An Approach of Monetary Policy Simulation by Agent-Based Model

An Approach of Monetary Policy Simulation by Agent-based Model

Xiao Xiao1, Jianwei Tian2, Minjie Xu3

1.School of Business and Administration, North China Electric Power University, Beijing, China

2.School of Electrical Engineering, Beijing Jiaotong University, Beijing, China

3.State Power Energy Research Institute, Beijing, China

e-mail: xiaoxiaocba@https://www.360docs.net/doc/509288738.html, (X.Xiao), 07117318@https://www.360docs.net/doc/509288738.html, (J.W.Tian),

xuminjie@https://www.360docs.net/doc/509288738.html, (M.J.Xu)

Abstract—Multi-Agent System (MAS) is developed to organize agents as participants of real economic world. On support of macro-statistics, agent’s status and interaction with others will lead to evolution of the whole economic system. The effectiveness of monetary policy tools as reserve ratio and open-market operation promulgated by central bank is validated through implementing Monetary Policy Simulation System (MPSS).

Keywords-Multi-Agent System; monetary policy; policy simulation

I.I NTRODUCTION

The economic simulation has been paid closer attention since financial crisis engulfed the whole world, and forecasting approaches that depend on historical data and model always failed under volatile domestic and overseas economic circumstances. Computable General Equilibrium (CGE) and Non-Linear Regression (NLR) are good examples. These methodologies are desired when being applied in regular economic trend. However, when facing unpredictable alteration, such as macro-policy, they are probably inefficient in analyzing and solving problems.

Fortunately, Artificial Intelligence and Complex Adaptive System technologies have provided us a new scope of viewing the real world. ASPEN of Sandia uses agents to be representative of firms, people and so on [1]. In industry production sectors, application of agent and hybrid agent are utilized in various aspects: Water pricing-policy is assessed, and a social community is constructed to imitate consumers’ behaviors [2]; Day-ahead electricity market is modeled with real demand in buyer and statistical supply in seller. A clearing-house mechanism is used to calculate the price in balance status [3]; Game analysis of stock market is reviewed, and dividend amplitude parameter is proved to be a crucial factor of market uncertainty [4]; To improve the robustness and adaptation, agents are designed to be capable of reinforcement learning supported by Temporal Difference (TD) Algorithm [5].

In this paper, agents are characterized as members of China economic environment. After their communication and cooperation, macro indices such as value-added, final consumption will be modified on the basis of decision-making mechanism of each unit. In section 2, Multi-Agent System (MAS) modeling technique and Monetary Policy Simulation System (MPSS) are described; In section 3, an illustrative example for MPSS is carried out; In section 4, we conclude the obtained results.

II.M ULTI-A GENT S YSTEM D ESIGN Agent is an artificial intelligent unity capable

of autonomous, cooperation and communication. By clustered agent, MAS is regarded as the technology concerning evolutionary and deductive issue, in which elements are set as the foundation of bottom-up simulation. Agent’s inner structure, mechanism of communication and environment are shown in Fig. 1.

In general, an agent contains Knowledge

2010 International Symposium on Computational Intelligence and Design

Figure 1. Structure and interaction of agent.

Base, Rules Base and Behavior Base. It is motivated by Target and Target Comparison. The interaction occurs when communicating with environment, especially with other agents.

Based on Input-Output Table (I-O Table) published by National Bureau of Statistics of China [8] and electricity consumption data published by power sector, we summarize the number of industry sectors into 151, and also build corresponding Industry Agents (IA). Besides, we add one Government Agent (GA), one Resident Agent (RA), two Bank Agents i.e. Central Bank Agent (CBA) and Commercial Bank Agent (C m BA) and two Market Agents i.e. Products Market Agent (PMA) and Financial Market Agent (FMA). They are described in detail as follows:

A.C m BA

C m BA is an organization that not only receives prescriptive messages from CBA to expand or tighten money supply, but also absorbs in the idle money-flow from residents, government and industries. Taking the investment risk of real world into the account, C m BA should make decision relying on two essential factors: the risk and the profit. Assuming the Internal Rate of Return (IRR) of industry is from IO-Table, thus, the judgment should be described as:

1 They are: Agriculture Agent, Mining and Quarrying Agent, Foodstuff Agent, Textile, Sewing, Leather and Furs Products Agent, Other Manufacturing Agent, Power, Heat Power and Water Agent, Coking, Gas and Petroleum Refining Agent, Chemical Industry Agent, Building Materials and Nonmetal Mineral Products Agent, Metal Products Agent, Machinery

and Equipment Agent, Construction Agent, Transportation, Postal and Telecommunication Services Agent, Commercials and Catering Services Agent, and Other Services Agent.

Max.D

L

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credit

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t sψ(2)

where

cmb

π is the profit of C m BA, iψ is the

probability that IA i is capable of paying back the loan; L is the industrial credit amount from

commercial bank;

credit

γ,

deposit

γ are interest rate of credits and deposits; D is the total deposits that commercial bank absorbed from RA, GA and IA. To pursue benefit, C m BA targets at maximizing credits surplus over deposits.

B.CBA and GA

CBA and GA are the promulgator of monetary and other policies. Therefore， they are able to be interrupted and modified whenever the exogenous decision-maker inclines to change economic trend, especially the money supply. Definitely, it will affect the final result of economic operation and equilibrium.

C.IA

Industries’ profit activates themselves to loan more from commercial bank. Meanwhile, profit of IA could be formulated as: Profit = total products – cost – interest – tax. It is obvious that monetary policy mainly impacts on “interest” as well as financial policy on “tax”. The I-O Table data are calculated in current price and production function of IA is shown as：

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i

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I≤

where

i

∏is the profit of industry i, i q is the total output of industry i, w is the wage rate, i

K is the fixed capital, r is the credit interest rate, i

L is the labor force of industry i, t is the tax

rate,

i

p is the price factor of products of industry i determined by supply and demand relationship of PMA,

ji

x is the amount of

intermediate input from industry i to j,

ji

a is

intermediate input coefficient from industry i to j , which is the direct consumption coefficient in I-O Table, i V is the value-added of industry i ,

in i I , and max ,i I are capital input and maximum

available capital of industry i [6]. D. RA

RA’s primary decision and behavior are consumption and deposits, and judgment of deposits more or less is represented by the Deposits/Deposits-Interest elastic coefficient. It would be acquired after statistical analysis based on empirical data. E. PMA

The main function of PMA is to gather all messages from both supply and demand sides, and through judgment, it would balance them and feed back dynamic states to IA. Hence, IA is able to make a new-round decision and send demand of labor forces, as well as supply of products to PMA. Price function of products market is:

)()1()1(t P t P j j η+=+ (4) where

)(t P j is the time series of industrial j ’s price and )

()(t D t S j j Δ?γ=η, )(t S j Δis the supply-demand difference at phase

t , )(t D j is the total products demand at phase t ,

γ is the calculating coefficient. Therefore, the

sign of η is determined by relationship of demand and supply at phase t .

F. FMA

Money-flow of financial market, which is

influenced by monetary policy, is derived from deposits of commercial bank. Tools for monetary

policy mainly include Reserve ratio and Open-market operation. Reserve ratio is the proportion of deposits reserved in central bank, aiming at ensuring safety of clients and commercial banks. However, owing to impact of money-multiplier and consequent money creation ability, the reserve ratio has been promoted to control amount of social money supply indirectly; Open-market operation is a business activity that central bank deals securities in money market in

order to regulate reserve and money supply correspondingly [7].

Under function of these monetary tools, relative items of Financial Statement [8] are altered, and the total money supply is:

b r r d d

c S i S i S S ++=)()( (5)

where c S is the total available money amount to be credits. d S is the total deposits gained from residents which is a function of deposits interest rate (d i ), )(r r i S is the variables that presents

change of reserve amount influenced by reserve ratio (r i ), b S is the amount of open-market operation.

On the demand side, it is the total amount of credit demand from IA. Therefore, when balancing entire market in supply and demand, FMA would obey the IF-THEN statements of:

IF d s M M >, THEN di i C C = (6) IF d s M M ≤, THEN di i C C ?= (7)

where s M ,d M is the total money supply and demand in Finance Market; i C is the actual credits to industry i ;

di C is the credit demand

of industry i ; d

s M M =? means total money demand will adjust based on ability of money

supply in financial organizations accordingly.

MPSS is achieved by applying platform of

Multi – Agent Environment (MAGE) [8], and the

ACL Message proposed by FIPA is set as the

communication language [10]. The structure of economy concerned is outlined in Fig. 22.

III. E XPERIMENTS

We set the year 2005 as fundamental year, and relative I-O Table [9] will account for

economic condition at that time. Graphics User Interface of MPSS is shown as Fig. 3. If assumed that, when typing monetary policy data at the end of 2006, the equilibrium result will present the

2

In Fig.2, each number means: (1) Residents provide labor

forces to industry and get payment from Products Market; (2) Affected by deposits interest rate, residents change saving accordingly, which is the upper-limit of total available credit; (3) Commercial Bank provides money to Credit Market; (4) Central Bank publishes monetary policies to Commercial Bank; (5) Central Bank modifies deposits interest rate to affect the extent of residential saving.

Figure 2. Economic structure of monetary policy.

impact of yearly policy. The estimated actual policy effect during 2006 is shown as Fig. 4, representing the GDP, Secondary Industry and Tertiary Industry will decrease in 0.30%, 0.68%, and 0.15%, whereas Primary Industry will ascend 0.72%. The simulation results of setting Credit Interest Rate (CIR), Reserve Ratio (RR) and Open-Market Operation (OMO, maintain Sold-out status) as marginal factors, are summarized in Table Ⅰ

.

Figure 3. Graphics User Interface of MPSS.

Figure 4. Result of setting credit interest rate.

IV. C ONCLUSION

MPSS provides a new approach to evaluate

TABLE.I E CONOMIC INDICES OF MPSS EXPERIMENT

Monetary

Policy Effect

GDP

Primary Ind.

Secondary Ind.

Tertiary Ind.

CIR (+50%) -0.18% -0.34% -0.17% -0.15% CIR (-50%) 0.15% 0.02% 0.29%

0.02%

RR(+1% point) -0.10% 0.06% -0.07% -0.17% RR(-1% point) 0.06% 0.05% 0.12% 0.00% OMO(+50%) -0.49% -2.34% 0.76%

-1.45%

OMO (-50%)

-0.29% 0.05%

-0.32% -0.37%

technology, flexible policies influence not only

the suppliers in product and monetary markets, but also the ones who are available to loan or buy for reproduction or consumption. If combined with annual or five-year economic plan, an acceptable solution domain of policy would be obtained to guide direction of economy development, which is the future key point of this research.

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