This course equips doctoral students with advanced theoretical and applied econometric skills for rigorous economic research and policy analysis. It emphasizes identification, estimation, inference, causal reasoning, computation, replication, and scholarly communication so that learners can specify, estimate, interpret, critique, and communicate sophisticated econometric models using real-world data and reproducible workflows.

CLO 1:Evaluate advanced econometric models by examining their assumptions, identification conditions, theoretical properties, empirical applications, and limitations.

CLO 2: Apply advanced econometric techniques in STATA and R, including dynamic panel estimation, cointegration analysis, causal inference methods, and nonlinear limited dependent variable models, using real-world datasets.

CLO 3: Analyse econometric identification strategies, robustness, validity, and suitability for addressing endogeneity, dynamics, nonlinearity, and causal inference problems.

CLO 4 Design research-ready econometric analysis by integrating data management, reproducible workflows, rigorous econometric reasoning, and policy-relevant reporting.

Learning