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Research Techniques in Economics

Code: 40170 ECTS Credits: 10
2024/2025
Degree Type Year
4313805 Economic Analysis OT 2

Contact

Name:
Amedeo Stefano Edoardo Piolatto
Email:
amedeo.piolatto@uab.cat

Teachers

Joan Llull Cabrer
Pau Milán Solé
Mikhail Drugov Plitman
(External) Hugo Rodríguez Mendizabal
(External) Marta Troya Martinez
(External) Pau Roldán
(External) Peter Bayer

Teaching groups languages

You can view this information at the end of this document.


Prerequisites

No specific prerequisits.


Objectives and Contextualisation

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. 

 


Competences

  • Apply the methodology of research, techniques and specific advanced resources to research and produce innovative results in a specific area of specialisation
  • Capacity to articulate basic economic theory, analytically deriving them from mathematical reasoning
  • Capacity to identify basic statistical analysis and econometric techniques deriving them from the laws of probability and statistics
  • Demonstrate an open , innovative and analytical attitude towards research questions
  • Design, plan and carry out economic research
  • Develop the ability to assess sex and gender inequalities in order to design solutions.
  • Make independent judgements and defend them dialectically
  • Possess and understand knowledge that provides a basis or opportunity for originality in the development and/or application of ideas, often in a research context
  • Search for information in the scientific literature using the appropriate channels and integrate the information to propose and contextualise a research topic
  • Student should possess the learning skills that enable them to continue studying in a way that is largely student led or independent
  • Students should be able to integrate knowledge and face the complexity of making judgements based on information that may be incomplete or limited and includes reflections on the social and ethical responsibilities associated with the application of their knowledge and judgements
  • Students should know how to apply the knowledge they have acquired and their capacity for problem solving in new or little known fields within wider (or multidisciplinary) contexts related to the area of study
  • Students should know how to communicate their conclusions, knowledge and final reasoning that they hold in front of specialist and non-specialist audiences clearly and unambiguously
  • Use new technology for the collection and organisation of information to solve problems in professional activities
  • Use the main computer packages to program economic data analysis

Learning Outcomes

  1. Adapt microeconometric methodologies to specific fields such as the labour market or immigration or education policies
  2. Apply the methodology of research, techniques and specific advanced resources to research and produce innovative results in a specific area of specialisation
  3. Conceptualise the design of an experiment and the analysis of data to give a rigorous response to an economic question
  4. Demonstrate an open , innovative and analytical attitude towards research questions
  5. Describe the models of decision-making that include different assumptions from the neoclassical ones on the behaviour of economic agents
  6. Know how to apply the instruments of gender perspective in the analysis of organisations.
  7. Know how to carry out a gender-sensitive analysis.
  8. Know how to carry out research with a gender perspective.
  9. Know how to integrate the conditions and needs of women and men, in addition to a human- rights approach, into development-cooperation policies.
  10. Know how to make an inclusive and non-sexist use of language.
  11. Make independent judgements and defend them dialectically
  12. Possess and understand knowledge that provides a basis or opportunity for originality in the development and/or application of ideas, often in a research context
  13. Produce, collect and interpret empirical data in a gender-sensitive manner.
  14. Program microeconometric methodologies in different applied contexts
  15. Search for information in the scientific literature using the appropriate channels and integrate the information to propose and contextualise a research topic
  16. Student should possess the learning skills that enable them to continue studying in a way that is largely student led or independent
  17. Students should be able to integrate knowledge and face the complexity of making judgements based on information that may be incomplete or limited and includes reflections on the social and ethical responsibilities associated with the application of their knowledge and judgements
  18. Students should know how to apply the knowledge they have acquired and their capacity for problem solving in new or little known fields within wider (or multidisciplinary) contexts related to the area of study
  19. Students should know how to communicate their conclusions, knowledge and final reasoning that they hold in front of specialist and non-specialist audiences clearly and unambiguously
  20. Use new technology for the collection and organisation of information to solve problems in professional activities

Content

  • 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 .


Activities and Methodology

Title Hours ECTS Learning Outcomes
Type: Directed      
Theory classes 75 3 1, 2, 3, 4, 5, 11, 12, 14, 15, 16, 17, 18, 19, 20
Type: Supervised      
Practice classes, problems sets, tutorials 25 1 1, 2, 3, 4, 5, 11, 12, 14, 15, 16, 17, 18, 19, 20
Type: Autonomous      
Learning based on problem solving, personal study, study groups, 150 6 1, 2, 3, 4, 5, 11, 12, 14, 15, 16, 17, 18, 19, 20

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.

 

Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.


Assessment

Continous Assessment Activities

Title Weighting Hours ECTS Learning Outcomes
Class Attendance and Problem sets and assignments 22% 0 0 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20
Midterm Exam 26% 0 0 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20
Midterm Exam 26% 0 0 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20
Midterm Exam 26% 0 0 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20

 

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. 


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

Language list

Name Group Language Semester Turn
(PLABm) Practical laboratories (master) 30 English annual morning-mixed
(TEm) Theory (master) 30 English annual morning-mixed