# Chapter 1 Introduction

## 1.1 General Info

### 1.1.1 Contact information

Feel free to email at any time to ask questions about the methods covered in class, although I will prioritize communications over the Slack channel. In this way everyone can benefit from others’ questions and answers. If anyone knows how to solve a problem, debug or fix the code in the Slack forum s/he can help.

There are some rules for making questions on the procedures. Before asking, it is mandatory that you consult the documentation of the function/package; also try to search the answer in a public forum (i.e. Stack Overflow). If after that you still have troubles, post the question taking the following into consideration:

• Be clear and concise, so everyone can understand you
• Be as specific as possible, being clear and straightforward
• Include sufficient information: your goal, the code, the data, everething in order to reproduce the error

Also, you can ask questions about the interpretation of the results, the theory behind, and the like.

## 1.2 Objective

This class notes are an interactive e-material for the Microeconometrics course in the master APE in Paris School of Economics. The aim of this notes is to provide an e-learning material to apply the theorical concepts of the class. The notes are in open review: comments, corrections or contributions that you can make to this part of the course and the material provided are more than welcome.

This part of the course does not cover the theory, and assumes you already had it covered and understood. We will depart from the theory with direct application of the methods.

## 1.3 Prerequisites

Please install R and Rstudio in your laptop. Here is a video to install R and Rstudio in windows and mac. If you have questions or you could not manage to install it, bring your laptop next session. I will help out for the installation.

Why R? R is a free software programming language and a software environment for statistical computing and graphics. The R language is widely used among statisticians, economist, in finance and academics circles.

• R is a free software, easy to install and runs in multiple OS.

• A lot of documentation and forums. Excellent documentation on packages.

• Very active community which allow to use other people codes and projects.

• Great visualization tools thanks to ggplot and plotly packages.

• If you understand the logic behind R you will get into every statistical software very easily.
• Everything seems hard at the beginning. Just try and ask.

A prior knowledge on the use of R is required. We dont have much time to cover the basics. For an introduction to R you can check the following material:

## 1.4 Course structure

• We will have only 3 sessions (2 hours each)
• Bring your laptop with R installed on it
• The material for each session will be online just before each session. In that way you can follow from the e-notes and do the exercises with me during class
• What to expect from each session:

1. Brief explanation on the method (how it works)
2. Replication of a published paper that applies the method (downloading data, cleaning data, estimation, tables and plotting results)
3. Discussion on the interpretation of the results
4. Q/A`
• There will be suggested exercises. These are not mandatory, but remember that if you want to master something, you need to practice. I will be happy to give some feedback on the suggested exercises if you want.

This book is in Open Review. I want your feedback to make the book better for you and other readers. To add your annotation, select some text and then click the on the pop-up menu. To see the annotations of others, click the in the upper right hand corner of the page