NetCourseNow 471: Introduction to panel data using Stata

$495.00Self-paced

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Become an expert in the analysis and implementation of linear, nonlinear, and dynamic panel-data estimators using Stata. This course focuses on the interpretation of panel-data estimates and the assumptions underlying the models that give rise to them. The course is geared for researchers and practitioners in all fields. The breadth of the lectures will be helpful if you want to learn about panel-data analysis or if you are familiar with the subjects.

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Discounts available for enrollments of two or more participants.

Prerequisites

Stata 19 or Stata 18, installed and working
Course content of NetCourse 101 or equivalent knowledge
Familiarity with basic time-series, cross-sectional summary statistics and linear regression
Internet web browser, installed and working
(course is platform independent)

Course content

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Lesson 1

An introduction to panel data and its features

Getting started with panel data
Summary statistics and dynamics

Overview of basic concepts

Data generation
The regression model

Variance–covariance estimators

Margins and marginal effects
Basic panel-data estimation concepts

Moment-based estimation

Panel data, regression, and efficiency

Closing remarks

Lesson 2

Random-effects model

The model

Fixed-effects model

Within estimator

Comparing within and random-effects estimates

First-differenced estimator

Deciding between random and fixed effects

Hausman test
Mundlak test

Population-averaged models

Lesson 3

Probit model

Probit models for panel data: Random effects
Probit models for panel data: Population averaged
Probit models for panel data: Remarks

Logit model

Logit models for panel data: Random effects
Logit models for panel data: Fixed effects
Logit models for panel data: Population averaged

Poisson model

Poisson models for panel data

Lesson 4

Endogeneity

Cross-sectional estimation under endogeneity
Panel-data estimation under endogeneity

Dynamic models
Building your own dynamic models

A more complex dynamic structure

Concluding remarks

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