a 3-regional cge-model for china

A 3-regional CGE-model for China

Development Research Centre, PRC

Development Research Center, The State Council, PRC

Presentation Outline

Introduction

Economic part of the three-regional model

Environmental part of the three-regional model

Further Analysis


Introduction

The main goal: To analyze environmental implications of Chin

a’s WTO accession Geographic differentiation: A single China-wide model A two regional model (GD-Guangdong and ROC-Rest of China)

A multi-regional model


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 China’s 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?


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.


Shanxi Province

GuangdongProvince


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.

……


Some indicators for GD&SX in 2003SX GD

ChinaRatio to National

level

Ratio to National

level

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


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、 Sich

uan

Xizang、 Gansu、 Inner Mongolia、 Qinghai、 Henan

Per capita GDP

GDP growth HighLowAverage

High

Low

Average


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 China’s coastal area.


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.


Difference between 2 regional model and 3 regional model

- “bilateral” to “triangular” , etc. Some important issues in the model

- data

- environmental issues

- “new” energy


Economic part of the three-regional model

Data-three regional SAM

CGE-Model


Data-three regional SAM

Inter-regional trade

Two separate trade regimes

Different household groups



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)


Table 1: The main methods for estimating the interregional trade

TECHNIQUE USED FOR THEESTIMATION

SOME MODELS

A P

OS

TE

RIO

RI →

A P

RIO

RI

INDIRECT ESTIMATION

Use of Gravitational model TIM, (Funck et al. 1975)

Use of Entropy Maximising Paradigm Batten (1983)

Pool-Approach of LeontiefLeontief (1977)INTERREG (Martellato et al, 1996)

DIRECT ESTIMATION BASE ON REAL DATA

Use of International trade flows EU-IRIO (Oosterhaven et al., 1995)

Use of Transport flows

MRIO-HERP (Polenske 1980);Hewings, 1993; Kazumi H., 2000.INTERTIO, (Llano, 2000)

Use of surveys designed ad-hoc forproducers 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,



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 (3×3) for merchandise trade.

For services trade we use the net outflow.


12T 13T 1OF

21T 23T 2OF

31T 32T3OF

1IF2IF

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.

3IF


Gravity model

d

OIOIGDPGDP

TDS

SDT jijiij

ij

2121

Where, suffix i refers to the origin, j refers to the destination. Dj i

s the total demand for a given commodity in region j; Si is the tot

al 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. α,β ,γ andδ are parameters.


first step :To choose the parameters, we structure the following programming problem :

0 0

)(

..

min

,

2

2121

ROCROC

ij

j iij

ROC

ROCROCROC

jiij

jijiij

ij

jj

iij

OFIFT

OFIFOUTPUT

OFIFOI

OFTd

OIOIGDPGDP

TDS

SDT

ts

IFTtion destina


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

0

,

,

..

min0

0

ij

ijij

jiij

i j ij

ij

j

ij

T

"GD","SX"jIFT

"GD","SX"iOFT

ts

T

TLN

OF

T entropy


sector β sector β sector β sector βAutomobile 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

The verification of the result


(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.


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.


Different household groups

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

LowestLowLower-middleMiddleUpper-middleHighHighest


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


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


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

j

jji

iii j

jiji XAXPCE ,,

I

Emission with

intermediate consumption

III

Emission with

final consumption

II

Emission with

sectoral production


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 .

ij

i

j


Health benefit

Step 1: introduce of dispersion model

Estimate impacts on air pollution exposure

Step 2: introduce of dose-response function

Step 3: introduce of VSL (Value of a statistical life)

Estimate impacts on mortality etc. health risk end-points

Estimate units values of health risk end-points

Emission Change


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).


In China, the biomass also does not introduce into the official account

How to Import the residential combustion of biomass to China’s environmental CGE


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


What determines the choice of biomass energy


Agricultural ModernizationDevelopment

Township EnterprisesDevelopment

Labor Transfer From Agriculture To Other Industries etc.

The Increase income Of Peasants

High Quality of

Living Standard

Transition ofEnergy Consumption

Development of large mines and

power generation etc.

Construction and Opening-up of energy market

Decrease of the biomass energy consumption

Substitution

Energy ladder

Figure 2: The transition of energy consumption


The factors

Cost

Opportunity cost of collecting biomass and price of other energy

Income

Living custom etc.


Key issues of adding the biomass energy in the model

“Exogenous”-simple

“Semi-exogenous”

“Endogenous”-complicated


The function for the biomass consumption

Demand

-income

Supply

-the forest coverage rate and per cap output of grain


Where, denote the forest coverage rate and per cap output of grain respectively.

itittittitttit zzyq 2211ln

1z 2z


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.


Table 2 Partial empirical result for non-commerce biomass consumption in rural

area

1991 1992 1993 1995 1996 1998 1999

I ntercept - - - - - - -

-203. 6522 -188. 8393 -136. 5411 -186. 4200 -84. 8028 -83. 1575 -115. 7410 Ln( I NC)

(Per net i ncome i n rural area) ( -3. 646318) ( -4. 350736) ( -3. 318059) ( -3. 654203) ( -3. 010487) ( -3. 356177) ( -3. 687193)

250. 0117 225. 4915 179. 9735 254. 9298 126. 5163 127. 6774 166. 3154 l n(GRAI NP)

(Per cap output of grai n) (4. 358807) (4. 996974) (4. 094587) (4. 331719) (3. 827585) (4. 408217) (4. 412811)

4. 7703* 6. 2152 4. 8507 4. 3929* 3. 6836 3. 2955 2. 9507* FCR

(Forest coverage rate) (2. 776916) (4. 448686) (3. 041686) (2. 161174) (3. 130782) (3. 267888) (2. 150377)

R2 0. 49070 0. 61935 0. 47488 0. 51589 0. 47540 0. 51104 0. 45200

Adj usted R2 0. 44642 0. 58625 0. 43287 0. 46979 0. 43343 0. 47343 0. 41141

D. W. 1. 56799 1. 53491 1. 24243 1. 61724 1. 84065 1. 42560 1. 62037

Notes: 1.All the results are derived from the estimation by Eviews

3.1.

2.* Significant at the level of 5%.


per capita annual

biomass consumption*

Income Elasticity of

biomass consumption

1991 -203.7 295.1 -0.69

1992 -188.8 250.8 -0.75

1993 -136.5 265.5 -0.51

1995 -186.4 273.9 -0.68

1996 -84.8 220.7 -0.38

1998 -83.2 224.9 -0.37

1999 -115.7 220.1 -0.53

Average -0.56

Notes: * Per capita annual biomass consumption in national level, unit:10-3tce/person.


“Semi-exogenous”

Link the biomass consumption function to the model

-the income is the linkage


Further Analysis

To design scenarios of China’s WTO accession

To analyze environmental implications of Chin

a’s WTO accession

a 3-regional cge-model for china

Documents

state council

prcdevelopment research

regional cgemodel

regional model bilateral

regional modelthe

regional modeldata

regional modelenvironmental

regional model gdguangdong