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PBPL 204: Regional Policy-Making Across Administrative Jurisdictions (Spring 2019)

Instructor: Sergio Rey
Tuesdays: 5:40-8:30PM
CHASS INTS-N Room 1006
Office hours (Tues 4-5pm, Virtual Thurs 4-5pm)

Introduction

This course provides an introduction to the analytical tools used in regional policy analysis as well as to the process of policy development, implementation, and evaluation. It includes analysis of case studies of councils of government and other regional bodies that have emerged or been created to provide regional governance.

Organization

We meet one time a week and will organize the in-class meetings as follows. Each session will begin exercises in collaborative knowledge building. These will adopt active learning strategies involving collaborative discussion of a regional concept, tool, or model. The collaboration will take the form of group development of answers to several prompts/questions related to the topic at hand. Readings related to the concept are listed by week and are to be completed prior to the weekly meeting.

In the second part of the weekly meeting, we will put theory and concepts into practice by implementing related models, tools, and frameworks using open source computing resources. We will cover basic programming concepts useful for data wrangling, visualization, statistical analysis, and modeling.

The motivation for this organization is three-fold. First, computational learning provides a deeper understanding of the theoretical concepts and frameworks that are the focus of the readings and collaborative knowledge development sessions. It is one thing to read about a regional economic multiplier, but actually implementing the estimation of the particular multiplier for a regional economy provides insights beyond what theory can offer. Second, through these hands-on exercises, you will acquire skill-sets that are highly sought in the field of public policy analysis. Third, no single package currently exists that can handle the wide variety of data sets, and formats, along with the diversity of models and analytical tools. This means that the ability to do customized scripting is vital for success as a regional policy analyst.

The key focus is on learning the main regional analytical tools used in the study of regions. Programming and scripting are a means to this end. Although prior programming experience would be helpful, it is not assumed, as all computational concepts will be presented from first principles.

Learning Outcomes

Through this course, students will:

  • gain an understanding of the different types of analytical tools and models used in regional policy making and analysis;
  • acquire working knowledge of the key sources of economic and demographic data for the study of regional economies in the United States;
  • develop the ability to construct and apply a subset of the more widely used regional models to regions in California;
  • learn principles of computational scripting and the importance of documentation and reproducibility in regional policy analysis workflows.

Grading

Your course grade will be based on the following components

  • Exercises (60 points)
  • Quizzes (30 points)
  • Participation (10 points)

Four exercises will be introduced in class and are due on the dates listed in the schedule. No late assignments will be accepted. Starting on 4/09, Quizzes will be given at the beginning of each class meeting drawing from the material in the assigned reading. Each quiz will be repeated following the class discussion period. Your quiz grade for that week will be the average of these two scores.

Academic Integrity

The UCR student academic integrity policy lists violations in detail. These violations fall into eight broad areas that include but are not limited to: cheating, fabrication, plagiarism, facilitating academic misconduct, unauthorized collaboration, interference or sabbotage, non-compliance with research regulations and retaliation. For more information about the UCR student academic integrity policy, please use the following web link http://conduct.ucr.edu/policies/academicintegrity.html

Disability accommodations

Qualified students with disabilities who will require disability accommodations in this class are encouraged to make their requests to me at the beginning of the quarter either during office hours or by appointment. Note: Prior to receiving disability accommodations, verification of eligibility from the Student Disability Resource Center is required. Disability information is confidential.

Code of Conduct

As course instructor, I am dedicated to providing a harassment-free learning experience for all students, regardless of gender, sexual orientation, disability, physical appearance, body size, race, religion, or choice of operating system. All course participants are expected to show respect and courtesy to other students throughout the semester. As a learning community we do not tolerate harassment of participants in any form.

All communication should be appropriate for a professional audience including people of many different backgrounds. Sexual language and imagery are not appropriate in this course.

Be kind to others. Do not insult or put down other students. Behave professionally. Remember that harassment and sexist, racist, or exclusionary jokes are not appropriate for the course.

Students violating these rules may be asked to leave the course, and their violations will be reported to the UCR administration.

This code of conduct is an adaptation of the SciPy 2017 Code of Conduct.

Schedule Summary (Planned)

Week Date Topic Exercises
0 4/02 Introduction
1 4/09 Regions: Concepts and Policies
2 4/16 Economic Base Theory and Models
3 4/23 Git and Github 1 Out
4 4/30 Economic Base Exercise
5 5/07 Bifurcation Methods 2 Out
6 5/14 Diversification and Growth 1 Due
7 5/21 Imputation and Regression
8 5/28 Regions revisited: Mapping and Scale 2 Due, 3 Out
9 6/04 Studio: Ex 3
10 6/11 Final Exam Week 3 Due

Schedule Detailed (Planned)

Week 0 April 2

Course Introduction

  • Syllabus

Tools and Analysis

Week 1 April 9

Readings/Resources

Collaborative Discussion

Tools and Analysis

Week 2 April 16

Readings/Resources

Collaborative Discussion

  • Regional Accounts
  • Regional Data
  • Economic Base

Tools and Analysis

  • Location Quotients
  • Economic Base Multipliers

Week 3 April 23

Readings/Resources

Tools and Analysis

Week 4 April 30

Readings/Resources

Tools and Analysis

Week 5 May 7

Readings/Resources

Collaborative Discussion

  • Regional Diversification, Stability, and Growth

Tools and Analysis

  • Anaconda Python Distribution
  • Git: pull requests

Week 6 May 14

Tools and Analysis

Week 7 May 21

Tools and Analysis

  • Growth and Diversification: Imputation and Regression Analysis
  • Exercise 2 hints

Week 8 May 28

Mapping for regional analysis

Week 9 June 04

Exercise 3 Work Studio

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