RESEARCH AND DEMONSTRATION OF AGRICULTURAL

POLICY SIMULATION BASED ON CGE MODEL

Zhigang Li, Quan Qi

College of Information Science and Technology, Shihezi University, Shihezi 832000, China

Yan Liu, Dongqin Zhu

College of Information Science and Technology, Shihezi University, Shihezi 832000, China

Keywords: Agricultural Policy Simulation, Computable General Equilibrium Model (CGE), DSS, Integrated.

Abstract: In the event that lacks of faced to policy simulation platform, we presented a simulation platform which

makes use of computer technique in this paper. On this platform, we integrated CGE model, DSS, data

warehouse, data convert and other components together, established a prototype of policy simulation

platform system, and simulated the agriculture subsidizes policy through the scene analysis method. The

analytic results demonstrated the feasibility and functionality of the simulation platform prototype system.

1 INTRODUCTION

Policy simulation is a virtual policy test aimed at

policy problems based on mathematical modeling,

computer simulation and computer technology.

Facing with various social and economic problems,

it is necessary to test them on virtual economic

system, which means to analyze its impact through

the simulation of economic policy on many aspects

of society, assess the effects of policies and improve

the science of policy establishment (Xueming Liu,

2004). The development of policy simulation is

helpful to progress policies of economic, trade,

energy and environment, determines the state of the

economy and so on. Particularly, it is very realistic

to improve governmental decision-making in the

conditions of policy development through simulation

competition in the market of developed countries

after China joined WTO.

In the research field of policy simulation,

developed countries has developed a number of

policy simulation systems by computer technology

and widely used computer optimization. U.S.

economic model ASPEN (Basu, 1998) is a new

economic simulation platform, whose prototypal

version was used for the analysis of business cycle

phenomena and extended version was used to

analyze the effects of monetary policy. T.Iba (Iba,

2000) et al developed crates economic model which

provided a model of open development environment.

Zhang Shiwei et al (Shiwei Zhang, 2004) developed

a macroeconomic model platform called ASMEC-I,

which used to analyze the effects of various

agricultural products, consumption, prices, markets

and trade in China under policies and external

shocks. Jikun Huang et al (Jikun Huang, 2003)

established the Chinese Agricultural Policy Analysis

and Prediction Model (CAPSiM for short), which

used to analyze of policies and external shocks on

the production of various agricultural products in

China, consumption, prices, markets and trade. The

current version is programmed by Visual C #. It has

friendly user interface and is easy to operate.

Computable General Equilibrium (CGE for short)

model (Yuxin Zheng, 1999; Yong Zhao, 2008)

treated the economic system as a whole analytic

object, analyzed specific changes in economic policy

by simulation of the whole economic system, and

investigated the supply and demand relationship

between various commodities and factors of

production with a comprehensive view. CGE model

divided macro-economic system into a large number

of computable parts, calculated by computer

simulation rather than analytical analysis to study

the general equilibrium price changes within the

framework of the impact of the economic system.

Based on CGE technology, developed countries

established a number of macroeconomic modeling

Li Z., Qi Q., Liu Y. and Zhu D..

RESEARCH AND DEMONSTRATION OF AGRICULTURAL POLICY SIMULATION BASED ON CGE MODEL.

DOI: 10.5220/0003423300130017

In Proceedings of the 13th International Conference on Enterprise Information Systems (ICEIS-2011), pages 13-17

ISBN: 978-989-8425-54-6

 2011 SCITEPRESS (Science and Technology Publications, Lda.)

and analysis systems (Powell, 1995), such as Fair-

model system in United States, the Murphy Model

systems in Australia, the MSG2 multi-country model

from the United States, Japan, Germany, Australia

and other countries. In this field, China’s previous

experience mainly relied on statistical analysis,

which is a wide gap. In recent years, there have been

some developments in models, but not enough.

Policy simulation system has broad prospects for

development, so this type of research and

development of new simulation platform has great

theoretical and practical significance.

With the widely use of CGE model in policy

simulation fields, the studies on integration of policy

simulation, CGE model and DSS decision-making

system is still rare yet. This study aimed to construct

a CGE model based on policy simulation platform

called PSPBCGE (Policy Simulation Platform Based

on CGE), applied advanced computer technology

into the economic system modeling and policy

simulation, effectively analyzed the policy

simulation centered the CGE model as the core

driver for the simulation platform, provided an

effective system tools for the establishment and

maintenance of CGE models by using the

advantages of DSS and give full play to the efficacy

of mathematical economic models.

2 COMPUTABLE GENERAL

EQUILIBRIUM MODEL

The basic idea of CGE model is: based on the

principle of profit maximization and under the

conditions of resource constraints, producers

determined the optimal supply of various

commodities and needs of production factors; rested

on the principle of utility maximization and in the

budget constraint conditions, consumers determined

the demand for various commodities. When the

optimal supply is equal to the optimal, economic

system achieved to the most stable equilibrium and a

set of equilibrium price of a commodity could be

calculated by the balance of supply and demand.

From the point of modeling view, CGE model is

a set of equations for the balance between supply

and demand economic systems, generally includes

three equations of supply, demand and equilibrium.

Its general structure can be shown in Table 1 below:

3 CONSTRUCTION OF POLICY

SIMULATION PLATFORM

Policy simulation is the development of science

policy in the computer age, therefore the extension

of the policy simulation in technology respect is

decision support system. From a purely technical

point of view, policy research is also a process of

information requiring, processing transmission and

analysis, which is an intelligential technology

comprehensively utilized of information technology

and human brain functions. This allows us to take

full advantage of modern computer technology to

build data collection, processing and delivery system,

establish comprehensive and effective database and

carry out policy simulation analysis.

Table 1: Basic structure of CGE models.

Supply Demand Supply-demand relationship

Main body

Producer= National

production sector

Consumer= Residents +

Business + Government

Market

Behavior

Producers maximize

profits

Consumers maximization

utility

Seek the market equilibrium

price

Equations

Production equations

Constraint equations

Optimization condition

equations

Demand equation of

production factors

Consumer utility equations

Constraint equations

Optimization condition

equation

Demand equation

Supply equation of

production factors

Product market equilibrium

equation

Factor market equilibrium

equations

Residents of the Balance

Equation

Government budget balance

equation

International market equilibrium

equation

Va ri ab le s

Commodity price and quantity, price and quantity of production factors, institutional

variables, the variables that technological progress, the macro variables

ICEIS 2011 - 13th International Conference on Enterprise Information Systems

3.1 Basic Functions and Features

of Simulation Platform

(1) Data acquisition, import, processing functions.

System has the function of importing data from an

external database, establishing realistic standards for

data structure in order to conveniently access to user

data system and updating data warehouse at any

time. Data query can be process at any time by user

needs, and data can be stored and converted so that

each module can facilitate the data.

The system can response users request at any time of

data query, data storage and data conversion, so that

the data can be conveniently invoked by all

functional modules.

(2) Functions of policy simulation, calculation and

analysis. The system can satisfy the calculation

needs of the CGE model, policy-oriented integrate

the CGE model, DSS decision-making methods and

tools and data warehouse, and maximally provide an

efficient, comprehensive and visualized policy

simulation platform to users.

System can provide users to maximize an efficient,

comprehensive, policy simulation visualization

platform.

(3) System running process is a process of

interaction with policy makers, provides visual and

vivid support to help users understanding the

structure of CGE models, social accounting matrix

and policy simulation theory. Furthermore, this

process can clarify decision-making problems and

form policy simulation scenario by gradually

interactive process, obtains policy simulation results

after running the system and finally get policy

recommendations.

3.2 Simulation Platform based

on the Overall Data Warehouse

Structure

Prototype system consists of six modules:

knowledge base management system (KBMS),

database management systems (DBMS), question

generation system (QGS), CGE model generation

system (CGEGS), CGE model solving system

(CGESS), input and output and analysis system

(IOAS). Figure 1 shows the overall structure.

3.3 Programming Language

There are three parts: Human Machine Interface and

decision-making processing system based on

Microsoft Visual C++.Net (Hongshen Gao, 2009),

CGE model generation and solving system based on

GAMS software (http://www.gams.com, 2009)

which is a calculation module simulation platform,

and database system based on Microsoft SQL sever

2000 (William, 2007). The hierarchy of the

simulation platform is shown in Figure 2.

3.4 Implementation Process of Policy

Simulation

Users can use the CGE model to simulate policy

changes on economic systems to meet the needs of

government policy makers. Establish the base year

equilibrium data namely social accounting matrix,

design specific policy variables according with

specific policy issues and department assembly,

simulate, calculate and analyze in the last. The

implementation process shows in Figure 3.

Figure 1: PSPBCGE overall structure simulation platform.

RESEARCH AND DEMONSTRATION OF AGRICULTURAL POLICY SIMULATION BASED ON CGE MODEL

Figure 2: The Hierarchy Structure of PSPBCGE.

Figure 3: Chart flow of simulation platform.

4 EMPIRICAL SIMULATIONS OF

AGRICULTURAL SUBSIDIES

Using simulation platform prototype, given China’s

agricultural subsidy policy as policy variables,

Empirical simulations of agricultural subsidies can

analyze the scenario simulation how the change of

policy variables impact national economy and test

the construct validity of the policy simulation

platform.

Scenario assumptions: on the premise of other

variables remained constant, change one variable

and calculate the changed value of other variables,

and achieve the impact results from policy variables

to other variables.

Simulation process: According to specific policy

issues assemble sectors, design specific policy

variables, select variable base value, set the

simulation scenario, simulate calculation and

analysis, and give recommendations in policy

analysis.

4.1 Simulation Program Design

Departmental assembly: 1. Agriculture; 2. Industry;

3. Construction industry; 4. Post and

telecommunication; 5. Commercial food service; 6.

Non-material production sectors.

Evaluating indicator: 1. Classification wages

(wage), divided into urban income and rural income;

2. Consumer price index (CPI); 3. Actual

government savings (RSg); 4. Government subsidies

(TSubs); 5. Exports (PS).

Variable base value: yellow box agricultural

subsidies in 1997 were 50.092 billion (Yuan

Xiwen

Cheng, 2005)

Scenarios are: Scenario 1: 20% increase of

agricultural subsidies based on 1997 base value;

Scenario 2: 30% increase of agricultural subsidies

based on 1997 base value; Scenario 3: 40% increase

of agricultural subsidies based on 1997 base value.

4.2 Simulation Results and Analysis

The results are shown in Figure 4, where: horizontal

ordinate shows income of urban residents income,

rural people’s income, consumer price index, real

government savings, government subsidies and

export value index; vertical ordinate shows the

impact from raise of agricultural production

subsidies indexes to evaluating indicator under 3

scenarios, namely the percentage relative to the base

period. The result shows that increase of agricultural

sector production subsidies significantly impacted

the income of rural residents but little effect to

wages of non-agricultural sector. Simultaneously,

consumption has increased, so rural workers were

beneficiaries. Increased agricultural production

subsidies declined government’s saving, but not

great. Escalation of production subsidies expanded

governmental public spending. Moreover, as the

international competitiveness of agricultural

products increased the increase in agricultural

subsidies to stimulate exports to some extent.

ICEIS 2011 - 13th International Conference on Enterprise Information Systems



Figure 4: The impact of economic indicators.

5 CONCLUSIONS

From the respect of policy simulation, this paper

proposed and built a simulation platform for policy

decision-making prototypes. The construction of

simulation platform included modeling, model

computer expression, establishment of data

warehouse, data exchange and format conversion,

CGE computing environment and effective

integration of DSS and so on. Using this integrated

simulation platform, an empirical simulation for

policy issues of agricultural subsidies was tested.

The results showed that the simulation platform

achieved the intended purpose and could solve

practical problems. We hope this paper can play a

role in attracting valuable opinions and promote the

application of policy simulation platform.

REFERENCES

Xueming Liu. An Analysis of the Developmental Process

and Real Achievement of China's Policy Science.

Journal of Nanjing Normal University (Social Science

Edition).4: 24-29(2004)

Basu N, Pryor R, Quint T. ASPEN: A micro simulation

model of the economy. Computational Economics,

12:223-241(1998)

Iba T, Hirokane M, Takenaka H, et al. Boxed economy

model: fundamental concepts and perspectives [C].

First International Workshop on Computational

Intelligence in Economics and Finance (CIEF’2000).

Atlantic City, New Jersey, USA: Association for

Intelligent Machinery.941-944 (2000)

Shiwei Zhang. Agent-based micro-simulation models of

the economies. Journal of Finance and Economics

1:74-78(2004).

Jikun Huang, Ninghui Li. China’s agricultural policy

simulation and projection model-CAPSiM. Journal of

Nanjing Agricultural University (Social Sciences

Edition). 2:33-44 (2003).

Yuxin Zheng, Mingtai Fan, Gang Ma. China CGE Model

and Policy Analysis. Beijing: Social Sciences

Academic Press, China (1999)

Yong Zhao, Jinfeng Wang. CGE Model and Its application

in Economic Analysis. Beijing: China Economic

Press, China (2008)

Powell A.A., Murphy C.W., Inside a Modern

Macroeconometric Model. Springer-Verlag Berlin

Herdelberg New York (1995)

Hongshen Gao .Decision Support System (DSS) -- Theory

and Methods (Fourth Edition). Beijing: Tsinghua

University Press. China (2009)

The Solver Manuals, GAMS development corporation.

http://www.gams.com. (2009)

William H. Inmon. Building the Data Warehouse, Fourth

Edition. China Machine Press. China (2007)

Xiwen Cheng, Jun Han, Yang Zhao. Public Finance

System in China Rural-Theory, Policy, Empirical

Study. Beijing: China Development Press (2005)

RESEARCH AND DEMONSTRATION OF AGRICULTURAL POLICY SIMULATION BASED ON CGE MODEL