Links to section notes and relevant files.

These notes (and I) owe a lot to previous GSIs for this class: Fiona Burlig, Kenny Bell, Patrick Baylis, and Dan Hammer.

Install R, RStudio, and other relevant programs; resources for R; general suggestions for coding.

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**Section 1**: Getting started with R

Learning the basics of R: installing and loading packages; loading various data types (`haven`

and `readr`

); basic data summarization and manipulation (introduction to `dplyr`

).

pdf | R script | zip

Vectors, matrices, and general mathematical usage of R.

pdf | R script | zip

**Section 3**: Functions and loops

Writing your own (OLS) functions, using loops, and running simulations in R.

pdf | R script | zip

**Section 4**: FWL and model fit

Logical operators, optional arguments to your custom functions, Frisch-Waugh-Lovell (FWL) theorem, omitted variable bias, and measures of fit/overfitting.

pdf | R script | zip

**Section 5**: Inference and parallelization

Statistical inference via hypothesis testing: *t* tests and \(F\) tests. Plus simulation and parallelization.

pdf | R script | zip

Generalized least squares (GLS), weighted least squares (WLS), and more simulations!

pdf | R script | zip

**Section 8**: OLS in asymptopia

OLS as \(N\) gets (very) big. Also: simulations, coding efficiency, and new `ggplot2`

techniques.

pdf | R script | zip

**Section 9**: Standard errors, Vol. I

Calculating standard errors via analytical methods and via the Delta Method. Includes linear and nonlinear combinations of parameters. Plus making prettier tables.

pdf | R script | zip

**Section 10**: Standard errors, Vol. II

Calculating standard errors in various situations: spherical errors, heteroskedastic errors, temporally correlated errors, spatially correlated errors, clustered errors.

pdf | R script | zip

**Section 11**: Instrumental variables

Instrumental variables (IV) and two-stage least squares (2SLS). Plus measurement error.

pdf | R script | zip

Spatial data. Shapefiles, points data, maps, and—more generally—R as a GIS.

pdf | R script | zip

**Section 14**: Simultaneous-equation models

Simultaneous equations—theory, identification, estimation, and simulation.

pdf | R script | zip

Introductions to and resources for LaTeX and `knitr`

.

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