Doctoral Level Data Analysis

MGMT-7830

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.

3 credits
Prereqs:
none

Past Term Data

Offered
Not Offered
Offered as Cross-Listing Only
No Term Data
Spring Summer Fall
(Session 1) (Session 2)
2023
2022
2021
2020
2019
Data Analysis (3c)
  • Nishtha Langer
Seats Taken: 7/15
2018
2017
2016
Data Analysis (3c)
  • Nishtha Langer
Seats Taken: 5/15
2015
2014
2013
2012
2011
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