SUSTRUS Developing a sustainability model for Russia

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SUSTRUSDeveloping a sustainability model for
Russia

• Christophe Heyndrickx (TML)
• Victoria Alexeeva-Talebi (ZEW)
• Natalia Tourdyeva (CEFIR)

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Overview

• Introducing the project
• Model characteristics
• Applications
• Conclusions

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Overview

• Introducing the project
• Model characteristics
• Applications
• Conclusions

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The SUSTRUS project

• Goal Development of a tool for sustainability
  assessment in Russia
• Partners CEFIR, Ural State University, Voronezh
  State University, Far Eastern Centre for economic
  development, Institute for the Economy in
  Transition, ZEW
• Time funding 3 years, EU DG Research grant
• Expected result (s)
• Development of a regional computable general
  equilibrium model that can be used for integrated
  analysis of current sustainability policy in
  Russia
• Database on economy, society and environment of
  Russia
• Results of current policy analyzed with the model

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Workplan
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Sustainability ?

• EU Sustainable development framework
• Environmental protection
• Social equity and cohesion
• Economic prosperity
• Meeting international responsibilities
• Russian context
• Unfavorable demographic situation and low labour
  mobility
• Agglomeration around large cities (Moskow,
  Sint-Petersburg, Ekaterinburg,..)
• Medium to highly educated labour force
• Large areas in very cold regions (economic
  coldness)
• Misallocated investments in infrastructure and
  economic development under Soviet regime
• Abundant natural resources (gas, crude oil,
  timber)
• Dependent on export of resources and primary
  energy
• Polluted areas and health problems in some
  regions
• Increasing inequality in income and regional
  development
• Poor institutional development
• Large informal economy

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• In general, there is no specific model, which
  fits all requirements for comprehensive SIA, but
  rather a package of models or methods depending
  on the policy measure or issue to be assessed and
  the availability of data (Böhringer C., Löschel,
  2006)

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Overview

• Introducing the project
• Model characteristics
• Applications
• Conclusions

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SUSTRUS (1)

• Formulation based on our experience with regional
  economic models for Belgium (ISEEM) and the
  Netherlands (RAEM)
• Some elements were removed, others were extended
  to fit with the Russian context
• Input and experience with other models (GEM-E-3,
  EPPA, WorldScan)
• Consumers three household types with LES-type
  utility function (low, middle and high incomes)
• Producers perfect or imperfect competition
• Factor market nested CES functions
• Foreign sector small open economy assumption,
  Armington in imports, CET in exports
• Region 7 regions (Russian federal level),
  intraregional trade in goods and services
• Transport and trade trade involves consumption
  of transport (margins) produced by a
  representative transport and trade sector, we do
  not use the iceberg transport cost assumption

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SUSTRUS (2)

• Government taxation and subsidies, depending on
  available data income tax, VAT, corporate income
  tax, import tax, export subsidies, product
  tax/subsidy, etc Federal and regional level
  government
• Investment representative investment agent with
  Cobb-Douglas utility
• Model dynamics recursive dynamic structure with
  accumulation of capital through investment
• Closure (s)
• - labour supply fixed on short term, mobile
  between sectors
• - flexible exchange rate / fixed exchange
  rate
• - regional capital fixed on short term
• - investment savings
• - GDP deflator used as numeraire
• - Government consumption / savings fixed

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SUSTRUS structure
ENVIRONMENTAL MODULE
TRADE MODULE
SOCIO-ECONOMIC MODULE
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Production
KLEM
KLE
MAT
KL
E
K
L
Elec
Nonelec
Coal
Petr
Gas
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Supply
XD
Sigma T
XXD
EXP
Sigma A1
Reg1
Reg2
Reg..
EU
EROW
Eu1
Eu2
ROW1
ROW2
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Sales
X
Sigma T
XDD
IMP
Sigma A1
Reg1
Reg2
Reg..
EU
EROW
Eu1
Eu2
ROW1
ROW2
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Production commodities
Agriculture, ea Machinery
Fishing Electric and optics
Coal Transport Eq.
Gas Other manufacturing
Oil Electricity, gas and water (distribution)
Mining (non-energy) Electricity
Food, beverage and tobacco Construction
Textiles Wholesale trade
Leather Hotels and restaurants
Wood Communication
PulpPaper Transport
Cokes, petroleum refineries Financial intermediation
Chemicals Government service and defence
Rubber and plastics Real estate, renting and business activities
Non-metallic products Education
Basic metals Health and social work
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Socio-economic module

• Optional monopolistic competition of
  Dixit-Stiglitz type, based on concentration
  indices (Herfindahl index) in Guriev S. (2004)
• Unemployment modelling via simplified wage curve
  for each skill type
• Different household types modelled, based on
  CEFIR data on
• Income by household type (low, middle and high
  income)
• Source of income (capital, labour by skill type,
  transfers)
• Consumption data by household type
• Production sector has demand for each skill type
  ? endogenous labour price by skill
• Labour demand by skill type is based on ILO data

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Environmental module

• Built in as an endogenous module within SUSTRUS,
  based on the GEM-E-3 modelling approach.
• ZEW translated the environmental module of
  GEM-E-3 to fit within our framework
• Emissions of CO2 and other greenhouse gasses and
  the most important non-greenhouse gasses NOx,
  Sox, PM and VOC on regional level
• Elements modelled
• Emissions (combustion) by fuel type and sector
• Abatement (end-of-pipe) by sector
• ETS system with caps on national and regional
  level
• Recursive dynamics within the emissions module
• Grandfathering of emissions / hot air / other
  constraints

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International module

• Armington and CET functions for disaggregation of
  imports/exports by international destination
• EU countries and RoW countries are grouped
• Full disaggregation
• ? Middle East, Africa, South America, North
  America, West Europe, East Europe, Scandinavia,
  Baltics, South Europe, Rest Europe, Rest Asia,
  FSU, China, Japan, Ukraine, RoW
• FDI is treated within the recursive dynamic
  structure of the model

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Overview

• Introducing the project
• Model characteristics
• Applications
• Conclusions

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Possible applications
ENV
ECO
Taxation redistribution Innovation
Energy Tax Emission tax Energy efficiency Abatemen
t
Trade infrastructure Trade openness Energy prices
TRADE
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Stabilization of CO2 emissions

• Sensitivity analysis of the SUSTRUS model to the
  introduction of a general cap on CO2 emissions
• Introduce a cap on emissions equal to the 2006
  level
• Run the model for 20 time periods
• Economic growth increases the demand for emission
  permits gradually over time
• We assume that demand for emission permits grows
  with 2 in each year
• Test both model dynamics and environmental module

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Main indicators - country
    2007 2013 2018 2023 2026
Welfare Mil.Rubles (e4) -8.62 -75.04 -157.44 -281.01 -385.01
  Change -0.05 -0.30 -0.49 -0.69 -0.82
Tax Revenue Mil.Rubles (e4) 7.62 83.23 198.10 381.13 535.18
  Change 0.08 0.61 1.15 1.73 2.10
GDP Mil.Rubles (e4) -17.87 -151.52 -309.83 -538.24 -725.57
  Change -0.07 -0.43 -0.68 -0.93 -1.09
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GDP regional level
GDP Region 2007 2013 2018 2023 2026
Change Central -0.05 -0.26 -0.36 -0.44 -0.49
  NorthEast -0.07 -0.44 -0.70 -0.97 -1.14
  SouthWest -0.07 -0.33 -0.42 -0.45 -0.46
  Volga -0.07 -0.46 -0.78 -1.12 -1.34
  Urals -0.08 -0.64 -1.11 -1.57 -1.83
  Siberia -0.10 -0.66 -1.13 -1.62 -1.93
  FarEast -0.07 -0.43 -0.66 -0.86 -0.99
mil. Rubles (e4) Central -4.76 -32.89 -58.08 -90.70 -117.52
  NorthEast -1.80 -15.12 -31.11 -54.70 -74.33
  SouthWest -1.24 -8.39 -13.77 -18.90 -22.13
  Volga -3.01 -26.55 -56.91 -104.01 -144.37
  Urals -3.79 -39.41 -87.84 -158.16 -213.95
  Siberia -2.50 -23.16 -50.47 -92.24 -127.31
  FarEast -0.76 -6.00 -11.66 -19.53 -25.96
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SWF-regional level
  2007 2013 2018 2023 2026
Central -2.69 -22.78 -47.86 -87.13 -121.51
NorthEast -1.36 -12.16 -26.01 -46.93 -64.44
SouthWest -0.69 -5.13 -9.47 -15.04 -19.40
Volga -1.54 -13.85 -29.97 -55.00 -76.41
Urals -1.09 -10.35 -21.77 -37.27 -49.10
Siberia -0.93 -8.16 -17.18 -30.67 -41.97
FarEast -0.33 -2.61 -5.19 -8.97 -12.18
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CO2 emission abatement
CO2 (Mtonnes) 2007 2013 2018 2023 2026
Central -6 -47 -87 -134 -164
NorthEast -4 -26 -44 -64 -77
SouthWest -4 -23 -37 -52 -60
Volga -4 -32 -59 -89 -109
Urals -2 -19 -38 -60 -76
Siberia -4 -32 -56 -82 -99
FarEast -2 -11 -19 -27 -32
Total -25 -189 -341 -508 -616
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CO2 emissions by fuel
    2007 2013 2018 2023 2026
Change coal -2.35 -14.69 -23.34 -30.95 -35.11
  gas -2.12 -14.23 -23.39 -31.66 -36.22
  petrol -0.47 -3.64 -6.58 -9.73 -11.71
  total -2.00 -13.19 -21.53 -29.07 -33.24
Mtonnes coal -7.75 -54.66 -95.86 -140.33 -168.94
  gas -17.03 -128.54 -233.22 -348.62 -423.21
  petrol -0.66 -5.72 -11.43 -18.67 -23.84
  total -25.44 -188.93 -340.52 -507.63 -616.00
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Market price by good
Price () 2007 2013 2018 2023 2026
Gas -0.85 -5.31 -8.19 -10.38 -11.41
Coal -0.26 -1.47 -2.14 -2.54 -2.67
Trade -0.05 -0.47 -0.92 -1.46 -1.81
Oil -0.03 -0.25 -0.52 -0.90 -1.18
Petrol 0.05 0.36 0.66 1.01 1.24
Basic metal 0.05 0.48 0.98 1.61 2.05
Heating 0.09 0.81 1.65 2.72 3.47
Electricity 0.55 4.53 8.71 13.71 17.15
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Conclusions

• Preliminary results of simulation follow economic
  intuition
• Regions dependent on resource intensive sectors
  experience a decrease in GDP
• Emissions from gas and coal decrease relatively
  more than petrol emissions
• Emission permit system leads to higher energy
  efficiency
• Market price for electricity, heating and heavy
  manufacturing increase
• The results illustrate the relative difference
  between regional structure
• The SUSTRUS model is sufficiently broad to handle
  not only environmental issues, but also
  socio-economic and interregional or international
  issues consistently

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Thank youFor your attention