Training Calendar

Stata Econometrics Winter School 2020

5 days (20th January 2020 - 24th January 2020) Stata Intermediate, Introductory
Delivered by: Miguel Portela (Universidade do Minho, Escola de Economia e Gestão); João Cerejeira (Universidade do Minho, Escola de Economia e Gestão); Anabela Carneiro (Universidade do Porto, Faculdade de Economia); Paulo Guimarães (Universidade do Porto, Faculdade de Economia and Banco de Portugal); Kit Baum (Boston College)
Econometrics, Statistics, Winter School

Overview

Our sixth annual Stata Econometrics Winter School runs in Oporto, Portugal between 21-25 January 2020.

This series of one-day short courses are jointly organised with the Faculdade de Economia da Universidade do Porto. The School aims to provide the full set of tools and techniques that any modern applied economist needs to know. Participants will learn the techniques properly using Stata statistical software.

The courses that comprise the 2020 Stata Winter School are:

  • Day 1: Introduction to Stata
  • Day 2: Data Analysis, Linear Regression, and Spatial Econometrics
  • Day 3: Linear Panel Data Models
  • Day 4: High-dimensional fixed-effects & Managing Output Files
  • Day 5: Introduction to programming in Stata

Who Should Attend?

Academic Staff, Masters / PHD students and professionals that need to analyse data. The courses aim to offer an effective way to reach an advanced level of econometric analysis. Therefore, in order to get the most out of the course, basic knowledge of statistics and econometrics is required.

All courses will be delivered in English.

Agenda

Day 1 - Introduction to Stata

  • Introduction to the Stata: from menus to 'do' files
  • Handling data with different data types: Stata, ASCII, Excel, CSV, Web Data and ODBC
  • Data reshaping
  • Combining different data sets: merge and fuzzy merge
  • Exploratory data analysis: descriptive statistics and graphic manipulation




Day 2 - Data Analysis, Linear Regression, and Spatial Econometrics


  • Bivariate inferential statistics
  • Simple and multiple linear regression
  • Specification issues: regression with indicator variables, nonlinear relationships and regression diagnostics
  • Regression analysis and causality: internal and external validity
  • Spatial data analysis and spatial econometrics

Day 3 - Linear Panel Data Models

  • Introduction to Panel Data Analysis
  • Fixed Effects Model
  • Test for the Presence of Fixed Effects
  • Random Effects Model
  • Test for Random effects: the Hausman test
  • Pooled OLS Model
  • Comparison of Estimators

Day 4 – High-Dimensional Fixed Effects (HDFE) & Managing Output Files


Session 1 - High-Dimensional Fixed Effects

  • The Linear Model with one HDFE
  • The Linear Model with two HDFE
  • "Spell” fixed effects
  • Estimation with two HDFE
  • Identification of the fixed effects
  • Multiple HDFE

Session 2 - Managing Output Files

  • Exporting Output Results (Tables and Graphs): Excel, Word, PDF, Latex
  • Creating and modifying files from within Stata: Excel, Word
  • Literate Programming with Stata
    • Markdown / Pandoc
    • Markstat: Outputting to HTML/Word/PDF/Latex/Beamer
  • Automating the Production of Papers and Reports: Examples

Day 5 - Introduction to programming in Stata

Session 1 - do-file programming

  • Overview of the Stata environment
  • do- and ado-files
  • Data types
  • Dates and time
  • Time series operators
  • Factor variables
  • Debugging and tracing
  • Protecting your data
  • Guidelines for writing do-files
  • Generate and egen functions
  • Transformation of string and numeric variables
  • Local macros and scalars
  • Looping commands
  • Global macros
  • Extended macro functions and list functions
  • Stata matrices
  • Prefix commands
  • Selected tools for do-file authors

Session 2 - Automation, ado-file and Mata programming

  • Post and postfile commands
  • Production of summary statistics
  • Production of estimates tables
  • Production of sets of tables and graphs
  • Structure of an ado-file
  • Selected examples of ado-file programming
  • Mata fundamentals
  • Syntax of the language
  • Design of a Mata function
  • Mata’s interface functions
  • Selected examples of Mata programming
  • Integration with Python

References

Prerequisites

Day 1 - Introduction to Stata

  • No prior knowledge of Stata required. Knowledge of using other statistical software is an advantage but not necessary.

Day 2 - Data Analysis, Linear Regression, and Spatial Econometrics

  • Prior knowledge of Stata is not essential but very helpful.

Day 3 - Linear Panel Data Models

  • Basic knowledge of Stata and panel data models.

Day 4 - High-dimensional fixed-effects & Managing Output Files

  • A basic understanding of Stata and familiarity with regression analysis are required.

Day 5 - Introduction to Programming in Stata

  • Previous working experience in Stata is expected, as well as an interest in programming.

Terms and Conditions

  • Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrolment).
  • Additional discounts are available for multiple registrations.
  • Cost includes course materials, light buffet lunch and refreshments.
  • Delegates are provided with temporary licences for the software(s) used in the course and will be instructed to download and install the software prior to the start of the course. Alternatively, laptops can be hired at an additional daily cost. Limited availability. Please contact us should you need to hire a laptop for the course.
  • If you need assistance in locating hotel accommodation in the region, please notify us at the time of booking.
  • Payment of course fees required prior to the course start date.
  • Registration closes 5-calendar days prior to the start of the course.
    • 100% fee returned for cancellations made over 28-calendar days prior to start of the course.
    • 50% fee returned for cancellations made 14-calendar days prior to the start of the course.
    • No fee returned for cancellations made less than 14-calendar days prior to the start of the course.

The number of delegates is restricted. Please register early to guarantee your place.

  •  CommercialAcademicStudent
    1-Day Pass (20/01/2020 - 24/01/2020)
    2-Day Pass (20/01/2020 - 24/01/2020)
    3-Day Pass (20/01/2020 - 24/01/2020)
    4-Day Pass (20/01/2020 - 24/01/2020)
    5-Day Pass (20/01/2020 - 24/01/2020)

All prices exclude VAT or local taxes where applicable.

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