COURSE: USING R IN APPLIED ECONOMETRICS
VCREME is pleased to announce the launch of the Basic R1 and Basic R2 technical application classes. The topic of this technical course is ‘Application of the R programming language in Econometrics’.
A. Objectives of the course
The course will equip students with the following basic and necessary knowledge:
1. Data Cleaning (also known as Data Cleaning, Data Wrangling, Data Manipulation). In fact, the data – the raw material for any quantitative analytical model – is never as desirable as the modeler expects. Before we can use the data for the model, we often have to, for example, process the missing data (Missing Data) or convert the data to the appropriate forms for the model.
2. Provide students with guidelines as well as the ability to design statistical graphs – also known as data visualization – necessary for not only academic research but also necessary for reporting purposes.
3. Use R to perform the analysis, econometric models commonly seen such as regression analysis, diagnosis of possible errors of the regression model, error correction method of the regression model (such as multi-collinearity, altered error variance, or abnormal observations).
4. Program self-written functions, self-design test procedures or analytical models, or have the ability to modify existing R models / functions to suit the specific requirements each study.
B. Curriculum / materials and sources of data used
Textbooks and data sources are an important element in gaining access to new, up-to-date knowledge and skills. VCREME selects the most commonly used textbooks (data sources) in the world:
1. Introductory Econometrics: A Modern Approach (Jeffrey M. Wooldridge).
2. Basic Econometrics (Damodar N Gujarati).
3. Applied Econometrics with R (Christian Kleiber & Achim Zeileis).
4. And some other materials.
C. Course content
Section 1: R as an econometric research tool
Overview of R
Install R, Rstudio and the necessary packages
Conventions for using R for analysis
Calculations and objects in R
Section 2: Statistics describing and visualizing data with R
Read data from files available in various formats, from external sources to R
Data management, renaming, data editing
Export data from R
Descriptive statistics with functions available in R
Piping pipe operator (%>%)
Section 3: Graph in R
Install the packages
Request a specific package to present
Use Rmarkdown to exchange, publish results on the Internet with Rpub
Use Latex and R / RStudio to present a study in accordance with the standards required by the journal.
Statistical Graphs Basic
Statistical Graphs with ggplot2 package
Section 4: Linear regression model in R
Perform some common tests for regression models
Section 5: Extension of the two-variable regression model
Regression through the origin – CAPM model
Linear logarithmic model
Section 6: Multiple regression models
Perform multiple regression in R and confidence intervals for coefficients
Confidence interval for an expression of the regression coefficient
Verify Wald on the binding of regression coefficients
Test F for simultaneous zero of multiple regression coefficients
Section 7: Diagnosis of regression model errors
The phenomenon of multi-collinear
An example illustrates the multi-collinear phenomenon
Treat hyperbolic phenomena by neglecting variables based on the Mallow criterion Cp
D. Registration information
Lecturer: Nguyen Chi Dung, PhD. Trinh Thi Huong
Estimated schedule: On Saturdays, Sundays (except public holidays)
+ Basic R1 Hanoi: 06/01/2018 – 04/02/2018
+ Basic R2 Saigon: 21/01/2018 – 11/02/2018
Duration: 21 hours / 07 sessions, 03 hours per session
Registration deadline: 17/10/2017 – 10/11/2017
Application Form: https://goo.gl/forms/QYoytfUr32oueSpj1
Course fee: VND 3,000,000 for VCREME pre-master course students
VND 4,000,000 for other students
Priority: The first 15 slots will be priorily given to students who are already enrolled in Econometrics at VCREME (www.vcreme.edu.vn).
Note: The above teaching materials and contents may be adjusted to suit the needs and situation of the trainees.
For more information please contact:
Mr. Nguyen Tuan – 094 396 5106 – firstname.lastname@example.org