FineResults Research Services invites you to training on:

Topics: Longitudinal/Panel and Time Series Data Analysis using Stata

Date: 13th to 17th July 2020

Cost: USD 800 or Ksh 65000

Contacts: +254 759 285 295, training@fineresultsresearch.org

Venue : FineResults Research, Nairobi, Kenya Training Centre.

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-stationary in long panels, where the time series (as opposed to cross-sectional) characteristic of the data dominates; and ii) co integration. 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:
• 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

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

NB: We are offering you a half day, fun and interactive team building event!

Be part of the Training
• Click HERE for the individual registration.

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