Economics | Econometrics: Data, Models & Decisions

About the course

Under the Budget 2024, more than ₹3 lakh crore has been allocated for schemes benefitting women and girls. What is the basis of this allocation? How is the budget for any scheme decided? How is the minimum wage decided? How is the funding allocated for different policies in general?

If you are curious about these aspects of the economy, then dive into the field of econometrics. Econometrics is the study of economic data to explain economic relations, theories and systems. Data is important for economists and people in general to understand the functioning of the economy. When you build a combined understanding of the principles of economics, statistics and data analysis, it will enhance your knowledge about the application of econometrics.

Econometrics: Data, Models & Decisions is a practical live course that provides a solid foundation of econometrics, focusing on the analysis of economic data through visualisation, basic statistics to understand the association between different economic variables across countries or time, modelling economic systems or relations through linear regression, making causal inference, etc. It is a skill to draw valuable information and insights from the raw economics data, and this course aims to help students take the first step in this direction by teaching them how to test economic theories through simple linear models on the data and, through this process, ignite interest in the fields of economics. The course will also introduce R as a programming language for conducting analysis and facilitating learning.

The course will culminate with a capstone project, where you will work on real-life data which has consequences in the macroeconomy – a real-world question of interest, for example: education, environment, health, etc. Each week, you will apply econometrics techniques such as visual, statistical, and modelling techniques on the dataset and derive useful insights. You will also get exposed to using R to analyse, build a model, and interpret findings.

What’s more? Top students will also achieve an extended opportunity to write a research article on a chosen econometrics topic based on an analysis of a current research paper that is extended in a certain direction for the article.

 

“During the course, I learned a lot about how to interpret data using statistics, especially concepts like linear regression and confidence bands. I enjoyed learning how to use R programming to create graphs and models — it helped me connect the math I know with practical tools.”

– Aratrika, Grade 10, Delhi Public School

Eligibility

• High school students from India and across the world are eligible to apply.
• Students should be entering or in grades 9-12 as of the programme commencement date.
• Students from all boards can enrol.
• Students should be comfortable with written & spoken English, which will be the medium of instruction for the courses.
• Students should have consistent access to the Internet and a computer that aligns with the recommended minimum specifications.
• Students should have a good and consistent academic record.

Who is this course for?

This course is for high schoolers who want to learn how to improve decision-making if real-life data is available. It is a skill to draw valuable information and insights from the raw data. This course aims to help students take the first step in this direction and ignite interest in fields such as statistics, data analytics, machine learning, economics, etc.

Prerequisites: High proficiency in written & spoken English. You will be required to submit your latest mark sheet in the application form.

What do I take away?

By the end of the programme, you will:

1. Visualise different types of economic data and highlight their important aspects.
2. Learn how to compress information into different statistics/measures, when to use them and how to interpret them.
3. Learn the fundamentals of modelling economic relations through linear regression.
4. Practice the fundamentals of causal inference and predictions, and what to keep in mind to achieve accuracy.
5. Differentiate between the buzzwords like Machine Learning, Econometrics, Big Data, etc.
6. Use data in facilitating decision-making in day-to-day life.
7. Develop a solid understanding of econometric principles and gain practical experience in economic data analysis.

Programme Details

Week	Lecture Module	Project Module
Week 1	Introduction to Econometrics – From Questions to Quantifications Introduction to econometrics Causation vs. correlation The role of data in economic and social sciences Simple linear regression Introduction to R & RStudio: navigating the interface, reading data	Labor Market Data Visualization  Visualise and understand trends for micro-level cross-sectional data on labour market variables like wage and education. *You will be using R programming and other software tools for this practical exercise.
Week 2	Statistics That Speak – Modelling Economic Data Multiple Linear Regression Model specification and assumptions Coefficient interpretation: slope, intercept, real-world meaning Inference	Statistical Application to Data Estimate basic summary statistics for the data set introduced on labour market variables. Understand what inference can be made through each statistical concept.
Week 3	Data-Driven Decisions & Model Evaluation Hypothesis Testing Communicating uncertainty: confidence intervals, robustness, P values. Explore the use of data, bias-variance tradeoff. Refine previous regression models and reflect on limitations	Labour Market Data Variable: Wage coefficients Build a simple linear regression model to understand wages as a function of other factors, such as education, experience, etc.
Week 4	Econometrics Across Disciplines Applying econometrics in varied fields: Politics: What affects voter turnout? Public Health: How effective are vaccination campaigns? Climate: Can we model pollution and health outcomes? Business/Marketing: What drives ad conversions or sales?	Application of Causal Inference Theory Improve the models based on the theory of causal inference. Present the findings of the analysis done in previous weeks.
	Counselling:  Get a chance to ask questions to the faculty and the mentor, and get their answers and perspective.  You are encouraged to ask questions to the faculty around the following aspects: What are some related fields that can be explored based on this course topic? What are the future trends in the related fields? How can the course learning help the student enhance their college applications?	Mentoring: You are encouraged to ask questions to the mentor around the following aspects: What are some sub-topics to learn/practice beyond the course? What is the scope of the course topic if the student wants to pursue/study it further? What are some personal projects that can be taken up outside of the course based on the knowledge gained in the course?

Capstone Project

You will work on real-life data, which has consequences in the macroeconomy – a real-world question of interest, for example: education, environment, health, etc. Each week, you will apply the econometrics techniques, such as visual, statistical, and modelling techniques on the dataset and derive useful insights. You will also get exposed to using R to analyse, build a model, and interpret findings.

Faculty

Parush Arora is an Assistant Professor of Economics at Ashoka University. He did his PhD in Economics from the University of California, Irvine. His primary research interests are Econometrics, Bayesian Inference and Empirical Macroeconomics. He holds a Bachelor’s in Economics from the University of Delhi and a Master’s in Economics from the Madras School of Economics.

Grading, assessments, and certification

Grading, Assessments, Certification and much more

Ashoka Horizons Achievers Programme offers a certificate on satisfactory completion of the course. 

• Weekly Attendance – 10%
• Weekly Project Progress – 40%
• Final Presentation – 50%

Class participation will be assessed based on your active engagement in live sessions, contributions to discussion forums, and involvement in Teaching Fellow-led activities. 

Achieve More…with Horizons Achievers Programme:

• Successful Course Completion Certificate
• Letters of Academic Achievement to the top 3 students based on exceptional performance
• Potential extended opportunity to write a research article on a chosen econometrics topic, where current research papers will be analysed and extended in a certain direction for the article.*

*For select students, subject to the discretion of the faculty

IT Requirements

This course is administered through an online platform. Students are expected to have a foundational understanding of computer usage, including but not limited to sending emails and conducting Internet searches. Consistent access to the Internet and a computer that aligns with the recommended minimum specifications are also requisite for participation in the programme.

Have a question about Ashoka Horizons Achievers Programme? Write to us at horizons@ashoka.edu.in