Towards optimal economic sanctioning coordination modelling
Methodical problems of macro-optimal socio-cybernetic international sanctioning planning and coordination modelling: Introductory remarks on preliminary postulates and conjectures
Jeremy Greenstock: “the reason sanctions are popular is not that they are known to be effective, but “that there is nothing else between words and military action if you want to bring pressure upon a government”
In the economic literature as one of the first example of economic sanctions is provided by the measures taken by the U.K. government in the Rhodesia independence conflict (The Penguin Dictionary of Economics 1978 p174). According http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1007387 the EU has had in the previous decades an ample chronology of sanctions and dominantly with low efficiency and abortive – probably due to low macro-cybernetic theoretical base.
See also for the current publications in http://en.wikipedia.org/wiki/Economic_sanctions – and recent definitions e.g.:
“Economic sanctions are domestic penalties applied by one country (or group of countries) on another country (or group of countries). Economic sanctions may include various forms of trade barriers and restrictions on financial transactions. Economic sanctions are not necessarily imposed because of economic circumstances — they may also be imposed for a variety of political and social issues. Economic sanctions can be used for achieving domestic political gain.“
Actually the latest recent example for the EU28 is provided by the Third Round measures presently implemented in unison by the EU and the USA in the coalition against Russian Federation in the case of the Russian aggression in the South-East Ukraine: http://europa.eu/newsroom/highlights/special-coverage/eu_sanctions/index_en.htm
As this seems to develop as a many-stage process – there may be still time to analyse the structure of process mechanism design theoretically in the specter of modern stochastic game theoretic and institutional economic etc methods (Appendix A) and make corrective suggestions.
Theoretically the most complicated problem in planning of collective sanctions in the EU context in this Third Round – is the central optimal coordination of the defensive sanction measures taken by the imposing member states – as these penalty measures projected by the imposing countries against transgressing third national economy – are as a rule hurting the imposing states economies as well in different stochastic rates directly and indirectly. Additionally stochastic may come into game via third country fuzzy logic. And most importantly the complexity of the problems increases as with the sanctions to the antagonist the coalition has to introduce complementary domestic economic policies and mechanisms for the minimization the losses inflicted to the national economies from the counter-reactions of the antagonist. Alas in the text of the http://europa.eu/newsroom/highlights/special-coverage/eu_sanctions/index_en.htm – we cab not find a smallest measures by EU to organize complementary domestic counter-strategies.
It seems these complex circumstances make hardly a pragmatic normative quantitative modelling too-bad (see e.g.: Jonathan Schlefer. 2012. The Assumptions Economist Make. Harvard University Press).
Basic extant modern evolutionary heterodox macro-socio-economics and -cybernetics (see e.g.: Lindau Nobel Laureate Meetings 5th Economic Sciences 19-23 August 2014 Abstracts pp 24-44 – http://mediatheque.lindau-nobel.org/videos/33963/joseph-stiglitz/meeting-2014-eco ) provides at least a three-postulate pillar – probably sufficient methodical framework for modelling about an optimal coordination of international sanctions for the group of countries in the conditions of complex uncertainties:
First is the consideration of uncertainties and risks in the hierarchical coordination – and these in most complicated stochastic cases as e.g. Donald Rumsfeld’s “known unknowns” etc (as one example see *) – Bayesian approaches – mixed strategies and in many stages game theoretic decentralized/democratic coordinated equilibrium mechanisms.
Second is modelling of coordinated optimization of socio-economic institutional/mechanism structural changes**
Third is consideration of changes in the national knowledge structures and consideration connected moral-hazard risks and moral coordination***
All the various contributions of these methodical tools to the implementation by the agents for optimal strategies and institutional designs in the case of antagonistic coordinated games are presented in the above quoted Papers containing also relevant significant classical References.
First is that in the case of financial-economic union the optimal sanctioning of the third national economy – the specific all-union sanctioning tax for member states (as in the ESM example) should be introduced for solidarity compensation mechanism (analogous to e.g. ESM mechanism and European Semester mechanism etc) of the union members who suffer to losses at the most in the economic sanction war – war in the defense against the escalation of political and armed aggression.
Second is that besides other common real factors as international trade losses in the sanction wars – also the financial and capital losses should be taken into consideration – as well losses/gains in the imaginary international credibility capitals of national societies and losses in the respectability of their political and knowledge structures.
Third and most importantly: strict material and moral penalties and restrictions should be implemented to the institutions/agents distorting internationally national knowledge structures – authorized under the auspices of the third transgression state – resident agents or not: as these kind of distortions prolong the duration of economic wars with relevant damages to the probabilities of nationals sustainability ***.
Complex modelling involving indirect relations and feed-backs may produce counter-intuitive conclusions. E.g. from the aspect of impairment of the Russian economy the “Mistral” deal may with grate probably be justified – and – in the Estonian example financial restrictions on some Russian capital founded banks may probably give new opportunities to improve national balance of payments and international investment position etc.
For the qualitative measurement of effectiveness of the implied sanctions in the short term: a) the speed of nationals’ statistical production should be enhanced on the level of present ICT level b) national official statistical publications have to be made more transparent and ample and open for the public – especially national central banks must openly publish international balances of payments also in the country by country format etc. BTW considering complex uncertainties (e.g. fuzzy logic of the antagonistic country) it is important to have in mind by the effectiveness assessments that in these conditions the diversity of sanctions is as important as the generally moderate degrees of sanctions – and open possibilities for further bargains.
*) Ennuste, Ü. 1989. Some Models of Stochastic Planning Mechanisms. – Finnish Economic Papers, 2, 2, 116 – 124: http://econpapers.repec.org/article/fepjournl/v_3a2_3ay_3a1989_3ai_3a2_3ap_3a116-124.htm
John F. Nash Jr.
Artificial Intelligence and Cooperative Games
Session: Thursday, 21 August, 11.30 hrs – In: http://mediatheque.lindau-nobel.org/videos/33963/joseph-stiglitz/meeting-2014-eco
Recently I have been researching in the area of “cooperative games” with the
stimulation of an idea which effectively enables the theoretical reduction of
a cooperative game to a non-cooperative game of a special sort or variety,
specifically the sort of game which arises when several players COULD do
well, playing among themselves with legitimate “game moves”, but where,
if they were not given some mechanism that would tend to induce them to
take game actions relatively favorable for the joint welfare of all of them together,
then they might naturally behave so badly in relation their possible
mutual best interests that that would be like the simple non-cooperative
equilibrium in a prisoners’ dilemma game.
One of the observations that can be made here is that a human player playing
in a game and strictly following a completely detailed game strategy
becomes equivalent to a robot and behaves as if he were an “artificial intelligence”.
So we have the possibility of gaining understanding of “cooperative games”
through gaining understanding of how a good class of model “artificial intelligences”
might naturally play them.
The class of cooperative games introduced by Von Neumann and Morgenstern
in their book still provides a good and stimulating challenge to game
Perhaps nothing like a set of points, or a class of sets of points, nor sometimes
any single point would be the ideal concept that we would like to find
and appreciate relating to these games (which have transferable utility (like
a conveniently transferable utility) usable as businesses use money). But
there is the natural psychology to appreciate something that might seem
comparable to the solution of a classical “chess problem”.
I have myself been involved with studies which have considered games of
three players that are DEFINED by a “characteristic function” (and which
correspondingly involve “transferable utility”). Such a basic type of threeperson
game is completely defined by its “characteristic function” specifying
v(0)=0, v(1)=k1, v(2)=k2, v(3)=k3, v(1,2)=j12, v(1,3)=j13, v(2,3)=j23, and
v(1,2,3)=m123. (And usually the characteristic function is presumed to be
My first involvement in these studies led to a program of calculations which
developed as sponsored research and led to a publication in “The International
Game Theory Review”. An experimental games study deriving from
that work attempts to study cooperative games and cooperation in games
through the device of “the method of agencies” which provides a standard
means for the formation of effective coalitions and the enabling of cooperation.
**) Ennuste, Ü. 2003. A Linear Planning Analysis of Institutional Structure in the Economy: http://pdc.ceu.hu/archive/00001564/01/linear.PDF
***) Ennuste, Ü. 2008. Synthetic Conceptions of Implementing Mechanisms Design for Public Socio-Economic Information Structure: Illustrative Estonian Examples. In – Socio-economic and institutional environment: harmonisation in the EU countries of Baltic Sea Rim. Tallinn University of Technology, 9 – 39: http://www.ies.ee/iesp/No4/Ennuste.pdf
APPENDIX A: Technical Remarks
Table (Draft 19.VIII 14): The institutional mechanism structure of the players
|Coalition Coordination Symposium*(CS)||Antagonist Third Countries||Significant Fourth Countries||…||…|
|EU US||RF||CH BRICS|
|Symposium of Corporative28Memberstat(SEU)||Non-coordinated||Non-actives|
|Member stat’sCoalition Symposiums(SMC) e.g.: BRICSor/andMember’sSymposium(SM) e.g.: EE|
*Symposium – code name of the sanction and complementary domestic strategies (SS) coordination mechanism – coordination may be material and moral***.
Schematic aggregated compact structure of the coordination strategic (CS) optimisation model SS=F(CS) and Losses (material, political, moral, environmental etc) inflicted to the EU and US from the RF=LRF(SS) and self-inflicted by (EU)&(US) LEUUS=R(SS) and passively from the forth countries P(SS):
e.g. – MinMaxR(SS)=LRF(SS)+R(SS)+P(SS)
The game theoretic coordinated decomposed equilibrium solution is based on the optimal mechanisms optimizing coalition members losses by side-payments (material and moral) in the situation of optimal all-coalition collective sanction strategies.
APPENDIX B: Illustrative Case Study on Estonian Example (the Author WBA)
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