Policy design analysis and evaluation

A.Y. 2020/2021
12
Max ECTS
80
Overall hours
SSD
INF/01 SPS/04
Language
English
Learning objectives
The students will be equipped with the conceptual and empirical tools to understand the most salient features and the most relevant consequences of today's processes in a number of significant social domains.
Expected learning outcomes
By the end of the course students will acquire the ability to critically evaluate and discuss the impact, development and use of the topics covered during the course. The final exam aims to verify the expected learning outcomes in relation to these topics.
Course syllabus and organization

Single session

Responsible
Lesson period
Second trimester
The course relies on Teams and other integrated apps, regardless of the measures of physical distancing in force.

The course channel is bit.ly/PolDAE
The office hours channel is bit.ly/ADVirtualOffice
Course syllabus
Class 00 - The map of the course
The first class illustrates (a) the object and goal of the course; (b) the available resources; (c) the learning path.
Essential backing: Dunn, Ch. 1
Planned date: 2020.09.23

Module A - THE CONTEXT
Contexts are the space-time regions where policy arguments take their shape and, ultimately, wither as nondecisions or thrive as the motivation of policy designs. Moreover, contexts are the major source of reasons for the practical implausibility of the argument. The module introduces the issue of relevant contexts from the threefold perspective of the policy actors, of the policymaking process, and of the governance structures within which the process unfolds.
Essential backing: Dunn, Ch. 2 and 9 + Box 3.1

2020.09.24 - Class 01 - The stake of the policymaking: substantive policy tools as solutions to policy problems
2020.09.25 - Class 02 - The policymaking cycle: an overview
2020.09.30 - Class 03 - Unbounded rational decisions, their actors and structures
2020.10.01 - Class 04 - Bounded rational decisions, their actors and structures
2020.10.02 - Class 05 - Second-best decisions, their actors and structures
2020.10.07 - Class 06 - Disjointed incrementalism, its actors and structures
2020.10.08 - Class 07 - Analytic tools to define contexts
2020.10.09 - Class 08 - Group-work: identify your policy context
2020.10.14 - Class 09 - Group-work: identify your policy context
2020.10.15 - Class 10 - Presentations, review, and discussion

Module B - THE CONTENT
The immediate worth of a policy argument lies in its capacity of mobilizing interests, justifying choices, promoting agreements. A policy argument, however, is as tenable as the theory that it conveys about the reasons for a state of affairs and the ways to improve it. The module narrows on the causal core of a policy argument, explicates its constituting elements, and introduces students to the minimal algebra that formalizes its structure.
Essential backing: Toulmin et al., parts II-V; Dunn, Ch.8; Duşa, Ch.3

2020.10.16 - Class 11 - The soundness of policy arguments: claims and grounds
2020.10.21 - Class 12 - The soundness of policy arguments: warrants, rules, and backings
2020.10.22 - Class 13 - The strength of policy arguments: qualification and rebuttals
2020.10.28 - Class 14 - The strength of policy arguments: presumptions, quandaries, and relevance
2020.10.29 - Class 15 - Argument fallacies: missing, irrelevant, defective grounds
2020.10.30 - Class 16 - Argument fallacies: poor warrants and ambiguity
2020.11.04 - Class 17 - Wrapping up: Policy arguments as provable causal structures
2020.11.05 - Class 18 - Classwork: gather enough information to support an argument for a debate
2020.11.06 - Class 19 - Classwork: structure your policy argument and publish it
2020.11.11 - Class 20 - Defend your argument, discuss others', and rate all.

Module C - EVALUATING TENABILITY WITH QCA
The module introduces Qualitative Comparative Analysis as a suitable technique for the systematic possibilistic evaluation of the tenability of a policy argument.
Essential backing: Dunn, Ch. 6 and 7; Duşa, Ch. 4-8.

2020.11.12 - Class 21 - Configurational renderings of policy arguments
2020.11.13 - Class 22 - Measurement issues
2020.11.18 - Class 23 - Turning attributes into sets, with special attention to outcomes
2020.11.19 - Class 24 - Parameters of fit to necessity and sufficiency
2020.11.20 - Class 25 - Truth table analysis and minimizations
2020.11.25 - Class 26 - XY plots: visualizing solutions
2020.11.26 - Class 27 - Group-work: replicating a QCA study
2020.11.27 - Class 28 - Group-work: replicating a QCA study
2020.12.02 - Class 29 - Group-work: replicating a QCA study
2020.12.03 - Class 30 - Presentations, review, and discussion

2020.12.04 - Class 31 - Wrapping up

(Please always check https://bit.ly/PolDAE for variations)


Module D - ESTABLISHING TENABILITY WITH FREQUENTIST STRATEGIES
Visiting Professor
The module introduces students to a suite of quasi-experimental techniques as strategies of reference for the probabilistic assessment of the tenability of a policy argument.
Essential backing: Dunn, Ch. 4 + further readings
Schedule and materials will circulate in due time.
Prerequisites for admission
The course assumes no previous knowledge. Students are warmly suggested to bring their laptops during classes and, especially since Module C, to have the updated version of R and RStudio installed.
Teaching methods
The course relies on a mix of lectures, classroom exercises and pollings, discussions, group-work, and presentations.
Teaching Resources
Dunn, WN (2003). Public Policy Analysis: An Introduction (3rd edition). Upper Saddle River, NJ: Pearson Prentice Hall.
Toulmin, S, Rieke, R, Janik, A (1984) An Introduction to Reasoning (2nd edition). New York, NY: Macmillan.
Duşa A (2019). QCA with R. A Comprehensive Resource. Cham, CH: Springer.
PN: Additional readings may be provided during classes as needed.
Assessment methods and Criteria
The course aims to equip students with the knowledge and the techniques to identify an argument about a policy design; establish/assess its formal, causal, practical tenability; and, ultimately, learn how to construe them.

Students will be evaluated for:

1. their active participation.
Lectures include instant modes of reviewing comprehension that support the fine-tuning of contents and promote learning.
Their proper usage accounts for up to 6 pts.

2. their capacity to identify policy stakes, analyze contexts, and summarize results.
In the last part of module A, students are organized into groups and assigned materials. Each group pinpoints the relevant information required to identify a context and arranges it into a presentation for class discussion.
An effective groupwork accounts for up to 6 pts.

3. their capacity to structure a policy argument, and identify its weaknesses.
In the last part of module B, students are organized into two camps, claiming the success and the failure of the same policy intervention, respectively. In step one, they brainstorm up the information required to make a sound argument. In step two, every student develops their own argument and publish it. In step three, arguments are discussed and rated.
Completion accounts for up to 6 pts.

4. their competence in configurational analysis.
At the end of module C, replicable published QCA works is assigned to each student. Under guidance, they produce a script that answers the following questions:
i) the model: is it configurational?
ii) case and raw variable selection: does it ensure the fair probation of fitting?
iii) calibration: is it replicable?
iv) directional expectations: are they empirically supported?
v) truth table: is there any inconsistent primitive?
vi) solutions: is the deserving one that is discussed?
Proper completion accounts for up to 6 pts.

5. their competence in quasi-experimental design.
The details of the assessment will be circulated in due time.
Proper completion account up to 6 pts.

The individual final colloquium discloses the points earned during the whole course and offers the opportunity to review past exercises, discuss shortcomings, and add insights.
The colloquium decides the final mark with a possible adjustment of up to 3 points.
INF/01 - INFORMATICS - University credits: 6
SPS/04 - POLITICAL SCIENCE - University credits: 6
Lessons: 80 hours
Professor(s)
Reception:
Thursday 11:30-12:30 (students) - 13.30-15.30 (thesis students and PhD candidates)
internal building, 2nd floor, room 12 | VirtualOffice channel in Teams