Comprehensive Course Listing Across All Semesters

Advanced Departmental Elective Courses

Data Science for Economics: This course equips students with tools to analyze large datasets using statistical software and machine learning techniques. Students learn to apply regression analysis, time series forecasting, and data visualization methods relevant to economic research.

Behavioral Economics: The course explores how psychological biases affect economic decision-making. Through case studies and experiments, students examine topics such as loss aversion, present bias, and social preferences in market behavior.

Advanced Econometrics: Designed for students with a solid background in econometrics, this course covers advanced modeling techniques including panel data analysis, instrumental variables, and causal inference methods.

Policy Evaluation Methods: This module teaches students how to design and evaluate economic policies using empirical evidence. Topics include impact evaluation, randomized controlled trials, and quasi-experimental designs.

Health Economics: Students investigate the intersection of health outcomes and economic factors. The course covers healthcare financing, cost-effectiveness analysis, and the economics of public health interventions.

Labor Economics: This course examines labor markets from microeconomic and macroeconomic perspectives. It explores wage determination, employment discrimination, unemployment dynamics, and labor mobility.

Climate Change Economics: The course analyzes the economic impacts of climate change and evaluates policy responses. Students engage with topics such as carbon pricing, green growth strategies, and adaptation financing.

Urban Economics: This module studies urbanization processes and their economic implications. Topics include housing markets, transportation economics, and regional development policies.

Economic History: Students examine historical events through an economic lens, analyzing the evolution of institutions, trade, and development over time.

Economic Growth Models: This course introduces students to theoretical frameworks explaining long-term economic growth, including endogenous growth theory, innovation economics, and structural change models.

Project-Based Learning Philosophy

At Ahmedabad University Ahmedabad, project-based learning is central to the Economics curriculum. Students begin working on research projects in their third year, selecting topics aligned with their interests and career goals. Projects are supervised by faculty members who guide students through literature review, data collection, modeling, and interpretation phases.

The structure of these projects involves several milestones:

• Initial proposal submission
• Mid-term progress report
• Presentation to peers and faculty
• Final deliverable including written thesis and oral defense

Evaluation criteria include research quality, clarity of presentation, originality of approach, and depth of analysis. Projects are designed to be challenging yet achievable, encouraging students to engage deeply with economic literature and develop critical thinking skills.

The capstone thesis in the final year represents a culmination of all previous learning experiences. Students choose an independent research topic under faculty mentorship, applying advanced econometric tools and contributing new insights to existing knowledge. This process prepares students for graduate studies or professional roles requiring analytical rigor and scholarly communication.