Home  /  Learn  /  Webinars  /  Bayesian econometrics in Stata

Webinar: Bayesian econometrics in Stata

Overview

Duration: 1 hour
Where: Join us from anywhere!
Cost: Free—but registrations are limited

Description

Stata 17 introduced Bayesian support for many time-series and panel-data commands. In this webinar, we will discuss Bayesian vector autoregression models, Bayesian DSGE models, and Bayesian panel-data models. Bayesian estimation is well suited to these models because economic considerations often impose structure that is captured well by informative priors. We will describe the main features of these commands as well as Bayesian diagnostics, posterior hypothesis tests, predictions, impulse–response functions, and forecasts.

How to join

The webinar is free, but you must register to attend. Registrations are limited so register soon.

We will send you an email prior to the start with instructions on how to access the webinar.

Presenter: David Schenck

David Schenck portrait

David Schenck is a Senior Econometrician at StataCorp LLC. He earned his bachelor's degree in economics from Vanderbilt University and a PhD in economics from Boston College. His interests include time series, Bayesian analysis, and macroeconomics. At Stata, he is the primary developer of DSGE and other time-series features.


Register

Registration is now closed.

To be notified of future course offerings, sign up for an email alert below.

First name *
Last name *
Email address *
Confirm email address *
Country *
Company/Organization/University *
Department/Field *
Stata serial number
(optional)

Yes, I would like to receive emails regarding the following:

We appreciate that our users do not want to be inundated with email. Those who sign up to receive emails can anticipate receiving no more than a couple in a month. For example, someone who signs up to be informed of Stata Conferences may receive four emails in one year.


To ensure delivery of emails to your inbox, add [email protected] to your address book.

StataCorp has a strict privacy policy.