1. PPA 691 – Seminar in Public Policy Analysis
Lecture 5 – Forecasting Policy Futures

2. Forecasting in Policy Analysis
Forecasting is a procedure for producing factual information about future states of society on the basis of prior information about policy problems.
Forms of forecasting.
Projection.
A forecast based on the extrapolation of current and historical trends into the future.
Prediction.
A forecast based on explicit theoretical assumptions.
Conjecture.
A forecast based on informed or expert judgments about future states of society.

3. Forecasting in Policy Analysis
Aims of forecasting.
Forecasts provide information about future changes in policies and their consequences.
Forecasting permits greater control through understanding past policies and their consequences, implying that the future is determined by the past.
Forecasting also enables us to shape the future in an active manner, irrespective of what has happened in the past.

4. Forecasting in Policy Analysis
Limitations of forecasting.
Forecast accuracy.
Recent simple forecasting models have had huge errors in recent years (as much as 50%) in econometric forecasting.
Comparative yield.
Both simple and complex theoretical models have been no more accurate than simple extrapolative models and informed expert judgment.
Context.
Institutional (nonprofit more accurate than business and government).
Temporal (long-term less accurate than short-term).
Historical (modern complexity reduces accuracy).
“Assumption drag”.

5. Forecasting in Policy Analysis
Types of futures.
Potential futures.
Future societal states that may occur.
Plausible futures.
Future states that, on the basis of assumptions about causation in nature and society, are believed to be likely if policymakers do not intervene to redirect the course of events.
Normative futures.
Potential and plausible futures which are consistent with an analyst’s conception of future needs, values, and opportunities.
The specification of normative futures narrows the range of potential and plausible futures, thus linking forecasts to specific goals and objectives.

6. Forecasting in Policy Analysis
Table 1. Contrast between goals and objectives
CHARACTERISTIC
GOALS
OBJECTIVES
Specification of purposes
Broadly stated (. . . To upgrade the quality of health care)
Concrete (. . . Increase the number of physicians by 10 percent)
Definition of terms
Formal ( The quality of health care refers to the accessibility of medical services)
Operational ( The quality of health care refers to the number of physicians per 100,000 persons . . .)
Time period
Unspecified ( In the future)
Specified ( In the period )
Measurement procedure
Nonquantitative (adequate health care insurance)
Frequently quantitative ( The number persons covered per 1,000 persons)
Treatment of target groups
Broadly defined ( People in need of care)
Specifically defined ( Families with incomes below $19,000)

7. Forecasting in Policy Analysis
Sources of goals, objectives, and alternatives.
Authority.
Insight.
Method.
Scientific theories.
Motivation.
Parallel case.
Analogy.
Ethical systems.

8. Approaches to Forecasting
Decide what to forecast, or determine the object of the forecast.
Decide how to make the forecast, or select one or more bases for the forecast.
Choose techniques that are most appropriate for the object and base selected.

9. Approaches to Forecasting
Objects.
The object of a forecast is the point of reference of a projection, prediction, or conjecture.
Objects of forecasting.
Consequences of existing policies.
Consequences of new policies.
Contents of new policies.
Behavior of policy stakeholders.

10. Approaches to Forecasting
Bases.
The basis of a forecast is the set of assumptions or data used to establish the plausibility of estimates of consequences of existing or new policies, the content of new policies, or the behavior of policy stakeholders.

11. Approaches to Forecasting
Bases (contd.).
Bases for forecasts.
Trend extrapolation (projection).
The extension into the future of trends observed in the past.
Based on inductive logic.
Theoretical assumptions (prediction).
Systematically structured and empirically testable sets of laws or propositions that make predictions about the occurrence of one event based on another.
Based on deductive logic.
Informed judgments (conjecture).
Knowledge based on experience and insight, rather than inductive or deductive reasoning.
Based on retroductive logic.

12. Methods and Techniques of Forecasting
APPROACH
BASIS
APPROPRIATE TECHNIQUES
PRODUCT
Extrapolative forecasting
Trend extrapolation
Classical time-series analysis
Linear trend estimation
Exponential weighting
Data transformation
Catastrophe methodology
Projections
Theoretical forecasting
Theory
Theory mapping
Causal modeling
Regression analysis
Point and interval estimation
Correlational analysis
Predictions
Judgmental forecasting
Informed judgment
Conventional Delphi
Policy Delphi
Cross-impact analysis
Feasibility assessment
Conjectures

13. Methods and Techniques of Forecasting
Classical time-series analysis.
Time series are made up four components.
Secular trend.
Seasonal variation.
Cyclical fluctuations.
Irregular movements.
Linear trend estimation.
Nonlinear time series.
Oscillations.
Cycles.
Growth curves.
Decline curves.
Catastrophes.

14. Time – Series Example

15. Methods and Techniques of Forecasting
Linear forecasting example.
Major disaster data set,
Disaster Declarations = * years; R2 = .592.
Where 1953 is set to zero.
1953 – 1971: Disaster Declarations = * years; R2 = .103.
: Disaster Declarations = * years; R2 = .497.
: Disaster Declarations = * years; R2 = .329.
Projection for (55) using whole data set: 54.0.
Projection for 2008 (55) using post-1988 set: 61.1.

16. Methods and Techniques of Forecasting
Theoretical forecasting.
Theory mapping.
Types of causal arguments.
Convergent arguments.
Divergent arguments.
Serial arguments.
Cyclic arguments.
Procedures for uncovering the structure of an argument.
Separate and number each assumption.
Underline the words that indicate claims (“therefore”, “thus”, “hence”).
When specific words are omitted, but implied, supply the appropriate logical indicators in brackets.
Arrange number assumptions and claims in an arrow diagram that illustrates the causal argument or theory.

17. Methods and Techniques of Forecasting
Example for theory mapping from Daniels and Clark-Daniels.

18. Methods and Techniques of Forecasting
Causal modeling and regression analysis.
The creation of theoretical models on the basis of previous research and logic.
The testing of these models with causal analysis methods such as path analysis and structural equation modeling.
Example:

19. Methods and Techniques of Forecasting
Judgmental forecasting.
Delphi technique.
Principles.
Selective anonymity.
Iteration.
Informed multiple advocacy.
Polarized statistical response.
Structured conflict.
Computer conferencing.

20. Methods and Techniques of Forecasting
Judgmental forecasting (contd.).
Delphi technique (contd.).
Steps.
Issue specification.
Selection of advocates.
Questionnaire design.
Forecasting items (probability of occurrence).
Issue items (ranking of importance).
Goal items (desirability and feasibility).
Option items (alternatives).
Analysis of first-round results.
Development of subsequent questionnaires.
Organization of group meetings.
Preparation of final report.

21. Methods and Techniques of Forecasting
Delphi article.