Impact Evaluation in Practice using R- Cohort 4.0

An Online International Spring School Program
A Two-Month Immersive Online Introductory Hands-On Certificate Training Course

April-May 2027

Details of the #WebPolicyLearning:

The fellowship duration is a total of 2 months.
Key Highlights: Regression Analysis, Randomised Controlled Trials (RCTs), Panel Data Analysis, Difference-in-Differences (DiD), Regression Discontinuity, and Instrumental Variable (IV) Estimation

Live Sessions with Experts & Program Team-

Dates: April-May 2027
Coming Soon
Time: TBA
Platform: Zoom

Registration form link: https://forms.gle/d22aJ1716or27dkCA

Course Fee in INR (inclusive of GST):

Special 20 percent discount for IMPRI Alumni. Bulk Discounts can be availed for groups of more than 5 participants. IMPRI Alumni can avail benefits through the IMPRI Referral Policy for Alumni & Friends.

Payment of Course Fee: https://pages.razorpay.com/impricoursefee
Alternatively, can use any payment method from here: https://www.impriindia.com/payment-details/

Last Date to Apply: coming soon

About

Building on the success of previous cohorts, the Generation Alpha Data Center (GenAlphaDC) at IMPRI is proud to present the fourth edition of the program, “Impact Evaluation in Practice using R.” This advanced course is designed to equip researchers, policymakers, and professionals with the analytical skills required to conduct rigorous impact evaluations using the powerful R programming language. By integrating practical applications and real-world datasets, this program ensures participants gain actionable insights and technical expertise to make data-driven decisions.

Throughout the course, participants will explore essential methodologies such as Regression Analysis, Randomized Controlled Trials (RCTs), Panel Data Analysis, Difference-in-Differences (DiD), Regression Discontinuity, and Instrumental Variable (IV) Estimation. These tools and techniques will enable attendees to analyze complex datasets, interpret results effectively, and contribute to meaningful social and policy outcomes.

What sets this program apart is its hands-on approach, guided by expert instructors who provide participants with practical learning experiences. By the end of the course, attendees will have mastered the use of R for data analysis, from data cleaning to interpreting results. This skillset empowers participants to evaluate the true impact of programs and interventions critically and systematically.

To maximize the learning experience, the first session will focus on downloading and setting up R Studio for new users. Participants already familiar with R are encouraged to have the software installed beforehand. Foundational pre-readings will also be shared in advance, covering key concepts, and participants are strongly encouraged to review these materials before the first session.

This program is more than just a training—it’s an opportunity to become a leader in the field of impact evaluation. Whether you are looking to enhance your research capabilities or influence policy with evidence-based strategies, this course provides the technical expertise and practical insights needed to drive impactful change. Register now to join this transformative learning journey and redefine the way you approach impact evaluation!

Objectives

To build a solid foundation in the core principles of causal inference, experimental design, and quantitative impact evaluation.
To equip participants with hands-on technical proficiency in R and RStudio for reproducible data cleaning, econometric analysis, and visualization.
To master key identification strategies, including Randomized Controlled Trials (RCTs), Regression Discontinuity, Difference-in-Differences (DiD), and Instrumental Variables (IV) estimation.
To develop advanced analytical skills in handling complex data structures, panel models, and addressing threats to identification such as bias, attrition, and endogeneity.
To translate empirical findings into actionable insights, policy briefs, and evidence-informed recommendations for development interventions.
To empower development practitioners, researchers, and policymakers to design, commission, and rigorously evaluate high-impact social programs.
To cultivate a collaborative community of analytical practitioners committed to data-driven decision-making, rigorous evaluation standards, and social change.

Key Highlights: Regression Analysis, Randomized Controlled Trials (RCTs), Panel Data Analysis, Difference in Difference (DiD), Regression Discontinuity, and Instrumental Variable (IV) Estimation

For Whom

Our course is designed for a diverse audience, including nonprofit leaders, government professionals, social entrepreneurs, development practitioners, educators, researchers, consultants, philanthropists, healthcare professionals, environmentalists, entrepreneurs, community leaders, students, and graduates. It serves individuals across sectors who want to build a foundation in impact assessment, drive positive change, and effectively measure and communicate their initiatives’ impact.

Applications from participants across disciplines, sectors, and regions are encouraged. IMPRI courses promote a multidisciplinary, inclusive learning environment that brings together diverse stakeholders to engage with real-world challenges.

 coming soon

Convenors:
Dr Simi Mehta, CEO & Editorial Director, IMPRI
Dr Arjun Kumar, Director, IMPRI

Note: The final experts’ list along with session dates & time will be updated shortly.

Impact Evaluation in Practice using R- Cohort 2.0 | November 2024
DAPRF Data Analytics for Policy Research Fellowship | September 2024
Data, Monitoring and Evaluation- Cohort 2.0 | July 2024
Data Analytics for Policy Research – Cohort 3 | April 2024
Impact Evaluation in Practice | December 2023
Data Analytics for Policy Research – Cohort 2 | November 2023

Program Approach

The course uses a flexible, interactive, and applied learning model to help participants develop strong foundations in impact evaluation practice.

1. Flexible Learning
An online structure with live sessions, recordings, curated readings, and peer-support channels enables participants to learn at their own pace alongside academic or professional commitments.

2. Capacity Building
Expert-led live sessions, hands-on R coding labs, and guided empirical case studies build econometric, data manipulation, and causal inference skills across program evaluation, social policy, economic development, public health, and related areas.

3. Applied Leadership
Through hands-on coding labs, empirical research writing, and data-driven presentations, participants critically evaluate real-world development programs and translate complex econometric findings into actionable policy insights and public discourse.

Learning Outcomes

• Gain proficiency in setting up reproducible data workflows in R and RStudio, from raw data cleaning and transformation to advanced econometric analysis.
• Master the design, implementation, and interpretation of key causal inference methods, including RCTs, Panel Data, DiD, Regression Discontinuity, and IV estimation.
• Detect and address common methodological challenges such as selection bias, endogeneity, unobserved heterogeneity, and violation of identification assumptions.
• Confidently interpret statistical outputs, coefficient estimates, and diagnostic metrics to assess the true impact of social policies and programs.
• Bridge the gap between quantitative evidence and real-world policy by producing rigorous evaluation reports, analytical essays, and policy briefs.
• Expand professional networks by collaborating with development practitioners, econometricians, and policy researchers across diverse social sectors.

Benefits

• Develop a deep understanding of impact assessment methodologies.
• Gain knowledge from globally and nationally renowned thematic experts and practitioners.
• Access valuable insights and build connections with professionals in the field.
• Receive a course outline and a reading list prepared by experts.
• Review and reinforce your learning with access to session recordings for 15 days.
• Earn a certificate upon successful program completion.
• Have the opportunity to publish their essays on the IMPRI Insights Blog, featuring contributions from eminent global thinkers.
• Find your name in the Participants’ list published in IMPRI Insights and in the Event Outcome Report.

The course duration is a total of 2 months.

1. Technical Sessions
Live classes, interactive discussions and networking with leading experts, covering the core curriculum and subject matter in depth.

Session Topics & Experts:

coming soon

2. Program Sessions
coming soon

Note: Exact session dates, times, and expert details will be communicated through the program Guidelines Document.
The Guidelines Document comprises the Templates for all required submissions, Submission guidelines and timelines, Reference materials for each submission, Reading resources shared by experts and Communication and coordination support.

Flexible Learning: All session recordings are available for 2 weeks post live session.

1. Do I need prior knowledge or an academic background in public policy or governance?
No prior background is required. The course builds from foundational to advanced understanding and is suitable for beginners as well as experienced learners.

2. What is the time commitment? Can full-time working professionals apply?
Yes, full-time professionals can apply. The program requires about 2–3 hours per week, including live sessions and preparation.

3. Will the online sessions be recorded?
Yes. All live sessions are recorded, and participants can access the recordings for 15 days after each session.

4. Will I receive an e-certificate?
Yes. All participants who complete the program requirements will receive an official IMPRI e-Certificate of Participation & Completion.

5. Will I get networking opportunities?
Absolutely. Fellows engage with experts, mentors, and peers through sessions, discussions, and collaborative work, becoming part of the wider IMPRI learning and alumni network.

Impact Evaluation in Practice using R- Cohort 2.0 | November 2024
Power BI Essentials for Impact Assessment | October 2024
DAPRF Data Analytics for Policy Research Fellowship | September 2024
Data, Monitoring and Evaluation- Cohort 2.0 | July 2024
Data Analytics for Policy Research – Cohort 3 | April 2024
Impact Evaluation in Practice | December 2023
Data Analytics for Policy Research – Cohort 2 | November 2023
Data, Monitoring and Evaluation | June-July 2023
Data Analytics for Policy Research | October-November 2022
Exploratory Data Analysis with Categorical Variables Regression Models: Dummy Variables and Logit/Probit using Eviews | December 2022