Course: Applied Economics Methods

Syllabus of the course

Starting day: 21 Mar 2016

Instructors: Prof. Gianfranco Atzeni, Prof. Silvia Balia, Prof. Rinaldo Brau, Prof. Manuela Pulina, Prof. Giovanni Sulis

Contacts: atzeni@uniss.it; silvia.balia@unica.it; brau@unica.it; mpulina@uniss.it, gsulis@unica.it

Module 1: Identification and estimation methods for structural equation models, Prof. Silvia Balia and Rinaldo Brau.

Lecture 1: Identification issues in triangular and fully simultaneous equation systems,         Rinaldo Brau, 21 Mar 2016, h. 14:30 – 17:00

Reading:

• Lecture handouts (to be uploaded in a private dropbox space)
• Rigobon Roberto, “Identification Through Heteroskedasticity.” Review of Economics and Statistics, 2003, vol. 85, issue 4.
• Joshua D. Angrist and Alan B. Krueger, Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments, Journal of Economic Perspectives—Volume 15, Number 4—Fall 2001—Pages 69–85

Lecture 2: Identification through heteroscedasticity and control function approaches,               Rinaldo Brau, 23 Mar.2016, h. 10:00 – 12:30

Reading:

• Lewbel Arthur, “Using Heteroskedasticity to Identify and Estimate Mismeasured and Endogenous Regressor Models, Journal of Business & Economic Statistics, Volume 30, Issue 1, pages 67-80.
• Klein, R. and Vella, F. 2010. “Estimating a Class of Triangular Simultaneous Equations Models without Exclusion Restrictions,” 154–164. Journal of Econometrics 154
• Farré, Lídia, Roger Klein, and Francis Vella (2013) “A parametric control function approach to estimating the returns to schooling in the absence of exclusion restrictions: an application to the NLSY”, Empirical Economics, 43 (1), 2013.

Lecture 3: Simulation-based maximum likelihood for categorical data: application to multiple equations models, Silvia Balia, 30 Mar.2016, h. 14:00 – 17:00

Reading:

• Lecture handouts (to be uploaded in a private dropbox space)
• Chapter 5 in Andrew M. Jones, Nigel Rice, Teresa Bago d’Uva, Silvia Balia (2012). Applied Health Economics, 2nd Edition, Routledge.
• Chapter 12 (12.4.2, 12.6.1) Panel Data Methods and Applications to Health Economics in The Palgrave Handbook of Applied Econometrics (2009) edited by Terence Mills and Kerry Patterson.

Lecture 4: Unobservable heterogeneity and finite mixture models in non-linear models: applications to multiple equations models using latent classes and discrete factor models, Silvia Balia, 31 Mar.2016, h. 14:00 – 17:00

Reading:

• Lecture handouts (to be uploaded in a private dropbox space)
• Chapter 18 (18.1-18.5) in Colin Cameron and Pravin Trivedi (2005) Microeconometrics Cambridge University Press, New York
• Chapter 14 (14.1, 14.2, 14.3.1, 14.3.2, 14.3.3) Microeconometrics: Current Methods and Some Recent Developments in The Palgrave Handbook of Applied Econometrics (2009) edited by Terence Mills and Kerry Patterson.
• Balia S, Brau R (2014). A country for old men? Long-term home care utilization in Europe. Health Economics, vol. 23, p. 1185-1212
   

Module 2: Limited dependent variable models, Prof. Gianfranco Atzeni.

Lecture 5: Censored and truncated regression models, Sassari 4 Apr 2016, h. 15:00 – 17:00

Readings:

• Greene ch 19 – Limited Dependent Variables, truncation and sample selection available to download at: http://people.stern.nyu.edu/wgreene/Lugano2013/Greene-Chapter-19.pdf

Lecture 6: Two stage estimation models, Sassari 5 Apr 2016, h. 10:00 – 12:00

Readings:

• Cotei and Farhat (2007), An Application of the Two-Stage Bivariate    Probit-Tobit Model to Corporate Financing Decisions available to download at: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1478882

Lecture 7: Self-selection models, Sassari 6 Apr 2016, h. 15:00 – 17:00

Readings:

• Li and Prabhala, Self-Selection Models in Corporate Finance

Module 3: Equilibrium search models and wage differentials, Prof. Giovanni Sulis.

Lecture 8: Basic Search Model and Gender Differentials, 14 Apr 2016, h. 14:00 – 17:00

Readings:

• Zvi Eckstein, Gerard J. van den Berg. Empirical Labor Search: A Survey. Journal of Econometrics 136 (2007) 531–564
• Richard Rogerson, Robert Shimer and Randall Wright. Search-Theoretic Models of the Labor Market: A Survey. Journal of Economic Literature. Vol. XLIII (December 2005), pp. 959–988
• http://wol.iza.org/articles/wage-compression-and-gender-pay-gap
• http://wol.iza.org/articles/equal-pay-legislation-and-the-gender-wage-gap

Lecture 9: Equilibrium Search Models and Structural Estimation, 15 Apr 2016, h. 09:00 – 12:00

Readings:

• Mortensen, Dale (2003) Why Are Similar Workers Paid Differently? MIT Press.
• Burdett, K. and Mortensen, D. (1998), “Wage Differentials, Employer Size, and Unemployment,” International Economic Review, 39 (2), 257-73;
• Sulis, G. (2012), “Gender Wage Differentials in Italy: A Structural Estimation Approach,” Journal of Population Economics, Springer, vol. 25(1), pages 53-87, January;
• Sulis, G. (2011), “What Can Monopsony Explain of the Gender Wage Differential in Italy?” International Journal of Manpower, 32 (4), 446-470.

Module 4: Mixed methods in applied economics, Prof. Manuela Pulina.

Lecture 10: Survey methodology and Factor analysis (SPSS simulations) 26 Apr 2016, h. 15:00 – 18:00

Readings:

• An Gie Yong and Sean Pearce 2013. A Beginner’s Guide to Factor Analysis: Focusing on Exploratory Factor Analysis. Tutorials in Quantitative Methods for Psychology, 9(2), 79-94. http://www.tqmp.org/RegularArticles/vol09-2/p079/p079.pdf

Lectures handouts (Slides)

Lecture 11: Mixed methods analysis (STATA simulations), 27 Apr 2016, h. 15:00-18:00

Readings:

• Greene, W. (2013) Binary Choice – Nonlinear Modeling. In Empirical Methods for Microeconomic Applications.

Lectures handouts (Slides)

Course Material

There is no textbook for this course. See the reading lists above.

Course Assessment

The introductory lectures by prof. Brau will not be part of the exam.

The grading will be based on two parts:

• an essay dealing with topics treated in one of the four modules
• a written exam where students are supposed to answer to two questions related to the other three modules

READ ME FIRST: This is the list of optional courses for the II semester. Each student should earn a minimum of 12 credits. The deadline to communicate the doctoral student’s choice of the course is: 19^th February at 1 p.m.

In addition to the courses chosen, each student is recommended to communicate also an additional course, that s/he is interesting in taking if one of the courses chosen is to be cancelled because it does not meet the minimum number of students enrolled.

Advanced Macroeconomics (6 CFU)
Instructor: Fabio Cerina, Miguel Leon-Ledesma, Alessio Moro
Location: UNICA
Period: March-May 2016

The purpose of the course is to provide an overview of the following topics: models of Structural Change; Models in International economics, Models in Agglomeration, growth and trade

Evaluation
The grading will be based on two parts:
– an essay dealing with topics treated in one of the three modules
– a written exam on the other two modules

Applied Economics Methods (6 CFU)
Instructor: Gianfranco Atzeni, Silvia Balia, Rinaldo Brau, Manuela Pulina, Giovanni Sulis
Location: UNICA-UNISS
Period: March-April 2016

The purpose of the course is to provide an overview of the following topics: Identification and estimation methods for structural equation models; Limited dependent variable models; Equilibrium search models and wage differentials; Mixed methods in applied economics.

Evaluation
The grading will be based on two parts:
– an essay dealing with topics treated in one of the four modules
– a written exam where students are supposed to answer to two questions related to the other three modules

Advanced Regression methods (with application in R) (3 CFU)
Instructor: Claudio Conversano, Luca Frigau
Location: UNICA
Period: March 2016

The purpose of the course is to provide an overview of the following topics: Linear regression models and its extensions; Regression with K-nearest neighbors; Resampling methods in linear regression; Linear model selection and regularization.

Evaluation
The grading will be based on a written exam where students are supposed to answer to the abovementioned topics.

Classification (with application in R) (3 CFU)
Instructor: A. Wilhelm
Location: UNICA
Period: April-May 2016

The purpose of the course is to provide an overview of the following topics: Logistic regression; Linear Discriminant Analysis and extensions; Classification with K-nearest neighbors; Resampling methods in classification.

Evaluation
The grading will be based on a written exam where students are supposed to answer to the abovementioned topics.

Statistics for economic and Social Application (4 CFU)
Instructor: M. Cannas
Location: UNICA
Period: April-May 2016

The purpose of the course is to provide an overview of the following topics: Random variables; Sampling theory; Maximum likelihood estimation methods; Decision theory (overview).

Evaluation
The grading will be based on a written exam where students are supposed to answer to the abovementioned topics.

Topics in Vector Generalized Additive Models (3 CFU)
Instructor: T. Yee (University of Auckland)
Location: UNICA
Period: May-June 2016

This course will look at both the theory and the practical aspects of vector generalized linear and additive modelling. The VGLM/VGAM class provides a very convenient statistical framework from which to perform many types of common statistical analyses. The focus of the workshop is to be practical; therefore it will have a large practical (computer) component doing real data analysis. The aim of the course is to show students how to apply several common statistical techniques to real data. By the end of the course students should be able to apply these methods confidently on their own data sets.

Evaluation
The grading will be based on a written exam where students are supposed to answer to the abovementioned topics.

ORGANIZATION Theory (4 CFU)
Instructor: M.Chiara Di Guardo
Location: UNICA
Period: September 2016

The purpose of the course is to provide a roadmap to roam the terrain of organizational theory. This course introduces doctoral students to the principal theoretical perspectives and empirical findings used to explain relationships among environments, organizational strategies, designs, and performance.

Public Management (6 CFU)
Instructor: Alberto Asquer; Enrico Deidda Gagliardo; Patrizio Monfardini; Aldo Pavan; Alessandro Spano; Ileana Steccolini
Location: UNICA
Period: end of April-May 2016

The course aims at providing participants with an overview of Public Sector management theories, from Public Administration, to New Political Management and Public Value. The main reforms that took place in western countries will also be analysed with a comparative approach, with a focus on the implementation gap between the designed and the implemented reforms. In this framework, performance management systems in public sector organizations plays a significant role and will be investigated during the course. Specific issues such as financial management and the merger of local governments will complement the above-mentioned topics.

Evaluation
The final grade will be based on active, individual participation (40%) and on an assignment: each student will be asked to choose one topic linked public sector management issues, make a literature review and prepare a final report (60%).

Students are required to attend all classes; in case of a maximum absence of up to two classes the attribution of the credits will be considered.

Research design in Accounting, Governance and Reporting (6 CFU)
Instructor: Andrea Melis, Patrizio Monfardini, Alessandro Mura, Simone Aresu
Location: UNICA
Period: end of March-May 2016

The course aims to introduce doctoral students to a variety of theories (agency theory, institutional theory, legitimacy theory, rent-extraction theory, stewardship theory, etc.) and research methods widely used in accounting, corporate governance and reporting research published in international academic journals. The course relies on prior conceptual and empirical literature to address some of the major conceptual and design issues. Each class will consist of two teaching and learning components. During the first part of the class, the doctoral students will present and lead the discussion of the readings previously assigned to them. During the second part, the instructor will provide an overview of the conceptual and methodological topics of a paper published in an international academic journal from an author’s perspective.

Evaluation
The final grade will be based on three components of the PhD student’s work in the course: class presentations, class participation and written critical reviews.
– Class presentations: The PhD student will prepare presentations of research papers assigned to him/her and will lead the discussion of these papers. The number and the schedule of presentations will depend on the number of students registered in the course. Papers will be assigned one week before each class.
– Class participation: The PhD student is expected to actively and constructively participate in each class by asking questions, making comments and providing feedback on all required readings covered in the course.
– Critical reviews: At the end of the course, the PhD student will submit written critical reviews of two research papers, assigned by the instructor and not previously presented in class. Each review must not exceed four single‐spaced pages.

RESEARCH METHODOLOGY IN BUSINESS ADMINISTRATION (6 CFU)
Instructor: Aldo Pavan, Isabella Fadda
Location: UNICA
Period: March 2016

The course aims at introducing students to the basic concepts of the theory of knowledge and epistemology. The short-term objective is to provide the student with knowledge and tools to assist him in doing his final project and dissertation for the doctoral programme. The long-term objective is to help the student develop his ability to deal with research or problem solving studies and reports in his role both as a scholar or as a manager:
– to initiate and define research projects;
– to evaluate critically reports and papers;
– to conduct a research project and write a paper or a report.

It is important to recognise that in order to achieve the above the course is also about the much broader issue of how the student relates to the real world in his everyday life. It is about how he derives meaning from the mass of information available to him, how he makes judgements on the validity and relevance of that information and how he learns and develops more effective theories and models.

Evaluation
Students may choose to present one of the following:
A project for a master degree final dissertation
A critical analysis of a published paper
A presentation of an out-of-syllabus subject

Selected topics in Statistical learning (with application in R)(3 CFU)
Instructor: Claudio Conversano, Luca Frigau
Location: UNICA
Period: April 2016

The purpose of the course is to provide an overview of the following topics: Tree based methods and extensions; Principal component analysis; Clustering.

Evaluation
The grading will be based on a written exam where students are supposed to answer to the abovementioned topics.

 STRATEGIC MANAGEMENT (4 CFU)
Instructor: Francesca Cabiddu
Location: UNICA
Period: September 2016

The course aims to introduce doctoral students to strategic management exploring some threads of the development and articulation of the strategic management field through an introductory journey conducted with the help of a “helicopter view” of relevant strategy streams. Moreover, it offers ways of how they can make use of theoretical evolution to advance strategy and entrepreneurship analysis and support strategic choices especially at the firm (i.e., corporate/business), industry and entrepreneurial levels.

RISK MANAGEMENT (3 CFU)
Instructor: Marcello Galeotti (University of Florence)
Location: UNICA
Period: June 2016

The purpose of the course is to provide an overview of the following topics: Quantitative risk management (risk aversion, VaR, Expected shortfall, arbitrage and risk neutral probability), Extreme value theory (Light and heavy tails distributions, Hazard rate, Fisher-Tippet theorem, Generalized Pareto distribution).

Evaluation
The grading will be based on a written exam where students are supposed to answer to the abovementioned topics.

Because of an unexpected health issue, the aforementioned seminar has been cancelled. Students will receive as soon as possible a new info for the new date. Sorry for any inconvenience.