Economics | Econometrics Essentials

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 economical data to explain economics 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 Essentials is a practical live course that provides a solid foundation of econometrics, focusing on the analysis of economic data through visualization, basic statistics to understand association between different economic variables across countries or time, modeling 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 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.

What’s more? You will also get to work on a hands-on capstone project where you will visualize and understand trends for micro-level cross sectional data on labor market variables like wage and education and build a simple linear regression model for understanding wages as a function of other factors such as education, experience etc.

The course will also introduce R as a programming language to conduct the analysis and facilitate learning. This learning will be enhanced as selected students will get an opportunity to intern where they will work on their R programming skills.

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Eligibility

• High school students from India and across the world are eligible to apply.
• Students should be entering or in grades 9-12 as in summer 2025.
• 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 analyze economics data and improve their understanding about the functioning of the world. It is for students interested in the fields of economics, statistics, economic data science, economic research analysis 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. Visualize different types of economic data and highlight their important aspects.
2. Compress information into different statistics and measures, and explore when to use them and how to interpret them.
3. Learn fundamentals of modelling economic relations through linear regression.
4. Interpret coefficients, make inferences, and evaluate model performance.
5. Practice causal inference and policy analysis through real-life economic applications.
6. Develop a solid understanding of econometric principles and gain practical experience in economic data analysis.

Programme Details

Week	Lecture Module	Project Module
Week 1	Present economic data: Trend analysis & visualization Create meaningful visualizations and make meaningful presentations that highlight key trends and patterns in various types of economic data.	Labor Market Data Visualization  Visualize and understand trends for micro level cross sectional data on labor market variables like wage and education. *You will be using R programming for this practical exercise
Week 2	Summarize economic data: Descriptive statistics Use  statistical concepts on economic data sets to derive insights and make inferences. Statistics for data description Measures of central tendency Dispersion and association	Statistical Application on Data Estimate basic summary statistics for the data set introduced on labor market variables. Understand what inference can be made through each statistical concept.
Week 3	Disperse economic data: Model building & interpretation Linear regression models  Interpretation of coefficients Inference and methods of evaluating the model	Labor Market Data Variable: Wage coefficients Build a simple linear regression model for understanding wages as a function of other factors such as education, experience etc.
Week 4	Refine regression model Difference between Prediction and Causality and how causal inference is the core of econometrics.	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.
Week 5	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 with micro level cross sectional data to understand the labor market. Each week, you will apply the course learning on the dataset and derive useful insights. Eventually, you will run linear regression models to understand the effect of different levels of education on wages and recommend which level of education the government should allocate the highest proportion of budget to.

Faculty

Parush Arora is an Assistant Professor of Economics at Ashoka University. He did his Ph.D. 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, certification and much more

Grading, Assessments, Certification and much more

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

• Weekly Attendance – 10%
• Weekly quizzes – 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 top 3 students based on exceptional performance
• Potential opportunity to get an internship*

*For select students, subject to discretion of the faculty

IT Requirements

This programme  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 on horizons@ashoka.edu.in