or/ie? what future for or/ie? çağlar güven may 2013 what future for or/ie?1

what future for OR/IE? 1

what future for OR/IE?

çağlar güven

may 2013


outline

• planning for resource allocation•market failure• climate change• complexity• systems thinking• the challenge for OR/IE

3

•most problems in OR/IE are problems of resource allocation in human-activity-systems• resource allocation is central to all economic decisions• several questions can be posed about allocation:

who is going to allocate resources?how are resources to be allocated?what is the mechanism and the scope of allocation?

• allocation is a two-stage process:planningimplementation

what future for OR/IE?


•OR/IE is concerned both with planning and implementation • however our primary contribution is planning• for planning OR/IE depends on:

mathematical modelling in generaloperational researchstatistics engineering sciencesmicroeconomics ...

• planning has to answer the questions:what to do? how to do?


•what should be done to realise the long-term goals of the human-activity-system?

the aim is effectiveness → doing the right thing

concern is about morality, ie,

the what-question is a moral question• how should it be done without wasting resources?

the aim is efficiency → doing things right

concern is about technique and technology, ie,

the how-question is a technical question• these questions come up in different contexts


type-1 planning takes place at the micro-operational level; for example: • production and inventory management• supply chain management, etc..

type-2 planning takes place at the micro-strategic level; for example:• business planning• value chain analysis• strategic planning• investment planning, etc..

type-3 planning takes place at sectoral or the macro level; for example:• energy planning• industrial policy• sectoral planning• regional planning, etc..


• the how-question primarily appears in type-1 planning• the what-question appears in type-2 and type-3 planning• the what-question comes first; it is crucial for resource

allocation in all human-activity-systems • but in the last 30+ years, it was commonly accepted that only

free markets could tell us what to do• hence industrial engineers have had to forget about the what,

and focus on the how• as a result, OR/IE was generally excluded from (type-2 and

type-3) planning


• this has weakened and marginalised the contribution of OR/IE to critical and strategic debate about resource allocation• as a result, the OR/IE profession has become almost irrelevant for a wide range of issues facing society•why did this happen?• to explain why, we have to consider how resource allocation works• let us consider the following two questions:


1. who is going to allocate the resources?• a central authority such as the government,• or consumer choice?

2. by what means are resources to be allocated?• by planning and government directives,• or by letting the market mechanism to decide?

• the practice of the last 30+ years has been: • allocation by consumer choice• free-market policies and,• no need for type-2 or type-3 planning

• how can we justify this, is there a scientifically-based argument for free market policies?


•market policies are often said to be rational, efficient or optimal; implying such policies are ‘scientifically’ grounded• this claim is founded on two fundamental theorems in

microeconomics, the welfare theorems:• the first welfare theorem says:

“ if every good is traded in a market at known prices and if households and firms act perfectly competitively, then the market outcome is Pareto optimal; ie. when markets are complete, any competitive equilibrium is necessarily Pareto optimal”

•which means that the invisible hand of the market makes sure that marginal costs equal marginal benefits (MC = MB) in perfectly competitive markets


• the second welfare theorem says: “if household preferences and production sets are convex, there is a complete set of markets with known prices, and every agent acts as a price taker, then any Pareto optimum can be achieved as a competitive equilibrium if appropriate lump-sum transfers of wealth are arranged.”

• in effect, the first theorem is telling us that all perfectly competitive market equilibria are efficient, and,• the second theorem is saying that economic policy can lead us to any desired equilibrium, thus ensuring maximum welfare


• but these are just two theorems in mathematics, they have strong internal validitybut almost no external validity

• external validity is weak because the assumptions made are very strong:an infinity of producers and consumers, perfectly elastic

demand for goods and factors perfect informationhomogeneous productsfree entry, free exitconstant returns...


• in reality perfect competition is never achieved and markets fail to provide either efficiency or optimality

• there is cause for market failure:

1. many agents are not price takers; this leads to imperfect competition

2. some goods cannot be priced by markets because the relevant market is missing; this causes externalities

3. all goods are not private, there are public goods (and bads) that are accessible to shared consumption by several agents

4. not all agents have perfect information; information asymmetry is common


• externalities and public goods are particularly common:transactions of the externality take place outside the markettotal marginal cost becomes MSC = MC + MECbut there is no market that prices the MECso the optimality rule MSC = MB fails to hold

•market failure is a result of the nature of things, it cannot be avoided and is common to all economies• but if this is so, then the promise of free markets will not be

realised• so why should we stick with free market policies?


• free market supporters claim that: the closer an economy comes to realise the conditions of a free

market, the closer to optimum will be the allocation

• however this claim has no proof even in mathematics, under assumption of an idealised free market, this means that: • pursuing market policies is a political choice• free market economists claim

that failures exist but only as exceptions that can be put right and,

that the government’s only business is to prevent or repair market failure


• in fact there are conflicting views on what to do about failures:neoliberals say that market failure is the exception and markets

can correct such failure in timeliberals say that market failure is the exception and government

action may be needed to address the failure Keynesians say that market failures are common and governments

have to take care of failuresMarxists say that failures are the rule, not the exception, and

central planning is necessary

• but something is happening now, that effectively puts an end to this debate:


• climate change is causing externalities at a global scale; it is no longer possible to treat market failure as an exception; it has become the rule in all economic activity• the IPCC as well as bodies like the "National Climate

Assessment and Development Advisory Committee" of the US Congress now agree that:climate is changing fast and global warming is realchange is man-made, andit will cause catastrophic results

• change is mainly caused by CO2 concentration

• all economic activity consumes energy and emits CO2


• hence all economic activity now causes an external cost• there are no market signals telling us what that cost is

• market failure is therefore universal all markets have now failed (witness markets since 2007)• we can no longer expect markets to function effectively on their

own; (type-2 and type-3) planning is needed to ensure that MSC = MB holds• mainstream economists do not dare to admit this, but there is no

escape from reality• most messes we are facing today are caused directly or indirectly

by the failure of market policies

• planning is back in force at every level of economic activity


• even a bigger cause for messes is our failure to recognise the complexity of nature and of human-activity-systems

• the Newtonian paradigm that continues to dominate scientific inquiry assumes that,

– the world is knowable; objective knowledge is possible and subject-object duality holds

– cause and effect act linearly– nature is deterministic or predictable– reduction and analysis works

• the new realisation however, is that many of the systems that surround us are complex, and that the metods of Newtonian science are incapable of dealing with complexity


• the complexity paradigm tells us that,─ systems contain many constituents interacting nonlinearly─ there is constant interplay between chaos and nonchaos─ systems have emergent properties, analysis fails─ objective knowledge is not possible; subject-object duality is false

• all human-activity systems are complex, exhibiting technical, stochastic and purposive complexity

• complex systems can be characterised by thermodynamics concepts a gradient must be imposed on a system if work is to be done work can be done if a system is not in thermodynamic equilibrium, ie. when a

boundary separates the system from its environment complexity is the degree to which a system maintains thermodynamic

disequilibrium; whereas a total lack of complexity is randomness, a state of maximum entropy, or a state of total disorder and disorganisation


systems maintain disequilibrium by dissipating gradients in a locally reduced entropy state; all human-activity system are dissipative

dissipative systems self-organise into structures that dissipate gradients life itself is a dissipative structure that has emerged to counter the gradient

imposed by the sun, mainly through photosynthesis

• markets, when left to their devices, act as self-organising systems that dissipate (chemical, physical, kinetic etc..) gradients generated by the world’s resource-base, thus accelerating the progress towards disorder and disorganisation

• planning is necessary to counter this tendency of markets in order to keep our distance from thermodynamic equilibrium

• all the messes we face are caused by failure to recognise the complexity of human-activity systems, complexity of the highest order


• how can we deal with complexity, how should we conduct inquiry?

• the mathematical results of complexity studies cannot easily be applied to human-activity systems

• there are two main strategies that can help us in inquiry:boundary settingseparating scaleschanging boundaries and scales as needed

• these are the basic topics of systems thinking, a meta-methodology that aims to deal with complex human-activity systems

• for example soft OR extends the methodology of OR to deal with systems in which purposive complexity is predominant

• in general the soft systems approaches are essential in dealing with messes


• a world in which neither the methods of science nor the market mechanism is effective, presents new opportunities for the OR/IE profession:

resource allocation is no longer possible without planning, without operational research

this opens up new areas for OR/IE, like:• policy analysis• strategy analysis• value chain planning• complex systems design• ...

• which calls for competence in:• systems thinking• microeconomics• cge modelling• sustainability analysis• transdisciplinary team work• ...


• in conclusion, the challenge for OR/IE is to stop doing what it has mostly been doing in the last 30+ yearsto accomplish a paradigm change, and shift its attention from the

how-question to the what-question

• if this challenge cannot be met, the threat for OR/IE isfurther marginalisation, and evenirrelevance

• first resposibility lies with universities who are primarily to blame for the present state of the profession

or/ie? what future for or/ie? çağlar güven may 2013 what future for or/ie?1

Documents

contribution of orie

planningfor planning

orie profession

resource allocation

systemsresource allocation

scope of allocation

resource allocationas

free market policies