Charles University in Prague
Faculty of Social Sciences
Institute of Economic Studies
MASTER THESIS
The Basic Income concept in the
perspective of Agent-Based modelling
Author: Bc. Vı́t Macháček
Supervisor: Petr Janský, Ph. D
Academic Year: 2015/2016
Declaration of Authorship
The author hereby declares that he compiled this thesis independently, using
only the listed resources and literature.
The author grants to Charles University permission to reproduce and to distribute copies of this thesis document in whole.
Prague, July 29, 2016
Signature
Acknowledgments
The author is grateful especially to the supervisor Petr Janský Ph.D., who was
patiently following the progress of the work and forcing the author to think
twice before jumping in the conclusion.
Special thanks belongs also to Dr. Tomasso Ciarli and the whole Scientific
policy research unit at University of Sussex who demonstrated the beauty of
evolutionary economics. Also Institute of Economic Studies at Charles University have their important role in teaching the importance of empiric research
methods.
Abstract
The thesis study the relationship between the basic income introduction and
the price level. The basic income would replace the existing social security.
The resulting redistribution induce changes in the aggregate demand through
the concave consumption function. The aggregate demand in turn affect the
price creation mechanism. Because the price level is a result of activity of
many different agents with private motivation and information, the work used
a simple macroeconomic agent-based model to isolate the relationship. The
simulation however did not succeed in isolating the possible link between the
price level and the basic income introduction.
JEL Classification
Keywords
H3, H53, D31, E31, E37
Basic Income, Price level, Agent-based macroeconomics, Policy-testing
Author’s e-mail
Supervisor’s e-mail
[email protected]
[email protected]
Abstrakt
Práce studuje vztah mezi zavedenı́m základnı́ho přı́jmu a cenovou hladinou.
Základnı́ přı́jem by nahradil existujı́cı́ sociálnı́ systém. Z toho vyplývajı́cı́
přerozdělenı́ skrze konkávnı́ spotřebnı́ funkci působı́ na agregátnı́ poptávku,
která následně ovlivňuje cenotvorbu. Protože ceny na sobě nezávisle vytvářı́
mnoho různých agentů, z nichž každý má jiné motivace i informace, je vztah studován pomocı́ jednoduchého makroekonomického multiagentnı́ho modelu. Výsledky simulace ale neprokázaly jednoznačný vztah mezi zavedenı́m
základnı́ho přı́jmu a cenovou hladinou v ekonomice.
Klasifikace JEL
Klı́čová slova
H3, H53, D31, E31, E37
Základnı́ přı́jem, Cenová hladina, Multiagentnı́ model,
Testovánı́ politik,
makroekonomie
E-mail autora
[email protected]
E-mail vedoucı́ho práce [email protected]
Contents
List of Tables
vii
List of Figures
viii
Acronyms
ix
Thesis Proposal
x
1 Introduction
1
2 Basic income concept
2.1 Definition of basic income . . . . .
2.1.1 Basic income and price level
2.1.2 Proposed schemes . . . . . .
2.1.3 Financing challenge . . . . .
2.1.4 Redistribution effects . . . .
2.1.5 Labour supply . . . . . . . .
2.2 Examples of basic income . . . . .
2.3 Evaluations of the BI introduction .
2.3.1 Labour supply . . . . . . . .
2.3.2 Redistribution . . . . . . . .
2.3.3 Financing . . . . . . . . . .
3 Motivation for ABM modeling
3.1 Complexity in economics . . .
3.2 Key ABM features . . . . . .
3.2.1 Agents . . . . . . . . .
3.2.2 Rules of interaction . .
3.2.3 Environment . . . . .
3.2.4 Building a model . . .
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Contents
3.3
3.4
3.5
vi
Agent-based macroeconomics . . . . . . . . . . . . . . . . . . .
Price level in ABM . . . . . . . . . . . . . . . . . . . . . . . . .
Policy testing in the ABM framework . . . . . . . . . . . . . . .
4 The Model
4.1 Model selection . . . . . . . . . .
4.1.1 Desired model properties .
4.2 Model description . . . . . . . . .
4.2.1 General setting . . . . . .
4.2.2 Environment . . . . . . .
4.2.3 Rules of interaction . . . .
4.2.4 Capital market and wealth
4.2.5 Government . . . . . . . .
5 Simulation
5.1 Results . . . . . . . . . . . . . .
5.1.1 Calibrating the model .
5.1.2 Business cycles and price
5.1.3 Price level . . . . . . . .
5.2 Discussion and further research
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distribution
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dynamics
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6 Conclusions
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Bibliography
59
A Appendix
I
B Content of Enclosed file
VII
List of Tables
4.1
Distribution rates for social schemes . . . . . . . . . . . . . . . .
37
5.1
5.2
5.3
5.4
Parameters calibration . . . . . . .
Redistribution and price level . . .
Descriptive statistics for different of
Income groups descriptive statistics
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List of Figures
2.1
2.2
2.3
Basic income implementation schemes . . . . . . . . . . . . . . .
The effect of income distribution on BI . . . . . . . . . . . . . .
Alaska permanent fund dividend . . . . . . . . . . . . . . . . . .
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4.1
The timeline of agents decisions . . . . . . . . . . . . . . . . . .
30
5.1
5.2
5.3
5.4
Employment . . . . . . . . . . . . . . . . . . . .
’Long Cycles’ in the simulation . . . . . . . . .
Inflation in different periods of simulation . . .
Dynamics of inequalities and the business cycle
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A.1
A.2
A.3
A.4
A.5
A.6
A.7
A.8
A.9
Phillips Curve . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Granger causality test on different periods of simulation . . . . .
Transfers in 1st and 10th wealth decile . . . . . . . . . . . . . .
Price level and concavity of the consumption function . . . . . .
Perceived price-level in different income groups . . . . . . . . . .
Inventories growth in different periods of simulation . . . . . . .
The difference of price level and demand with the tax rate 70 %
Price and demand with transfers flowing only to poorest decile .
25 randomly selected realizations of the simulation . . . . . . . .
I
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Acronyms
DGP
data-generating process
ABM
agent-based model
AD
aggregate demand
BI
Basic Income
NIT
Negative income tax
Master Thesis Proposal
Author
Supervisor
Proposed topic
Bc. Vı́t Macháček
Petr Janský, Ph. D
The Basic Income concept in the perspective of AgentBased modelling
Motivation Recently there is a growing debate about the ”basic income concept”. The introduction of single social transfer which would replace most of
the existing social benefits is getting more and more attention. Utrecht and
several towns have announced a plan ”taking a small step” towards a basic
income for all by allowing small groups of benefit claimants to be paid L660 a
month? (The Guardian, 2015). Similarly ”Finland has become the latest country to propose a basic income for all. If put into practice, the scheme would
eventually see all Finnish citizens receiving an 800 euro stipend, per month,
tax-free” (World Economic Forum, 2015).
The growing interest on the topic on the other is not well reflected in the
literature yet (see Colombino et al 2010 or Moffit 2003) - the theoretical assessment of the concept is even scarcer. Atiknson (1996) provides a set of
theoretical definitions and methodological concept in assessing the basic income concept. This is why I would like to contribute on incorporating the
basic income introduction in the economic theory while as far as I know there
is no paper exploring the relationship between basic income and inflationary
pressures. One can also differentiate between negative income tax and basic
income. One can also differentiate between negative income tax and basic income as it is very similar concept, but the implementation process is slightly
different.
The main interest of the work is the effect of basic income introduction
on the inflation as inflation is a typical emergent phenonomena - it is a result of interactions of thousands agents, rather than independent process. In
Master Thesis Proposal
xi
the situation, where everybody gets additional income might result in higher
prices very easily. In my work I will test the introduction the basic income
on the macroeconomic aggregates such as inflation and unemployment level
in the framework provided by Langnick (2013). The agent-based modelling
framework, which Langnick (2013) exploits allows for policy testing with respect to some complex system properties. It is a very simple model based on
interactions between the firms and households in the two sector economy. I
will add the third sector collecting taxes and distributing social benefits. If it
was feasible I will also try to calibrate the model to correspond to the income
structure of the Czech economy. With inflation incorporated in the model I can
assess the impact of the inflation and basic income introduction on the lowest
income households. The basic income scheme which would be high enough not
to make poorest people worse off would probably be too expansive to finance
it in the long run.
The main contribution of the thesis would be more general - my goal is
to show relative simplicity of the agent-based modelling framework and the
possibility to use it for policy-testing. The second contribution is exploiting of
the relationship between inflation and the possibility to evaluate the impact of
basic income introduction on the poorest members of society.
Hypotheses
(i) The introduction of the basic income scheme which would not make the
poorest decile worse off would be too expansive to finance in the long run.
(ii) The introduction of the basic income (and replacement of social transfer
scheme) will boost inflation in the economy
(iii) The real income of the lowest income decile in the economy will be lower
in the situation of the basic income, than original social transfer scheme
Methodology The agent-based modelling is an alternative way to model the
economy, slightly different to the mainstream economic approach. In the center
of attention is set of heterogenous agents who interact with each other and
thus simulate a real economy. It use object-oriented programming to execute
economic decisions within agents, which are based on behavioural rules rather
than on explicit optimization. The aggregate functions in the economy are
then calculated through simple summing or averaging. For further details on
Agent-based modelling see Tesfatsion and Judd (2006)
Master Thesis Proposal
xii
In the first stage I will replicate the Lengnick (2013) and extend it for the
government sector - who collect taxes and distribute part of it back within the
agents as social transfer. In each month of the simulation (see Lengnick 2013)
they will divide the set of households on deciles and those will get different
amount of social transfers which will correspond to the social benefits income
of the Czech economy. I will try to differentiate between negative income tax
and basic income implementation of the principle.
Afterwards I will replace the social transfers scheme with the basic income
concept. I can actually look on more of them - several different versions are
available in Colombino et al (2010). Using monte-carlo simulations I will study
the influence of basic income introduction on macroeconomic variables (see
Tesfatsion and Judd (2006) and Windrum et al (2007).
Expected Contribution The expected contribution of the thesis is twofold:
First I will study the impact of the basic income scheme on the inflation.
The second contribution is more general - I try to demonstrate that simple
agent-based models can be used for practical policy testing. It does not aim
to replace standard policy methods but it would rather extend them. I would
like to further develop continue with the second contribution during my Ph.D
studies.
Outline
1. Introduction
2. The Basic Income Scheme: introduction to the literature, different concepts and reasoning for introduction
3. Complex Systems and emergent properties in economics
4. Agent-based models: approaches and concrete examples of policy testing
5. Lengnick (2013) model extended for tax collection and social benefits
distribution
6. Basic Income introduction and its effect on inflation
7. Basic Income introduction and its effect on the poorest decile of households
8. Concluding remarks
Master Thesis Proposal
xiii
Core bibliography
Atkinson, Anthony Barnes (1996). ”Public economics in action: the
basic income/flat tax proposal.” OUP Catalogue.
Bergmann, Barbara R. (2004) ”A swedish-style Welfare state or Basic
Income: Which should have Priority?.” Politics & Society 32.1: 107-118.
Colombino, Ugo, et al. (2010) ”Alternative basic income mechanisms:
An evaluation exercise with a microeconometric model.” Basic Income
Studies 5.1.
Dosi, Giovanni, Giorgio Fagiolo, and Andrea Roventini (2010).
”Schumpeter meeting Keynes: A policy-friendly model of endogenous
growth and business cycles.”Journal of Economic Dynamics and Control
34.9: 1748-1767.
Dosi, Giovanni, et al. (2013) ”Income distribution, credit and fiscal policies in an agent-based Keynesian model.” Journal of Economic Dynamics
and Control 37.8: 1598-1625.
Dosi, Giovanni, et al.(2014) ”Micro and Macro Policies in the Keynes
Schumpeter Evolutionary Models.” Available at SSRN.
Fagiolo, Giorgio, and Andrea Roventini(2012). ”Macroeconomic
policy in dsge and agent-based models.” Revue de l’OFCE 5: 67-116.
Farmer, J. Doyne, and Duncan Foley(2009). ”The economy needs
agent-based modelling.” Nature 460.7256: 685-686.
Garfinkel, Irwin, Chien-Chung Huang, and Wendy Naidich (2006).
”The effects of a basic income guarantee on poverty and income distribution.” Redesigning distribution 117.
Gilbert, Nigel, and Pietro Terna (2000). ”How to build and use
agent-based models in social science.” Mind & Society 1.1: 57-72.
Harvey, Philip L.(2006) ”The relative cost of a universal basic income and
a negative income tax.” Basic Income Studies 1.2.
LeBaron, Blake. (2000) ”Agent-based computational finance: Suggested
readings and early research.” Journal of Economic Dynamics and Control
24.5: 679-702.
Master Thesis Proposal
xiv
Lengnick, Matthias. (2013) ”Agent-based macroeconomics: A baseline
model.” Journal of Economic Behavior & Organization 86: 102-120.
Leombruni, Roberto, and Matteo Richiardi(2005). ”Why are economists
sceptical about agent-based simulations?.” Physica A: Statistical Mechanics and its Applications 355.1: 103-109.
Moffitt, Robert A. (2003) The negative income tax and the evolution of
US welfare policy. No. w9751. National Bureau of Economic Research.
Pech, Wesley J.(2010) ”Behavioral economics and the basic income guarantee.”Basic Income Studies 5.2.
Tesfatsion, Leigh, and Kenneth L. Judd, eds.(2006) Handbook of
computational economics: agent-based computational economics. Vol.
2. Elsevier.
The Guardian (2015, December 26). Dutch city plans to pay citizens a
’basic income’, and Greens say it could work in the UK. Retrieved March
01, 2016, from http://www.theguardian.com/world/2015/dec/26/dutchcity-utrecht-basic-income-uk-greens
Tcherneva, Pavlina R.(2007) ”What are the relative macroeconomic merits and environmental impacts of direct job creation and basic income
guarantees?.”.
Van Parijs, Philippe.(2004) ”Basic income: a simple and powerful idea
for the twenty-first century.” Politics & Society 32.1: 7-39.
Windrum, Paul, Giorgio Fagiolo, and Alessio Moneta (2007).
”Empirical validation of agent-based models: Alternatives and prospects.”
Journal of Artificial Societies and Social Simulation 10.2: 8.
World Economic Forum. (2015, December 10). Finland’s basic income experiment - can it work? Retrieved March 01, 2016, from http://www.weforum.org/ag
basic-income/
Author
Supervisor
Chapter 1
Introduction
”The question is a simple one: if in the future robots take most people’s jobs,
how will human beings eat?” (Hughes 2014, p. 1). The current discussion about
a radical reform of welfare programs is closely connected with the technological
development. Similarly as during the previous technological revolutions (see
Perez (2009)) there are serious concerns about the demand for labour in the
future (see Ford & Cummings (2015)). Predictions of the jobless future have
been on the place before and in the end turned out to be false, but there exists
serious reasons why not to reject the possibility of technological unemployment
immediately (see Walker (2014)). The Basic Income (BI) is proposed as at
least a partial solution to the problem. The income would provide the jobless
citizens with the amount of money necessary to survive.
Introduction of the basic income concept is a radical reform which would
cause many changes in the society. Obvious is redistribution effect, which is a
primary function of any social policy, and funding. BI is often mentioned as
a serious threat on a labour supply, as BI can cause decrease of incentives to
work. But the main goal of this work is to describe the potential effect on price
level, caused by redistribution of wealth.
In the recent years the basic income gains political interest in Europe there was a referendum in Switzerland, serious political proposals are discussed
also in Finland and Netherlands. That is the major reason why studying the
possible link between price level and policy is relevant. The transition between
the standard social security scheme which is used in the European countries
and the scheme based on the BI proposal is a very sensitive issue, especially
for those who in some extent depend on the recent social system.
If introduced, any basic income scheme would be affecting the situation of
1. Introduction
2
the poorest members of the society. Those are the people that are probably receiving some transfers from the existing social system. The introduction of the
basic income thus impose a serious threat for their income. The exact outcome
of the BI introduction however largely depends on the detailed parameters of
the proposal which is beyond the scope of this work. But if possible changes
in the aggregate demand and subsequently on prices would be predicted in advance relevant policy makers (especially social policy, but also central bankers)
could incorporate it in their expectations. The consequences of aggregate demand changes would also have implications for other actors, both in the public
and private sector. To the knowledge of the author, there is no paper studying
the possible relationship between the two.
The concavity of consumption function suggests that possible large changes
in the redistribution schemes might result in changes of the aggregate demand
and subsequently on the price level. The goal of this work is to verify the
possible link between social transfers regime and price level. If the link was
proved, the policy recommendation would be clear - decision-makers proposing
the transition between standard social regime and basic income should take
into account not only nominal monetary value of the basic income introduction,
but also the possible influence on real purchasing power of households. Possible
inflationary pressures would be relevant for the central bank.
The hypothesized direction of the price-level effect depends on the redistribution. If, in comparison with the standard social security, the basic income
introduction would lead to redistribution from the rich people to the poor, than
it would lead to pressures on increasing prices. On the other hand, if it went
opposite direction, the BI introduction would create a pressure on lowering
prices.
The redistribution effect of the BI is closely connected with financing - the
way how the taxes financing the BI are collected is a crucial factor for the net
redistribution effect. For simplicity I neglect the financing issue in the model the tax collection would stay the same under both social distribution regimes.
Not surprisingly there is higher amount of eligible receivers under the basic
income regime. Therefore I study the situation of redistribution from poor to
wealthy households.
The agent-based model (ABM) framework can be used as a tool for policytesting macro relations. Important feature of this class of models is its ability
to capture non-linear emergent phenomena. The economy is a typical example of a complex system. Very important aspect of every complex system is
1. Introduction
3
complicated, non-linear relationship between the behaviour of individuals and
aggregate patterns. The relationship between micro and macro-behaviour can
be much more complicated than traditionally expected linear scaling.
The price generating mechanism is a also an example of y complex process every agent decides their prices on based local information and interactions with
its peers. In this way the agents ’learn’ about what price is beneficial for them.
Price-generating process in the ABM framework allows for local informations
as an input into the analysis.
Bonabeau (2002) calls the data-generating process of ABM as natural description of the system (p.7280). In macroeconomic models the data-generating
process is similar to the real world - the computer simulates individuals, whose
actions then sum-up to aggregate variables. As a side effect, it allows the researcher to study both individual micro data and aggregate data in a single
model.
The benefits of ABM can be named also as its main limiting factors. The
simulated micro-interaction can have a wide variety of forms and researcher face
large number of degrees of freedom to choose from. Although the ABM allows to
study price-generating mechanism based on local information, the researcher
does not know how exactly how the local information is distributed within
the economy. The conclusions drawn from the ABM models should ideally be
supported by a variety of different ABM models, other class of models or even
empirical studies.
In this work the adjusted version of Lengnick (2013) is used. The model is
extended for government collecting taxes and distributing them within households. Moreover the capital market was extended to try to control for level of
inequalities in the economy, which is a key factor for realistic policy-testing.
Unfortunately, the strong deterministic trend in the model does not allow for
effective control of inequalities in the economy.
The results of the simulation do indicate any sign of the possible relation
between the basic income introduction and the price-level. The transfer distribution regime affects the aggregate demand ’long’ cyclic component, but
unfortunately does not show any systematic changes in the direction of price
level.
The structure of the thesis is as follows: In the chapter 2 the basic income
concept, its definition and important factors of redistribution effects are described. The context of BI introduction is provided by describing several recent
basic income proposals. Chapter 3 describes the major properties of the ABM.
1. Introduction
4
What component does it usually have and how it can be used. Emphasize is
given to the usage of ABM for macroeconomics and policy-testing. Chapter 4
describes the Lengnick (2013) model and its extension. The next chapter 5
covers the model calibration and simulation results. The discussion summarize results and suggest some future research proposals. The last chapter 6
concludes the thesis.
Chapter 2
Basic income concept
The possible link between the price level and the basic income would be very
sensitive on parameters of the proposed scheme. Generally, social transfers are
closely linked to taxation, since both of them affect the net income of treated
individual. The proposal connected with flat tax would affect the households
incomes differently, than the same one connected with strongly progressive tax
scheme.
Costs and redistribution effects on the society depend on the distribution of
wealth within the society. Both outcome and the costs of any proposed schemes
would be similar in the equal society, than in the society where exists a wide
gap between poor and rich members of the society.
2.1
Definition of basic income
Before proceeding to the deeper analysis it is necessary to define the basic
income. Phillipe Van Parijs, one of the leaders of the recent BI movement
use this definition of basic income: ”A basic income is an income paid by a
political community to all its members on an individual basis, without means
test or work requirement.” (Van Parijs 2004, p. 4). The BIEN network who
serves as a platform to promote basic income internationally adopted the same
definition, but in 2014 they have extended it: ”BI should be high enough to live
in dignity and with full participation in society” BIEN (2014).
There are several dimensions in the definition. The most important is universality connected with unconditionality - the basic income policies are typical
with broad scope. The basic income is proposed as a right - both rich and poor,
both hard-working self-made men and the people with low motivations to work
2. Basic income concept
6
are eligible for the transfer. It is also unconditional - every recipient just get
the BI, no matter whether he works or how he lives.
But the individual proposals differ in the definition of the recipient. There
are serious issues about eligibility of children, students, retired, non-citizens of
the political community etc. In the simplified model framework every household
represents a single potential worker and is eligible for the basic income.
Basic income introduction is also usually connected with at least partial
abolition of an existing social scheme (Van Parijs 2004, p.9). This step is
straightforward - it would be very hard to finance even itself, together with
existing social security measures it is not realizable. Moreover the BI is often
proposed to eliminate the problems with existing social schemes, mainly unemployment trap. But in the situation of limited access to finance, the transition
process between the two systems would be very hard to balance such, that the
poor people does not get hurt. This is where the topic of the price dynamics
becomes important - if the occurrence of increasing price level or inflation was
probable, the transition process must take it to account.
Van Parijs (2004) also extends the definition with technical details: Basic
income should be paid on regular basis. In the model derived model, the
social benefits (either standard social security or basic income) that will be
paid monthly. It will also be financed solely from direct income taxes imposed
on firms and workers and collected from the central state level. There is no
consumption tax in the model.
2.1.1
Basic income and price level
The central question of the thesis is possible effect of BI introduction on the
price level, channelled through aggregate demand (AD). To my knowledge,
there is no paper which study the causal link between the two.
The effect can be at least partially explained by the idea of concave consumption function. This idea is rooted already in Keynes’s The General Theory of Employment, Interest and Money. Keynes writes explicitly that ”... the
marginal propensity to consume [is] weaker in a wealthy community (Keynes
2007, p.28). The argument is simple - the higher the income of the household,
the lower the portion the individual would consume. Souleles (1999) have found
the relationship between income and the marginal propensity to consume on
the micro-data of tax refunds. The theoretical background is also available in
Carroll & Kimball (1996).
2. Basic income concept
7
But the question remains - why should concave function imply inflationary
pressures in the economy? The link is a demand channel - if the BI introduction
would lead to redistribution from wealthier towards poorer households than it
would lead to higher aggregate consumption. The higher demand on firms
would then lead to higher prices.
The strength of a relationship again depends on the size of redistribution
effects. If only a small amount of money was redistributed within the society,
than there would be only a small effect. The introduction of basic income
would have stronger price level effect in the more unequal societies than in the
equal societies.
The other factor that would influence the size of the effect is the difference
between marginal propensity to save between the rich and poor households. If
the rich households would save larger part of their wealth than poor households,
then it would lead to larger difference in the aggregate demand.
The size of the effect is also affected by the distribution of income within
the society - the larger the difference between poor and rich households, the
higher influence it would have on the aggregate demand.
The former can be summarized in following hypotheses:
ˆ H1: If the introduction of basic income would cause the redistribution
from rich to poor, than it would lead to higher price level in the economy.
Otherwise it would to cause pressures on lower prices.
ˆ H2: The larger amount of money is redistributed within the economy,
the larger effect on price level.
ˆ H3: The higher difference in propensity to save between rich and poor,
the larger effect on price level can be expected.
ˆ H4: The economy with more unequal wealth distribution would see stronger
price level effects than the one with more equal distribution.
2.1.2
Proposed schemes
Since BI is a very general concept there exists a wide variety of different implementation proposals. In what follows three descriptive examples according to
(Van Parijs 2004, p.31 - 37) will be briefly introduced. The basic income might
be seen as a special case of a broader concept of Negative income tax (NIT).
For illustration I will compare both of them to the minimum guarantee scheme
2. Basic income concept
8
Figure 2.1: Basic income implementation schemes
a) Minimum guaranteed income
Net income
b) Basic income combined with flat tax c) Nonlinear negative income tax
Net income
Net income
NI
NI
NI
G
G
G
T
Gross income
T
Gross income
T
Gross income
Source: Van Parijs (2004)
as well. All the presented concepts are just theoretical - in practice the net
income of the receivers of social security is much more complicated.
For evaluation of the efficiency of the social system it is useful to compare
with the no system - the situation with no transfers, no redistribution and
no taxes financing the social system. This rather hypothetical situation can
provide useful information about how much actually the agents involved in the
system gain from it or how much do they pay. The net position of households
towards the hypothetical no system is called net income and is depicted on
figure 2.1.
The comparison of the proposed system with old social system, that is
being replaced, would give us an insight about the relative costs and effect of
the proposed system. The potential transition costs are especially relevant for
policy makers who propose the new system, because those are the money they
have to add to (or subtract from) the system to make it work.
To understand how the basic income works in practice it is useful to start
with what is not a basic income - the minimum income guarantee is often used
for example with the unemployment benefits - benefits that are paid only if
the recipient does not work. Those systems are providing an income to those
’in need’ and break the condition of universality. In the moment when the
individual exceeds an income G he will start paying taxes and lose the right
to get the income. This is problematic, if the recipients do not expect to get a
well paid job, they would have a very low incentive to look for any, since the
marginal revenue from finding an employment is rather small. Social systems
thus may contribute for creating unemployment trap. ”[Unemployment trap]
consists in the lack of a significant positive income differential between no work
and low-paid work” (Van Parijs 2004, p. 9).
The tipping point which affect the work incentives may be removed in the
2. Basic income concept
9
scheme. As it might be seen in the figure 2.1, in the context of basic income
there is no ’break’ of N I and people’s motivation to work does not have to be
harmed.
The simplest case of the BI is basic income combined with flat personal tax.
Those who do not earn any income would just get a transfer of G, on the other
hand they will be taken no taxes. Their net income is exactly G. With any
income they get, it will be taxed a tax rate τ , which may be seen in the figure
as the slope of the net income line N I.
It can be clearly seen from the figure that basic income is connected with
greater amount of redistribution - the break-even moment T of agent who gets
the same amount as he earns is much higher in the case of BI, than in the case of
minimum guarantee. Not surprisingly, the basic income is much more expansive
instrument than minimum guarantee (neglecting administration costs) - not
only the poor, but everyone gets transfer and in most cases it has to be financed
through taxes.
In terms of the net income the basic income is just a special case of a broader
concept of negative income tax. The social transfer in this sense is basically the
same as the tax debt relief. People with no income would get a basic transfer
(or tax return) G. The additional income would then be taxed by the rate of
benefit withdrawal β ≥ τ until the threshold level of gross income T . After
the threshold level the tax τ is levied as in the previous cases. If τ = β then
negative income tax has the same effect as the basic income. This situation is
called linear negative income tax. Otherwise it is non-linear.
Because BI proposals have not been introduced in a full-scale manner yet
its consequences are highly uncertain. But still there are some obvious issues
that has to be discussed when proposing any BI . Some of them are basically
the reason why the BI is proposed, others are taken as a ’necessary evil ’.
BI
2.1.3
Financing challenge
The basic income is often proposed as a very futuristic concept - as a tool for
handling issues connected with the effects of automation and high productivity
linked to high inequalities in the society. Especially for financing issue, for
which the high productivity might become the key factor that allows for BI
introduction. This always has to be taken in account when thinking about the
BI.
There are basically two options of financing - either from taxes or from
2. Basic income concept
10
large-scale resources available for the community (such as oil revenues). Unfortunately, the latter is in the most cases unavailable. Van Parijs (2004) also
mentions alternative financing proposals such as money creation, but those will
be neglected in the thesis.
BI introduction can lead to a significant decrease of the administration
costs - the universality principle do not require controlling mechanisms testing whether the transfers are not abused. But the administration costs would
probably not lead to such savings, that would allow to significantly decrease
the tax funding. In the case of Czech Republic more than 90 % of the budget
for Ministry of Labour and Social Affairs is spent directly on transfers (see
Parlament ČR (2016)).
The financing challenge can be well illustrated on the figure 2.1. The overall
costs are always the area C = 0GT −AS, where AS is savings from administration costs and the rest is depicted on the picture. The 45 degrees dashed line
shows the distribution of incomes (in this case uniform) with no taxes and redistribution. The costs of BI introduction are then those where N I line is above
the 45-degrees line. On the other hand, revenues necessary for sustainable financing is at least the same area in reverse situation - when the 45-degrees line
is above the N I line. When the difference between net and gross income is positive, the individual gets additional transfer, which impose costs for financing.
When the difference is negative, the individual is taxed. The amount of collected taxes then must be at least equal to the costs, to create a self-financing
system.
In other words the tax revenues area must be greater or equal than the
cost area. It is clearly visible from the figure 2.1, that the financing issue
is problematic in case of BI combined with flat tax. Non-linear negative tax
can make the system cheaper, but still more expansive than the minimum
guarantee.
The financing challenge must also take into account its dynamics. If the BI
introduction implied slowing down economic activity due to the increasing tax
leverage or negative effect on the labour supply (see below), it would lead to
further challenges and the whole system could effectively collapse even if the
financing issues were sufficient in static terms.
The potential effect on price level and AD would make the situation even
more complicated. The increased price level (in case of redistribution from
wealthy towards poor) would cause reduction in the purchasing power of households.
2. Basic income concept
11
Financing is a key factor, but it is not a main goal of this work. For
simplicity the financing issue is almost neglected. The transition costs between
the ’old’ social security and the BI proposal are supposed to be 0. Assuming
that ’old’ social security aims at rather poor households, it automatically leads
to the redistribution from poor to wealthier households - the poorer households
must leave part of the benefits they get in the old system to the wealthier.
According to H1 the introduction of the BI scheme would decrease the price
level. Although most of the proposals try to avoid the situation that would
lead to significant decrease of transfers for the poorest1 , it does not make a
significant problem since the focus of this work is isolating the price level effect
itself, not in the particular direction. The concave consumption function imply
that it is reasonable to suppose that if there exists a strong decrease after the
BI introduction that leads to redistribution from poor to wealthy people, there
would also exist the opposite effect if the transfers were redistributed from
wealthy to poor.
2.1.4
Redistribution effects
Naturally, the main argument for introduction of any social policy reform is
its redistribution effect. Strictly speaking the amount of money redistributed
should be exactly the same as the costs of financing less administration costs.
The key factor for the redistribution effect is distribution of wealth and income
within the society.
In terms of the developed world the BI is suggested as an alternative to an
existing social security scheme. This is the main reason why the policy-makers
must take into account the effect of BI on the wealth of the poorer people.
This can be illustrated on the model of BI with flat tax rate. If the size of
the transfer GSS was smaller, than existing social transfers that are going to
be replaced it would actually hurt the those with N I + GSS < GBI . Not only
G, but also the tax rate, which determines the slope of the net income line N I
is important since it affects N I. This point is obvious, but its a point, that
makes BI introduction very sensitive on technical parameters of the system.
The simplified proposals described earlier in this chapter neglect another
important aspect of the BI - sensitivity on distribution of wealth and income
in the society. The model depicted on the figure 2.1 assumes the uniform
1
18).
This is why most proposals are connected with progressive taxation (Van Parijs 2004, p.
2. Basic income concept
12
distribution of gross income within the society. But this assumptions is far
from reality. In fact, the distribution would certainly be much closer to normal
distribution.
In practice the distribution is often skewed towards less income groups (see
for example Italian case in Brandolini et al. (2006)). In other words, there is
more people getting wage from the lowest decile of wages, than those getting
the highest decile. For details on income distribution see Keeley (2015).
There is a difference between the distribution of income and distribution of
wealth in the society. The difference is based on history of past incomes and
historical social situation. In most cases the existing social benefits are based
on testing monthly income rather than wealth. In practice the two distribution
are very similar (see again Brandolini et al. (2006)). For simplicity this work
will differentiate between poor and rich based on their wealth, not their income.
Figure 2.2 shows, that financing and redistribution can be seen as two side of
the same coin. The closer to uniform distribution, the more expansive in terms
of overall costs the system would be. However, by the same logic, it would also
lead to much larger redistribution. This results from the fact that in uniform
distribution, there is a large number of extremely poor and extremely rich
households. Uniform distribution of wealth implies very weak middle class and
strong extremes. The effect on aggregate demand would be very strong and so
would be the effect on price level.
The existence of strong middle class, characteristic for most (if not all)
economies implies much smaller need of financing (and smaller redistribution
effect). The net income of the middle income households is much smaller than
of those in the extremes. If there is strong middle class there is not such a
strong need for redistribution. That would significantly decrease the effect on
aggregate demand and on the price level.
But different distributions can also differ with variance. In other words, if
there is a larger difference between wealthy and poor members of the society
and stronger effect on price level can be expected. On the other hand very
equal societies redistribute only small amount of wealth and the effect would
be rather small.
Left skewed income distribution leads to greater concentration of income
at the bottom side. Those would decrease the tax collection and increase the
transfers needed to finance the BI). It would imply either lower basic income
transfer G or higher funding required to finance it.
2. Basic income concept
13
Figure 2.2: The effect of income distribution on BI
a) Income distribution
Frequency
b) Net income
Net income
G
Gross income
Gross income
Source: author, the figure is only illustrative
2.1.5
Labour supply
The effect on labour supply is the key issue for the sustainability of the basic income. The potential effect of BI or NIT is twofold. Friedman express
it illustratively: ”Like any other measures to alleviate poverty, it reduces the
incentives of those helped to help themselves, but it does not eliminate that
incentive entirely, as a system of supplementing incomes up to some fixed minimum would. An extra dollar earned always means more money available for
expenditure” (Friedman 2009, p. 158). There are two possible effects on labour
supply, one offsetting each other.
a) The BI might lead to decreasing the labour supply itself. i.e. move the
labour supply curve lower. The people would be granted an income, no matter
whether they work or not and part of the population might choose to work less
or not to work at all.
b) The BI might limit the unemployment trap problem and smooth the
labour supply curve. The condition of universality implies that the system
would not create disincentives to look for a job. But this holds only in situation
where the relationship between marginal income and labour supply was linear,
which might turn-out to be an oversimplifying assumption.
Although it is one of the most controversial elements of the BI introduction,
the effect on labour supply is not discussed in this work. If there existed a
significant detrimental effect on labour supply according to a), it would cause a
decrease of aggregate demand. This effect would be asymmetric because much
higher disincentive to work are for the poor. However that would affect not
only labour supply, but also financing and probably the economy performance
2. Basic income concept
14
itself.
2.2
Examples of basic income
The main reason of studying policy implications of BI is the growing political
movement supporting it, at least in Europe. The reform proposals are discussed
in most of the European countries and in some cases the BI reforms are proposed
even by administration. The introduction of BI policies is becoming a highly
recent topic which has to be discussed in detail. There also already works
a scheme which is very similar to the BI in Alaska, but it is financed from
oil revenues, which puts it in slightly different context. Several basic income
experiments such as the one in Manitoba (seeHum & Simpson (2001)) show
strong interest about the issue of basic income might become real no matter
whether its desirable or not.
Alaska
Alaska use their natural resources to finance the scheme, which is based on the
BI principle already for more than 30 years. The oil dividend scheme distributes
the revenues from the natural resources among all citizens of Alaska including
children, with exemption of convicted criminals and people in prison. The Permanent Fund have been established in 1976. ”The Constitutional amendment
establishing the permanent Fund required that at least 25 % percent of the royalties collected from the sale of all state owned resources would be deposited
into the fund, that the fund would invest only in income producing assets and
that only fund earnings, but never fund principal, could be spent.” (Goldsmith
2002, p.1)
This scheme thus clearly fulfils the definition of basic income. The dividend
amount calculation2 is subject to strict rules and depends mainly on the fund
performance over the five years. The amount of dividend is changing based on
the revenues of the oil industry - see figure 2.3.
Recent efforts in the EU
Recently there is a wave of increased interest about the possibility of BI introduction in Europe. Utrecht and several towns have announced a plan ”taking
2
see http://www.apfc.org/home/Content/dividend/dividend.cfm
2. Basic income concept
15
Figure 2.3: Alaska permanent fund dividend
$2 500
$2 000
$1 500
$1 000
$500
$0
1982
1986
1990
1994
1998
2002
2006
2010
2014
Source:APF (2016)
a ’small step’ towards a basic income for all by allowing small groups of benefit claimants to be paid £660 a month” (Boffey 2015). Similarly ”around
10,000 people in Finland could soon be paid ¿550 each month if the government goes ahead with a universal basic income pilot project.”(Rosamond &
Armbrecht 2016). Very recently, ”Switzerland has turned its back on a basic
income scheme, in which the federal government would have given every resident a monthly payment - expected to be around 2500 Swiss Francs ($2,500) ’regardless of their income and assets’” (Rosamond & Armbrecht 2016).
The BI is clearly a strengthening political issue, which can find a political
support. No matter of the personal opinion on the issue it is better to think in
advance about its consequences.
2.3
Evaluations of the BI introduction
The effect that BI or NIT would have on the society is far from being clear. The
literature is limited by two factors: high diversity in existing proposal and the
lack of well-prepared experiment with valid detailed micro-data.
Moreover the price level is highly macroeconomic phenomena, which is very
hard to test on micro-data. This makes a big problem - there is only one
country in the world that runs a scheme similar to BI and this country is quite
specific. The test with one only observation would not be valid. That may be
one of the reason why, to my knowledge, there is no paper studying the link
between price level and the basic income.
At least partial solution to the problem is simulation. The simulation is
2. Basic income concept
16
often used to test the possible consequences of the BI introduction. Colombino
et al. (2010) use an EUROMOD tax-benefit simulation to test the consequences
of the introduction of BI. Micro-simulation calibrated for particular countries
provide a very useful tool for social and tax policy testing. Unfortunately, the
EUROMOD model is not calibrated to test the effect on inflation and pricelevel.
There is a large difference in BI for developed and developing countries.
While in developed countries the BI is introduced to replace the existing social
system, the situation in poor countries might be very different. In my work,
I will focus more strongly on developed countries, but because the scarcity of
literature is quite severe in some cases I will also the sources aimed on the
developing countries.
For the context of Europe there is very scarce information on costs and
redistribution effects of replacement of recent social scheme (which in such
extent does not exist anywhere else in the world) with BI. The impact of
universal cash transfers on eliminating poverty in some developing countries will
be rather neglected, since the situation is radically different from the European
context. For more information on developing countries and BI see Widerquist
et al. (2013).
2.3.1
Labour supply
As it was mention in ??, there are two effects the unconditional transfers may
have on the supply curve of the individuals - the transfer can move the curve
itself, but it can also contribute to removing the problem of unemployment
trap.
The only paper found dealing with the labour supply in European context
is already mentioned Colombino et al. (2010). They used EUROMOD model
to estimate the effect of BI introduction in four European countries - Denmark,
UK, Italy and Portugal. Although they found some evidence that labour supply
might be decreased, this evidence is not clear - in some cases, BI can even
increased the labour supply. Potential labour supply estimates do not expect
strong strong changes, that would cause severe consequences.
The influence on labour supply is rather neglected in the case of Alaska
as well: ”Initially there was some interest in the effect of the dividend on
the supply of labour, but there have been no studies of this effect, which from
casual observation appears to be small...But it does raise the possibility that the
2. Basic income concept
17
apparent higher incomes from the dividend are being partially offset by lower
real wage rates.”(Goldsmith 2002, p. 10). But this claim is not supported by
any empirical evidence.
Mideros & O’Donoghue (2015) use a unitary discrete labour supply model
to test the introduction of BI. They argue that there is ”no negative income
effect of social transfers on poor adults because leisure could not be assumed
to be a normal good under such conditions”. They have also provided some
empirical validation on data from Ecuador: ”cash transfers, unconditional in
labor, does not produce labor disincentives in the case of household heads, but
may be paying for housework and childcare provided by partners and single
adults.” (p.225). Also in India ”the grants led to more labor and work ...
There was a shift from casual wage labor to more own-account (self-employed)
farming and business activity, with less distress-driven out-migration. Women
gained more than men.” (Standing 2013, p. 3)
Mentioned studies do net expect severe consequences of BI on the labour
supplies. However testing of such paradigm shifting proposal such as basic
income can be tricky and those results must be interpreted carefully.
2.3.2
Redistribution
Naturally, the large attention is focused on the redistribution effects of the
possible BI introduction. According to Malul et al. (2009) the large scale BI
in Israel ”could decrease poverty incidence in relation to the existing poverty
line by 100 %” It might also be connected with substantial decline in inequality (measured by Gini coefficient) (p. 16). However it would be connected
with enormous costs and create immense and dangerous pressures on Israeli
economy. Also an alternative proposal of taxed BI ”would offer a more efficient decrease in poverty and inequality, but would also entail a problematic
economic burden in the Israeli case.” (Malul et al. 2009, p.16)
The simulation of redistribution effects have also been conducted by Colombino et al. (2010): ”... four general suggestions emerge rather clearly: i) the
universal policies tend to show a better performance; ii) the progressive tax
rules seem able to exploit more efficiently the pattern of behavioral responses;
iii) there is very large policy space in every country for improving upon the
current status; iv) there are significant differences across countries in the performance of tax-transfer reforms.” (Colombino et al. 2010, p. 10).
Also another simulation is favour with non-conditional transfers: ”The BIG
2. Basic income concept
18
plans we simulate decrease poverty more effectively than the current system.
This highlights the fact that some of the benefits in the current system, such
as tax expenditures favor the rich instead of the poor or the middle class. All
the BIG plans redistribute income from the highest quintiles to the lower ones”
(Garfinkel et al. 2003, p. 131).
2.3.3
Financing
The financing is a key issue for viability of BI proposals - definitely, the BI is a
costly measure. The calculation by Malul et al. (2009) are estimating the costs
of full BI scheme to be around 17 - 20 % of GDP. Thus, the countries which are
not similarly ’lucky’ as Alaska, who have open access to large pool of natural
resources, the financing issue is extremely limiting for any proposal.
The Manitoba experiment shown that ”the ’pure’ BI consisting of a tax free
universal transfer set at the poverty level so as to eliminate poverty completely
is too expensive and politically unacceptable in Canada. Hum & Simpson
(2005).
The more detailed analysis has to depend on the specific proposals, because
BI proposals are very broad and may have substantially different costs and
redistribution impacts.
Chapter 3
Motivation for ABM modeling
3.1
Complexity in economics
The economy is a typical example of a complex system - a system of many
interacting individuals whose outcome cannot be predicted just by studying
the micro-foundations. The complexity results from the local interactions of
many individuals. Those interactions can be very simple, but in large amount
they create very complicated patterns: ”Complexity is ubiquitous in economic
problems ..., since (i) the economy is inherently characterized by the direct
interaction of individuals, and (ii) these individuals have cognitive abilities”
(Gallegati & Kirman 2012, p. 7-8).
The ABM is proposed as an option to deal with the complex phenomena.
Their major benefit is different construction than traditional models. The
latter are built from bottom-up: ”Heavy reliance is placed on extraneous coordination devices such as fixed decision rules, common knowledge assumptions,
representative agents, and imposed market equilibrium constraints.” (Tesfatsion 2002, p.2). The data-generating process (DGP) employed by agent-based
modellers is radically different. The models are built from bottom to up: ”As
in a culture-dish laboratory experiment, the modeller starts by constructing an
economy with an initial population of agents. These agents can include both
economic agents (e.g., traders, financial institutions,...) and agents representing various other social and environmental phenomena (e.g., government, land,
weather,...).”
ABM are built around the rules of interactions between individuals. Thousands and millions of interactions then create a whole system which is studied
using a computational simulation. This is why Bonabeau (2002) calls it a natu-
3. Motivation for ABM modeling
20
ral description of the system and Epstein (1999) use the term generative social
science.
The major difference to traditional models is that agent-based models do
not require a central assumption of the economy converging to equilibrium.
Although equilibrium might occur in the agent-based model, their existence is
rather a consequence of the DGP, then the central assumption as it is in mainstream economics. For more information on equilibrium in the ABM framework
see Arthur (2006).
While neoclassical economics relies heavily on the existence of an equilibrium, which is holding the model together and assures that studied agents are
’behaving properly’. In the case of ABM this role is prescribed to the pathdependence. In every moment of the simulation agents are depending on the
choices they have made earlier in history. Path-dependence is a concept closely
related to evolution and ABM naturally tend to be described as evolutionary
models. ”There is no guarantee that the particular economic outcome selected
from among the many alternatives will be the ”best” one. Furthermore, once
chance economic forces select a particular path, it may become locked in regardless of the advantages of other parts” (Arthur 1990, p. 92). ABM also
allow for strong heterogeneity among agents: ”assumption common to most
studies is that agents differ in the way they react to aggregate patterns; they
have different circumstances, different histories, different psychologies” (Arthur
2006, p.3).
The central motivation for using ABM is very often its ability to capture
non-linearities in the process. The unique DGP allows researcher to study the
emergent phenomena - e.g. how interaction of many subjects can on macro
level lead to outcomes, that are not observed on the micro level. ”Emergent
phenomena result from the interactions of individual entities. By definition,
they cannot be reduced to the system’s parts: the whole is more than the sum
of its parts because of the interactions between the parts.” (Bonabeau 2002,
p.7280).
3.2
Key ABM features
Every agent-based model can be decomposed in three different features: (a)
agents, (b) rules of interaction and (c) environment they are settled in.
3. Motivation for ABM modeling
3.2.1
21
Agents
According to Macal & North (2005) there is no consensus on the definition of
agent, but scholars generally agree that ”the fundamental feature of an agent is
the capability of the component to make independent decisions. This requires
agents to be active rather than passive”. Agents typically tend to have following
features (p. 74):
ˆ An agent is identifiable, a discrete individual with a set of characteristics
and rules governing its behaviours and decision-making capability
ˆ An agent is situated, living in an environment with which it interacts
along with other agents.
ˆ An agent may be goal-directed, having goals to achieve (not necessarily
objectives to maximize) with respect to its behaviours.
ˆ An agent is autonomous and self-directed. An agent can function inde-
pendently in its environment and in its dealings with other agents
ˆ An agent is flexible, having the ability to learn and adapt its behaviours
based on experience
3.2.2
Rules of interaction
While neoclassical models are typical with full-scale mathematical rationality
imposed on agent, who are thus able to optimize their action, it is usually not
the case in the ABM framework.
Many ABM models adopt some form of bounded rationality (see Dosi et al.
(2001)). There are two reasons why the neoclassical rationality is of limited
use in the ABM framework: (a) information availability and (b) computational
capacity (Epstein 1999, p. 42). Instead of the exact utility function the ABM
modeller rather define how agents react in the specific situations. There exists
a broad range of possible implementations of rules - agents can have static
rules, that do not evolve through time (the case of Lengnick (2013), or their
behaviour can dynamically evolve - agents can learn (for example using genetic
algorithms (Mandel et al. (2010)) or through reinforcement learning (Chan &
Steiglitz (2008)). For details on learning algorithms see Dosi et al. (2001).
3. Motivation for ABM modeling
3.2.3
22
Environment
Environment is basically the institutional design - it is the rules of the game.
There might be a spatial dimension of environment - the limits of which agent
can interact with each other or there can be time dimension - the sequence of
turns during which agents are allowed to perform interactions. Basically environment settles the rules of interaction that are not autonomous to individual
agents.
Environment can also be used as the data input for the analysis. In many
studies the spatial environment (or the ’topology’) is some kind of geographical structure - such as road and urban infrastructure (see Batty (2007)) or the
electricity network (Weidlich & Veit (2008a)). In many application the market structure determines the interactions opportunities - for example on the
financial markets (Samanidou et al. (2007) or a trading network in Lengnick
(2013).
3.2.4
Building a model
Macal & North (2005) provides a tutorial with a very brief general procedure
for building an agent based model:
1. Agents: Identify the agent types and other objects (classes) along with
their attribute
2. Environment: Define the environment the agents will live in and interact
with.
3. Agent Methods: Specify the methods by which agent attributes are updated in response to either agent-to-agent interactions or agent interactions with the environment.
4. Agent Interactions: Add the methods that control which agents interact,
when they interact, and how they interact during the simulation
5. Implementation: Implement the agent model in computational software.
(Macal & North 2005, p. 78)
3. Motivation for ABM modeling
3.3
23
Agent-based macroeconomics
Since the fall of Lehman Brothers, the economists are widely criticized for
failing to predict the financial crisis. This is why there is a growing interest
in exploiting agent-based models potential for studying macroeconomics (see
Farmer & Foley (2009) or The Economist (2010)).
The ABM models roughly divide into two categories: ”The first one tries to
mimic real world economies in a highly detailed way. The large-scale agentbased model is developed in the EURACE project, that model European economy1 . ... At the same time, the need for massive computational power and the
high demand of computational skills generate practical problems for economists
to replicate or advance the models like EURACE. The second category consists of stylized models that abstract from real economies in a number of ways.
They only contain a small number of different agent types and interaction rules”
(Lengnick 2013, p.5). For obvious reasons, I will follow the latter methodology
in my work.
Very good illustration of the recent progress can be seen in the two reviews
of the agent-based macroeconomics available from the same author - there is
one from 2003 and the other is from 2016 (see Chen (2003) and Chen (2016)).
In the former, there is no ’truly’ macroeconomic model mentioned - ie. the
models are not able to simulate the economy as a whole, there are only models
aiming at rather specific macroeconomic problems - such as inflation (Arifovic
(1995)) or exchange rate Arifovic (1996). But in the recent review, there is
13 such complex models and the review is not complete - it aims explicitly to
search for a minimal model described below.
Searching of a minimal macroeconomic model is an important challenge of
the emerging field: ”Perhaps the first step is to come up with a minimal model
as a benchmark and then to include additional features when needed. Hence
the first question placed in this line of research is: What are the minimal
elements? or What is the minimal model? ” (Chen 2016, p.73). Not only it
is one of the goals necessary for successful establishment of the agent-based
macroeconomics, but it is also a starting point for finding a suitable model for
policy-testing. Some of minimal models candidates will also be described here.
The simplest macroeconomic model is presented by Wright (2005). There is
only one type of agents who consume, employ and can be employed. Agents are
divided to three types: workers, capitalists and unemployed. The interaction
1
For details see Deissenberg et al. (2008)
3. Motivation for ABM modeling
24
rules are based on the random actions rather than behavioural heuristics or
even optimization. The agents behaviour is very close to the zero-intelligence
agents. But still, the model is able to replicate many macro-stylized facts such
the distribution of firm size or of GDP growth.
Lengnick (2013), a model used in this paper, was constructed to be used as
a benchmark model. It simulates a simple two-sector economy, where firms are
hiring households to produce a single good. The labour and goods market are
fully decentralized the both households and firms rely on the local information
only. The capital market in this model does not exist in a strict sense, the firms
profits are distributed centrally as an automated process based on the wealth
of receiving households. The model is described in detail in chapter 4.
Dosi et al. (2013) constructed the model well-grounded in a standard economic theory - it incorporates Schumpeterian terms (firms invest in R&D),
Keynesian mechanism of demand (namely the important role of fiscal policy)
and Minskian credit (banks leverage causes the business cycle fluctuations).
The model is also explicitly aimed to serve for policy-testing purposes.
3.4
Price level in ABM
Studying price level and inflation in the ABM framework is logical. Inflation
is definitely a complex phenomena resulting from price generating mechanism
in individual firms based on the local market environment they face to. In
standard neoclassical settings the inflation is a result of Phillips curve or different output gap mechanism. (See for example Basic Neo-Keynesian Model
from Galı́ (2015), the Phillips curve is derived on p. 49). The price-generating
mechanism is based on the aggregate information only. The problematic part
is its usage as an inflation transmission mechanism - inflation process is much
more complicated DGP.
The former is not a rejection of neoclassical approach for modelling macroeconomics. But for deeper understanding of the inflation process one can use
bottom-up approaches such as ABM. Some models are already able to replicate
some inflation stylized facts such as mentioned Phillips curve (Riccetti et al.
(2015); Lengnick (2013)).
The ABM scholars are studying price generating mechanisms at least since
Arifovic (1995). However, hand in hand with ABM macroeconomics, the studying inflation as a macroeconomic phenomenon have started only recently. The
model of Salle et al. (2013) studies the inflation targeting in the ABM. His
3. Motivation for ABM modeling
25
goal is very different from the scope of this work. He tries to mimic standard
Neo-Keynesian Model as close as possible to a standard Neo-Keynesian model
(such as in Galı́ (2015).
Salle et al. (2013) also appreciate the ABM for its ability to capture the
dispersed nature of information. The price generating mechanisms in the ABM
can be based on purely local informations. In standard neo-classical model, the
only information often present on the central level only - the equilibrium. Salle
et al. (2013) is ”characterized by radical uncertainty, in which future paths of
relevant variables cannot be given by standard probability laws. Information
is only local and agents are not aware of other agents’ characteristics and decisions.” This has far reaching consequences - mainly inability to derive optimal
consumption paths given by the usual first order conditions.
3.5
Policy testing in the ABM framework
With no doubt, there is a potential in using ABM to evaluate policies at least
as a supplementary information for standard approaches. As the DGP is radically different to the common policy-testing techniques, it might improve the
robustness of the results or undermine them.
Agent-based models allow to study the economic effects also in the out-ofequilibrium state of the economy: ”A simulation approach allows us to study
the open-ended dynamics (including the transient phase) of the economic system under consideration rather than restrict our attention to the existence and
(local) stability analysis of equilibria or characterizations of limit distributions”
(Dawid & Fagiolo 2008, p. 351).
But there also exist quite serious limitations: (a) problems are connected
with large degrees of freedom, that agents face. Although a modeller can
appreciate freedom to parametrize ’almost anything’, in the policy-testing case
it is often a big problem, because one does not know which setting is the right
one. (b) is a limited access to empirical validation. More information on the
problem of empirical validation can be found in Janssen & Ostrom (2006);
Windrum et al. (2007).
There exist quite large range of literature who use the topology structure as
an input and simulate it to find an effective solution. Such microeconomic studies are simulating an electricity market (Weidlich & Veit (2008b)), land market
(Filatova et al. (2009); Matthews et al. (2007)) or urban infrastructure (Chen
3. Motivation for ABM modeling
26
& Cheng (2010); Schelhorn et al. (1999)). However in abstract macroeconomic
models such detailed topology is not available yet.
Other microeconomic studies employ agent-based models to study labour
market relations. Neugart (2008) creates a simple model where agents are investing in their human capital to be used in specific sectors. He finds that the
government subsidies in training are reducing the outflow of from unemployment to employment. In this study the specific topology - the sectors exist
within a circle network structure, where the training in ’more distant’ sector
than the particular agent is trained in requires higher human capital investment. Network structure of agents can also be used for macroeconomic models
The institutional set-up of particular market is also studied in Mannaro
et al. (2008). In ABM framework they simulate an introduction of Tobin tax
on market where 4 types of agents differ with behaviour: a) Random traders,
b) Fundamental traders, c) Momentum traders and d) Contrarian traders. Extensive simulations showed that transaction tax is connected with increased
volatility and decreased trading volumes.
Also the macroeconomic models presented in the previous section can be
used to study the impact of policies on macroeconomic variables similarly as
is the goal of this work. Dosi et al. (2015) and Dosi et al. (2013) use extended
Keynesian-Schumpeterian model presented earlier to test the impact of crisis
management Europe. Authors show that the model is able to reproduce a
business cycle where GDP is more volatile than consumption and investment
is more volatile than GDP. The latter model is also able to partially control for
the level of inequalities in the economy.
The model of Lengnick & Wohltmann (2012) use a combination of agentbased and neo-keynesian model to examine the relationship between financial
(ABM part) and real sector (NKM part) in the economy. The combined model
shows that market sentiment represented through higher volatility on financial
markets is connected to with greater uncertainty in the real sector and thus
makes the effect of hard shocks less predictable.
Generally ABM models are sensitive on the internal structure of the model,
which is not always obvious. This is the price, that ABM modellers pay for the
ability to capture complex phenomena. Although often the models are able to
replicate many stylized facts such is the case of Dosi et al. (2013) or Lengnick
(2013) it is however not clear from the texts of the papers how for example
the distribution of wealth in the society look like. Thus adopting those models
3. Motivation for ABM modeling
27
is a ’risky business’. The short format of journal articles does not allow to
exhaustively describe all the relevant properties of such complex model.
When the focus of the modeller is not to empirically estimate the size of
particular effect for particular decision making, but rather disclose the theoretical connection which was unclear before, the simplification and functioning of
crucial parts of the models can be satisfying.
Chapter 4
The Model
I will use an existing model to evaluate the impact of the BI introduction. In
this chapter the properties that the model should have are specified. Then the
best suitable model based on those criteria is found and briefly described. The
last section is dedicated to the extension of the model.
4.1
Model selection
The model used for analysing basic income must have the following properties. There are generally two options: either the adopted model would already
have those properties or offers a simple way to implement them within the
model. The theoretical foundations for the price level propagation mechanism
is available in the section 2.1.1.
4.1.1
Desired model properties
ˆ Simplicity - the model should be as simple as possible to avoid the
problem of large number of degrees of freedom. The simpler the model
is, the less sensitive on the detailed parameters it is. That is why I will
restrict the selection on minimal models described in Chen (2016) only.
ˆ Consumption pattern - To affect aggregate demand the model should
reflect the concave consumption function. See section 2.1.1
ˆ Modelling wealth distribution - The model must be able to endo-
genize the wealth distribution in the simplest possible manner, ideally
through one parameter. The ideal candidate for controlling wealth dis-
4. The Model
29
tribution is capital market distributing profits from firms to households
- that should be as simple as possible, but there have to be one.
ˆ Price mechanism - The price setting mechanism should be on the indi-
vidual firm level and reflect the purchasing power of households that are
trading with the household. The model whose price mechanism would
rely on local information would also be preferred, although it is not the
most important aspect.
From all the models presented in Chen (2016) (the table 3.3 summarize a
very good overview) only three models have got into a ’short list’ from which
the used model is selected. I describe the Lengnick (2013), Dosi et al. (2013)
and Kinsella et al. (2010) models and compare them to the selection criteria.
The model of Dosi et al. (2013) have got into short-list for two major benefits
- the explicit aim of the model to be used for policy-testing purposes and its
explicit to ability to control for income distribution. The drawback of the model
is the consumption pattern, where there are no intended savings involved. This
limitation could be corrected in the model.
Very problematic for testing of price level impact is how the model controls
for distribution of wealth in the society - ’price mark-ups’ are used for such
control. Low price mark-ups indicates low profit and the majority of wealth
is distributed through wages. High price mark-ups on the other hand skew
the distribution of wealth to profits. The using of price mechanism itself to
control for distribution of income in the society prevents for using the model
to evaluate the effect of redistribution on price level.
Agent-based model explaining income distribution have been already developed by Kinsella et al. (2010). The households in the model have inmate skills,
which can be invested in and developed to increase the chance on the labour
market. Reportedly, the model also replicates realistic income distribution (p.
37) The model however lacks an explicit pricing mechanism so it cannot be
tested for the purpose of this work.
Lengnick (2013) fulfils all conditions - the model is very simple and understandable, with agents deciding solely on the local information. The capital
market is not operationalized in the agents decision. It is rather an automatic
distribution process, which can be easily adjusted to control for the distribution of dividends between society. Consumption follows the concave shape with
growing wealth and price decision is based solely on the level of inventories and
clearly reflect the demand from households.
4. The Model
30
Figure 4.1: The timeline of agents decisions
Beginning
of month
Firms: set wages, employment and prices
Households: adjust trading relations,
look for jobs and plan consumption
Day 1
Day 2
...
Households: purchase consumption
goods
Firms: produce consumption goods
Day 21
End
of month
Firms: pay wages, distribute profits
Households: adjust reservation wages
Government: collect taxes, distribute
transfers
Next month
Source: author, based on Lengnick (2013) and the own extension of the model
The great benefit of Lengnick (2013) is also its relative simplicity, timing
and modularity which allows to extend it easily, without breaking the logic and
dynamics of the model.
4.2
Model description
The model have been suggested as an attempt to create a baseline macroeconomic model. ”[Model] provides a reasonable starting point for ABM modelling in macroeconomics by developing a minimal model that is able to reproduce some stylized facts such as endogenous business cycles, a Philips curve,
a Beveridge curve, long-run neutrality and short run non-neutrality of money”
(Lengnick 2013, p. 104). The majority of following section is based on Lengnick
(2013).
4. The Model
4.2.1
31
General setting
The agents decision in the model take place in two time levels - on a daily and
monthly basis. Strategic decisions such as planning consumption, labour market or capital market decision take place only once in a month. The purchase
of goods and production happens daily.
On the beginning of the month firms and after them households are randomly chosen to execute their strategic decisions. When they finish, the first
day starts and during the 21 subsequent days both firms and households are
executing their daily operations. On the end of month firms pay wages and
profits and households reflect their labour market status and thus end a month
cycle. In the extension of the model the government operations are added in
the very end of a month cycle. See figure 4.1 for the detailed sequence of events.
The agents are defined through several major properties. For household it
is a reservation wage ωh which describe its minimal claim on labour income
(although in practice it can be lower - see below) and their wealth mh . The
firms also have the liquidity property mf and they set their price of consumption
good pf , wage rate wf and inventories if . The major influencing factor for both
firms and households is the network of relationship they operate within.
There is fixed number of infinitely living agents in the economy - H households and F . Agents are not allowed to have negative wealth and inventories
m, i > 0. Firms are forbidden to fire their last employee. Because of the
production function that would mean death for them practically.
4.2.2
Environment
The topology of the model is directed by networks. There are two types of
networks in the model - the trading relationships network and the labour relationships network. Households can only trade with firms they have a trade
connection with. The network relationship can be established between one
household and one firm. While the number of connections one household can
have is constant (η), firms can have infinite trading connections. During the
medium term the network structure evolves, while the agents learn about their
peers and replace unsatisfying connections with those who better fit their expectations.
At the same time households have separate labour market network. Each
household can only have one job - only one connection with a firm. Similarly
as before the number of connections that firms can have is infinite. With small
4. The Model
32
exception - since the number of both firms and households is fixed and they
neither get born nor die, the firms are forbidden to fire their last employee.
Otherwise the firm would stop producing.
4.2.3
Rules of interaction
The interactions will be described for each agent class separately. Firms start
operating in the model, so they will be described first:
Firms
Beginning of month: Firms do strategic decisions about wages, employment
and prices. Firms increase wages wf if a free position was offered but no worker
was found to accept it. It is decreased if all positions have been filled during
last γ month. The wage adjustment is described in equation 4.1.
wfnew = wfold · (1 ± µ)
µ ∼ U(0,δ)
(4.1)
Price setting and employment decision is both connected to inventories. If
the firms inventories are within the specified range firms do not make any decision. But if the inventories level fall below the satisfying level if a new position
is created. If the inventories are above if , a randomly chosen worker is fired.
While hiring decision is executed immediately, the firing decision takes one
month to take effect. The boundary levels of inventories are decided according
to:
if = φ · dold
f
(4.2)
if = φ · dold
f
(4.3)
where dold
f is the consumption goods demand the firm faced in the last month
and parameters are 0 < φ < φ. The price setting decision is also executed only
if the inventories are outside the satisfying range. If the inventories are below
if the increase in price is considered and if are above if than the firm might
decrease the price. But there are additional conditions. a) The prices be inside
their satisfying range:
pf = ϕ · mcold
f
(4.4)
pf = ϕ · mcold
f
(4.5)
4. The Model
33
where mcold
f are the marginal costs of production function, which is linear
function of wage mcold
f .
b) The new prices are set only with probability θ < 1 and would be derived
similarly as wage adjustment:
pnew
= pold
f
f · (1 ± υ)
υ ∼ U(0,ϑ)
(4.6)
Lapse of a day: During a day firms are just producing goods using a very
simple linear production function:
inew
= iold
f
f + λ · lf
(4.7)
where if are inventories and lf is the number of workers.
End of month: Firms use their liquidity to pay wages to all employed
workers, create a buffer and the rest distribute as a profit dividend through the
capital market. Firms use the same wage for all their workers. The buffer that
is being saved by firms is given relative to total labour costs:
f er
mbuf
= χ · wf lf
f,t
(4.8)
The additional money left above the buffer is distributed among household
as profit. The distribution is described in the separate section 4.2.4.
Households
After firms finish their decision it is households turn to execute their strategic
decisions:
Beginning of month: Households are selected in random order to improve
their trading relationships, look for better jobs and finally plan consumption.
Households can change their trading connections to look for better prices
and also because of inability of firms to deliver the demand. Every month
households with probability ψprice < 1 randomly choose one firm he has a
trading relationship with and one firm he does not have such relationship with.
If the price of the new one is lower than of the old, than the relationship will
be replaced.
If during the last month one or more trading firms did not fully satisfied the
goods demand the household requested, then one of those firms is chosen with
a probability proportional to the extend of this restriction. With probability
4. The Model
34
ψquant < 1 the connection with chosen firm is cancelled and replaced with a
new one.
Every month households might be looking for job. There are three different
regime of the job-searching effort: Unemployed households, households whose
reservation wage ωh is higher than their actual wage wf and the rest. The
job-looking effort is based on two parameters: number of firms to ask for a free
position β and probability of searching in particular month π.
Unemployed person is looking for job certainly (πun = 1) and visit more
firms βun = 7. If the household is employed than the search effort is less
intensive (β<ω , βsat ). The search effort if employed is based on the wage. If
wf < ωh the search effort is higher π<ω . If the person is satisfied with their
job they still might randomly ask for position, but with much lower probability
πsat .
Households also make a strategic decision about consumption and savings.
They allocate part of their wealth based on their individual price level. Those
are just a strategic plan which does not have to be fulfilled - the firm the
household is trading with might fail to satisfy their demand.
Consumption expenditures are concave - they increase with personal wealth,
but at a decaying rate. The consumption function is based on Carroll & Kimball
(1996):
crh =
m α
h
pIh
(4.9)
where mh is the wealth of household and pIh is the average price of the
firms he has a trading relationship with. The consumption is adjusted to avoid
inconsistencies if the fraction was lower than 1:
crh
mh α mh
, I
= min
pIh
ph
(4.10)
Lapse of a day: Every day starts with households trying to fulfil their
demand plans. Households are trying to distribute consumption evenly across
the whole month - they divide their consumption plans to 21 days. They are
cr
not allowed to spent daily more than 21h .
Each household visits randomly chosen firm he has a trading relationship
with to ask for consumption goods. If the firms inventories are high enough
and the household’s liquidity is high enough to buy the goods, the transaction
takes place. If the household cannot afford the planned amount of goods, the
4. The Model
35
demanded amount is lowered to maximum affordable amount mh /pf . If the
firms inventories are not high enough than the amount is limited to the highest
possible amount if . Thus neither firms inventories nor households wealth can
become negative.
If the household did not satisfy her demand fully, she continues with another
firm she has a trading relationship with. This continues until she visits n = 7
firms or at least 95 % of planned consumption is satisfied.
End of month: On the end of month households adjust their expectations
about the wage depending on their current income. If their wage is higher
than their reservation wage wh > ωh then ωh is increased to their the level of
their labour income. If it is lower nothing happens. Households decrease their
reservation wage only if they are unemployed - by κ per month without job.
4.2.4
Capital market and wealth distribution
During the end of a month the firms send part of their wealth to their owners
as a dividend. The capital market is not operationalized as an individual
trading process such consumption goods market or labour market, but rather
as an automatic, aggregate process which is the main channel to control for
inequalities in the society.
The profits are distributed according to the proportion of wealth of households. Each household receives a share of aggregate profits that is proportional
to their current liquidity. Aggregates profits are expressed in equation 4.11:
Π=
F
X
(1 − τF ) · (mf − Bf )
(4.11)
f =1
where Π are aggregate profits that are distributed to households,F is a
number of firms in the economy, τf is a corporate tax rate and mf and Bf are
money holdings and buffer savings respectively.
In the original model of Lengnick (2013) each household gets a share of
profits P rh corresponding to the proportion of the aggregate wealth mh /M .
mh
·Π
P rh =
M
where H is a number of households.
This can be simply generalized to:
M=
H
X
h=1
mh
(4.12)
4. The Model
36
mρh
P rh =
·Π
Mρ
Mρ =
H
X
mρh
(4.13)
h=1
If ρ = 1 the equations 4.12 and 4.13 are equal. But if ρ < 1 than it would
distribute the capital among households more equally. If ρ > 1 then richest
households would get higher portion of the aggregate profits and inequality in
the economy would be increased.
Thus we could get a way to control a distribution of wealth in the simulated
economy, which could be used for example to calibrate the model for specific
countries.
4.2.5
Government
The extension of this work is adding a government who collect taxes and distribute social transfers, either in a form of the BI, which is the same for all
households or standard social scheme which is distributed according to the
wealth of a receiver.
The government is the specific agent who is alone in the economy and he
is always called on the end of month to collect the taxes and immediately distribute it. Government is not involved to any other fiscal or monetary activities.
It is always strictly fiscally neutral - it does not produce neither surplus nor
deficit. It does not create any additional wealth neither. Its only goal is to
redistribute wealth already existing in the economy.
Tax collection
First the government collect money from firms who are taxed by a flat corporate
tax rate τF from liquidity they have over a buffer (in fact, taxed is part of the
profits they would be distributing to households through the capital market).
Contrary to the firms, households are taxed not on their wealth, but only a
monthly income Ih = wh + P rh , a sum of wage and profit they got in the last
month. They are also taxed by a flat income tax rate τH .
The government revenues are thus equal to:
G=
H
X
h=1
(τH · Ih ) +
F
X
f =1
(1 − τF ) · (mf − Bf )
(4.14)
4. The Model
37
Social transfers
There are two types of social transfers schemes which will be compared in the
latter part of the paper. It is a) standard social scheme and b) basic income
scheme.
Standard social scheme simply divides households to 10 decile groups
according their wealth. Each decile group then get a portion σSS,d of G, which
is specified in table 4.1. This portion is then equally distributed among the
whole decile group. Social rates are distributed according to data about Czech
transfers as estimated by Janský et al. (2016).
G
, where H is
Basic income is simple - every household receive a transfer H
a number of households. In other words σBI,d is constant across the distribution
- 10 %.
Table 4.1: Distribution rates for social schemes
Decile (d)
1
2
3
σSS,d
σBI,d
0.32
0.1
0.11 0.09
0.1 0.1
4
5
6
0.09 0.09
0.1 0.1
7
0.09 0.06
0.1 0.1
8
9
10
0.05
0.1
0.04
0.1
0.04
0.1
To be sure that government only distribute - not create new wealth, nor
restrict it the distribution rates must follow:
10
X
d=1
σSS,d = 1
10
X
σBI,d = 1
(4.15)
d=1
In this context the model neglect the financing issue of the basic income
- the budget for social transfers is the same for both social schemes. In our
case BI makes poor people poorer, while improve the conditions of wealthier
people, who gets higher part of their taxes back in the form of social transfer.
See details in table 4.1 or in figure 2.1b.
Chapter 5
Simulation
5.1
5.1.1
Results
Calibrating the model
The simulation have been run for 5000 month, while the first 1000 have been
burnt out to in order to limit the influence of the initial equilibrium search.
To keep the model stable, it was calibrated with the parameters from Lengnick (2013). Complete list of parameters is in the table 5.1. If not indicated
otherwise those parameters are used for the simulation. The model extension
required some new parameters. In the lower section of the table are parameters
related to the extension of the model.
Janský et al. (2016) have estimated the amount of social transfers distributed to the Czech households. Those will be used in the simulation. There
is no VAT in the model and income tax rate is set 20 % for both firms and
households.
Inequality
Any social policy measure have to be tested on the distribution of income which
at least approximately correspond to the real world distribution. Two measures
to control for inequality in the model have been employed: a) initial conditions
and b) capital market distribution.
The first measure is straightforward - introducing inequalities among households as initial money holdings in the first round. But it turned out, that in
terms of inequalities, the model dynamics are oscillating around a statistical
equilibrium. No matter how the initial conditions are stated the model quickly
5. Simulation
39
Table 5.1: Parameters calibration
Firms
Number of Firms
Number of trade-links
Wage decrease
Wage speed
Minimum inv.
Maximum inv.
Minimum profit
Maximum profit
Price probability
Price speed
Technology
Buffer
Households
F = 100
η=7
γ=1
δ = 0.019
φ = 0.25
φ=1
ϕ = 1.025
ϕ = 1.15
θ = 0.75
ϑ = 0.02
λ=3
χ = 0.1
Government
HH tax rate
F tax rate
Social transfers
τH = 0.2
τF = 0.2
see table 4.1
Number of HHs
Replace link (demand)
Replace link (price)
Prob. of job search
F asking for job
Savings progression
Reserv. wage decrease
H = 1000
ψquant = 0.25
ψprice = 0.25
πun = 1
π<ω = 1
πsat = 0.1
βun = 7
β<ω = 1
βsat = 1
α = 0.885
κ = 0.1
Capital market
Profit to rich
ρ=1
Firms and Households parameters are adopted from Lengnick (2013).
converges to very equal society or it explodes. The equilibrium inequalities
measured by Gini of wealth distribution oscillates between 3 - 10 % in the
standard social security regime and 5 - 15 % when the transfers are distributed
equally among all households (see 5.4).
The other proposed measure to incorporate inequalities in the model is
described in the section 4.2.4. It use the profit distribution process and skew
profits more or less towards rich households. Unfortunately, neither the second
measure lead to increasing inequalities to values we observe in the real world
economies.
The level of inequalities oscillates in a regular cycle (see figure 5.4 on the end
of the section). On the beginning of each cycle there is a rising level of profits,
resulting from growing prices. Those profits are distributed among households
and increase inequalities in the economy. In the certain moment the profits
peak, because firms are not allowed to hold more inventories. Selling inventories
results in a decline of profit margins and with certain delay to decreasing price
level. Profit margins are not high enough to fuel the inequalities and low income
workers get higher wages. The level of inequalities is decreasing. This ’vicious
circle’ is very hard to break in the model setting while keeping meaningful
5. Simulation
40
results.
The inequality issue does not allow the model to test the introduction of
basic income realistically to be used by decision makers, however it can still be
possible to find some patterns in the data, which are discussed below.
Figure 5.1: Employment
1000
Employment
Basic Income
Standard Social security
Employment
980
960
940
920
900
1000
1500
2000
2500
1500
2000
2500
Aggregate Demand
70000
3000
3500
4000
4500
5000
3000
3500
4000
4500
5000
Aggregate Demand
68000
66000
64000
62000
60000
1000
5.1.2
Month
Business cycles and price dynamics
The extension of the model did not lead to significant changes in the model
dynamics. The model still fulfils stylized facts, such as Phillips curve (see figure
A.1 in Appendix) or the business cycle.
First it must be noted that the supply side of the model is very simplistic and every eventual interpretation must be very careful. The production
is a linear function of employment and thus production and employment are
basically identical. The decision whether to work or not is not based on the
solid microeconomic background, as it lacks a possibility of voluntary unemployment. The model thus cannot be used to estimate the labour supply effects
of BI introduction.
5. Simulation
41
The model is able to study aggregate demand effect of the basic income
introduction and its consequences. Assuming the aggregate amount of distributed transfers is constant (which appears to be a plausible assumption - see
appendix A.3), then social transfers distributed evenly among each household
shift the transfers towards richer households. Thanks to higher saving rate
among rich decrease AD. Rich people would save greater part of their income,
which would not become part of the aggregate demand (there is no investment
in the model).
First look on the results (see 5.4 on the end of a chapter) indicate that
the relationship between price level and social distribution regime would not
be that simple basic income. Price level is copying very similar trajectories
under both regimes. Clearly the BI introduction cause redistribution changes
in the society. Introduction of BI increases the mean gini coefficient of wealth
by 2-3 %, while keeping the variance relatively stable. Redistribution from
poor to rich households, as it is done in the simulation, clearly affects the level
of inequalities in the economy.
The aggregate demand dynamics (consumption + unsatisfied demand of
households) are strongly affected by the presence of the ’long cycles’. In different time periods the aggregate demands reacts differently, but this also seems
to have cyclic properties. When looking at particular time-periods in the simulations, the relationship looks to be existing, but in different period the relationship looks to be the exact opposite. The model with transfers distributed
as basic income does not show lower AD than the model with standard social
security scheme. The presence of strong cycles in the aggregate demand is
shown on periodogram 5.2. There is a strong cyclic component on period 150,
however the density of longer periods is significantly higher.
One classical business cycle lasts approximately 150 months, i.e. 12.5 years
(see periodogram 5.2). The peak of a cycle is characterized with full employment and growing inventories. In certain moment firms start to sell their
stocks and dismiss workers (this results from equation 4.2). In the same moment those firms start to lower their prices to attract new costumers. The
inventories peaks in the moment when most firms dismiss workers. This is a
bottom of the business cycle. The economic growth is renewed when firms start
selling inventories and allow for hiring new workers and increased production.
Inventories are depleted and after a while start to fill new inventories.
Pricing mechanism in the model is also connected to inventories. Price
changes are only considered, when the firm has too high or too low level of
5. Simulation
42
Figure 5.2: ’Long Cycles’ in the simulation
1.0 1e7
Periodogram of Aggregate Demand
Density
0.8
0.6
0.4
0.2
0.00
500
1000
1500
Period (months)
2000
2500
inventories ( eq. 4.6). The price are kept within the specified range, which
is constant, relative to the marginal costs of production (the linear function
of employment) (eq. 4.4). This is the mechanism, that keep the prices price
trajectory inverse to the AD.
The aggregate demand is leading the changes in price level, which react
approximately 5 - 15 months later. This is visible in figure A.2. The series of
granger test between price level and AD have been performed. The long cycle
properties of the model time series makes it dangerous to run the test for whole
period at once. It is useful to run the test for different periods separately. The
test was run for 8 periods, each taking 500 rounds. The test results show, that
AD granger-cause prices in all periods up to lag 100, while the opposite usually
does not hold.
The effect of basic income introduction leads to shift in the dynamics of aggregate demand. Again this shift appears to affect the ’long cycle’ component,
rather than the mean price value or inflation rates. When looking at particular
time periods the inflation dynamics is different - see 5.3. In the first period,
5. Simulation
43
the basic income introduction is connected with lower inflation rates, in the
last the inflation is lower for the basic income schemes than for the standard
social security. Interesting is that the long cycles affect price dynamics only
during the upturn phases of the business cycle. During economic (and price
level) downturns the behaviour looks the same. The reason is connected with
inventories growth (see figure A.6). The more the firms accumulate inventories,
the lower the inflation rate.
Inflation rate
Inflation rate
Inflation rate
Figure 5.3: Inflation in different periods of simulation
0.04
0.02
0.00
0.02
0.04
2000
Basic Income
Inflation rate
Inflation rate2300
Standard Social security
2100
2200
2400
2500
0.04
0.02
0.00
0.02
0.04
3500
3600
3700
3900
4000
0.04
0.02
0.00
0.02
0.04
4300
4400
4500
4700
4800
Inflation rate3800
Months
4600
In order to verify robustness of the simulation it was run with 50 random seeds. Following Lengnick (2013) more heterogeneity to the model have
been introduced by setting the first month that firms and government starts
their planning. The first month have been randomly chosen from the interval
(24, 108).
The results of 16 realization are presented in A.9. In all simulation there
is no clear relationship between the different social transfers regime and the
price level. In all cases there is no change in the price level connected with the
transfers distribution scheme.
5. Simulation
44
Table 5.2: Redistribution and price level
τF = τH
20
30
40
50
60
70
80
90
99
SS: Mean (StDev)
24.19
24.11
24.08
24.02
23.83
23.76
23.62
23.47
23.39
(0.33)
(0.33)
(0.32)
(0.31)
(0.32)
(0.31)
(0.29)
(0.28)
(0.30)
BI: Mean (StDev)
24.27
24.29
24.29
24.32
24.32
24.26
24.28
24.36
24.31
(0.31)
(0.30)
(0.29)
(0.30)
(0.30)
(0.31)
(0.30)
(0.29)
(0.29)
Diff.
T-test*
0.08
0.18
0.21
0.31
0.49
0.50
0.66
0.90
0.92
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
*p-value of two-sided T-test (µBI = µSS with equal variances)
5.1.3
Price level
The hypothesis H1 suggests that BI introduction would lead to deflationary
pressures when it distributes wealth from rich towards poor. Although the
redistribution is clearly happening (see figures A.3 and gini in 5.4), the standard
setting do not show clear pattern resulting from the BI introduction.
Redistributed amount
Maybe the low inequalities in the economy makes the effect of social transfer
regime too weak to be found in the data. Redistributing in the equal society
does not lead to major differences in AD. If a link between price level and
basic income exist, it might be found when redistributing larger amount of
wealth within the society. This can be tested in the model by changing the
tax-rates τF = τH . The larger amount of taxes is collected, the higher amount
is redistributed within the society (see section 4.2.5). According to hypothesis
H2 increasing τ in this model setting would lead to higher price level in the
standard social security regime, because the model redistributes from poor to
rich.
The table 5.2 shows that also this hypothesis is not proved by the simulation
- moreover the increased taxation cause the exactly opposite effect. The higher
the taxation and higher amount of money redistributed within the society the
lower the price level in the social security scheme. The BI regime remains
unaffected.
Since the price generating mechanism is a complex process, it is necessary
to identify aggregate demand as a transmission channel between the two. The
5. Simulation
45
figure A.7 shows, that the differences in prices are are present, but the difference in AD remains oscillating around zero. The price level difference results
rather as a consequence of the initial searching for the equilibrium price level.
This cannot be interpreted as a causal link for a simple reason: the ABM
models does not have to behave realistically right after the simulations starts.
This is especially the case of Lengnick (2013) who start the production and
consumption planning after several month of a ”free-run”.
Neither increasing amount of resources redistributed to households seem to
be influencing the aggregate demand. Also H2 is rejected.
Propensity to save
If there was a link between price level and social transfer regime, then according
to H3, the larger the difference between propensity to save of rich and poor
households, the larger the effect on price level. This can be tested in the model
using variation of parameter α, which affects the shape of the consumption
function (see equation 4.10). The lower α, the larger differences in propensity
to save and thus higher inflationary pressures. It is important to emphasize,
that the effect we are looking for is not affecting the price level by changing
parameter α per se. What we are looking for is the situation when changing
the parameter leads to affecting the price differently in the particular social
transfers regimes.
The figure A.4 do indicate any changes in the price level in the BI regime.
Changing parameter α strongly affects the price level, but this effect is only
one-off. However the effect is not different in the particular social transfers
regimes. Moreover table 5.3 indicates that substantial changes in prices cannot
be explained by changes in the AD. Neither H3 can be supported with the
model simulation.
Social distribution rates
Another option to boost the potential effect of the social transfer regime and
price level such, that it would be visible in data, is changing the gap between
the two regimes. Because in the basic income regime any changing of the
redistribution is not possible by definition, the distribution rates for standard
rates will be changed from the values in table 4.1. The goal is to have maximum
possible redistribution. This is why I will change the distribution rates as
5. Simulation
46
Table 5.3: Descriptive statistics for different of α
α
Mean price SS
Mean price BI
Diff/mean BI
90
85
80
75
70
65
60
55
26.2 (0.012)
20.0 (0.013)
14.7 (0.013)
10.4 (0.013)
7.0 (0.013)
4.5 (0.012)
2.6 (0.012)
1.4 (0.012)
26.2 (0.013)
20.1 (0.013)
14.8 (0.013)
10.5 (0.013)
7.1 (0.012)
4.5 (0.013)
2.6 (0.014)
1.4 (0.013)
0.003
0.005
0.007
0.003
0.006
0.001
0.013
0.009
AD SS / BI
65
65
65
65
65
65
65
65
285
262
325
318
348
409
529
457
/
/
/
/
/
/
/
/
65
65
65
65
65
65
65
65
245
235
278
310
335
427
385
394
Variation coefficient in brackets
follows:
σSS,1 = 1
σSS,i = 0
i ∈ 2, 3, ..., 10
(5.1)
In other words - all the transfers are given only to the poor members of
the society. This case is not realistic, many social policies are supporting lower
middle class or even higher income households, but if there was an effect to
identify, it might be revealed. Because such simulation design leads to strong
redistribution from poor to rich, according to H2 it is expected that under the
regime of the basic income the price level is expected to be lower.
The results are similar as in the case of changing the tax rates - the first look
indicates exactly opposite effect than expected (see figure A.8). The effect again
is not linked to AD changes. It is rather a results of changes on the beginning of
simulation which states a statistical equilibrium and is not relevant for analysis.
The hypothesis cannot be confirmed also when changes are made to standard
social scheme redistribution.
Income groups
The great benefit of the ABM is that it allows for studying both micro and macro
properties in one model. Although the model was not calibrated to incorporate group effects, it can still be interesting to see how the price level differs
among the income groups. To keep things simple only three income groups are
considered - a) the whole society, b) the poorest decile of the households and
c) the wealthiest decile.
The price level dynamics of those groups are shown in the figure A.5. Not
surprisingly the price trajectories of both income groups follows very similar
patterns such as the aggregate price level. On both extremes of the income,
5. Simulation
47
the price level volatility during the business cycle is significantly higher than
aggregate price level. It also seems that both very poor and very rich households
are less effective in choosing their trading relations or in pushing their trading
partners to decrease prices - the prices of the firms they trade with are on
average by 2 % higher than the aggregate price level. This is consistent across
different periods of the simulation. However there is still no difference between
the basic income regime and standard social scheme.
The simulation did not find any indication that the hypothesized relationship between social distribution schemes and price level would exist.
Table 5.4: Income groups descriptive statistics
Basic Income
Standard scheme
5.2
Aggregate
Mean (St.Dev)
Poor
Mean (St.Dev)
Rich
Mean (St.Dev)
24.27 (0.31)
24.19 (0.33)
23.81 (0.53)
23.75 (0.52)
23.78 (0.55)
23.73 (0.54)
Discussion and further research
The simulation did not show any signs of the possible linear effect of the transfer
scheme on the price level. The replacement of standard social security scheme
with basic income did not move the price level in any particular direction it rather affected the ’long cycles’ that are present in the AD dynamics. The
effect of the basic income introduction have not been isolated even when the
simulation redistributed unrealistically large amount of wealth kept by households (up to 99 %) or when there was a large difference in the saving rates of
poor and rich households.
The interpretation of the results must take into account the inability to
control for distribution of wealth in the society, which is of special importance
for testing social policy reforms. Lengnick (2013) is built around a strong deterministic trend of profit-inventories business cycle, which does not allow the
households income inequalities to arise. The gini coefficient of wealth distribution is always oscillating around 5 %, which is far from the values observable
in the real world (World Bank (2013)).
The low inequalities can lead to the ’false negative’ - rejecting the hypothesis, even when the effect was present, but so small that it can be isolated
only with higher redistribution. Large amount of wealth redistributed in equal
5. Simulation
48
society is still different from redistribution of wealth in unequal society. The
best test of the basic income would come from the model which is able to
realistically capture the income and wealth distribution.
Natural way to finally confirm or reject the possible effect of the BI introduction on the price level would be to try it in a natural experiment. Some
attempts are already planned in the Netherlands or Finland. However because
inflation is in a large extent macroeconomic phenomenon the effect can probably be directly measured after at least 5 years after the BI is adopted on
the state level on the aggregate data. For example differences in differences
macroeconomic analysis might be an appropriate tool to test for the effect.
Unfortunately, this may be late - motivation for this work is mainly the transition process between the two transfer regimes. Until that moment, probably
the only insight into the relationship between redistribution and price levels
are various kinds of simulations.
The simulation can be performed in the EURACE model - see Deissenberg
et al. (2008). This model try to mimic the structure of the European economy.
The major drawback of the model is that it demands enormous computational
capacity and requires broader scientific cooperation. Moreover, neither this
complicated model, when used in different paper, seems to be able to capture
income distribution realistically. The gini coefficients reported by Dawid et al.
(2013) on figure 2b are between 5 - 15 %.
The model of Dosi et al. (2013), who explicitly link their model to income
inequalities unfortunately cannot be used for testing the hypothesis of this
work. The model use the pricing mechanism itself to control for income distribution. The direct link to price-generating mechanism does not allow to
study for the price effect. The simple financial market connecting credit market with households asset could be a solution, but that might turn out to be
very complicated.
ABM is not the only simulation method available for economic modelling.
Unfortunately, EUROMOD model is designed to test macroeconomic relationships on price level. But the heterogeneous agents able to simulate unequal
economy can be incorporated also in the DSGE framework, for example according to Troch (2013).
5. Simulation
49
ABM model explaining wealth inequalities
Another option, with no doubt very complicated, is to build a new ABM model,
whose main goal would be to realistically capture the wealth inequalities in the
economy. Such macroeconomic model, which would be connecting real business
sector with economic inequalities emerging from social relationships, could then
be used as a tool for testing of tax and social policies. In what follows I will
very briefly suggest the main contours of such model.
While Dosi et al. (2013) simulate income distribution to be used rather as an
input for further analysis, the model suggested here would be aiming to develop
inequality rather as an outcome of processes on the labour market, financial
markets, the social relationships or the skills and education distribution within
the society.
Kinsella et al. (2010) have already developed an agent-based model generating income inequalities through the investment in education. This model can
serve as an inspiration for incorporating human capital investment. Unfortunately its internal structure, mainly the lacking pricing mechanism, would have
to be rebuilt.
The business sector of the model could be a simple one goods economy similar to Lengnick (2013). The strong deterministic trend keeping the inequalities
in the economy low, would have to broken. The model able to study the effect of
aggregate demand on price level would also require a simple pricing mechanism
which reflects the changes on the labour market and households balance-sheet,
but it is not explicitly involved in generating inequalities in the economy.
The business and public sector in the suggested can also draw inspiration
from Lengnick (2013) with its modularity. To be able to be used as a social and
tax policy tool, the model should be able to be easily extended or adjusted,
without breaking the model logic.
The wealth inequalities is a result of complex social relationships. In the
simplified framework that is suggested are three key factors behind the rise
of wealth inequalities - it is a social mobility, human capital investment and
financial markets.
The key aspect of the wealth distribution is a social mobility. The network effects might in some cases be an important determinant of the success
on the labour market (see Munshi (2003); Beaman (2012)). The ABM design
enables to incorporate some network effects of social mobility. Similar network
structure as in Lengnick (2013) goods market enables to simulate the economy,
5. Simulation
50
where household can use their social relationships and skills to succeed on the
labour market. The labour market would be localized. Households who have
social relationships with high-income households can have a higher probability
to be recommended for a job and thus increased chance on the labour market.
An ABM with a small-world network labour market is suggested in Tassier &
Menczer (2001; 2008), network effect was also studied in the EURACE framework by Dawid & Gemkow (2014).
Households would be investing in the human capital, which could also fuel
the inequalities within the society. The higher price of the human capital
investment (such as school tuition fees) would discourage poorer member of
the society to invest and might lead to higher level of inequalities. Inspiration
could be drawn from ABM agent based model with investment in education by
Kinsella et al. (2010). In this model wealth inequalities are also maintained
in the model through generations by heritage - the wealth, in difference with
skills, is transmitted from generation to generation.
The financial market could be a third source of inequalities among households. The trading on financial market is costly, but the price would relatively
decrease with the amount traded. The access to additional gains from the financial market would thus be skewed towards higher income households. Modelling
financial markets is quite common among ABM modellers (see Samanidou et al.
(2007)).
If the suggested model succeeded in the ability for effective control over the
inequalities in the economy, while keeping the simple economic structure and
the ability to reproduce major business cycle stylized facts (which is far from
being sure), the suggested ABM could provide better insight in the relationship
between the basic income, aggregate demand and the price level.
26.0
25.5
25.0
24.5
24.0
23.5
23.0
1000
0.20
0.15
0.10
0.05
0.00
1000
500000
400000
300000
200000
100000
0
1000
100000
80000
60000
40000
20000
0
1000
Gini of wealth Price level
Profits
Inventories
2000
1500
2000
2000
1500
1500
2000
1500
Basic Income
2500
2500
2500
2500
3500
3500
3000
Inventories
3000
3500
3000
Profits
Month
3500
Gini of3000
wealth
Price level
4000
4000
4000
4000
Figure 5.4: Dynamics of inequalities and the business cycle
4500
4500
4500
4500
5000
5000
5000
5000
Standard social security
5. Simulation
51
Chapter 6
Conclusions
The thesis did not succeed in its aim to show a clear relationship between the
price level and social security reform, that would replace the standard social
security scheme with the basic income. While traditional social security focus
mainly at the poor and the lower middle class, the basic income provides a
minimum guaranteed income without any tests of eligibility. The channel of
price level changes in the model, the aggregate demand, did not react on the
changes in the redistribution schemes, even when unrealistically large amount
of money was distributed within the society.
The models inability to effectively control for wealth distributions may have
caused, that the possible effect was too small to be found in the data. The
model, designed to study social policies in the realistic wealth distribution
would yield more valuable insight in the problem and make the relationship
between the transfer scheme and the price level more clear. The basic contours
of the possible model with network effect on the labour market, investment in
human capital and financial market favouring wealthier costumers is suggested
in the discussion. The main research question of the thesis remains open.
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Appendix A
Appendix
Phillips Curve
Figure A.1: Phillips Curve
Phillips Curve
0.05
0.04
0.03
Inflation Rate
0.02
0.01
0.00
0.01
0.02
0.03880
900
920
940
Employment
960
980
1000
A. Appendix
II
Figure A.2: Granger causality test on different periods of simulation
Demand predicting price
1.0
1.0
0.5
0.5
Cumulative Granger test p-value
0.0
0
20
40
60
80
100
starting month: 1000
120
140
0.0
1.0
1.0
0.5
0.5
0.0
0
20
40
60
80
100
starting month: 2000
120
140
0.0
1.0
1.0
0.5
0.5
0.0
0
20
40
60
80
100
starting month: 3000
120
140
0.0
1.0
1.0
0.5
0.5
0.0
0
20
40
60
80
100
starting month: 4000
120
140
0.0
Price predicting demand
0
20
40
60
80
100
starting month: 1500
120
140
0
20
40
60
80
100
starting month: 2500
120
140
0
20
40
60
80
100
starting month: 3500
120
140
0
20
40
60
80
100
starting month: 4500
120
140
Lag
A. Appendix
III
Figure A.3: Transfers in 1st and 10th wealth decile
70000
60000
Poor Transfers
Poor Transfers
Basic Income
Standard social security
50000
40000
30000
20000
10000
0
1000
1500
2000
2500
1500
2000
2500
70000
3000
3500
4000
4500
5000
3000
3500
4000
4500
5000
Rich Transfers
Rich Transfers
60000
50000
40000
30000
20000
10000
0
1000
Month
Figure A.4: Price level and concavity of the consumption function
Price level
28
27
26
25
1000
16
15
14
1000
7.5
7.0
6.5
1000
2.8
2.7
2.6
2.5
1000
Standard social security
3000
alpha = 0.9
3000
alpha = 0.8
3000
alpha = 0.7
3000
alpha = 0.6
5000
21 Basic Income
20
19
1000
3000
alpha = 0.85
5000
11.0
10.5
10.0
1000
5000
4.6
4.4
4.2
1000
5000
1.5
1.4
1.3
1000
Months
5000
3000
5000
3000
5000
3000
5000
alpha = 0.75
alpha = 0.65
alpha = 0.55
A. Appendix
IV
Poor - price level
Total price level
Rich - price level
Figure A.5: Perceived price-level in different income groups
26.0
25.5
25.0
24.5
24.0
23.5
23.0
1000
26.0
25.5
25.0
24.5
24.0
23.5
23.0
1000
26.0
25.5
25.0
24.5
24.0
23.5
23.0
1000
Rich - price level
Basic Income
Standard Social Scheme
1500
2000
2500
3000
Total price
level
3500
4000
4500
5000
1500
2000
2500
Poor - 3000
price level
3500
4000
4500
5000
1500
2000
2500
3000
3500
4000
4500
5000
Month
Growth of inventories
Growth of inventories
Growth of inventories
Figure A.6: Inventories growth in different periods of simulation
0.20
0.15
0.10
0.05
0.00
0.05
0.10
0.15
0.20
2000
0.20
0.15
0.10
0.05
0.00
0.05
0.10
0.15
0.20
3500
0.20
0.15
0.10
0.05
0.00
0.05
0.10
0.15
0.20
4300
Basic Income
Growth of inventories
Standard Social security
2100
2200
2300
Growth
of inventories
2400
2500
3600
3700
3800
Growth
of inventories
3900
4000
4400
4500
4700
4800
Months
4600
A. Appendix
V
Figure A.7: The difference of price level and demand with the tax rate
70 %
Price level
0.5
Price level
0.0
0.5
1.0
1.5
Demand
2.0
6000
4000
2000
0
2000
4000
6000
8000
1000
2000
1000
2000
Demand
Month
3000
4000
5000
3000
4000
5000
diff = XSS − XBI
Figure A.8: Price and demand with transfers flowing only to poorest
decile
Price level
Basic Income
Transfers to poor
Demand
Price level
26.0
25.5
25.0
24.5
24.0
23.5
23.0
1000
70000
68000
66000
64000
62000
60000
1000
1500
2000
2500
1500
2000
2500
3000
Demand
3500
4000
4500
5000
3000
3500
4000
4500
5000
Month
Price level
3000
3000
3000
26
25
24
23
1000
26
25
24
23
1000
26
25
24
23
1000
Seed: 3598
Seed: 2663
Seed: 1572
3000
Seed: 1013
26
25
24
23
1000
5000
5000
5000
5000
26
25
24
23
1000
26
25
24
23
1000
26
25
24
23
1000
26
25
24
23
1000
3000
Seed: 3659
3000
Seed: 2682
3000
Seed: 2045
3000
Seed: 122
5000
5000
5000
5000
Months
Standard social security
26
25
24
23
1000
26
25
24
23
1000
26
25
24
23
1000
26
25
24
23
1000
3000
Seed: 3747
3000
Seed: 3230
3000
Seed: 2323
3000
Seed: 1350
5000
5000
5000
5000
Basic Income
26
25
24
23
1000
26
25
24
23
1000
26
25
24
23
1000
26
25
24
23
1000
3000
3000
Seed: 3805
3000
Seed: 3427
3000
Seed: 2514
Seed: 1461
Figure A.9: 25 randomly selected realizations of the simulation
5000
5000
5000
5000
A. Appendix
VI
Appendix B
Content of Enclosed file
There is a a zip file enclosed to the thesis which contains empirical data and
Java, Python and R source codes. The files are divided to following folders:
ˆ Agent-based model
ˆ Data analysis
ˆ Simulation outputs
Agent-based model
The main logic of the model is described in the java source code.
The model is separated to the different files:
ˆ Main.java
ˆ Simulation.java
ˆ Agents.java
ˆ Household.java
ˆ Firm.java
ˆ Government.java
The program is run from the Main.java. The program runs the Simulation.java where major parameters are set. I attach also the brief instruction
set provided by Matthias Lengnick.
The topology and time logic of the model is defined in Agents.java. Also
micro-data collection, aggregation and saving is done in this file. Data are saved
B. Content of Enclosed file
VIII
at the end of simulation to the directory specified at line 647 in the method
Write to CSV().
Behaviour of individual classes of agents are then defined separately for each
class in particular agents class.
The data analysis
Most of the data analysis is done in Python, with little exception of granger
tests, which are done in R.
All figures and tables in the thesis can be approached from Main.py by
changing the string parameter on the last line. The parameters can be find in
the method SelectExample().
Simulation output
The basic simulation output can be found in the folder Standard Setting. Each
simulation output consists of the datafile macro.csv and the file with parameters modelInfo.csv. The simulations of basic income and standard social security is always in different folder.
Different redistribution amounts are in tau playing folder
Consumption function behaviour is analysed in alphaPlaying
The simulation robustness is verified SeedPlaying.
The redistribution only to poor is in ExtremeSocialRates