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# Econometrics I

 Code 12101 Year 3 Semester S1 ECTS Credits 6 Workload TP(60H) Scientific area Economics Entry requirements - Probabilities and Statistics - Statistics Applied to Economics - Spreadsheet basics Mode of delivery Face-to-face Work placements Not applicable Learning outcomes - Familiarize students with the instruments and techniques for the development and interpretation of econometric models.- Develop knowledge of econometric subjects that are essential for carrying out work of a theoretical and empirical nature.- To design and develop strategies to adapt the studied methods to real problems.- To initiate students in the use of widely used programs in the academic and professional field (mainly Eviews and R). Syllabus 1. Introduction: object and methodology of econometrics2. Data analysis and transformation3. Linear regression model (LRM)3.1 Correlation and causality3.2 Violation of assumptions3.3 Quality of fit3.4 Confidence intervals3.5 Hypothesis tests4.Model evaluation and diagnostic tests4.1 F test4.2 Coefficient of determination4.3 Test for normality4.4 Multicollinearity4.5 Heteroscedasticity4.6 Structure permanence tests5.Some extensions of LRM5.1 Functional form of regression models.5.2 Binary variables.5.3 Descriptive models of trend and seasonality.5.4 Coefficients tests of two regressions.5.5 Robust least squares method.5.6 Weighted Least Squares Method.6.Models with Qualitative Dependent Variable6.1 Introduction: binary choice models6.2 Linear Probability Models6.3 Probit and Logit Models Main Bibliography Wooldridge, Jeffrey M., Introductory econometrics: a modern approach. 7th ed., South-Western/Cengage Learning, 2019Asteriou, Dimitrios e Hall, Stephen G., Applied Econometrics, Palgrave Macmilan, 4th Ed., 2021Christoph Hanck, Martin Arnold, Alexander Gerber, and Martin Schmelzer, Introduction to Econometrics with R, 2023 Language Portuguese. Tutorial support is available in English.

### Course

Economics
Last updated on: 2023-10-02

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