ECON 102B: Applied Econometrics
Hypothesis tests and confidence intervals for population variances, chi-squared goodness-of-fit tests, hypothesis tests for independence, simple linear regression model, testing regression parameters, prediction, multiple regression, omitted variable bias, multicollinearity, F-tests, regression with indicator random variables, simultaneous equation models and instrumental variables. Topics vary slightly depending on the quarter. Prerequisites:
Econ 102A or equivalent. Recommended: computer experience (course often uses STATA software to run regressions).
Terms: Win, Spr
| Units: 5
| UG Reqs: WAY-AQR, WAY-SI
Instructors:
McKeon, S. (PI)
;
Francisco Pugliese, J. (TA)
;
Huang, Z. (TA)
...
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Instructors:
McKeon, S. (PI)
;
Francisco Pugliese, J. (TA)
;
Huang, Z. (TA)
;
Walter, J. (TA)
;
Warnick, M. (TA)
;
Yan, N. (TA)
ECON 105: Economic Forecasting
The objective of the course is to introduce you to time series analysis and forecasting methods. Students will master a mix of theoretical and applied econometrics techniques used in macroeconomic and financial applications. Topics to be covered potentially include but are not limited to: regression from a predictive viewpoint; forecasting trends and seasonality; exponential smoothing models; ARMA models; stochastic trends, unit roots, and cointegration; structural breaks; point, interval and density forecasts; forecast evaluation and combination; vector autoregression including impulse-response estimation and analysis; dynamic factor models; volatility forecasting using GARCH models; conditional forecasting models and scenario analysis. The course emphasizes hands-on experience, and all students will acquire knowledge of the programming language R in the context of time series models and forecasting. Prerequisites:
ECON 102B. Students with a strong background in Statistics may reach out to the Economics Undergraduate office for permission to enroll.
Terms: Win
| Units: 5
Instructors:
Boul, R. (PI)
;
Chittaro, L. (TA)
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