The objective of this class is to develop skills necessary to understand and assess applications that use panel data techniques. Standard linear regression models are used as a benchmark. Basic knowledge of time series analysis is introduced, followed by panel data settings involving 'fixed' and 'random' effects. Recently developed GMM and instrumental variables methods are introduced and nonlinear panel data with binary outcomes is covered. Students will work through practical examples using Stata and Matlab.
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2023 | ||||
2022 | ||||
2021 | ||||
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2019 |
Data Analysis (3c)
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2018 | ||||
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2016 |
Data Analysis (3c)
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2015 | ||||
2014 | ||||
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2012 | ||||
2011 | ||||
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2007 |