industrial wood in india: key determinants of demand and supply

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Industrial Wood in India: Key Determinants of Demand and Supply

P.J.Dilip Kumar,

Group Coordinator (Research), Institute of Wood Science of Technology,

Bangalore-560003

[Third, revised, draft, 1 Jul 1995]

Paper presented at the international workshop on "India's Forest Management

and Ecological Revival" organised by CIFOR (Center for International

Forestry Research, Indonesia) and TERI (Tata Energy Research Institute, New

Delhi, India), in February 1994 at New Delhi. The workshop proceedings

(Lele, Mitra and Kaul, 1994) has a summary.

1. Introduction

There has long been a pervasive impression of shortages in the economy of

primary forest products in India. This impression extends to biomass

products in general. In the case of fuelwood, for instance, there is an

overall impression of a gradually worsening situation in the country-side,

with sources of supply - the trees, wooded commons, private woodlots, etc. -

becoming scarcer or poorer. In the case of fodder, the impression of overall

scarcity is reinforced by the experience of regular periods of distress when

little palatable biomass is available near at hand, and animals have to

migrate long distances often with loss of life and vigour. In the case of

industrial wood (timber for sawnwood, veneer products, pulp and paper

products, etc. - please see Appendix for definitions of the product groups

in production and in international trade), raw material of the requisite

quality has often been hard to get. Arrivals from the forest divisions have

gradually declined from the heydays of the postwar decades; under

environmentalists' urging, fellings in the natural forests have been

curtailed. Price increases of timber have been generally higher than of

other product groups, as other authors portray in this volume. Imports of

round logs have gone up to over a million cubic metres a year, and have been

liberalised in an effort to save our remaining natural forests. Rising

prices and shrinking domestic arrivals from the forest divisions, together

constitute the symptoms which signal the rising scarcity of timber.

Should it matter? That depends on our point of view. In an economist's

terms, there can really be no "gap" btween demand and supply as long as

prices are flexible: the market is supposed to rapidly adjust the price

until demand and supply balance out. From the welfare point of view, a free

market may raise the equilibrium price to eliminate 'excess' demand, but

these imply welfare losses to consumers.

There are many imperfections in the markets for forest products. For

instance, government imposes many controls on felling, transport, etc.

Government policies may exercise controls, directly or indirectly, on the

price and distribution (at one time not many years back, raw material was

being supplied to forest-based industry on quota systems at very low rates

compared with market prices). There are also systems of forest rights and

privileges that enable certain people to get costly timber at negligible

prices.

When there is a large difference between such controlled prices and the

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prevailing market prices, there is naturally a tendency for 'unofficial'

transactions to take place, often illegally. Smuggling of timber and

fuelwood is also ubiquitous in our forests: universally by 'headloaders'

for their daily sustenance, but also frequently by regular gangs for big

money, involving chains of agents from the forest to the market. The

economic model of the perfect market breaks down when property rights

(whether of private or public owners) cannot be, or are not, maintained. All

these are signs of a serious shortage of legal supplies.

While some authors deplore the emphasis on the 'special' nature of forestry,

it does make a difference that supply decisions cause their real effects

many years in the future. Some market situations can result in counter-

stabilising decisions. For instance, a price rise would normally call forth

an increase in supply levels. In a forestry crop, this is achieved by

shortening rotations (some crops will be felled a little earlier than before

the price rise), but this shortening of the rotation implies a lower mean

annual product in the future. This would result in a lower annual supply

(production) from the exising land base. Thus long-run supply would

contract: unless the land base itself were expanded, and more hectares of

crops were raised. The production from these additional hectares, of course,

would not be available for many years, during which time prices would

continue to rise as production fell.

These long time lags, the bulky nature of the produce, the ease with which

the 'factory' (i.e. the standing crop) can be converted into product (the

timber logs), the counter-stabilising effects of economic responses, and the

ubiquitous externalities (e.g. environmental and bio-diversity conservation)

make it unlikely that purely private operators, acting in the market, can

ensure the public good. These considerations imply that questions of

optimal supply and demand are within the ambit of public administration and

policy considerations. This is all the more so in India, where the forest

economy is under close control of the government (for good or for bad): most

of the forest is nationalised, there are strict controls on felling and

transport of forest produce even from private lands, many states have

stringent penalties for forest offences, etc.

2. Forecasting consumption demand of forest products

The foregoing discussion illustrates the reasons why governments and policy

makers, private or public, assemble information on consumption and

production of various commodities and services over time. Forest products

are no different. Consumption analysis helps us to understand and predict

behaviour of forest products markets, using a combination of statistical

techniques and specific knowledge of the sector and of the policy

environment: quantities, prices, trends, outlook for product sales, etc.

Effects of policy changes may be discernible from such analysis of past

consumption. It can also warn of possible divergence between consumer's

wants and producer's abilities to supply these wants, in time for corrective

action (Gregory, 1966).

According to Gregory, in market economies, consumption may differ

substantially in the short term from sales, the intersection of demand and

supply curves. In non-market economies or products with poorly organized

markets (e.g. firewood), sales may be taken as synonymous with consumption

(Gregory, 1966).

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How can we use our information on consumption during the past years, to

predict future levels? There are two main approaches to consumption

analysis: statistical time series analysis, and econometric modeling.

Time-series analysis looks at the patterns in changes over time in

consumption, such as an upward or downward trend, and tries to project this

pattern into the future. Usually, as population keeps on rising, total

consumption of a product - say, foodgrains or fuelwood - also rises. A

change in the trend may occur as a response to changes in policy,

incentives, or other factors. Cyclic variation and serial correlation are

also analyzed in the time series.

The advantage of time series analysis is its relative intuitive simplicity:

e.g., if consumption has been increasing steadily at say 2%, we could expect

it to continue increasing at the same rate in the near future as well. In

effect, we can say that the time series reflects certain underlying

phenomena that influence consumption, like a steady increase of the

population. The disadvantage is that we do not explicitly describe the

effects of other variables or factors in the economy, like the supply or

prices of other commodities that are either substitutes or complementary to

the commodity we are studying; or the effects of changes in income, which

may move up or down (and not steadily be increasing or steadily decreasing,

like population).

The econometric approach seeks to identify such links, or dependencies, of

consumption demand, in relation to other, 'exogenous' or 'independent',

variables. For instance, as income increases, families may use less of

fuelwood and more of a superior energy source like electricity or oil.

Theoretically, we could derive demand and supply functions of a generalized

form, relating observed market quantities to variables like market price,

income, population, etc.:

Consumption = b1(population) + b2(income) + b3(urban/rural ratio) + b4(area

of forest land) + b5(forest growth rate) + b6(cost of production) +

b7(availability of competing materials) +...

To do such an analysis, we need to asemble a data set, giving the values of

all the selected variables at each observed 'point'. One way of doing this

is to collect information from many markets or countries at a given period

in time. Such cross-section data from many countries have been used to

advantage, as in the FAO study (1960) on 'World Demand for Paper to 1975',

on the assumption that consumption change over time in a particular country

will follow the pattern shown by different countries at a point in time.

The other approach, if we could lay our hands on the data, is to use time

series - say, 15 to 20 years' observations - of the variables of interest

pertaining to one market or one country. McKillop (1967) used time series of

economic indicators and of production, consumption, prices, etc. of various

commodity groups, for the US, for such an analysis. But such detailed data

are seldom available in less developed countries; long time series may be

available of population, national income, GDP, and a few other economic

indicators, but seldom of prices or quantities produced, sold, or consumed,

of individual products.

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Gregory (1966) argues that if we chose to ignore production policy, and

instead viewed directly the less complicated problem of consumption, we

could ignore price, as price and consumption are jointly determined by

factors (like income) that shift supply and demand curves.

Another consideration against a complete specification of equation systems

like McKillop's is that they are of limited use in forecasting: each of the

'independent' variables themselves would have to be forecast, and this is

usually done on the basis of time series analysis. McKillop, in the example

cited above, projected future values of economic variables on the basis of

strong linear trends. Ultimately, it may be simpler to describe the

behaviour of the individual product itself by trend equations, instead of

going through the elaborate exercise of estimating econometric relationships

among a number of variables which cannot be forecast themselves without

making many assumptions.

3. Examples of consumption analysis and forecasting

An early study on consumption demand and production possibilities in the

Asia-Pacific Region was made by FAO/ECAFE (1961). Rate of change in

consumption depends on income per cap, rate of increase of population,

availability of supplies, and price of wood in relation to other products.

The relation between income and consumption was not precisely determined for

most forest products, being clearest for pulp and paper.

The study assumed that population in South and Southeast Asia would increase

over 1955-1975 at annual rates of 4.50% (urban), 1.75% (rural), and 2.25%

(total); income per cap would grow at 2% per annum in all countries except

Japan and Australia-New Zealand. Combining growth of income per cap and

population, national income (NI) at current prices was predicted to increase

by 1975 to 225% of the 1953-55 level (4.1% annual growth rate).

Consumption of individual products in different end uses was projected to

grow as follows in South Asia over the period 1953-55 to 1975:

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Projections of consumption demand of induatrial wood peoducts in South Asia,

1955 to 1975

Product Sector Index of consumption Annual growth

1955 1975 rate, %

Population 2.25

NI per cap 2.0

NI (aggregate) 100 225 4.1

Sawnwood Housing - urban 100 400 7.1

- rural 100 140 1.7

- total 100 240 4.51

Agricultural uses 100 180 3.02

Non-residential 100 225 4.13

construction

Packaging 100 175 2.84

Vehicles 100 175 2.8

Railway sleepers 100 130 1.3

Transportation and 100 154 2.2

vehicles (incld. boats)

Furniture 100 230 4.3

Other end uses 100 225 4.1

Total sawnwood 100 210 3.8

Wood used in the round (WUIR)

Housing 100 153 2.2

Agricultural 100 180 3.02

Vehicles 100 175 2.8

Pitprops Mining 100 400 7.2

Total WUIR 100 195 3.4

Pulp & Paper products

Newsprint 100 440 7.7

Printing & Writing Paper 100 400 7.2

Packing, Wrapping & Other Paper 100 460 7.9

Paperboard 100 470 8.1

Dissolving Pulp 100 210 3.8

Total Pulp & Paper Products 100 410 7.3

Net Roundwood equivalent of wood fibre pulp

100 480 8.25

Roundwood used for veneers, plywood, fibreboard and particleboard

100 190 3.36

Total industrial roundwood 100 230 4.3

___________________________________________________________

Notes: 1constitutes 40% of all industrial wood consumed

2same growth rate as agricultural production

3same growth rate as National Income

4accounts for 20% of total roundwood equivalent consumed; total

packaging demand growth faster than NI, but wood replaced by

pulp products

5 excludes Nonwood Fibre Pulp

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6 rate of increase of Fibreboard & Particleboard would be greater than

that of Plywood & Veneers, which in turn would rise faster than

Sawnwood

Thus, aggregate industrial wood demand was projected to grow at around the

same rate as National Income.

Gregory (1966) stressed the importance of the supply side in determining

consumption of wood products. He defined a Wood Availability Index to

characterize supply conditions:

WAI= 142*[0.8(coniferous area per cap) + 0.2(hardwood area per cap)]

The reasoning was that 80% of all sawnwood in the northern hemisphere is

from coniferous species. 'Area' is that of forests in use, reflecting

accessibility; a country that may be very rich in forests may still have low

WAI if the forests are not under exploitation (e.g. Nigeria, WAI=1). Per

capita basis is to reflect population pressure in determining relative wood

availability. The constant 142 was set to give USA a WAI of about 80 (to

reflect 80% availability). The maximum score was 100 (Canada, Finland);

India had a WAI of only 3. No consistent and objective means was found to

quantify factors like differences in importation possibilities.

Gregory found that per capita income is a very good proxy variable for most

of the factors that tend to influence industrial wood consumption on the

demand side. Rural/urban ratio was not significant, probably because it was

itself closely correlated with income. Perhaps the most interesting of the

initial regressions were the following, derived from data of 53 countries:

1. Cs = -2.73 +0.130 Y -0.0000362 Y² +1.83 WAI -31.7 log WAI

R² =.94 (.013) (.0000075) (.183) (7.66)

2. Cr = 0.919 +0.031 Y -0.0000050 Y² +0.49 WAI -11.0 log WAI

R²=.96 (.0031) (.0000017) (.042) (1.75)

where

Cs= Sawnwood consumption per capita in board feet (using FAO conversion

factors of 424 board feet per cubic meter and 35.3 cubic feet per

cubic meter),

Cr= Roundwood consumption per cap in cubic feet

Y = Income per capita, in US$ using currency exchange rates

WAI = Wood Availability Index

R² = coefficient of determination; standard errors in ().

Regression coefficients were highly significant, and the relationships were

as per generally expected patterns. Thus, for sawnwood, a sigmoid curve

would be expected: in very low income areas, income would play a relatively

minor role, as essentials like food would have priority; at intermediate

income levels, there should be a more pronounced effect of income on wood

consumption as a result of increased construction activity, shipping,

crating, etc. As incomes pass beyond some level, the effect of further

income increases would decline, as income would go to purchasing services

and other non-wood items. A negative coefficient of the Y² term "at least

partially confirms the hypothesized form (the upper part)". In almost every

case the coefficient of WAI was positive and that of log WAI negative,

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indicating that the effect of WAI tends to decline as the index rises. This

is as expected: marginal utility of any commodity decreases with increasing

level of consumption.

Countries with low incomes and a shortage of available timber would have

high consumption elasticity with respect to both income and WAI. As either

income or WAI or both increase, elasticities drop substantially. Income

elasticity is very sensitive to changes in WAI particularly at low income

levels. If WAI is high, income elasticity is lower.

In general, Gregory found the results of the analysis highly satisfactory:

regression coefficients tested highly significant, with income and WAI

accounting for as much as 95% of the variance. These two factors together

accounted for - or were associated with factors that accounted for - much of

the variation in industrial wood consumption.

Another example of consumption forecasting is the study by FAO (1971) of

agricultural commodities, which used population and income (personal

consumption expenditure, PCE, at 1970 prices, in equivalent US$) as the

major shifters of demand. Time series of income were assembled first, and

these were used to obtain growth assumptions for the period 1970 to 1980:

for developing countries, GDP was assumed to grow faster than PCE. Income

(PCE) was brought into the demand equations through preselected values of

income elasticities and appropriate demand functions derived from historic

data of average national per capita consumption and income, family budget

surveys and intercountry comparisons, at 1970 prices. An additional 'trend'

parameter was included to account for other factors, like preferences,

urbanization, etc.

Income elasticities were derived from functions of per cap consumption C

with per cap income Y. Some 200 household surveys were analyzed. Three types

of functions, i.e. log-log, semi-log and log-inverse, were fitted to the

same data of per cap consumption (expenditure) by income groups, using

least-square (LS) regressions, weighted by number of households in each

group. The assumption is that as households get higher incomes in the

future, their consumption will change to resemble those families that are

already at the higher income levels in the cross section survey. To account

for other conditions, families were, where possible, stratified by

socio-economic factors like size, occupation, urban and rural, and

covariance analysis applied to isolate effect of income. The regression

functions have the following properties:

1. double-log: ln C= a + b ln Y

coefficient of elasticity (with respect to income)= b (constant)

Marginal propensity to consume MPC = bC/Y

Comments: Displays constant elasticity over all income ranges; problem of

transforming zero C into log values. Mainly used for 'luxury' goods where

consumption still far below saturation limits.

2. semi-log: C= a + b ln Y

coefficient of elasticity = b/C= b/(a+b ln Y)

MPC = b/Y

Comments: Coefficient of elasticity varies inversely with quantity consumed

(or expenditure); MPC inversely proportional to income: 'necessity' or

'inferior' good - consumption expected to fall as income grows, but no

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saturation level.

3. log-inverse (sigmoid): ln C= a + b/Y (b usually negative)

coefficient of elasticity= -b/Y

MPC= -bC/Y²

Comments: Coefficient of elasticity falls with income; consumption

approaches saturation level as income approaches infinity. Typically applies

to calorie intake: starting from point of hunger, increases rapidly with

income, but at high income levels, tends towards a saturation limit. With

positive elasticity, applies to those commodities for which consumption

already high, but that will still increase moderately as income increases,

but approaching saturation; and with negative elasticity, consumption will

decline slightly toward a minimum level at which it will stabilize.

4. log-log inverse (bell-shaped): lnC= a +b lnY +c/Y (b,c usually negative)

coefficient of elasticity = b -(c/Y)

MPC= C(bY-c)/Y²

Comments: When income rises from very low level to a very high one, first

behaves as 'luxury' good, consumption increasing more than proportionately

(elasticity > 1); then as a 'necessity', consumption increasing at a falling

rate (coefficient of elasticity < 1); then an 'inferior' good, consumption

decreasing as income rises. Characteristic of long term evolution of per cap

demand for staple food in developing countries.

Time series analysis based on national averages of per cap consumption and

per cap income was also carried out for a large number of countries and

commodities. Additional variables were often introduced: e.g. price of

commodity, prices of substitutes and /or complementary commodities; and a

trend term (zt, where t stands for time variable, z is the coefficient) was

added in some cases to evaluate globally the influence of factors other than

income and prices (e.g., double-log function would become ln C= a+b ln Y +

zt). But because of high correlation over time of income with prices and

'time', findings were not very reliable - multicollinearity increases the

variance of estimates, reducing their efficiency. To make up incomplete time

series, especially of prices, time series of different countries were

combined.

The study included projections of forest products as well. For forest

products other than pulp, paper and paperboard, i.e fuelwood, industrial

roundwood, sawnwood, and wood-based panels, for developing countries,

log-inverse functions were fitted with the growth rates of income and

population used throughout the projection study. For each product group,

income elasticities of demand were estimated from cross-section analysis of

average consumption and income per capita from 1964 to 1966. For pulp, paper

and paperboard, in addition to basic econometric calculations, data and

projections from other sources were used, including questionnaires to

governments; a log-inverse function was used to project demand for

developing regions. Two consistency tests were applied: i. demand for paper

and pulp products as a group was arrived at by independent projections of

each product, and resulting composition adjusted if it seemed improbably

different from recent trends; ii. growth rates of consumption were adjusted

so that they either consistently rose or consistently fell over the 3 time

periods 1962-68, 68-75 and 1975-80. The final demand projections for paper

and pulp products were, therefore, the result of a combination of somewhat

different methodologies for different regions.

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Madas (1974) suggested the following expected trends in consumption: paper

and packaging would be growing; construction material, sawnwood, panels

would be stable; pitprops, line posts, railway sleepers would be decreasing.

Consumption of industrial wood was correlated with GDP: from data in the FAO

Yearbook 1971 (for 1969-70), he found in general that there was an average

increase of 0.1 cum per cap of wood raw material equivalent (WRME) for every

$100 increase in GDP (1970 prices). Per capita consumption in net exporting

countries was about twice that in importing countries with a similar GDP

level.

Per cap consumption of Industrial Wood, cum WRME (wood raw material

equivalent (from Madas, 1974)

Consumption Per cap GDP (US$ of 1961-63 purchasing power)

(cum WRME) 200 400 600 800 1000 1200 1400 1600 1800

Importers 0.17 0.30 0.44 0.55 0.65 0.72 0.79 0.83 0.86

Exporters 0.38 0.63 0.86 1.08 1.25 1.30 1.50 1.58 1.63

Madas (1974) went on to forecast world consumption of industrial and

fuelwood for the year 2000, using correlation with per cap GDP of

consumption in each major product category. Graphs of consumption (on a

logarithmic scale) against time were used to draw envelope curves connecting

the peaks by inspection. For new products like fibreboard and particleboard,

consumption rises at exceptionally high rates for a few years, then adapts

to long- term rate of economic growth. For paper and paperboard a quasi-

logistic curve against time (year) was recommended.

4. Consumption of industrial wood in India

How do these estimates and projections of growth relate to the situation in

India? That is the subject of this paper. One of our problems is the

variability in estimates of consumption. It is possible that much of the

consumption of sawnwood and wood used in the round doesn't really get

registered in the available statistics. Official figures of production and

trade (imports and exports) of manufactured products (pulp and paper

products, panel products, etc.) are probably more reliable.

There are then two ways in which we can put together our estimates of

roundwood consumption. One is to take the estimates of roundwood production

and trade and hence arrive at 'apparent' consumption (production + imports -

exports; changes in the balance stock or inventory held by producers or

consumers are ignored). The other is to start from estimates of consumption

of finished products (mainly, sawnwood, pulp and paper products, and panel

products) and work backward to the derived demand of roundwood based on

average conversion factors; to this, we then add estimates of WUIR to arrive

at total industrial roundwood (IR) consumption.

Both these approaches have been applied, and the resulting consumption

series given in Table 1, which gives the basic data on consumption (from the

Yearbooks of Forest Product Statistics published by FAO) as also our

calculated 'derived' roundwood equivalents. The Yearbooks data required a

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little modification of the figures, especially for the initial years, to

account for varying definitions of product categories, intermittent revision

of old estimates, and other quirks. We are able to put togther series of

'observed' production, import and export from 1955 to 1990 for many

products, and from later years for others.

The 'derived' demand figures for roundwood equivalents have been calculated

afresh, based on standard conversion factors (discussed separately for each

product category below; for pulpwood, we give the roundwood equivalent of

the entire quantity as well as the lesser roundwood requirement assuming

that only 40% of the demand is met from wood, and the rest is from non-wood

raw material like bamboo). It can be seen that the 'derived' demand figures

in general are higher than the 'observed'. For instance, in the 1990

estimates: observed consumption of 'Sawlogs & Veneer Logs' is 19.2 million

cum(r), but the derived demand is 32.3 million cum(r). One possible

explanation is that wood is re-used many times, hence roundwood requirement

is not as high as the derived raw material equivalent. The discrepancies,

however, appear to be too large to really be explained away on this basis.

Our impression is that consumption demand of wood raw material is

systematically under-estimated if we go by only the FAO figures of

'observed' consumption (see especially Section 6.3 below). Official

estimates usually give even lower figures.

The series in Table 1, whether 'observed' or 'derived', give us the basic

data sets for estimating statistical relationships or trends, and hence for

forecasting future demand. With all the limitations inherent in statistical

techniques, we can still discern a rise in consumption over time. Instead of

estimating a simple time-based trend, an exercise is made here of

correlating consumption per capita with gross domestic product (GDP) per

capita at constant prices. The series of GDP at 1970 prices (1960 to 1984)

has been derived from data presented in the International Finance

Statistics, the source for the population figures as well. The basic series

of GDP and population are also presented in Table 1.

Per capita GDP (1970 prices) and population, the two 'exogenous' economic

variables that are needed for the subsequent analysis, have been regressed

upon time (year) on the basis of exponential as well as linear equations.

The exponential function shows per capita GDP (1970 prices) increasing at

1.40% per annum over the period 1960 to 1984. The linear form would have an

increase in GDP per capita, of Rs.10.57 (1970 prices), every year: this

would work out to a proportional rate of 1.64% in 1960, and 1.16% in 1984.

Population has increased at 2.19% per year over the period 1950 to 1985 if

we go by the exponential equation. If we adopted the linear population

growth model, the annual increase would be 11.41 million per year, which

would amount to a proportional growth rate of 3.19% in 1950, and 1.52% in

1985. This is not realistic, considering that decennial increase of

population from 1950 to 1960 was only 19.74%, 1960 to 1970 was 25.65%, and

1970 to 1980 was 23.10%.

Regression equations of GDP (Rs per cap, 1970 prices) and Population

(millions) on Year

Exponential:

ln gdp70cap = -20.9063 + 0.01396 year (R² = 92.39%, df= 23)

ln pop = -36.8729 + 0.02191 year (R²= 99.83%, df= 34)

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Linear:

gdp70cap = -20099.3 + 10.5734 year (R² = 91.48%, df= 23)

pop = 21924.9 + 11.4098 year (R²= 98.36%, df= 34)

where the variables are

gdp70cap = GDP per cap, in Rs. 1970 prices, 1960 to 1984

pop = population, in millions, 1960 to 1984

year = calendar year (1960, 1961 ... 1984)

A linear growth equation will result in lower projections into the future,

compared with the exponential growth form. Both projections are given in

Table 1 for population as well as for per cap GDP.

As far as population goes, a constant rate of growth of 2.19% over the next

couple of decades is probably not an over-estimate. Indeed, it would be

premature to assume that the population growth rate will stabilize at even

this level, as there is always the momentum in population growth. Even if

couples take to limiting their family size, the population at large is

growing younger, and the number of children born per 1000 capita is bound to

keep increasing as a greater proportion of the population moves into the

child bearing stage. Assumptions of decreasing growth rates, such as those

made by the United Nations (UNO, 1985, medium scenario) that it would fall

from a peak of around 2.17% over 1980-1985, to 1.09% during 2000-2025, and

0.58% by 2020-2025, would appear to be over-optimistic and unfounded.

As for GDP per cap, a continuous increase of 1.4% per year implies an annual

growth of aggregate GDP in real terms of around 3.6% (i.e. 1.4+ 2.2%

population growth). This should not be too optimistic, keeping in mind

especially the liberalisation of the economy, inflow of capital,

diversification into modern industries and financial and information

sectors, development of communications and infrastructure, etc.

The regression models used to extrapolate per capita GDP and population are,

therefore, those represented by the exponential forms given above.

The function forms used to correlate per capita consumption of industrial

wood and wood products to per capita GDP are the double-log (which usually

gives a high estimate), semi-log (usually a low estimate), log-inverse (a

medium estimate), and log-log-inverse (bell-shaped, diminishing, curve).

Tables 7 and 8 give the regression coefficients in tabular form for Product

and Roundwood categories respectively. The projected per cap consumption is

then multiplied by projected population (on the exponential time trend), to

give projected aggregate consumption in four variants. This exercise has

been done both for the roundwood categories (Sawlogs & Veneer Logs;

Pulpwood; and Other Industrial Roundwood), as well as for the processed

goods categories, from which roundwood requirement is derived using the

standard input coefficients (listed in Appendix 2). The projections of

roundwood requirements by these two methods are presented and compared.

5. Consumption of wood products

5.1. Paper and Paperboard

Per capita consumption of paper is very low in India, reflecting the

relatively low levels of literacy and technical skills of the work force. In

common with other South Asian countries, suitable raw materials are scarce,

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and imports form a substantial portion of consumption.

Aggregate consumption of Paper and Paperboard has been described by the

'quasi-logistic' function of aggregate consumption against year (Madas,

1974). The FAO (1961) study indicates that the relation of consumption to

income is represented not so suitably by a straight-line logarithmic

function as by the 'log-normal' curve, as the former implies that income

elasticity does not change with level of income, while the latter can

accommodate a diminishing elasticity with rising income in consonance with

historical data:

t

C= S - (1/2π) exp(-t²/2) dt

where C= consumption in kg per cap, S = assumed saturation value, kg per

cap, and t= (log X -a)/b, where X= income (GNP) per cap and a, b are

constants. There is a linear relationship between t and log C; the

projection is made by applying estimates of future population to the

predicted consumption per cap.

The FAO study (1971) of world agricultural commodity projections used a

'log-inverse' function between consumption per cap and GDP per cap

(converted to 1970 US $); with modifications to make the aggregate of

individual components agree with projection of aggregate consumption.

The National Commission on Agriculture (NCA, 1976) estimated different

relationships between per capita GDP at constant prices and per capita

consumption, to formulate a set of estimates in 'high' and 'low' variants.

The product group consists of three categories, namely Newsprint, Printing &

Writing Paper, and Other Paper & Paperboard, which are analysed in turn

below.

Newsprint

Observed consumption of Newsprint is given in Table 1, and in per (thousand)

capita terms in Table 2. Production did not really increase till the early

1980s, from 50 th MT in 1981 to 102 th MT in 1982, and up to 375 th MT in

1990. Imports have been higher than production till the mid-1990s.

Regression functions of per (th) cap consumption on per cap GDP (1970

prices) are tabulated below. The double-log function indicates an income

elasticity (b) of 2.12. The semi-log function shows income elasticity

(b/conscap) falling as consumption increases: 0.78884/0.233550= 3.38 in

1960, 0.78884/0.520798= 1.515 in 1984. The log-inverse equation shows

elasticity (-b/gdp70cap) falling with income: 1591.16/643.979= 2.471 in

1960, 1591.16/908.484= 1.752 in 1984. The log-log-inverse function (without

constant term) gave income elasticity (b-c/gdp70cap) of 0.140285 +

1487.08/643.979= 2.450 in 1960, 0.140285 + 1487.08/ 908.484 = 1.777 in 1984.

Regression equations of Newsprint consumption (MT/th cap) on GDP (Rs/cap,

1970 prices)

ln conscap = -15.1205 + 2.12317 ln gdp70cap (log-log; R²=64.79%)

conscap = -4.86348 + 0.78884 ln gdp70cap (semi-log; R²=63.33%)

ln conscap = 1.0682 - 1591.16/gdp70cap (log-inverse; R²= 63.96%)

13

ln conscap = 0.140285 ln gdp70cap -1487.08083/gdp70cap (log-log-inverse; R²=

97.66%)

Projections of aggregate consumption based on the four regressions are given

in Table 4. The lowest projection (semi-log) is 463 th MT in 1990, 690 th MT

in 2000, 1690 th MT in 2025, a growth rate of 3.77% per annum. The highest

(log-log) is 487 th MT in 1990, 816 th MT in 2000, 2960 th MT in 2025, a

growth rate of 5.29%. Unless domestic production increases at a much higher

rate (from 375 th MT in 1990), we will be dependent on imports.

The FAO (1961) study projected, for South Asia, a 4.4-fold increase in

Newsprint consumption from 1955 to 1975, implying a growth rate of 7.7% per

annum over the 20-year period. Consumption in India rose from 75.5 th MT in

1955 to 153 th MT in 1975, a 2.03-fold increase with implied growth rate of

only 3.6% per annum. By 1984, however, apparent consumption grew to 555 th

MT, making an equivalent annual growth rate of 5.8% over the period 1955 to

1984, closer to the FAO (1961) projection; the difference may be due to the

slower growth of income. Imports meanwhile grew from 80 to 200 th MT, an

equivalent of 2.65% per annum. Production really increased only from 1982,

to 375 th MT by 1990.

It may be interesting to compare some other projections. NCA (1976) used the

following functions between consumption per cap Y and GDP per cap (constant

prices) X for projecting Newsprint consumption:

1980, 1985 2000 Low 2000 High

Newsprint Y=a+bX Y=a+bX logY=a+blogX

The NCA (1976) projections were: 363-471 th MT by 1985, 757-1272 th MT by

2000. Consumption in 1985 is estimated (by FAO) at 378 th MT, nearer the low

variant of NCA. Our highest estimate for 2000 is only 816 th MT, lowest 691

th MT. The NCA estimates were apparently over-optimistic. Chandrakant et al.

(1979) projected a consumption of only 67 th MT (based on national income)

and 277 th MT (time-based) for 1990, which does not fit in with the observed

values at the level of even order of magnitude.

Printing & Writing Paper

Observed consumption of Printing & Writing Paper are given in Table 1 and 2.

Imports being much less prominent, apparent consumption does not have the

periodic peaks of Newsprint consumption.

Regression functions of per cap consumption on per cap GDP (1970 prices) are

given below. The double-log function indicates an income elasticity of (per

cap) consumption (b) of 1.77. The semi- log function shows income elasticity

(b/conscap) falling as consumption increases; 1.44085/0.511864= 2.82 in


elasticity (-b/gdp70cap) falling with income: 1337.46/643.979= 2.08 in 1960,

1337.46/908.484= 1.47 in 1984. The log-log-inverse function (without

constant term) gave income elasticity (b- c/gdp70cap) of

0.205897+1181.93/643.979= 2.04 in 1960, 0.205897+1181.93/ 908.484 = 1.51 in

1984.

Regression equations of Printing & Writing Paper consumption (MT/th cap) on

GDP (Rs/cap, 1970 prices)

14



ln conscap = 1.571578 - 1337.46/gdp70cap (log-inverse; R²=77.48%)

ln conscap = 0.205897 ln gdp70cap -1181.93/gdp70cap (log-log-inverse; R²=

89.06%)

Projections of aggregate consumption based on the four regressions (assuming

exponential increase of population and per cap GDP over time) are given in

Table 4. The lowest projection (semi-log) is 983 th MT in 1990, 1433 th MT



growth rate of 4.77%. Domestic production has increased from 99 th MT in

1953 to 975 th MT in 1990, a growth rate of 6.38% over a pretty long period,

a more satisfactory position than in the case of newsprint.


Printing & Writing Paper consumption from 1955 to 1975, implying a growth

rate of 7.2% per annum over the 20-year period. Consumption in India rose

from 122.67 th MT in 1953-55 to 507 th MT in 1975, a 4.13-fold increase with

implied growth rate of 6.99% per annum. Over the period 1953-1955 to

1983-1985, apparent consumption grew from 122.67 to 831.67 th MT, equivalent

to an annual growth rate of 6.59%.

NCA (1976) projected a consumption of 935-1175 th MT by 1985, and 1777-3675

th MT by 2000; as in the case of Newsprint, these are rather high estimates.

The function forms used were as follows (Y= consumption per cap, X= GDP per

cap at constant prices):

1980, 1985 2000 Low 2000 High

Printing & Writing Y=a+blogX Y=a+blogX Y=a+bX

Paper

Chandrakant et al. (1979) projected a consumption of 280 th MT (based on

national income) and a high of 1074 th MT (time-based trend) for 1990; the

range is excessive, indicating some problem with their data base or their

analysis. Using the function form lnY= a+ b lnX + cX, where Y is aggregate

consumption, X is aggregate national income, is perhaps the cause of their

projections of decreasing consumption.

Other Paper & Paperboard

Observed consumption of Other Paper & Paperboard are given in Table 1 and

Table 2. Imports are again negligible. Regression functions of per cap

consumption on per cap GDP (1970 prices) are tabulated below. The double-log

function indicates an income elasticity of (per cap) consumption (b) of

1.06. The semi-log function shows income elasticity (b/conscap) falling as

consumption increases; 0.644114/0.444735= 1.45 in 1960, 0.644114/0.771802=

0.84 in 1984. The log-inverse equation shows elasticity (-b/gdp70cap)

falling with income: 803.698/643.979= 1.25 in 1960, 803.698/908.484= 0.89 in

1984. The log-log-inverse function (without constant term) gave income

elasticity (b-c/gdp70cap) of 0.077586 + 744.39/643.979= 1.23 in 1960,

0.077586+ 744.39/ 908.484 = 0.897 in 1984.

Regression equations of Other Paper & Paperboard consumption (MT/th cap) on

15





ln conscap = 0.077586 ln gdp70cap - 744.38989/gdp70cap (log- log-inverse;

R²= 97.79%)

Projections of aggregate consumption based on the four regressions (assuming

exponential increase of population and per cap GDP over time) are given in

Table 4. The lowest projection (log-inverse) is 655 th MT in 1990, 910 th MT



growth rate of 3.73%. Domestic production has increased from 65.67 th MT in

1953-55 to 850 th MT in 1990, a growth rate of 7.37% over a pretty long

period; from 1975 to 1990, production rose from 355 th MT to 850 th MT,

indicating a growth rate of 5.99% per annum.


consumption of Packaging, Wrapping and Other Paper & Paperboard, from 132 th

MT in 1953-55 to 620 th MT 1975, implying a growth rate of 8.05% per annum

over a 20-year period. Consumption of Other Paper & Paperboard in India rose

from 105.97 th MT in 1953-55 to 367 th MT in 1975, a 3.46-fold increase with

implied growth rate of 6.09% per annum. Over the period 1953-1955 to

1983-1985, apparent consumption grew from 105.97 to 587.33 th MT, an annual

growth rate of 5.87%.

NCA (1976) projected consumption of Industrial Paper and Paperboard by

regressing per cap consumption Y on per cap GDP X using the following

function forms:

1980, 1985 2000 Low 2000 High

Industrial Paper Y=a+bX Y=a+bX logY=a+blogX

Paperboard Y=a+blogX Y=a+blogX Y=a+bX

The NCA projections of consumption of these categories together were:

732-943 th MT by 1985, 877-2883 th MT by 2000; as in the case of Newsprint,

these are rather high estimates. Chandrakant et al. (1979) projected a

consumption of 256 th MT (based on national income) and a high of 569 th MT

(time-based trend) for 1985, and 153 th MT (based on national income) and

686 th MT (time-based trend) for 1990; as before, they arrive at decreasing

aggregate consumption on their NI-based regression, which is by all counts

not acceptable for a developing country like India which has a long way to

go before reaching saturation limits of paper consumption.

Aggregate Paper & Paperboard

Observed consumption of the three component categories put together are

given in Table 1 and Table 2. Regression functions of per cap consumption of

the aggregates on per cap GDP (1970 prices) are tabulated below. The

double-log function indicates a constant income elasticity of (per cap)

consumption (b) of 1.59. The semi- log function shows income elasticity

(b/conscap) falling as consumption increases: 2.87457/1.189688= 2.42 in


elasticity (-b/gdp70cap) falling with income: 1202.796/643.979= 1.87 in

16

1960, 1202.796/908.484= 1.32 in 1984. The log-log-inverse function (without

constant term) gave income elasticity (b- c/gdp70cap) of 0.286111 +

987.019342/643.979= 1.82 in 1960, 0.286111+ 987.01342/ 908.484 = 1.37 in

1984.

Regression equations of Paper & Paperboard consumption (MT/th cap) on GDP

(Rs/cap, 1970 prices)

ln conscap = -9.96579 + 1.59162 ln gdp70cap (log-log; R² = 83.49%)

conscap = -17.2306 + 2.87457 ln gdp70cap (semi-log; R^2 = 84.27%)

ln conscap = 2.18336 -1202.796/gdp70cap (log-inverse; R²= 84.20%)

ln conscap = 0.286111 ln gdp70cap - 987.01955/gdp70cap (log- log-inverse;

R²= 98.45%)

Summing the separate projections of the three categories gives projections

which are very close to projections based on these regression equations;

slightly higher in the case of log-log and log-inverse, almost identical in

the case of semi-log, and very slightly lower in the case of log-log-inverse

model respectively. To take into account differing elasticities, we use the

sum of the individual projections in place of projections of the aggregate.

The sum of projected consumption of Newsprint, Printing & Writing Paper, and

Other Paper & Paperboard, on the four GDP-based regressions (assuming

exponential increase of per cap GDP and population over time) are given in

Table 4. The lowest projection (semi-log) is 2098 th MT in 1990, 3030 th MT



growth rate of 4.62%. Domestic production has increased from 225.60 th MT in

1955 to 2200 th MT in 1990, a growth rate of 6.72% over a pretty long

period; from 1975 to 1990, production rose from 911 th MT to 2200 th MT,

indicating a growth rate of 6.05% per annum. Shortfall of production is, as

discussed above, mainly in Newsprint.


consumption of paper plus paperboard, from 376 th MT in 1953-55 to 1605 th

MT 1975, implying a growth rate of 7.53% per annum over a 20-year period.

Consumption of Paper & Paperboard in India rose from 369 th MT in 1955 to

1048.33 th MT in 1974-76, a 2.84-fold increase with implied growth rate of

5.36% per annum. Over the period 1955 to 1984-1986, apparent consumption

grew from 369 to 1896 th MT, equivalent to an annual growth rate of 5.61%.

The NCA (1976) projections of total Paper & Paperboard consumption were:

2030-2589 th MT by 1985, 3411-7836 th MT by 2000; as in the case of

individual components, these are rather high estimates, and the range

between low and high variants is excessive. Chandrakant et al. (1979)

projected a consumption of 796 th MT (based on national income) and 1649 th

MT (time-based) in 1985, 518 th MT (based on national income) and a high of

2017 th MT (time-based trend) for 1990; as before, their decreasing

consumption based on NI is not realistic.

However, a note of caution is struck by Gupta and Shah (1987). After

comparing various projections of paper and paperboard demand with actual

levels of consumption, they go so far as to say that most projections are

exaggerated, and some of them may well have been aimed at "creating fear

psychosis with the object of molding policies". They point out that there is

17

already idle capacity in the existing paper factories (they have not

included newsprint in their critical analysis), and one must be careful

before recommending further expansion.

5.2 Wood-based panel products

The panel products include plywood, veneer sheets, particle board and

fibreboard (compressed and non-compressed). These relatively recent,

technology-intensive products are expected to expand rapidly in the initial

years as they move into their most competitive uses, and then grow at a more

sedate pace in tune with the economy and with population. The first two

products are fairly exacting in their raw material requirements, while

particle board and fibreboard can be made from small sized material, chips,

waste, etc.

Plywood & Veneer Sheets

Observed consumption of Plywood & Veneer Sheets is given in Table 1 in th

cum(s), and in Table 2 in cum(s)/th cap. Figures of production from 1985 to

1990 are suspect, as they repeat the figure for 1984; perhaps there was no

authentic information available in time for compilation. Veneer Sheet forms

a minor component, in fact only 4 th cum from 1979 to 1990 according to FAO

Yearbook (1992). Interestingly, India has had net exports from 1966, though

in small quantities.


tabulated below. The double-log function indicates an income elasticity (per

cap) of 2.37. The semi-log function shows income elasticity (b/conscap)

falling as consumption increases; 0.660338/0.165027= 4.00 in 1960,

0.660338/0.476504 = 1.39 in 1984. The log-inverse equation shows elasticity

(-b/gdp70cap) falling with income: 1757.649132/ 643.979= 2.73 in 1960,

1757.649132/908.484= 1.935 in 1984. The log-log-inverse function (without

constant term) gave income elasticity (b-c/gdp70cap) of 0.12112 +

1670.583568/ 643.979 = 2.715 in 1960, 0.12112 + 1670.583568/ 908.484 = 1.96

in 1984. The log-log-inverse function with constant (intercept) term yields

reasonable, if high, predictions within the range of observed values, but

gives absurdly high projections for later years, hence was replaced by the

same function with zero intercept.

Regression equations of Plywood & Veneer Sheet consumption (cum(s)/th cap)

on GDP (Rs/cap, 1970 prices)




ln conscap = 0.12112 ln gdp70cap - 1670.583568/gdp70cap (log-log-inverse;

R²= 98.81%)

Projections of consumption of Plywood & Veneer Sheet based on the four

regressions (assuming exponential increase of per cap GDP and population

over time) are given in Table 4. The lowest projection (semi-log) is 345 th

cum(s) in 1990, 525 th cum(s) in 2000, 1323 th cum(s) in 2025, a growth rate

of 3.79% per annum. The highest (log-log) is 357 th cum(s) in 1990, 618 th

cum(s) in 2000, 2444 th cum(s) in 2025, a growth rate of 5.65%. Domestic

production has increased from 29 th cum(s) in 1954 to 364 th cum(s) in 1990,

18

a growth rate of 7.28% over the period; from 1974 to 1984, production rose

from 151 to 364 th cum(s), indicating a growth rate of 9.20% per annum.

The FAO (1961) study estimated that during 1953-55, in South Asia, the match

industry took some 63% of annual consumption of veneer, while of plywood

consumption, packaging took 81%, furniture 8%, and construction only 1.3%.

The study projected, for South Asia, over the period 1953-55 to 1975, a

modest 1.67-fold increase (450 to 750 th cum(r)) in consumption of veneers,

a 2.00-fold increase (185 to 370 th cum(r)) in plywood consumption, for a

total for both together from 635 th cum(r) in 1953-55 to 1120 th cum(r) in

1975, or 1.76 times; implying a growth rate of 2.87% per annum over the

20-year period. According to the FAO series, consumption of Plywood & Veneer

Sheet in India rose from 29 th cum(s) in 1954 to 120 th cum(s) in 1975, a

4.14-fold increase with implied growth rate of 7.00% per annum. Over the

period 1954 to 1983-1985, apparent consumption grew from 29 to 335 th

cum(s), equivalent to an annual growth rate of 8.50%. These high rates

indicate that these technologically advanced products were still moving into

new uses in which they had a competitive edge.

NCA (1976) projected consumption of Plywood & Veneer Sheet (computed at 2.3

cum(r) per cum(s)) as 304.4 to 419.6 th cum(s) by 1985, 584.8 to 937.0 th

cum(s) by 2000. These are higher than our projections. Chandrakant et al.

(1979) projected a consumption of 70 th cum (based on national income) and a

high of 166 th cum (time-based trend) for 1985, and 38 th cum (based on

national income) and a high of 191 th cum (time-based trend) for 1990; as

before, decreasing consumption on their NI-based regression is unrealistic.

One question about the FAO statistics is that veneer consumption for matches

does not seem to be included. NCA (1976) quotes Planning Commission

estimates of projected roundwood requirement for match manufacture as rising

from around 328 th cum(r) in 1973-74 through 485 th cum(r) in 1978-79, to

1339 th cum(r) in 2000. At roundwood input of 1.9 cum(r) per cum(s) of

veneer, this implies production of respectively 201, 255 and 705 th cum(s)

veneer sheet. The FAO production figure of veneer sheet in 1973 was only 2

th cum(s), and that in 1974 only 8 th cum(s); plywood production was 126 and

143 th cum(s). FAO estimates of veneer production (FAO 1992) from 1979

through 1990 is only 4 th cum(s).

A plausible explanation is that FAO includes match billets in the category

Sawlogs & Veneer Logs, and does not make a separate estimate of roundwood

input from veneer used in match production. If this has to be separated out,

we can make a rough projection as follows. Installed capacity of matches in

1979 and 1980 was around 5000 million boxes of 50 sticks each (Govt. of

India, 1982); a conversion factor available is 28.8 thousand boxes per

cum(r) of wood, or 0.03472 cum(r) for 1000 boxes or 34.72 cum(r) for 1

million boxes; 5000 million boxes therefore required 5*34.72 = 173.6 th

cum(r). At 1.9 cum(r) per cum(s) of veneer, this implies production of

veneer of 173.6/1.9 = 91.37 th cum(s) (1980). Actual production during 1980

was 4037.4 million boxes, or 80.75% of capacity (ibid.). This can be

projected at the population growth rate of around 2.19% per annum. In any

case NCA estimates of matchwood requirements (e.g. 485 th cum(r) in 1978-79)

seem too high in comparison with capacity, let alone actual production of

matches. Perhaps NCA perceived a major shortfall in matchwood availability

when compared to 'desired' consumption levels.

19

Fibreboard & Particleboard contribute such a tiny part of the requirement

that they are ignored for the purpose of roundwood projections (although, as

a growing sector with less exacting raw material specifications than

plywood, they are very important for planning future development).

5.3 Sawnwood & Sleepers

The bulk of industrial wood is used as sawnwood and wood in the round. Per

cap consumption of sawnwood, as of other industrial wood products, is low in

South Asia, due to supply side constraints and low purchasing power of

consumers.

Observed consumption of Sawnwood & Sleepers is given in Table 1, in th

cum(s), and in Table 2 in cum(s) per th cap. Earlier FAO Yearbooks gave

separate figures for Sawnwood and for Sleepers, but the two have been

clubbed in the 1992 issue. In any case, consumption of sleepers is quite a

minor component (e.g., 252 th cum(s) compared with 14500 th cum(s) for

sawnwood in 1983). Figures of production from 1986 to 1990 are suspect, as

they repeat the figure for 1985, forming a break in the upward trend. Trade

forms a negligible component.


tabulated below. The double-log function indicates an income elasticity (per

cap) of (b=) 5.06. The semi-log function shows income elasticity (b/conscap)

falling as consumption increases; 50.801972/4.1344= 12.29 in 1961,

50.801972/23.2521 = 2.19 in 1984. The log-inverse elasticity (-b/gdp70cap)

falls with income: 3842.546651/ 651.731= 5.90 in 1961, 3842.546651/908.484=

4.23 in 1984. The log-log-inverse function (without constant term) gave

income elasticity (b-c/gdp70cap) of 0.96066 + 3114.371751/651.731= 5.74 in

1961, 0.96066 + 3114.371751/908.484 = 4.39 in 1984. The log-log-inverse

function with forced constant (intercept) term gives non-significant

coefficients, hence was rejected for the zero-intercept function. The

semi-log regression gives negative consumption figures for the years 1950 to

1957, reminding us that projections outside the range of observations must

be interpreted with caution.

Regression equations of Sawnwood & Sleepers consumption (cum(s) per th cap)

on GDP (Rs/cap, 1970 prices)




ln conscap = 0.96066 ln gdp70cap - 3114.371751/gdp70cap (log-log-inverse;

R²= 99.44%)

Projections of consumption of Sawnwood & Sleepers based on the four


over time) are given in Table 4. The semi-log regression gives lowest

projections: 19,100 th cum(s) in 1990 (against observed 17,465), 31,155 th

cum(s) in 2000, and 85,769 th cum(s) in 2025, a growth rate of 4.42% per

annum. The highest projection (double-log) is 26,026 th cum(s) in 1990,

65,644 th cum(s) in 2000, and 663,243 th cum(s) in 2025, a growth rate of

9.69%. From 1974 to 1984, domestic production rose from 6212 to 15907 th

cum(s), a growth rate of 9.86% per annum.

20

The FAO (1961) survey estimated that the major end-use sectors of industrial

wood in 1953-55 were housing construction (40%) and packaging (20%). It was

estimated that every new house required sawnwood of 1/6 cum(s) in rural

construction, 1 2/3 and cum(s) in urban. FAO (1961) estimated that 450,000

to 500,000 new houses needed to be added every year for the increasing urban

population (1955 level), against actual addition of only 175,000 to 200,000

(or, by the more liberal Indian definition of urban, 260,000) dwellings a

year.

The FAO (1961) study projected, for South Asia, over the period 1953-55 to

1975, the following rise in annual consumption of sawnwood: in urban house

construction, a 4-fold increase; in rural construction, a 1.4-fold increase,

in pace with rural population; rural and urban construction combined, a

2.4-fold increase, implying a growth rate of 4.5% per annum over the 20-

year period. The other major end-use, non-residential construction, was

projected to grow in pace with national income, and annual sawnwood demand

to grow at the same rate as national income, i.e. 2.25 times (growth rate

4.1%). Consumption of sawnwood in packaging, which took 20% of all

industrial wood in 1953- 55 (69% of this being sawnwood) was projected to

grow 1.75 times, slower than NI. Transport and communications was another

major user sector (railway lines, vehicles, etc.): annual consumption of

sawnwood was projected to grow 1.54 times. Including other end-uses like

furniture, annual demand for sawnwood was projected to grow on the whole to

2.1 times (growth rate 3.8%).

According to the FAO Yearbooks series, consumption of Sawnwood (excluding

Sleepers) in India rose from 1396 th cum(s) in 1955 to 11124 th cum(s) in

1975, a 7.97-fold increase with implied growth rate of 10.94% per annum,

much higher than the FAO (1961) projection for South Asia. Over the period

1955 to 1984, apparent consumption of Sawnwood (excluding Sleepers) grew

from 1396 to 15660 th cum(s), equivalent to an annual growth rate of 8.69%.

NCA (1976) projections of sawlog demand are compared later. Chandrakant et

al. (1979) projected a sawnwood consumption of 3591 th cum (based on

national income) and a high of 4744 th cum (time- based trend) for 1985, and

3403 th cum (based on national income) and a high of 5681 th cum (time-based

trend) for 1990; as before, decreasing consumption on their NI-based

regression is unrealistic, and their projections are inexplicably low

compared to FAO estimates of past consumption.

6. Derived demand of Industrial Roundwood

For the industrial wood products analyzed above (Paper & Paperboard, Plywood

& Veneer Sheet, Sawnwood & Sleepers), roundwood equivalent can be computed

by adopting standard conversion factors. The first exercise we do now is to

compare such derived demand figures with the time series for intermediate

product and roundwood categories in the FAO Yearbooks.

6.1 Pulpwood

Roundwood equivalent of Paper & Paperboard

Overall, pulp requirement was assumed by NCA (1976) as 1.050 MT pulp per MT

of Printing & Writing Paper, Newsprint, Industrial Paper, Absorbing Paper,

Other Paper & Paperboard, and Rayon-grade Pulp, for projections from 1970

21

through 2000 AD. The only deviation from this conversion ratio was in the

case of Printing & Writing Paper projection for 2000, which was 0.960 MT

pulp per MT product. From the FAO series we are using, multiplying produc-

tion of Paper & Paperboard by 1.050 gives figures that are close to

consumption of Pulp excluding Dissolving Woodpulp up to 1979, but lower for

the years 1980 to 1990. For our purposes, we can adopt a standard input of

1.050 MT pulp for all products for projecting pulp requirements.

This will not lead us directly to pulpwood requirements, however, without

some intervening assumptions. Non-wood pulp (Other Fibre Pulp which includes

bamboo pulp) has been more important in South Asia than in other regions. As

per the FAO series, Other Fibre Pulp constituted over 90% of pulp production

during the 1950's and early 1960's, falling to around 65% in the 1980's. The

NCA projections of pulpwood requirements assume that wood pulp will grow in

importance as industrial pulpwood plantings are expanded. NCA (1976)

predicts the following input composition per MT of product:

Wood Non-wood pulp (OFP) Total

pulp Bamboo Other Total pulp

(MT pulp input per MT of product)

Print. & Writ. Paper 1970 0.188 0.478 0.384 0.862 1.050

1980 0.529 0.453 0.068 0.521 1.050

2000 0.615 0.125 0.220 0.345 0.960

Newsprint 1970 0.600 0.450 0.450 1.050

1980 0.750 0.180 0.120 0.300 1.050

2000 0.950 0.100 0.100 1.050

Industrial Paper 1970 0.068 0.573 0.409 0.982 1.050

1980 0.516 0.451 0.083 0.534 1.050

2000 0.612 0.174 0.264 0.438 1.050

Absorbing Paper 1970 1.050 1.050 1.050

1980 0.150 0.900 0.900 1.050

2000 0.200 0.850 0.850 1.050

Other Paper & 1970 0.572 0.478 1.050 1.050

Paperboard 1980 0.433 0.147 0.470 0.617 1.050

2000 0.321 0.204 0.525 0.729 1.050

Rayon grade pulp 1970 0.210 0.840 0.840 1.050

1980 0.840 0.210 0.210 1.050

2000 0.900 0.150 0.150 1.050

Putting together these assumptions and the demand for end-products, NCA

arrived at the following projections of Pulpwood requirement: 3675-4175 th

cum(r) in 1980, 4715-6055 in 1985, 9680-17695 in 2000. These are quite high

compared with FAO estimates of current availability (1208 th cum) as well as

with our projections.

A paper by the Chairman of the Development Council for Pulp, Paper and

Allied Industries (Singhania, 1990) gives another scenario. His projections

of demand, especially of Newsprint, are rather high compared with ours, but

projection for 2015 (7981 th MT consisting of Newsprint 2648 th MT plus

Paper & Board 5333 th MT), is not too different from our estimates. The

22

author then estimates raw material requirements at 2 MT pulpwood per MT of

newsprint, and 2.8 MT pulpwood per MT of paper (average 2.62 in 1990 falling

to 2.54 in 2015). The pulpwood requirement comes out to 6443 th MT in 1990,

20228 th MT in 2015. Pulpwood availability in 1990 is estimated at 1310 th

MT, only 20.33% of total requirement of 6443 th MT (FAO estimates 35% of

pulp production in 1990 came from wood sources, and Pulpwood production in

1990 was 1208 th cum); and availability of bamboo in 1990 at 1900 th MT,

29.49% of total requirement of 6443 th MT. The remaining 49.82% (in wood

equivalent) must have come from other fibres (and imports). The forest raw

materials (wood and bamboo) together account for only 1235 th MT of paper

and newsprint, or 50.24% of the requirement of 2458 th MT in 1990.

Singhania goes on to explore the requirement of non-wood fibres if it is

assumed that forest raw material availability will not improve over time.

Paper production from bagasse is projected to rise from 180 th MT in 1990 to

840 th MT in 2015; paper from straw will rise from 200 th MT in 1990 to 250

th MT in 2015. Waste paper will account for production of 215 th MT paper in

1990, 1000 th MT in 2015; both the quantity of waste paper and the

utilization will improve. Thus the total production of paper and newsprint

from identified sources of raw material will increase from 1829 th MT in

1990 to 3325 th MT in 2015, with the corresponding production-demand gap

growing from 629 th MT paper (25.6% of demand of 2458 th MT) in 1990 to 4656

th MT (58.34% of demand of 7981 th MT) in 2015. His inference is that if

imports to this tune of newsprint, waste paper or pulp are to be avoided,

industrial pulpwood plantations will have to be raised.

Different types of pulp require different quantities of wood. Singhania (op.

cit.) uses the input coefficients 2.80 MT wood per MT of paper, and 2.00 MT

wood per MT newsprint. If density of pulpwood is assumed to be 0.750 MT per

cum(r), this would correspond to 3.73 and 2.67 cum(r) respectively per MT of

product. (Standard FAO conversion factors are given in Appendix 2).

Mechanical pulp is used mainly for newsprint, and thus the raw material

requirement (roundwood equivalent) for newsprint can be computed fairly

precisely. For other product groups, however, pulpwood requirement would

depend on types of pulp, and of course on quantity of non-wood pulp

utilized. There are thus many factors that are simultaneously variable,

subject to policy and planning decisions. Ultimately one guess may be as

good as another.

In the above circumstances, perhaps the best that could be done here is to

make an estimate of roundwood requirement taking the latest FAO conversion

factors, rather than computing pulp equivalents and then roundwood

requirements. We use the semi-log regressions of per cap consumption versus

per cap GDP of each product category, which give the lowest projections; and

use the roundwood input coefficients 2.8, 3.5 and 3.25 cum(r) per MT of

Newsprint, Printing & Writing Paper, and Other Paper & Paperboard,

respectively. Bamboo forms a substantial part of Other Fibre, and it is not

anticipated that bamboo supplies from the forest will increase in the

future. We make a gross assumption, therefore, that Pulpwood will form

around 40% of the wood raw material equivalent computed as above, against

the 35% estimated by FAO for 1989 and 1990.

On this basis, Pulpwood requirement for Paper & Paperboard will grow from

2743 th cum(r) in 1990 to around 3957 th cum(r) in 2000, 6628 th cum(r) in

2015, and 9190 th cum(r) in 2025 (Table 3). This accounts for only 40% of

23

the roundwood equivalent of projected Paper & Paperboard consumption. Any

other scenario could be accommodated. For comparison, Table 3 also gives

pulpwood equivalent of the entire projected consumption of Paper and

Paperboard and Dissolving Pulp. Further, this is as per the semi- log

regression; this gives low projections overall, and it must be mentioned

that the aggregate consumption as per the equations for 1981 to 1990 is

lower than observed consumption. The spurt in production from 962 th MT in

1980 to 1266 th MT in 1981 is not reflected by the regression function,

which can only indicate a broad trend at the average level over the time

period. Thus we expect that the above projection will be a realistic, fairly

modest one, in spite of not using a factor of 1.6 cum(r) per MT of

Paperboard (FAO conversion factor) separately.

The FAO series of Pulpwood & Particles shows production (equal to

consumption) peaking at 1355 th cum(r) in 1976, then stagnating at 1208 th

cum(r) through to 1990. These are rather low figures even on the basis of

the FAO series of product categories. For instance, roundwood equivalent of

paper products imports has apparently not been added, which may bring the

figure to the neighbourhood of 2000 th cum(r). For consumption of 1990, wood

raw material equivalent would be (2.8*555+ 3.5*1020 + 3.25*867)= 7941.75 th

cum(r); 40% of this would be 3176.7 th cum(r). For domestic production

alone, roundwood equivalent would be 7225, 40% of which is 2890 th cum(r).

The FAO series of Pulpwood & Particles probably under-estimates pulpwood

production. Regression against per cap GDP gives the following equations.

Regression equations of Pulpwood & Particles consumption (cum(r)/th cap) on

GDP (Rs. per cap, 1970 prices)

ln conscap = -47.6953 + 7.17336 ln gdp70cap (log-log; R²= 55.32%)

conscap = -34.7987 + 5.43001 ln gdp70cap (semi-log; R²= 61.09%)


ln conscap = 456.6649 - 58.8647 ln gdp70cap - 50129.25/gdp70cap

(log-log-inverse; R²= %)

The semi-log equation gives projected Pulpwood demand (on exponential growth

of population and GDP per cap) of 2083 th cum(r) in 1990, 3382 th cum(r) in

2000, 6340 th cum(r) in 2015, and 9258 th cum(r) in 2025. These projections

are generally lower than the sum of the (semi-log) projections of component

products (see above), but the two projections come close together by the

year 2025 (9258 and 9190 th cum). As already discussed, NCA projections are

on the high side.

Dissolving Wood Pulp

Dissolving Pulp requires around 5.5 cum(r) per MT as per the FAO Yearbook,

1966. Here again wood is only one source: NCA (1976) projects that, out of

1.050 MT pulp, wood pulp proportion will rise from just 0.210 MT in 1970, to

0.840 MT in 1980 and 0.900 MT in 2000; the other component being bamboo

pulp. For our analysis, however, as in the case of paper products, we assume

that wood pulp will provide uniformly around 40% of total pulp requirements.

Regression equations of consumption of Dissolving Pulp (MT/th cap) on per

cap GDP (Rs/cap, 1970 prices)


24

conscap = -5.68677 + 0.881948 ln gdp70cap (semi-log; R²= 65.27%)


ln conscap = 450.5080 - 58.12919ln gdp70cap - 50754.78/gdp70cap

(log-log-inverse; R²=71.95%)

Of these, the double-log and log-inverse give unrealistically high

projections, while the log-log-inverse predicts consumption falling away to

zero. The semi-log regression is adopted as the most 'reasonable':

consumption demand would rise to 309 th MT by 1990, 513 in 2000, 979 in

2015, and 1441 th MT in 2025 (Table 4). Roundwood equivalent is calculated

at 5.5 cum(r) per MT; only 40% of this is assumed to be from wood, which

will be 644 th cum(r) in 1990, 1129 in 2000, 2155 in 2015, 3171 in 2025

(Table 3).

Adding this requirement to the pulpwood requirement of Paper & Paperboard

will give us total pulpwood requirements (40% of roundwood equivalent of all

paper and pulp products, semi-log regressions of consumption on GDP per

cap). On this basis, consumption of Pulpwood & Particles should be 3423 th

cum(r) in 1990, 5086 in 2000, 8783 in 2015, 12361 th cum(r) in 2025 (Table

3).

6.2 Veneer Logs

We consider here the roundwood requirements of plywood and veneer sheets;

fibreboard and particleboard are relatively minor items so far, and their

raw material requirements are different. Conversion factors for panel

products used by FAO are given in Appendix 2.

As before, we use the 'low' projection of consumption from the semi-log

regression. Veneer sheet production in the FAO series does not include

veneer going into plywood production, and in any case forms a very minor

part (only around 4 th cum(s) per year), hence the entire quantity of

Plywood+Veneer Sheet is treated as plywood, and converted at 2.3 cum(r) per

cum(s). The roundwood requirement then would be expected to rise from 793 th

cum(r) in 1990, through 1208 th cum(r) in 2000, 2137 th cum(r) in 2015, to

3042 th cum(r) in 2025. NCA (1976) predicted a demand of 520-600 th cum(r)

in 1980, 700-965 in 1985, 1345-2155 th cum(r) in 2000; as per FAO estimates

of actual production and consumption, at 2.3 cum(r) per cum(s), requirement

of roundwood was 446 th cum(r) in 1980, 816.5 th cum(r) in 1985, and 819 th

cum(r) in 1990. Our projections are on the low side, compared with NCA

projections.

For matchwood, we start from the production of 4037.4 million boxes in 1980,

and project this at the population growth rate of 2.19% per annum,

converting to roundwood equivalent at 28.8 thousand boxes per cum(r) of

wood. This is evidently an optimistic scenario, seeing that both capacity

and production were falling from a peak in 1960. Be that as it may, the

added roundwood requirement is projected to grow from 174 th cum(r) in 1990,

to 216 in 2000, 299 in 2015, and 372 th cum(r) in 2025. NCA (1976), on the

other hand, has 535 th cum(r) [281.58 th cum(s)] in 1980, 680 (r) [357.9

(s)] in 1985, and 1415 (r) [744.74 (s)] in 2000: over 6.5 times our

projection.

6.3 Sawlogs

25

The FAO Yearbook 1974 recommended slightly higher roundwood input

coefficients for India to account for lower efficiency in conversion.

However, recycling of sawnwood will reduce the roundlog requirement to some

extent. We use an average of 1.8 cum(r) per cum(s) for our computations.

Using the 'low' projections provided by the semi-log regression of per cap

consumption on per cap GDP, round logs required (at coefficient of 1.8) will

grow from 34380 th cum(r) in 1990, to 56079 in 2000, 105565 in 2015, and

154385 th cum(r) in 2025. NCA (1976) has projections of sawlog demand of

13145-14100 th cum(r) in 1980, 15665-18300 in 1985, and 22940- 29650 th

cum(r) in 2000: the 'high' estimate is just over one half of our figure for

2000.

6.4 Sawlogs & Veneer Logs

Adding together our projections of roundwood equivalent of Sawnwood &

Sleepers, Plywood & Veneer sheets, and Matches, we get our projections of

total requirement of Sawlogs & Veneer logs (Table 3). These projections are;

35347 th cum(r) in 1990, 57503 in 2000, 108001 in 2015, 157798 in 2025. This

works out to an annual growth rate of 4.37% over the period 1990-2025.

NCA (1976) projections of round logs for Sawnwood, Veneer and Matches are:

14200-15235 th cum(r) in 1980, 17045-19945 in 1985, and 25700-33220 in 2000:

all much lower than our estimates. Chandrakant et al. (1979) give

projections of 8076-8802 th cum(r) in 1980, 8598-10579 in 1985, and

8643-12716 th cum(r) in 1990: lower than even the FAO series.

Comparing with our FAO series of Sawlogs & Veneer logs as well, our derived

consumption figures are on the high side: for 1985, the FAO series has 18369

th cum(r), around the NCA projection and quite low compared to our

computation of derived demand of 32245 th cum(r) or the calculated figure of

26821. Looking closer, if we take roundwood equivalents of Sawnwood &

Sleepers (conversion coefficient 1.8) and Plywood & Veneer Sheet (conversion

coefficient 2.3), the resulting series is lower than the FAO series of

Sawlogs & Veneer Logs up to 1973, but takes off to higher levels

subsequently: for 1990, the figures are respectively 32256 and 19184 th

cum(r). Adding matchwood naturally increases the difference.

Regression functions of per cap consumption on per cap GDP (1970 prices) of

the FAO series for Sawlogs & Veneer Logs are tabulated below. The double-log

function indicates an income elasticity (per cap) of (b=) 2.88. The semi-log

function shows income elasticity (b/conscap) falling as consumption in-

creases; 45.0275/9.11= 4.94 in 1961, 45.0275/23.53= 1.91 in 1984. The

log-inverse elasticity (-b/gdp70cap) falls with income: 2203.01/ 651.731=

3.38 in 1961, 2203.01/908.484= 2.43 in 1984. The log-log-inverse function

gave income elasticity (b-c/gdp70cap) of -12.3057 + 11524/651.731= 5.38 in

1961, -12.3057+ 11524/908.484 = 0.38 in 1984.

Regression equations of Sawlogs & Veneer Logs consumption (cum(r) per th

cap) on GDP (Rs/cap, 1970 prices)




ln conscap = 99.6627 -12.3057 ln gdp70cap - 11524/gdp70cap (log-log-inverse;

R²= 86.10%)

26

Projections of consumption of Sawnlogs & Veneer Logs based on the four


over time) are given in Table 3. The semi-log regression gives projections

of 23,108 th cum(r) in 1990 (against observed 19,184), 35,306 th cum(r) in

2000, and 89,323 th cum(r) in 2025, a growth rate of 3.94% per annum. The

highest projection (double-log) is 26,731 th cum(r) in 1990, 49,712 th

cum(r) in 2000, and 234,464 th cum(r) in 2025, a growth rate of 6.40%. The

log-log- inverse regression yields projections that closely track the

observed consumption, and rise to a peak of 21003 th cum(r) in 1998, then

fall to 10666 th cum(r) in 2025.

Since it appears to be the sawlog category that is contributing mightily to

projected increase in consumption demand of industrial wood, it would be

worthwhile to look at other, independent estimates of consumption. One

source is the series of Wood Consumption Studies undertaken by the Forest

Survey of India (FSI), Dehradun. We have looked at the studies for some of

the districts of Karnataka state, which give estimates based on surveys of

mainly the wood in use in construction, furniture, and agricultural

implements (apart from bamboos and fuelwood) (Table 5).

If population growth were the only factor contributing to annual consumption

demand, aggregate consumption would grow every year at say 2.2% to meet the

additional requirement; and the per cap annual consumption would be 2.2% of

per cap wood in use. In addition, some portion of the wood in use is

replaced every year for repairs and replacements. Based on observations, FSI

found that in Mysore and Bangalore, 1.3% of the wood in use in construction,

2% of the wood in use in furniture, and 8% of that in agricultural

implements, is replaced every year. We have made the calculations of this

afresh, in Table 5, for all the 5 districts cited; the replacement demand

works out to between 1.55% and 3.00% of wood in use, with the median around

1.9, or say 2%. For Chikmagalur and Hassan districts, the FSI survey reports

annual replacement of 3% for dwellings (average life 33 years), 0.5% (sic)

for furniture (average life 50 years) and of 25% (sic) of wood in use in

agricultural implements (average life 10 years). The FSI figures of annual

per cap consumption demand are also given in the last line of Table 5.

While it is not clear in the FSI reports whether the wood in use is measured

in cum (sawn) or cum (round), we assume that it is the latter. FSI estimates

of annual demand of timber are of the order of 0.04+ cum per cap per annum

in Shimoga, Mysore, Chikmagalur, 0.03 in Hassan, and 0.017 in Bangalore and

Bellary. The former are closer to the derived figures of sawlog demand in

Table 2, rather than to the (lower) observed consumption in the FAO

Yearbooks, which range from 0.02255 cum(r) per cap in 1980 through 0.02446

in 1985. Not unexpectedly, districts with better access to forest resources

(Shimoga, Mysore, Chikmagalur) had higher consumption than the drier

districts (Bangalore, Bellary), with an intermediate figure for Hassan.

One feature which should be noted, for sawlogs as for all other categories,

is the steady rise in per cap consumption. Thus, aggregate consumption

rises, not only because of increasing population, but also because people

are consuming more of all commodities. It may not be correct to assume that

it is the rich alone or the urbanites alone who are increasing their

consumption per cap, as incomes are increasing in all classes. In fact, the

FSI surveys quoted are a timely reminder that per cap consumption of wood in

27

rural areas is actually higher than in urban.

On balance, it appears that the FAO series of consumption of Sawlogs &

Veneer Logs may be under-estimates, possibly caused by taking lower input

coefficients than recommended. Recycling of wood already in use will reduce

current demand, but it is anyone's guess what this proportion should be. Our

projections based on roundwood equivalents of sawnwood and plywood may be

over-estimating annual roundwood demand to a certain extent by ignoring

recycling, but otherwise the derived demand figures are probably closer to

reality.

6.5 Other Industrial Roundwood

This includes many forms like poles, pitprops, posts, etc. which are

especially used in rural and low-cost housing, construction industry,

mining, etc. The FAO (1961) study of timber trends estimated 'wood used in

the round' annually in South Asia in 1953-55 was 2115 th cum(r), of which

housing construction accounted for 30.7%, non-residential construction 7.1%,

rural uses 42.6% (repair and fabrication of wooden ploughs taking the bulk),

mining 9.5%, communication 0.7%, and other uses, 9.5%. A growth rate of 1 to

1.5% per year in agricultural production was used to project demand:

overall, they estimated that wood used in the round would increase to 150%

of the 1953-55 base level by 1975.

This is a category for which we have little more than educated guesses, and

the FAO statistics are themselves based on assumed per cap production in

each country: for India the figure used was 0.0040 cum(r) per cap in 1972

(FAO, 1974), revised to 0.0057 cum(r) in FAO, 1986 (these are quite

comparable to FSI survey results quoted in Table 5). The trend, therefore,

simply follows that of estimated population. To extend the approach adopted

previously, however, results of regression on per cap GDP are given below;

the last regression equation is however the exponential equation of

aggregate consumption on time (year, from 1961 to 1990), analogous to the

regression for total population.

Regression equations of Other Industrial Roundwood consumption (cum(r) per

th cap) on GDP (Rs /cap, 1970 prices)

ln conscap = 1.03549 + 0.11152 ln gdp70cap (log-log; R² = 10.59%)

conscap = 1.62239 + 0.64554 ln gdp70cap (semi-log; R²= 10.20%)



(log-log-inverse; R²= 59.71%)

ln cons = -37.0614 + 0.0229023 year (exponential; R²= 97.80%)

As expected, coefficients of determination (R²) of GDP-based regressions are

quite low. It would not be justifiable to use these regressions. If we

simply multiply the constant per cap consumption of 0.0057 cum(r) by the

projected population (exponential growth), we get estimates of 4763 th

cum(r) in 1990, 5930 in 2000, and 10255 th cum(r) in 2025. If exponential

growth of aggregate consumption is taken (the last equation above), annual

growth rate would be around 2.29%: projected consumption would work out to

4985 th cum(r) in 1990 (against FAO estimate of 4862), 6267 in 2000, 11111

th cum(r) in 2025. This is the preferred basis for projecting consumption of

Other Industrial Roundwood that we will adopt.

28

For comparison, NCA (1976) has quite high projections: consumption of

7045-7390 th cum(r) in 1980 (FAO estimate 3925), 8165- 9055 in 1985 (FAO

estimate 4383), and 11645-13335 in 2000. Chandrakant et al. (1979) have

income-based projections of 4044 (1980), 4354 (1985) and 4547 (1990), and

time-based projections of 4037 (1980), 4990 (1985), and 5878 (1990).

6.6 Industrial Roundwood (aggregate)

Two types of series can be considered for (aggregate) consumption of

Industrial Roundwood. One is the FAO series, available for the period 1961

to 1990 (figures for prior years are rather confused). GDP-based regression

on the FAO series of total Industrial Roundwood gives the following

equations:

Regression equations of Industrial Roundwood consumption (cum(r)/th cap) on



conscap = -315.938 + 51.2727 ln gdp70cap (semi-log; R² = 84.47%)



(log-log-inverse; R²= 85.78%)

The log-log-inverse gives declining consumption in later years; among the

others, the double-log regression gives the highest projections; the

semi-log the lowest: 30241 th cum(r) in 1990 (against FAO estimate of

25254), 45093 in 2000, 78151 in 2015, 110170 th cum(r) in 2025.

The second series for observed consumption is got by totaling up roundwood

requirements (derived demand) for different product categories. We have

already used roundwood input coefficients 2.8, 3.5 and 3.25 cum(r) per MT of

Newsprint, Printing & Writing Paper, and Other Paper & Paperboard,

respectively, but multiplied the result by 0.4 to reflect our assumption

that wood pulp provides only 40% of the requirement (in terms of wood

equivalent). Dissolving Pulp is converted to wood equivalent at 5.5 cum(r)

per MT, and again only 40% of this is assumed to be met from wood. For

Plywood & Veneer Sheet, roundwood requirement is 2.3 cum(r) per cum(s); and

for Sawnwood & Sleepers, 1.8 cum(r) per cum(s). Other Industrial Roundwood

consumption is taken as such. The resulting estimates of derived roundwood

consumption (raw material requirement) are close to FAO estimates of

Industrial Roundwood consumption up to 1973, but diverge sharply thereafter.

For 1990, the figures are respectively 25254 and 44599 th cum(r).

The second set of projections of aggregate consumption is got analogously,

by totaling derived roundwood equivalents of the preferred GDP-based projec-

tions (usually semi-log) of individual products as discussed already.

Pulpwood, as before, will be assumed to be only 40% of total wood raw

material equivalent of Paper & Paperboard and Dissolving Pulp consumption;

Other Industrial Roundwood is projected as growing exponentially with time

(see above). The resulting projections of aggregate Industrial Roundwood

requirement are: 43755 th cum(r) in 1990, 68858 in 2000, 125622 in 2015,

181270 in 2025. These are substantially higher than those computed by the

semi-log regression on the FAO series, but a little lower than projections

on the double-log regression for 2015 onwards.

29

Even though we have chosen usually the low projections for the individual

products, derived roundwood requirements are nearer the highest GDP-based

projection on the FAO aggregate series. It appears that FAO yearbooks have

used lower conversion factors than their own recommended values to derive

roundwood consumption from final product consumption or production, at least

from 1974. The truth is that roundwood production figures are subject to

great uncertainty, especially in case of Sawlogs, which forms the great bulk

of all Industrial Roundwood. Consumption of Sawnwood & Sleepers is probably

more a guess than an estimate. Other Industrial Roundwood is the next

highest in consumption levels, estimates of which are equally arbitrary.

On the whole, then, we should take the estimates, and projections, as a

broad guide to the orders of magnitude, product-wise compositions, and

ranges, rather than as precise targets for policy or management decisions.

In summary, we can take the projections based on semi-log regression on (per

cap) GDP as a 'low' variant, and the projections got by totaling up derived

demand (requirement) of roundwood for each product category as a 'high'

variant. It may be noted that even our 'high' variant is linked to 'low'

GDP-based projections, usually based on the semi- log regression. The main

difference is that derived demand of roundwood raw material based on

standard conversion factors gives figures that are higher than the FAO

series for the aggregate roundwood categories (as discussed above).

On this basis, the 'low' projections of Industrial Roundwood demand would

be: 30241 th cum(r) in 1990 (FAO estimate 25254), 45093 in 2000, 78151 in

2015, and 110170 th cum(r) in 2025. 'High' variants would be 43755 (1990),

68857 (2000), 125622 (2015) and 181270 th cum(r) (2025). The annual growth

rate of projected consumption between 1990 and 2025 works out to 3.76%

('low') to 4.15% ('high' variant). The consumption in 2025 will be between

3.64 times the 1990 consumption ('low' projection) and 4.14 times ('high').

Raw material for sawnwood will grow in importance, unless a ban on using

wood in construction and packaging is implemented in practice and

cost-effective substitutes are found. Modern products like plywood and pulp

products, on the other hand, have more exacting quality requirements.

Shortage of suitable raw material has been one factor that has slowed their

growth and depressed utilization of installed capacity, especially in ply-

wood industry (but other factors are significant: shortage of power, labour

problems, teething troubles of new plants, a high cost economy which renders

domestic production non-competitive, administrative price and other

controls, depressed demand; see the critique by Gupta and Shah, op. cit.,

for an argument that the popular picture of supply-demand gap is a fiction,

at least in the case of Paper & Paperboard).

For comparison, NCA (1976) has total industrial roundwood demand at

25005-26895 th cum(r) in 1980 (FAO Yearbook estimate 19669), 30030-35180 in

1985 (FAO estimate 23960), 47180-64450 in 2000. NCA also quote projections

made by the Indicative Plan for Forestry in India for the period 1965-1985

(a part of the Indicative World Plan sponsored by FAO): 32000 th cum(r) in

1980, 50000 in 1985, which are high compared with FAO Yearbook estimates of

actual consumption. Chandrakant et al. (1979) have projections of

13987-14818 (1980), 16661-18179 (1985) and 19651-22316 (1990), which all

seem too low.

30

7. Supply of industrial wood

Supply can be equated to production as given in the FAO series. This may not

give us any independent estimate of supply schedules in the economic sense,

or of trends, as many roundwood categories are estimated on the basis of

conversion factors from wood products.

The other important aspect in talking about timber supply, is that standing

trees can be felled at any age, and it is difficult to estimate annual

growth (increment of trees) from the quantity felled. A high level of

arrivals of timber in the market may not denote a high level of annual

growth; instead, the stock of standing trees may be under liquidation, or

perhaps old growth is being 'mined'. Periods of glut may be followed by

periods of timber famine, when young trees are growing but mature trees are

not available. Conversely, if large plantings take place in response to a

temporary timber shortage (as signaled by, say, rising prices or shrinking

arrivals), there may well be a glut in the market when the trees mature

(e.g. fast-growing trees producing mainly pulpwood in Haryana). Timber being

difficult to transport over long distances, processing capacity within

economic distances may need to be built up to provide a market for the

product.

Imports form a minor part of domestic consumption of sawlogs (even though

imports of sawlogs and veneer logs have gone up to 1000 th cum(r) per annum

at the end of the last decade). If the FAO estimates of consumption are

realistic, it does not appear feasible to meet the projected increase in

consumption from imports. For specialized uses, however, like long-fibred

pulp or plylogs, imports are significant. Singh,A. (1992) reports that over

50% of the 1.2 million cum used by the plywood industry is imported, mainly

hardwood logs from tropical countries; he suggests that as deforestation

problems in these countries may reduce supply in future, we may have to

switch to softwood from northern Europe and North America. R.V.Singh,

formerly DG, ICFRE, however contends that imports are not a long-term

solution, and we must increase the productive capacity of our own forests

(Singh,R.V., 1992).

Production from the government forests accounts for only a part of the

estimated demand. 'Recorded' production of industrial wood in 1979-80 was as

follows: (Govt. of India, 1985, quoted in Singh, R.V. 1992):

Recorded production, 1979-80 million cum

Sawlogs, veneer logs, sleepers 6.13

Poles, posts, pulpwood, pitprops 2.43

Other industrial wood 4.94

Total 13.50

For comparison, FAO estimates of consumption are:

Year 1979 1980

Sawlogs & Veneer Logs 13.877 14.536

Pulpwood 1.208 1.208

Other Industrial Roundwood (OIR) 3.843 3.925

Total 18.828 19.669

31

Pulpwood supplies can be raised on short rotations. One successful example

is provided by Mysore Paper Mills in Karnataka, which requires around 120 th

MT of hardwood, and 140 th MT of bamboo to produce 80 th MT of newsprint and

30 th MT of printing and writing paper a year. Up to 1990-91, the entire

pulpwood requirements were obtained from plantations raised by Karnataka

Forest Develpment Corporation and from private sources. Around 30000

hectares of barren and degraded land were leased out from the government,

and plantations were raised by MPM from 1981. Around 16807 hectares were

raised in Phase I of the plantation programme (eucalyptus in the dry zone,

Acacia auriculiformis in the wet zone). In 1991-92, 91 th MT of eucalyptus

and Acacia auriculiformis were extracted from the MPM plantations, while 39

th MT were obtained from private plantings.

The productivity of the wet zone plantations was higher than anticipated

(around 68 MT per hectare against projection of 45 MT per ha), while the dry

zone plantations were not so successful (10.9 MT per ha compared with antic-

ipated yield of 21 MT per ha). A yield of 45 MT/ha at 7 years from wet zone

plantations works out to a mean annual productivity of 45/7= 6.43

MT/ha/year. At average volume-weight ratio of 1.38 cum per MT, this is equal

to 8.87, or say 8.0, cum/ha/year.

To increase annual pulpwood production by 1000 cum per year, we would then

need to have productive plantations of 250 ha (worked on a sustained yield

basis). As per our 'high' version, supply of pulpwood is to be raised from

2993 th cum(r) in 1990 (computed roundwood equivalent of products; FAO

estimate of pulpwood consumption itself being only 1208 th cum(r) in 1990),

to 5086 th cum(r) in 2000, and 12361 th cum(r) by 2025 (40% of roundwood

equivalents of consumption projected on semi-log relationships). Thus we

need to add a productive plantation area of 250*2,094= 523,500 th ha, or

52,350 ha per year for 10 years. From 2001 to 2025, we need to add another

1818500 ha, or 72,740 ha per year.

The total increase in productive pulpwood plantation will be 523.5+1818.5=

2342 th ha, or 2.342 million ha, over 35 years, which may not be an

impossible task. In fact farmers themselves have taken to tree cropping on a

large scale, as in Kolar district of Karnataka, so that the pulp industry is

no longer dependent on forest supplies.

The shortfall is going to be more serious in sawlogs and veneer logs, for

which growth in demand is going to be the largest. If 'recorded' production

accounts for less than 50% of the FAO- estimated consumption, and imports

are maintained at levels around 1 million cum(r), this means that 6 to 7

million cum(r) are coming from private sources (or perhaps recorded removals

are under-estimates of actuals to some extent). In the past, timber used to

come not only from regular forest workings, but from massive clearing of

prime forest for other uses. It will not be advisable to go back to those

questionable methods to increase sawlog and veneer log production,

especially as the remaining stores of such timber are in ecologically

fragile areas like the Andaman Islands and the Western Ghats. It may not be

advisable to work these forests for timber even under organised working

plans.

The government is trying a two-pronged approach to this problem. On the one

hand, use of wood for building, furniture, etc. is being discouraged, even

prohibited in the government sector. On the other hand, the forest policy

32

speaks of industry supporting the farm sector in raising their timber

requirements, as shown in practice by WIMCO.

The steep increase in timber prices has also prompted farmers in many areas

to plant species like teak on their vacant lands, road and farm verges, etc.

Many entrepreneurs have started companies to raise teak and other tree

species on scientific lines, and thousands of individuals have subscribed to

such schemes.

One question is what sort of productivity these plantations will achieve,

and what the quality (and hence the price) of the timber will be if cut at

the relatively tender age of 20 years as planned. According to the All-India

Yield Tables for teak (FRI, 1959) the mean annual increment (MAI) of

(standard stem) timber from the best site quality (SQ I) teak plantations

peaks at 7.14 cum per ha per year at 50 years (final crop of 94 trees,

237.90 cum, and accumulated yield of thinnings of 117.20 cum, totalling to

stem timber of 355.10 cum per ha at 50 years). A lower site quality, would

give lower MAI of timber. Thus, a SQ II hectare would give a maximum of 4.06

cum/ha/year at age 60 years; SQ III, 2.17 cum/ha/year at 80 years; and SQIV,

0.55 cum/ha/year at 80 years.

If we assume that good plant quality, irrigation and fertilisation will

boost the growth to equal SQ I, we will need, for every 1000 cum per year

production, a productive plantation base of 1000/7.14= 140 ha plantation. To

increase annual production from 32,256 th cum(r) in 1990 (computed roundwood

equivalent of sawnwood and plywood; FAO estimate of Sawlog+Veneer Log

consumption itself being only 19134 th cum(r) in 1990), to 57503 th cum(r)

in 2000, and 157798 th cum(r) by 2025 (roundwood equivalents of consumption

of sawnwood, plywood projected on semi-log relationships and matches on

exponential trend), we need to add a productive plantation area of

140*25247= 3,534,580 ha, or 353,458 ha per year for 10 years. From 2001 to

2025, we need to add another 14,041,300 ha, or 561,652 ha per year. The

total increase in productive sawlog and plylog plantation will thus be

3534.58+14041.30= 17575.88 th ha, or 17.58 million ha, over 35 years. The

catch in this is of course that we will have to wait another few decades

befor these plantations come to the maximum MAI of 7.14 cum/ha/year which we

have assumed.

These are rather formidable targets, considering our productive forest area

itself is of the order of 30 million ha. The situation can be mitigated only

by involving the farm and corporate sectors in raising tree crops on a large

scale. We also need to work out how best to grow a traditional plantation

species like teak, as well as other species like Acacia auriculiformis

(which gives timber of fairly good quality, albeit rather heavy compared to

teak), even Eucalyptus, on short rotations for timber. The plantation sector

(coffee, tea, rubber) can also be a significant producer of timber; with

timely treatment, rubberwood becomes applicable in many uses. In rural areas

even coconut and other palms may be able to provide a large proportion of

timber requirements with some treatment. We may also have to think in terms

of easing some of the restrictions and rules that make it difficult for the

average farmer to dispose of his forest produce at a good price.

An unanswered question, but one raised quite strongly by many writers,

concerns the role of public lands in producing industrial wood. The author

will not try to address this question, at the rump end of this paper; it

33

needs a fresh look all by itself. It has to be said, however, that all

industrial wood need not necessarily be going to support big, bad industries

or big, bad, rich city-dwellers. A large proportion of it is wood used in

the round, and sawn timber used in such basic necessities as housing, both

urban and rural.

In the experience of social forestry projects in many states, any product

that is marketable (like babul wood) finds its way to the market, and only

the lops and tops or litter may go to meet domestic needs. That is the way

Homo economicus can be expected to function, whether rich or poor. If there

is degraded land capable of producing timber, and if this can be worked as

an economically viable enterprise, it is possible that village communities

will be willing to undertake it jointly with the corporate sector. The owner

of the land and the entrepreneur should both be able to get a fair return

for their investment of capital and other resources. If land is left under

low-valued uses, however, we cannot but expect it to be degraded further

under the inevitable working out of the 'tragedy of the commons'. The

technical question will be how to grow a combination of useful products,

including grasses for fodder, plaiting, thatching, etc. and other non-timber

products, along with the timber.

34

References

Buongiorno,J. (1977). Long-term forecasting of major forest products

consumption in developed and developing economies. Forest Science

23:pp.13-25.

Buongiorno,J. and G.L.Grosenick (1977). Impact of world economic and

demographic growth on forest products consumption and wood requirements.

Can. J. Forest Res. 7:pp.392-399.

Chandrakant,M.G., J.V.Venkataram, K.N.Ranganatha Sastry, R.Ramanna,

S.Bisaliah and K.S.Arun Kumar (1979). Consumption of forest products in

India - a quantitative analysis. Ind. J. Agr. Economics 34:3, pp.51-60.

FAO (1958). World Forest Products Statistics. A 10-Year Summary 1946-1955.

Rome.

FAO (1960). World Demand for Paper to 1975. FAO World Consultation on Pulp

and Paper Demand, Supply and Trade. 14-19 September, 1959. Rome.

FAO (1961). Timber trends and Prospects in the Asia-Pacific region.

(FAO/ECAFE) Geneva.

FAO (1962). Yearbook of Forest Products Statistics, 1962. Rome.

FAO (1966). Yearbook of Forest Products Statistics, 1966. Rome.

FAO (1971) Agricultural Commodity Projections, 1970-1980. Vol.II.General

Methodology and Statistical Appendix. Rome.

FAO (1974). Yearbook of Forest Products 1972, Review 1961-1972. Rome.

FAO (1986). Yearbook of Forest Products 1984, Review 1973-1984. Rome.

FAO (1992). Yearbook of Forest Products 1990, 1979-1990. Rome.

FRI (1959). Yield and Stand tables for Plantation Teak (Tectona grandis,

Linn. f.). Indian Forest Records (New Series), Silviculture. Vol.9, No.4.

silviulture Branch, Forest Research Institute, Dehradun, India. Manager of

Publications,. Delhi.

FSI (1987). Report on Wood Consumption Study in Chickamagalur District

(Karnataka). Forest Survey of India, Southern Zone, Bangalore.

FSI (1988). Report on Wood Consumption Study in Hasan District (Karnataka).

Forest Survey of India, Southern Zone, Bangalore.

FSI (1989). Report on Wood Consumption Study in Shimoga District


FSI (1989). Report on Wood Consumption Study in Bangalore District


FSI (1989). Report on Wood Consumption Study in Bellary District


35

FSI (1994). Report on Wood Consumption Study in Mysore District (Karnataka).

Forest Survey of India, Southern Zone, Bangalore.

Govt. of India 1982. Statistical Abstract of India, 1982.

Govt. of India. 1985. India Country Report. Min of Environment & Forests.

New Delhi.

Gregory, G.Robinson 1966. Estimating wood consumption with particular

reference to the effects of income and wood availability. Forest Science

12:pp. 104-117.

Gupta, Tirath and Nitin Shah (1987). Paper and Paperboards in India. Demand

Forecasts and Policy Implications. Oxford & IBH Publishing Co. Pvt. Ltd. C

Indian Institute of management, Ahmedabad. New Delhi.

Lele, Uma, Kinsuk Mitra and O.N.Kaul (1994). Environment, Development and

Poverty: A Report of the International Workshop on India's Forest

Management and Ecological Revival. CIFOR Occasional Paper No.3, Sept 1994.

(Summary of papers and discussions of the International Workshop, 10-12 Feb

1994, New Delhi, organised by Center for International Forestry Research

(CIFOR), Bogor, Indonesia, supported by Ford Foundation, Swedish

International Development Authority, and International Development Research

Centre).

Laurie,M.V. and Bakshi Sant Ram (1940). Yield and Stand tables for Teak

(Tectona grandis, Linn. F.) Plantations in India and Burma. For. Records

(NS) Silviculture, Vol.IV-A, No.1. Manager of Publications, Government of

India Press, New Delhi.

Madas,A. (1974). World Consumption of Wood. Trends and Prognosis. Akadémiai

Kiadö, Budapest.

McKillop,W.L.M. (1967). Supply and demand for forest products - an

econometric study. Hilgardia (J. California Agricultural Experiment Station)

38(1): March 1967.

Singh, Ashbindu. Trends in pulp and timber import. In Anil Agarwal (1992)

(Ed.). The Price of Forests. Proceedings of a Seminar on the Economics of

the Sustainable Use of Forest Resources. Centre for Science and Environment.

New Delhi.

Singh,R.V. Timber demand in India: prospects for future supply and

substitution. In Anil Agarwal (1992) (Ed.). The Price of Forests.

Proceedings of a Seminar on the Economics of the Sustainable Use of Forest

Resources. Centre for Science and Environment. New Delhi.

Singhania, Harishankar (1990). Paper Industry. Raw Material Scenario

(1990-2015). June, 1990.

UNO (1985). World Population Prospects. Estimates and Projections as

Assessed in 1982. Department of International Economic and Social Affairs.

Population Studies, No.86. New York.

37

Appendix 1. Classification of industrial wood and wood products

Wood is produced and used in many forms. The following classification has

been followed by the Food and Agriculture Organization (FAO) in its

Yearbooks of Forest Products (Statistics). Slight differences exist between

definitions of commodities in production and in trade, the latter following

the Standard International Trade Classification (SITC). The descriptions are

summarized below (for full definitions, FAO, 1992 may be consulted). The

name applied in production is given first, followed by the SITC Rev. 2 code

number and name applied in trade (the prefix EX indicating that not all

commodities listed under the code number are included). Total production of

primary products is reported, even though a portion may immediately be

consumed in the production of another commodity (e.g., wood pulp, which may

be immediately converted into paper); except in the case of veneer produc-

tion, which excludes veneer sheets going into plywood production within the

country.

Commodity names and composition of aggregates

(C): coniferous; (NC): non-coniferous

ROUNDWOOD

Units: solid volume of roundwood (or roundwood equivalent) without bark.

ROUNDWOOD (C), (NC)

245/246/247 ROUNDWOOD

Wood in the rough, as felled; with or without bark; may be treated (e.g.

telegraph poles), roughly shaped or pointed. Comprises removals from trees

within or outside forest. Commodities included are Sawlogs and Veneer Logs,

Pulpwood, Other Industrial Roundwood (including Pitprops) and Fuelwood.

Statistics include recorded volumes, as well as estimated unrecorded

volumes; in the trade statistics, roundwood from removals as well as the

estimated roundwood equivalent of Chips and Particles, Wood Residues and

Charcoal.

FUELWOOD+CHARCOAL

245 FUELWOOD+CHARCOAL

Commodities included are Fuelwood (C and NC); the trade statistics include

the roundwood equivalent of Charcoal, at 6 cum (solid) to a MT.

FUELWOOD (C), (NC)

245.01 FUELWOOD

245.02 CHARCOAL

Wood in the rough (from trunks, branches) to be used as fuel. Figures for

trade in Charcoal given in weight.

INDUSTRIAL ROUNDWOOD (C), (NC)

246/247 INDUSTRIAL ROUNDWOOD

Commodities included are Sawlogs and Veneer Logs, Pulpwood, Other Industrial

Roundwood; in trade, includes Chips and Particles and Wood Residues.

SAWLOGS+VENEER LOGS

247 SAWLOGS+VENEER LOGS

Sawlogs and Veneer Logs, logs for sleepers, C and NC. Includes logs whether

or not roughly squared, to be sawn (or chipped) lengthwise for the

manufacture of sawnwood or railway sleepers; logs for production of veneer,

38

by peeling or slicing; match billets; special growths (burrs, roots, etc.)

for veneers.

SAWLOGS+VENEER LOGS (C), (NC)

247.1 SAWLOGS+VENEER LOGS (C)

247.2 SAWLOGS+VENEER LOGS (NC)

PITPROPS

Included with Other Industrial Roundwood.

PULPWOOD+PARTICLES

246 PULPWOOD+PARTICLES

Pulpwood, Chips, Particles and Wood Residues. In production, commodities

included are Pulpwood, C and NC. In trade, includes, in addition, Chips or

Particles and Wood Residues.

PULPWOOD (C), (NC)

246.01 PULPWOOD

Wood in the rough other than logs. For pulp, particle board or fibreboard;

barked or unbarked; may be in the form of roundwood or splitwood. In

production, it may include the equivalent of wood chips made directly from

roundwood.

246.02 CHIPS+PARTICLES

Wood chips and particles. Wood that has been deliberately reduced to small

pieces from wood in the rough or from industrial residues, suitable for

pulping, particle board and fibreboard production, for fuelwood and for

other purposes.

246.03 WOOD RESIDUES

Miscellaneous wood residues. Wood residues that have not been reduced to

small pieces: consist mainly of industrial residues, like sawmill rejects,

slabs, edgings and trimmings, veneer log cores, veneer rejects, sawdust,

bark (excluding briquettes), residues from carpentry and joinery, etc.

OTHER INDUSTRIAL ROUNDWOOD (C), (NC)

247.9 OTHER INDUSTRIAL ROUNDWOOD

Roundwood used for tanning, distillation, match blocks, gazogenes, poles,

piling, posts, pitprops, etc.

SAWNWOOD

Units: solid volume.

SAWNWOOD+SLEEPERS (C), (NC)

248 SAWNWOOD+SLEEPERS

Sawnwood and sleepers, C and NC.

SAWNWOOD (C), (NC)

248.1 SAWNWOOD (C)

248.2 SAWNWOOD (NC)

Sawnwood, unplaned, planed, grooved, tongued, etc. sawn lengthwise, or

produced by a profile-chipping process (e.g. planks, beams, joists, boards,

rafters, scantlings, laths, boxboards, 'lumber', etc.) and planed wood,

which may also be jointed, etc. Wood flooring is excluded. With few

39

exceptions, sawnwood exceeds 5 mm in thickness.

SLEEPERS

Separate table not included in later Yearbooks.

WOOD-BASED PANELS

Units: solid volume.

WOOD-BASED PANELS

634/641 WOOD-BASED PANELS

Includes Veneer Sheets, Plywood, Particle board and Fibreboard compressed or

non-compressed.

VENEER SHEETS

634.1 VENEER SHEETS

Thin sheets of uniform thickness, peeled, sliced or sawn, for use in

plywood, laminated construction, furniture, veneer containers, etc. In

production, excludes veneer sheets used for plywood production within the

country.

PLYWOOD

EX634 PLYWOOD

Plywood, veneer plywood, core plywood, including veneered wood, blockboard,

laminboard and battenboard; cellular board, composite plywood.

PARTICLE BOARD

634.32 PARTICLE BOARD

Made by bonding together small pieces of wood, etc. by an organic binder

with a combination of heat, pressure, humidity, etc. Flaxboard included;

wood wool and other particle boards, with inorganic binders, excluded.

FIBREBOARD

641.6 FIBREBOARD

Includes compressed and non-compressed fibreboard.

FIBREBOARD, COMPRESSED

641.6 FIBREBOARD, COMPRESSED

641.62 FIBREBOARD, NON-COMPRESSED

PULP

Units: weight (air-dry = 10% moisture)

WOOD PULP

EX251 WOOD PULP

Mechanical, semi-chemical, chemical and dissolving wood pulp (the last being

chemical pulp, bleached, from C or NC wood, of special quality, with a very

high alpha-cellulose content usually over 90%, used mainly for manufacture

of synthetic fibres, cellulosic plastic materials, lacquers and explosives).

OTHER FIBRE PULP

251.92 OTHER FIBRE PULP

Pulp of fibrous vegetable material other than wood: includes straw, bamboo,

bagasse, esparto, other reeds and grasses, cotton linters, flax, hemp, rags,

other textile wastes. Used for manufacture of paper, paperboard and

fibreboard.

40

PAPER AND PAPERBOARD

Units: weight

PAPER+PAPERBOARD

EX641 PAPER AND PAPERBOARD

Aggregate of Newsprint, Printing and Writing Paper, Other Paper and

Paperboard.

NEWSPRINT

641.1 NEWSPRINT

Uncoated paper, containing at least 60% mechanical wood pulp (percentage of

fibrous content), usually weighing 40 to 60 g/m2, used mainly for printing

of newspapers.

EX641 PAPER+BOARD-NEWSPRINT

Paper and paperboard other than Newsprint. Includes Other Printing and

Writing Paper and Other Paper and Paperboard.

PRINTING+WRITING PAPER

641.2 PRINTING+WRITING PAPER

Other printing and writing paper, except Newsprint, including paper for

books and magazines, wallpaper base stock, box lining and covering,

calculator paper, duplicating paper, banknote, etc.

OTHER PAPER+PAPERBOARD

EX641 OTHER PAPER+PAPERBOARD

Includes construction paper and paperboard, household and sanitary paper,

special thin paper, wrapping and packaging paper and paperboard, and other

paper and paperboard not elsewhere specified (NES).

41

Appendix 2. Conversion factors

The FAO Yearbooks are a compilation of information supplied by governments,

as well as estimates made by FAO and data obtained from additional sources.

Figures for previous years are often revised and presented as series in

subsequent years.

Trade figures are usually reliable. Production data of roundwood may be

fairly reliable in respect of government forests (the main problem here

being that timber felled in the forest may take many months to come to the

sale depots and get included in the forest department's accounts or

reports). Production of roundwood outside the forest is often difficult to

estimate, and educated guesses may have to be made. Sometimes, roundwood

production has to be estimated by inference from the reported output of

processed products like pulp, paper and paperboard, panel products, etc. in

the organized sector.

The following standard conversion factors have been recommended by FAO to

convert different units of measurement, as well as to estimate roundwood

equivalent of processed products.

Some conversion factors

Cubic Cubic

metres feet

Panel products

1000 square metre (1 millimetre thickness) 1 35.315

1000 square feet (1/8 inch thickness) 0.295 10.417

Pulpwood

1 cord 2.55 90

Fuelwood

1000 stacked cubic feet 18.41 650

1 cord 2.12 74.9

Weight/volume Kg/CUM CUM/MT

Fuelwood C 625 1.60

NC 750 1.33

General 725 1.38

Charcoal G 167

Sawlogs+Veneer Logs Tropical NC 730 1.37

Other C 700 1.43

Other NC 800 1.25

Pitprops C 700 1.43

NC 800 1.25

G 725 1.38

Pulpwood C 650 1.54

NC 750 1.33

G 675 1.48

Other Industrial Roundwood C 700 1.43

NC 800 1.25

G 750 1.33

Sawnwood C 550 1.82

NC 700 1.43

Sleepers G 780 1.28

Veneer sheets G 750 1.33

42

Plywood G 650 1.54

Particle Board G 650 1.54

Fibreboard, compressed G 950 1.053

Fibreboard, non-compressed G 250 4

(Source: FAO YB of Forest Products, 1990, 1979-1990)

Standard conversion factors for roundwood input

Sawnwood (C) 1 cum(solid) = 1.8 cum(r) (India)

Sawnwood (C) 1 cum(solid) = 1.67 cum(r) (standard)

Sawnwood (NC) 1 cum(solid) = 2.2 cum(r) (India)

Sawnwood (NC) 1 cum(solid) = 1.82 cum(r) (standard)

Sleepers 1 cum(solid) = 2.2 cum(r) (India)

Sleepers 1 cum(solid) = 1.82 cum(r) (standard)

Veneer sheet: 1 cum(solid) = 1.9 cum(r)

Plywood: 1 cum(solid) = 2.5 cum(r) (India)

Plywood: 1 cum(solid) = 2.3 cum(r) (standard)

Wood Pulp

Mechanical 1 MT = 2.5 cum(r)

Semi-chemical 1 MT = 3.3 cum(r)

Chemical 1 MT = 5.0 cum(r) (India)

Chemical 1 MT = 4.9 cum(r) (standard)

Sulphite 1 MT = 4.9 cum(r)

Sulphate 1 MT = 4.8 cum(r)

Dissolving 1 MT = 5.5 cum(r)

(Source: FAO YB of Forest Products, 1972, Review 1961-1972)

Charcoal 1 MT = 6.0 cum(r)

Particle Board 1 MT = 2.0 cum(r)

Fibreboard 1 MT = 2.0 cum(r)

Newsprint 1 MT = 2.8 cum(r)

Printing, writ. paper 1 MT = 3.5 cum(r)

Other paper 1 MT = 3.25 cum(r)

Paperboard 1 MT = 1.6 cum(r)

(Source: FAO YB of FP Statistics, 1966)

Wood Pulp

Dissolving 1 MT = 6.9 cum(r)

Newsprint 1 MT = 3.0 cum(r)

Printing, writ. paper 1 MT = 3.65 cum(r)

Packaging, Wrapping

& Other Paper 1 MT = 3.65 cum(r)

Paperboard 1 MT = 1.8 cum(r)

(Source: FAO, 1961)

Appendix 3. Abbreviations

Economic indicators:

GDP Gross Domestic Product

NI National Income

Names of variables in regression equations:

gdp70cap GDP per cap, Rs. 1970 prices

pop Population, millions (mid-year)

43

conscap Consumption per capita (usually per thousand capita)

year Year, e.g. 1985

Units of measure:

Th thousand

MT metric tonne (1000 kilograms)

Kg kilogram

cum(r)cubic metre (round wood)

cum(s)cubic metre (solid wood)

Rs Rupees (Indian)

Functions and operators:

log X logarithm to base 10 of X

ln X logarithm to base e of X (natural logarithm of X)

exp(X)exponential of X (e raised to power X)

R² Co-efficient of determination (proportion of variance explained by the

regression)

Df Degrees of freedom (number of observations minus number of co-efficients

determined)

Acronyms:

FSI Forest Survey of India

FRI Forest Research Institute (Dehradun, India)

NCA National Commission on Agriculture (India)

UNO United Nations Organisation

industrial wood in india: key determinants of demand and supply

Documents