- TypeWorkshop
- Location Nairobi, Kenya
- Date 19-12-2022 - 23-12-2022
Education/Teaching/Training/Development
Research/Science
Information Technology
INTRODUCTION
Longitudinal or panel data are multi-dimensional data 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.
DURATION
5 Days
COURSE OBJECTIVES
By the end of this training, participants will become knowledgeable in the following:
COURSE OUTLINE
Module 1: Introduction
Introduction to Panel Data
• Why Are Panel Data Desirable?
• Problems with Panel Data
• Examples of Time-varying and time-invariant variables
Opportunities and challenges of panel data.
• Data requirements
• Control for unobservable
• Determining causal order
• Problem of dependence
• Software considerations
Module 2: Linear models
• Robust standard errors
• Generalized estimating equations
• Random effects models
• Fixed effects models
• Between-within models
Module 3: Logistic regression models
• Robust standard errors
• GEE
• Subject-specific vs. population averaged methods
• Random effects models
• Fixed effects models
• Between-within models
Module 4: Count data models
• Poisson models
• Negative binomial models
Module 5: Linear structural equation models
• Fixed and random effects in the SEM context
• Models for reciprocal causation with lagged effects
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TRAINING CUSTOMIZATION
This training can also be customized for your institution upon request. You can also have it delivered to your preferred location. For further inquiries, please contact us through: Telephone: +254 732 776 700 or Email: [email protected]
REQUIREMENTS
Participants should be reasonably proficient in English. During the trainings, participants should come with their own laptops.
TRAINING FEE
The course fee covers the course tuition, training materials, two break refreshments, lunch and a study visit (where applicable).
ACCOMMODATION
FineResults Research Services arranges accommodation for their clients upon request. For reservations contact us through Telephone: +254732776700 or Email: [email protected]
Fahari Palace Apartments, along Church Road, Nairobi Kenya
+254 732 776 700 +254 732 776 700