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Apr 21, 2016 by Cristin Guinan-Wiley (cgw)
ECON 6376 : Time Series Analysis
Thu, 21 Apr 2016 09:12:36 GMT
Wed, 20 Apr 2016 15:05:55 GMT
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Programs referencing this course
DS-MS: Data Science
ECN-AMA: Applied Economics
Columbian College of Arts and Sciences
Long Course Title
Time Series Analysis
Short Course Title
Time Series Analysis
Number of Credits
Default Grading Method
applied economics MA students only
Repeatable for Credit?
ECON 6374, ECON 6305
Frequency of Offering
Are there Course Equivalents?
Are Fees Applicable?
Explanation and Description of Fees
Are Additional Resources Required?
Explanation of Additional Resources
Justification for Additional Resources
Describe any Sources of Additional Funding
The objective of this course is to give students the tools required to understand, implement, and interpret common models used in time series econometrics. Emphasis is placed on intuition and application. The course will both help students understand how to use time series data to test hypotheses and serve as an introduction to the ideas and techniques of forecasting. Topics covered are: time series properties of data (unit roots, near unit roots, stationarity), difference equations, stationary models (autoregressive and moving-average models), models with trends (deterministic and stochastic), multi-equation models (reduced-form and structural VARs), cointegration and error-correction models, models with time-varying coefficients, forecasting models, and basic forecast evaluation. Students will become proficient with performing basic time series analysis and forecasting using time series statistical software.
As a result of completing this course, students will be able to: 1. Understand time series data, test for stationarity or trends. 2. Perform and evaluate hypothesis tests and other statistical methods for time series analysis including VARs, and regression analysis of time series data. 3. Utilize econometric software for time series analysis and economic forecasting. 4. Evaluate forecasts and test different forecast models.
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Time Series Analysis 6376.pdf
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