An Agent-Based Model for
Designing a Community Currency Scheme

Mc Angelo Antonio M. Miro1, Ferdinand C. Maquito2

1 Electronics and Communications Engineer, Junior Researcher (Sekiguchi Global Research Association, Philippines)
2 Assistant Professor, College of Public Affairs and Development, University of the Philippines Los Baños

自律的に意思決定する参加者を多数モデル化し、その相互作用をコンピュータでシミュレーションするABMの手法を用いて、真に有効な地域通貨のシステム設計を考察した。

Abstract

This paper reports on the development of an Agent-Based Model (ABM) that could help actual communities in thedesigning of Community Currency (CC) schemes, which have been deemed, in various seminars held in thePhilippines and Japan by the Sekiguchi Global Research Association, as mechanisms for sustainable shared growth.
As such, the ABM depicts a CC scheme for a community economy that essentially has no interest rate, but has thetwo other basic prices: (1) the price for a community-produced private good, expressed in both CC and fiat money(Philippine Peso) depending on the acceptance rate; and (2) the exchange rate between the CC and fiat money. The
ABM has three types of producers: community-based private good producers; community-based local public (volunteer) good producers; and external private good producers. The community economy also includes laborers that
could work to produce either private or volunteer goods. There is trade between the community’s laborers and theprivate good producers, both community-based and external, where the latter accepts only fiat money as payment.
By definition, CC is accepted only within the community as payment. The ABM helps in identifying various combinations of design parameters such as price acceptance rate, and population, which are critical for the sustainabilityof a CC scheme.
Keywords

community currency, agent-based model

Introduction

As the term implies, a Community Currency (CC) isa form of money that is usable only within a certaincommunity. In this paper, we define a community in ageographical sense, as having clear geographical boundaries and much smaller in scale compared to the nationalboundaries.
In previous seminars held by Sekiguchi Global
Research Association (SGRA) mostly in the Philippines,
CC’s have been deemed as good mechanisms for achieving sustainable shared growth, having the socio-economic goals of efficiency, equity, and environmental
friendliness.
One important step in adopting a CC scheme is its

design. Yoshida and Kobayashi (2018) recommend thatmuch consultations with the community. Thinking ofadopting a CC scheme must be done prior to the actual
implementation of the scheme. Through simulations,they found the following factors to be important for thepromotion of use of a CC: the premium rate of CC; theproportion of CC in the salaries; and the probability ofvolunteers with CC. Their simulation model, however,
was not publicly available, making it impossible for us
to replicate.
Nevertheless, we followed the lead that simulation
models would be useful for the design phase of a CCsystem. Our search for a CC simulation model led us tothe graduate report of (Grinza and Beqaraq 2012) which057

Mc Angelo Antonio M. Miro, et al.

contains the codes for the simulation. The model, however, is designed for the EU setting, and most of thevariables considered in the model are not really the ones
relevant in an early design of a CC scheme.
In this paper, we share the results of adopting this EU
model, called the EAC Model by the authors, to what wethink are the important considerations in a developing
country case such as the Philippines. We call our model,
the Tanuki, or raccoon, Model1.

Methodology

We use the EAC Model as our basic source for theNetLogo codes of their agent-based model. One very big
advantage of NetLogo is that it is available publicly forfree. Agents in this model, called turtles, are given
simple rules of behavior in a two-dimensional world,
formed from a group of patches. Turtles could interact
with each other or the environment in a prescribedmanner at each run (tick) of the simulation model.
We then proceeded to revise the EU Model to introduce variables that we thought important to designing aCC scheme in a developing country setting. We also
ensured that the model did not give strange results, suchas money stocks continually increasing.
Once we had a stable Tanuki Model, we did some
simple simulations to see how the number of hungry
tanukis (rejected transactions) moved with changes in
the acceptable combination of CC and fiat money that
community vendors, as well as in the population of vendors in the community accepting CC.

The Tanuki Model

The model that we created is called the “TanukiModel”. It is a system with a fixed number of community members (Tanukis), a fixed number of outside vendors (Shops) and a variable number of local vendors(Markets). It is designed in a way where it simulates theeveryday interactions of community members and vendors for 1,080 days or 3 years. At the start of the simulation, the Tanukis are given a random amount of cash that
ranges from 4,000 to 20,000 PhP and an amount of CC
1 In honor of the alumni of the Atsumi Foundation.

058(Tane, or seed) equal to 15 percent of their initial cash.
Upon running the simulation, the Tanukis are programmed to move randomly and once they come near avendor, they spend a random amount of Tane and/or PhP
if they have sufficient balance. The amount being paid
to the vendors is specified in Table 1 in the next sectionof this paper.
Additionally, every 30 days, the Tanukis receive payment or salary equal to a percentage of Tane and PHP
earned by the vendors. Thus, creating a closed system
where the initial Tane and PhP are just being circulated.
For a more detailed picture, see Figures 6 and 7 in thenext section of this paper.

Fig. 1. Screenshot of the community

Fig. 2, 3 and 4. T he community members (Tanukis) andvendors (Markets and Shops)

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The figures above show the community as a whole,as seen in the simulation, and the different charactersthat interact within the community.

The EAC Model vs Tanuki Model

The table below shows the basic differences between
the two models.
Table 1. Differences of the two models
AspectFig. 5. Screenshot of the entire application.

Figure 5 shows the interface of the application that
we developed. The buttons on the left are the control
buttons: setup (start) and go (run), the middle part is thevisual representation of the interactions of the community, the green boxes are the design variables, and theyellow boxes are the monitors.
To run the application or model, the designer, first,needs to set up the five design variables, the initial CC of
the the tanukis (percent-tane-initial), the percent of CC
the markets accept as payment (percent-tane-payment),
the percent of CC and cash the tanukis receive from themarkets (market-to-tanuki-percent), the percent of cash
the tanukis receive from the shops (shop-to-tanuki-percent) and the number of markets (number-of-markets).
After setting up the design variables, the “setup”
button is clicked to initialize the system. Here you will
see the Tanukis and Markets (local vendors) scattered
randomly within the system and the Shops (outside vendors) placed in fixed points.
Once the characters are set up, the “go” button isclicked to simulate the interactions. While the system isrunning, you can freely monitor the amount of cash andCC of the Tanukis, markets and shops; and also, the performance indicator, which is the percentage of which
the tanukis have insufficient cash or CC when they go to
any of the vendors.

EAC Model

Tanuki Model

Population

Angents (150)

Tanukis (150)

No. of CC’s2

1

Starting CC1

EAC(random 12,000+ 3,000)

TANE(15% ofstarting cash)

Starting CC2Tickets(random 4000+ 1000)

N/A

Starting CashEURO(random 80,000+ 20,000)

PHP(random 16,000+ 4,000)

Vendor1 PaymentMethod

Markets:
Shops:
random 270 + 30
random 270 + 30(accepts all by %) (accepts both by %)Vendor2 Payment
MethodBars:
random 15 + 5(accepts all by %)Shops:
random 15 + 5(accepts cash only)

No. of Vendor1’s

4

10 and 100

No. of Vendor2’s

24

No. of Days (Ticks)

1000

1080

Credit & Debit

Yes

No

Note: The “random <number>” is equal to a random number from 0 to<number>.

Additionally, there is also a difference on how thecommunity earns their money and CC. In the Tanuki
Model, every 30 days or ticks, the amount of Tane andPhP the vendors have earned are dispersed by percentage, set by the community designer, to the Tanukis andtheir fellow vendors. This distribution simulates thesalary or payment the tanukis receive monthly and thetrading system between the vendors. The Tane and PhP
flows are further illustrated in the following figures.

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Results and Discussion

Tables 2 and 3 show the average % rejection rates forthe cases of 10 and 100 market vendors, respectively.
The maximum, minimum, and standard deviation of the% rejection rates are also shown for each case. The
amount of CC in the price varied from 0% to 90% asshown in the tables.
Table 2. Simulation results for case of 10 market vendors

Fig. 6. CC flow every 30 days

Figure 6 shows the CC flow every 30 days where“tmt” is the total amount of CC the Tanukis paid theMarkets.

% TanePayment0%
AVE. %REJECTED 9.2

10% 20% 30% 40% 50% 60% 70% 80% 90%
8.7

11.2

MAXIMUM
37.6

17.6 22.1 27.3 29.5 33.3 34.9 37.6
MINIMUM
8.7

STD. DEV.
11.0

Note: For 50 runs, 1080 days per run

Table 3. Simulation results for case of 100 market
vendors% Tane
Payment0%
AVE. %REJECTED 1.2
MAXIMUM
48.8

10% 20% 30% 40% 50% 60% 70% 80% 90%
0.9

1.6

4.9

11.4

MINIMUM
0.9

21.4

31.0 38.5 44.4 48.8
STD. DEV.
19.0

Note: For 50 runs, 1080 days per run

Fig. 7. Cash flow every 30 days

Figure 7 shows the CC flow every 30 days where“tmp” is the total amount of cash the Tanukis paid theMarkets and “tsp” is the total amount of cash the Tanukis
paid the Shops.
Whereas in the EAC Model, the agents earn a randomamount of cash and CC every 30 days or ticks, andappear like manna from heaven.

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At lower values of % Tane Payment in price, theaverage rejection rate for the 100-vendor case was lower
than for the 10-vendor case. At higher values of % Tane
Payment in the price, however, the average rejection rate
becomes higher in the 100-vendor case than in the10-vendor case. This suggests that there are non-linearities in the model that might produce an optimum atsome intermediate level of % Tane Payment in the price.
The non-linearities could be due to two opposing
effects of increasing the number of vendors on the %rejection rate. A positive one, wherein the higher numberof vendors increases the number of purchases of thetanukis, increasing the probability that they would haverun out of money. A negative one, wherein the higher
number of vendors, increases the number of transactions, increasing the denominator faster than the numerator in the % rejection rate formula.

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Patterns
We found the following three encouraging patterns
from our simulation of our Tanuki Model.
Pattern #1: Inventory-like pattern of money stocks.
This pattern reminded the second author, an economist,of the inventory money demand for money model(Baumol 1952). Figure 3 shows the sawtooth pattern ofmoney holdings, depending on the number of trips tothe bank.

Fig. 9b. Average PhP held by Tanukis

Fig. 9c. Average CC held by Tanukis

Fig. 8. An inventory model of money
Source: (Karmakar, n.d.)This sawtooth pattern was seen in the average stockof money held by the tanukis and market vendors in theTanuki Model, shown in Figures 9 below.

Fig. 9a. Average CC held by Tanukis

Fig. 9d. Average PhP held by market vendors.

Note that the sawtooth pattern for the markets isinverted due to the fact that the markets collect the payments from the Tanukis.
Such a sawtooth pattern was taken as a signal that theTanuki Model has stabilized. In its original form, theEAC Model, the money stocks had a tendency to either
continuously follow upward or downward movement
through time. We thought this inappropriate for theTanuki Model, where the stock of CC is essentially kept
constant.
Pattern #2: Introduction of tane reduces % rejectedtanuki. Our simulation shows that in all of the cases
studied, the % rejected tanuki drops as soon as a small

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Mc Angelo Antonio M. Miro, et al.

amount of tane becomes acceptable to the market vendors. This suggests that the CC could be a mechanism
for adding cash into a community. This role of a CC isalso observed in the case of a developing country like
Kenya, where a substantial increase in transactions isobserved after the introduction of a CC into the community (Ruddick, Richards, and Bendell 2015). Higher
transactions mean lower rejected transactions.
Pattern #3: Having more market vendors in the community helps to reduce % rejected. The initial number ofmarket vendors in the Tanuki Model was only ten, since
this was the number of vendors in the EAC model, whichis the baseline model. We increased this to 1002, which isabout the number of vendors in the developing country
case of Kenya. This finding supports the widespread
introduction of a CC into a community with manyvendors.

Conclusion

The Tanuki Model is a significant improvement overthe EAC model, since the former includes design andcommunity structural variables that could be useful indesigning a CC scheme to suit the particular set of structural characteristics of the community considering aCC’s adoption. Table 4 lists up the major design andstructural variables. In the actual implementation of themodel, the design variables are set by the designer of thesimulation model, while the structural variables areobtained based on consultations with the community
considering the adoption of a CC scheme.
Table 4.	Summary of design and structural variables of theTanuki Model
Design Variables-percent of Tane accepted aspayment-initial Tane-percentage of Tane and cash
Tanukis receive from Markets-percentage of cash Tanukis
receive from Shops

Structural Variables-number of community
members-number of local vendors-number of outside vendors

2 (Ruddick, Richards, and Bendell 2015)

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The Tanuki Model could be easily further modified
as the situation demands. Some of the modifications weare currently thinking about is capturing the interaction
between the market vendors in the community, and thecreation of a CC bank, where the issuance of CC could
be taken to be a measure of the degree of volunteerism
in the community.
In terms of methodology, we are thinking of automating the sensitivity analysis of the model, which we
did manually in this study. Moreover, agent-based modeling presents an alternative way of research that could
be useful in the age of pandemics, where field work has
become more risky.

References
1) Baumol, William J. 1952. “The Transactions Demand for Cash:
An Inventory Theoretic Approach.” The Quarterly Journal ofEconomics 66, no. 4 (November): 545-556. https://doi.org/10.2307/1882104.
2) Grinza, Elena, and Claudio Beqaraq. 2012. “EconomicSimulation with NetLogo “A monetary experiment.”” Universityof Turin. https://terna.to.it/tesine/a_monetary_experiment.pdf.
3) Karmakar, Diptimai. n.d. “The Transactions Demand for Money:
A Close Look.” Economics Discussion. Accessed March 28,
2021. https://www.economicsdiscussion.net/money/demand-formoney/the-transactions-demand-for-money-a-close-look/16115.
4) Ruddick, William O., Morgan A. Richards, and And J. Bendell.
2015. “Complementary Currencies for Sustainable Developmentin Kenya: The Case of the Bangla-Pesa.” International Journalfor Community Currency Research 19.
5) Yoshida, Masayuki, and Shigeto Kobayashi. 2018. “UsingSimulation and Gaming to Design a Community Currency
System.” International Journal of Community Currency Research
22 (Winter): 132-144. http://dx.doi.org/10.15133/j.ijccr.2018.011.