Prof. François Rycx (ULB), Mélanie Volral (UMons) & Guillaume Vermeylen (UMons)
ULB – UMons
Methods / Core Learning
This course is intended for PhD candidates planning to conduct econometric analysis or understand the econometric approaches of their peers. The course is designed to allow teams of 2 or 3 students to write their first econometric study. Each team will receive individual advice throughout the process.
The course will first help students to define an appropriate research question in light of the available data and existing literature.
Second, it will give them a concise overview of standard principles, methods and estimation techniques such as the classical linear normal regression model (ordinary least squares (OLS), multicolinearity, heteroscedasticity, serial correlation, normality of the error term, endogeneity), functional forms of regression models, time series (unit roots, cointegration, error correction models), panel data techniques (pooled OLS, fixed and random effects models), qualitative response models (linear probability, logit, probit, Tobit models).
Finally, students will be thought ‘how to get started with Stata’. Put differently, they will learn how to use a state-of-the-art econometric software to handle data and do econometrics.
Academic Year 2023-2024
This course will not be organized during the academic year 2023-2024.
To provide the best experiences, we use technologies like cookies to store and/or access device information. Consenting to these technologies will allow us to process data such as browsing behavior or unique IDs on this site. Not consenting or withdrawing consent, may adversely affect certain features and functions.
The technical storage or access is strictly necessary for the legitimate purpose of enabling the use of a specific service explicitly requested by the subscriber or user, or for the sole purpose of carrying out the transmission of a communication over an electronic communications network.
The technical storage or access is necessary for the legitimate purpose of storing preferences that are not requested by the subscriber or user.
The technical storage or access that is used exclusively for statistical purposes.The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you.
The technical storage or access is required to create user profiles to send advertising, or to track the user on a website or across several websites for similar marketing purposes.