AD ALTA
JOURNAL OF INTERDISCIPLINARY RESEARCH
projects, its size depends on adopted obligations of individual
states, the condition of the government budget, intensity of lobby
groups’ activity and the voters’ response to the rising market
prices resulting from subsidies. The issue of the internal yield is
therefore more or less a question of political decisions.
In terms of subsidised renewable energy projects, the unforeseen
legislation changes may result in a reduction of subsidy of the
purchase price of electricity produced (feed-in tariff – FIT).
Under a FIT, the renewable electricity producers are paid a cost-
based purchase price for the renewable electricity they supply to
the grid, the access of which is guaranteed by long-term
contracts (Klein et al., 2008). These purchase prices are one of
the building blocks for cash flow calculations within budgeting
and as such create the core of the NPV.
Risk modelling for subsidised production presents complexity
due to the strong interaction between the trading of the products,
the supply and demand imbalances and state of the economy and
political stability. In this paper, we contemplate the market risk
of subsidized energy product
ion using a variable indicator σ
expressing a ratio of the realized (actual) purchase price (P) for
energy produced and the budgeted price given by the FIT (P
E
).
The value of this ratio is a direct consequence of investor
confidence in the stability of the legislative framework, the grade
of which is measured by diverse rating agencies. To capture the
risk of a legislative change, we utilize the Euromoney Country
Risk rating. It includes the investment risk of a country, risk of
losing direct investment and risk to global business relations;
factors that are covered in ranking countries by risk are political
risk, economic performance/projections, structural assessment,
debt indicators, credit ratings, access to bank finance, access to
capital markets, etc. (Euromoney, 2018).
2.1 Approach to the external risk measurement of subsidized
projects
Let us consider the risk of legislative change of selected EU
countries according to data released by the rating agency
Euromoney Country Risk summarized in Tab. 1 (the original
data were divided by a hundred and converted into opposite
numbers in order to express the country non-risk perception –
further on marked as Euromoney Index). All the selected
countries in Tab. 1 are the EU members that have committed to
fulfill the EU agreement set of the Kyoto protocol.
Let us denote ρ as a parameter of certainty degree represented by
the value of Euromoney Index
, where ρ
∈ 〈0,1〉; the higher the
parameter ρ the lower the risk of undesirable changes relating to
the legislative change that could threaten the performance of
subsidized projects. The Index value ρ signals the level of
confidence in the expected profitability in dependence of the
country the projects are implemented.
Table 1: The assessment of the selected EU countries in terms of
the quality of legislative environment measured by Euromoney
Index ρ
∈ 〈0,1〉
Country
Euromoney Index, ρ ∈ 〈0,1〉
Croatia
0.517
Czech Republic
0.577
Estonia
0.7
Hungary
0.587
Latvia
0.6
Lithuania
0.61
Poland
0.64
Slovak Republic
0.598
Slovenia
0.65
Note: 0 stands for the worst assessment, 1 is the best assessment.
Source: Euromoney (2018) input data adjusted.
The legislative changes can, for instance, negatively influence
the situation in the renewable energy market, as I. they
contribute to uncertainty regarding the future development of
profits from the renewable energy projects and II. subsidy
recipients (especially in agriculture) become fully dependent on
the government support, the cut of which would result in putting
the project out of business in many cases (Maroušek, 2013).
In the next, we focus on the point I. within the evaluation of a
subsidized bioenergy project based on the net present value
(NPV). Within the calculation, we distinguish the level of risk of
a legislative change described as certainty degree ρ and with it
connected the market risk σ expressed by the ratio of actual
purchase price of energy produced and the expected (budgeted)
price.
3 Results – case study: the biofuel plant project (BSP) cash
flow budgeting reflecting the market risk
To analyze the impact of a legislative change to the profitability
of BSP we draw from the data of Tab. 2, in which the symbols a,
b, c, d represent the values
of budgeted revenues. Symbol σ is
the variable parameter expressing the market risk for which it
applies σ = P / P
E
∈
, σ (0,1〉; symbols P and P
E
stand for the
actual purchase price for the energy produced and the expected
(budgeted) price, respectively. In the case of σ = 1, the project
budgeted revenues are estimated as follows: a = 1800, b = 1900,
c = 2500, d = 3800; all the values are stated in thousands of
euros (further marked as kEUR).
Table 2: The average yearly cash flows (CF) generated by an
average BSP reflecting the market risk σ in kEUR; σ
∈ (0,1〉
Period
(years)
0
1
2
3
4
5
6-21
22-31
Year
2013
2014
2015
2016
2017
2018
2019-
34
2035-
44
1
Cap.
subsidy
1000
2
Cap.
investment
3000
500
3
Revenues
a· σ
b· σ
c· σ
d· σ
d· σ
d· σ
4
Operating
costs
1400
1400
2000
2400
2400
2400
5
Depreciation
in total
80
150
170
180
180
30
6
EBT (3–4–5)
a· σ
−1480
b· σ
−1550
c·
σ
−2170
d· σ
−2580
d· σ
−2580
d· σ
−2430
7
Tax 24 % of
EBT
0.24·a·
σ −350
0.24·c·
σ −370
0.24·c·
σ −520
0.24·d·
σ −620
0,24·d·
σ −620
0,24·d·
σ −580
8
EAT (6 – 7)
0.76·a·
σ−1130
0.76·b·
σ
−1180
0.76·c·
σ−1650
0.76·d·
σ
−1960
0,76·d·
σ
−1960
0,76·d·
σ
−1850
9
Operating
CF (8+5)
0.76·a·
σ−1050
0.76·b·
σ −970
0.76·c·
σ−1480
0,76·d·
σ
−1780
0,76·d·
σ
−1780
0,76·d·
σ
−1820
10
CF of cap.
bud. (1-2+9)
−2000 −500 0.76·a·
σ−1050
0.76·b·
σ −970
0.76·c·
σ−1480
0,76·d·
σ
−1780
0,76·d·
σ
−1780
0,76·d·
σ
−1820
Note: 0 stands for the worst result, 1 is the best result.
Source: Authors.
The data of Tab. 2 correspond to the CFs of an average biofuel
plant built and put into operation in countries listed in Tab. 1 for
the installed electrical power 1000 kW (
Menind and Olt, 2009;
Holm-Nielsen
et
al., 2009)
. The average BSP is financed from
the firm resources and through government subsidy, here in the
total amount of 1000 kEUR. The budgeted revenues and
operating costs result from the expert assessment, which is based
on similar projects with regard to the unique characteristics of
the particular project. The purchase tariffs and operating costs
are not adjusted to inflation. Therefore, Tab. 2 corresponds to the
situation with zero inflation or both the cash revenues and
operating costs change in exactly the same proportion as general
price level.
Annual cash flows generated by the project are recorded in the
last row of Tab. 2. The CFs steady state is expected from the 5
th
year; between the years 6-31 the CF prognosis creates two time-
shifted annuities: the first, the 16-year annuity, starts in the 6
th
period, the second, the 10-year annuity, starts in the 22
nd
period.
This allows us to simplify the cash flow structure as indicated in
Fig. 1.
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