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Policy Analysis: Frameworks and ModelsPowerPoint Presentation

Policy Analysis: Frameworks and Models

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Policy Analysis: Frameworks and Models

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Policy Analysis: Frameworks and Models

Stokey and Zeckhauser Ch1-3

Jenkins-Smith Ch1-3

Weimer and Vining Ch1-2

- Executive Summary
- Introduction
- Statement of the Problem
- Current State
- Statement of the Policy Goals
- New Ways of Organizing
- Comparing the Alternatives with the Policy Goals
- Summary Table
- Evaluation and Recommendation

- What do you do when a complicated policy issue lands on your desk?
- Establish the context
- Lay out the alternatives
- Predicting the consequences of each alternative – including likelihood
- Valuing the outcomes
- Making a choice

- Model: a simplified representation of some aspect of the real world
- Types:
- Diagrammatic: flow charts, decision trees; they identify distinct stages in a process
- Conceptual models: taking complex ideas and concepts and simplifying them
- Long division: large numbers are sometimes confusing
- Tragedy of the Commons: (Garrett Harding) describes the incentives associated with the common grazing ground of a medieval English village. Where individuals ignore the cost their use has on others with the inevitable result of overgrazing that is costly to all.

- Types:

- Simple: formal mathematical models that describe explicitly the quantitative changes in a particular variable in response to stimuli.
- Example: $ in a savings account/interest

- Descriptive: describing the way the world operates
- Prescriptive: provide rules for making an optimal choice– prescribing courses of action (normative/optimizing models)
- First, construct a descriptive model that encompasses all choices open to the decision maker and predicts the outcome of each
- A set of procedures for choosing among alternative actions given the decision maker’s preferences among the outcomes.

- Deterministic: the outcome is assumed to be certain. Natural Laws: E=mc2
- Probabilistic: Where the outcome of a particular action is not unique, instead there is a range or a number of possible outcomes.

- How do we judge a model?
- We judge a model on how well it works or how accurately it predicts.
- Taking great care with our assumptions and model specification (Are we including the right explanatory variables?)
- A useful model is streamlined and relatively simple (How do we decide on which variables to omit?)

- We judge a model on how well it works or how accurately it predicts.

- The discipline helps us get our thinking straight; it forces us to think about fundamental principles
- The possibility of experimenting with the model rather than the system itself
- Facilitates communication among those concerned – why did you make those assumptions? Why did you leave out those important variables?

- Allocating scarce resources – with a focus on the public sector

There are two primary elements of any

act of choice:

- The alternatives available to the decision maker
- The decision maker’s preferences among the alternatives

- Trade-offs are the essence of difficult decisions
- This model assumes little significant uncertainty

- Two definitions…
- Efficiency: a combination of attributes is said to be efficient if, given the available alternatives, it is impossible to increase one output without giving up some of at least one other.
- Domination: When comparing two alternatives (A and B), A dominates B when A is better in every respect. Dominated points can never be efficient.

p.24 of S&Z

- The possibility frontier: the set of efficient alternatives. The frontier may be straight or curved, continuous or discrete, or a few isolated points.

This curve tells us the maximum achievable output of water for every possible output of electricity. Point F indicates that with an electrical output of 8 thousand kwh, the maximum water output is 32 million gallons, and conversely.

Electricity (thousands of kwh/day)

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- The 2nd element of the fundamental choice model describes the decision maker’s preferences – Indifference Curves

Electricity (thousands of kwh/day)

Each of these points are found to be equally satisfactory and all of those along the curve – they lie on the same indifference curve because they are equally satisfactory.

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- Similarly, we could draw other indifference curves depicting lower and higher levels of satisfaction.

Remember, we don’t assign specific values to these levels of satisfaction, we say I1 is better than I0. Also, there is no implication that movements of equal distance across the graph are equally valuable. Things get better as we move north and east. Such a family of curves is called an indifference map.

Electricity (thousands of kwh/day)

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- Here we combine the continuous possibility frontier and the indifference map.

The best choice for the planner is the combination of electricity and water represented by point __.

This is because only at that point can the planner reach the highest possible indifference curve.

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At any point on the curve, the rate at which one output can be transformed into another is given by the slope at that point on the possibility frontier. We refer to the rate at which one output can be transformed into the other at a particular point as the marginal rate of transformation (MRT).

Electricity (thousands of kwh/day)

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The slope of an indifference curve may be interpreted in a similar way. It represents the way in which the decision maker is willing to trade electricity for water while still remaining on the same indifference curve. The steepness of the indifference curve indicates the rate at which the planner is willing to trade off between the two outputs.

This trade off rate is called the marginal rate of substitution (MRS).

Electricity (thousands of kwh/day)

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