“energy-economy-environment interaction using olg ......3 the mitigation of enhanced ghg effects...
TRANSCRIPT
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Very preliminary and incomplete. Please do not cite.
“Energy-Economy-Environment Interaction Using OLG Framework: Evaluation of
Alternative Policies under Demographic Transition“
Ebru Voyvoda
Department of Economics
Middle East Technical University, Ankara/Turkey
Abstract
This paper presents a multi-sectoral, large-scale OLG model calibrated to a developed (German) and
a developing (Turkish) economy, including details on demographic structure, age-dependent
consumption patterns, government taxes and expenditures and energy production. The model,
based on the seminal work of Auerbach and Kotlikoff (1987) closely follows Rutherford, Böhringer
and Pahlke (1999) and Rasmussen (2003) by its representation of energy-related activities and
environmental variables. The model is then used (i) to study the effects of demographic transition on
the energy demand and GHG emissions (ii) to study the effect of alternative policies under age-
dependent consumption structures, within a dynamic general equilibrium framework. The results
emphasize that life-cycle of consumers and the demographic structure of a society play an important
role in OLG analysis of energy-economy-environment relations.
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I. Introduction
This paper aims to analyze the effects of alternative energy/environment policies under demographic
transition. To this end, it builds up and utilizes a multi-sectoral, large-scale overlapping generations
model that represents the economy-energy-environment interactions to serve the purpose of
carrying out impact assessment of alternative energy-environment policies. The model is calibrated
to the German economy to match the data on the demographic structure and the age-dependent
consumption patterns of the households as well as the production structure of the economy.
The energy–economy–environment (E3) Computable General Equilibrium (CGE) modeling has been
one of the widely employed frameworks for the analysis of alternative environmental policies and
their potential impacts on economy, environment and social welfare. The E3-CGE models, which
often explicitly model the linkages between economic activities, energy transformation and
associated environmental impacts have been identified to provide a decent coverage of
environmental and economic indicators.1
Inherent in the policies focusing on environment, for instance policies aiming at mitigating climate
change, lies a long time frame, which naturally raises the question of intergenerational welfare and
intergenerational equity. A broad range of policy issues – natural resource scarcity, biodiversity
conservation, ozone depletion, and climate change involve both long term horizons and an
asymmetric distribution of costs and benefits between present and future society. This question has
received increasing attention and culminating in the discussions and recent contributions to the
literature. Böhringer and Löschel (2006) for instance, identify that whereas most existing E3-CGE
models have a good coverage of central economic and environmental indicators, they lack through
representation of the social indicators including ageing society, demographic change, the welfare of
older vis á vis younger generations...etc.
The infinitely-living agent (ILA) modeling framework, which has been the central structure in the
assessment of climate change policies, is based on the assumption that future generations can be
represented by a single consumer/household living over infinite periods of time. This representative
agent acts on behalf of all future generations, by possessing the rights to decide on the amount of
saving and investment of the entire present and future generations. . The dynamic ILA framework
makes it an appropriate environment to study questions such as the effects of abatement policies,
1 Böhringer and Löschel (2006) provide a detailed analysis of the uses of E-3 CGE models for Sustainability
Impact Analysis (SIA).
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the mitigation of enhanced GHG effects over long time horizons etc., but falls short of answering
questions around the effects of demographic transition or the inter/intra-distribution of welfare
among/within different generations. Schelling (1995) points out the standard ILA framework in the
context of climate change modeling involves a fallacy of composition in that the generations that are
making the sacrifices are not the ones that would be reaping the benefits. He proposes that the
evaluation of abatement policies should be seen in the context of decisions involving
intergenerational re-distribution rather than intertemporal saving. The ILA framework, where the
(infinite) life-span of individuals and the life-span of the economy are the same, analyzes the problem
in the context of intertemporal-saving rather than analyzing it in the context of decisions involving
intra and intergenerational re-distribution. Accordingly, Rasmussen (2003) emphasizes the
opportunity of investigating the distributional effects of alternative green-house gas abatement
policies between current and future generations within the finite-lifetimes framework.
The OLG structure (the finite-lifetime framework) provides a dynamic environment within a general
equilibrium framework. First, it provides an adequate treatment of the individual’s finite-life span in
a (relatively) open-ended world. The framework particularly avoids the assumption that an immortal
agent acts as a trustee on behalf of both the present and future generations. Moreover, it provides a
realistic modeling of the demographic structure of a society. The OLG structure, which, not only
distinguishes the agents by their age groups but allows one to represent different (age-dependent)
consumption patterns, different wealth endowments etc. , provides an environment to analyze in
detail any energy-environment policy action taken by the government. Such policies of course,
would have both short-run and long-run influences on the production structure, energy demand,
consumption/saving patterns, government budget, current account balance, environmental variables
(e.g. GHG emissions) and therefore, on the distribution of wealth and welfare. These features make
the OLG approach applicable to a wide range of intertemporal phenomena such as the trade-off
between intergenerational equity and economic efficiency of climate policy.
Applied studies of global environmental change, however, remain strongly focused on the
representative agent model in ILA framework. However, taking into account both the public good
nature and the intergenerational equity concerns of the problem has recently led to a few but
growing literature of quantitative, welfare-based evaluation of government policies designed to
mitigate the effects of climate change in the “finite-lifetimes framework. The very restricted set of
"calibrated" CGE models in this field include John and Pecchenino (1994, 1997), Howarth (1998),
Rutherford, Böhringer and Pahlke (1999), Rasmussen (2003), Dalton et al (2008), Kavuncu (2007) and
Leach (2009).
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Based on this literature, this paper presents a multi-sectoral, large-scale OLG model (calibrated to
German and Turkish economies), including details on demographic structure, age-dependent
consumption patterns, government taxes and expenditures and energy production. Thus the model,
based on the seminal work of Auerbach and Kotlikoff (1987) follows Rutherford, Böhringer and
Pahlke (1999) and Rasmussen (2003) closely by its representation of energy-related activities and
environmental variables. The model is then used (i) to study the effects of demographic transition on
the energy demand and GHG emissions (ii) to study the effect of alternative policies under age-
dependent consumption structures, within a dynamic general equilibrium framework.
II. Applied - OLG Models for Climate Change Policy Analysis
The earliest OLG modes were basically used for the purpose of re-examining the climate change
policy implications derived from planner-based ILA models within the finite-lifetimes framework.
Manne (1999) presents concise CGE models of climate change which allows for comparison of the
two approaches and conclude OLG and ILA models particularly lead to similar results w.r.t carbon
prices, share of fossil fuels in energy consumption, economic damages, etc. On the other hand,
Howarth (1998), Rutherford et al. (1999), Gerlagh and van der Zwaan (2001), Schneider et al (2010)
present models with substantial differences between the results of OLG and ILA models.
The discussion of Inter-generational equity/trade-offs both within ILA and OLG frameworks and
comparison of the results of these two different approaches has basically set up the basis for
employing finite-lifetimes framework for energy- economy-environmental modeling. Howarth
(1998), for instance examines structural ties between the well-known DICE mode (Nordhaus, 1994)
and the homologous OLG model and establishes that the ILA prescribes optimal (equivalent) paths
for aggregate variables provided that: (i) The weight the decision maker attaches to the life-cycle
utility of successive generations declines geometrically over time (ILA sensitive to changes in inter-
generational weights used in the social welfare function); and (ii) Transfers of capital from present to
future generations are affected by private/public institutions to achieve an optimal distribution of
welfare between generations.
The ILA framework is based on the assumption that future generations can be represented by a
single consumer/household living over infinite periods of time. This representative consumer also
acts as the representative on behalf of all future generations by possessing the rights to decide on
the amount of saving and investment of the entire present and future generations. The infinite-
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horizon nature of the model characterizes it as an environment that is appropriate to study questions
on abatement of emissions, the mitigation of enhanced GHG effects over long time horizons. The
model, to an extent, also allows for concerns on inter-generational equity by achieving equity
between generations by assuming each generation’s utility depends only on own consumptions,
adding the resulting utility levels by means of a certain weight procedure using a properly chosen
discount factor.
The argument of the properly chosen discount factor has led to a wave of discussion on the positive
vs. normative approaches surrounding the problem of global warming. Rutherford et al. (1999)
points to the case that if per-capita incomes continue to increase at even modest rates over a long-
horizon, it is likely that carbon abatement today would benefit the rich (future generations) at the
expense of the poor (those alive today). Similarly, Parfit (1983) emphasizes the moral discussion on
importance of future events declining “n” percent a year in a standard positive approach utilizing the
interest rate to calibrate for the discount factor. Schneider et al. (2010) also show that the
preference parameters of the households in an OLG economy differs from those of ILA economy. In a
general discussion, Solow (1986) argues that adjusting utility discount rates within infinitely lived
agent models is an unattractive way to frame inter-generational choices.
The set of "calibrated" CGE models for climate change policy analysis within finite-lifetimes
framework can generally be divided into three sets: (1) Standard models taking into account only the
interaction between the economic activity and energy and the directed impact of the economic
activity on the environmental indicators (i.e. greenhouse gas emissions), (2) the integrated
assessment models (IAMs) that also take the feedback of the environmental outcome on the
economic activity, (3) the models that take into account the directed technical change, i.e. the
models of endogenous growth or induced innovation models. Rutherford, Böhringer and Pahlke
(1999), Rasmussen (2003), Dalton et al (2008) are among the first set of modeling practices; Howarth
(1998) and Leach (2009) set examples of the second set; and finally, John and Pecchenino (1994,
1997), Kavuncu (2007) and Laurent-Lucchetti and Leach (forthcoming) are the few studies that
represent the induced innovation mechanism in an OLG-general equilibrium framework.
Rutherford, Böhringer and Pahlke (1999) is one of the basic examples of such CGE Models. The
authors’ focus in the study is the emissions target of Germany as adopted as part of the Kyoto
Meeting in 1997 and show that the OLG modeling framework is the appropriate framework for the
analysis of policies to achieve the carbon abatement target. To this end, the authors construct a
multi-sectoral OLG model (10 – sectors aggregated on the basis of carbon intensity) to investigate
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how alternative schemes for limiting carbon emissions can affect welfare of different generations.
The model is calibrated to 1993 macroeconomic general equilibrium of the German economy. The
policy analyses of the paper basically focus on revenue-neutral tax reforms: carbon taxes (sufficient
to reduce emissions by 15% from a growing baseline trajectory) to raise revenue which can be used
to reduce other distortionary taxes (capital, labor, consumption) in the economy. The results of the
OLG setting is then compared to the results of the associated dynamic ILA model.
Rasmussen (2003) adopts a very similar model to that of Rutherford, Böhringer and Pahlke (1999)
and presents another basic example for the methodology employed in this research. Rasmussen
builds up a multi-sectoral OLG model (8 sectors depending on energy intensities, 55 period lifetime)
to investigate the inter-generational impact of CO2 abatement for the US economy. Here, the CO2
emissions are defined as fixed proportions to the use of fossil fuels in the production processes. The
author, utilizing such an environment, investigates the impact of 15.4% reduction in CO2 emissions
over a 10 year period via emission tax. Following a similar approach with Rutherford, Böhringer and
Pahlke (1999), the tax revenues are recycled through consumption, labor, capital taxation.
Accordingly, an emission tax that is accompanied by a reduction of either the capital or the
consumption taxes benefit the current elderly who have large consumption shares and substantial
capital income. On the other hand, when it is the labor tax that is reduced to accompany the
introduction of the emission tax, all current generations are made worse off.
The model constructed in this paper is designed to be a close follower of the first set of CGE models
for climate change policy analysis within finite lifetimes framework: it takes into account the
interaction between the economic activity, energy usage and directed impact of economic activity on
environmental indicators (CO2 emissions).
III. Model Structure
The OLG model constructed is based on the idea each generation born (entering into economy to
carry out economic decisions) in each period make independent decisions on consumption/saving
throughout the finite-lifetime. Under this basic set up, there is no bequest-leaving behavior to the
off-spring. The model assumes perfect competition and no uncertainty with consistent expectations.
The economy is assumed small in world commodity and financial markets. Domestic and foreign
products are distinguished in accordance with Armington assumption. The calibration procedure
carried out ensures that solving the model with constant policy gives the solution where the first
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period aggregate values match the benchmark data and where all real variables grow at a constant
rate. The economy is disaggregated into n sectors on the basis of their relevance to the topic.
Each period, the households of different generations, that are at different stages of their finite-
lifetimes make their consumption/saving decisions which accrues to aggregate consumption/saving
of the macro-economy and thorough financial and international markets to the government and
international trade balances. The sources of household income are the factor incomes that are
coming from the supply-side and the transfers. The government gets revenues from taxes (capital
income, labor income, output) and spends these revenues on total government expenditures
(government consumption) and gives transfers to households. The model allows for any potential
government deficit to be financed by either domestic private of foreign savings.
Figure 1 adopted from by Rutherford, Böhringer and Pahlke (1999), displays the general structure of
the model which also sets the general framework for the proposed research. The economy is
disaggregated into n sectors on the basis of their carbon intensity.
Figure 1. Economic structure within a single period
Source: Adopted from Rutherford, Böhringer and Pahlke (1999)
Production OLG Demand System
Input-Output Matrix
(12x12)
capital taxes value added taxes
labor taxes transfer income
output taxes
labor income labor-income profiles
capital income
go
ve
rnm
en
t
de
ma
nd
fore
ign
de
ma
nd
inv
estm
en
t
de
ma
nd
consumption demand by
different cohorts: g=0, g=G
government
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PRODUCTION
Firms face competitive output and input markets to maximize profits. To keep the basic model as
tractable as possible, the production structure is assumed to be Cobb-Douglas with physical capital,
labor, non-energy intermediate inputs and energy composite. There is a simple nested structure for
the production technology where the energy composite input is produced along a constant elasticity
of substitution (CES) production technology using fossil fuel and electricity:
[ ] iii
xx
iELiEL
x
iFOiFOii IDIDAEENGρρρ κκ
/1
,,,,´
−−− += (1)
Under the above production technology, differentiation of the minimum cost per unit of primary
energy inputs gives the sectoral demand for coal, petroleum and gas and electricity:
)1/(1
2
,,
)1(
i
i
x
C
ij
px
i
ENG
iij
i
ij
PtNCOAE
P
ENG
IDρ
κ+
−
+= j= FO, EL (2)
The energy composite, iENG along with physical capital, labor, non-energy intermediate inputs
enters into the production technology for gross output of sector i:
= ∏ iEijIDiLiK
i
j
iiii ENGIDLKAXXS ,,,,, λλλλ (3)
with i typically representing the sectors of the economy. AXi is the technology level parameter, iK ,λ ,
iL,λ , iE ,λ denote the shares of capital input, the labor input and the energy input in the value of
gross output in sector i.
Capital and labor are assumed to be perfectly mobile between sectors. In period t, gross investment,
It, add to the next period’s capital stock, Kt+1, according to the standard accumulation equation Kt+1 =
(1-δ) Kt + It. Factor demands are obtained from profit maximization decision of the firms by paying
each factor its marginal product.
An exogenous technological improvement which is “labor-augmenting” is specified. Every generation
entering the workforce has a higher stock of technological knowledge than the previous one, and
thus becomes more productive by a constant factor, ϕ :
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1,1,1 )1( −Ω+=Ω tt ϕ (4)
Moreover, in order to be able to account for the effect of demographic changes and related policy
alternatives in future stages of this study, the model also incorporates an age-related productivity
profile:
)exp(3
3
2
210, gcgcgcctg +++=π (5)
With c0, c1, c2 and c3 are labor productivity parameters to be estimated based on the micro-data.
Therefore, not only each generation is more productive than the previous one, but also once in the
workforce accumulates labor productivity with age. Based on these specifications, aggregate labor
stock of the economy at time t is:
∑=
=G
g
tgtgtgt neL1
,,, π (6)
where g is the index for each generation and ng,t is the population of age-group g at time t.
HOUSEHOLDS
The household part of the model is disaggregated in overlapping generations (cohorts) which
typically face an identical life-cycle but different time profiles of labor supply decision and
consumption profiles over their lifetime. Each age cohort is carries out its economic decisions on a
finite life-span. Taking prices as given, the household’s life-time maximization problem is of the
form:
ερ
ε
111
1)(
11
,
0
,max, −
+=
−
+
=+ ∑
+
gtg
gG
g
gtgt
z
zzu
gtg
(7)
s.t.
[ ] )1/(/11
,
/11
,, )1(−−
+−
++ −+=σσσσ χχ gtggtggtg lecz
∑∑=
++++++
=
+ +−Ω=G
g
gtg
F
tgtggtggtg
l
gtgtg
G
g
c
gt trfplepcp0
,,,,,
0
))(π
gtggtgle ++ Ω≤ ,,
, 0, ,, ≥++ tgtgtg lec
Here, zg,t and the formulation of it as a composite of (composite) consumption and leisure represents
the constant elasticity of substitution (CES) demand structure and implies interior solutions for
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(composite) consumption cg,t and labor/leisure, leg,t. 1/(1-σ) is the elasticity of substitution between
(composite) consumption and leisure, ptc is the price of consumption and
l
tp is the wage rate at
time.
The discount rate ρ, and the intertemporal elasticity of substitution, ε are the two parameters
governing the utility function of each generation. trfg,t+g represents the total transfers that an agent,
born at time t gets at the age of g at time t+g. Following Rasmussen and Rutherford (2004), lump-
sum transfers are assumed to be dominated in foreign exchange for simplicity.
The household’s decision is based on the life-time budget constraint where each period each
member of generation t (an agent entering the economy at time t) earns the ongoing market wage
per efficiency unit of labor she supplies. While age-related productivity profile is the same for all
generations ( tg ,π ), each new generation’s efficiency labor is larger than the previous one due to
labor augmenting technological progress as stated in Equation (4).
GOVERNMENT
The government distributes transfers and does public consumption. Government expenditures are
financed by tax revenues. At this current state of the model, I define labor/capital income taxes and
production tax for each sector.
Since, in a dynamic setting, it is possible to define intertemporal solvency constraint, the model at
each period allows for running government surpluses/deficits to be financed by either domestic
private savings (through private saving –investment balance) or through foreign saving (through
trade balance). The period-wise budget constraint of the government then, is:
∑∑ −+=++g
tttg
F
tti
Y
ti
i
Y
it
R
tRt
l
tl DGtrfpXSpRpLp ,,,τττ (8)
where Lt is the aggregate labor supply in efficiency units, Rt is the aggregate capital services, XSi,t is
the (gross) output of sector i and Dt is the government budget deficit at time t.
ENVIRONMENTAL EFFECTS, TAXATION
Following an earlier modeling framework employed by Telli, Voyvoda and Yeldan (2008), three basic
sources of CO2 emissions are distinguished in the model: (i) due to (primary) energy usage, (ii) due to
industrial processes (for instance, cement production), and (iii) due to energy consumption of
households. Total CO2 emissions in the economy is the sum over from all these sources. Emissions
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from industrial processes is regarded to depend on the level of industrial activity, and is regarded
proportional to gross output:
IND
iEMCO2 = iXSiδ (9)
On the other hand, total emissions due to energy usage originate from sectoral emissions due to
combustion of fossil fuels (coal and petroleum and gas). The mechanism of emission is dependent on
the level of pollutant-emitting inputs in each sector:
ENG
iFOEMCO ,2 = ij,ϖ IDFO,i (10)
Finally, total emission of CO2 in the use of energy by households is given by:
∑=i
iiCDHHTOTCO ψ2 (11)
Here, iψ is the coefficient of emissions of CO2 in private consumption (CDi) of the basic fossil fuels
by households.
Carbon taxes can be introduced via at rates CO2tP, CO2tNi and CO2tCi per tons of carbon dioxide
emitted, on production, on intermediate input usage, and on consumption respectively.
FOREIGN TRADE, CAPITAL FLOWS, AGGREGATION
The economy is treated small relative to the world market. Domestic and foreign products are
distinguished by origin according to the Armingtonian specification. The Armingtonian goods are
aggregated with identical import shares for a given import good across all components of final and
intermediate demand. Similarly, on the export side, products of Armingtonian specification are either
supplied to the domestic market or to international markets under the assumption that they are
imperfect substitutes. I assume here a constant elasticity of transformation function (CET):
ααα χχ /1))1(( iiii EXDATXS −+= (12)
with export-domestic good ratio:
12
γγ
χ
χε
−
⋅=
1i
W
i
i
i
PD
P
D
EX (13)
with, α = (γ-1)/ γ.
The aggregate demand in the macro-economy is characterized by national account balances relating
capital income, Rt, labor income, Lt, government transfers to households Tt, private sector aggregate
consumption, Ct, private sector net saving, St, and investment It, primary government deficit Dt, and
trade deficit Bt. So, together with the government budget constraint, the following equilibrium
conditions are to be satisfied:
Rt + Lt + Tt = Ct + St (14)
with
St - Dt + Bt = It (15)
Together with the aggregate demand-supply conditions, the equilibrium in each commodity and
factor markets has to be satisfied through the adjustment of the associated price vector in each
period.
CALIBRATION, CONSTRUCTION OF BENCHMARK2
In comparison to models of ILA framework, the OLG set-up introduces extra dimensions in the
calibration process, namely the decisions of the overlapping generations households should be
consistent with the aggregate observed values of the macro-economy at any point in time. Therefore
the calibration of an OLG model, first should solve for the optimal profile of decision variables of a
reference generation subject to given aggregate levels using the steady state assumption. Next,
comes the stage where the aggregate variables for the rest of the economy should be put in
consistency with the aggregate variables that come out of the household model of the first stage.
Rasmussen and Rutherford (2004) present both a consistent set of procedures and steps to set-up a
baseline reference path of the model. I do generally follow the procedure described to set up the
basic modeling environment I will be utilizing for the rest of the paper here. Transformation of the
standard OLG modeling environment to account for energy-economy-environment interactions
demands further extensions to this basic modeling framework.
2 This Section is to be completed.
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As is customary in applied general equilibrium analysis, the model is based on economic transactions
in a benchmark year3. Benchmark data helps to determine the parameters of the functional forms of
the model framework as described above. Here, I provide a brief summary of the basic steps
followed in the calibration process and the set of the parameter values associated.
Time-generation structure of the OLG modeling framework demands that, on the one axis, one has
to trace and keep account of the time t, and on the other axis lies the generations, g=0,…G alive at
each time period. By the life-span of the representative generation that enters the economy at time
t=0, there is an indirect relationship between the household’s maximization problem given in
Equation (7) and the macroeconomic general equilibrium at time t=0. For the optimal life-span
problem to be consistent with the macro-aggregates of the economy, one has to establish
consistency in terms of the parameters of the household’s maximization problem.
It is customary for the calibration procedure to assume that initially the economy is at its steady-
state equilibrium. Therefore the parameter ϕ represents the steady –state growth rate of the
economy (in case there is no population growth). Similarly, given the (real) interest rate, one can
impose the dynamic path for the level of general price index pt = (1+r)t with the value equated to p=1
for t=0. Such restrictions can also be imposed for the steady state path of the overall trade deficit of
the economy: Bt+1 = (1+ϕ ) Bt.
The following equations help understanding the general calibration procedure followed. In terms of
aggregate consumption observed in t=0, and aggregate labor income generated at t=0, one has to
match the household optimization problem in Equation (7) and the macro- balance of the economy,
represented in Equations (14)-(15):
∑+
=+
gg
gtg
t
cC
)1(
,
ϕ (16)
∑+
−Ω=
+++
gg
gtggtggtg
t
leL
)1(
)( ,,,
ϕ
π (17)
3 In this version of the paper, the benchmark year for German data is 2008, for Turkish data, it is chosen to be
2010.
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Similarly, consistency between micro-and-macro behaviors implies that total value of household
assets equals total domestic plus foreign assets. Therefore, it is the value of the trade deficit that
determines the volume of foreign asses in the economy. Then, the value of households’ total assets
has to be equal to the value of aggregate capital stock of the economy less future obligations to
government. Therefore, allowing for permanent deficits, the steady state assumption implies:
∑−
+−++==
g
ttttgtr
rDBKrmA
ϕ
1)()1(´, (18)
where mg,t is the value of assets held at period zero by the members of the generation of age g.
Imposing such a condition helps the calibration procedure to represent the steady-state relationship
between capital income, Rt and the capital stock of the economy Kt, such that Rt = (r+ϕ )Kt.
The model described is calibrated to both developing (Turkish) and developed (German) economies
to investigate the effect of demographic transition under different economic structures. The data for
the Turkish calibration comes from the multi-sectoral Social Accounting Matrix (SAM) of the Turkish
economy, constructed on latest TURKSTAT 20002 Input-Output Table that is re-arranged accordingly
to give a structural portray of intermediate flows at the intersection of commodities row and
activities column in the 12-sector 2010 macro-SAM.
The calibration for the German economy is based on the World Input Output Database (WIOD) that
is re-arranged accordingly to give a structural portray of intermediate flows at the intersection of
commodities row and activities column in the 35-sector 2008 macro-SAM.4
As the model described contains a number of economic and environmental parameters, the
estimation of them becomes important in evaluating the quantitative results of the alternative policy
scenarios. In this case, it is important to represent the critical sectors w.r.t. energy demand and also
w.r.t environmental variables.
Following the model structure and the calibration procedure described above, two pieces of
quantitative analysis has been carried out: (i) Calibration of parameters ρ, the utility discount rate
and Ω, time endowment-scaling factor along with tax rates, emission parameters etc. ; (ii) the base-
path of the economy under the assumption of steady-state has been generated. This base path
4 See Pothen and Koesler (2012) for more on WIOD data and the transformation of the raw data into a form to be
utilized in environmental CGE models.
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generated typically serves as the benchmark case to which alternative policy simulation results will
be compared in later stages of the research.
To provide an idea on the consistent set of calibrated values, Table A1 in Appendix displays the set of
selected (exogenous) variables and parameters (for calibration to Turkish data), and the calibration
results under two different settings: (i) under the assumption that leisure is given a positive
importance in the period-wise utility of each representative household, (ii) under the assumption of
exogenous (full) labor supply.
IV. SCENARIOS AND RESULTS
THE EFFECTS OF DEMOGRAPHIC TRANSITION
Demographic structure may have serious impacts on the economy. The issue of demographic change
has been addressed around the questions on sustainability of social security systems, or fiscal policy
etc., but not within the question of sustainable environment. Yet, change in demographic structure
may affect the greenhouse gas emissions (not only via its effects on household consumption or
consumption patterns but also via its indirect demand effect on the production structure of the
economy).
For instance, by increasing the share of old people in total population, demographic change may
affect the use of different energy sources, which in turn affects the emissions.
Dalton et al. (2008) study that the demographic change in US reduces the CO2 emissions in US by
40% between 2000 and 2100. Kronenberg (2008) has also shown that demographic change in
Germany has a significant impact on the structure of private households’ consumption expenditures.
Especially, the energy use of households is also significantly affected. Generally, the findings of the
paper show that demographic change tends to increase the consumption of energy for heating
purposes and to reduce the consumption of motor vehicle fuels. Thus, demographic change has an
interesting effect on the ‘energy mix’ consumed by private households. The change in the structure
of consumption expenditures also triggers effects on the sectoral production of output. Most
notably, the output of the sector refined petroleum products and other fuels is reduced, while the
output of the sector electricity and district heat is increased.
16
Following the claim that demographic change (relative to stable population dynamics) may have
serious impact on the greenhouse gas emissions of an economy, the model constructed is first
utilized to simulate the forecasted German/Turkish demographic structures. Given the population
projections by United Nations (UN), one can observe the projected demographic structures. Figure 2
provides the forecasts for the population growth rate of Germany/Turkey vis á vis Western Europe.
Figure 2. Population growth rates, Germany, Turkey & Western Europe, % (1950-2100)
Source: UN
A transformation of such population forecasts into the modeling framework here is the change in
the cohort-structure. Using the UN Population Projections w.r.t age, a simulation designed is to give
the demographic shock and evaluate the changes in the model economy (Figure 3 and 4).
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
Germany
Western Europe
17
Figure 3: Future Projections (t = t0, t0+50, t0+100) on population of different age-groups relative
to a stable population growth (Germany)
(with 0.2% population growth rate)
Age-group
Source: Based on UN Projections
One can observe from Figure 3 that the current middle-income dominated demographic structure
(w.r.t. a stable population growth) of the German economy is forecasted to move towards a more
older structure in t+50 and a more balanced structure in t+100.
As Figure 4 indicates, Turkish demographic structure as of 2005-2010 period, on the other hand,
shows a youth-dominated picture compared to the case of constant population growth. Yet, with
the forecasted reduction in the population growth rate and increase in life-spans, Turkish
demographics is expected to move towards a middle-aged profile in the medium run and towards
an older profile in the longer run. Yet, a lower value relative to a constant 0.2% population growth
rate, causes the ratios to stay lower than 1.0 in the Figure.
0
0.2
0.4
0.6
0.8
1
1.2
1.4
20-25 25-30 30-35 35-40 40-45 45-50 50-55 55-60 60-65 65-70 70-75
0
50
100
18
Figure 4: Future Projections (t = t0, t0+50, t0+100) on population of different age-groups relative
to a stable population growth (Turkey)
(with 0.2% population growth rate)
Age-group
Source: Based on UN Projections
Demographic Shock: Germany
I compare the baseline path under a stable population growth to the path generated under the
demographic shock, as pictured in Figure 3 for Germany. Figure 5 and Figure 6 display the effects of
such a transition on the major macroeconomic variables; Figure 7 portrays the path of aggregate
CO2 emissions by the production sectors of the economy and the households.
Both Figures 5 and 6 indicate that the currently relatively older population structure of the German
economy keeps both the aggregate labor supply (in efficiency labor units) and aggregate capital
supply of the economy higher than it would have been under a stable population growth. Yet, in the
longer run, as the population growth rate turns into negative the aggregate labor supply follows a
path that decreases at a higher rate than aggregate capital supply. Such a result is expected for it is
the middle-aged and older generations that have accumulated assets over their lifecycles. The
comparison of Gross Domestic Product (GDP) and Private Consumption variables (Figure 6) also
provide similar results w.r.t. to effects of projected demographic transition on the macroeconomic
0
0.2
0.4
0.6
0.8
1
1.2
20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74
0
50
100
19
variables. As the economy get deprived of capital and labor supplies, (in comparison to the stable
population growth benchmark case), total GDP, total income and private consumption decreases. In
line with decreased consumption demand, CO2 emissions by households decrease faster than the
CO2 emissions by the production sectors of the economy.
Figure 5: Effects of Demographic Shock, Germany:
Macroeconomic variables, % Change w.r.t. Benchmark
Figure 6: Effects of Demographic Shock, Germany:
Macroeconomic variables, % Change w.r.t. Benchmark
20
Figure 7: Effects of Demographic Shock, Germany:
Emission variables, % Change w.r.t. Benchmark
Yet, we observe from Figure 8 that the source of aggregate emissions by households changes its
structure over time. In the short run, as the economy shows a more middle-age dominant structure,
the majority of the emissions is caused by the households that fall into this age group. Over time
(t0+20 - t0+25) the economy becomes older and it is now the old-age group that becomes
responsible for a major portion of total CO2 emissions. The contribution of younger age groups (w.r.t.
an age structure under stable population growth) reduces and becomes negative over time. Such a
picture strongly emphasizes that effects of different environmental policies will be differentiated for
different age groups living together in the economy.
21
Figure 8: Effects of Demographic Shock, Germany:
Household Emissions by Age Structure over Time, % Change w.r.t. Benchmark
Demographic Shock: Turkey
In order to provide insight for the effects of demographic transition on the macroeconomic, energy
and environmental variables in the context of a developing economy, Figures 9-12 illustrate the
paths of a selected set of variables for the Turkish economy under demographic transition. Here, a
demographic shock that keeps the population of each age group below the corresponding level
under a stable population growth indicates a lower profile for the aggregate capital stock and
aggregate labor stock variables, w.r.t. benchmark (Figures 9, 10). As the population becomes more
middle-aged, both the profile of aggregate capital and aggregate (efficiency) labor stock increases;
in the longer run, as the population gets older, both macro-variables show a declining trend.
Similarly, gross domestic product shows a trend below the benchmark, along with private
consumption. Yet, both the upturn and downturn of GDP is smoother than that of consumption
since the older tend to consume relatively higher and it is mostly the younger and the middle-aged
that hold labor and capital stocks of the economy.
22
Figure 9: Effects of Demographic Shock, Turkey:
Macroeconomic variables, % Change w.r.t. Benchmark
Figure 10: Effects of Demographic Shock, Turkey:
Macroeconomic variables, % Change w.r.t. Benchmark
The paths of emission variables under the effect of the Turkish demographic change mostly follow
the patterns of consumption and the real GDP (Figure 11). The lower consumption path generates a
lower emissions path for the households’ contribution. Yet, the lower demand also causes shifts
within the production structire of the economy and in line with the path of GDP, produces a
23
relatively favorable path for contribution to total emissions by the production sectors of the
economy.
Figure 11: Effects of Demographic Shock, Turkey:
Emission variables, % Change w.r.t. Benchmark
The contribution of different age groups to aggregate household emissions through time is illustrated
in Figure 12. Following the Figure, one can trace that as the population gets older, the contribution
of young decreases and the contributions of middle-aged and old increases. Although aggregate
household emissions are lower than the benchmark in the short run (Figure 11), one can understand
that such lower figure is actually governed by the lower consumption profile of old households. The
contribution of young and middle aged are still high, even in the short run; thanks to relatively higher
consumption possibilities for these age groups. As the economy moves towards medium-long run,
the population structure stabilizes and the contribution of different age groups to total household
emissions also stabilizes at lower paths w.r.t. benchmark.
24
Figure 12: Effects of Demographic Shock, Turkey:
Household Emissions by Age Structure over Time, % Change w.r.t. Benchmark
THE EFFECTS OF DEMOGRAPHIC TRANSITION UNDER AGE-DEPENDENT CONSUMPTION PATTERNS
To be completed.
V. DISCUSSION
The energy–economy–environment CGE modeling has been one of the widely employed frameworks
for the analysis of alternative environmental policies and their potential impacts on economy,
environment and social welfare.
The OLG structure built in this paper provides a dynamic environment within a general
equilibrium framework. First, the framework provides an adequate treatment of the
individual’s finite-life span in a (relatively) open-ended world. Moreover, it provides a more
realistic modeling of the demographic structure of a society. As the OLG structure
characterizes the agents/generations not only by their age but by their wealth/endowment,
revenue-raising, expenditure decreasing devices will naturally have distortionary side-effects
on the allocation of resources. These features make the OLG approach applicable to a wide
range of intertemporal phenomena such as the trade-off between intergenerational equity
and economic efficiency of climate policies.
25
Following the discussion, the model designed in this paper is utilized to show what OLG structure
can provide for the energy-economy- environment analysis. To such an end, this report illustrates
the results of a simulation experiment to reflect demographic shocks for a developing (Turkey) and a
developed (German) economy. The change in demographic structure of an economy is important
for the analysis since it may affect the greenhouse gas emissions (not only via its effects on
household consumption or consumption patterns but also via its indirect demand effect on the
production structure of the economy). As the greenhouse gas, especially CO2 emissions are closely
related with the use of fossil fuels, an energy tax is one of the effective policy instruments in
mitigation effects. The OLG framework constructed is used to show the impact of demographic
shocks to the macroeconomic, sectoral and generational variables of the economy.
The large-scale OLG model that represents the economy-energy-environment interactions is an
effective tool to serve the purpose of carrying out impact assessment of alternative energy-
environment policies. Further calibration of the model to World scale should help to set up an
environment where numerical evaluations of alternative policies w.r.t. economy, environment and
intra-and inter-generational welfare can be carried out.
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27
Appendix
Table A1. Selected Variable and Parameter Values, Calibration Results (Turkish Case)
Variable and Parameter Values
Consumpti
on share in
composite,
χ = 0.8
Consumption
share in
composite, χ =
1.00
Annual real interest rate r 0.05
Steady-state growth rate n 0.005
Annual depreciation rate for physical capital δ 0.07
Elasticity of substitution (c vs le) 1-1/ σ 0.80
Elasticity of transformation D vs EX η 4.00
Armington elasticity on imports σ_AL 4.00
Intertemporal elasticity ε
Age-Productivity parameters
Constant c 0 1.078462
Coeffcient on age (starting at age 21) c 1 0.097136
Coefficient on age squared c 2 -0.001517
Coeffcient on age cubed c 3 0.000007
Calibrated Parameters
Ratio of capital stock to assets θA 0.712
Ratio of government deficit to assets θD 0.094
Ratio of trade deficit to assets θB 0.194
Household behavioral parameters
Period utility discount rate ρ -0.126 -0.202
Scaling factor on time endowment Ω 2.038 0.786
Tax rates
Labor Income τl 0.200
Capital Income τR 0.239
Output τiY
AG 0.038
MW 0.010
CO 0.034
ET 0.007
PG 0.005
AU 0.005
PE 0.028
EL 0.003
CE 0.016
CN 0.025
IS 0.011
OE 0.018
Emissions coef.
Coal 13.409
Petroleum-Gas 4.978
Industrial Proc. 1.509
ij,ϖ
iδ