The Tasmania Forest Case Analysis in
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Executive Summary:
Changes in price of Lumber can affect the supply of timber.
If the price of lumber increases substantially there will be an increase in the
quantity of timber. The Tasmanian Forestry Industry has its main goals. If there
is a change in demand then there will be a change in supply.
Government legislation also raises the costs of production
of timber, the abolition of legal barriers to setting up business in the
industry, or tax changes are some examples of how government can change the
level of supply in an industry.
If Tasmanian Forestry Industry expects the future prices to
be much higher, they must restrict supplies and stockpile goods; if they expect
disruptions to their future production because of the occurrence of the weather
occurrence they may stockpile raw materials, paying for them, thus increasing
their costs and reducing supplies.
The weather conditions affect the prices of the timber. The
weather plays a crucial role in determining supply, bad weather reducing
supply, good weather producing bumper yields.
The Tasmanian Forest Industry priority is to put an end to
the reserve making process which would have resulted in so much potential
production forest being lost to the industry permanently. It needs to seek
certification that will achieve the future changes of activities in the
forestry development.
Part 1- Introduction:
Australia undertook an independent strategic review of
Forestry Tasmania to examine and report on the future structures, governance and
business models under the Forestry Tasmania could best operate in the context
of challenging market conditions and major industry changes.
There was a recommendation of the
separation of the commercial and non-commercial in terms of function in Tasmanian
Forestry that highlight the financial issues. The Australian government
has signed a memorandum of agreement to
provide a long term sustainable management
and development of both public and privately owned of Tasmanian forest
that applies a 20 year period and a review of every five years, www.
Stategrowth-tas-gov-au/forestry/transition, (2011).
Tasmania was the first state in Australia to be fully
covered by the Tasmania Regional Forest agreement (RFA).
The Tasmanian Government recognizes that there are
limitations with datasets describing the extent of Tasmania’s native forest
vegetation and so continues to invest programs to improve the precision of this
information for the future. These programs include the use of satellite imagery
to detect changes in vegetation extent.
The conduct and behavior of
Tasmanian Forestry Industry will be determined by their objectives and the
actual market conditions. A need to produce a quality and quantity of resources
should be maintained. Capital goods, equipment like modern technological
innovations and investments are being used during the production process in
relations with harvesting and replanting of trees, www.stategrowth-tas-gov-au/forestry/transition (2011)
Tasmanian Forest Industry deals with
the government in developing and producing these natural resources. The central
government and its constituent organizations take
responsibility,www.helpteaching.com/questions/123837/the-key-features-of-a-command-economy-is-that-control-government
(2011)
·
To allocate resources
·
Targets of production
for the industry on annual level
·
How wages and income are
fairly distributed
·
Long term planning to
contribute in the growth of the economy
From the practical standpoint, some of these decisions have
to be decentralized, either geographically or by sector, to other government
organizations. In certain cases these bodies have control over the workings
limited market and climatic changes mechanism.
Part 2- Government
Policy
Tariff
Tariff tax is a tax on expenditure. The two major indirect
taxes are VAT and Excise Tax.
Tariff are compose of VAT
or AD VALOREM tax. The tax levied increases in proportion to the value
of the tax base. In the case of VAT the tax base is the price of the good. Most
goods carry a 17.5 percent VAT charge. Excise tax or tariff on the other hand
is an example of a specific tax or unit tax. The amount of tax levied does not change
with the value of goods but with the amount or volume of the goods purchased,
Padilla, J (2011).
Price theory can be used to analyze the impact of the
imposition of tariff tax on goods. Assume that a specific tax of $1 is imposed
upon timber. This has the effect of reducing the supply. Sellers of timber will
now want to charge extra per tons sold. In Figure 1, this will show the
vertical shift of $1 in the supply curve at every level of output. However, as
many timbers are produced, seller wants to charge $1 more tons of timber and
therefore there is a parallel shift upwards and to the left of the whole supply
curve from S1 to S2.
Using Figure 1, we can also show the change in total
expenditure before and after imposition of tariff tax as well as the amount of
tax revenue gained by the government. The government will receive total tax
revenue of $1 x 40 $198 million ($3.30 x 60 producers will fall from $198
million ($3.30 x 60 million) to $120 million ($3 x 40 million)
The above analysis can be extended to deal with tariff
taxes. The imposition of tariff taxes will lead to upward shift in the supply
curve, however, the higher the price, the greater will be the amount of tax.
Hence the shift will as in Figure 2. Consumers will pay FG tax per unit whilst
the incidence of tax on producers per unit will be HG.
Figure 1
Figure 2
Two points need to be made. First the demand curves in
Figure 3 have been drawn as straight lines. These demand curves drawn show a
hypothetical (or imaginary) position. They are drawn straight purely for
convenience and do not imply that actual demand curves for timber are straight.
Second, the shift in the demand curves is drawn parallel as parallel shifts.
Again this is done for convenience and neatness but it is most unlikely that a
rise and fall in income for an actual product would produce a precisely
parallel shift in the demand curve, Chan, M (2009).
Figure 3
2. Subsidy
A subsidy on good will leads to an increase in supply,
shifting the supply curve downwards and to the right. This is shown in Figure
4. It should be noted that a subsidy of AC will not lead to fall in price of
AC. A part of the subsidy, AB, will be appropriated by producers because of the
higher unit cost of production of higher levels of output, (shown by the upward
sloping supply curve). Prices to consumers will only fall by BC.
Figure 4
Taxes, Subsidy and elasticity
The extent to which the tax incidence falls on consumers
rather than producers depends upon the elasticity of demand and supply. Figure 5
shows a situation where either the supply curve is perfectly elastic or the
demand curve is perfectly inelastic. In both cases, the vertical shift in the
supply curve, which shows the value of the tax per unit, is identical to the
final price rise. Therefore all the tax will be paid by consumers, Padilla, J
(2011).
Figure 5
Figure 5 on the other hand, shows two cases where the
incidence of tax falls totally on the producer. Producers will find it
impossible to shift any of the tax onto consumers if the demand curve is
perfectly elastic. Consumers are not prepared to buy at any higher price than
the existing price. If the supply tax curve is perfectly inelastic, then the
supply curve after imposition of the tax will be the same as the one before.
Equilibrium price will therefore remain the same and producers will have to
bear the full burden of the tax.
Generalizing from these extreme situations, we can conclude
that the more elastic the demand curve or the more inelastic the supply curve,
the greater will be the incidence of tax on producers and the less will be the
incidence of tax on consumers. So far as the government is concerned, the
taxation revenue will be greater, all other things being equal, the more
inelastic the demand for the timber taxed. For instance, if demand were
perfectly elastic, the imposition of an indirect tax would lead to quantity
demanded falling to zero and tax revenue being zero. At the opposite extreme,
if demand were perfectly inelastic, consumers would buy the same quantity after
the imposition of tax as before. Hence revenue will be equal to the tax per
unit times the quantity demanded before imposition. If the price elasticity of
demand lies between these two extremes, its imposition of a tax will lead to a
fall in quantity demanded. The higher the elasticity, the larger will be the
fall in quantity demanded and hence the lower will be the tax revenue received
by the government, Chan, M (2009).
The same analysis can be applied to subsidies. In general,
subsidies tend to be given where the policy objectives is to reduce the price
of goods. The largest fall in price will occur when either demand is highly
inelastic or supply is highly elastic. If demand is very elastic or supply is
very inelastic, there will be very little, if any change, in price following
the granting of subsidy. This is because producers will not pass on the subsidy
to consumers. This will absorb the subsidy, which will allow them to increase
their profits.
Part 3- Market Trends
Trend is a general long term movement in the time series
value of the variable over a long period of time. The variable (Y) is a factor
that we are interested in evaluating for the future. These variables are
observed over a long period of time and any changes related to time are noted and
calculated and a trend of these changes is established. There are many types of
trend; the series may be increasing at a slow rate or a fast rate or these
maybe decreasing at the various rates. Some remain relatively constant and some
reverse their trend from growth to decline to growth over a period of time.
Figure 6 (PLOT) c/o Abbas
Seasonal variation
Seasonal variation is a pattern that repeats over time
period longer than one year. These variations are generally unpredictable in
relation to the time of occurrence, duration as well as amplitude. The measure
we use to identify cyclical variation as the percentage of trend and the
procedure used is known as residual trend. There are four components of time
series. Since the time period considered for seasonal variation is less than
one year, it can be excluded from the study , because when we look at time
series consisting of annual data spread over many years, then only the secular trend, cyclical variation
and irregular variation are considered, Padilla,J (2010).
Figure 7- PLOT
Forecasting
Accurate forecasting is an essential element of planning of
any organization or policy.When a projection of the pattern of future economic
activity is known and the level of future business activity is understood, the
desirability of an alternative course of action and the selection of optimum
alternative can be examined and forecast. The quality of such forecasts is
strongly related to the relevant information that can be extracted from past
data. Hence, the time series analysis method helps in making accurate
predictions and also in situations where the future is expected to be similar
to or at least predictive from the past, Chan, M (2009).
Part 4- Structural
Modeling
Regression Analysis is an extremely useful toll especially
in problems of business and industry. While using regression analysis for
making predictions, the following assumptions are made:
1.
There is an actual relationship between the
dependent and independent variables
2.
The values of the dependent variable are random
but the values of the independent variable are fixed quantities without error
and are chosen by the experimentor.
3.
There is a clear indication of direction of the
relationship. This means that dependent variable is a function of independent
variable.
4.
The conditions are the same when the regression
model is being used. In other words, it simply means that the relationship has
not changed since the regression equation was computed.
5.
The analysis is to be used to predict values
with the range for which it is valid.
In using linear regression model, a single variation is used
to predict another variable on the assumption of linear relationship between
the given variables. The variable to be predicted is called the dependent
variable and the variable on which the prediction is based is called
independent variable, Chan, M(2009).
Forecasting
Forecasting models have either an implicit or error
structure, where error is defined as the difference between the model
prediction and the true value, Further, serious data snooping methods in the
domain of statistics requires to be applied to data supplied to a forecasting
model. Also, diagnostic checking, as defined within the field of statistics, is
required for any model which uses data.
The application of any technique for forecasting requires
the use of a performance measure to evaluate its quality. Mean Absolute
Deviation (MAD) and variance are the best measures. However, MAD does not lend
itself to further use variance is preferable as variances of independent
(uncorrelated) errors are additive. MAD is not additive Chan, Michael (2009).
Part 5 Future Industry Prospects
The Tasmanian government issued a policy for maintaining a
permanent native forest estate which states the utmost importance of
sustainable management of Tasmania’s native forest. It recognizes different
types of mechanisms that are ecologically sustain forest management. The policy
has primary elements in line with the sustainable forest management practice
under the Forest Practices Code to ensure that the right practice is correctly
followed an get the best sustainable return from the forestry operations. It
also develops a comprehensive, adequate, and representative forest service
reserve system to securely protect nature conservation values, www. Stategrowth-tas-gov-au-data.pdf-file/007188135/policy-for-maintaining-a-permanent-native-forest-estate
(2011)
The Tasmanian Government has had a formal policy in place
since 1996 to regulate the extent of clearing and conversion of the native
forest estate. This policy does not aim
to maintain a native forest estate exactly as it is because forest condition
will change from place to place and from time through regeneration after fire
or harvesting or through natural succession as forest age. It is about
reservation of native forests and how native forests are maintained as native
forest and managed for variety of reasons.
The forest community retention levels and the property
conversion limits need to be applied in a practical and meaningful way. For
this reason, the levels and the limits may be exceeded where the conversion of
native forest does not result in the loss of significant nature of conservation
values in an IBRA bio-region. The forest be considered to be representative of
that forest community and it is incapable of returning to an intact condition
by natural regeneration with the mitigation of existing threatening processes.
The forest in question is part of an approved property management plan.
Clearance of the forest in question would result in a more appropriate and
practical management boundary, provided that the annual property conversion
limit is not exceeded by more than 10 percent. Expert opinion indicates that the
threshold is being triggered as a result of inadequate mapping, inappropriate
community classification of the nature of fuzzy IBRA bioregional boundaries rather
because of depletion of a bio-regionally significant community, www.
Stategrowth-tas-gov-au-data.pdf-file/007188135/policy-for-maintaining-a-permanent-native-forest-estate
(2011)
Part 6- Conclusion
It has been long recognized that the market for timber are
the primary determinant of profitability. The principal reason for this is
Tasmanian Forestry Industry has to induce the economies of scale in managing
the forests. Deforestation without replanting of trees will diminished the
natural resources which results to depleted environment. Quarrying is the most
blatant signs of forest depletion. The lower costs are due partly to economies
of scale. In productions of timber, purchasing and administration pertaining to
Tasmanian Forestry Industry operations.
This is also partly due to experience effect, whereby the
cost of most timber decline by a fixed percentage as shown in the time series
analysis each time Tasmanian Forest Industry experience in harvesting and
selling them.
Of the two, the nature and sources of experience of
economies of scale are by far the best known, and it is therefore not our
intention to do anything more than draw the attention to its significance and
to emphasize that these economies of scale can provide a significant input to
the pricing decision.
The less well known experience effect, however, is of equal
and in some instances even greater, strategic significance. The concept is
based on the discovery that costs decline with cumulative production and that
this decline is measurable and predictable. The origins of the effect can be
traced to the idea of learning curve, which recognizes that the time needed to
perform a task decreases as workers become more familiar with it. In the 1960’s however, evidenced emerged to
suggest that this phenomenon was limited not just labor costs, but applied also
to all total value added costs including administration, sales, harvesting and
distribution, .
“That each time cumulative volume of timber doubled, total
value added costs fell by constant and predictable percentage. In addition, the
costs of purchased items usually fell as suppliers reduced prices as their
costs fell, due to experience effect. The relationship between costs and
experience was called the experience curve which is observed and studied by
Padilla, J (2010) to all forestry industry.
The experience effect has a variety of sources which are
identified by Padilla as:
1.
Greater labor efficiency
2.
Work specialization and methods improvement
3.
New production processes
4.
Obtaining better performance from existing
equipment
5.
Changes in resource mix
6.
Greater product standardization
7.
Forestry redesigns
Abelle and Hammond (1979, p113) point out that the results
of substantial concerted effort and pressure to lower cost during the
production of timber if left unmanaged , costs rise. Thus experience does not
cause reductions but rather provides an opportunity that alert the Tasmanian
Forestry Industry managements can exploit. Consequently strategies resulting
from market opportunity should explicitly address how cost reductions are to be
achieved.
The strategic implications of the experience curve are
potentially significant in the Tasmanian Forestry Industry, since by pursuing a
strategy to gain experience faster from replanting to harvesting, it lowers it
cost base and has greater scope for adopting an aggressive and offensive
pricing strategy and sound management of forest, Abelle and Hammond, (1979).
The main strategic message from the experience curve is that
if costs in real terms decrease predictably with cumulative output, then the
forest has a potential to achieve a lowest costs and higher profits.
Part 7- Recommendation
In order to determine whether or not a variable qualified as
a key success factor which would be required to measured), the following
question was asked: “Will continued failure of Tasmanian Forestry Industry
prevent attainment of management’s responsibility for advancement in this key
Australia’s Industry which is a leader in a strong, competitive economy, even
though results in all key result areas are good?
A range of key success factors emerged from this project:
·
Profitability
·
Market position
·
Product leadership
·
Productivity
·
Personnel development
·
Employee attitude
·
Public responsibility
·
Balance between short run and long run goals
While these might be generally applicable, it is their
precise definition within the context of Tasmanian Forestry Industry activities
that determines how critical they are. This highlights a fundamental aspect of
designing any control system; it must be highly situational, if it is
effective. In other words , it must be tailored to the specific characteristics
of the situation, which means the TFI objectives ,I operations, TFI managers
and TFI environment.
References:
Abelle, R and Hammond, C (1979),-
Strategic Management, Planning, Implementation and Control, pp113, Pearson.
Chan, Michael (2009) Statistics for MBA, 2nd
edition, pp.35,67,89,90, University of Hongkong Press (Prentice Hall)
Padilla, J (2010) Strategic
Management 1st edition, pp279, 279, Nanyang University Press,
Prentice Hall
www. Stategrowth-tas-gov-au/forestry/transition,;2011,
September
www.
Stategrowth-tas-gov-au-data.pdf-file/007188135/policy-for-maintaining-a-permanent-native-forest-estate
; 2011, September
www.helpteaching.com/questions/123837/the-key-features-of-a-command-economy-is-that-control-government
, 2011, September
Wilson, R. (2011) The Academy of
Management Journal , 10 Data Points: Information and Analytics for Work; Vol.
53. No.4 (August 2010) pp110-117
