Local Projections for Time-Series and Panel Data Analysis: Methods, Applications, and Replication in Stata

This intensive two-day course provides a practical and applied introduction to local projections (LPs)as a flexible econometric framework for estimating dynamic effects in macroeconomic, financial, and policy-related settings. The course begins with the foundations of local projections in time-series analysis, then expands to panel local projections, state-dependent and time-varying specifications, and finally to LP-DiD approaches for dynamic treatment analysis in staggered intervention settings. Throughout the course, participants will learn both the conceptual logic and the empirical implementation of local projections in Stata, with emphasis on model design, identification, inference, interpretation, and replication. The course combines theory, methodological discussion, and hands-on exercises based on applied examples.

The program is methodologically centered on local projections as a modern empircal tool for estimating impulse responses and dynamic treatment effects. It is designed to move progressively:

• From basic time-series local projections;

• To panel local projections;

• To nonlinear and flexible LP frameworks;

• And finally to LP-DiD methods and common empirical pitfalls

This creates a clear learning path from foundational concepts to more advanced research applications. The course integrates:

• Theory and intuition, helping participants understand why local projections are useful

• Software implementation in Stata, making the material directly applicable
• Empirical examples, linking methods to substantive research questions
• Replication exercises, reiniforcing learning through practice
• Critical methodological reflection, especially on identification, inference, nonlinearities, and design pitfalls

By the end of the course, participants should be able to:

• Understand the logic of local projections and explain how they differ from VAR-based approaches
• Specify and estimate time-series local projection models in Stata
• Interpret dynamic responses in terms of sign, timing, persistence, and peak effects
• Implement panel local projections and understand the role of fixed effects, clustering, and heterogeneous responses
• Apply state-dependent and time-varying LP frameworks to more flexible empircal settings
• Understand the intuition and empirical usefulness of LP-DiD methods in staggered treatment contexts
• Evaluate the strengths and limitations of alternative LP designs across different empircal questions
• Conduct replication exercises and robustness checks using applied Stata workflows
• Recognise common pitfalls in indentification, inference, interpretation, and graphical communication
• Design and report a credible empircal LP analysis for academic or policy-orientated research

After completing the course, participants will be able to:

• Estimate impulse responses using local projections in both time-series and panel settings
• Choose appropriate horizon lengths, lag structures and identification strategies
• Implement LP methods using lpirf, locproj, and LP-DiD workflows in Stata
• Interpret interaction terms, threshold effects, and regime-dependent results
• Compare constant-parameter, state-dependent, and time-varying dynamic specifications
• Diagnose weaknesses in event-study and TWFE designs when treatment timing is stagered
• Present dynamic empirical findings clearly and rigorously

This course is best suited for:

• Master's students in economics, econometrics, finance or public policy
• PHD students working with macroeconomic, financial, or panel data
• Applied researchers interested in dynamic causal analysis
• Research assistants and analysts using Stata for empirical work
• Policy researchers who need to evaluate shocks, interventions, or dynamic responses over time

Participants should ideally have:

• Prior exposure to econometrics
• Basic understanding of time-series and panel data methods
• Familiarity with regression analysis and inference

• 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.
• Delegates are provided with temporary licences for the software(s) used in the course and will be instructed to download and install the software prior to the start of the course.
• Payment of course fees required prior to the course start date.
• Registration closes 5-calendar days 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 than 14-calendar days prior to the start of the course.

The number of delegates is restricted. Please register early to guarantee your place.