Central banks’,ntegration of&limate&hange,ssues into an,ncreased
Taylor5ule in the Mediterranean5egion: An$nalysis based on the
6ystem The Generalized Method of Moments (GMM)
BENJILALI MOHAMED 1, AZHARI MOURAD 1, CHIKHI EL MOKHTAR 1, ABARDA ABDALLAH 2
1Center of Guidance and Educational Planning, Rabat
MOROCCO
2Laboratory of Mathematical Modeling and Economic Calculations,
Faculty of Economics and Management, Hassan 1st University, Settat,
MOROCCO
Abstract: Climate change could have significant consequences such as rising sea levels, intensified storms, floods,
droughts and forest fires. These effects could lead to forced migration, ecosystem degradation and extinction
of many species. In addition, they could also affect the ability of central banks to maintain price stability. This
research proposes an innovative method to integrate CO2 emissions into a Taylor rule, considering a risk premium
related to climate change. This risk premium is determined by the CO2 emission gap. The model is evaluated over
a period from 2002 to 2022 for 14 countries in the Mediterranean region, using the two step system Generalized
Method of Moments (GMM). The results show that the coefficient associated with the CO2 emission gap is both
positive and statistically significant at a level of 5%. This means that a 1% increase in this gap leads the Central
Bank to increase its policy rate by 2.64%.
Key-Words: Central Bank; Climate change; CO2 emissions; Taylor’s Rule; System Generalized Method of
Moments (GMM); Mediterranean region.
Received: April 29, 2024. Revised: September 20, 2024. Accepted: October 21, 2024. Published: November 22, 2024.
1 Introduction
Central banks around the world are paying increasing
attention to climate change, recognizing that it could
undermine their ability to achieve their monetary
and financial stability goals. In addition, climate
change poses major economic and social challenges,
requiring a central role for the financial system in
managing climate risks and financing the transition to
a low carbon economy. Climate change can influence
monetary policy in several ways. First, the physical
and transitional risks associated with climate change
can affect macroeconomics and inflation forecasts.
Second, climate change can indirectly influence
monetary policy by changing the expectations of
households and businesses about future economic
performance, [1]. Climate risks also directly affect
central bank balance sheets. Thus, central bank risk
managers need to integrate these risks into their day
to day operations.
An effective approach is to establish climate
risk management principles, which provide the basis
for the identification, assessment, mitigation and
disclosure of climate risks.These principles should
also detail the tools used by the central bank at
each stage of this climate risk management process.
In November 2020, the ECB published a Guide on
Climate and Environmental Risks,[2], setting out its
supervisory expectations for the management and
communication of climate risks. Although the guide
is not formally binding, it sets out the standards
that banks should comply with. It covers several
areas such as strategy, governance, organization,
measurement and risk management, as well as non
financial reporting.
As part of its supervision, the ECB launched its
first climate stress test, involving 104 major euro area
banks, [3]. The main objective was to assess banks’
ability to perform internal stress analyses related to
climate risks. This included their ability to develop a
framework for climate risk analysis, assess different
climate risk factors and project climate risk into the
future.
At the heart of monetary policy is Taylor’s famous
rule, [4]. This rule proposes that the EDF’s interest
rate policy should follow a simple pattern: respond to
differences between inflation and the inflation target,
as well as between real output and potential output.
Since then, many econometric studies, such as, [5],
[6], [7], [8], [9], [10], have estimated Taylor’s rule
for various countries and economic contexts. This
research examined the central principle that a central
bank reacts when real macroeconomic performance
diverges from its objectives. For example, if inflation
exceeds its target and/or real output exceeds potential,
a central bank must raise its key interest rates.
Taylor’s rule has become a central tool in the teaching
of monetary policy, as noted by Waters in 2021.
Our analysis extends the application of the Taylor
rule by considering the gap between CO2 emissions
and their target, as a key factor influencing changes in
interest rates. The most polluting economies should
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bear higher interest rates to reflect their increased
level of polluting emissions. This proposal introduces
a premium, called the climate change premium, which
must be integrated into central bank decision making.
The new model of Taylor’s rule is examined in
the Mediterranean region using the system method
GMM. Our work aims to answer the following
research question: how can central banks in the
Mediterranean region adapt their monetary policy to
incorporate CO2 emissions into an augmented Taylor
rule, in the face of the challenges posed by climate
change?
To address this issue in a systematic way, our study
is structured along two main lines. The first is a
review of the literature on climate change and the role
of central banks. The second axis is dedicated to the
application of an augmented Taylor rule, integrating
CO2 emissions, using the GMM system method, and
to the analysis of the results obtained.
2 Climate&hange and the5ole of
&entral%anks
The main thrust of this proposal is that central banks
should incorporate climate change issues into their
decision making processes. We plan to analyse
the origins and impacts of climate change and then
examine the role that banks can play in combating this
phenomenon.
2.1 Climate&hange
The industrial revolution was propelled by the
intensive use of fossil fuels, mainly coal, which, once
burned, released carbon dioxide into the atmosphere,
contributing to global warming. Watt’s steam
engines and most of the means of transport at
the time operated with coal. During the 20th
century, oil became crucial to fuel vehicles, aircraft
and ships. The agricultural revolution has also
played a role in climate change due to the use of
nitrogen fertilizers, which emit powerful greenhouse
gases. The expansion of agricultural land to meet
growing demand has led to massive deforestation,
releasing carbon stored in trees, while livestock emit
methane during digestion. These revolutions have
led to remarkable economic growth, significantly
reducing poverty and hunger in many parts of
the world. However, this growth has also led
to an unprecedented increase in greenhouse gas
emissions, causing man made climate change. The
correlation between real GDP growth and the increase
in global CO2 emissions is not accidental, but
demonstrates a causal relationship, as illustrated in
Figure 1 and Figure 2. Climate change represents
an unprecedented challenge for humanity, capable
of profoundly altering the biosphere and raising
Fig.1: Global GDP, Source: Federal Reserve
Economic Data
Fig.2: Increase in CO2 concentration, Source: Our
World in Data
awareness of the global ecological impact of human
development. The current era, described by some
as the ”Anthropocene”, bears witness to the fact that
humanity is now a threat to itself. In this section,
we examine the causes and consequences of climate
change.
2.2 The&auses of&limate&hange
Industrialized nations are generally identified as
the main contributors to climate change, while the
countries of the South are seen as having less
responsibility for climate change. Much research has
been done to understand the reasons for the difference
in pollution between certain countries. Most of these
studies have shown a positive correlation between
economic growth and greenhouse gas emissions,
[11]. Another factor contributing to the increase
in greenhouse gas emissions is population growth.
According to United Nations projections, the world
population is expected to reach about 9 billion by
2050. This population growth is mainly concentrated
in the countries of the South: Africa and Asia have the
highest growth rates, while the European population
is declining. By 2050, it is estimated that 60 per cent
of the world’s population will reside in Asia and 20
per cent in Africa.
OECD countries account for only about 12%
of the world’s population, underscoring the need
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for more involvement of other nations in emission
reduction efforts, particularly major economies such
as China, India or Brazil, [12]. Human activities
have contributed significantly to increasing levels of
greenhouse gases in the atmosphere.
2.3 The&onsequences of&limate&hange
Climate change has emerged as one of the major
challenges of our time. The impacts of global
warming are now evident, as shown by the changes
in adverse global climate events illustrated in Figure
3.
Existing research on the relationship between
climate and the economy highlights several
mechanisms by which progressive global warming
could curb the potential for economic growth.
First, it could lead to a decline in the effective
supply of labour in the economy due to lower
labour productivity caused by physical and cognitive
changes in human capital. In addition, extreme heat
waves could also reduce this supply by increasing
mortality and morbidity, promoting the spread of
diseases such as malaria, [13]. For example, [14]
observed a decrease in productivity of about 1.7% for
each 1◦C increase in daily average temperature above
15◦C, based on variations between U.S. counties
over a 40 year period. Similarly, [15] found that
higher temperatures have a negative impact on a
more comprehensive indicator of human well being,
as measured by the Human Development Index.
Another possible consequence of global warming
could be a reduction in the rate of accumulation of
productive capital, either by permanent damage or by
an increase in the rate of depreciation of capital, [13].
There is a strong link between agriculture and climate
change, where changes in environmental conditions
affect crop production and productivity, contributing
to global food insecurity, [16], [17], [18], [19]. The
rise in global temperature leads to an increase in
the water pressure deficit, resulting in a reduction
in crop productivity. To cope with this, agriculture
adopts adaptation strategies such as changing crop
cycles and selecting more resistant seeds, such as
wheat varieties adapted to heat and requiring less
sunlight. Other agricultural production methods are
expanding, such as organic farming, agro ecology,
permaculture and urban agriculture.
2.4 The5ole of the Central Bank in the)ight
against&limate&hange
Central banks are institutions responsible for
overseeing the financial system and implementing a
country’s monetary policy. In many countries, they
are public entities with institutional independence
from government. Unlike commercial banks, central
banks do not function as deposit taking institutions
Fig.3: Number of deaths from natural disasters
worldwide, Source: Our World in Data
open to the general public; it is generally impossible
for an individual to open an account or apply for a
loan. The evolution of the role of central banks has
been marked by a great diversity throughout history,
however, contemporary central banks are generally
assigned two main functions:
• Monetary policy: Its role involves the issuance
of notes and coins, while developing monetary
guidelines aimed at ensuring price stability and
confidence in the currency. In many countries, an
inflation target is defined, and it is up to the central
bank to achieve it. Therefore, determining ”key
interest rates” is the main measure used by central
banks to implement their monetary policy;
• Financial stability: It takes place through the
supervision of the financial system, where central
banks use their regulatory and supervisory authority
to ensure the stability of financial institutions, prevent
bank crises and discourage reckless or fraudulent
banking practices. In times of financial crisis, they
also act as ”lenders of last resort” for the banking
sector.
Central banks must take climate change risks
into account because of their potentially significant
implications for the economy and the financial
system. Climate change can cause disruptions
at different levels of the economy, both through
natural disasters and transition shocks, making it a
potential source of price and financial instability,
[20]. Since climate risks can directly affect
the traditional responsibilities of central banks, all
institutions should integrate climate related physical
and transition risks into their strategies to maintain
financial stability.
2.5 Physical5isks and7heir,mpact on
0onetary3olicy
Physical hazards include damage caused by weather
events such as floods, droughts, fires, heat waves,
sea level rise, and damage to ecosystems and the
services they provide. These risks can be immediate,
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as in floods, or prolonged, such as changes in
precipitation patterns or rising temperatures. Since
tightening monetary policy could aggravate the
economic consequences of weather disasters, a
flexible approach to the inflation target would allow
a central bank to exercise discretion in mitigating
these adverse effects. Central banks should carefully
examine the impact on supply and demand as well
as on the output gap, especially because of the
increased difficulty in forecasting potential output
during unforeseen shocks such as climate events.
The destruction of the capital stock following natural
disasters reduces overall supply, while reconstruction
efforts could stimulate aggregate demand. If a natural
disaster leads to an increase in surplus output and
inflationary pressure, a central bank may consider
tightening its monetary policy, [21]. However,
a natural disaster could also have a significant
and lasting negative impact on demand, creating
a production deficit, if it damages the balance
sheets of households and businesses in the affected
areas, leading to a decrease in consumption and
investment. In addition, a natural disaster could
undermine business confidence, trigger a large sale
in financial markets, increasing the cost of financing
new investments and reducing investment demand.
According to, [22], storms lead to a temporary
increase in food price inflation, although this effect
fades during the year. Similarly, floods generally
have a temporary effect on inflation. [23] also notes
that exogenous shocks affecting food prices have a
significant impact on consumer prices, contributing
on average to 25-30% of inflation volatility. Thus,
climate change could increase the volatility of overall
inflation by increasing the volatility of food price
inflation rates. [24] points out that climate change has
long lasting stag flationary effects that central banks
cannot effectively cope with. The main channels
through which these impacts are transmitted to the
traditional risks of banking are as follows, [25]:
• Credit risk: Physical and transition risks increase
a bank’s credit risk by compromising a borrower’s
ability to repay and service its debt, or by impeding
the bank’s ability to recover the value of a loan in the
event of default.
• Market risk: Climate risk factors can have a
significant influence on the value of financial assets.
Physical and transition risks may alter or reveal
new prospects for future economic conditions or
for the value of real or financial assets, leading to
downward price shocks and increased volatility in
the markets for traded assets. In addition, climate
risk could disrupt asset to asset correlations, reducing
the effectiveness strategies and undermining banks’
ability to actively manage their risks. However,
early consideration of climate risk could mitigate the
potential for unforeseen price movements.
• Liquidity risk: Climate risk factors can also
influence banks’ liquidity risk, both in terms of their
ability to raise funds and indirectly through additional
liquidity outflows from customers and/or reductions
value of assets used as collateral. It has been noted
that a natural disaster may constitute a potential
liquidity outflow factor.
• Operational and reputational risk: Within
the framework of the Basel Capital Agreement,
operational risk is defined as the possibility of
suffering losses due to faulty internal processes,
human errors, systemic failures or external events,
including legal risk but excluding strategic and
reputational risk. However, the operational risk
management of banks should, if necessary, take into
account the latter. Physical risks can directly impact
banks as operational risks. Although public research
on these risks related to physical risk factors is
limited, similarities with other natural disasters can
be established. For example, physical disruptions to
transport and telecommunications infrastructure can
reduce the operational capacity of banks. Companies,
as well as banks, may also face an increased risk of
non compliance with laws and regulations, as well as
costs related to litigation and civil liabilities resulting
from climate sensitive investments and activities.
2.6 Transition5isks and7heir,mpact on
0onetary3olicy
Regulatory changes represent the most significant
transformation risk, as they can alter overnight returns
on investments. Figure 4 highlights transition risks
and summarizes how these risks are spreading across
the financial system. The risks associated with the
transition to a low carbon or zero carbon economy
can be examined using the Kaya identity model,
[26]. This model provides an analytical framework
by breaking down global variations in greenhouse gas
emissions into fundamental factors:
CO2emissions =population ×GDP
population
×Energy
GDP
×CO2emissions
Energy
Kaya’s identity breaks down CO2 emissions
into four basic elements: population, GDP per
capita (GDP/population), energy intensity of
GDP (Energy/GDP), and CO2 intensity of energy
(CO2/energy). This formulation implies that to
specifically reduce carbon emissions, action must
be taken on two fronts: on the one hand, to reduce
energy intensity by reducing the energy used per
unit of GDP, and on the other, to reduce the carbon
intensity of energy by adopting cleaner energy
sources. According to, [27], growth accounting
assesses the impact of emission reductions, including
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Fig.4: Channels of Climate Risk to Financial Risk
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reductions in energy consumption, on economic
growth. In a competitive economy, the elasticity
of energy in relation to production corresponds to
the share of energy costs in production, which is
generally low on a global scale. Thus, an approximate
10% reduction in energy consumption could lead to
a decrease in production of up to 1%.
The main threat to macroeconomics associated
with the transition from climate change comes from
climate policies. Some of these policies, such as
those based on pricing mechanisms such as carbon
taxes or regulations, can lead to economic constraints.
Compliance with these environmental regulations
may force companies to reduce production or allocate
part of their resources to reduce emissions, which may
have negative effects on profitability, productivity,
employment and, ultimately, GDP. From a monetary
policy perspective, the carbon pricing approach
can be interpreted as a negative supply side shock.
By imposing a price on carbon, the authorities
seek to discourage the production and consumption
of emissions intensive goods. Disturbances in
macroeconomic and financial markets caused
by climate change and transition policies could
undermine the effectiveness of monetary policy and
the ability of the Central Bank to achieve its objective
of price stability through various channels, including
interest rates, credit, asset valuation, exchange rates
and expectations. These disruptions could result in
particular from the depreciation of assets and the
subsequent weakening of the banking sector, thus
hampering the transmission of monetary policy. In
addition, climate change and the transition to a low
carbon economy are changing the value and risk
profile of assets held in the central bank’s balance
sheet, which could accumulate climate related
financial risks. [28] identifies three ways climate
change could affect price stability:
• Initially, the impacts of climate change could
disrupt the transmission of monetary policy measures
from central banks to the financing conditions
available to households and businesses, thus
influencing consumption and investment.
• Secondly, climate change could further restrict
the policy space of traditional monetary policy by
lowering the real equilibrium interest rate, which
balances savings and investment. For example, rising
temperatures could lead to lower labour productivity
or higher disease and mortality rates. This could lead
to the diversion of productive resources to adaptation
financing, while climate uncertainty could encourage
precautionary savings and discourage investment.
• Thirdly, climate change and efforts to mitigate
its effects can directly influence inflation dynamics.
Recent events have shown that an increase in the
frequency of physical risks can lead to short term
fluctuations in output and inflation, exacerbating long
term macroeconomic instability (see figure 4).
2.7 Rethinking the,ntegration of&limate
5isks into Macroeconomic Models
The economic impact of climate change and
mitigation measures requires careful assessment
through macroeconomic models, given the
fundamental uncertainty surrounding this
phenomenon. Conventional approaches to financial
risk management may be insufficient in the face
of this uncertainty, [29], [30]. Greenhouse gases
accumulating in the atmosphere and its implications
for future temperatures remain uncertain despite
efforts to reduce emissions. This uncertainty
includes not only the average temperature rise,
but also their spatial and temporal variability. For
example, identifying and assessing climate risks
requires alternative approaches, [31], [32].
[33] developed a network based climate stress
testing method applied to major euro area banks
through ”green” and ”brown” scenarios. Their
results underline the importance of timing in
the implementation of climate policies, with
differentiated impacts on the valuation of assets
according to the early and stable political framework.
An early and stable climate policy would allow
gradual adjustments, while a delay or abrupt change
could lead to negative systemic consequences. A
study by, [34], assessing the potential impact of a
disruptive energy transition on financial stability in
the Netherlands suggests that financial institutions
could face significant but manageable losses. These
losses could be mitigated by considering the risks
associated with the energy transition. Policymakers
have a crucial role to play in putting in place timely,
reliable and effective climate policies to avoid
unnecessary financial losses. In 2020, the Bank
of France launched a pilot stress test involving
French banks and insurance companies to assess
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their exposure to transition and physical risks, while
raising awareness of climate issues, [35].
For many years, economists have been using
Integrated Assessment Models (IAM) to study the
impact of climate change. These models make it
possible to anticipate the future implications of global
warming on the Gross Domestic Product (GDP)
by examining the complex interactions between the
physical and economic aspects of the phenomenon.
For example, they are used to estimate the ”social
cost of carbon”, which helps to define an optimal
trajectory for the carbon price. However, Integrated
Valuation Models often rely on damage functions
that can be unreliable, thus limiting their usefulness
for monetary policy development. Among these
models, the Integrated Dynamics of Climate and the
Economy (DICE). [36], is widely considered to be the
most influential, taking into account CO2 emissions,
climate impacts and associated economic losses. [37]
estimated the social cost of carbon at 31$.
Per tonne of CO2 for the year 2015, with an
annual increase of 3% until 2050. In parallel, [38]
analyzed a dynamic stochastic general equilibrium
model (DSGE) integrating an externality linked to
climate change due to the use of fossil energy.
Their study revealed that coal, due to its abundance,
represents a major threat to economic well being,
unlike oil.
3 Modeling Tests of the Taylor Rule
Augmented with CO2 Emissions in
the Mediterranean Region
3.1 Description of the Variables
Our analysis covers 14 countries in the Mediterranean
region over the period 2002 to 2022. The descriptive
data of the variables are presented in Table 1. On
average, GDP per capita in the Mediterranean region
is estimated at 17 577.82 with a standard deviation of
12 410.98. The average money market rate is 3.53%
with a standard deviation of 4.78%. As regards CO2
emissions, the average is 144 million tonnes with a
standard deviation of 148 million tonnes. Domestic
credit to the private sector, expressed as a percentage
of GDP, has an average of 73.77% with a standard
deviation of 46.49%. Figure 5 illustrates a positive
correlation between the interest rate and the inflation
gap. When inflation exceeds the target, the Central
Bank reacts by raising the interest rate.
Figure 6 shows a positive correlation between
CO2 emissions and inflation. Figure 7 illustrates a
positive correlation between the interest rate and the
CO2 emissions gap. It is noted that a 1% increase in
this gap leads the Central Bank to increase its policy
rate by 4.43%. In the Mediterranean region, the
correlation between GDP growth and CO2 emission
Table 1.Description of variables
Fig.5: The relationship between the money market
rate and the inflation gap, source: Authors
growth is not an accident; rather, it reflects a causal
relationship, as illustrated in figure 8. In the end,
figure 9 shows a positive correlation between the
interest rate and credit Gap. When the credit exceeds
the target, the Central Bank reacts by raising the
interest rate.
3.2 Taylor’s Original Rule
In 1993, John Taylor enriched the reflection on
the objectives of monetary policy by proposing his
equation (known as the Taylor equation) to explain
the central bank’s interest rate policy:
it=β0+β1(πt−π∗
t) + β2(yt−y∗
t)(1)
With
β0=rt+πt(2)
Fig.6: The regression of Inflation (INF) on CO2
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Fig.7: The regression of MMR on CO2 Gap
Fig.8: The relationship between CO2 growth and
GDP growth
Fig.9: The regression of MMR on Credit Gap
Where i is the short term interest rate targeted by
monetary authorities, ris the real equilibrium interest
rate, πis inflation, π∗is the inflation target, yis real
GDP ,y∗is potential GDP, and β1and β2are positive
coefficients. The real equilibrium interest rate is
generally estimated either by taking the difference
between the average of short term interest rates and
the average of inflation rates over a period, or by using
the potential growth rate of the GDP. The Taylor rule
with its own parameters becomes, [4]:
it= 2%+πt+ 0.5(πt−2%)+0.5(yt−y∗
t)(3)
The rule suggests a tighter monetary policy when
inflation exceeds its target and production exceeds its
potential, and vice versa. [4] and [39] put forward
the idea that a simple interest rate rule, reacting
systematically to inflation and trend production,
can, with the appropriate coefficients, represent
the evolution of the federal funds rate during the
Greenspan era. Empirical evidence of the constancy
of this Taylor rule over time and in various countries
is presented, [5], [40], [8]. [41] evaluated rules
with seven different models. These rules include the
Taylor Rule, a ”balanced approach” rule, a difference
rule that responds to growth rather than inflation and
unemployment levels, as well as two rules that take
into account periods with federal funds rates close
to zero in particular by implementing a promise of
future guidance to compensate for periods of lower
zero bound with a later looser policy.
3.3 System GMM Estimation
In this study, the empirical analysis of the augmented
Taylor’s rule, which integrates CO2 emissions in
the Mediterranean region, is carried out using
the generalized moment method estimator (GMM)
proposed by, [42], [43]. We use the generalized
moment (GMM) system method rather than standard
panel OLS or intra group estimates, as the latter
produce biased and inconsistent estimates, [42],
[43], [44], [45]. Firstly, level OLS estimates are
biased and inconsistent because they neglect country
specific effects, which are unobserved and time
invariant. The estimator of the coefficient of the
lagged dependent variable remains biased upwards,
and the estimated coefficients of the exogenous
variables are biased downwards, [46]. Using the
standard within group estimator for dynamic models
with fixed individual effects leads to estimates
that become inconsistent when the number of
”individuals” increases indefinitely, while the number
of periods remains constant, [47]. The GMM
system estimator corrects the bias associated with
these two approaches. Secondly, the system GMM
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estimator offers efficient and consistent parameter
estimates in a regression where the explanatory
variables are not strictly exogenous. This means they
are correlated with past and present errors, and/or
there is heteroskedasticity and auto correlation within
individuals, [48].
Third, the estimator GMM solves the problem of
endogeneity by using instruments for the delayed
dependent variable and/or any other endogenous
variable. These instruments are selected to be
unrelated to fixed effects, [47]. Finally, compared
to the estimator GMM in differences, introduced
by, [49], the estimator GMM in system proves
more effective by adding an additional hypothesis
that the first differences of the instruments are not
correlated with the fixed effects, allowing the use
of more instruments, [48]. [49] suggested using
delayed differences of the dependent variable as
instruments for the level equation and delayed levels
of the dependent variable as instruments for the first
difference equation. It is well known in econometrics
that instrumental variable instrument performance
decreases when we have ”too many instruments”, [48]
and [50] introduced a statistical test to assess the
validity of over identified restrictions in instrumental
variables. Hansen then extended this Sargan test to
apply to the GMM method. The null hypothesis of the
Sargan/Hansen J tests states that the over identified
restrictions are valid. In this situation, we prefer
that our restrictions be appropriate. Therefore, we
do not wish to reject the null hypothesis, so higher
p values are preferable. [51] has shown that the Jtest
is weakened by many instruments. More worryingly,
when the number of instruments equals the number of
panels, it is even possible to obtain a false p= 1, [48].
We search a test capable of assessing the validity of
our instruments, because the results of GMM depend
on it. However, this test becomes ineffective if too
many instruments are used. [48] recommends that
a p value slightly above 0.05 be sought, but little
more. Pvalues above 0.25 could indicate that the
many instruments compromised the validity of the
test. [49] proposed to verify the presence of auto
correlated errors by examining the auto correlation in
the residues of the estimated differentiated equation.
A first order auto correlation in these residues is
to be expected. However, we encounter a problem
if we find auto correlated residues in the second
differences. The null hypothesis for this test is that
there is no auto correlation. Thus, if we obtain a
small p value, we can reject the null hypothesis of
the absence of auto correlation; on the contrary, we
have proofs of auto correlation. Therefore, we should
look for p values greater than, say, 0.05 for AR(1) in
the first differences and p values greater than 0.05 for
AR(2).
3.4 Discussion of the Results
The Taylor rule approach can be increased to consider
the difference between actual and potential CO2
emissions. In the same way as for variables such as
inflation and production, a positive coefficient should
be included for CO2 emissions. This reasoning
stems from the fact that exceeding the desired CO2
emissions leads to externalities that need to be
addressed through higher borrowing costs, which
reduces the demand for credit and ultimately the
level of economic activity. The dynamic version of
Taylor’s rule is expressed:
MMRi,t =β0+β1MMRi,t−1+β2IN Fi,t −IN F ∗
i,t+β3GDPi,t −GDP ∗
i,t
+β4CO2i,t −CO2i,t
∗+β5InterINFCO2 i,t+β6Cred-Cred ∗+ϵi,t (4)
where : β0=ri,t +INFi,t The estimated values of
INF∗, GDP ∗, Cred ∗and CO2∗are obtained by using
a HodrickPrescott filter:
-rtis the real equilibrium interest rate.
- InterINFCO2 is the interaction between Gap
inflation and Gap CO2 emissions.
-ϵi,t means an error term.
Table 2 shows that the coefficients are statistically
significant. The coefficients associated with the
output gap and the inflation gap are positive and
significant at the 5% threshold. Therefore, the
Central Bank should increase its policy rate, as
inflation exceeds the target and output exceeds its
potential. The Central Banks of the Mediterranean
countries attach particular importance to inflation
and output gap. This suggests these countries are
concerned with both price stability and the stability
of economic activity. The coefficient associated with
a time lag in interest rates is positive and significant
at the 5% threshold. We also find that the coefficient
associated with the CO2 emission gap is positive and
significant at the 5% threshold. An increase of 1% in
this gap leads to a reaction from the Central Bank,
which increases its interest rate by 2.64%. According
to a study conducted by, [52], using the Global Vector
Auto regressive (GVAR) methodology, a restrictive
monetary policy in a country has been associated with
a reduction in national CO2 emissions, both in the
short and long term. The coefficient associated with
the interaction between the inflation gap and the CO2
gap is positive and significant at the 5% threshold.
Droughts, heat waves and frequent floods can lead
to higher commodity and food prices, increasing
inflation, [53]. In response, the Central Bank must
increase its policy rate by 2.29%.
The coefficient associated with the credit gap granted
to the private sector is positive and significant at
the 5% threshold. This means that an increase of
this 1% gap leads to a reaction from the central
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2024.20.61
Benjilali Mohamed, Azhari Mourad,
Chikhi El Mokhtar, Abarda Abdallah
E-ISSN: 2224-3496
640
Volume 20, 2024
Table 2.The estimation of the Taylor rule increased
by the system method GMM
bank, which increases its policy rate by 3.11%.
Second tier banks adjust the rates they apply to their
customers based on changes in key rates, whether
they increase or decrease. Higher policy rates tend
to slow down economic activity, while lower rates
stimulate economic activity.
The equation of the augmented Taylor rule is as
follows:
MMRi,t = 1.48 + 0.49M MRi,t−1+ 0.02 IN Fi,t −IN Fi,t
∗
+13.68GDPi,t −GDPi,t
∗+2.64 CO2i,t −CO2∗
i,t
+2.29(InterI NF CO2i,t ) +3.11Cred-Cred ∗+ϵi,t (5)
Table 2 shows that the tests AR(1) and AR(2)
show the absence of auto correlation in the residues,
since the values of p are greater than 0.05.
The results of the Sargan and Hansen over
identification tests support the legitimacy of the
instruments used. In this context, a value of p greater
than 0.05 is generally considered satisfactory, but
an excessively high value, ([48] suggested that 0.25
was too high), suggests an excess of instruments.
Therefore, the pvalues of 0.08 and 0.16 that we
obtained are encouraging.
4 Conclusion
Climate change is influencing the financial sector
through two types of risks: physical risks and
transition risks. The increased public awareness
of these risks underlines the importance of the role
of central banks in managing environmental risks
and supporting the development of green finance.
Traditionally, central banks use three monetary
policy levers to regulate the money supply in the
economy: key interest rates, minimum reserves and
open market operations. These traditional tools
can be enriched by environmental considerations,
thus allowing monetary policy to contribute to
environmental protection. Key interest rates are
a monetary policy instrument commonly used by
central banks to regulate the money supply. As part
of initiatives to integrate ecological considerations,
central banks can integrate environmental elements
into the determination of interest rates. For example,
a central bank could introduce differentiated interest
rates for banking institutions according to their
ecological commitment. Thus, banks fully committed
to ecological initiatives could benefit from lower
interest rates, while those with little or no ecological
commitment could be charged higher rates.
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The authors wrote, reviewed and edited the content
as needed and They have not utilised artificial
intelligence (AI) tools. The authors take full
responsibility for the content of the publication.
References:
[1] Lane, Philip R., Monetary Policy and Below
Target Inflation, Speech at the Bank of Finland
conference on Monetary Policy and Future of
EMU, (2019).
[2] European Central Bank, Monetary policy
decisions, (2020).
[3] European Central Bank (ECB), Supervisory
assessment of institutions ”climate related and
environmental risks disclosures ECB report on
banks” progress towards transparent disclosure
of their climate related and environmental risk
profiles, (2022).
[4] Taylor, J.B. , Discretion versus policy rules in
practice, Carnegie Rochester Conference Series
on Public Policy, Vol.39, (1993), pp. 195-214.
doi: 10.1016/0167-2231 (93) 90009-l
[5] Clarida, R., Gali, J., & Gertler, M., Monetary
policy rules in practice, European Economic
Review, Vol. 42, N°. 6, (1998), pp. 1033-1067.
doi: 10.1016/s0014-2921 (98) 00016-6
[6] Galimberti, J.K., & Moura, M.L., Taylor rules
and exchange rate volatility in a small open
economy, Journal of International Money and
Finance, Vol. 32, N°. 1, (2013), pp. 1008-1031.
https://doi.org/10.1016/j.jimonfin.2012.08.006
[7] Orphanides, A., Monetary Policy Rules Based
on Real-Time Data, American Economic Review
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2024.20.61
Benjilali Mohamed, Azhari Mourad,
Chikhi El Mokhtar, Abarda Abdallah
E-ISSN: 2224-3496
641
Volume 20, 2024
, Vol. 91, N°. 4, (2001), pp. 964-985. doi:
10.1257/aer.91.4.964
[8] Orphanides, A., Historical monetary policy
analysis and the Taylor rule, Journal of Monetary
Economics, Vol.50, N°. 5, (2003), pp. 983-1022.
doi: 10.1016/s0304-3932 (03) 00065-5
[9] Peersman, G., & Smets, F., The Taylor Rule: A
Useful Monetary Policy Benchmark for the Euro
Area?, International Finance, Vol. 2, N°. 1, pp.
85-116. doi: 10.1111/1468-2362.00020
[10] Sauer, S., & Sturm, J.-E., Using Taylor
Rules to Understand European Central Bank
Monetary Policy, German Economic Review
, Vol. 8, N°.3 , (2007), pp. 375-398. doi:
10.1111/j.1468-0475.2007.00413.x
[11] Grossman, G.M., & Krueger, A.B. , Economic
Growth and the Environment, The Quarterly
Journal of Economics, Vol. 110, N°. 2, (1995),
pp. 353-377. doi: 10.2307/2118443
[12] Gemenne, F., Climate geopolitics: International
relations in an overheating world, (2021),
Armand Colin .
[13] Fankhauser, S.,& S.J. Tol, R., On climate change
and economic growth, Resource and Energy
Economics, Vol. 27, N°. 1, (2005), pp. 1-17. doi:
10.1016/j.reseneeco.2004.03.003
[14] Deryugina, T., & Hsiang, S. M., Does the
environment still matter? Daily temperature
and income in the United States (No. w20750),
National Bureau of Economic Research, (2014).
[15] Acevedo, S., Mrkaic, M., Novta, N., Pugacheva,
E., & Petia, T. , The effects of weather shocks
on economic activity: What are the channels
of impact? IMF Research Department Working
Paper, Washington, DC: International Monetary
Fund , Vol. No. 18/144), (2018)
[16] Hatfield, J.L., Boote, K.J., Kimball, B.A., Ziska,
L.H., Izaurralde, R.C., Ort, D.,... Wolfe, D. ,
Climate Impacts on Agriculture: Implications
for Crop Production, Agronomy Journal,
Vol. 103, N°. 2, (2011), pp. 351-370. doi:
10.2134/agronj2010.0303
[17] Arora, N.K. , Impact of climate change on
agriculture production and its sustainable
solutions, Environmental Sustainability,
Vol. 2,N°. 2, (2019), pp. 95-96. doi:
10.1007/s42398-019-00078-w
[18] Guntukula, R., Assessing the impact of climate
change on Indian agriculture: Evidence from
major crop yields, Journal of Public Affairs ,
(2019) Vol. 20, N°. 1. doi: 10.1002/pa.2040
[19] Guntukula, R., & Goyari, P. , Climate Change
Effects on the Crop Yield and Its Variability in
Telangana, India, Studies in Microeconomics,
Vol. 8, N°. 1, (2020), pp. 119-148.doi: 10.1177/
2321022220923197
[20] Bolton, P., et al. , The green swan. Central
banking and financial stability in the age
of climate change, Bank for International
Settlements, (2020).
[21] Keen, B.D., & Pakko, M.R., Monetary policy
and natural disasters in a DSGE model, Federal
Reserve Bank of St, Louis Research Division
Working Paper, No. 2007-025D, (2010).
[22] Parker, M. , The impact of disasters on inflation,
Economics of Disasters and Climate Change,
Vol. 2, N°. 1, (2018), pp. 21-48.
[23] Peersman, G. , International food commodity
prices and missing (dis) inflation in the euro area,
Review of Economics and Statistics, Vol. 104,
N°.1, (2022), pp. 85-100.
[24] Olovsson, C., Is climate change reporting to
Central Banks?, Sveriges Riksbank Economic
Commentaries, (2018).
[25] BCBS, Climate-related risk drivers
and their transmission channels, (2021),
www.bis.org/bcbs/publ/d517.pdf
[26] Kaya, Y. , Impact of carbon dioxide emission
control on GNP growth: Interpretation of
proposed scenarios, Paper presented to the
IPCC Energy and Industry Subgroup, Response
Strategies Working Group, Paris , (1990).
[27] Smulders, S., Toman, M., & Withagen, C.,
Growth theory and green growth , Oxford Review
of Economic Policy, Vol. 30 (3), (2014), pp.
423-446. doi: 10.1093/oxrep/gru027
[28] Schnabel, I., Climate Change and Monetary
Policy, Finance & Development, Vol. 58, N°. 3,
(2021), pp. 53-55.
[29] Ackerman, F., Worst case economics: Extreme
events in climate and finance, Anthem Press,
(2017)
[30] Barnett, M., Brock, W., & Hansen, L.P. , Pricing
uncertainty induced by climate change, Review
of Financial Studies, Vol. 33, N°. 3, (2020), pp.
1024-1066. https://doi.org/10.1093/rfs/hhz144
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2024.20.61
Benjilali Mohamed, Azhari Mourad,
Chikhi El Mokhtar, Abarda Abdallah
E-ISSN: 2224-3496
642
Volume 20, 2024
[31] Battiston, S. , The importance of being forward
looking: Managing financial stability in the
face of climate risk, Financial Stability Review,
(2019), pp. 23, 39-48.
[32] Broeders, D., & Schlooz, M. , Climate change
uncertainty and central bank risk management,
Journal of Risk Management in Financial
Institutions, Vol. 14, N°. 2, (2021), pp. 121-130.
https://ideas.repec.org/a/aza/rmfi00/y2021v14i2
p121-130.html
[33] Battiston, S., Mandel, A., Monasterolo, I.,
Schütze, F., & Visentin, G. , A climate stress
test of the financial system, Nature Climate
Change, Vol. 7, N°. (4), (2017), pp. 283-288.
https://doi.org/10.1038/nclimate3255
[34] Vermeulen, R., Schets, E., Lohuis, M., Kölbl,
B., Jansen, D.-J., & Heeringa, W. , An
energy transition risk stress test for the financial
system of the Netherlands (DNB Occasional
Studies, Netherlands Central Bank, Research
Department, (2018), Vol. 16/07).
[35] Clerc, L., Bontemps-Chanel, A. L., Diot, S.,
Overton, G., Soares de Albergaria, S., Vernet, L.,
& Louardi, M. , A first assessment of financial
risks stemming from climate change: The main
results of the 2020 climate pilot exercise, Banque
de France, Supervisory and Resolution Authority,
Vol. 122, (2021).
[36] Nordhaus WD. , A question of balance:
weighing the options on global warming policies,
Yale University Press, (2008).
[37] Nordhaus, W.D. , Revisiting the social cost of
carbon, Proceedings of the National Academy of
Sciences, N°. 7, pp. 114, , (2017),pp. 1518-1523.
doi: 10.1073/pnas.1609244114
[38] Golosov M, Hassler J, Krusell P, Tsyvinski
A. , Optimal taxes on fossil fuel in general
equilibrium, Econometrica, Vol. 82, N°. 1,
(2014), pp. 41-88.
[39] Taylor, J.B. , A Historical Analysis of Monetary
Policy Rules. In: Taylor, J.B., Ed., Monetary
Policy Rules, University of Chicago Press,
Chicago, (1999), pp. 319-348.
[40] Clarida, R., Gali, J., & Gertler, M. , Monetary
Policy Rules and Macroeconomic Stability:
Evidence and Some Theory, Quarterly Journal of
Economics, Vol. 115, N°. 1, (2000b), pp. 147-180.
doi: 10.1162/ 003355300554692
[41] Cochrane, John H., and John B. Taylor. (2020).
Strategies for Monetary Policy. Stanford, CA:
Hoover Institution Press.
[42] Arellano, M., & Bover, O. , Another look at
the instrumental variable estimation of error
components models, Journal of Econometrics,
Vol. 68, N°. 1, (1995), pp. 29-51. doi:
10.1016/0304-4076 (94) 01642-d
[43] Blundell, R., & Bond, S. , Initial conditions
and moment restrictions in dynamic panel data
models. Journal of Econometrics, Vol. 87, N°.
1, (1998), pp. 115-143. doi: 10.1016/s0304-4076
(98) 00009-8
[44] Blundell, R., Bond, S., Windmeijer, F. ,
Estimation in Dynamic Panel Data Models:
Improving on the Performance of the Standard
GMM Estimator, In: Baltagi, B.H., Fomby, T.B.,
Hill, R.C. (Eds.), Nonstationary Panels, Panel
Cointegration, and Dynamic Panels, flight. 15,
Emerald Group Publishing Limited, (2001), pp.
53-91.
[45] Bond, S.R., Hoeler, A., Temple, J.R., GMM
Estimation of Empirical Growth Models. CEPR
Discussion Papers, (2001), No. 3048 (Available
at SSRN: http://ssrn.com/abstract =290522).
[46] Hsiao, C., Analysis of Panel Data. Cambridge
University Press, (2014).
[47] Nickell, S. , Biases in Dynamic Models with
Fixed Effects, Econometrica, Vol. 49, N°. 6,
(1981), pp. 1417-1426. doi: 10.2307/1911408
[48] Roodman, D. , A Note on the Theme of Too
Many Instruments. Oxford Bulletin of Economics
and Statistics, Vol. 71, N°. 1, (2009), pp. 135-158.
doi: 10.1111/j.1468-0084.2008.00542.x
[49] Arellano, M., & Bond, S. , Some Tests of
Specification for Panel Data: Monte Carlo
Evidence and an Application to Employment
Equations, The Review of Economic Studies,
Vol. 58, N°. 2, (1991), pp. 277-297. doi:
10.2307/2297968
[50] Sargan, J.D. , The Estimation of Economic
Relationships using Instrumental Variables,
Econometrica, Vol. 26, N°. 3, (1958), pp.
393-415. doi: 10.2307/1907619
[51] Windmeijer, F. , A finite sample correction for
the variance of linear efficient two-step GMM
estimators, Journal of econometrics, Vol. 126,
N°. 1, (2005), pp .25-51.
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2024.20.61
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E-ISSN: 2224-3496
643
Volume 20, 2024
[52] Attilio, L. A., Faria, J. R., & Rodrigues, M.,
Does monetary policy impact CO2 emissions?
A GVAR analysis. Energy Economics, Vol. 119,
(2023), p. 106559.
[53] Batten, S., Sowerbutts, R., & Tanaka, M.,
Climate change: Macroeconomic impact and
implications for monetary policy, Ecological,
societal, and technological risks and the financial
sector, (2020), pp. 13-38.
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