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Easwari School of Liberal Arts Economics M.Sc. Economics

M.Sc. Economics

Rebuilt with AI. Rooted in Theory.

"The main aim of the Programme is to equip the students with theories and tools of economic analysis in major areas of its application and focus on the emerging area of Economics"

The M.Sc. Economics programme at SRM University-AP is designed to equip students with a strong foundation in economic theory while integrating advanced computational methods for real-world applications. The curriculum blends data science, policy analysis, and economic modelling to prepare graduates for a rapidly evolving, technology-driven global economy.

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Program Overview

The M.Sc. Economics program at SRM University-AP  offers rigorous training in economic theory, econometrics, quantitative methods, and applied analysis for a rapidly evolving, data-driven world. The program is built around a central principle: artificial intelligence, machine learning, and large language models are not replacing core economic reasoning and analytical tools — they are extending them.

Students develop strong foundations in microeconomics, macroeconomics, statistics, and empirical analysis while learning to work with modern computational and data-driven methods increasingly used in economics, finance, policy, and research. The curriculum combines analytical depth with practical training and prepares students to engage with contemporary economic problems using both traditional and emerging tools.

The program offers specialization pathways in Finance & Data Science and Development & Policy, preparing graduates for careers in research, consulting, finance, data analytics, public policy, international development organizations, and doctoral studies in economics and related disciplines.

Why Choose This Programme?

Industry-Relevant Curriculum

The programme integrates economics with emerging fields like Artificial Intelligence, Machine Learning, and Data Science, ensuring graduates stay ahead in the evolving job market.

Research-Led Learning

Students engage in advanced research through dissertations, policy analysis, and real-world case studies.

Strong Analytical Foundation

Focus on quantitative techniques, econometrics, and computational tools for data-driven decision-making.

Career-Ready Approach

Designed to prepare students for roles in finance, consulting, public policy, and analytics.

Global Opportunities

Exposure to international academic standards and opportunities for higher studies and research collaborations.

Specialisations Offered :

Track 1 — Finance & Data Science

This track prepares students for careers in financial analysis, risk management, fintech, and quantitative finance. Students develop expertise in programming, financial econometrics, derivatives, portfolio management, and data-driven decision making.

Track 2 — Development & Policy

This track equips students for careers in policy research, international development, public sector economics, and social sector work. Students gain expertise in causal inference, impact evaluation, institutional analysis, welfare economics, and sector-specific policy domains including health, agriculture, labor, and gender economics.

Highlights

  • Globally-oriented and Multi-dimensional approach
  • Proficiency in Quantitative methods
  • Internship Opportunities with Reputable Institutions
  • Tutelage of Highly-Qualified Faculty members
  • State-of-the-art Infrastructure

M.Sc. Economics : 1 Year Program

All students complete a common first semester. The fifth course is a track elective whose choice determines the Semester II specialization. AI and Computational Methods for Economists (2 credits) runs alongside all core courses, building the computational foundation for Semester II.

Code Course Title Credits
EC XXX Advanced Microeconomic Theory & Applications 4
EC XXX Dynamic Macroeconomic Modelling 4
EC XXX Advanced Mathematical Methods for Economics 4
EC XXX Econometric Methods 4
EC XXX Advanced Development Economics OR Advanced Financial Economics ★ 4
EC 5XX AI and Computational Methods for Economists 2

★  Choice of track elective determines the student’s Semester II specialization.

Three fixed courses; students choose two from the Track 1 Core Elective menu.

Code Course Title Credits
EC 5XX Machine Learning for Economics (also open to Track 2 students) 4
EC 5XX Big Data Analytics & Text Mining 4
EC 5XX Financial Econometrics 4
EC 5XX Core Elective 1 (from Track 1 elective menu) 4
EC 5XX Core Elective 2 (from Track 1 elective menu) 4

Three fixed courses; students choose two from the Track 2 Core Elective menu.

Code Course Title Credits
EC 5XX Causal Methods and Impact Evaluation 4
EC 5XX Social Welfare & Policy 4
EC 5XX Institutional Economics 4
EC 5XX Core Elective 1 (from Track 2 elective menu) 4
EC 5XX Core Elective 2 (from Track 2 elective menu) 4

Students select two electives from their respective track menu. Machine Learning for Economics also appears in the Track 2 menu as an option.

Track 1 — Finance & Data Science Track 2 — Development & Policy
Derivatives and Risk Management Machine Learning for Economics
Portfolio Management Labor Economics
Corporate Finance Agricultural Economics
Monetary Theory & Policy Health Economics

Note: Electives offered subject to availability of faculty and student interest.

One-Year M.Sc. Program
Component Credits
M.Sc. Semester I — Common Foundation 22
M.Sc. Semester II — Specialized Track 20
Total Credits 42

Note: Electives offered subject to availability of faculty and student interest.

M.Sc. Economics with Research

Students from both tracks may elect a third semester comprising a 12-credit dissertation under faculty supervision. Successful completion leads to the award of M.Sc. Economics with Research. The dissertation must engage with a substantive economic question using methods from the student’s chosen specialization track.

One-Year M.Sc. Program
Component Credits
M.Sc. Semester I — Common Foundation 22
M.Sc. Semester II — Specialized Track 20
M.Sc. Semester III - Dissertation ( Optional) 12
Total Credits 54

Note: Electives offered subject to availability of faculty and student interest.

M.Sc. Economics : 2 Year Program

Students with a three-year Bachelor’s degree complete Year 1 alongside B.Sc. Economics Honours students, building the analytical and quantitative foundation for M.Sc. studies.

Code Course Title Credits
ECO 4XX Optimization for Economics 4
ECO 4XX Statistical Methods for Economics 4
ECO 4XX Topics in Microeconomics (Social Choice & Welfare) 4
ECO 404 Theories of Economic Growth 4
ECO 4XX Computational Methods in Economics 4
Code Course Title Credits
ECO 420 Time Series Econometrics 4
ECO 405 Industrial Organization 4
CE Monetary Economics (Core Elective) 4
CE Political Economy of States & Markets (Core Elective) 4
CE 400 level (Core Elective) 4

Note: Students complete all three core elective courses in Semester II.

Two-Year M.Sc. Program
Component Credits
Year 1 — Advanced Undergraduate (Semesters I–II) 40
Semester I 20
Semester II 20
Year 2 — M.Sc. Program (Semesters I–II) 42
M.Sc. Semester I — Common Foundation 22
M.Sc. Semester II — Specialised Track 20
Total Credits 82

Note 1: Students pursuing M.Sc. Economics with Research will have an additional 12 credits for the dissertation semester.

Note 2: Students who exit the two-year M.Sc. program after successfully completing the first year will be awarded a B.Sc. (Honours) degree.

Program Features

Flexible Entry, Shared Computational Foundation

The program is designed to ensure that all students develop a strong foundation in programming, computational methods, and data analysis early in their training, regardless of their undergraduate background. This common quantitative foundation enables students to engage confidently with AI tools, machine learning methods, computational workflows, and modern empirical research throughout the program.

AI-Augmented Specialisation Tracks

Both specialization pathways integrate AI-augmented and data-driven approaches into economic analysis. Students learn to combine economic reasoning with modern computational tools, applying machine learning, data analytics, and quantitative methods to problems in finance, public policy, development, and empirical research. The program ensures that all students, irrespective of specialization, engage with contemporary computational techniques shaping the future of economics.

Econometrics Redesigned for the AI Era

The program rethinks econometrics for the AI era by emphasizing the relationship between economic theory, causal inference, and modern computational methods. Students learn the strengths and limits of traditional econometric approaches, when structural reasoning remains essential, and how machine learning techniques can complement economic analysis in prediction, inference, and empirical research. The program maintains a theory-first approach in which computation and AI-driven tools are used to deepen economic understanding rather than replace core economic reasoning.

Frontier Research Tools, Grounded in Theory

The program equips students with hands-on experience in contemporary computational and AI-driven research methods, including machine learning, natural language processing, and large language model applications for economic analysis. Students work with large-scale real-world datasets and modern empirical workflows while developing a clear understanding of the strengths, limitations, and appropriate use of these tools in economic research and policy analysis. Throughout the program, computational methods are taught in relation to the economic questions they can meaningfully address and the limits of what they can identify or explain.

Specialisations Offered

  • Finance & Data Science
  • Development & Policy

Programme Structure

  • 1-Year Programme (for 4-year UG degree holders)
  • 2-Year Programme (for 3-year UG degree holders)

Career Opportunities

  • Economic & Policy Research
  • Banking & Financial Services
  • Data Analytics & Consulting
  • Government & International Organisations

Fee Structure (Per Year)

Category Tuition Fees (₹) Concession UG % CGPA
A 0 100% 85 & ABOVE 9.0 & Above
B 25,000 75% 75 – 84.99 8.0 – 8.99
C 50,000 50% 65 – 74.99 7.0 – 7.99
D 1,00,000 0% 60 – 64.99 6.0 – 6.99

Additional scholarships and financial aid options are available for eligible candidates.

Eligibility Criteria

For 2-Year M.Sc. Economics (3-Year UG Degree)

  • Three year UG in any discipline.
  • A minor in Economics or Mathematics is preferable.

For 1-Year M.Sc. Economics (4-Year UG Degree)

  • Four year degree in any discipline.
  • A minor in Economics or Mathematics is required.

Admissions Open

Join a future-focused economics programme that combines theory, data, and technology to shape tomorrow’s leaders in policy, finance, and analytics.

Apply now to take the next step in your academic and professional journey.
Along with acquiring content knowledge, students in each course will practice critical thinking skills, communication skills, quantitative reasoning, and economic citizenry.
To prepare them to pursue higher studies and conduct research.
To train them and build their careers where they are likely to make a long-lasting contribution in either policy making or research career.
To solve real-life problems using economic theory and applications.
Analysis of data to solve complex economic problems.
Apply economic theories and concepts to contemporary social issues, as well as policy formulation and analysis.
Programme Outcomes (PO)
Scientific and Disciplinary Knowledge
Capable of demonstrating comprehensive knowledge and understanding of one or more disciplines that form a part of an undergraduate programme of study.
Ability to evaluate the reliability and relevance of evidence; Capacity to extrapolate from what one has learned and apply their competencies to solve different kinds of non-familiar problems, rather than replicate curriculum content knowledge; and apply one’s learning to real-life situations.
Capability to apply analytic thought to a body of knowledge; analyse and evaluate evidence, arguments, claims, and beliefs based on empirical evidence; identify relevant assumptions or implications; formulate coherent arguments; critically evaluate practices, policies and theories by following a scientific approach to knowledge development. Critical sensibility to lived experiences, with self-awareness and reflexivity of both self and society.
Ability to analyse, interpret and draw conclusions from quantitative/qualitative data; and evaluate ideas, evidence and experiences from an open-minded and reasoned perspective pertaining to incorporating into a system.
A sense of inquiry and capability for asking relevant/appropriate questions, problematising, synthesising, and articulating; Ability to recognise cause-and-effect relationships, define problems, formulate hypotheses, test hypotheses, analyse, interpret and draw conclusions from data, establish hypotheses, predict cause-and-effect relationships; ability to plan, execute and report the results of an experiment or investigation.
Capability to use ICT in a variety of learning situations; demonstrate the ability to access, evaluate, and use a variety of relevant information sources; and use appropriate software for analysis of data.
Understand the impact of scientific solutions in societal and environmental contexts, and demonstrate the knowledge of and need for sustainable development.
Possess knowledge of the values and beliefs of multiple cultures and a global perspective; and the capability to effectively engage in moral/ethical values in conducting one’s life, formulate a position/argument about an ethical issue from multiple perspectives, and use ethical practices in all work. Capable of demonstrating the ability to identify ethical issues related to one’s work. Avoid unethical behaviour such as fabrication, falsification or misrepresentation of data or committing plagiarism, not adhering to intellectual property rights; appreciating environmental and sustainability issues; and adopting objective, unbiased and truthful actions in all aspects of work.
Ability to work effectively and respectfully with diverse teams; facilitate cooperative or coordinated effort on the part of a group and act together as a group or a team in the interests of a common cause and work efficiently as a member of a team.
Ability to express thoughts and ideas effectively in writing and orally; Communicate with others using appropriate media to confidently share one’s views and express herself/himself; demonstrate the ability to listen carefully, read and write analytically, and present complex information clearly and concisely to different groups.
Capability for mapping out the tasks of a team or an organisation, setting direction, formulating an inspiring vision, building a team that can help achieve the vision, motivating and inspiring team members to engage with that vision, and using management skills to guide people to the right destination, in a smooth and efficient way.
Ability to work independently, identify appropriate resources required for a project, and manage a project through to completion; Ability to acquire knowledge and skills, including “learning how to learn”, that is necessary for participating in learning activities throughout life, through self-paced and self-directed learning aimed at personal development, meeting economic, social and cultural objectives, and adapting to changing trades and demands of the workplace through knowledge/skill development.

Curriculum

Admission India
International Admission

"The main aim of the Programme is to equip the students with theories and tools of economic analysis in major areas of its application and focus on the emerging area of Economics"