INTRODUCTION TO ECONOMETRICS

The course aims at providing the students with the terminology and the most relevant statistical tools needed for the implementation of empirical/quantitative analyses. This with the objective of addressing interesting questions in the area of economics and management. Through an introduction to the main econometric models and to the fundamentals of regression analysis, and leaving room for the interpretation of the empirical results, the course aims to encourage the students to exploit the acquired skills and knowledge to study and solve issues of main interest for professionals in the field of management. In particular, students will develop data analysis competences and critical thinking, which are transversal to many disciplines in economics and management.

Knowledge and competences:
- understand how to specify an econometric model starting from an economic model
- understand the implications of the assumptions underlying each econometric model and recognize potential violations of those assumptions

Application of acquired knowledge and skills:
- being able to design useful strategies to measure and quantify economic phenomena and relationships that are of particular interest in the field of business and management
- know how to solve analytically and empirically basic problems about the relevant dynamics and relationships in economics and business
- exploit the statistical tools studied throughout the course to perform an empirical assessment of relevant issues for management

Judgement and interpretation skills:
- evaluate strengths and weaknesses of the methodologies analysed and of their empirical application
- being able to critically interpret the outcomes of empirical analyses

Compulsory: Microeconomics
Strongly suggested: Command of mathematical and statistical tools at an introductory level; in particular, a proper command of descriptive statistics, probability distributions and fundamentals of statistical inference are useful.

- The Nature of Econometrics and Economic Data

REGRESSION ANALYSIS WITH CROSS-SECTIONAL DATA
- The Simple Regression Model (Ch. 2)
- Multiple Regression Analysis: Estimation (Ch. 3)
- Multiple Regression Analysis: Inference (Ch. 4)
- Multiple Regression Analysis: OLS Asymptotics (Ch. 5)
- Multiple Regression Analysis: Quadratic forms, interaction terms, adjusted R-squared (Ch. 6)
- Multiple Regression Analysis with Qualitative Information: Binary (or Dummy) Variables (Ch. 7)
- Heteroskedasticity (Ch. 8)
- Specification and Data Problems: RESET test (Ch. 9.1)

REGRESSION ANALYSIS WITH LIMITED DEPENDENT VARIABLE
- Linear probability model (Ch. 7.5), Logit and Probit Models (Ch. 17.1)

REGRESSION ANALYSIS WITH PANEL DATA
- Pooling Cross Sections Across Time: Simple Panel Data Methods and Fixed Effects Estimation (Ch. 13 and 14.1)

Chapters' references refer to:
Wooldridge, J.M., Introductory Econometrics: A Modern Approach
Fifth Edition
South-Western College Publishing, 2013

Wooldridge, J.M., Introductory Econometrics: A Modern Approach, Fifth Edition,
South-Western College Publishing, 2013

Written discussion of the estimation results of cross-sectional and panel data models and analytical solutions of basic econometric problems. Part of the final mark depend on homework that can be handed in on a voluntary basis by the deadlines set by the instructor.

Lectures, classes and tutorials. Students will be encouraged to solve and to hand some pieces of homework throughout the course.

English

Accessibility, Disability and Inclusion
Accommodation and support services for students with disabilities and students with specific learning impairments

Ca' Foscari abides by Italian Law (Law 17/1999; Law 170/2010) regarding support services and accommodation available to students with disabilities. This includes students with mobility, visual, hearing and other disabilities (Law 17/1999), and specific learning impairments (Law 170/2010). If you have a disability or impairment that requires accommodations (i.e., alternate testing, readers, note takers or interpreters) please contact the Disability and Accessibility Offices in Student Services: disabilita@unive.it.

written and oral

This subject deals with topics related to the macro-area "Human capital, health, education" and contributes to the achievement of one or more goals of U. N. Agenda for Sustainable Development