Introduction to Theory and Practice of Public Policy Analysis

Code:

PDEPP001

Acronym:

ITPAPP

Keywords
Classification	Keyword
OFICIAL	Technological Policies

Instance: 2020/2021 - 1S

Active?	Yes
Responsible unit:	Department of Industrial Engineering and Management
Course/CS Responsible:	Doctoral Program in Engineering and Public Policy

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
PDEPP	4	Syllabus since 2011/12	1	-	7,5	45	202,5

Teaching language

English

Objectives

The objective is to enable students to look critically at the strengths, limitations and underlying assumptions of key policy research and analysis tools and problem framing and sensitize students to some of the critical issues of taste, professional responsibility, ethics and values that are associated with policy analysis and research.

Learning outcomes and competences

The goal of the study cycle is to train specialists and researchers capable of formulating and solving complex and fuzzy problems that require a multi-disciplinary approach involving both engineering and social sciences, making use of scientific methodologies for the analysis of public policies in areas such as telecommunications, energy and creative industries.  By exposing the student to the frontier of knowledge in engineering and social sciences, in combination with advanced tools for analysis, estimation and optimization of complex processes, the study cycle will yield graduates that have the necessary knowledge and skills to provide consultancy services and decision support, in particular for scenarios that are characterized by the existence of multiple agents, antagonistic objectives, conflicting criteria and emergent behavior, thus resulting in heavy uncertainty and high risks.

Working method

Presencial

Program

This course reviews and critically examines a set of problems, assumptions and analytical techniques that are common to research and policy analysis in technology and public policy. Topics covered include the difference between science, trans-science and policy analysis, policy problems formulated in terms of utility maximization, issues in the valuation of intangibles, uncertainty in policy analysis, selected topics in risk analysis, limitations and alternatives to the paradigm of utility maximization, issues in behavioral decision theory, issues related to organizations and multiple agents, and selected topics in policy advice and policy analysis for the federal government.

Mandatory literature

Millett Granger Morgan,Max Henrion,Mitchell Small; Bibliografia principal: Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis. ISBN: 0 521 42744 4

Teaching methods and learning activities

Most of the course is built around class discussion (not formal lectures) based on assigned readings and on the analysis of case studies. One midterm and one final exam are the main items for student’s assessment/evaluation.

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Participação presencial	20,00
Teste	40,00
Trabalho escrito	40,00
Total:	100,00

Calculation formula of final grade

Final Grade = 20% X Participation in class + 40% X Written work + 40% X Final exam