Advances in Causal Inference and Program Evaluation using Stata

Advances in Causal Inference and Program Evaluation using Stata

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US$ 360,00
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2 Days
Online
Stata

Overview

Econometric modelling for causal inference and program evaluation have witnessed a tremendous development in the last decade, with new approaches and methods addressing an expanding set of challenging problems, both in medical and the social sciences. This course covers some recent developments in causal inference and program evaluation using Stata.

 

This live and online short course will cover:

  • The essential tools, both theoretical and applied for a proper use of recent micro-econometric methods for policy evaluation and casual modelling, in situations where the standard treatment set poses limitations.
  • Difference-in differences (DID), with time varying and time-fixed binary treatment.
  • The Synthetic Control Method (SCM), for program evaluation, suitable when datasets, on many times and locations, are available.
  • Models for multivalued and quantile treatment effect estimation.
How It Works
What You’ll Learn

Mastery of Recent Micro-Econometric Methods: 

  • Gain a deep understanding of recent developments in causal inference and program evaluation within the last decade. 
  • Master essential tools, both theoretical and applied, for utilizing micro-econometric methods in policy evaluation and causal modeling. 

 

Proficiency in Advanced Approached

  •  Acquire expertise in Difference-in-Differences (DID) with both time-varying and time-fixed binary treatment settings.
  • Learn to apply the Synthetic Control Method (SCM) for program evaluation, particularly when dealing with datasets spanning multiple times and locations.
  • Develop skills in models for multivalued and quantile treatment effect estimation. 

 

Practical Application and Interpretation: 

  • Gain hands-on experience in setting up and managing a correct evaluation design using Stata.
  • Learn to identify the appropriate econometric method based on the policy framework and interpret results accurately.
  • Apply learned concepts to real datasets through various instructional examples. 
Why This Course?

On completion of this course, you will be able to set up and manage a correct evaluation design using Stata, by identifying the policy framework and the appropriate econometric method to interpret correctly the results.

 

You will receive a signed certificate of as proof of professional development upon completion of this course.

Real-world applications
  • Informed Decision-Making in Various Domains: Participants will be empowered to apply machine learning techniques in diverse fields, such as social sciences, economics, and health. This knowledge will enable them to make informed decisions based on insights extracted from large datasets.
  • Enhanced Research Capabilities: Researchers can apply the learned techniques to enhance their research methodologies. The course's focus on correct model specification and model-free classification ensures robust analysis, contributing to the reliability of research findings.
  • Efficient Data Utilization: Professionals and policymakers will benefit from the ability to extract valuable information from large and possibly noisy datasets. This efficiency in data utilization can lead to improved policy formulation, strategic planning, and business decision-making.
Who Should Attend?
  • This course is tailored for researchers, analysts, and academics working in fields like economics, social sciences, or finance. Familiarity with basic econometrics is helpful, but no prior experience with panel data methods or Stata is required.

Agenda

Day 1:

Econometrics of program evaluation: an overview
Difference-in-differences (DID) with time-varying binary treatment
DID with many times and locations: the Synthetic-Control Method (SCM)
Day 2:

Multivalued and quantile treatment effect estimation
Causal inference with continuous treatment: dose-response models
Q&A Session

Prerequisites

It is preferable but not strictly needed to have attended the course “Econometrics of program evaluation using Stata”. It is also required some knowledge of basic econometrics: notion of conditional expectation and related properties; point and interval estimation; regression model and related properties; probit and logit regression.

Basic knowledge of the Stata software

 
Principal texts for pre-course reading:
  • Cerulli, G. (2015), Econometric Evaluation of Socio-Economic Programs: Theory and Applications, Springer.
  • Wooldridge, J.M. (2010). Econometric Analysis of cross section and panel data. Chapter 21. Cambridge: MIT Press.
 
Principal texts for post-course reading:
  • Abadie, A., Diamond, A., and Hainmueller, J. (2010), Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program, Journal of the American Statistical Association, Vol. 105, No. 490, 493-505.
  • Bia, M. and Mattei, A. (2008), A Stata package for the estimation of the dose–response function through adjustment for the generalized propensity score, Stata Journal, Volume 8, Number 3.
  • Cattaneo, M., Drukker, D., and Holland, A. (2013), Estimation of multivalued treatment effects under conditional independence, Stata Journal, Volume 13, Number 3.
  • Cerulli, G. (2015), ctreatreg: Command for fitting dose-response models under exogenous and endogenous treatment, Stata Journal, Volume 15, Number 4.

Course Timetable

Subject to minor changes

Morning Session

Afternoon Session

Q&A with Instructor

10am-12pm (London time)

2pm-4pm (London time)

4pm-4:30pm (London time)

10am-12pm (London time)

2pm-4pm (London time)

4pm-4:30pm (London time)

 

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 5-calendar days prior to the start of the course.

 

Cancellations or changes to your registration

  • 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.

 

Delivered By

Student Testimonials

Giovanni's delivery is fantastic; makes great connections between new and prior knowledge and focuses on the key strengths and limitations of the discussed methods. Excellent course design that builds on the Introductory Machine Learning course and knowledge acquired in the PhD Econometrics sequences of courses. This is all nicely supplemented by detailed Stata code with explanations and sample datasets. 

Excellent course and great explanations on ML techniques and applications from Giovanni ! I leanred so much including the coding and applications plus the fundamentals of ML.

The 'Advanced Machine Learning (AML)' experience was excellent for trying to gain more experience in Statistics using links Python and STATA.  

I'm not a Statistician! However, Giovanni managed to link the 'Fundamentals of Machine Learning (FML) ' to 'Advanced Machine Learning' in his usual excellent way. When starting the AML, for me I am pleased that the FML was a tremendous help and allowed me to use my mathematical knowledge for Physics and Science. I'm looking forward to Giovanni's next course (using large datasets) and his book.

Linking my knowledge of mathematics (from Science and Engineering) to Statistics. I do hope it is leading towards becoming better at 'Medical Statistics' that require very large datasets...and a big thank you to Giovanni!

Very well organized, very useful and relevant content, looking forward to joining future events!

As always great service and real good courses. In addition, thanks to Professor Cerulli for making himself understood in the best way.

The delivery of this course was exceptionally well done. It really helped me to appreciate the concepts as well as the practical applications in Stata. If you are new to this topic, this will provide a good introduction to complex issues.

Very easy to communicate, all emails contained all the information necessary. I think that the course was very well structured and organized. The tutor provided a number of codes that were extremely helpful for understanding. Overall, very useful and easy to follow!

I highly appreciated Professor Giovannu Cerulli course. The classes notes are very clear   and well prepared with an extensive coverage of the course subjects. And they are simultanesouly quite objective by focusing on the most important contents. Professor Giovannu Cerulli lectures are very didatic which greately helps the easily assimilation of the   corespondent knowledge. Furthermore, the course materials are quite   comprehensive and they englobe not only the classes notes, but also the referenced papers as well as data and Stata programs to estimate the models in this software. All in all, I greatly recommend this   course, as it really amazingly speeds up the acquaintance of the underlying theory and appied aplication in a very short period of time.

I found the Stata Summer School 2021 very useful and interesting. The course was perfectly structured and organised, with a good progression during the week. The instructors presented the topics covered in an easy and understandable way. There were room for questions and answers when needed. Materials shared for the course were tidy and informative, and I am sure I will use them frequently. This course was arranged online, which in my opinion worked very well. I believe the course delivered as promised and according to information found online when I signed up for the course. Easy to purchase/sign up for the course. User friendly. Quick and timely response.

Very efficient in terms of communication and delivery. Provides a very comprehesnive applied knowledge of stata. I would definitely recommend others to buy from them.

I went UK University of Cambridge for a summer school with Timberlake, it was excellent.

It was a great course and I thoroughly enjoyed it. Many of my fellow participants were eager to share their ideas. I thought the course could help further many people in a similar stage to my career!