Aprendizaje automático avanzado con Stata

Panel time series models are essential tools in modern applied econometrics, enabling researchers to analyze data with both temporal and cross-sectional dimensions. This two-day, interactive online seminar introduces participants to the estimation and interpretation of time series panel data models using Stata.

Participants will explore key challenges such as slope heterogeneity, structural breaks, and cross-sectional dependence, while gaining hands-on experience with both static and dynamic panel model estimation. The course focuses on intuitive explanations supported by practical exercises in Stata, and is designed for researchers with a basic understanding of panel data and time series analysis.

• Introduce key econometric concepts in panel time series models with large N and T dimensions.

• Explore issues such as heterogeneity, cross-sectional dependence, and structural breaks.

• Provide practical experience with estimation techniques for static and dynamic models.

• Equip participants with hands-on skills using Stata for analyzing complex panel datasets.

By the end of the course, students will understand:

• The structure and properties of panel time series data (large N and T).

• How to test for and model slope heterogeneity and structural breaks.

• How to detect and address cross-sectional dependence in panel datasets.

• Estimation strategies for static and dynamic models using advanced estimators (CCE, CS-ARDL, etc.).

• How to implement panel time series techniques effectively in Stata.

• Conceptual Understanding: Develop a clear understanding of the theoretical challenges in time series panel models and how to address them.

• Technical Application: Gain experience using modern estimation techniques including Common Correlated Effects and interactive fixed effects.

• Data Diagnosis & Estimation: Learn how to diagnose cross-sectional dependence and heterogeneity and apply tailored estimation tools accordingly.

• Practical Skills: Apply course methods to real-world research questions in macroeconomics, development, finance, and growth empirics using Stata.

Format: Two-day online seminar
Daily Sessions: 10:00–12:00 & 14:00–16:00 (BST)
Q&A: 1-hour concluding session on Day 2
Total contact time: 8 hours of instruction + 1 hour Q&A

Knowledge of basic statistics, Stata and econometrics is required, including:

• The notion of conditional expectation and related properties;
• point and interval estimation;
• regression model and related properties;
• probit and logit regression.

Reading List:

• The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Hastie, T., Tibshirani, R., Friedman, J., Springer (2009)
• An Introduction to Statistical Learning, Gareth, J., Witten, D., Hastie, T., Tibshirani, R., Springer (2013)
• Microeconometrics Using Stata, Cameron e Trivedi, Revised Edition, StataPress (2010)
• A Super-Learning Machine for Predicting Economic Outcomes, Giovanni Cerulli

Terms:

• Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrolment).
• Additional discounts are available for multiple registrations.
• Temporary, time limited licences for the software(s)  used in the course will be provided. You are required to install the software provided prior to the start of the course.
• Payment of course fees required prior to the course start date.
• Registration closes 1-calendar day prior to the start of the course.

• 100% fee returned for cancellations made over 28-calendar days prior to start of the course.
• 50% fee returned for cancellations made 14-calendar days prior to the start of the course.
• No fee returned for cancellations made less that 14-calendar days prior to the start of the course