Research in Applied EconometricsChapter 0. Organization 2017-18

Pr. Philippe Polomé, Université Lumière Lyon 2

M1 APE Analyse des Politiques ÉconomiquesM1 RISE Gouvernance des Risques Environnementaux

2017 – 2018

Plan

I PresentationI MotivationI Organisation

Myself gate.cnrs.fr/spip.php?article44

I All the slides available via this page

Master RISE http://risques-environnement.universite-lyon.frParcours “Gouvernance des Risques Environnementaux”

risques-environnement.universite-lyon.fr

Course Objectives & Motivations

I Class in EconometricsI In a unit of English language

I Goal: Expose students to applied econometrics in English

I Applied examples with environmental economics dataI Students should improve both their applied econometrics skills

and their English levelI Attendance and interactions in class

I Focus on applied techniques: Introduction to R

I More on that laterI Context : ex ante valuation of public (environmental) policies

I Contingent valuation / stated preferencesI In econometrics detailsI With R commandsI With data & examples

The relevance of valuation studiesI Cost-benefit analysis

I Newly in France: public project with a “déclaration d’utilitépublique” have to justify that Benefit > Cost

I For market and nonmarket goods & servicesI Including e.g. value of human life, ecosystem services, patrimonial

& heritage valuesI In principle

I How do we compute that ?I That includes environmental “services”, e.g. ecosystem functionsI But also all kinds of benefits & costs, e.g. a prison removes

criminal from society and helps their rehabilitationI “valeurs tutélaires” (guidelines) & consensual discount rate

I Damage assessment for non-market goodsI France introduced a few years ago the principles of

environmental damage and compensation in kindI well-embodied in US legislationI not so much in EU legislation

I Greening the National Accounts

Course Plan

1. Introduction to R2. Nonmarket valuation basic theory

I French tend to say “évaluation”I English stresses the idea of valuing

I “assigning a value”

3. Contingent valuationI Most well-known technique

4. (Choice experiment)I Harder econometrics

Course Organization

I 6 lectures of 3.5 hours eachI Every week

I “Dispense d’assiduité” not possible for language coursesI Bring your laptop as much as possible

I Do not forget it is a language courseI Please interrupt me when you don’t understand

Evaluation: “Contrôle continu” in class for 100%

I About 20’ at some point of each lectureI Beginning, end or middle

I On what we have seen during that lecture & the previous one (notseveral)

I If you miss one, you get zero at that oneI The 1st one is just practice

I No final exam in “first session” in DecembreI “Rattrapage” in June

I It is super important that you read / study the class notes before

coming to classI That is why we do CC

References

I Aizaki et.al. Stated Preference Methods Using R. Chapman andHall/CRC, 20140815. VitalBook file.

I Use DCchoice-package {DCchoice} in RI Base documentation in R

I Kleiber & Zeilis, Applied Econometrics with R, Springer, 2008I Wooldridge, J. Introductory Econometrics : A Modern

Approach, Michigan State University, 2012I Click this linkI BU Chevreul[330.015.2 WOO] (1)

I Not [330.015.2 WOO] (2) Econometric analysis of cross sectionand panel data

Install R

I Come to class w/ a laptopI R & R-studio installed & up-to-date

I R @ www.r-project.org/I R-Studio https://www.rstudio.com/

I IDE (integrated development environment)I Not a Graphical User Interface, but more useful

I Packages “add functionalities”I Most often from within R-studio

I Start R-StudioI R-Studio calls R

Presenting R-studio: 4 windows

R-Studio Upper Left Window: editor

I Invoked with any of 2 leftmost buttons of the toolbar (New orLoad)

I Color-coded, with online help & command recognitionI Programming is written in the editor

I Programming = sequence of commands in a text file “script”I with an .R extensionI This file is saved for further use, between “sessions”

ICommands are passed by e.g. plot(x)

I The editor recognizes command and colors them in blueI Commands are executed in the editor by CMD - row by row

I Command results may be stored in objects with <-I y_lm <- lm(y~x1+x2)

I Several command files may be simultaneously openI tabs

R-studio Windows

I Lower Left : console

I Print out command results from editorI Usual way to write code : write one or a few lines, test it

I Write commands for immediate execution (with -)I Does not stay in memory

I Upper RightI Environment: List in memory

I Can be data or results or functionsI Within a project (later) or not

I Command historyI Can be reused

R-studio Lower Right Window : 5 tabs

I Files within the projectI Visualisations of PlotsI Packages that are present

I Loaded if checked squareI Install button

I Click it (you must be connected)I Type swirl & follow instructions

I HelpI Viewer

I to view local web content (if you edit webpages)I These 5 tabs have in common the Search window

First commands: Project

I A project is a file that refers to a collection of filesI R command files .R, data files, results

I There’s an icon in the upper-right corner of R-StudioI Click it & create a project “Research in Applied Econometrics”

I Where you create it is your work directoryI Do not use the desktop, the root, or any hard-to-find location

I Download the RAE2017.R on my courses’ siteI Into the same directory as your projectI Open it from R-studio Editor : Icon upper left

I R-Studio recalls the projectsI You can go from one to anotherI All the files written on disk remain available

First commands

I Some manipulation in ConsoleI write Sys.setenv(LANG = "fr")

I Sets R Console in French, only for “core”, not for most packageI R-Studio is only in English

I write install.views("Econometrics")I For about all the packages we will ever needI This is long : don’t do that in class !I In the future update.views("Econometrics")

I EditorI Write here things that you intend to reuseI

Avoid French symbols é, è, ê, ë, à, ù, ç, ...I

Avoid symbols like #, $, &, -... if you are unsure of their useI

Try to stick to unaccented latin characters (i.e. US alphabet)I CAPITALISATION is important

I Starting a row w/ # indicates to R that it is a commentary

I Green-colored, will not be executed

SWIRL: set of basic training modules

I Install swirl as any package from R-studio (should be installedby now)

I Then typeI install_course("R Programming")I install_course("Regression_Models")

I Other courses https://github.com/swirldev/swirl_coursesI About SWIRL: http://swirlstats.com/students.htmlI Slides https://github.com/DataScienceSpecialization/courses

I Self-training : Type swirl( ) in concoleI do course 1: R programming, Lessons 1-9 + 14

I By yourself, from home, before 1st classI We will redo Lesson 1 in class

Some ressources about R on the web

I Use Google !I Ask question based on English keywords

I e.g. “R read Stata data”I From R home page www.r-project.org

I Getting help, Manuals, FAQS...I A few interesting links

I Quick-R www.statmethods.net/index.htmlI http://stats.idre.ucla.edu/r/I http://varianceexplained.org/RData/I www.r-bloggers.comI R for economists

I www.mayin.org/ajayshah/KB/R/R_for_economists.html

I En français: forget about French for R

To sum up

I For the 1st course you have to haveI installed R & R-Studio on your machinesI From R-Studio

I install.views("Econometrics")I install swirl

I In swirl :I install the 2 modules (programming & regressions)I do course 1: R programming, Lessons 1-9 + 14

I Install packages : DCchoice, Ecdat, statsI Created your project & opened RAE2017.RI Classes are mandatory

I There is CC in each one, no final exam