Asia-Pacific Forest Products Model

Price-Endogenous Linear Programming System (PELPS III)
Countries and Regions
Products
Demand
Supply
Trade Relationships

To analyze and forecast forest products consumption, production and trade in the countries of the Asia-Pacific region, a dynamic spatial equilibrium model, the Asia-Pacific Forest Products model, or ASIA-PAC in short, was developed with the Price Endogenous Linear Programming System (PELPS III) (Zhang et al. 1993).

Price-Endogenous Linear Programming System (PELPS III)

A useful technique in forest sector modelling is to simulate market equilibria by means of mathematical programming. There have been several applications of the technique over the last two decades. The Price Endogenous Linear Programming System is a general PC-based modelling tool that facilitates the application of this technique. Originally developed for the North American pulp and paper industry, PELPS III can be used for any sector to predict consumption, production and capacity by technology, and trade within or among several regions or countries. The theoretical structure is that of spatial equilibrium in competitive markets. PELPS III solves the equilibrium by maximizing the sum of producer and consumer surplus subject to material balance and capacity constraints in each country or territory. Because material flows throughout the system must balance, it is a powerful way of checking the consistency of current data, and insuring the coherence of forecasts.

The system has been used by the United States and Canadian Forest Services to develop the North American pulp and paper model (NAPAP) and the North American solid wood model (NASAW). The Asia-Pacific Tropical Timber Trade (Market) model of the International Tropical Timber Organization (ITTO) is also based on the PELPS system.

Countries and Regions

The countries and territories included in the model are in Table 80. The demand and supply regions were selected based on the volumes of consumption, production and trade. Within Asia-Pacific, twelve countries are treated individually and the rest are grouped into a single region called "Rest of the Asia-Pacific". The other parts of the world are classified as Canada, the European Union, the United States and "Rest of the World".

Products

The products in the model are in Table 81. They are essentially the same as those in Table 2. Figure 16 displays the wood and non-wood material flows.

Demand

The Asia-Pacific Forest Products model has demand equations of fuelwood & charcoal, coniferous sawnwood, non-coniferous sawnwood, veneer sheets, plywood, particle board, fibreboard, newsprint, printing & writing paper, and other paper & paperboard for all countries and territories listed in the Table 80.

Table 80. Countries and territories used in the model.

Code	Asia-Pacific	Code	Rest of the World
01	Australia	21	Canada
02	China	22	Chile
03	Hong Kong	23	European Union
04	India	24	Russia
05	Indonesia	25	United States
06	Japan	26	Rest of the World
07	Korea Rep
08	Malaysia
09	Myanmar
10	New Zealand
11	Papua New Guinea
12	Philippines
13	Singapore
14	Solomon Islands
15	Thailand
16	Rest of the Asia-Pacific

Table 81. Products included in the model

Code	PRODUCTS				DEMAND	SUPPLY
50	ROUNDWOOD (245/246/247)
51		FUELWOOD & CHARCOAL (245)			E	E
52		INDUSTRIAL ROUNDWOOD (246/247)			I	E
53			Sawnwood (C) (248.2/3)		E	I
54			Sawnwood (NC) (248.4/5)		E	I
55			Veneer Sheets (634.1)		E	I
56			Plywood (634.3/4)		E	I
57			Particle Board (634.2)		E	I
58			Fibreboard (634.5)		E	I
59			Wood Pulp (EX251)		I	I
60				Newsprint (641.1)	E	I
61				Printing and Writing Paper (641.2/3)	E	I
62				Other Paper & Paperboard (EX641)	E	I
63	OTHER FIBRE PULP (251.92)				E	E

Note:

E = relation simulated by econometric equation.
I = relation simulated by input-output data.

The demand equations assume that demand for forest products is determined by economic activity. Let q_it (of price p_it) be the amount of a forest product consumed or imported by a country (or territory) i during period t; with i_it an index of the price of all other goods and services used in combination with this product to produce an output designated by the variable y_it, which in this study was measured by the real national product. Then, assuming cost minimization under a Cobb-Douglas technology with constant returns to scale leads to the following derived demand:

Figure 16. Wood/non-wood material flows.

According to economic theory, we would expect the price elasticity b to be negative while g should be positive.

The demand equation for each product was estimated for three income groups: "high" (developed market economies), "low" (developing market economies), and "world" (combination of developed and developing economies), based on the country and territory classification of FAO (1994, p.ix).

Commodity prices were weighted averages of unit values of imports and exports, by country and territory. The data on production, imports and exports were obtained from FAOSTAToPC (FAO 1996). GDPs were measured in constant US dollar at 1987 prices, based on GDP in domestic currency, exchange rates, and the US GDP deflator. The data on GDPs, exchange rates, and the US GDP deflator came from the World Tables of the World Bank (1995).

The parameters of demand equation [1] were estimated by analysis of covariance (OLS with one dummy variable for each country and territory, corrected by AR1 when autocorrelation was present). The results in Table 82 show that the equations explained well consumption across countries and over time. GDP elasticities were all positive, as they should, except for fuelwood and other industrial roundwood in high income countries, as expected. GDP elasticities tended to be higher in low-income countries. Price elasticities were low, though statistically and economically significant in many cases.

In this model, prices are endogenous (the equilibrium between demand and supply leads to the prices). So, no assumption have to be made regarding future prices. Only national GDPs are shifters of demands, and are strictly exogenous. Thus, specific scenarios regarding GDP growth had to be developed. The GDP projections available were used until 1997 (IMF 1996). Beyond, it was assumed that the GDP growth rates of countries in the region would tend to converge, though countries with higher current economic growth continued to grow faster until 2010.

The assumptions on the GDP growth rate of each country and territory are summarized in Table 83. The region, which had the fastest growth in the last decade continued to do so in the projections, but at lower rates. For the Asia-Pacific region, growth began at above 8% and then declined progressively to 3% in 2010. Exceptional growth, maintaining 4.5% per year by 2010 was assumed for China, Indonesia, Japan, Malaysia, Singapore, Thailand and Viet Nam. Parallel but substantially lower rates were assumed for Oceania.

For North America, GDP was projected to grow at between 2 and 2.5% per year throughout the projection period. Chile, viewed as a major player in the region in South America, was expected to grow faster at a rate that would slow down from above 8% per year initially to about 3.5% by 2010. In Europe, growth that began at 2.1% in 1996 (International monetary Fund 1996) was assumed to increase to 2.6% by 2000 and reach 2.3% by 2010. The countries of the former USSR have endured large recessions in the past decade. The projections assume a progressive recovery, ending with a 2.5% GDP growth rate by 2010.

Table 82. Price and income elasticities of demand for forest products.

Table 83. Assumed growth rates of real GDP (percent per year) by country and territory, 1988-2010.

	88-95	1995	1996	2000	2010
Australia	2.89	3.50	3.40	2.86	2.20
China	9.78	10.20	9.66	7.76	4.50
Hong Kong	5.28	5.00	4.93	4.64	4.00
India	5.49	6.20	6.02	5.36	4.00
Indonesia	7.86	8.10	7.79	6.66	4.50
Japan	2.84	0.90	2.70	2.86	2.20
Korea REP	8.08	9.00	8.59	7.14	4.50
Malaysia	8.91	9.60	9.13	7.46	4.50
Myanmar	3.00	7.20	6.92	5.92	4.00
New Zealand	1.46	3.20	3.50	3.75	2.20
Papua New Guinea	4.35	-4.60	1.00	1.43	3.50
Philippines	3.49	4.80	4.74	4.52	4.00
Singapore	8.91	8.90	8.50	7.09	4.50
Solomon island	2.90	0.20	0.24	0.52	3.50
Thailand	9.88	8.60	8.24	6.93	4.50
Rest of the Asia-Pacific	3.94	4.20	4.47	4.28	3.17
Canada	1.90	2.20	1.90	2.72	2.20
Chile	7.23	8.50	8.01	6.32	3.50
European Union	-0.50	2.60	2.04	2.49	2.30
Russia	-12.60	-4.00	1.00	1.30	2.50
United States	2.24	2.00	1.80	2.20	2.20
Rest of the world	2.40	3.50	3.48	3.08	2.29

Source: World Economic Outlook (International monetary Fund, may 1996). Shaded figures are assumptions.

Supply

The supplies of fuelwood and charcoal, industrial roundwood (logs, chips, particles, wood residues, and other industrial roundwood), and other fibre pulp were represented by a reservation price, assumed to be equal to the world price, up to the sustainable production potential. This simple representation of supply implies that the cost of production is constant up to the production potential. Costs and prices would then rise sharply when the potential was reached. The supply of end products and demand for raw materials in each country or territory were linked by input-output coefficients.

The maximum potential roundwood supplies in 1992 and 2010 are shown in Table 84, together with the implied growth rates. Those rates set the maximum growth of supply, the actual supply predicted by the model may be less if conditions are such that it is worth producing only part of the maximum potential. But supply cannot exceed that upper bound.

The state of the world's forests is still not well known. Nevertheless, international cooperation under the FAO has produced forestry information with wide coverage and coherent definitions. Specially important here are the Tropical Forestry Assessment 1980 (FAO 1986), Tropical Forest Assessment 1990 (FAO 1995a) and Forest Resource Assessment 1990 global summary (FRA90, FAO 1995a). The Tropical Forest Assessment compares the forestry situation around the years 1980 and 1990. Country specific data vary widely in quantity and quality. The Forest Resource Assessment 1990 includes developed countries.

These assessments served as the basis to estimate the potential output, i.e. the most countries could produce, in sustainable fashion. The assessment of production potential started from the observed trends in harvests, and increased or decreased them based on informed judgement.

Asia as an aggregate is projected to have a timber supply potential growing at about 1 % per year. This will, as will be seen below, make this fast growing region into a large net importer. The largest countries, China and India are likely to face wood supply constraints. Still, both countries have a long term commitment to forestry, and their annual plantation rate of one million hectares was three times the losses from 1980 to 1990. Furthermore, Japan has an excellent forest resource, which might be more utilized in the future.

In Oceania, New Zealand, and Australia are in an excellent position. As wood suppliers they are exceptions amongst the industrialized countries. They are projected to have some of the highest potential supply growth rates of any country in these projections, near 3% per year.

In North America, forest sector policies and conservation considerations are constraining the potential timber supply of the USA and Canada. The supply scenario assumed less than 0.5% growth in supply potential for the USA and about 1% growth for Canada.

Chile was projected to have one of the highest potential supply expansion rates (2.7% per year), reflecting excellent resources and an expansive forest policy.

For Europe, the trend projections were based in part on the UN-ECE/FAO (UN-ECE/FAO 1993, Pajuoja 1995) assessments. As in North America, there is much uncertainty regarding the effects of environment and agriculture policies on timber supply. The annual growth rate of roundwood supply potential was assumed to be around 0.5% per year.

Roundwood supply in the Former USSR region is constrained more by infra-structure than by biological limits, the best prospects are in the Russian Federation and Belarus. Still, the assumption is that timber supply from the Former USSR group of countries would be only be in 2010 at approximately the 1992 level of production.

In total, the growth rate of the world roundwood supply potential was assumed to be about 1 % per year.

Table 84. Roundwood supply in 1992 and supply potential up to 2010 (thousand m³).

	1992	2010	Annual Growth
Australia	18249	31717	3.12%
China	275118	370255	1.66%
Hong Kong	625
India	282190	330570	0.88%
Indonesia	184743	240912	1.49%
Japan	28063	31497	0.64%
Korea REP	6485	8631	1.60%
Malaysia	54008	59860	0.57%
Myanmar	22731	28737	1.31%
New Zealand	15042	25460	2.97%
Papua New Guinea	7991	10583	1.57%
Philippines	38273	46000	1.03%
Singapore	0	20
Solomon island	468	644	1.79%
Thailand	37081	48282	1.48%
Rest of the Asia-Pacific	103097	123427	1.00%
Asia Pacific	1074162	1356595	1.31%
Canada	181873	221816	1.11%
Chile	25648	41624	2.73%
European Union	261277	290551	0.59%
Russia	308332	318297	0.18%
United States	483211	515779	0.36%
Rest of the world	1071478	1282104	1.00%
World	3405982	4026766	0.93%

Note: Shaded figures are projections

Trade Relationships

The structure and trends of trade in forest products are determined by a wide range of factors of which only the main elements were recognized in this study - levels of demand, costs of wood and other factors of production. Also, recognizing that models of trade in forest products should effectively be global forest sector models (United Nations 1986), this study has concentrated on intra-regional trade between the major importers and the major exporters of the Asia-Pacific while recognizing the inter-regional trade between the major importers/exporters of the Asia-Pacific and other regions.

With the implementation of WTO underway, the member countries are expected to reduce or eliminate trade tariffs and non-trade barriers in the near future. Thus, it was assumed that forest products would be traded freely within the Asia-Pacific region and between it and other countries and territories in the future, moreover, taking into account that the adjustment of trade flows between countries or territories is bound to take time, inertia constraints were introduced to limit trade in a given year to be within a specified fraction of the previous year's trade (Buongiorno and Gilless 1980).