The minimum qualification required to apply for this programme is 55 per cent marks in a 4-year UG degree in Economics, Statistics, Mathematics, Science, Commerce, or Engineering from a recognised university or institution.
Duration: 1 Year (2 Semesters)
The 1-Year M.A. in Applied Econometrics is an intensive, industry-aligned postgraduate programme designed to build advanced capabilities in economic analysis, econometric modelling, and data-driven decision-making. Developed by the Department of Economics, the programme aligns with the University’s vision of fostering human development through high-quality education, research excellence, and innovation-driven growth.
Learners gain a strong theoretical grounding in microeconomics, macroeconomics, financial economics, and advanced econometric theory, combined with extensive hands-on training in leading analytical tools, including STATA, R Programming, EViews, and machine learning applications. The curriculum emphasises contemporary quantitative techniques, forecasting models, macro-financial analysis, panel data methods, and empirical research design—equipping students to interpret complex socio-economic issues with precision.
With well-defined Graduate Attributes, Programme Outcomes (POs), and Programme Specific Outcomes (PSOs), the programme nurtures analytical thinking, technological competency, ethical research practice, and multidisciplinary engagement. Through internships and a full-scale Econometric Research Project and Dissertation, students develop strong capabilities in model specification, data analysis, empirical estimation, and economic interpretation, preparing them for high-impact roles in academia, industry, government, and policy institutions.
Core Foundations & Applied Training
Total Credits: 20
Advanced Applications, Machine Learning & Research
Total Credits: 22
Advanced Econometric Expertise: Rigorous training in microeconometrics, macroeconometrics, panel data methods, time-series analysis, and financial econometrics using industry-standard tools (STATA, R, EViews).
Strong Theoretical Foundation: Robust grounding in advanced microeconomics, macroeconomics, financial economics, and econometric theory for thorough policy and economic analysis.
Hands-on Software Training: Intensive lab-based courses focusing on applied econometric methods, forecasting techniques, computational modelling, and data analytics.
Machine Learning Integration: Specialised modules equipping learners to incorporate machine learning algorithms for predictive modelling and big-data econometric applications.
Industry-Oriented Curriculum: Designed to meet the needs of government agencies, financial markets, think-tanks, consulting firms, and data-driven industries.
Research-Focused Learning: A structured Econometric Research Project and Dissertation that enhances independent inquiry, empirical modelling, and academic writing.
Internship Component: Mandatory internship providing practical exposure to policy evaluation, financial modelling, forecasting, and applied economic research.
High-End Analytical Skills: Training in risk modelling, financial forecasting, econometric simulations, and evaluation of economic policies using real datasets.
Aligned with NEP 2020 and Global Standards: Emphasises critical thinking, ethical reasoning, leadership, and multidisciplinary engagement.
Career-Ready Competencies: Prepares graduates for specialised roles such as Econometrician, Financial Analyst, Data Scientist (Economics), Policy Analyst, and Research Consultant.
The programme integrates a strong career and research development ecosystem, enabling students to build specialised quantitative and analytical expertise.
Certifications in Industry-Relevant Analytical Tools
Mentorship for Research & Professional Development
Graduates of the M.A. in Applied Econometrics emerge with advanced analytical, statistical, and computational competencies suited for diverse roles across academia, government, financial institutions, and industry.
Econometrician, Data Analyst / Senior Data Analyst, Financial Analyst / Quantitative Analyst, Research Associate / Research Scientist, Policy Analyst / Economic Consultant, Machine Learning Analyst / Applied Data Scientist, Business Intelligence Analyst, Forecasting & Risk Modelling Specialist, Banking and Financial Services Roles, PhD Researcher / Academic Career
The programme equips learners with the expertise necessary for leadership roles in applied economics, financial analytics, and quantitative research.
The programme emphasises advanced quantitative, econometric, and analytical training, combining economic theory with software-based applications using STATA, R, EViews, and machine learning tools. Students learn to interpret complex economic and financial datasets with rigour and accuracy.
Applicants with a 4-year undergraduate degree in Economics, Statistics, Mathematics, Finance, Commerce, Engineering, or related fields, with at least 55% marks, are eligible.
Students receive extensive training in:
STATA, R Programming, EViews, Python (optional), and machine learning frameworks—essential for modern econometric and data-analytic practice.
Graduates can pursue roles such as Econometrician, Data Analyst, Financial Analyst, Policy Researcher, Machine Learning Analyst, Risk Modelling Expert, and positions in banking, consulting, government agencies, and think tanks. The programme also prepares students for doctoral research.
Yes. Students complete a full Econometric Research Project and Dissertation along with a mandatory internship, providing applied exposure to policy evaluation, forecasting, and quantitative analytics.