying harvest

q (t) q(t)

q (t ) ' q (t ) c / p

Growth rate of cost

pqðt Þði−r Þeði−rÞt cði−rÞeði−rÞt − ði−rÞt : eði−rÞt −1 e −1

Growth rate of capital cost due to delaying harvest

1/ t

Growth rate of return

Some manipulations result in the optimum condition " pqðt Þ′ ¼ ði−r Þpqðt Þ þ ði−r Þ ð

pqðt Þ−ce i−r Where S ¼ eði−rÞt −1

ði−r Þt

pqðt Þ−ce eði−rÞt −1

i r 1 e (i r )t

# :

Þt

is the site value; and

L ¼ ði−r ÞS is the land rent or opportunity cost of the land:

ð12Þ

ð13Þ ð14Þ

This modified Faustmann condition implies that the growers should wait until the time when the incremental value of the net revenue growth (the left-hand side of Eq. (12)) equals the marginal cost of delaying the timber harvest (the right-hand side of Eq. (12)). Note that the marginal cost consists of the cost of interest adjusted for inflation on the capital embodied in the timber (the first term on the right-hand side) and the land opportunity cost L (the second term on the right-hand side). An illustration of the optimum condition can be derived by rearranging Eq. (12), which becomes qðt Þ′ i−r ¼ : qðt Þ−c=p 1−e−ði−rÞt

ð15Þ

In Fig. 1, the economic optimum rotation time (t**) can be shorter or longer than biological optimal time (t*), depending on the interest rate (r) and the level of cost over price (c/p). As a particular case for t * * ≥ t *(also consult Binkley, 1987), first, c/p should be large enough to keep the growth rate of return curve distant from the curve q′(t)/q(t). However, c/p must be low enough to keep W ≥ 0. Mathematically, this condition can be derived from Eq. (11) c qðt Þ ≤ : p eði−rÞt

ð16Þ

ð17Þ

And then rewrite the first-order condition, maximizing the biological optimum rotation (7) qðt Þ′ 1 ¼ : qðt Þ t

0

t*

t**

Year

Fig. 1. Optimal biological rotation (t*) and economical rotation (t**) for economic timber management.

Equate (17) and (18) to have " !# c 1−e−ði−rÞt ¼ qðt Þ 1− : p ði−r Þt

ð19Þ

Substituting (19) into (16) yields " !# qðt Þ 1−e−ði−rÞt ð Þ ≥q t 1− : ði−r Þt eði−rÞt Therefore, the condition of r is ði−r Þ≤1=t:

ð20Þ

Graphically, from Fig. 1, we can observe that when the real interest rate (i-r) is relatively small, the growth rate of the capital cost curve shifts closer to the curve of the inverse value of t, making t** increase. Mathematically, when (i− r) → 0, using L'Hospital's rule, we observe lim

i−r

ði−r Þ→0 1−e−ði−r Þt

¼

1 : t

ð21Þ

3. Materials and methods 3.1. Sampling plot selection and population quality

The condition of r, such that t** equals or greater than t*, is derived in the subsequence. First, we rewrite the economic optimum condition Eq. (15) as qðt Þ′ ði−r Þ−cði−r Þ=pqðt Þ ¼ : qðt Þ 1−e−ði−rÞt

1

ð18Þ

This study examines eucalyptus seedlings and four eucalypt clones: PN14 (a hybrid by the Phu Ninh Forest Research Center), U6, GU8, U16 (imported from China), and seedlings. These clones and seedlings were planted in Bacgiang in Northeast Vietnam (Fig. 2) at two selected sites, representing two main soil types in the Northeast: a clay mineralogy affected by the floodplain (Fluvic Gleysol) and a gray degraded soil on granite (Ferric Acrisol). These sites are situated at heights of 101–150 m above sea level and at coordinates of approximately 21°28′ N and 105°37′ E. The climate in the study area is tropical, with an average temperature of 22.3 °C and a humidity range of 73–87%. Precipitation is abundant, reaching 1434–1644 mm per year.

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63

Fig. 2. Location map of the studied site. The map is adapted from http://home.vnn.vn/english/map.

The original experimental design was a randomized complete block, with 4 blocks containing 3 plots for each clone per soil type and 1 block containing 1 plot for seedling per soil type; hence, there were 24 total plots in both sites for clones and 2 for seedlings, ensuring 3 replications for measurement were made on each clone at a soil type, except those for seedlings, due to having only one seedling plot at harvestable age. The plots were 1000 m 2 in size (25 × 40 m) and were spatially separated within the landscapes. The trees were planted in monoculture in May 2000 under uniform treatment: they were fertilized with 400 kg of NPK5-10-3 per hectare at establishment, with weeding control for the first 3 years and no thinning and pruning. The spacing within the plantations was 2.5 × 3 m. Prior to statistical analysis, diameters at breast height (D1.3) of all sampling plots within each clone and soil type were measured and tested for normality using histograms in combination with the Shapiro– Wilk test. The result of D1.3 revealed that the Gaussian distribution tendency appeared in PN14 and GU8 in Fluvic Gleysol (FG), U6 in Ferric Acrisol (FA) and U16 in both soils. Their distributions had normal shapes, and all p values in the Shapiro–Wilk test were greater than 0.05. In contrast, clone PN14 in FA had kurtosis (somewhat high peaks and flat fails) of −0.760, −0.756, and −0.781 in plots 1, 2, and 3, respectively, negative skewness (fewer big trees) and a slight departure from normality at a significance level of 5% (p equals 0.038, 0.013 and 0.005 in plots 1, 2 and 3, respectively). Likewise, the D1.3 of U6 in FG (p = 0.01 in plot 3) and GU8 in FA (p = 0.00 in plot 1) were more or less skewed and tended to follow non-normal distribution. The existence of both normality and non-normality in the sample data leads us to use two methods to check if the results obtained with different sampling plots for one clone and soil type varied significantly or if the variation was to be expected among different samples of the same population (Kruskal and Wallis, 1952). Due to having relatively large sample sizes (over 100 samples for every plot), a single-factor ANOVA test was employed for normal-distribution populations, despite some slight imbalance of the data sets (Shaw and Mitchell-Olds, 1993). Meanwhile, the Kruskal–Wallis test was used for non-normal populations. Our result (see online Supplementary data in Appendix) showed that the observed Kruskal–Wallis test statistics were less than the chisquare table distribution, with two degrees of freedom (Hcritical = 5.99; Hstatistic = 3.90–5.47 for particular plots). Therefore, the null

hypothesis (the sampled trees are from the same population) should be accepted at the 5% significance level. The same conclusion was also drawn from the single-factor ANOVA test: the F-statistic significance was greater than 0.05 (Hstatistic = 0.06–0.69), rejecting the null hypothesis that clones come from different populations. As a result, 3 sampling plots for one clone in a soil type can be considered as a statistically identical plot. Thereafter, we could expand subplot volumes to a per-hectare volume and could compare timber volumes across different clones. 3.2. Volume of a log and a hectare Volume functions were derived by destructively sampling 26 standard operational trees in every sampling plot subset in 2007. These trees were conditioned through diameter breast height (D1.3) and total height (Htop): (i) their D1.3 and Htop equaled or were within ±5% of the average D1.3 and average Htop of each sampling plot, and (ii) these trees had normal growth, straight shapes, well-proportioned bodies and crowns, no diseases, and were planted around the center of the respective plots. All selected trees were cut down. The stems were stripped of branches, and 5-cm disks were sectioned at intervals that were 1 m long and 1.3 m high, except the top sections of trees, at which the intervals were 1–3 m long. The upper surfaces of the discs were planed smoothly to make the cores visible. The growth rings were counted, and diameter of each growth ring was measured in four perpendicular directions in centimeter precision under stereomicroscopes. The log volume inside the bark was then calculated as a sum of sectional volumes using Smalian's formula (see Avery and Burkhart, 1994). The average volume of sampling trees was calculated by dividing the sum of the sampling trees' volume with the number of sampling trees in their respective plots. The timber volume per hectare of each soil type was the average volume per tree multiplied by the stand density per hectare. These data (Appendix) were used as inputs for estimating the growth functions. 3.3. Optimum rotation age Growth functions and biological optimum rotation ages were estimated by regression using SPSS version 10. A 5% level of significance was assigned to define the goodness of fit of the models. The

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N. Huu-Dung, Y. Yeo-Chang / Forest Policy and Economics 15 (2012) 60–69

estimated parameters of the selected models were replaced into Eqs. (1) and (4)–(9) for statistical inference. Economic optimization rotation ages were computed based on the modified Faustmann model. Financial information and the consumer price index were collected from the Northeast Forest Company's survey and the General Statistic Office of Vietnam for the period 2000–2007. The stumpage value is calculated by multiplying the timber volume with the net stumpage price, in which the selling price was taken from the base year market price of 325,000 VND/m 3. The price and cost were fully compensated for an inflation of 6.3% per year (which was the average consumer price index of Vietnam from 2000 to 2007), as they were shown in the investigated period (the nominal price increased throughout the studied period, from 320,000 VND/m 3 in 2000 to 585,000 VND/m3 in 2007). This trend reflected the regional conditions. In the Northeast, most eucalyptus growers have small market outlets (i.e., they produce small volumes per lot) and do not have the means to transport timber (Hieu, 2004). Therefore, the farmers often depend on timber demand of the local paper mills, which are, in fact, largely owned by the government. Very few growers can market their timbers directly to other buyers (Hieu, 2004), especially when there are no substantial woods readily imported or exported from the region by foreign operators (Bueren, 2004). The world stumpage price has a very limited effect on this sub-region market. Instead, there has been a dominant government control over the local pulpwood price (Bueren, 2004) under the policy of focusing on inflation control by using price controls. The government, through the Vietnam Paper Corporation, sets a price range for pulpwood to be bought at the state paper plants (Bueren, 2004). Consequently, the nominal stumpage prices are generally under the government control: “stabilization” measures tend to be imposed when the price outpaces costs, thus keeping the price relatively steady in real terms (the short term swings are ignored because our focus in this paper is largely on forest crops over the long-term). The stumpage value allows us to compute the site value by Eq. (13). The initial total set-up cost varies from 9,717,874 VND to 10,800,224 VND per hectare, depending on particular clones. The harvesting cost is treated uniformly for all clones at 176,059 VND/m 3. Costs are computed with grower's borrowing interest rates of 8.4% on average from the Vietnam Bank for Social Policies (VBSP) and the Vietnam Bank for Agriculture and Rural Development (VBAD), which are two major formal micro-financial sources of credit for rural households (Dufhues et al., 2004). This interest rate reflects the opportunity cost of capital, with risk-adjusted premium subsidies by the government reflecting the government's support of the rural poor and the social desire to also pursue environmental externalities in the private sector. The land rent calculated by Eq. (14) is the interest cost embodying the expected inflation on the site value that the growers have to bear with (i.e., the opportunity cost of the land). The annual incremental cost of growers includes the annual interest on the crop value due to delaying harvest and the maximum opportunity cost that land growers have to bear. In a continuing succession of crops, the growers wait until the incremental gain in value no longer exceeds the incremental cost of delaying the timber harvest (Pearse, 1990), which is the year we can realize the highest calculated site value from a treegrowing business by the modified Faustmann model.

a tree can reach, it should not have a negative value. Therefore, the Mitscherlich curve is rejected. The Weibull curve behaves better than the Mitscherlich curve, with goodness of fit statistics of approximately 0.99 for all clones, but its k ranges from 85.15 to 245.37, which is substantially lower than the observed value of a maximum tree volume in reality; therefore, it is unrealistic to consider it a good model. Meanwhile, the Korf function has a slightly high asymptote, but for a short rotation of eucalyptus, this problem has very little impact on the accuracy of the model. The Korf function possesses the highest goodness of fit, with approximately 99% of variation in volume around its mean being explained by the model. The RMSE of the Korf function is also smaller than that of the Weibull function and is at a low level. Specifically, the RMSE values of the Korf functions of clones GU8, PN14, U6, and U16 and seedlings in FA are 0.899, 1.361, 0.974, 0.574, and 0.480, respectively; in FG, the values are 0.619, 0.924, 0.950, 1.134, and 1.068, respectively. The Korf function shows the best predicted statistics and was therefore used to depict the forest growth curve in our analysis of optimum rotation age. We estimated growth functions using the Korf curve to have parameters a, b and k. The results are summarized in Table 1.

4.2. Biological optimum rotation time The parameters generated from the regressions of the growth function are substituted into Eqs. (7)–(9) and are shown in Table 2. An illustration for the two best performing clones in the two different soil types is shown in Fig. 3. On the basis of timber production, our results in Table 2 show that all clones grown in FG have higher timber yields than those grown in FA. Furthermore, the growth curves (substituting the parameters in Table 1 into Eq. (1)) clearly demonstrate that the clones in FG shoot up earlier and stay in the mature phrase longer. This indicates that the clones excel in FG, which is moister and more fertile than FA due to the natural organic materials added from surrounding sources (Hai and Kazuhiko, 2008). This finding draws a parallel conclusion to Henri (2001) concerning soil factors affecting Eucalyptus urophylla growth rates in Western Venezuela. All clones in our study produced substantial improvement in timber yield over the seedlings. In FG, clone U16 attained the highest MAI of 30.7 m 3 timber per hectare at the age of 14 years. The MAI of this superior clone exceeds the MAI of seedlings by 2.1-fold, while the MAI values of clones PN14, U6, and GU8 only exceed those of Table 1 Parameter estimates of growth functions of average Eucalyptus urophylla clones and seedlings grown in Northeast Vietnam. Clone

Soil

GU8

FA

604.993

9.291

0.775

FG

1154.634

9.704

0.717

FA

782.310

10.831

0.894

FG

1212.500

9.259

0.769

FA

511.935

9.624

0.886

FG

857.091

10.344

0.854

FA

786.249

8.300

0.764

FG

1964.879

8.834

0.667

FA

499.254

10.809

0.852

FG

939.216

8.871

0.659

PN14

U6

4. Results and discussion 4.1. Growth function The results of the fitness of growth models reveal that the Mitscherlich curve has the lowest R 2 (R 2 = 0.978–0.980 for particular clones) and that its estimated parameters are all negative, ranging from −24.10 to −5.67 for k and from − 0.27 to 0.36 for a. Because k is the asymptote of the function representing the maximum volume

U16

Seedlings

k

a

b

Growth rate at age t 7:202 t 1:775 6:956 t 1:717 9:684 t 1:894 7:118 t 1:769 8:524 t 1:886 8:838 t 1:854 6:344 t 1:764 5:891 t 1:667 9:219 t 1:852 5:844 t 1:659

N. Huu-Dung, Y. Yeo-Chang / Forest Policy and Economics 15 (2012) 60–69 Table 2 Mean annual increments (MAI), maximum mean annual increments (fmmax), and biomax logical optimum rotation times (tm ) of average Eucalyptus urophylla clones and seedlings grown in Northeast Vietnam. Clone GU8

Soil

MAI

FA

−9:291 604:993e t0:775

FG PN14

U6

t

−10:831 t 0:894

FA FG

1212:501e t

FA

FA FG

Seedlings

−9:705 1154:635e t0:717

782:310e t

FG U16

t

FA FG

−9:259 t 0:769

−9:625 511:935e t0:886

t 857:091e t

−10:345 t 0:854

−8:300 786:249e t0:764

t

−8:834 1964:879e t0:667

t 499:254e t

−10:809 t 0:853

−8:871 939:216e t0:659

t

fmmax

max tm

13.035

13

19.116

15

20.172

13

25.705

13

14.724

11

20.748

13

18.947

11

30.701

14

11.428

14

14.109

15

may be somewhat over-stated. Nevertheless, k does not affect the biological optimum rotation time, as the function of maximum rotation (10) is totally independent of k. 4.3. Economic optimum harvesting time

seedlings by 1.8-, 1.5-, and 1.4-fold, respectively. In contrast, the best growth rates in FA were recorded for clone PN14, followed by U16, U6, GU8, and seedlings. The highest MAI for clones grown in FA was PN14, at the age of 13 years. Among the clones, U16 was the outperformer in FG, while clone PN14 performed the best in FA. These findings somewhat contradict Kha et al. (2003b), who reported the superiority of clone PN14 over clone U16 for young-age eucalyptus stands at 39 months in central-northern Vietnam. However, Borralho et al. (1992) and Griffin and Cotterill (1988) warned that using earlyage trees as an indicator might lead to a substantial bias in timber estimation. This suggests a possibility that the difference between our findings and those of Kha et al. (2003b) may be due to the difference of the tree ages in the experiments and the responses of the clones to the differences in the climatic and soil conditions of the sites studied. Nevertheless, the growth of these two clones far exceeded the others and was almost 2 times greater than the growth of the seedlings, indicating their superiority. It is noted that the estimated value of the parameter k, which represents the highest potential growth of a tree (see Table 1 for the calculated value), is larger than the maximum value of volume obtained from field surveys. This problem renders the growth curves rather stiff at high ages; thus, the predicted values for volume at older ages

Incremental growth in volume (m3/yr)

65

The analysis results for economic optimization rotation age are summarized in Table 3. Illustrations of the economic optimal rotation ages for the two best-performing clones, PN14 in FA and U16 in FG, are shown in Figs. 4 and 5, respectively. Our findings indicate that the EOR of clones is higher than the biologically optimal rotation period for the formal rural financial market in Vietnam. This finding can be understood; as these clones have remarkable fast-growing rates (their MAI values are 2–3 times greater than the MAI of a fast-growing species by definition of FAO Staff (1965)). In addition, the farming business is enjoying an average interest rate of 8.4%, which is low when it is converted to a real term, i-r, of 2.1%. This rate of real interest is well below the inverse value of t** (the optimal economic rotation age), by which the condition that t** N t* is satisfied (1/t** N 0.07 for all clones). Graphically, from Figs. 4 and 5, the curve representing the growth rate of capital cost due to delaying harvest (open diamond) is located close to the curve of the inverse value of t (filled diamond), due to the low real interest rate (see Eq. (21)), making the intersection point t** fall to the right of t*. Indeed, as long as the nominal interest rate is lower than 12.9% (equivalent to the real interest rate of 6.6%), with all other things being equal, our sensitivity analysis illustrates that the EOR time will always be longer than the biologically optimal period. This indicates that the growers are enjoying a favorable interest rate; therefore, the interest cost after offsetting for inflation falls behind the net return from a higher stock. However, the ratio of the establishment and managing costs per hectare to the price of wood per cubic meter equals approximately 30, which is high enough to keep the business profitable, but not too high to cause the economically optimal time to fall behind the biologically optimal time. This situation was also shown in Binkley (1987). Overall, the nominal interest rate for the growers is likely to be below the opportunity cost of an alternative investment forgone (e.g., the interest rate has been subsidized). Our results in Table 3 and Figs. 4 and 5 confirm that the EOR ages are longer than the biologically optimal rotation ages and exceed the current cutting scheme by 2–2.5×, which is usually only 7–8 years. This anticipates substantial gains if the current rotation period is adjusted to the optimal economic rotation. A question thus arises: why do farmers decide to harvest their farms so early? The first interesting observation is that the threshold point of the annual incremental growth of trees occurs at around year 7 (obtained

45 40 35

14

30 25 13

20 15 10 5 0 0

5

10

15

20

Age (year) Fig. 3. Biological optimal rotation age of the two best clones, PN14 in FA and U16 in FG, in Northeast Vietnam. CAI in volume (open diamond for PN14 in FA, open circle for U16 in FG); MAI in volume (filled diamond for PN14 in FA, filled circle for U16 in FG).

66

N. Huu-Dung, Y. Yeo-Chang / Forest Policy and Economics 15 (2012) 60–69

Table 3 Costs, stumpage values and optimal rotation lengths of eucalyptus clones and seedlings grown in two types of soil in Northeast Vietnam under subsidized credit scheme. Clone

Soil

Optimal rotation age (year)

Volume (m3/ha)

Stumpage value (VND/ha)

Annual interest on stumpage value (VND/ha)

GU8

FA FG

17 17

215.226 323.139

32,055,957 48,128,679

673,175 1,010,702

38,742,839 78,707,692

813,600 1,593,316

PN14

FA FG

15 14

298.949 358.874

44,525,769 53,451,091

935,041 1,122,473

80,904,552 117,594,315

1,678,237 2,385,522

U6

FA FG

15 14

213.500 289.527

31,798,934 43,122,514

667,778 905,573

47,486,549 87,560,195

956,409 1,838,764

U16

FA FG

14 15

260.584 460.154

38,811,589 68,535,755

815,043 1,439,251

71,983,523 147,912,976

1,486,036 3,040,013

Seedlings

FA FG

18 18

199.195 250.459

29,668,261 37,303,602

623,033 783,376

31,325,916 50,334,315

629,086 978,140

by substituting parameters in Table 1 into Eq. (5)), which is the year that the growers log wood. Eucalypts are likely cut as soon as the farmers observe a fall in the growth of timber (see the open diamond and open circle curves in Fig. 3). In fact, the threshold point of the annual incremental growth in stumpage is not the right time for Vietnamese famers to harvest. They should instead wait until the growth rate of value no longer outpaces the growth rate of cost (e.g., beyond the intersection point of the dashed line and the open diamond curve in Figs. 4 and 5). In seeking further explanations for the early harvesting decisions of farmers, we found several pieces of evidence that are attributed to the problem. First, it is worth noting that most Vietnamese growers have low incomes and few assets. In many cases, growers cannot approach the government's banks for financial support due to the complicated loan process and certain collateral requirements of the banks, such as taking the farmer's land use rights certificates, houses or durable goods as subprime credit, despite the fact that the

Site value (VND/ha)

Annual maximum opportunity cost of land (VND/ha)

government obligated these banks to lend collateral-free loans to growers. For those who can approach the government for a loan, the banks regulate a maximum grant of 20 million VND for an investment with a rather short loan term, which commonly matures within 36 months, regardless of the optimum rotation period (Bien, 2006). Such a small and short-term loan is indeed not adequate to remedy the grower's financial difficulty. In addition, growers lack essential information regarding optimal rotation and the financial profitability of production forestry (Bien, 2006; Hieu, 2004) and are therefore incapable of anticipating their future income. Consequently, Vietnamese growers are very anxious about the risk of losing their ability to pay back their outstanding debts if they extend their rotation times by more years. While under pressure from living expenses, most growers choose to liquidate their forests into instant cash, even if the trees are in a premature phase. This implies that in business practices, Vietnamese forest growers often take additional risks that alter their harvesting times substantially from the actual optimal one. It is

1.2

1

Rate

0.8

0.6

0.4 tcom. = 11 tsub. = 15

0.2

tbio. = 13

0

0

2

4

6

8

10

12

14

16

18

20

Age (year) Fig. 4. Optimal rotation age of clone PN14 in FA in Northeast Vietnam. Dashed line = growth rate of return; Open square = growth rate of cost for r at the level of 15.24%; Open diamond = growth rate of cost for r at the level of 8.4%; Filled triangle = q′/q; Filled diamond = 1/t.

N. Huu-Dung, Y. Yeo-Chang / Forest Policy and Economics 15 (2012) 60–69

67

1.2

1

Rate

0.8

0.6

0.4 tpriv. = 10

t com. = 11

0.2

0

t sub. = 15

t bio. = 15

0

2

4

6

8

10

12

14

16

18

20

Age (year) Fig. 5. Optimal rotation age of clone U16 in FG in Northeast Vietnam. Dashed line = growth rate of return; Open circle = growth rate of cost for r at the level of 19.08%; Open square = growth rate of cost for r at the level of 15.24%; Open diamond = growth rate of cost for r at the level of 8.4%; Filled triangle = q′/q; Filled diamond = 1/t.

worth underlining that the risk premium added by growers mainly comes from financial factors rather than from pests and pathogen damage, because disease prevalence in eucalyptus trees in Northeast

Vietnam is low (Thiep, 1996). Excessive risk could lead to substantial losses of profits for forest owners and a reduction of the national production value and the environmental service for society at large.

Table 4 Costs, stumpage values and optimal rotation lengths of eucalyptus clones and seedlings grown in two types of soil in Northeast Vietnam under non-subsidized credit scheme. Clone

Soil

Optimal rotation age (year)

Volume (m3/ha)

Stumpage value (VND/ha)

Growers borrow from commercial government banks with an average interest rate of 15.24% GU8 FA – – – FG 12 225.187 33,539,635

Annual interest on stumpage value (VND/ha)

Site value (VND/ha)

Annual maximum opportunity cost of land (VND/ha)

– 2,998,443

– 2,163,216

– 193,391

PN14

FA FG

11 11

219.831 280.053

32,741,982 41,711,455

2,927,133 3,729,004

2,577,802 9,137,634

U6

FA FG

– 11

– 225.866

– 33,640,731

– 3,007,481

– 4,390,548

–

U16

FA FG

11 12

208.388 364.545

31,037,554 54,295,746

2,774,757 4,854,040

1,629,047 12,953,728

145,637 1,158,063

Seedlings

FA FG

– –

– –

– –

– –

– –

– –

– –

– –

– –

Growers borrow from private banks and cooperatives with an average interest rate of 19.08% GU8 FA – – – FG – – –

230,455 816,904

392,515

FA FG

– 10

– 250.528

– 37,314,026

– 4,768,733

–

U6

FA FG

– –

– –

– –

– –

– –

– –

U16

FA FG

– 10

– 293.204

– 43,670,102

– 5,581,039

– 2,934,968

–

FA FG

– –

– –

– –

– –

– –

– –

PN14

Seedlings

711,999

90,993

375,089

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N. Huu-Dung, Y. Yeo-Chang / Forest Policy and Economics 15 (2012) 60–69

Therefore, a restructuring of the financial assistance policy and interventions should be undertaken to promote the long-term viability of growers and to make the tree-growing business environment favorable, so that the forests should be left uncut until their optimal rotation times. The analysis above refers to the case when the borrowing interest rate of growers is subsidized by the government. However, Dufhues et al. (2004) and Duong and Izumida (2002) pointed out that the rural capital market in Vietnam is highly segmented; therefore, various credits in different market segments can be considered when analyzing the rotation time. This is because the excessive demand for soft loans tends to encourage lenders to engage in rationing behaviors. Particularly, the two major banks, VBSP and VBAD, tend to use various devices, such as the Commune People's Committee, which act as “rationing mechanisms” that discriminate against the poor, causing segmentation of the rural financial market (consult Dufhues et al., 2004 for the rural financial markets of Northern Vietnam). In essence, when growers cannot access the subsidized interest rate from the prevailing borrowing sources, they may turn to seeking funds from other money providers that require less strict credit contracts but higher interest rates. The common sources are the commercial government banks, with an average interest rate of approximately 15.24%, and cooperatives and private banks, with an average interest rate of 19.08%. Although fewer households borrow from these sources due to their high interest rates, these interest rates represent alternative rural financial credits; therefore, we wish to extend our analysis using these unsubsidized interest rates. The summarized results are shown in Table 4. For growers who cannot access the subsidy scheme and hence borrow from commercial government banks instead, the interest rate increase is nearly two times higher than the subsidized one, reaching a rate of 15.24% per year. Under this situation, the treegrowing business becomes unprofitable for clones GU8 and U6 in FA and for seedlings in both soils due to the negative site value; thus, these should not be grown for timber business purposes. The EOR times of the other clones are reduced substantially for years 11–12 and are no longer higher than the biological rotation time. As can be seen from Figs. 4 and 5, the higher interest rate makes the growth rate of the capital cost curve (open circle) shifts to the right and enlarges the distance to the curve of the inverse value of t (open diamond), resulting in a shorter t**. Nevertheless, their economic rotation times are still longer than the current cutting scheme by 4– 5 years. More precisely, the rotation times of clones GU8 and U16 in FG should be extended to year 12, while clones U6 in FG, U16 in FA, and PN14 in both soils should be left uncut until year 11. If growers borrow from financial private providers with an average interest rate of 19.08%, the results are not economically efficient, as most clones have negative land value resulting from the too-high interest rate relative to site productivity. This evidence highlights that the private financial market is not favorable for the tree-growing business in Vietnam. Unless the government provides financial assistance to private growers to keep their investments at desired profit levels, the target for the national timber supply may not be met. Only the very fast-growing clones, PN14 and U16, in the highly productive FG site in this case can be economically viable for the tree-growing business. For these two high-growth-rate clones, the economic rotation times are shortened to year 10. However, this is still longer than the current harvesting time of 3 years. The preceding discussion reveals the need for the subsidization of household growers. While a subsidy is justified to serve economic efficiency through alleviating the liquidity constraints and strengthening the risk-bearing capacity of growers, it does not work as well as one may think. Despite receiving heavy subsidies, for a number of reasons discussed earlier, constrained households cannot optimize their production and thus end up with inefficient production. Accordingly, it turns out that access to credit is the more important issue than credit price. Furthermore, too heavy a subsidy may be costly

and may lead to unsustainable financial institutions. It is likely that a milder subsidized interest rate (i.e., a higher rate but within a low range of the real interest rate, from 2.1% up to 6.6%, where t** N t*) may reduce the optimal rotation length, but this effect will be offset by improved access to credit and reduced financial market segmentation. The net effect is an increase in production because the banks will have a higher breadth of outreach and can channel funds more sustainably to constrained growers, allowing for extensions of the current rotation period. This insight highlights the government's role in coordinating forest plantation policies and restructuring financial assistance mechanisms so that tree growers can extend their current harvesting times to capture higher profits from the tree-farming business. 5. Conclusions Using the best-fitting Korf growth model to depict eucalypt clone growth curves, this study shows that all of the investigated clones performed better than eucalyptus seedlings in both soil types (1.14 to 1.77 times better in FA and 1.36 to 2.18 times better in FG). However, FG in Vietnam can grow eucalyptus better than can FA. If growers solely attempted to maximize fiber volume, clone U16 would be the best option in FG, while clone PN14 would be the best option in FA. Our study reveals that the economic optimal rotation of eucalyptus plantations in Northeast Vietnam is even longer than the biological rotation, exceeding it by 1–3 years under the subsidized interest rate by the government for rural households. If growers borrow from commercial entities, such rotation period will be substantially shortened; in many cases, it becomes economically unviable. Nevertheless, wherever the tree-growing business is profitable, Vietnamese growers should extend their current farming business cycle of 7 years to 14–18 years under the subsidized credit scheme and to 10–12 years under the market-borrowing interest rate to capture the highest gains from eucalypt plantations. This finding suggests that the Vietnamese government should restructure the credit scheme and should institute proper supervision and enforcement to ensure that the economic optimal harvesting time is achieved in practice. Acknowledgments We sincerely thank the Korea Forest Service (project number S210911L010100) and the National Forestry Cooperatives Federation of Korea for their financial support of this research. We especially thank Nguyen Van The and Tran Van Trung, who are staff members of the Northeast Forest Company, for providing portions of the data and for their expertise during our stays in the study fields. Any errors are those of the authors. Appendix A. Supplementary data Supplementary data to this article can be found online at doi:10. 1016/j.forpol.2011.09.011. References Anderson, J.A., Luckert, M.K., 2007. Can hybrid poplar save industrial forestry in Canada?: a financial analysis in Alberta and policy considerations. The Forestry Chronicle 83 (1), 92–104. Avery, T.E., Burkhart, H.E., 1994. Forest Measurements, four ed. McGraw-Hill Inc, New York, p. 408. Bailey, R.L., Dell, T.R., 1973. Quantifying diameter distributions with the Weibull function. Forest Science 19, 97–104. Bettinger, P., Boston, K., Siry, J.P., Grebner, D.L., 2009. Forest Management and Planning. Elsevier Inc, USA, pp. 106–112. Bien, N.N., 2006. Why Do Farmers Choose to Harvest Small-sized Timber? — A Survey in YenBai Province. EEPSEA, Northern Vietnam. Available from www.eepsea.org. [Accessed 27th September 2010].

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