# Cornerstone Course – Day 2: Climate Change I

The focus of the afternoon is Argument Analysis applied to environmental decisions, specifically Climate Change.

Part 1 – Modelling:

Understanding modelling by the example of the oblique throw in football:

A target system describes what we want to achieve (e.g. getting the ball to a specific location). Based on the target system a conceptual model can be devised. Specifically, we idealise properties that allow us to model the specific target system (weight, but not colour).

Model equations (e.g. Newton’s laws) are selected, parametrized (e.g. wind) and implemented. The implementation must consider numeric code, parameter values, initial conditions and boundary conditions.

Running the implementation produces a simulation results which is  deterministic *).

The problems focus on structural model uncertainty (uncertainty of numerical code, parameters, initial conditions and boundary conditions) and deductive uncertainties.

*) Up to randomization and parallelisation effects.

Part 2 – Argue with uncertain information:

An important logic puzzle to consider is the Wason Selection Task as it shows difficulties with reasoning, even in relatively simple case.s

We argue if it is controversial whether a statement is true or not. Further we want to show that our reasoning is sound. Most arguments are deductive, but also non-deductive arguments are possible.

The standard form of arguments is inference. Premises are used to justify a conclusion. The correctness of premises as well as the inference is debatable and needs to be confirmed to accept the conclusion.

Argument analysis begins with a complete arguments and follows these steps:

1. Reconstructing arguments: Identify premises and conclusions in the argument.
2. Evaluating arguments: Are premises true or not and can the relationship between premises and conclusion be proven correct? Deductive arguments can be formally verified, whereas in non-deductive arguments there validity cannot be confirmed by correctness. Premises do not guarantee the conclusion  (i.e. they are probabilistic). Fallacious arguments can follow if premises are too weak to support the conclusion. Weakness can be caused by critical points:
• Inductive inferences
• incomplete information
• sample sizes, representativeness
• Causal arguments
• Inappropriate concept of causality (single/multiple causes; feedback)
• Incomplete information
• inference from mere positive correlation, or temporal sequence
• Arguments by analogy
• Incomplete Information
• Illustrative or relevant (dis-)analogy of different strength

A (logical) side note:

On sufficiency and necessity:

In the assertion of the form “If A, then B”:

• A (true) is a sufficient condition for B (true) .
• B (true) is a necessary condition for A (true): “If not B, then not A”.

The assertion “If and only if A, then B”:

• A is sufficient and necessary condition for B, and vice versa.

In an assertion of the form “Only if A, then B”:

• A(true) is a necessary condition for B (true)
• B (true) is a sufficient condition for A (true). “If not B, then not A”.

On conditionals:

(to be filled in)

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# Cornerstone Course – Day 2: Energy Transition II

Policy and Politics:

Goals of public policy related to energy follow a balance between environmental impact, cost and supply security called the triple bottom line of energy policy. However, a fourth factor – industry competitiveness – is a strong factor. The Paris agreement was largely driven by the last from a energy perspective.

Environmental impact is mostly last because it is based externality, however the London Smog is an example where that is not the case. Currently in China Security of Supply is number one However, in Beijing and Shanghai the environmental impact is a close second.

OECD Politics/policy:

They provide useful statistics via the IEA, however, their forecasts are highly political. They reflect political interests including overestimation of nuclear power and Carbon Capture Storage (CCS), whereas they underestimated renewables.

The report is partially driven by transnational companies that can exert political power on the OECD because in that case they can behave similar to sovereign states.

Climate Change and public policy intervention:

CO2 emission represent a negative externality. To obtain an ideal equilibrium the social cost should be added to the private cost. The actual market equilibrium however is only based on the private cost.

The IMF estimate externalities to be 2 Trillion dollars whereas carbon prices recuperates about 50 billion dollars. Resulting in a Carbon price of around negative 60 dollars per tone.

The problem is that the discount rate is deciding. For instance Switzerland has a low social discount rate because values are stable whereas Lebanon recently emerged from a civil war and has a high social discount rate as people spend what they have before the next war takes it away.

The Kyoto protocol was a market solution to the environmental problem.  It offered pollution rights that could be traded such that cheap pollution reductions would offer financial benefit. The cap of rights was based on scientific analysis of how much CO2 can be emitted without surpassing the goal.

The EU is the largest market and had large fluctuation. However, the financial crisis caused governments to flood the markets with allowances provided by Berlin, Paris and Brussels for their national companies to protect them from the crisis impact. Steel and concrete producers where making more money of carbon trading than their actual business.

In the end the carbon trade makes energy production slightly more efficient, but does not provide an effective solution to the increasing CO2 emission.

Marginal Emission Abatement Cost (MAC)

Irrational behaviour causes many products to have negative costs associated per ton of CO2 emission. For instance switching to LED reduced CO2 emission costs per ton by 160\$. However, product standards (white light versus yellow light) hinders adaptation.

For low cost adaptions the problem is that markets forces play a role. For instance, Holcim – a Swiss concrete producer – is a global player that is important for Switzerland. Regulating it too much could cost its global competitiveness and therefore requirements are usually low.

For high cost projects R&D is necessary to reduce the costs in viable ranges. For wind turbines you need up to two years of full-scale tests before you know the efficiency. With 3 years of development and 1 year of pretesting this results in 6 years of time before a cost reducing technology can be used.

Many companies dwarf government R&D spending on energy technology. For instance Switzerland roughly spends 200 million, whereas Siemens spends roughly 2 billion or 10 times more.

Markets allow for the improvements of manufacturing process which drives prices lower, e.g. in solar technology.

Lock-in:

In the energy sector we have several forms of lock-ins. For instance we have infrastructure lock-in as past infrastructure dictates future developments to a point. Learning effects improve infrastructure and makes it more cost efficient even if its overall efficiency than newer less developed technology. Carbon prices lead to short term efficiency as they merely favour the currently cheapest technology rather than the optimal technology. It is difficult not to pick the loosing technologies so lock-ins can hamper developments.

Germany made the decision to become the industrial leader in photovoltaic and thereby drove down the prices for photovoltaic. This is also in response to the loss semi-conductor business that collapsed during a price competition with Asia. However, China took over the manufacturing business and Germany now only produces the machines that produce the photovoltaic.

Now we are back to pre-Kyoto policy approaches to tackle climate change which is more policy driven. Technology allowed to drive down CO2 emissions which enabled a political race to be the one leading this technological wave which consequently drove the Paris negotiations.

80% of future development studies overestimate the cost of technologies by more than 25%. The learning effects in manufacturing are often underestimated and incumbent firms drive estimations to be slanted in their favour.

Another factor is China’s ten year industrial plans that allow China to focus on industries and provided them with financing which made China take over the solar panel productions. Without directed financing China could probably not have taken the solar production industry.

Elephants in the (climate change) room:

China and US coordinated their climate change policies which allowed the Paris agreement to be politically viable. Industry policy was a major issue. China wants to transform into a service economy, it doesn’t have the luxury like Europe to just letting things happen. Therefore China tries to drive policies that allow the shift. The Paris agreement allows the federal Chinese polity to force change upon the local polities that could otherwise resist change. Therefore the Paris agreement can be seen as a industry policy. China has an opportunity to move beyond combustion engines and directly go to electrical engines which could move global mobility markets.

Some Definitions:

An externality is an impact you have on other that you choose not to pay for. Further the externalities are mostly invisible and only impact on a cumulative basis.

A side note:

a) Technology is always political and nuclear is the most political technology. Military power drives technological political request. After the financial crises in 2007/2008 the British Government considered exiting the CERN research, but the military intervened to stay on the edge of technological development. Energy is always political because it is so fundamental to human activity.(paper mentioned later).

b) Decentralised energy is democratic (German Feeding Tariff / Energieeinspeisungstarif was based on democratic energy) and therefore solar energy on the roof is a unprecedented shift in how energy is politically used.

c) In a 100.000 inhabitants city in China a company moved out destroying 5000 jobs after the city did not change policy. Consequently 25000 jobs where lost and the city government completely collapsed. Companies have to be factored in by local governments whether they like it or not.

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# Cornerstone Course – Day 2: Energy Transition I

What is energy?

A state of excitation of matter. At the highest excitation level it changes to waves. But this is too abstract for our use.

Thermodynamics is about the transfer of energy. Energy cascades down to lower to lower level which in turns entropy (e.g. disorder rather than chaos). Fundamentally it is about how the level of excitation of matter. Energy is the transfer of excitation. Work describes the transfer. Power is needed for industry. You need something that changes and work provides change.

The sun is the core of your energy supply. The fusion taking place in the sun is the major source of energy (minus nuclear power supply).

An industrial base takes fuel (stored work) into something useful. The impacts on society are in terms of quality of life, economics and environmental impact.

The following countries experience specific energy challenges and we will illuminate a few of them: Colombia, Argentina, Finland, Iceland, Thailand, Indonesia, South Korea, New Zealand, and Fiji.

Any policy change will only show its results two to three generations later making it hard for politicians to act.

Primary fuels

Coal, oil, gas, combustible renewables & waste are carriers of energy rather than energy. They drive a thermodynamic cycle to perform work.

Energy is used most for transportation, electricity and heat. They can be considered the 3 main pillars. Oil contributing 52% in 1973 / 36% in 2009 is mainly used for transportation.

The energy sector is the biggest economic sector on the world. It dwarfs food, military or anything else. It is slow-moving and has a linear trend slowly increasing . The consumption of primary fuels roughly doubled from 1973 to 2009 ( from 4674 Mtoe to 8353 Mtoe [Million tonnes of equivalent oil]. The OECD changed from 3741 Mtoe to 5413 Mtoe in the same period. China has contributed to the biggest rise with a per capita growth rate of 10% whereas Europe has around 2%. India grows at around half the pace of China.

Around 4% of primary fuels are in bunkers which means in transit or used for airplanes.

Nuclear grew steadily until Fukushima, but since then it has been reduced in the OECD. Nuclear energy is mostly maintained to have the capability to construct nuclear weapons.

Energy Demand

Forecasts differ at around 2 percent.

Developing countries basic demands consist of transportation, light and food/medicine storage. China left these needs behind in the last 20 years and now has comparable needs to the developed countries.

In 2006 25% of the world population had no access to electricity. The number dropped recently due to the fast pace of urbanisation.

Heat needs in non-electrified areas are fulfilled by wood and the burning of wood causes around 1.5 million deaths per year due to carbon monoxide poisoning (ahead of Aids or Malaria).

In the developed world energy demand is about economic consideration. In the developing world energy demand is limited by resources.

The current demand hotspot is Southeast Asia. Indonesia currently has a need of 80 Gigawatts per year and will add 8-10 Gigawatts per year over the next years which is equivalent to the total consumption of Switzerland. Malaysia hosts the fastest-growing energy demand in the region around Singapore.

The large population growth in developing countries drives the energy demand for the next few decades. The fuel-consumption shifts from wood to liquid fuels and electricity.

Atmospheric CO2

Visible light enters the atmosphere and when hitting the Earth transforms to infrared. Infrared is absorbed by CO2 and therefore heats up the atmosphere. With less CO2 in the atmosphere more infrared light would escape the atmosphere.

Fossil fuels represent solar energy accumulated over 600 million years. Currently, we convert back 1 million years of CO2 storage per year.

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# Cornerstone Course – Day 1: Policy Example Cases

Scientist could help analysts creating policies with their knowledge. But how do they provide their input? How does it fit with the political landscape?

Three case studies were in the spotlight to see dilemma of policy analysis. This is not an in-depth analysis of policy analysis, but rather an observation of policies and their consequences.

Case 1 – Misunderstanding a policy:

An introductory case study is the new labelling by the FDA to get started discussing policy analysis.

Obesity is considered an issues by the FDA*). The FDA’s policy is meant create awareness. Due to the policy design the labels are meant to show the level of consumption as happening in the general population compared to recommended consumption based on scientific research. Studies suggest that people perceive the label to mean the latter rather than the former. So they take the average consumption as the recommended consumption.

The study can be critiqued as to whether it is generalizable to all food labels and do whether the scientific rigour was enough to support the hypothesis.

*) In a free society people should be able to choose whether they take up the danger of obesity. However, they cause externalities and those need to be considered as well and this is where the state steps in. The decision to step in is often economical, but may also be moral.

Case 2 – What is a policy aimed at:

Another case study is recycling. The underlying question is how to reduce waste? This question already opens more questions as there is no well definition of waste. It could be primary waste (collected before processing) or final waste (after recycling has taken place). Switzerland for instance has one of the highest primary waste levels, but a very low final waste level. Currently, there is a discussion in Switzerland whether the primary waste needs to be reduced to begin with, if the final waste levels are so long.

“Waste is something valuable that is at the wrong place at the wrong time”. – Anonymous

The problem is, that some problems could be technical like Micro-pollutants in water  (in waste water plants) whereas others like recycling require social engineering. Both need different policy solutions and approaches.

Case 3 – Who is burdened with a policy:

Organ replacement are another contested issue. It is not a free market where you can buy an organ as it is believed that rich people would benefit and poor would be left behind. However, currently organs cannot be artificially produced, so organ donation is the only option. Policy-wise there have been two approaches: opt-in and opt-out. Most countries require opt-ins and have low participation rates whereas opt-out countries (e.g. Austria) have very high participation rates. From a supply/demand perspective an opt-out seems to be the more efficient option, yet opt-in is the de facto default worldwide. Information and effort is a key factor. Opt-in means that a willing donor needs to make the decision, whereas the opt-out requires unwilling donors to decide. Switzerland has opted for opt-in in contrast to the similar Austria.

Similar issues are found for energy-mix, CO2-offset and other opt-in/opt-out policies

When is it a policy?

Policy is a statement within a defined unit (e.g. a sovereign state or a company). A (democratic) state can intervene in a society as it has the legitimacy and power to define policies. Another factor is that only the government can collect resources and redistribute them. A policy without an executing entity is merely an idea.

Summary of the morning:

Humans think linear. Therefore predictions of the future are often off as humans are bad at estimating non-linear processes. Most policies need many years – even decades – whereas politics work often from months to a few years. Technology arises in 30 to 75 years. The problem to solve is multi-scale as the necessities of each process work on a different scale. The course and institute what to bridge those time-scales.

Some definitions:

Effective means goal-attainment whereas efficient means how cost-efficient is it (in comparison to something else).

Technology is about how we manipulate the environment to the use of humans. Science is the underlying rules independent of humans and technology. Policy is the set of rules we gives ourselves to hopefully improve our conditions. Politics is the process of getting there.

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# Cornerstone Course – Day 1: Prologue

The cornerstone course should give a basic introduction into the topics of policy and the contents of the Master’s study.

Disciplines in university are very specialized and focused which offers a great advantage. Over the last two centuries that has created a line along department. 200 years ago you were in “science” and you would do biology, chemistry and physics. While the compartmentalizations allows for neat clear-cut teaching, today’s reality never poses problems in society, that are neatly placed within the department lines.

A forum of exchange is missing. Mindset, language, outlook, all is different in each department and has been and is diverging more. Technological advances drive society in the coming years as much as in the last years. 200 years ago a technological cycle would be 50 years, now it is 10 years and soon it could be 5 years. Finding a common language and a common mindset is an important task.

Policies how to deal with this change needs to be devised now and that is the reason for the course. The learning experience in the program is mutual – professors and students alike learn how to deal with interdisciplinary issues.

What is science? What is technology?

Technology is a means to fulfil a human purpose (W.B.Arthur, 2009).  Altering the physical world around you counts as technology (from fire-making, over wheels to the modern tablet). Consequently, engineering focuses on finding a technical solution is found to meet human demand. Engineering always involves a time scale and its goal must be met timely. The longest technological development can be found in air planes with 30 year cycles.

Science on the other hand focus on understanding phenomena that exist independently of humans and technology. Science does not require time scales and its concepts are more universal. The simple phenomena were understood quite early, but complex phenomena need more research and sometimes technology to be understood.

An illustrating example is the physics (i.e. science) behind light enables the engineering (i.e. technology) of lasers.

Social sciences focus on understanding social, economic and political phenomena – especially human behaviour and societal institutions and norms.

Research is done locally, but its rewards are reaped globally which points at a first policy issue. Where are the incentives to drive science/technology?

Widening Arthur’s narrow definition even money and parliaments can be considered technologies. The concept is loose and commonly differently defined depending on the source.

According to Arthur technology creates our wealth, economy and way of being. On the other hand it also brings unease as technologies seems to cause n new problems for every problem they solve. In general, humans hope that technology resolves issues, but they would rather trust nature. It boils down to a clash between what technology has to offer and what humans are comfortable with. Technology can cause fear because it is unclear how independent of technology humans can function and whether technology is really beneficial.

Society and technology

Is technological innovation like Darwinian evolution? Technology is rather “combinatorial evolution” which can be considered heredity: The more there is to invent with, the greater will be the number of inventions. Also social changes were necessary: Newton’s laws define most of modern technology, but for nearly 200 years there was little development. This can be linked to the little number of people who were able to dedicate time to research (and studying at all). New technology is created out of old technologies. The process is long-term and often iterative.

Creativity is a main driver of new technologies, but what is it? On one hand creativity is the solution strategy to needs based on sensory stimulus. But this doesn’t quite cover inventions and arts. A source of creativity seems to be making mistakes and discovering surprising things in the process.

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# Bardach’s Eightfold Path through Policy Analysis I

In the introductory post about Bardach’s work we discussed the overall context and content. In this post we will focus on the details of the first step of his guidelines. The other steps will be posted soon.

Step One: Define the problem

The most crucial step as it direct any further endeavours. Bardarch recommends to define problems quantitatively in terms of deficit and excess and specifically with a magnitude. Often magnitudes can only be estimated and it is worth providing point and range estimates (e.g. descriptive statistics with box plots). Magnitudes help to convey behavioral and concrete definitions. Since definitions of problems are by their own definition evaluative it is necessary to establish whether a problem is grave enough to concern the public. Bardach suggests that any form of market failure – i.e. a technical property of a good or a service malfunction – warrants an intervention but that on the contrary nearly no other kind of “problem” qualifies. Exceptions are

• Breakdown of non-market systems (e.g. family relationships)
• Low living standards for non-participants (voluntarily or involuntarily) of the market
• Any form of discrimination (racial, minorities, etc.)
• Government inability to deliver a service (public schooling, infrastructure, etc.)

Another issue with definitions is that they may also be diagnostic and in the worst case misleading if the diagnostic is mistaken. Causal claims of problem definitions need to be supported by evidence (see Step Two) or else they can easily fall victim to issue rhetoric.

Issue rhetoric

Bardach recommends to be wary of issue rhetoric that is usually loaded with connotations (partisan, ideological or personal) and recommends a more sober language to find a problem that is analytically manageable. Issue rhetoric also often enforces selective perception and allow parties (to the problem) to define their position as “correct”. At best issue rhetoric can used as the raw material for a first provisional problem definition.

Similarly, some words are connoted with a multitude of issues and therefore it may be necessary to provide a primary focus or exclude certain issues from the definition.

The odds

A special expression “The odds” should be used with care as it conveys vagueness and may under- or overstate an issue. It can be used to cover the uncertainty of the author about a specific event and it should be read this way in any policy analysis.

Latent opportunities

Policy analysis is mainly used to address existing grievances. However, there is a case to improve non-aggravated situations (against the modus operandi “if if ain’t broke, don’t fix it”). Bardach identifies five fields that can often yield improvements:

• Operations research strategies allow to optimise the use of resources and improve productivity.
• Cost-based pricing can reduce inequality by allowing for lower prices during off-peak hours and hand-off the price of peak-consumption to the actual users.
• By-products of personal aspiration can be incentivised such that personal advantage coincides with social advantage (e.g. give a percentage of the cost reduction as a wage increase to the inventing employee).
• Complementarity offers opportunities to join activities that have symbiotic effects.
• Input Substitution can reduce costs by replacing over-qualified employees with well-qualified employees (e.g. civial clerk for police administration instead of trained officer).
• Development support can provide opportunities to improve situation before they get out of hand (e.g. unemployment training before searching for a new job).
• Exchange-oriented policies can facilitate the flow of services by mimicking markets (e.g. Obamacare and the online-market place for insurances),
• Multiple Functions can be assumed by a single policy allowing to use synergies.
• Nontraditional participants can give a new perspective on problems and allow for previously unknown changes for improvement.
• Underutilized capacity can be put to use to reduce cost elsewhere (e.g. school buildings in the evening) but must be offered with caution in order to not endanger emergency capacities or baseline capacities.

The solution in the problem

A problem definition should not entail a solution and should be merely descriptive. Hidden solutions can be hard to see as exemplified by the problem definition “there are to little homeless shelters for families” compared to “too many families are homeless” where the first variation implicitly assumes that shelters are a solution the second options allows the exploration of stopping families from getting homeless in the first place.

As good definitions are hard to come by an iterative process to come up with a definitions is the recommended course of action according to Bardach. The iterative process should also increase the empirical and analytical understanding of the issue at hand.

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# Policy Analysis according to Bardach – Introduction

Bardach’s A Practical Guide for Policy Analysis (Fourth Edition, 2012) is an introductory work into policy analysis proposing an 8-step approach to policy analysis termed The Eightfold Path. It is directed at Master’s students with basic knowledge of economy.

Bardach focuses on the changes in policy analysis from a formal report to an interactive undertaking accompanying the process. The change is similar to changes in Software Engineering where the (static) Waterfall-Model has given way to the (dynamic/interactive) Agile Development paradigm.

The Eightfold Path – Overview

The Eightfold Path can be seen as a guideline to inexperienced policy analysts that struggle with balancing personal bias with organisational interests/biases. A quick overview (as listed in the book) is provided below:

1. Define the Problem
2. Assemble Some Evidence
3. Construct the Alternatives
4. Select the Criteria
5. Project the Outcomes
7. Devide!

The order as is not fixed as prescribed in the aforementioned list, but a rough guide. The problem-solving process has a circular logic to it meaning that several iterations may occur in a “trial and error” style similar to modern product/software development. The guidelines are tailored to practical situations but should be understood as conceptual and some parts of those guidelines may already be predefined by circumstances.

From the onset the book tries to foster efficiency as well as “correctness” (according the the defined/required standards of the problem). The details of the Eightfold Path will be discussed in future posts. In this overview (coinciding with the introduction of the book and summarising it) we will lastly look at the proposed resulting report of a policy analysis:

• A coherent description of the problem
• Several solutions
• Projected outcomes for the application of any solution including path of reasoning
• Trade-off analysis if no solutions can be clearly favoured
• Recommendation of required

Extended Literature

As a practical guide the book should be read in conjunction with in-depth literature for policy analysis (listed in Bardach’s order):

Author(s)YearTitle
Weimer and Vining2004Policy Analysis: Concepts and Practice. 4th ed.
Stokey and Zeckhauser1978Primer for Policy Analysis
Behn and Vaupel1982Quick Analysis for Busy Decision-
Makers
Friedman2002Microeconomic Policy Analysis
MacRae and Whittington1997Expert Advice for Policy Choice: Analysis and Discourse
Gupta2010Analyzing Public Policy: Concepts, Tools, and Techniques
Morgan and Henrion1990Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis
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