Important notice
The course guide is provisional.
The PDF version of the course guide may take a few days to become available in the DDD.
Research Techniques in Economics
Code: 45772Credits: 10
| Degree programme | Type | Course |
|---|---|---|
| Economic Analysis | OB | 2 |
Contact lecturer
- Name :
- Pau Roldan Blanco
- Email :
- pau.roldan@uab.cat
Teaching staff
- Marta Troya Martinez
- Pierre Magontier
- Amedeo Piolatto
- Francesco Ferlenga
- Luca Salvadori
- Peter Bayer
- Pau Milán Solé
- Mikhail Drugov Plitman
Teaching staff (external to UAB)
- Christopher Rauh
- Joan Llull Cabrer
Group languages
You can consult this information at the end of the document.
Prerequisites
No specific prerequisits.
Objectives
In this module students learn advanced research methods in Economics. These methods include frontier techniques in quantitative methods that allow the student to analyze complex datasets. Students will learn to use econometric techniques for both aggregate and micro data, networks and experimental methods. The different methods presented are used and derived from their theoretical foundations.
Learning outcomes
- CA25 (Design experiments integrating ethical and diversity criteria.) Design experiments integrating ethical and diversity criteria.
- CA26 (Develop evidence-based technical guides for companies and administrations.) Develop evidence-based technical guides for companies and administrations.
- CA27 (Create a framework of indicators for the monitoring of economic policies.) Create a framework of indicators for the monitoring of economic policies.
- CA28 (Apply sustainability approaches to the assessment of environmental impacts of economic decisions.) Apply sustainability approaches to the assessment of environmental impacts of economic decisions.
- CA29 (Communicate regulatory implications to non-specialist audiences clearly.) Communicate regulatory implications to non-specialist audiences clearly.
- KA41 (Identify advanced microeconometric techniques applied to labour market and development.) Identify advanced microeconometric techniques applied to labour market and development.
- KA42 (Explain theoretical labour market models and development for data interpretation.) Explain theoretical labour market models and development for data interpretation.
- KA43 (Describe principles of experimental economics and happiness for causal identification.) Describe principles of experimental economics and happiness for causal identification.
- SA35 (Apply advanced microeconometrics by generating reproducible code.) Apply advanced microeconometrics by generating reproducible code.
- SA36 (Experiment with experimental or quasi-experimental designs to detect causal effects.) Experiment with experimental or quasi-experimental designs to detect causal effects.
Contents
- Behavioural economics
- Economy of information
- Growth
- Industrial Organisation
- Microeconometrics
- Money and Banking
- Networks
- Policy evaluation
For a detailed description of the content of topics in this module go to https://sites.google.com/view/idea-program/master-program .
Learning activities and methodology
| Title | Hours | ECTS | Learning outcomes |
|---|---|---|---|
| Learning based on problem solving, personal study, study groups, | 150 | 6 | |
| Practice classes, problems sets, tutorials | 25 | 1 | |
| Theory classes | 75 | 3 |
The course will consist of sessions where the instructor presents the material, and sessions specifically dedicated to problem solving. Students are encouraged to form study groups to discuss assignments and readings.
The proposed teaching methodology may undergo some modifications according to the restrictions imposed by the health authorities on on-campus courses.
Assessment
Continuous assessment activities
| Title | Weight | Hours | ECTS | Learning outcomes |
|---|---|---|---|---|
| Midterm Exam | 26% | 0 | 0 | CA25, CA26, CA27, CA28, CA29, KA41, KA42, KA43, SA35, SA36 |
| Midterm Exam | 26% | 0 | 0 | CA25, CA26, CA27, CA28, CA29, KA41, KA42, KA43, SA35, SA36 |
| Class Attendance and Problem sets and assignments | 22% | 0 | 0 | CA25, CA26, CA27, CA28, CA29, KA41, KA42, KA43, SA35, SA36 |
| Midterm Exam | 26% | 0 | 0 | CA25, CA26, CA27, CA28, CA29, KA41, KA42, KA43, SA35, SA36 |
This modul does not contemplate an evaluation from a single comprehensive exam
Midterm Exam | 26% |
Midterm Exam | 26% |
Midterm Exam | 26% |
Problem sets, assignments & Class attendance and active participation | 22% |
The proposed evaluation activities may undergo some changes according to the restrictions imposed by the health authorities on on-campus courses.
In this course, the use of Artificial Intelligence (AI) technologies is not permitted in any of its phases. Any work that includes fragments generated with AI will be considered a breach of academic honesty and may result in a partial or total penalty to the activity's grade, or more severe sanctions in serious cases.
Bibliography
Akerlof, G.A., Kranton, R.E., 2000. Economics and Identity. Q. J. Econ. 115, 715—753
Alesina, A., Giuliano, P. and Nunn, N.: 2013, On the origins of gender roles: Women and the plough, The Quarterly Journal of Economics 128(2), 469–530.
Bartik, T.J., Who Benefits from State and Local Economic Development Policies, Kalamazoo, MI: W.E. Upjohn Institute for Employment Research,1991.
Bartolucci, Cristian, F. Devicienti, and I. Monz_on, Identifying Sorting in Practice,\" American Economic Journal: Applied Economics,October 2018, 10 (4), 408{438.
Baskaran, T., Min, B. and Uppal, Y.: 2015, Election cycles and electricity provision: Evidence from a quasi-experiment with indian special elections, Journal of Public Economics 126, 64–73.
Becker, S. O. and Woessmann, L.: 2009, Was weber wrong? a human capital theory of protestant economic history, The Quarterly Journal of Economics 124(2), 531–596.
Berndt, Ernst R., B. H. Hall, R. E. Hall, and Jerry A. Hausman, \\Estimation and Inference in Nonlinear Structural Models,\" Annal of Economic and Social Measurement, October 1974, 3 (4), 653{666.
Bisin, A., Verdier, T., 2001. The Economics of Cultural Transmission and the Dynamics of Preferences. J. Econ. Theory 97, 298--319.
Black, S. E.: 1999, Do better schools matter? parental valuation of elementary education, The Quarterly Journal of Economics 114(2), 577–599.
Blundell, R. and S. Bond, \\Initial Conditions and Moment Restrictionsin Dynamic Panel Data Models,\" Journal of Econometrics, August 1998, 87 (1), 115{143. and , \\GMM Estimation with Persistent Panel Data: An Application to Production Functions,\" Econometric Reviews, March 2000, 19 (3), 321{340.
Bonhomme, S., T. Lamadon, and E. Manresa, \\A Distributional Framework for Matched Employer Employee Data,\" Econometrica, May 2019, 87 (3), 699{739.
Brodeur, A., Lekfuangfu, W. N. and Zylberberg, Y.: 2017, War, migration and the origins of the thai sex industry, Journal of the European Economic Association 16(5), 1540–1576.
Camacho, M., G. Pérez Quirós and H. Rodríguez Mendizábal (2013): “Mixing the Ingredients: Business cycles, Technology Shocks, Productivity Slowdown and the Great Moderation”, unpublished manuscript
Carvalho, J.-P. (2013) \"Veiling\" Quarterly Journal of Economics 128(1); 337-370
Caselli, F.and W. J. Coleman, II, On The Theory of Ethnic Conflict, Journal of the European Economic Association, Volume 11, Issue suppl_1, 1 January 2013, Pages 161-192
Christiano, L. J., M. Eichenbaum, and C. L. Evans (1999): “Monetary Policy Shocks: What Have We Learned and to What End?,” in J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 2: 65-148, Elsevier.
Cooley, T. F. and G. D. Hansen (1995): “Money and the Business Cycle,” in T. F. Cooley (ed.) Frontiers of Business Cycle Research, Princeton University Press.
Gali, J. (1999): “Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?” American Economic Review, 89(1): 249-271.
Jackson, M. O. Social and economic networks. Princeton University Press,2010.
Newman, M.. Networks: an introduction. Oxford University Press, 2009.
Toke, A. , F. Albornoz and E. Hauk (2021) “Foreign influence in domestic policy”, Journal of Economic Literature 59(2):426-87
Additional references will be provided during the course.
Software
- Matlab
- R
- Phyton
- Stata
Course groups and languages
The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE