A 3-regional CGE-model for China

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A 3-regional CGE-model for China

• Development Research Centre, PRC

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Presentation Outline

• Introduction
• Economic part of the three-regional model
• Environmental part of the three-regional model
• Further Analysis

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Introduction

• The main goal
• To analyze environmental implications of
  Chinas WTO accession
• Geographic differentiation
• A single China-wide model
• A two regional model
• (GD-Guangdong and ROC-Rest of China)
• A multi-regional model

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• The three-regional model
• The three -region Chinese CGE model we employ in
  this study is an extension of the following
  models that had been used in Chinas WTO
  accession study
• the single region Chinese CGE model (Development
  Research Center, 1998)
• The two regional Chinese CGE model (Li and Zhai,
  2000,2002)
• Three regions
• GD (Guangdong), SX (Shanxi) and Rest of China
  (ROC)
• Why?

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• Introduce of the geographic differentiation into
  the model
• - to reflect the different impact on different
  regions of WTO accession in China according to
  different regional comparative advantage, etc.

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Shanxi Province
Guangdong Province
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The differentiation between GD and SX

• Location, Area
• Population
• Nature Resource
• Economic development
• GDP, Per capita GDP, Market openness, Industrial
  structure, International trade, etc.
• Infrastructure, FDI, Human resource,
  Institutions, etc.

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Some indicators for GDSX in 2003
SX SX GD GD China
Ratio to National level Ratio to National level China
Population (10000 persons) 3314 2.6 7954 6.2 129227
GDP(100 million RMB) 2457 2.1 13626 11.6 117252
Per capita GDP (RMB) 7435 81.7 17213 189.1 9101
Import Export (USD 10 000) 52 0.6 2892 34 8510
Export 37 0.8 1537 35.1 4382
Import 14 0.3 1355 32.8 4128
FDI(USD 10 000) 21361 0.4 782294 14.6 5350467

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Average
Low
High
GDP growth
Jilin?Xinjiang?Heilongjiang?Liaoning Beijing?Tianjing?Zhejiang?Shanghai?Guangdong?Fujiang?Hebei?Shandong?Hebei?Jiangsu
Shaanxi?Jiangxi?Hunan?Ninxia?Guizhou?Yunnan?Shanxi?Chongqing?Anhui?Hainan?Guangxi?Sichuan Xizang?Gansu?Inner Mongolia?Qinghai?Henan
High
Average
Per capita GDP
Low
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Guangdong Province

• Guangdong province locates in southern China,
  neighboring Hong Kong and Macao. As one of the
  largest economies in China,
• It accounts for 35 percent of national foreign
  trade in 2003.
• The development of Guangdong since 1978 and its
  economic structure could be a representation of
  Chinas coastal area.

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Shanxi Province

• Shanxi, locates on the middle part of North
  China.
• As the "Coal Warehouse of China", the output of
  coal in Shanxi ranks the first in China and
  accounts for nearly one-fourth of the country's
  total.
• According to the UNIDO technique classification,
  resource-based manufactured export account for
  61.94 of the total manufactured export in 2000.

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• Difference between 2 regional model and 3
  regional model
• - bilateral to triangular , etc.
• Some important issues in the model
• - data
• - environmental issues
• - new energy

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Economic part of the three-regional model

• Data-three regional SAM
• CGE-Model

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Data-three regional SAM

• Inter-regional trade
• Two separate trade regimes
• Different household groups

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Inter-regional trade

• In most countries, interregional trade is not
  covered by official statistics, which results in
  it having to be estimated by whoever has an
  interest in it (Pedro Ramos et al., 2003). In
  China, that is the case, too.
• With regional IO tables and Customs Statistics,
  we can get international trade, inflow (not incl.
  import) and outflow (not incl. export)

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Table 1 The main methods for estimating the interregional trade Table 1 The main methods for estimating the interregional trade Table 1 The main methods for estimating the interregional trade
TECHNIQUE USED FOR THEESTIMATION SOME MODELS
A POSTERIORI ?A PRIORI INDIRECT ESTIMATION INDIRECT ESTIMATION
A POSTERIORI ?A PRIORI Use of Gravitational model TIM, (Funck et al. 1975)
A POSTERIORI ?A PRIORI Use of Entropy Maximising Paradigm Batten (1983)
A POSTERIORI ?A PRIORI Pool-Approach of Leontief Leontief (1977) INTERREG (Martellato et al, 1996)
A POSTERIORI ?A PRIORI DIRECT ESTIMATION BASE ON REAL DATA DIRECT ESTIMATION BASE ON REAL DATA
A POSTERIORI ?A PRIORI Use of International trade flows EU-IRIO (Oosterhaven et al., 1995)
A POSTERIORI ?A PRIORI Use of Transport flows MRIO-HERP (Polenske 1980) Hewings, 1993 Kazumi H., 2000. INTERTIO, (Llano, 2000)
A POSTERIORI ?A PRIORI Use of surveys designed ad-hoc for producers and consumers. JAPAN IRIO TABLES (1960-70)
Source Carlos Llano Verduras, the estimation of the interregional trade in the context of an interregional input-output model for the Spanish economy, Source Carlos Llano Verduras, the estimation of the interregional trade in the context of an interregional input-output model for the Spanish economy, Source Carlos Llano Verduras, the estimation of the interregional trade in the context of an interregional input-output model for the Spanish economy,
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Inter-regional trade

• The main method used to estimate the
  inter-regional trade in this study
• Indirect Estimation--Use of Gravitational
  model
• We only estimation the inter-regional trade
  Matrix (33) for merchandise trade.
• For services trade we use the net outflow.

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Table 2 The schematic interregional trade matrix Table 2 The schematic interregional trade matrix Table 2 The schematic interregional trade matrix Table 2 The schematic interregional trade matrix Table 2 The schematic interregional trade matrix
Regions GD SX ROC Total
GD
SX
ROC
Total
Notes GD-Guangdong Province, SX-Shanxi Province, ROC-the Rest of China. Notes GD-Guangdong Province, SX-Shanxi Province, ROC-the Rest of China. Notes GD-Guangdong Province, SX-Shanxi Province, ROC-the Rest of China. Notes GD-Guangdong Province, SX-Shanxi Province, ROC-the Rest of China. Notes GD-Guangdong Province, SX-Shanxi Province, ROC-the Rest of China.
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• Gravity model

Where, suffix i refers to the origin, j
refers to the destination. Dj is the total demand
for a given commodity in region j Si is the
total supply in region i TDS is the total demand
(or total supply) for the three regions. GDP is
the regional economic size (share of GDP). OI is
the trade openness index. d is the distance
between the region i and j. a,ß ,? andd are
parameters.
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• first step To choose the parameters, we
  structure the following programming problem

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• Second step To balance the trade matrix, we use
  Cross Entropy Methods

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The verification of the result
sector ß sector ß sector ß sector ß
Automobile 0.632 Logging 3.813 Textile 11.202 Printing 15.498
corn 0.777 Leather 4.004 CoalMin 11.705 Instrumnt 15.754
Sawmills 0.923 OthManuf 4.217 OthAg 12.206 rice 16.215
Tobacco 1.467 Machinery 5.187 Beverage 12.797 ElecMach 16.792
NFerProd 1.48 Gas 5.611 FoodProc 12.818 Fishing 17.127
FerOreMin 1.952 wheat 5.651 OthCrop 13.478 SocActProd 23.217
Wool 2.239 Apparel 8.318 SpecEquip 13.5 BuildMat 25.566
Chemical 2.746 Quarrying 8.44 RefPet 13.844 GrainForage 37.231
MetalProd 2.763 Water 9.67 IronSteel 13.863 Medicine 61.694
Plastic 3.49 Forestry 9.771 Electron 14.293 Sugar 193.282
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(Continued)

• The statistic transportation yearbook provide the
  inter-regional transport data for coal.
• The correlation coefficient between the published
  trade matrix and estimated trade matrix is 0.82.

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Two separate trading regimes

• Two separate trading regimes
• Processing trade
• Ordinary trade
• In this SAM, both production and trade are
  divided between ordinary trade and processing
  trade.

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Different household groups

• In the SAM, all households are divided into 14
  groups, 7 groups of urban households and 7 groups
  of rural households.

Lowest
Low
Lower-middle
Middle
Upper-middle
High
Highest
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CGE-Model

• Model Dimension
• Production and Factor Markets
• Interregional and Foreign Trade
• Income Distribution and Demands
• Central and Regional Governments, and
  Extra-budget Public Sector
• Macro Closure
• Recursive Dynamics
• Data
• Parameters of the model

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Environmental part of the three-regional model

• Emission of Pollutant
• CO2,SO2,NMVOC,NOX,PM10, CH4 and N2O
• The impact on human health and other
  environmental end-points like crop damage and
  material damage
• Additional topic-Biomass

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• In the three regional CGE model, the total amount
  of a given polluting emission takes the following
  form

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where i is the sector index, j the consumed
product index, C intermediate consumption, XP
output, XA final consumption, the emission
volume associated with one unit consumption of
product j used by sector i the emission
volume associated with one unit production of
sector i. the emission volume associated
with one unit consumption of product j in final
consumption .
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Health benefit
Emission Change
Step 1 introduce of dispersion model
Estimate impacts on air pollution exposure
Step 2 introduce of dose-response function
Estimate impacts on mortality etc. health risk
end-points
Step 3 introduce of VSL (Value of a statistical
life)
Estimate units values of health risk end-points
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Biomass

• In China the biomass energy plays a very
  important role in the total energy consumption,
  especially in rural energy consumption and plays
  an important role in the discharge of GHG.
• While we consider only commercial energy sources
  both renewable and natural resources are
  explicitly treated. Traditional biomass fuels are
  ignored since national accounts and official
  input-output data do not include their value
  (Rana, 1999).

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• In China, the biomass also does not introduce
  into the official account
• How to Import the residential combustion of
  biomass to Chinas environmental CGE

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Import biomass to CGE

• What determines the choice of biomass energy
• Key issues of adding the biomass energy in the
  model
• The function for the biomass consumption

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What determines the choice of biomass energy
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The factors

• Cost
• Opportunity cost of collecting biomass and
  price of other energy
• Income
• Living custom etc.

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Key issues of adding the biomass energy in the
model

• Exogenous-simple
• Semi-exogenous
• Endogenous-complicated

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The function for the biomass consumption

• Demand
• -income
• Supply
• -the forest coverage rate and per cap output
  of grain

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Where, denote the forest coverage
rate and per cap output of grain respectively.
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• For the data of non-commercial biomass
  consumption in rural area, there is only
  ten-years-series data of non-commercial biomass
  consumption at national level. Maybe the data is
  too short for econometric analysis.
• Fortunately we have pooled data, non-commercial
  biomass consumption by province (31 provinces)
  and by years (1991, 1992, 1993, 1995, 1996, 1998,
  and 1999). So our empirical analysis is based on
  the pooled data.

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Notes Per capita annual biomass consumption in
national level, unit10-3tce/person.
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Semi-exogenous

• Link the biomass consumption function to the
  model
• -the income is the linkage

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Further Analysis

• To design scenarios of Chinas WTO accession
• To analyze environmental implications of Chinas
  WTO accession

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Thank you!