421-Lab-Notes

Here is where you can see the lab notes for Luciana Etcheverry’s Econometrics (EC421) for Fall 2019. We’ll periodically update these after class on Tuesdays, and I will generally try to make these serve as a complement rather than a substitute for lab.

For those having difficulty finding their filepath:

Mac: control+click on the file, hold down alt, and then select copy as filepath. That object should be able to go straight into an R read_csv() function. Make sure it’s surrounded by either ‘ ‘ or “ “

Windows: hold shift, right click, copy filepath. Paste this into read_csv(). Flip the direction of the slashes.

Some Useful Resources:

Getting Started With R

• A nice collection of resources for those starting out in R.

Tidyr cheatsheet

• A few of the most useful pages you can find.

ggplot2 cheatsheet

• Another few of the most useful pages you can find, ggplot this time

Lab Notes

Homework 1

Lab 1: Learning R: Introduction link 1 Alternatively, link 2

• Objects, Functions, Mathematical Operators, Dataframes, Regression, Basic Plots

Lab 1.5: Learning R: Enter the Tidyverse Alternatively, link 2

• Loading your own CSVs into R, dplyr commands (mutate, summarise, filter etc.), qplot

In Lab Activity 1: Getting started for Problem set 1

• Brief intro to objects, functions, loading your CSVs, loading packages, working with dataframes, and running regressions

Homework 2

In Lab Activity 2: Having fun with ggplot

• Review and introduction of tidyverse data cleaning, using tidyverse to create plots, ggplot, getting data from “tidy tuesday”

In Lab Activity 3: Problem set 2 Help

• Review of regression objects, performing GQ, BP and white tests, and heteroskedasticity standard errors. An aside:

In Lab Activity 4: For loops, functions and time series

• For loops, functions, and simulating time series, plus an aside on plotting lines in ggplot.

Mid-term Thursday, Oct 30th in class.

Homework 3

In-Lab Activity 5 Running Regressions with Time Series

• Simulating revisted, Learning how to manipulate time series data in R, running regressions in a time-series world and testing for autocorrelation.

In-Lab Activity 6 Problem Set 3 Help

• Similar to in lab activity 5, but using the data from your current problem set. Read my code carefully before copying - this is not the same as what is required for problemset 3.

Homework 4

In-Lab Activity 7 Soft Introduction to IV

• Do an intuition-driven approach to IV and show some of the tools you’ll want to use for the IV portions of your homework (Problem Set 4.)

Homework Helper, Problem Set 4 The help site

• Problem set 4 uses elements not only from activity 7 and your general knowledge, but specifically benefits from a review of in-lab activity 4 and in-lab-activity 5 plus a review of Luciana’s wonderful course slides.

If you’re adventurous, Grant McDermott’s data science for economists is an amazing resource. It’s designed for PhD students, but not those with any experience with computers. If metrics is your calling, you might enjoy looking at these.

Grant’s Notes