ECONOMETRICS USING STATA


Timberlake Consultants

Start Date:

End Date:

Application Deadline:

Type

Professional training

Location

Cass Business School

London

United Kingdom

Start Date:

End Date:

Location

United Kingdom

London

Type

Professional training

Application Deadline:

COURSE OVERVIEW

Prof. Christopher F. Baum delivers this interactive 3-day Stata course to be held at Cass Business School, London on 4-6 September 2017.

Prof. Christopher F. Baum is Professor of Economics and Social Work at Boston College, and DIW Research Fellow at the Department of Macroeconomics, DIW Berlin, Germany. He is also a key Stata Press author, including  An Introduction to Modern Econometrics using Stata and An Introduction to Stata Programming, Second Edition. The course covers the the following essential Stata capabilities:

  • A brief overview of Stata
  • Using Stata for Data Management
  • Working with the command line
  • Reading/writing external data
  • Estimation and forecasting: OLS, IV, IV-GMM
  • Panel data estimation
  • Time series estimation and forecasting
  • Automation and programming using Stata (including an introduction to Mata)

COURSE AGENDA

DAY 1

SESSION 1 (3 HOURS): USING STATA FOR DATA MANAGEMENT AND REPRODUCIBLE RESEARCH

  • Overview of the Stata environment
  • Working with the command line
  • Data management: principles of organisation and transformation
  • Reading external data
  • Writing external data
  • Combining data sets
  • Reconfiguring data sets

SESSION 2 (3 HOURS): ESTIMATION AND FORECASTING: OLS, IV, IV-GMM

  • Linear regression methodology
  • Regression with indicator variables
  • Using factor variables
  • Computing and graphing marginal effects
  • Instrumental variables estimators
  • Tests of overidentifying restrictions
  • Testing for i.i.d. errors in an IV context
  • Nonlinear least squares estimators
  • Ad hoc GMM estimation

DAY 2

SESSION 3 (3 HOURS): PANEL DATA ESTIMATION AND FORECASTING

  • Panel data management
  • Estimation for panel data
  • Fixed effects, between effects, random effects models
  • First difference models
  • Seemingly unrelated regressions (SURE) models
  • Ex ante forecasting from SURE
  • Instrumental variables panel models
  • Dynamic panel data (DPD) models and diagnostics
  • Ex ante forecasting from DPD

SESSION 4 (3 HOURS): TIME SERIES ESTIMATION AND FORECASTING

  • Time series data management
  • Rolling-window estimation
  • Structural break models
  • Time series filtering
  • Unobserved components models
  • ARIMA and ARMAX models
  • ARCH, GARCH, MGARCH models
  • Vector autoregressive models
  • Vector error correction models
  • Stata’s additional capabilities for time series data

DAY 3

SESSION 5 & 6 (FULL DAY): AUTOMATION AND PROGRAMMING WITH STATA

  • Programming with do-files
  • Do-file programming: recipes
  • Programming with ado-files
  • Ado-file programming: developing a Stata command
  • Programming ml, nl, nlsur, gmm function evaluators
  • Programming egen functions
  • Introduction to Mata
  • Mata language elements
  • Design of a Mata function
  • Mata programming: interfacing with Stata
  • Some examples of Stata-Mata routines

READING MATERIALS BEFORE AND AFTER THE COURSE

BOOKS

These books (and other Stata Press Books) are available to purchase from the course at a 20% discount off the price quoted on our website.

TIME SERIES FORECASTING

INSTRUMENTAL VARIABLES

These are also freely available from the Stata Journal web site.