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Course 2022-2023 a.y.

20469 - INSTITUTIONS, GOVERNMENT AND SOCIETY - MODULE I

DES-ESS
Department of Social and Political Sciences

Course taught in English

Go to class group/s: 20 - 21

DES-ESS (6 credits - I sem. - OB)
Course Director:
GIOVANNI FATTORE

Classes: 20 (I sem.) - 21 (I sem.)
Instructors:
Class 20: GIOVANNI FATTORE, Class 21: GIOVANNI FATTORE


Lezioni della classe erogate in presenza

Mission & Content Summary
MISSION

How do you design a research project? How do you identify a good topic, and what steps do you take from the start to producing a publishable paper? In this course we will take you from the very beginnings of your research idea through to producing high-impact research. We will show you how to define a feasible topic, conduct a systematic review of literature, and identify the appropriate method for your research question. The course will help you learn how to read effectively, so that you can write better and feel confident when critiquing existing research. We will also help you to avoid some of the most common pitfalls that graduate students make when engaging in research for what may be first time. In so doing the course we will cover multiple research methods which will help you, albeit less from a technical aspect (which is covered in your other courses) but from the perspective of design and real-world impact. Our training in this course is not bound to the confines of a specific field. We will, however, draw heavily on examples from economics, political science and population health. The overarching aim is to help you become good scientists – and to transition from being passive ‘consumers of research’ to start actively producing your own sound science by the end of the course.

CONTENT SUMMARY

The first part of the course covers causal inference in the social sciences by presenting the main models used in contemporary research. The second part discusses validity of empirical studies and complement the first part of the course with additional methods/topics that are increasingnly popular in empirical research in the social sciences.

Part 1. Main analytical approaches for causal interference:

    The conterfactual model.
    Randomization and its discontents.
    Regression Models.
    Instrumental variables.
    Regression Discontinuity Design.
    Difference-in-Differences Design.

Part 2. Validity and additional topics/methods for empirical research in the social sciences:

    Survey research and sampling.
    Social Network Analysis
    Content Analysis.
    Systematic Reviews and meta-analsysis.
    Validity of research designs.
 


Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
  • Conduct and write a systematic literature review
  • Understand the logics of causal inference.
  • Master different models to test causality.
  • Critically review a scientific paper
  • Conduct and write a systematic review
  • Produce a research proposal and present it in public
APPLYING KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...

 

  • Work in groups to prepare a research proposal.
  • Conduct a Systematic Review
  • Prepare a research proposal.
  • Deliver a presentation of a research proposal

Teaching methods
  • Face-to-face lectures
  • Group assignments
DETAILS

Through the preparation and discussion of the systematic review and the research proposal the faculty interacts with students to check their ideas. The presentation in class gives the opportunity to be exposed to a variety of research designs and methods in the social sciences in general and in economics in particular. Collaboration between peers also offers the opportunity to foster creativity, acquire presentation skills, learn from peers and understand the criteria used to assess research proposals in scientific international settings. 


Assessment methods
  Continuous assessment Partial exams General exam
  • Written individual exam (traditional/online)
  •     x
  • Group assignment (report, exercise, presentation, project work etc.)
  •   x  
    ATTENDING STUDENTS

    Students' assessment will be based on three elements to assess the overall comprehension of the content of the course: a) testing that they fully understand the essential approaches of research methods, b) conducting a literature review to summarize scientific evidence in a transparent and systematic way, c) conceptualizing an original research proposal to be presented in class. Each of these elements tests different competences and provides students with the essential approaches to master research design in the social sciences.

     

    Grading

    ​​​​​Systematic review.  Short paper no longer than 3000 words to be delivered on October 9th (10%).

     

    Group project. Project proposal presented by 4 students delivered in the last four sessions of the course (20%).

     

    Final written exam. Two hours exam with multiple choice and 2 open-ended questions (70%).

    NOT ATTENDING STUDENTS

    Students' assessment will be based on two elements to assess the overall comprehension of the content of the course:  testing that students fully understand the essential approaches of research methods and writing an original research proposal. Each of the elements tests different competences and provides students with the essential approaches to understand research design in the social sciences.

     

     

    Grading

    Final written exam. Two hours exam with multiple choice and 2 open-ended questions (60%).

     

    Individual research proposal. A word document no longer than 10000 words to be submitted submitted no later than 10 days before the date of the exam (40%).


    Teaching materials
    ATTENDING AND NOT ATTENDING STUDENTS

    The main text used in the course is

     

    Dunning, T. 2012. Natural experiments in the social sciences. A design-based approach. Strategies for social inquiry.

     

    Other texts that cover research design and methods that can help students to cover possible methodological gaps on specific topic are:

     

    - Cunningham, S. 2021. Causal inference: The Mixtape.

    - Angrist JD and Pische JS. 2018. Mostly Harmless Econometrics

     

    Material for each syllabus is reported in the syllabus of the course

    Last change 22/05/2023 15:02