Module Specifications.
Current Academic Year 2024 - 2025
All Module information is indicative, and this portal is an interim interface pending the full upgrade of Coursebuilder and subsequent integration to the new DCU Student Information System (DCU Key).
As such, this is a point in time view of data which will be refreshed periodically. Some fields/data may not yet be available pending the completion of the full Coursebuilder upgrade and integration project. We will post status updates as they become available. Thank you for your patience and understanding.
Date posted: September 2024
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Description The purpose of this module is to introduce students to basic regression methods that are used in analyzing social science data. The emphasis is on the application of statistical methods to analyze economic and/or financial data. In this module students will develop knowledge and skills in applying statistical methods to analyze data, using appropriate statistical software to analyze data, using regression models to test hypotheses, making and evaluating predictions based on statistical models. Students will participate in the following learning activities: attend and participate in lectures, familiarize themselves with the use of statistical software, work on take home assignments that replicate some previous empirical research, critically evaluate some of the literature in empirical research. | |||||||||||||||||||||||||||||||||||||||||||
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Learning Outcomes 1. carry out basic statistical inference procedures using regression models 2. use statistical software to produce and evaluate forecasts of real economic time series data 3. select appropriate econometric techniques to analyse particular data sets 4. evaluate empirical statistical work and critically assess econometric approaches 5. explain how to produce and evaluate forecasts using time series models | |||||||||||||||||||||||||||||||||||||||||||
All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml |
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Indicative Content and Learning Activities
Introduction to econometricsreview of statistical inference, data and data types, simple linear regression, hypothesis testing, dummy variables, the classical Linear Model.Using econometric modelstests of model specification, multicollinearity, heteroscedasticity, serial correlation, stochastic regressorsTopics in time series econometricsstationarity, cointegraton and error correction models, Granger causality, ARCH & GARCH, forecasting using regression and ARIMA models | |||||||||||||||||||||||||||||||||||||||||||
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Indicative Reading List
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Other Resources None | |||||||||||||||||||||||||||||||||||||||||||