[PPT] - Summary Introduction 1 Research program Gemmes research PowerPoint Presentation

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27/06/2018 #WorldInCommon AGENCE FRANÇAISE DE DÉVELOPPEMENT | FRENCH DEVELOPMENT AGENCY 0/72

#WorldInCommon

AGENCE FRANÇAISE DE DÉVELOPPEMENT | FRENCH DEVELOPMENT AGENCY

27/06/2018

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#WorldInCommon AGENCE FRANÇAISE DE DÉVELOPPEMENT | FRENCH DEVELOPMENT AGENCY 0/72

#WorldInCommon

AGENCE FRANÇAISE DE DÉVELOPPEMENT | FRENCH DEVELOPMENT AGENCY

GEMMES - ISEO 27, JUNE 2018

Gaël Giraud Chief Economist | AFD Senior researcher | CNRS Professor | ENPC Director | Energy et Prosperity Chair

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Summary

1

Introduction Research program

2

Gemmes research programme

3

Gemmes: the model Basics

4

Introduction Research program

5

Related Literature

6

Modeling set-up The macroeconomic core The climate module

7

Target achievements

8

Modeling uncertainty

9

Climate prospective Scope of analysis Scenario analysis

10 Concluding remarks

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Outlines

1 Introduction Research program 2 Gemmes research programme 3 Gemmes: the model 4 Introduction 5 Related Literature 6 Modeling set-up 7 Target achievements 8 Modeling uncertainty 9 Climate prospective 10 Concluding remarks

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Introduction

The 2008 crisis: a revival of Minsky’s theory of financial instability

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1 2 3 4 5 4.0 4.8 5.6 6.4 7.2 8.0 8.8 9.6 10.4 11.2 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 fred.stlouisfed.org Nonfinancial Business; Credit Market Instruments; Liability, Level/Gross Domestic Product (left) Civilian Unemployment Rate (right) % Chg. of (Bil. of $/Bil. of $) Percent

Figure: Time series of the private debt ratio and employment rate in the United States over the period 1990-2010.

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Introduction

A “New normal"? (1)

Figure: Quantitative Easing vs inflation, US.

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Introduction

A “New normal"? (2)

Figure: Public debt vs spread, US.

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Introduction

Failure of standard models

Figure: Troïka’s predictions on the Greek GDP ...

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Introduction

Dynamic Stochastic General Equilibrium (DSGE)

1. All the present and future variables are simultaneously at equilibrium
2. People maximize their individual utility (or profit) perfectly anticipating the future.
3. Returns to scale are decreasing by assumption.
4. Equilibrium is only disrupted by exogenous shocks but is always locally asymptoti-

cally stable

5. Money is neutral and there is no banking sector.
6. Private debts don’t matter.
7. Inequalities don’t matter.
8. Energy and matter don’t matter.
9. Climate backloops are harmless.

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Introduction

The trouble with macroeconomics

Blanchard (PIIE, 2016):

I see the current DSGE models as seriously flawed...

Romer (2016):

For more than three decades, macroeconomics has gone backwards...

Kocherlakota (2016):

...we simply do not have a settled successful theory of the macroeconomy. The choices made 25-40 years ago - made then for a number of excellent reasons - should not be treated as written in stone or even in pen.

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Introduction

Micro-foundations?

Figure: Sonnenschein-Mantel-Debreu (1975)

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Introduction

Rational expectations?

Cass & Stiglitz (1969) : trajectories with rational expectations are not locally stable

in the space of trajectories with expectations.

In the parlance of Guesnerie (2006) : REE are not eductively stable.

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Introduction

The Price-taking paradigm

1. Suppose you wanna travel from Iseo to Roma as quickly as possible...

2.

∂p ∂qi = 0 and dp dQ < 0 are mutually incompatible (unless each firm is atomless):

0 = ∂p ∂qi = dp dQ ∂Q ∂qi = dp dQ < 0.

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Introduction

The Price-taking paradigm

1. The conventional solution to

Maxqi π(qi) = p · qi − ci(qi) is not individually optimal (unless each firm is atomless): π(qi + dqi) − π(qi) = p(Q + dqi)(qi + dqi) − ci(qi + dqi) − p(Q)qi + ci(qi) ≃ p(Q)dqi + qidqi dp dQ + d2qi − c′

i (qi)dqi

≃ qidqi dp dQ < 0

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Introduction

The Price-taking paradigm 1. dπ dQ :=

j

∂π ∂qj dqj dQ =

j

∂ ∂qj

p(Q)qi − ci(qi)

dqj dQ =

p − c′

i (qi)

dqi dQ + qi dp(Q) dQ

j

dqj dQ ,

2. In the symmetric case:

dqi dQ = dQ −

j=i dqj

dQ = 1 − (n − 1) dqi dQ , 3. c′

i (qi) = p(Q) + nqi

dp(Q) dQ = p(Q) + Q dp(Q) dQ . (1)

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Introduction

The Price-taking paradigm

1. The price-taking solution coincides with the monopolistic one.
2. Hence, it is Pareto-suboptimal.
3. Discontinuity of the price-taking solution when n → +∞. (= Mas-Collel ()).
4. Perfect competition makes sense only with an atomless space of firms.

In the “real” world (n < +∞), competition is always imperfect.

5. Stigler (1954), Keen & Standish (2006), Giraud et al. (2018).

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Summary

1

Introduction Research program

2

Gemmes research programme

3

Gemmes: the model Basics

4

Introduction Research program

5

Related Literature

6

Modeling set-up The macroeconomic core The climate module

7

Target achievements

8

Modeling uncertainty

9

Climate prospective Scope of analysis Scenario analysis

10 Concluding remarks

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II. Debts and credit

Figure: Keen (2017)

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Debts and credit

7

Figure: Keen (2017)

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Debts and credit

Figure: UK (Keen (2017))

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Debts and credit

Figure: Keen (2017)

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Gemmes research programme

Key research highlights

1. Combine three potential sources of global instabilities (climate, finance and in-

equalities) in a minimal and consistent framework to provide prospective analysis insights on the climate-economy interactions

2. Identify the instability factors and their transmission channels (in particular the piv-
tal role of private debt) through non-linear dynamics.
3. Provide public policy guidance for the implementation of the Paris Agreement to

contain global warming “well below” +2◦C.

4. Provide insight on the impact of natural resource scarcity: biodiversity, energy, min-

erals...

5. Help drive the social-ecological transition.

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Summary

1

Introduction Research program

2

Gemmes research programme

3

Gemmes: the model Basics

4

Introduction Research program

5

Related Literature

6

Modeling set-up The macroeconomic core The climate module

7

Target achievements

8

Modeling uncertainty

9

Climate prospective Scope of analysis Scenario analysis

10 Concluding remarks

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Gemmes: the model –

Theoretical elements

Minimum (bounded) rationality in a stock-flow consistent set-up. Mathematical formalization of Minsky’s moment ◮ Lotka-Volterra relationship linking the employment rate to the wage share ◮ Dynamics of the private debt of firms + endogenous creation of non-neutral money by

banks.

Phenomenological empirical approach to ground aggregate behavior:

investment, consumption, short-term Phillips curve (Mankiw (2010)[? ], Gordon (2014), Krug- man (2014)).

Endogenous business cycles Multiplicity of long-term equilibria: ◮ A desirable steady-state equilibrium ◮ A bad attractor leading to a breakdown

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Gemmes: the model –

Stock-Flow consistency

Households Firms Banks Sum Balance Sheet Capital stock K K Deposits Mh Mf −M Loans −L L Sum (net worth) Xh Xf Xb X Transactions current capital Consumption −C C Investment I −I Accounting memo [GDP] [Y] Wages W −W Interests on deposits rMh rMf −rM Interests on loans −rL rL Financial Balances Sh Π −I Sb Flow of funds Gross Fixed Capital Formation I I Change in Deposits ˙ Mh ˙ Mf − ˙ M Change in loans −˙ L ˙ L Column sum Sh Π Sb I Change in net worth ˙ Xh = Sh ˙ Xf = Π − δK ˙ Xb = Πb ˙ X

Table: Balance sheet, transactions, and flow of funds in the economy

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Outlines

1 Introduction 2 Gemmes research programme 3 Gemmes: the model Basics 4 Introduction 5 Related Literature 6 Modeling set-up 7 Target achievements 8 Modeling uncertainty 9 Climate prospective 10 Concluding remarks

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Basic Model structure

Cass-Stiglitz (1969), Akerlof-Stigliz (1969), Keen (1995).

1. Leontief production function:

Yt = min Kt ν , atLt

= Kt

ν = atLt Wages are consumed, Profits reinvested ˙ K = It − δKt = (Yt − wtLt) − δKt

2. Short-term Phillips Curve (Mankiw, 2010)

˙ w w = Φ (λ)

3. Productivity and population grow exponentially

˙ a a = α > 0 , ˙ N N = β > 0.

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Basic Model structure (2)

1. The wage share:

ωt := wtLt Yt = Wt Yt The employment rate: λt := Lt Nt

2. Autonomous non-linear differential system

˙ ω ω = Φ(λ) − α , ˙ λ λ = 1 − ω ν − α − β − δ

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Gemmes: the model

The simple Keen (1995) model

1. ω ∈ [0, 1] wage share in the GDP;
2. λ ∈ [0, 1]= employment rate.
3. d := D/Y private debt ratio over real GDP

.

4. The model can be described by the “simple” non-linear system:

5. ˙ ω = ω

Φ(λ) − α
˙

λ = λ

g − α − β
˙

d = κ(π) − π − dg

α= productivity growth rate β: population growth rate. Φ(·): short-run Phillips curve. κ(π) = I investment as a function of the profit share π := 1 − ω. g= real GDP growth rate.

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Gemmes: the model – Basics

Convergence to the locally asymptotically stable steady-state equilibrium

Figure: Phase diagram in the Keen model (1995)[? ].

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Gemmes: the model – Basics

Viability analysis through the basin of attraction

Figure: Basin of attraction of the desirable steady-state in the Keen model. Source: Grasselli et al. (2012)[? ]

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Gemmes: the model

Some extensions

1. Under standard assumptions:

3 long-run equilibria.

2. A Solovian equilibrium (locally asymptotically stable) (cf. Harrod-Domar) with a

balanced growth path. g = α + β. Golden Rule. λ → NAIRU (Tobin, Akerlof-Stiglitz (1969)).

3. A debt-deflationary (Fisherian) equilibrium (locally asymptotically stable)

g = 0.

4. A “slavery equilibrium” (λ > 0 but ω = 0) unstable.

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Summary

1

Introduction Research program

2

Gemmes research programme

3

Gemmes: the model Basics

4

Introduction Research program

5

Related Literature

6

Modeling set-up The macroeconomic core The climate module

7

Target achievements

8

Modeling uncertainty

9

Climate prospective Scope of analysis Scenario analysis

10 Concluding remarks

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Outlines

1 Introduction 2 Gemmes research programme 3 Gemmes: the model 4 Introduction Research program 5 Related Literature 6 Modeling set-up 7 Target achievements 8 Modeling uncertainty 9 Climate prospective 10 Concluding remarks

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Introduction – Research program

The modelling tree Goodwin (1967) Keen (1995) Prices Banks Inventories Government Financial Markets Inequality Multisectoral Climate feedback loop Open economy Resources

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Introduction – Research program

1. Climate feedback loops: climate-finance interplay–Stern-Stiglitz commission (2017).
2. Inequality: Giraud-Grasselli (2017).
3. Banks: Giraud-Kockerols (2015), European parliament report.
4. Natural resources: Rostom-Giraud-Vidal (2017).
5. Capital Vintage: Lojkine-Giraud (2017).
6. Thermodynamics: Goupil-Herbert-d’Angelo-Giraud (2017).
7. Brazil: On financing the energy shift.
8. Other prospects: Colombia, Ivory Coast, Vietnam, Tunisia...

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Introduction

Climate change is a milestone for the 21st century

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Introduction

The trouble with macroeconomics

Blanchard (PIIE, 2016):

I see the current DSGE models as seriously flawed...

Romer (2016):

For more than three decades, macroeconomics has gone backwards...

Kocherlakota (2016):

...we simply do not have a settled successful theory of the macroeconomy. The choices made 25-40 years ago - made then for a number of excellent reasons - should not be treated as written in stone or even in pen.

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Introduction

The role of private debt

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1 2 3 4 5 4.0 4.8 5.6 6.4 7.2 8.0 8.8 9.6 10.4 11.2 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 fred.stlouisfed.org Nonfinancial Business; Credit Market Instruments; Liability, Level/Gross Domestic Product (left) Civilian Unemployment Rate (right) % Chg. of (Bil. of $/Bil. of $) Percent

Figure: Change in private debt and employment rate in the United States – Period 1990-2010

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Introduction

Research questions

Combine two sources of global instabilities, climate and finance, in a minimal dy-

namic framework to perform a prospective analysis. Can climate change drive the global economy in a deep recessionary state?

Provide guidance for the implementation of public policy objectives in order to en-

sure economic stability and perform the energy shift. Is a price signal sufficient?

Cope with climate as well as economic uncertainties in order to have a deeper

understanding of our chances to meet to Paris Agreement’s objectives. What are our chances to stay below +2◦C?

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Introduction

Main findings

In a business as usual scenario, climate change drives the global economy toward

a situation of “economic collapse.”-

A price signal (carbon tax) provides indeed the right incentives to perform the en-

ergy shift and avoid most of climate damages.

However, financial risks are not entirely precluded: in line with the Stern-Stiglitz

report (2017), a green public intervention is required to tackle both instabilities.

Our chances to achieve the Paris Agreement target stay, at most, below 25%.

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Summary

1

Introduction Research program

2

Gemmes research programme

3

Gemmes: the model Basics

4

Introduction Research program

5

Related Literature

6

Modeling set-up The macroeconomic core The climate module

7

Target achievements

8

Modeling uncertainty

9

Climate prospective Scope of analysis Scenario analysis

10 Concluding remarks

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Related Literature

The Integrated Assessment Modeling (IAM) approach A workhorse model: the Dynamic Integrated Climate Economy (DICE) model of Nord- haus in a seminal series of papers (1993, 2013, 2014, 2016)

The Ramsey-Kass-Coopmans’ approach as a core macroeconomic model A climate feedback loop with a damage function A carbon price instrument to shape the energy shift

Various extensions of the climate-economic interactions

Endogenous technological progress (Moyer, 2014) Allocation of climate damages (Dietz and Stern, 2015) Finance and green policies (Dafermos, 2016)

This paper: assesses financial instability (Keen, 1995 and Grasselli et al., 2012)

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Related Literature

The approaches of Goodwin (1967) and Keen (1995)

Endogenous business cycles as in Goodwin (1967) Dynamic interaction of deep macroeconomic behaviors ◮ Lotka-Volterra relationship linking the employment rate to the wage share ◮ Short-term Phillips curve (Mankiw, 2010 or Krugman, 2014) ◮ Investment as a function of profit share ◮ Dynamics of corporates’ private debt Multiplicity of long-term equilibria ◮ A Solovian steady-state ◮ A bad attractor leading to a breakdown in the long-run ◮ Asymptotic local stability becomes key

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Related Literature

Another view on public policy λ: employment rate ; ω : wage bill/GDP ; d: debt/GDP Source: Grasselli and Costa-Lima (2012)

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Summary

1

Introduction Research program

2

Gemmes research programme

3

Gemmes: the model Basics

4

Introduction Research program

5

Related Literature

6

Modeling set-up The macroeconomic core The climate module

7

Target achievements

8

Modeling uncertainty

9

Climate prospective Scope of analysis Scenario analysis

10 Concluding remarks

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Modeling set-up

Key modeling highlights Bridging climate and a global monetary economy

1. The macroeconomic core

◮ Non-neutrality of money ◮ Severe breakdowns do not appear as “black swan events” ◮ Emissions, carbon price and abatement technology (Nordhaus, 2016) ◮ Price dynamics under imperfect competition (Grasselli et al., 2014) ◮ Sigmoïd pattern of the global workforce (UN population scenarios, 2015) ◮ Dividends payments

2. The DICE climate feedback loop of Nordhaus (2016) refined with

◮ More convex damage functions (Weitzman, 2011) ◮ Allocation of environmental damages between output and capital (Dietz et al., 2015)

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Outlines

1 Introduction 2 Gemmes research programme 3 Gemmes: the model 4 Introduction 5 Related Literature 6 Modeling set-up The macroeconomic core The climate module 7 Target achievements 8 Modeling uncertainty 9 Climate prospective 10 Concluding remarks

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Modeling set-up

Stock-flow consistency

Households Productive Sector Banks Sum Balance Sheet Capital stock pK pK Deposits Mh Mc −M Loans −Lc Lc Equities E −Ef −Eb Sum (net worth) Xh Xf = 0 Xb = 0 X Transactions current capital Consumption −pC pC Investment pI −pI

Acc. memo [GDP]

[pY] Wages W −W Capital depr. −(δ + DK)pK (δ + DK)pK Carbon taxes pTf −pTf

Int. on loans

−rc Lc rc Lc Bank’s dividends Πb −Πb Productive sector’s dividends Πd −Πd

Int. on deposits

rM Mh rM Mc −rM M Column sum (balance) Sh Sc −pI + (δ + DK)pK Sb Flow of Funds Change in capital stock p ˙ K p ˙ K Change in deposits ˙ Mh ˙ Mc − ˙ M Change in loans − ˙ Lc ˙ Lc Column sum (savings) Sh Sc Sb Change in equities ˙ Ef −(Sc + ˙ pK) Change in bank equity ˙ Eb −Sb Change in net worth Sh + ˙ E ˙ pK + p ˙ K

Table: Balance sheet, transactions, and flow of funds in the economy.

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Modeling set-up – The macroeconomic core

Dynamics and behavioural relations

Short term Phillips curve:

˙ w w = φ(λ)

Dynamics of prices (Grasselli et al., 2014):

˙ p p = η(mω − 1)

Investment behavior:

I = κ(π)

Dynamics of private debt:

˙ D = I − Π − Πd

Taylor rule:

r = max {0, r ∗ + i + φ(i − i∗)}

Dynamics of capital:

˙ K = I − (δ + DK)K

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Modeling set-up – The macroeconomic core

Introducing climate change and public policies

Joint production process incorporating climate damages

Y 0 = min{K/ν; aL} Y = (1 − DY)

1 − A(pBS)
Y 0

Eind = σ

1 − n(A)
Y 0

Public policies and aggregate profit

Π = pY − wL − rD − pT(pC, Eind) − (δ + DK)pK,

Endogenous choice of the emission reduction rate in the productive sector

n = min pc pBS

1

θ−1

; 1

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Modeling set-up

Vulnerabilty toward climate change

Figure:

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Modeling set-up

Climate risks

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Outlines

1 Introduction 2 Gemmes research programme 3 Gemmes: the model 4 Introduction 5 Related Literature 6 Modeling set-up The macroeconomic core The climate module 7 Target achievements 8 Modeling uncertainty 9 Climate prospective 10 Concluding remarks

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Modeling set-up – The climate module

Physical processes overview

Figure: Climate-economy interaction diagram

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Modeling set-up – The climate module

CO2 accumulation

Figure: CO2 accumulation in a three-layer model

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Modeling set-up – The climate module

Climate damage as a percentage of real GDP

Figure: Shape of various damage functions

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Summary

1

Introduction Research program

2

Gemmes research programme

3

Gemmes: the model Basics

4

Introduction Research program

5

Related Literature

6

Modeling set-up The macroeconomic core The climate module

7

Target achievements

8

Modeling uncertainty

9

Climate prospective Scope of analysis Scenario analysis

10 Concluding remarks

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Target achievements –

Which temperature targets can be reached?

Nordhaus (2016) following a recalibration of the climate module of DICE:1

The study confirms past estimates of likely rapid climate change over the next century if there are not major climate-change policies. It suggests that it will be extremely difficult to achieve the 2◦C target of international agreements even if am- bitious policies are introduced in the near term. The required carbon price needed to achieve current targets has risen over time as policies have been delayed.

Illustration:

Figure: Temperature increase in 2100 as a function of the climate sensitivity whenever zero net emission is reached in 2016 (blue line) or 2018 (red line).

1http://cowles.yale.edu/sites/default/files/files/pub/d20/d2057.pdf

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Target achievements –

Which shape for the carbon price (1/2)?

A generalized logistic path:

˙ pC pC = βpC

1 − γpC

pC pBS

,

with, βpC > 0, and 1 ≥ γpC ≥ −1.

Set of carbon price paths considered

Figure: The carbon price functionals.

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Target achievements –

Which shape for the carbon price (2/2)?

Figure: Heatmap in 2100 depending on the carbon price path in the Type 3 scenario (exponential case in the white line).

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Summary

1

Introduction Research program

2

Gemmes research programme

3

Gemmes: the model Basics

4

Introduction Research program

5

Related Literature

6

Modeling set-up The macroeconomic core The climate module

7

Target achievements

8

Modeling uncertainty

9

Climate prospective Scope of analysis Scenario analysis

10 Concluding remarks

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Modeling uncertainty

Uncertainty parameters Uncertainty is divided into two classes:

1. On the macroeconomic parameters

◮ α, that drives the labor productivity growth, and consequently, the long-term growth.

2. On the climate module parameters

◮ S, the climate sensitivity parameter. ◮ Cup, the biosphere and upper ocean’s ultimate load capacity of absorption CO2. ◮ In all our simulations, we test various damage functions between Nordhaus’s and the

Dietz and Stern’s.

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Modeling uncertainty

Shapes of the probability density functions

−0.04 −0.02 0.00 0.02 0.04 0.06 0.08 5 15 25 35 α Normal density µ = 0.0206 σ = 0.0112 2 4 6 8 0.0 0.2 0.4 S log−Normal density µ = 1.107 σ = 0.264 200 400 600 800 1000 0.000 0.002 0.004 Cup log−Normal density µ = 5.8855763 σ = 0.2512867

Figure: Probability density function of the parameters

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Summary

1

Introduction Research program

2

Gemmes research programme

3

Gemmes: the model Basics

4

Introduction Research program

5

Related Literature

6

Modeling set-up The macroeconomic core The climate module

7

Target achievements

8

Modeling uncertainty

9

Climate prospective Scope of analysis Scenario analysis

10 Concluding remarks

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Outlines

1 Introduction 2 Gemmes research programme 3 Gemmes: the model 4 Introduction 5 Related Literature 6 Modeling set-up 7 Target achievements 8 Modeling uncertainty 9 Climate prospective Scope of analysis Scenario analysis 10 Concluding remarks

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Climate prospective – Scope of analysis

Design of the prospective scenarios

Calibration over a reconstructed world economy (approx. 85% of the “real” world)

with a panel of 36 countries over the period 2000 – 2015 (dataset from World Bank, Penn University, the Bureau of Economic Analysis and the United Nations).

Prospective analysis through 4 classes of scenarios:2

Scenario No climate Baseline Low policy High policy Carbon tax (Weak pC)

Yes
Carbon tax (High pC)
Yes

Yes

Abat. subsidy (25%)
Yes

Damage Type

Stern

Stern Stern Table: Scenarios considered for the prospective analysis

Where the public policies are

1. Weak pC represents non-constraining carbon price starting at approx. 2 in 2016 and

growing at a 2% rate per year

2. High pC represents a carbon price at 80 in 2020 and 100 in 2030
3. A x% of abatement subsidy is equivalent to reducing abatements costs by x%

2The scenarios listed in the presentation are drawn from a broader range assessed in this study.

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Outlines

1 Introduction 2 Gemmes research programme 3 Gemmes: the model 4 Introduction 5 Related Literature 6 Modeling set-up 7 Target achievements 8 Modeling uncertainty 9 Climate prospective Scope of analysis Scenario analysis 10 Concluding remarks

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Climate prospective – Scenario analysis

The no-warming scenario

Figure: [0.25; 0.75] probability interval of the No climate scenario with a damage-to-capital ratio of 0% in black shades (medians in solid lines)

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Climate prospective – Scenario analysis

Policy scenarios – Trajectories and narratives

Figure: [0.25; 0.75] probability interval of the Baseline, Low policy and High policy scenarios with a damage-to-capital ratio of 0% in red, purple and blue shades (medians in solid lines)

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Climate prospective – Scenario analysis

Policy scenarios – Staying under the temperature and debt thresholds

Figure: Probability density function of the temperature anomaly ratio in 2050 (dark blue) and 2100 (light blue).

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Summary

1

Introduction Research program

2

Gemmes research programme

3

Gemmes: the model Basics

4

Introduction Research program

5

Related Literature

6

Modeling set-up The macroeconomic core The climate module

7

Target achievements

8

Modeling uncertainty

9

Climate prospective Scope of analysis Scenario analysis

10 Concluding remarks

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Concluding remarks

Main results

Development of a stock-flow consistent monetary integrated assessment model

calibrated at the world level

Inaction would most likely lead to a global collapse of the world economic system A limited action (carbon price only) allows to avoid most climate damages but re-

mains insufficient to preclude financial instability

A wider public involvement (carbon price and subsidies) is more likely to meet both

bjectives, in line with the recommendations of the Stern-Stiglitz report (2017)

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Concluding remarks

Areas for further research

Refine the economic modeling (role of technical progress, explicit demand side) Distinguish between the various vintages of capital Build the spacial dimension of the energy shift Design additional green tools to tackle both instabilities

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#WorldInCommon

AGENCE FRANÇAISE DE DÉVELOPPEMENT | FRENCH DEVELOPMENT AGENCY

Thanks for your attention.