Econometrics

Explore the mathematical foundations of econometric models, concentrating on proofs and properties of estimators and tests.

Delve into real-world data analysis, applying econometric models to various economic phenomena and policy evaluation.

Understand the econometric methods used to analyze data collected over time, forecasting economic trends.

Study econometric models that handle data involving multiple entities observed over time, useful for examining individual behaviors.

Focus on the econometric techniques suitable for analyzing individual-level data within firms, households, and other micro-level entities.

Engage with econometric methods used for analyzing aggregate economic variables like GDP, inflation rates, and national income.

Analyze data collected from various subjects at a single point in time using econometric models suited for cross-sectional data.

Learn about the specialized software used in econometrics, such as Stata, R, EViews, and SAS, for data analysis and model estimation.

Examine econometric models that explicitly incorporate economic theory into the estimation of causal effects.

Investigate the application of Bayesian probabilistic approach in modeling economic data and incorporating prior information.

Understand the data-driven techniques in econometrics that do not rely on predefined functional forms of relationships.

Analyze econometric models that account for spatial interdependencies and geographical information.

Delve into methods and techniques used in econometrics to determine causation from correlations in economic data.

Learn about the econometric models used for predicting future economic and financial trends based on historical data.

Study the underlying principles and concepts that form the basis of various econometric models and techniques.

Explore regression analysis methods that allow for the estimation of conditional quantile functions, essential for understanding distributional effects.