Maximizing Owner’s wealth under uncertainty and volatility: A system dynamics
approach using evidence from Norwegian Oil Sector
This analysis focuses on maximizing firm value in presence of uncertainty and volatility in the
oil market considering investment, financing and dividend policies as decision tool under
different market conditions. Using system dynamics, we have developed a model for financial
and physical processes of a leading firm in oil sector to grasp the dynamics and test policies
in an effort to maximize the owner’s wealth. Assuming market growth condition, investment
policy seems to add most to the firm value. However, the combination of policies helps best to
maximize the firm value.
1, Introduction:
Maximization of owner’s wealth is the main and ultimate objective of a firm. Achievement of
this objective is challenging in a competitive world with complexities surrounding its
operations and the various options to decide on. This objective seems even more challenging
when it comes to energy sector where the investment decisions are generally huge and
irreversible whereas market prices are uncertain and volatile and of cyclical nature (Bloom et
al, 2001). This is very true especially in the context of Norwegian continental shelf where oil
is to be extracted from the seabed with relatively heavy irreversible investments. It is
contributing almost 21.5% of the Norway’s GDP, 29.5% to the state revenue, 30.7% of the
total investments are done in petroleum sector and 48.9% of the exports (Figures from 2014
from Norwegian Petroleum Directorate). Petroleum industry is a knowledge intensive
industry due to its complexity of operations. It took long years in Norway to reach a certain
level of knowledge in order to be able to explore and develop oil and gas reserves and reap
the benefits from production. Investment in oil industry is characterized by features that
represent investment models under uncertainty such as longer planning horizon,
irreversibility of the physical capital (under seabed in Norwegian case) and volatility and
uncertainty of the price (Hvozdyk and Blackman, 2010). Given these complexities, achieving
the objective of maximization of owners’ wealth is a challenging task. According to the
financial management theory, there are three major decisions including investment, financing
and dividend which ultimately determine the value of the firm (Haris and Raviv, 1991). Once
the amount of investment needed is determined in capital budget, the managers then take
financing or capital structure decision that determines sources of financing of the capital
budget. The complexity surrounding the intertwining feedback relationships of the market
prices, the capital budget and the capital structure decisions makes owners’ wealth
maximization objective even more challenging when the important decision variables are
distant in time and space.
System dynamics modeling is a useful tool to model such dynamic and complex
interrelationships which are non-linear and involve feedback relationships. Through system
dynamics, important variables can be endogenized to see the impact of policies. System
dynamics is based on systems thinking and creating a clear picture of the whole system in
order to solve a problem or define a policy. Therefore, this study is an attempt to address the
issue using system dynamics.
In order to understand these complex dynamics, we have used system dynamics by modeling
the physical processes and linking them to financial processes with a feedback structure using
data of Statoil. The rest of the paper is organized as follows: part 2 explains the model
structure, part 3 describes the parameter estimation of some important parameters used in the
model, part 4 presents model calibration. Policy design is explained in part 5 with discussion
of results in part 6. The paper is concluded in part 7.
2. Model Structure:
System dynamics model presents causal structure of the processes rather than relying on the
historical correlations to build the model. System dynamics model is capable of incorporating
nonlinearities and delays which better explain the physical processes in petroleum industry
(Sterman, Davidsen (P.69, 1990). Therefore, using system dynamics we have modeled
physical processes and their financial co-flows using data from a leading firm in the energy
sector in Norway.
2.1, Oil and Gas Production
For physical processes, we have modelled the production procedure and linked it with
financial part through feedback process to better understand the dynamics. Figure 1 represent
the structure diagram for oil and gas investment and production.
Depreciation
Capacity OF
Equipment for oil and
Gas
A
Potential oil Production
and constrained
Paes (ey
Depletion|
Investemnt
Jeestmints <i oil and gas Production
Loop
4 Cash & %
Equivalents __+
+ Sales Inventory
« + Revenue from oil sa“
Price and gas
Investment and production loop represents the main reinforcing loop for the physical and
financial processes. Firms need to invest in order to explore the reserves for oil and gas.
When reserves are proved to be there with the possibility of extraction, further investment is
needed to enable them ready for production. After development process reserves are
converted to proved developed reserves from which oil or gas could be extracted. These
developed reserves along with the capacity for production lead to production of oil and gas
which accumulates in inventory stock. The outflow from inventory leads to sales which along
with price represent revenue. Revenue generates cash which again leads to investment
needed. Capacity represents the constraint in terms of production as more than capacity to
extract cannot be produced. Production constrained loop represents the balancing loop which
is depleting the reserves because the oil or gas which is being extracted is depleting the
reserve and more investment is needed to stabilize the production in the future and there is
need to explore more reserves.
2.2.The Balance Sheet
For modeling the financial processes, we have modeled the financial statements including
balance sheet, income statement and cash flow statement. The financial statements are
modelled in compliance with generally accepted accounting principles (GAAP) as well as
system dynamics rules to represent the financial dynamics of the energy company. The
structure diagram for balance sheet is given below.
average ae of fxd assets
fixed assets 4 e
= expenditures lepreiation expense
cash ses
Treas
Exploration and Product
Common Stock L
Reliant of Stock
Tota Equity
coat sles faction
Interest Expense ag it
Long tam debt relucion|
Intangibles acer etl
peromance
notion
debt retirement time
‘anotizaion rate
ae average payment ptiod
<= QPP eit Eis
Cet Purhases OF Net inoone rained Lasses
Figure 2: The Balance Sheet
The balance sheet is structured according to the accounting principles of assets equal
liabilities and owner’s equity. Cash is a stock with inflows and outflow from physical cash
transactions. Inflows include net income retained (dividends are already subtracted from),
common stock issued and debt issued. Outflows include payments for accounts payable, debt
repayment, common stock purchased back and capital expenditure. Accounts receivable and
fixed assets represent other items on the left hand side of the equation besides cash. Long
term debt, common stock, accounts payable and retained earnings represent the right hand
side of the equation that is liabilities and owner’s equity.
2.3. The Capacity Planning
In order to plan for capacity, market price is the determining factor as how much capacity we
need in the future. Using expected revenue, we have formulated the desired capital budget
which drives the investments for future production capacity.
ct purchase Seti
Time to c!
expectation oil
Desired capital Budget Expected
forotandses ” — |_gevenye Oa [tango i oxpectod
FT ce
capital expenditure revenue oil
ction
<Manuiacturing and
Marketing sales> <Oil Revenue and gas
revenue>
Figure 3: The Capacity Planning
2.4.The Financial Planning
Here we are assuming that desired capital budget is financed through first internal financing and then
external financing. Debt to capital employed ratio determines how much debt and equity is required.
The structure for financial planning is given in figure 4 below.
depreciation __
expense:
a
Tnternal financing
— Desired new
equil ~
<Net income After ey. “new common
taxe: stock shares
tal Cash
s2otel Gash Need for external
dividends Paid> pus
Book Value per
Share
wr
<Desired capital
Budget for oil and gas <debt to capi
employed ratio= ‘=Fotal Equiy
<<
Common stock 4 —{=
issued
Figure 4: The Financial Planning
3. Parameter Estimation:
In system dynamics, parameters are used in formulation of equations in order to
describe some distinctive recognizable characteristic of the actual system. Therefore,
parameters should be set adequately accurate in order to fulfill the purpose of the
system. Some parameters and their used values are given in table 1.
Parameter Value
Interest Rate 10%
Dividend Payout Ratio 30%
Debt to capital employed ratio 40%
Tax Rate 64%
Capital Expenditure Fraction 15%
Time to change Expectation 5 years
Table 1: Parameter Values
4. Model Calibration:
Building a system dynamics model involves the process of searching and analyzing
data in order to support the development. The more accurate and comprehensive the
collected information would be used, the higher would be the prospective quality of
the quantitative model. Below are some graphs which represent the reference mode
and calibrated model.
‘Accounts Receivable Inventory
100 os
m8 mss
my 7S
Boson $ se
aE 758
°
20 72002 2004 2006 2008 2010 2012 o
mi 2000 aut Fat —Sa66 S65 FoI HE
The yeas
tvenry:Dala. Inventory Bae Rim
Graph 1: Accounts Receivable reference mode and model calibration Graph 2: Inventory reference mode and model calibration
fixed assets net income before taxes
4508 ai
NOK
g
0 2000 —-2002~—« OOH 200G~—00R—~OTO «OL
2092002200 2006 2008 2010 2010 Tine (oar
Tine (yea
Dat
Base Ri
fod assets Data
Graph 3: Fixed Assets reference mode and model calibration Graph 4: Net Income before taxes reference mode and model
calibration.
5. Policy Design:
This study designs policies for investment, capital structure and dividend decision of the firm
under stable, growing and declining product market given the cyclic nature of oil market.
Table 2 gives the detail of policy variables and optimist and conservative scenarios.
Variable Optimist Base Case | Conservative
Scenario Scenario
Oil Price Average Price Oil 5% Growth Average -2.5 Growth
Price
Gas Price Average Price Gas 5% Growth Average -2.5 Growth
Price
Investment Capital Expenditure | 25% 15% 10%
Policy Fraction
Debt Policy Debt to Capital | 20% 40% 60%
Employed Ratio
Dividend Dividend Payout Ratio | 15% 30% 45%
Policy
Table 2: Policy variables and Scenarios
The three policies investment, financing and dividend are crucial decisions in maximizing the
firm value. We have tested the three policies in order to see which policy maximizes the firm
value. The price represents the market condition which is stable and repeating the historical
trend in base run, growth of 5% in a growing product market and decline of 2.5% in
conservative market. Under these market situations, we have built three scenarios with
policies of investment, capital structure and dividend represented by policy variables of
capital expenditure fraction, debt to capital employed ratio and dividend payout ratio
respectively. The graph below represents the results of three scenarios.
Book Value per Share
fo)
2000
2016 2024 2028
ime (year)
2004 2008 2012 2020
Tr:
Book Value per Share
Book Value per Share : Base Run
Book Value per Share : C
Optimist Run
Run
Graph 5: Book Value under three scenarios Optimist, Base and conservative cases
5.1. Investment Policy:
Reference investment policy which is based on empirical investigation has the capital
expenditure fraction of 15%. For optimist and conservative case, the fraction is 25% and 15%
respectively. When tested in isolation, investment policy is most crucial in maximizing the
value of the firm given the product market growth.
5.2.Financial Policy:
Financial policy of the firm reveals that firm has less debt than the capacity in the capital
structure. Debt to capital employed ratio is 40% in the reference policy whereas 60% and
20% in conservative and optimist policy respectively.
5.3.Dividend Policy:
Reference dividend policy has dividend payout ratio of 30% which means that company pays
out dividend to its shareholders. In optimist policy the ratio is 15% and 45% in conservative
case.
6. Results and Discussion:
The objective of this analysis is to test which type of capital structure, investment and
dividend policies help maximize the firm value given stable, growing and declining oil
market conditions. To identify the best policies that maximize the book value, policies were
tested in isolation and combinations. Through system dynamics, we have tested the impact of
these policies in combinations as system dynamics takes into account nonlinearities and is
capable of better explaining the complex systems and dynamics as in case of policies a firm
has to take. In isolation, investment policy contributes most to the firm value given the
growing oil market. The assumption of growing oil market is important as prices have
significant impact on investments (Elder and Serletis, 2010). This policy outcome confirms to
the nature of investments in the oil sector as investments irreversible and long term and prices
are volatile and uncertain. In order to maximize the value, firm needs to invest to keep up the
capacity of production to meet the demand today and in the long term as it takes many years
to build the capacity for production in the oil sector. Regarding debt policy, firm is operating
with less debt than its capacity and relying more on internal funds. The risk of the firm is low.
The debt policy in our model has positive impact on the firm value in optimist case. Dividend
policy of firm currently is to pay dividends to shareholders. So, the policies in the model
assume dividends but with less percentage in optimist case and more percentage in
conservative case. These policies yield best result when they are in combination and add to
the book value significantly as evident from the graph above that optimist scenario case
maximizes the book value of the firm given the market growth condition.
7. Conclusion:
This analysis focuses on maximizing the firm value considering the cumulative effect of
investment, financing and dividend policies given the different market conditions. Through
system dynamics, we have built physical as well as financial processes model in an effort to
reflect the dynamics in the energy market where uncertainties are involved and prices are
volatile. A fter testing the policies, the analysis reveals that a bit higher investment in building
the capacities is most effective policy towards maximizing the firm value. Because of the
sound financial condition, the firm value is not very sensitive to the debt policy but less debt
in the capital structure mix adds to the firm value.
References:
Adedeji, A. (1998). "Does the pecking order hypothesis explain the dividend payout ratios of firms in the UK?" Joumal of Business Finance
& Accounting25(9-10): 1127-1155.
Ahmed Sheikh, N. and Z. Wang (2011). "Determinants of capital structure: An empirical study of firms in manufacturing industry of
Pakistan." Managerial Finance37(2): 117-133.
Baskin, J. (1989). "An empirical investigation of the pecking order hypothesis.” Financial management18(1): 26-35.
Berger, A. N. and E. B. Di Patti (2006). "Capital structure and firm performance: A new approach to testing agency theory and an
application to the banking industry." Jounal of Banking & Finance 30(4): 1065-1102.
Bloom, N., S. R. Bond, et al. (2001). "The dynamics of investment under uncertainty."
Davidsen, P. I, J. D. Sterman, et al. (1990). "A petroleum life cycle model for the United States with endogenous technology, exploration,
recovery, and demand." System Dynamics Review 6(1): 66-93
Davidsen, P. I., J. D. Sterman, et al. (1990). "A petroleum life cycle model for the United States with endogenous technology, exploration,
recovery, and demand." System Dynamics Review 6(1): 66-93.
Elder, J. and A. Serletis (2010). "Oil price uncertainty." Journal of Money, Credit and Banking 42(6): 1137-1159.
Fama, E. F. and K. R. French (2002). "Testing trade-off and pecking order predictions about dividends and debt." Reviewoffinancial
studies15(1): 1-33.
Ghazouani, T. (2013). "The Capital Structure through the Trade-Off Theory: Evidence from Tunisian Firm." Intemational Joumal
ofEconomics and Financial Issues3(3): 625-636.
Harris, M. and Raviv, A. (1991), “The theory of capital structure”, The joumal of finance, Vol.46, No.1
www npd.no/Global/Engelsk/3-Publications/Facts/Facts2014/Facts 2014 nett
Hvozdyk, L. and Mercer-Blackman, V. (2010) What Determines Investment in the Oil Sector?A New Era for National and Intemational Oil
Companies, IDB working paper series IDB-WP-209
Jensen, M. C. and W. H. Meckling (1976). “Theory of the firm: Managerial behavior, agency costs, and ownership structure” The joumal of
financial economics3(4): 305-360.
Kraus, A. and R. H. Litzenberger (1973). "A state-preference model of optimal financial leverage." The Journal of Finance28(4): 911-922.
Modigliani, F. and M. H. Miller (1958). "The cost of capital, corporation finance and the theory of investment.” The American economic
review48(3); 261-297.
Modigliani, F. and M. H. Miller (1963). "Corporate income taxes and the cost of capital: a correction." The Americaneconomic
Evian)! 433-443,
Myers, S. C. and N. S. Majluf (1984). "Corporate financing and investment decisions when firms have information that investors do not
have." Journal offinancialeconomics13(2): 187-221.
Qureshi, M. A. (2009). "Does pecking order theory explain leverage behaviour in Pakistan?” Applied Financial Economics19(17); 1365-
1370.
Shyam-Sunder, L. and S. C. Myers (1999). "Testing static tradeoff against pecking order models of capital structure." Joumal
offinancialeconomics51(2): 219-244.
Sterman, J. D. (2000). Business dynamics: systems thinking and modeling for a complex world, Irwin/McGraw-Hill Boston.
Titman, S. and R. Wessels (1988). "The determinants of capital structure choice." The Journal of finance 43(1): 1-19.
Tong, G. and C. J. Green (2005). "Pecking order or trade-off hypothesis? Evidence on the capital structure of Chinese companies." Applied
Economics37(19): 2179-218
Vilasuso, J. and A. Minkler (2001). "Agency costs, asset specificity, and the capital structure of the firm." Joumal ofEconomicBehaviors&
Organi: janization44(1): 55-69.
