Addressing climate change requires a deep understanding of both economic impacts and data-driven analysis. This course begins by introducing the concept of Marginal Abatement Cost (MAC), explaining its role in evaluating mitigation potential. You will learn how to construct and interpret MAC curves using Python, gaining hands-on experience in cost derivation and economic modeling essential for policy analysis.

The course explores immigration through the lens of climate economics, linking population movements to environmental and economic outcomes. Core economic theories relevant to climate change are examined to provide a robust framework for understanding market and policy mechanisms.

Emissions and energy data analysis form a crucial part of this course, with a focus on plotting and interpreting emissions intensity trends across Europe over two decades. These insights help visualize progress and challenges in reducing carbon footprints. Regional applications, particularly in South Asia, are highlighted through case studies on electricity access and energy generation mixes, demonstrating practical uses of economic and data science methods in diverse contexts.

Combining theory, programming, and real-world applications, this course prepares professionals and researchers to contribute effectively to climate policy development and sustainable energy planning.