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Modeling on service demands: Industry and Transport Industry and Transport Osamu Akashi (NIES) The 15th AIM International Workshop 20 22, February 2010 @NIES Tsukuba Japan @NIES, Tsukuba, Japan Objective Macroeconomic model Macroeconomic

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Modeling on service demands: Industry and Transport Industry and Transport

Osamu Akashi (NIES)

The 15th AIM International Workshop 20‐22, February 2010 @NIES Tsukuba Japan @NIES, Tsukuba, Japan

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Macroeconomic model

Objective

Population GDP Sector-wise value added Socio-economic macro frame model

Macroeconomic model

Steel production and trade model Cement production model Transportation demand model energy service demand model Agricultural trade model Waste generation model

Service demand model

Fluorocarbon emission model Crude steel production Cement production Value added

  • f secondary

industry Transportation volume Energy service demand (residential) Agricultural production Waste generation Emission of fluorocarbon Energy service demand (commercial) Iron and steel sector Cement sector Other industries sector Transportation sector Residential sector Commercial sector Agriculture sector Waste management sector Fluorocarbon emission sector Technology bottom-up model Technology b tt d l Primary energy Technology database Energy database Electricity demand

Initial cost Efficiency lifetime Maximum

bottom-up model （power generation sector） y gy production Endogenous gy Technology bottom-up model （energy mining sector）

Energy price Emission factor lifetime diffusion rate

Exogenous GHG reduction Cost Model Endogenous variable Database

Technology bottom-up model

Exogenous variable

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Methodology

Macroeconomic model ・Socio‐economic macro frame model

  • GDP
  • Value-added by sector

Exogenous scenario ・population Service demand models ・Steel production and trade model ・ Cement production model ・Transportation demand model

  • Steel production
  • Cement production
  • Cement production
  • Transportation volume

To technology bottom up model

3

To technology bottom-up model

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S i i f d l Socio‐economic macro frame model

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Socio‐economic macro frame model

  • To estimate macroeconomic variables in each region
  • Supply‐side macro economic model, which estimates

GDP from fixed capital stock and labor force

  • Sector‐wise value added are estimated based on the

GDP

  • Econometric approach
  • Historical data (1971

2005) are used for calibration

  • Historical data (1971 – 2005) are used for calibration
  • Inputs: Population
  • Outputs: GDP, final consumption, gross capital

formation, sector‐wise value added in US$ at constant 2000 price

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Model structure

Gross capital formation Fixed Capital Stock Ki t Population ages 15-64 formation Ii,t

i,t

ages 15 64 POP1564i,t Time trend Labor force Li,t Time trend TIMEt Share of agriculture, I d t d i Gross domestic product GDPi,t Exogenous Industry and service sector RVAi,s,t Endogenous variable Exogenous variable Final Value added of agriculture, industry Estimation equation variable i: region consumption CPi,t g , y and service sector VAi,s,t Definitional equation i: region t: year s: sector

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Estimated GDP

8 10 MEX 80 100 MEX

World

100 This study

Japan

4 6 000US$ at M 40 60 000US$ at M 80 90 100 This study SRES‐A1 (IPCC,2000) SRES‐A2 (IPCC,2000) ( ) 2 4 trillion 20 20 40 trillion 20 60 70 SRES‐B1 (IPCC,2000) SRES‐B2 (IPCC,2000) GEO4‐MK (UNEP,2007) 2000 2010 2020 2030 2000 2010 2020 2030 30 40 50 GEO4‐PL (UNEP,2007) GEO4‐SC (UNEP,2007) GEO4‐ST(UNEP 2007) 14 16 X

China

6 X

I di

10 20 GEO4 ST (UNEP,2007) WEO07 (IEA,2007) IEO08 (EIA,2008) 8 10 12 14 0US$ at MEX

China

3 4 5 0US$ at MEX

India

2000 2020 GEP07 (WB,2007) GS (Wilson,2003) PWC (Hawksworth,2006) 2 4 6 8 trillion 2000 1 2 3 trillion 2000 2 2000 2010 2020 2030 2000 2010 2020 2030

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St l d ti d t d d l Steel production and trade model

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Steel production and trade model

  • To estimate steel production in each region
  • Partial equilibrium model, which considers demand

and supply balance at domestic and international steel market

  • Econometric approach

pp

  • Historical data (1971 – 2005) are used for calibration
  • Inputs: Population GDP Industrial value added
  • Inputs: Population, GDP, Industrial value added
  • Outputs: Production, Consumption, Export, Import

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Model structure

International market

i i i i

Export Import =

∑ ∑

Exporti Importi InternationalPrice Domestic market at region i

i i i i

Consumption Production Export Import = − +

( ) ( ) ( )

, ,

i consumption i i i Production i

Consumption f Population GDP Production f DomesticPrice InternationalPrice E f P d i D i P i I i lP i = =

( )

, ,

i export i i

Export f Production DomesticPrice InternationalPrice Imp =

( )

, ,

i import i i

  • rt

f Consumption DomesticPrice InternationalPrice =

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Estimated steel production

140 160 2000 2500

World Japan

80 100 120 Mton 1000 1500 2000 Mton 2000 2500This study Od (Od 2007) 20 40 60 500 1000 1500 2000Oda (Oda,2007) SAGE (DOE,2003) Price‐A1 (Price,2006) 350 700 2000 2010 2020 2030 2000 2010 2020 2030

China I di

500 1000Price A1 (Price,2006) Price‐B2 (Price,2006) Hidalgo (Hidalgo,2003) 200 250 300

  • n

400 500 600

  • n

China India

2000 2010 2020 2030 DeBeer(de Beer,2003) 50 100 150 Mto 100 200 300 Mto 50 2000 2010 2020 2030 100 2000 2010 2020 2030

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C t d ti d l Cement production model

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Cement production model

  • To estimate cement production in each region
  • Statistical model
  • Statistical model
  • Historical data (1971 – 2005) are used for calibration

I t P l ti GDP

  • Inputs: Population, GDP
  • Outputs: Production

Exogenous variable GDP per capita GDP_P Production per capita PRD_P Estimation Endogenous variable Production Population POP Estimation equation Definitional equation

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PRD equation

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Estimated cement production

6000 7000 120 140

World Japan

3000 4000 5000 Mton 60 80 100 Mton 6000 7000 This study SAGE (DOE,2003) 1000 2000 3000 20 40 60 3000 4000 5000 Price‐A1 (Price,2003) Price‐B2 (Price,2003) SusCem A1 600 3000 2000 2010 2020 2030 2000 2010 2020 2030

China I di

1000 2000 3000 SusCem‐A1 SusCem‐A2 (Humphreys,2003) SusCem‐B1 (Humphreys,2003) 300 400 500 ton 1500 2000 2500 ton

China India

2000 2020 SusCem‐B2 (Humphreys,2003) Szabo (Szabo,2003) 100 200 300 Mt 500 1000 1500 Mt 2000 2010 2020 2030 2000 2010 2020 2030

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T t ti d d d l Transportation demand model

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Transportation demand model

  • To estimate both passenger and freight

transportation volume transportation volume

  • Statistical model
  • Inputs: Population, GDP
  • Outputs:

p Passenger transportation volume by mode ( Car, Bus, Rail, Domestic air, International air) in passenger‐ km, , , ) p g , Freight transportation volume by mode ( truck, rail, ship) in ton‐km p)

  • Historical data (1971 – 2005) are used for calibration

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Passenger transportation model

GDP per capita GDPPi,t Total transportation volume per capita PKTOTP PKTOTPi,t Population POPi,t Total transportation volume PKTOTi,t Modal share Transportation volume

  • f each mode

PK SHm,i,t PKm,i,t Endogenous i bl Exogenous i bl Estimation ti Definitional ti i: region t: year

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variable variable equation equation t: year m: mode

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Freight transportation model

GDP per capita GDPP GDP GDP Land transportation Ship transportation Total land trans. GDPPi,t GDPi,t volume per capita TKTOTPi,t Population POP Total land trans. volume TKTOTi,t POPi,t

i,t

  • Trans. volume

f h d Modal share SHm,i,t

  • Trans. volume

f h d

  • f each mode

TKm,i,t E d E E ti ti D fi iti l i: region

  • f each mode

TKm,i,t

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Endogenous variable Exogenous variable Estimation equation Definitional equation i: region t: year m: mode

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Passenger transportation by car

1.2 1.4 =1) 1.4 1.6 1.8 =1)

World Japan

0.6 0.8 1.0 ndex( 2005= 0.8 1.0 1.2 . ndex( 2005= 0 0 0.2 0.4 I 0 0 0.2 0.4 0.6 I 20 40 This study 4.0 4.5 6.0 0.0 2000 2010 2020 2030 0.0 2000 2010 2020 2030

Chi

20 2000 2010 2020 2030 IEA (Fulton,2004) MLIT (MILT,2008) 2.5 3.0 3.5 4.0 ex( 2005=1) 3 0 4.0 5.0 x( 2005=1)

China India

0 5 1.0 1.5 2.0 Inde 1.0 2.0 3.0 Inde 0.0 0.5 2000 2010 2020 2030 0.0 2000 2010 2020 2030

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Freight transportation by truck

1.2 1.4 =1) 2.0 2.5 =1)

World Japan

0.6 0.8 1.0 ndex (2005= 1 0 1.5 ndex (2005= 0 0 0.2 0.4 In 0 0 0.5 1.0 In 20 40 This study 3 0 3.5 4.0 4.5 0.0 2000 2010 2020 2030 0.0 2000 2010 2020 2030

China India

20 2000 2010 2020 2030 IEA (Fulton,2004) MLIT (MILT,2008) 2.0 2.5 3.0 ex (2005=1) 2.5 3.0 3.5 .0 ex (2005=1)

C a India

0.5 1.0 1.5 Inde 0 5 1.0 1.5 2.0 Inde 0.0 2000 2010 2020 2030 0.0 0.5 2000 2010 2020 2030

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Summary

GDP Annual change rate are estimated as follows

  • GDP:

World(3.2%), China(7.3%), India(7.0%), Japan(1.3%)

  • Steel production:

World(2.0%), China(2.0%), India(8.3%), Japan(‐0.1%)

  • Cement production:

World(1.9%), China(0.7%), India(5.6%), Japan(‐0.4%)

  • Pass. transport by car:

World(2.0%), China(6.8%), India(5.5%), Japan(0.2%)

  • Freight transport by truck:

World(2.7%), China(5.8%), India(3.4%), Japan(0.1%)

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