Timberlake (Portugal) and FEP (U. Porto) are jointly organizing a set of applied Econometrics courses using Stata. The aim of these courses is to familiarize the participants with key econometric tools commonly used in applied research.

The courses include a quick discussion of the relevant econometric theory as well as an in-depth discussion of empirical applications using real data. The course will take place at FEP (U. Porto) on January 2018.  

All participants are invited to wine tasting and special dinner on thursday, 25th. This event is included in the price of the Winter School.

Day 1 - Introduction to Stata delivered by Miguel Portela

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

Day 2 - Regression analysis & causality delivered by João Cerejeira

• 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 delivered by Miguel Portela

• 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
• Dynamic Panel Data: endogeneity & GMM - First-differences & the System GMM estimator

Day 4 - Discrete Choice Models delivered by Anabela Carneiro

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

Special Event: Wine tasting and dinner

Day 5 - Count Data Models delivered by Paulo Guimarães

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

> VIEW COURSE INFO, INCLUDING PRICES AND REGISTRATION

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