Training Calendar

Stata Econometrics Winter School - Porto

  • Location: Faculty of Economics - University of Porto - CEF.UP
  • Duration: 5 days (22nd January 2018 - 26th January 2018)
  • Software: Stata
  • Level: 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)
  • Topic: Econometrics, Statistics, Winter School
Stata Econometrics Winter School - Porto

Our sixth annual Stata Winter School runs in Oporto between 22-26 January 2018

The Stata Winter School comprises a series of four separate short courses that allows the flexibility to attend one, a combination of or all courses consecutively.

The courses forming the 2018 Stata Winter School are:

• Day 1: Introduction to Stata
• Day 2: Regression analysis & causality
• Day 3: Panel Data
• Day 4: Discrete Choice Models
• Day 5: Count Data Models

Click here to view the complete course agendas, schedule information, and suggested pre course reading list.


Please note all prices include the following: 

  • Coffee breaks (morning and afternoon)
  • Light lunch
  • 1 Stata Press book of your choosing from the reference list.

For prices in EUR, please contact or call +351 21 424 01 43

Day 1: Introduction to Stata - Miguel Portela

22 January 2018

  • 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 manupulation
  • From Stata to LaTex, Word and Excel: efficient procedures to export descriptive statistics graphs and regression tables

Day 2: Regression Analysis & Causality - João Cerejeira

23 January 2018

  • Econometric Concepts: Regression analysis - OLS & GLS
  • Basic issues in program evaluation; Causality and the problem of selection bias
  • Regression and Causality
  • Instrumental Variables (two stage least squares (2SLS); weak instruments; overidentification tests)
  • Propensity score matching
  • Longitudinal Data: Differences-in-differences (DD)

Day 3: Panel Data - Miguel Portela

24 January 2018

  • Panel Data Regression: Dealing with endogeneity issues
  • Data structure & formulation of the model
  • Fixed and Random Effects in Static Models
  • Hausman test for the validity of the random effects model 
  • Hypothesis testing, Test for the presence of fixed effects, Wald tests, testing multiple hypothesis
  • Heteroscedasticity, Autocorrelation, Robust Estimation 

Day 4: Discrete Choice Models - Anabela Caneiro

25 January 2018

  • Binary Response Models
  • Maximum Likelihood Estimation
  • Measures of Fit
  • Marginal Effects 
  • Hypothesis tests
  • Multinominal Models
  • Conditional Logit Models
  • Ordered models

Hour TBA: Special Event: Wine tasting and dinner

Day 5: Count Data Models - Paulo Guimarães 

26 January 2018

  • Discrete distributions
  • Poisson regression
  • Negative Bionominal Regression
  • Conditional Counts
  • Zero Truncated Regression
  • Excess Zeros
  • Endogenous Regressors
  • Panel data

Principal texts for pre/post course reading:

  • Financial Econometrics using Stata (Simona Boffelli and Giovanna Urga);
  • An Introduction to Modern Econometrics using Stata (Christopher Baum)
  • An Introduction to Stata Programming, second Edition (Christopher Baum)
  • Microeconometrics using Stata (A. Colin Cameron and Pravin K. Trivedi)
  • Introduction to Time Series using Stata (Sean Becketti)
  • Data Analysis using Stata, third Edition (Ulrich Kohler and Frauke Kreuter)
  • Regression Models for Categorical Dependent Variables using Stata, third Edition (J. Scott Long and Jeremy Freese)

DAILY TIMETABLE (subject to minor changes)

TimeSession / Description
08:50-09:20 Arrival & Registration
09:30-11:00 Session 1
11:00-11:30 Tea/coffee break
11:30-13:00 Session 2
13:00-14:00 Lunch
14:00-15:30 Session 3
15:30-16:00 Tea/coffee break
16:00-17:30 Session 4


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

Prior knowledge of Stata is not essential but very helpful;

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

Basic knowledge of Stata and discrete choice models.

Basic knowledge of Stata and count data models.

Terms • 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, 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 for a fee of £10.00 (ex. VAT) per day). • 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 (22/01/2018 - 26/01/2018)
    2 day pass (22/01/2018 - 26/01/2018)
    3-day pass (22/01/2018 - 26/01/2018)
    4-day pass (22/01/2018 - 26/01/2018)
    5-day pass (22/01/2018 - 26/01/2018)

All prices exclude VAT or local taxes where applicable.

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