Global School 3-14 DECEMBER 2018-MEDELLÍN, COLOMBIA Global School in Empirical Research Methods (GSERM) at Universidad EAFIT, 2018 2 MEDELLÍN Medellín is a dynamic metropolis that has undergone a cultural, social, and economic transformation in recent years. Colombia’s second city both economically and in terms of number of inhabitants, it is located 1,538 meters (5,046 feet) above sea level, boasts a temperate climate with year-round temperatures ranging from between 18 and 28 degrees Celsius (64 and 82 degrees Fahrenheit), and has a history dating back nearly 340 years. The Medellín metropolitan area, which comprises 10 municipalities located in the Aburrá Valley, currently is home to roughly 3,800,000 people. This urban conglomerate in northwestern Colombia (nestled amid the Andes’ Cordillera Central range) hosts world-class events such as the Flower Festival, the International Poetry Festival, the Medellín Book and Culture Festival, Colombiamoda, and Colombiatex. 3 EAFIT EAFIT is a university with 57 years of history that inspires the current generations to embark on a life project that maximizes their potential. An institution that both conveys and generates knowledge, thus fulfilling its role as a teaching and research university. A place that transforms society. EAFIT currently offers 22 undergraduate degree programs, nearly 50 graduate certificate programs, 34 master’s degree programs, and 6 doctorate programs in the schools of Management, Engineering, Humanities, Law, Economics and Finance, and Sciences, and It has been recognized in three times with the Institutional Accreditation conferred by the National Education Ministry MEN. (2003, 2010 and 2018). Research-backed teaching is a focal point of the institution’s road map, in so far as the goal is to not only convey but also generate knowledge. In that regard, the budget allocated to this area has been maintained and enabled EAFIT to achieve a range of objectives, including recognition by Colciencias of 41 research groups, the registration of 37 patents, and the participation of more than 1,170 students in research incubators. The institution’s reach also extends to other publics and in other parts of Colombia like EAFIT Bogotá, EAFIT Pereira, and EAFIT Llanogrande. All of these processes take place on a campus where the built infrastructure coexists with different species of flora and fauna to make a university-park equipped with cutting-edge technology. Music, literature, dance, theater, film cycles, exhibitions, and other artistic manifestations make up a cultural agenda that permeates all parts of campus, enables the formation of groups with shared interests, and fosters the organization’s reach and impact both externally and internally. And it is in this context, in which the university strives to give back all it has received from society, that its social responsibility efforts are infused with a greater sense of purpose. With these strategic commitments in mind, EAFIT is firm in its promise to inspire, create and transform. 4 5 6 COURSES 1ST SESSION: 3-7 DECEMBER 2018 Instructor Course Date Level ECTS Michael Lechner Causal Inference 3 - 7 December 2018 R 4 Machine Learning with Brett Lantz 3 - 7 December 2018 B 4 R – Introduction Andrew Bennett Case Study Methods 3 - 7 December 2018 B 4 2ND SESSION: 10-14 DECEMBER 2018 Instructor Course Date Level ECTS Carsten Q. Qualitative 10 - 14 December 2018 M 4 Schneider Comparative Analysis Sarah K. Jacobson Experimental Methods 10 - 14 December 2018 B 4 Sera Linardi for Behavioral Science Christian B. Econometrics 10 - 14 December 2018 R 4 Hansen of Big Data B = Basic | M = Intermediate | A = Advanced | R = Research Courses start at CHF 1000 (approx. USD 1050) | Deadline for application is 15 November 2018. PRICING COSTS PROGRAMME FEE EARLY BIRD DISCOUNT UNTIL 3O SEPTEMBER 2018 1 course (1 week) CHF 1000 (approx. USD 1’050) Discount for 1 course CHF 200 (USD 210) 2 courses (2 weeks) CHF 1900 (approx. USD 1’995) Discount for 2 courses CHF 300 (USD 315) 7 DESCRIPTION CAUSAL INFERENCE Modern microeconometrics has in empirical practice, such as we discuss estimation principles as the goal of empirically establishing matching, instrumental variables, well as particular estimators suitable and quantifying causal relations regression discontinuity designs for the context of the particular between interesting variables, such as well as difference-in-difference design. Finally, some time will be as participating in some government estimation based on cross-sectional devoted to look in more detail in intervention and individual labour and panel data. The methods will an empirical paper that uses the market outcomes. be explained together with their particular methods. These empirical potential virtues and limitations papers will come from the fields of In this course we discuss the in different disciplines. For each of labour, health and sports economics. most relevant methods (also the different research designs we Usually, in the morning we discuss called research designs in start with a general discussion of the theory while the afternoon is microeconometrics) that are used its key assumptions and how they devoted to empirical applications. relate to empirical settings. Next, 8 MACHINE LEARNING WITH R-INTRODUCTION Machine learning, put simply, most common machine learning involves teaching computers to techniques, but no advanced math learn from experience, typically or programming skills are required. for the purpose of identifying or The target audience may include responding to patterns or making social scientists or practitioners predictions about what may happen who are interested in understanding in the future. This course is intended more about these methods and to be an introduction to machine their applications. Students with learning methods through the extensive programming or statistics exploration of real-world examples. experience may be better served by a We will cover the basic math more theoretical course and statistical theory needed to on these methods. understand and apply many of the 9 CASE STUDY METHODS The course is designed for Master, but not required. Materials not in PhD students and practitioners the books assigned for purchase in the social and policy sciences, and not easily available through including political science, sociology, online library databases will be made public policy, public administration, available electronically. Bringing a business, and economics. Previous laptop to class will be helpful but is courses in research methods and not essential. philosophy of science are helpful 10 QUALITATIVE COMPARATIVE ANALYSIS This course introduces participants and discuss the most important data aggregation and the treatment to set-theoretic methods and problems that emerge when this of causally relevant notions of their application in the social analytical tool is used for exploring time. Examples are drawn from sciences with a focus on Qualitative social science data. Right from the published applications in the Comparative Analysis. The beginning, students will be exposed social sciences. Participants are course starts out by familiarizing to performing set-theoretic analyses encouraged to bring their own raw students with the basic concepts with the relevant R software data for in-class exercises and of the underlying methodological packages. When discussing set- assignments, if available. By the perspective, among them the theoretic methods, in-class debates end of the course, participants will central notions of necessity and will engage on broad, general be able to perform set-theoretic sufficiency, formal logic and Boolean comparative social research issues, analyses of their own and to algebra. From there, we move to the such as case selection principles, critically evaluate published QCA. logic and analysis of truth tables concept formation, questions of 11 EXPERIMENTAL METHODS FOR BEHAVIORAL SCIENCE This course provides an introduction Students in this course will develop Topics covered during this course to the use of experiments in the an understanding of the elements include: design and implementation social sciences. Well-designed of good experimental design and of experiments, field and internet experiments, in both the lab and the implementation and examine the experiments, classic games, and field, provide the control necessary interaction between theory and individual preference experiments to identify causal relationships and experimental design. Students will (risk, time, social). We will use studies to cleanly test theoretical constructs. further advance their knowledge in specific topic areas (environmental Experiments are an important part through experience: they will work and natural resource applications, of the social science toolkit, and are individually or in teams throughout and social policy, especially in becoming increasingly indispensable the course to develop and pilot interventions targeted to the poor) parts of the methodological toolkit their own experiment design, and to demonstrate central concepts in in economics, political science, and they will receive feedback from social science experimentation. other disciplines. instructors and fellow students. 12 ECONOMETRICS OF BIG DATA As in many other fields, economists provide a vehicle for modeling and building prediction models in high- are increasingly making use of analyzing complex phenomena dimensional settings. Second, we high-dimensional models – models and for incorporating rich sources