Panel Data Analysis using Stata
Panel Data Analysis using Stata
Enroll
now for instructor led online course in Panel Data Analysis using Stata
and master the application of advanced econometric methods to real
world cases. The course covers basic panel data techniques like fixed
effect and random effect models and advances to GMM and PMG estimators
for Panel Data
The course is best recommended for PhD students in Economics, Finance, Business, Management, Political Economy, Public Policy, International Trade, Health Economics, Environmental Economics and Social Sciences to help them write their PhD Thesis.
Read more about course contentsThe course is best recommended for PhD students in Economics, Finance, Business, Management, Political Economy, Public Policy, International Trade, Health Economics, Environmental Economics and Social Sciences to help them write their PhD Thesis.
Panel data analysis using stata
Course Objectives and Learning outcomes
Our
courses are designed specifically looking into the problems of students
and researchers in understanding the core concepts and application of
theory to test real world scenarios.
Course Objectives
Expected Learning Outcomes
Features of our Online Course in Panel Data Analysis
Personalized contents
Advanced course contents
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Weekly Live Lectures
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Each lecture is recorded
Research co-authorship
learn panel data analysis using stata
Course Contents
The
course in Panel Data Analysis using will cover the follow thematic
contents. The complete list of topics can be requested from the course
instructor as the following is only to describe the key topics covered
in the course. You can also add your own list of topics if you wish to
learn Applied Microeconometrics at advanced level.
Fixed Effects and Random Effects
Variables
in panel data can vary either only across individuals or only time
periods or both. To capture the true picture of such variations,
specific methods like fixed effects, random effects, population averaged
or between effects regression models will be discussed applied to real
data.
Enroll for the courseHausman test vs LM test
To
select the true model to capture the true variation, we will employ
Hausman test to determine between fixed effects or random effects of LM
test to determine between the random effects and pooled regression
models. The tests will be practically demonstrated using real world
data.
Enroll for the courseTesting all assumptions endogeneity
To
validate a regression model is the criteria to base the estimated model
should be used for all predictions and inferences, we need to to use
many assumptions of the underlying models. These assumptions include
autocorrelation, endogeneity, heteroskedasticity and multicollinearity.
Enroll for the course2SLS, GMM and Panel Time Series Models
The
course will cover the advanced topics in estimating instrumental
variable models, Hausman-Taylor estimator, Two stage least squares
regression model, testing for weak endogeneity, Durbin-Wu-Hausman test,
system and difference GMM, panel unit root, panel var, panel vecm and
panel ARDL.
Enroll for the courseComplete the course and earn verifiable certificates
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courses from AnEc Center for Econometrics Research offers digitally
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networks, as email signature or can be downloaded in PDF for using as
printed copy.

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address.
Enroll for Panel Data Analysis using Stata
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