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Econometrics and Statistics using R

Gades Training presents Econometrics and Statistics Using R. The 5 training days provide the full set of tools and techniques that any modern applied researcher needs to know. Participants will learn the fundamental principles of modern statistics, econometrics, time series and forecasting, and will also learn how to apply the techniques properly using R software.

This course covers main practical aspects in statistical and Econometrics computing. 

The objective of this course is to teach how to program R and how to use R for successful data analysis.


Day 1 - Introduction to R
- Introduction: The Fundamentals of R programming language
- Control Structures: conditionals and loops
- Functions
- Data management and visualization

Day 2 - Introductory Statistics with R: Estimation and Hypothesis Testing
- Probability and Distributions
- One and Two-sample Tests
- Categorical Data
- Nonparametric Tests

Day 3 - Causality in Econometrics 1: OLS and Difff-in-Diff 
- Large Sample Approximations and Matrices for Linear Models;
- Method of Moments Estimation;
- Generalized Method of Moments;
- Practical session.

Day 4 - Causality in Econometrics 2: IV and Regression-Discontinuity-Designs
- Holt Winters and exponential smoothing
- ARIMA model building in practice: Box-Jenkins methodology
- Non-stationarity and unit root test
- Forecasting with ARIMA models

Day 5 - Time-series 1: ARMA models and Forecasting
- Large Sample Approximations for Nonlinear Models
- Binary Outcome and Multinomial Models
- Tobit Models, Selection Models and Count Data
- Endogeneity in Nonlinear Models

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