Longitudinal or panel data are multi-dimensional Information involving measurements over time. Such data are analyzed using dynamic model. Dynamic models have become increasingly popular due to their ability to take into account both short and long term effects and unobserved heterogeneity between economic agents in the estimation of the parameter estimates. Stata is very specialized in handling dynamic data. this training course provides an overview of existing dynamic data analysis techniques. Participants will be taken through a series of illustrative examples, with a theoretical and applied overview. Recent issues in dynamic panel data analysis will also be covered. The course concludes by addressing the issues of; i) non-stationarity in long panels, where the time series (as opposed to cross-sectional) characteristic of the data dominates; and ii) cointegration. The training will pay particular attention (using a combination of both official Stata and user written dynamic panel data analysis commands) to: i) evaluating which specific econometric methodology/specification is more appropriate for the analysis in hand; ii) selection of the appropriate instruments; iii) rigorous post estimation diagnostic/specification testing; and iv) the problems of inference resulted from weak-instrument bias, instrument-proliferation bias and small-sample bias. Special attention will also be given to the interpretation and presentation of results.
Why Are Panel Data Desirable?
Problems with Panel Data
Examples of Time-varying and time-invariant variables
Data requirements
Control for unobservables
Determining causal order
Problem of dependence
Software considerations
Robust standard errors
Generalized estimating equations
Random effects models
Fixed effects models
Between-within models
Robust standard errors
GEE
Subject-specific vs. population averaged methods
Random effects models
Fixed effects models
Between-within models
Poisson models
Negative binomial models
Fixed and random effects in the SEM context
Models for reciprocal causation with lagged effects
Usefulness and problems with Panel Data
Opportunities and challenges of panel data.
Linear models data analysis with dynamic data
Logistic regression models with dynamic data
Count data models with dynamic data
Linear structural equation models with dynamic data
Find subjects you're passionate about by browsing our online course categories. Start
learning with top courses Built With Industry Experts.