ECN3620 Applied Econometrics and Causality Analysis
(Previously titled Econometrics)
4 Advanced Liberal Arts Elective Credits
In today’s data-driven world, organizations need professionals who can move beyond simple correlations and uncover true cause-and-effect relationships. This course introduces students to applied econometrics and modern causal inference methods used by economists, consultants, financial analysts, and policymakers to evaluate strategies, forecast outcomes, and support data-driven decision-making. Through hands-on analysis of real-world datasets, students learn how to use data to answer important business and policy questions.
Students gain practical experience with key analytical tools, including econometric modeling, causal inference methods such as Difference-in-Differences and Instrumental Variables, and forecasting techniques for economic and business outcomes. You will also gain experience using R, a widely used programming language for data analysis.
By the end of the course, students will be able to analyze complex datasets, identify credible causal relationships, evaluate business strategies and public policies, and communicate data-driven insights clearly. These highly valued skills prepare you for careers in consulting, finance, data analytics, marketing analytics, corporate strategy, and economic or policy analysis. The course qualifies for both the Economics and Business Analytics concentrations and the Business Analytics major.
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Prerequisites: SME2031 or ECN2002 or ECN 2000