Policy Analysis

QPAM: Introduction

Quantitative Policy Analysis and Modelling (QPAM) concerns itself with the goals that we set ourselves for society and how government can obtain these goals.

The “Grüne Wirtschaft” initiative currently up for a referendum in Switzerland can be said to have the goal of a sustainable economy by 2050. If accepted it mandates to assess the process every four years. Based on the assessment it is authorized to raise taxes, put subsidies in place, support research and impose regulation to achieve the goal. It is a policy with a policy target and a set of policy instruments (the mandate to review and the authority to enact other instruments). To answer the question, whether it is a good policy it needs to be assess whether it takes Switzerland in a desired direction and whether it is an effective mean to get there. Both the desired direction and the effectiveness of a policy can be highly contested as seen in the current public debate in Switzerland. The particular policy proposed is fairly vague except for the mandate to review (roughly 6 months of assessment every 4 years). The vagueness of the means leaves it open for different groups to interpret them and hence makes its meaning contested.

Policy Analysis

The term is confusing inasmuch it has two major meanings attached. This class will focus on the analysis of the effect of policies put in place. For the “Grüne Wirtschaft” initiative it would be assessing the means (raise taxes, put subsidies in place, support research and impose regulation) by their effectiveness. This approach involves a lot of economics and modelling and will drive the majority of the classes.

In Political Science Departments there is a second meaning to it that focuses on the analysis of the political factors that lead to a policy. It analyses the different coalitions that drive the creation of a policy. Our example would probably focus on how the Green Party drove the policy and how other polities react to it. This topic would be governed in Environmental Governance classes and will not be developed further here.

If  the referendum was to pass the Swiss Environmental Office would be tasked with implementing it and developing and analysing the means that will be the focus of this course.

Policy analysis is also used by NGO’s such as WWF to identify policies that they want to advocate for.

Eugene Bardach’s book “A Practical Guide for Policy Analysis”(Bardach, 2012)is the main resource for the course and I reviewed it here.

References

Bardach, E. (2012). A Practical Guide for Policy Analysis (4th ed.). Thousand Oaks, California: Sage.

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.

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.

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
  6. Confront the Trade-Offs
  7. Devide!
  8. Tell your story

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):

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