Checking date: 19/05/2024


Course: 2024/2025

Advanced Research Methods I
(19308)
Master in Social Sciences (Plan: 481 - Estudio: 325)
EPC


Coordinating teacher: LEON ALFONSO, SANDRA

Department assigned to the subject: Social Sciences Department

Type: Compulsory
ECTS Credits: 6.0 ECTS

Course:
Semester:




Requirements (Subjects that are assumed to be known)
Statistics I Statistics II
Objectives
Knowledge or Content: K-7. Advanced knowledge and understanding of statistics applied to Social Sciences. K-8. Specialized and applied learning of quantitative research methods in the study of political and social phenomena. K-9. Advanced learning about the role of causality in Social Sciences. Skills: S-5. Ability to organize and express ideas clearly and unambiguously, and to support theoretical arguments on a topic through a critical analysis of the literature. S-7. Understanding the fundamental concepts of descriptive statistics, probability theory, and the foundations of inferential statistics. S-8. Knowing the properties of different types of quantitative data associated with the study of Social Sciences and mastering data analysis techniques. S-9. Understanding the techniques of causal inference in social research. Competences: C-7. Ability to select appropriate statistical models for data analysis within the framework of conducting research in Social Sciences. C-8. Handling quantitative research data: mastering analysis tools and data management software in the empirical development of a research paper. C-9. Being able to generate new data and apply causal inference techniques in the empirical development of a research question.
Skills and learning outcomes
Description of contents: programme
1. Causality and Counterfactuals 2. Regressions and causal effects 3. Matching Models 4. Synthetic controls 5. Differences-in-Differences 6. Natural Experiments 7. Instrumental Variables 8. Regression Discontinuity Design 9. New Trends in Causal Inference
Learning activities and methodology
Training Activities: AF3 - Theoretical-practical class: learning theoretical content on mathematics, statistics, and causal inference. AF4 - Laboratory practices: using software programs on computers to develop statistical models learned in theoretical classes. AF5 - Tutorials: the possibility of weekly meetings with the course instructor. AF6 - Individual student work. Teaching Methodologies: MD1 - Classroom presentations by the professor with the support of computer and audiovisual media, in which the main concepts of the subject are developed. MD2 - Critical reading of texts recommended by the subject professor: press articles, reports, manuals, and/or academic articles. MD3 - Resolution of practical cases, problems, etc., proposed by the professor individually or in groups. MD5 - Preparation of individual or group assignments and reports.
Assessment System
  • % end-of-term-examination 70
  • % of continuous assessment (assigments, laboratory, practicals...) 30

Calendar of Continuous assessment


Basic Bibliography
  • Angrist and Pischke. Mostly Harmless Econometrics. An Empiricist's Companion. Princeton University Press. 2008
  • Jeffrey M. Wooldridge. Econometric Analysis of Cross Section and Panel Data. The MIT Press. 2010
  • Morgan and Winship. Counterfactuals and causal inference. Methods and Principles for Social Research. Cambridge University Press. 2007
Recursos electrónicosElectronic Resources *
Additional Bibliography
  • Imbens y Rubin. Causal Inference for Statistics, Social, and Biomedical Sciences. Cambridge University Press. 2015
(*) Access to some electronic resources may be restricted to members of the university community and require validation through Campus Global. If you try to connect from outside of the University you will need to set up a VPN


The course syllabus may change due academic events or other reasons.