NOVA Information Management School

Inferential Analytics

Code

200047

Academic unit

NOVA Information Management School

Credits

7.5

Teacher in charge

Manuel José Vilares

Teaching language

Portuguese. If there are Erasmus students, classes will be taught in English

Objectives

At the end of the course ,the student shall understand:

  1. The Classical Multiple Regression Models. The assumptions, The Estimation Method and The Proprieties of the Estimators;

  2. The Generalized Multiple Regression Models. The case of the Heterocedasticity;

  3. The Binary logit Model . The model, the estimation , the tests of the model validity and applications;

  4. The binary probit model. the model, the estimation, the tests of the model validity and applications

  5. The models with no ordered multinominal variables

  6. censored and truncated regression models

  7. Prerequisites

    A reasonable background in statistics  and linear algebra

     

    Subject matter

    Bibliography

    GREENE, W. H.(1997) Econometric Analysis, Third Edition, Prentice-Hall, New Jersey; HEIJ, C; De BOER, P.; FRANSES, P.H; KLOEK,T, VAN DIJK, H.K (2004) Econometric Methods with Applications in Business and Economics, Oxford University Press ; Johnston, J.; Dinardo, J. (1997). Econometrics Methods. 4th Edition, Economics Series, McGraw Hill (Existe também tradução em português). ISBN 007115342X; Wooldridge, Jeffrey M. (2008). Introductory econometrics: a modern approach, 4th ed. South-Western. ISBN 9780324585483; Other references will be given in class

    Teaching method

    The course will have theoretical and applied lessons

    In the theoretical lessons, the instructor introduces and presents the different topics of the program. In the practical lessons the instructor will provide examples and applications of the topics and invites the students to solve the exercises using the information they get from the theoretical lessons

    An important part of the class, and the term paper/project, involves the use of econometric software (SAS EG or programming). The instructions on how to use the software will be given in class and during scheduled office hours, whenever students consider it necessary

    Evaluation method

     

    The final grade will be a weighted average.

    Students can choose from the following two options:

    Option  A

    • Term project  50%

    • Final Exam   50%

      Option B

    • Final Exam   100%

       

    The final grade will correspond to the highest from the two options mentioned above. A minimum grade of 9.5 points (from 20) in the final exam is required to pass the course.

    Students are expected to develop a project where they should demonstrate their ability to apply econometric methods in a practical context. Although the work can be developed by a maximum of three students, instructors can require an individual discussion in order to clarify the participation of each student in the project development. Students have to submit a proj

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