🧮 recon — Learn R for Economics

recon (short for R + Economics) is an educational project that helps users learn how to use R for economic analysis.
It provides examples, exercises, and best practices for applying data science methods to real-world economic datasets.

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📘 Overview

This repository is intended for:

• Students and researchers new to R.
• Economists transitioning from tools like Excel, Stata, or Python.
• Anyone who wants a guided introduction to data analysis, visualization, and modeling in R.

You’ll learn how to:

• Work with data frames, tidy data, and use the tidyverse ecosystem.
• Apply statistical and econometric methods.
• Create publication-quality visualizations.
• Reproduce and share results in a reproducible way.

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🧰 Prerequisites

Before getting started, make sure you have:

• macOS (other platforms supported with minor modifications)
• Homebrew installed — Installation guide
• R and RStudio (or VS Code with R extension)

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💻 Installing R with Homebrew

If you don’t already have R installed, you can install it easily with Homebrew:

# Update Homebrew
brew update

# Install R
brew install r

# Verify installation
R --version

Optionally, install RStudio for a more user-friendly IDE:

brew install --cask rstudio

🛠 macOS: Configuring Renviron and Makevars

For building packages from source on macOS (especially on Apple Silicon), it can help to explicitly set SDK paths and compiler flags.

1. Create ~/.Renviron

mkdir -p ~/.Renviron.d
nano ~/.Renviron

Add the following:

# Use the macOS CommandLineTools SDK
SDKROOT=/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk

# Homebrew pkg-config path for dependencies
PKG_CONFIG_PATH=/opt/homebrew/opt/libxml2/lib/pkgconfig:/opt/homebrew/opt/icu4c/lib/pkgconfig:/opt/homebrew/opt/gettext/lib/pkgconfig

Save ('ctrl' + 'O') and close ('ctrl' + 'X')the file.

2. Create ~/.R/Makevars

mkdir -p ~/.R
nano ~/.R/Makevars

Add the following flags:

# SDK and compiler
SDKROOT=/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk
CC=/usr/bin/clang
CXX=/usr/bin/clang++
CXX11=/usr/bin/clang++
CXX14=/usr/bin/clang++
CXX17=/usr/bin/clang++
CXX20=/usr/bin/clang++

CFLAGS=-isysroot $(SDKROOT) -O2 -Wall
CXXFLAGS=-isysroot $(SDKROOT) -O2 -Wall
LDFLAGS=-isysroot $(SDKROOT)

# Homebrew libraries
PKG_CONFIG_PATH=/opt/homebrew/opt/libxml2/lib/pkgconfig:/opt/homebrew/opt/icu4c/lib/pkgconfig:/opt/homebrew/opt/gettext/lib/pkgconfig
CFLAGS += -I/opt/homebrew/include
CPPFLAGS += -I/opt/homebrew/include
CXXFLAGS += -I/opt/homebrew/include
FLIBS=-L/opt/homebrew/opt/gfortran/lib
F77=/opt/homebrew/bin/gfortran
FC=/opt/homebrew/bin/gfortran

This ensures R uses the correct compilers, SDK, and Homebrew-installed libraries when building packages from source.

📦 Setting Up Your Project Environment with renv

renv is a dependency management system for R.
It helps ensure everyone working on recon uses the same package versions — critical for reproducibility.

1. Clone the Repository

git clone https://github.com/smkacur/recon.git
cd recon

2. Initialize renv inside the project

From within your recon directory, start R and run:

install.packages("renv")
renv::init()

This will:

• Create a local renv environment inside the project.
• Snapshot installed packages to renv.lock.

3. Restore dependencies (if renv.lock exists)

If you’ve just cloned the repo and a lockfile already exists:

install.packages("renv")
renv::restore()

This ensures all required packages are installed in your isolated environment.

💡 Using R with VS Code

To use R within VS Code, follow these steps:

1. Install the R extension:

• Open VS Code
• Go to Extensions (⇧⌘X on macOS)
• Search for R and install the extension by Yuki Ueda (or similar)

2. Set the R executable path:

• Press Cmd+, to open Settings
• Search for R: Rterm Path
• Set the path to your Homebrew R binary, e.g.:

/opt/homebrew/bin/R

3. Install the R Language Server:

• Start R in your terminal or VS Code console:

renv::install("languageserver")

This provides code completion, diagnostics, and linting.

4. Optional: Configure VS Code terminal:

• Ensure that your PATH includes Homebrew and your compilers (/opt/homebrew/bin) so that packages can build correctly.

After this setup, you can run R scripts, use the interactive terminal, and benefit from code completions and diagnostics directly in VS Code.

5. Install the R Kernel for Jupyter

Make sure you have R installed (you already have it via Homebrew).

Open R (in terminal or VS Code) and install the IRkernel package:

renv::install("IRkernel")
IRkernel::installspec(user = TRUE)

IRkernel allows Jupyter to recognize R as a kernel. user = TRUE installs the kernel only for your user account.

6. Install Jupyter

If you don’t already have Jupyter:

# Using pip in your terminal
pip install notebook jupyterlab

🤝 Contributing

Contributions are welcome! If you’d like to add lessons, datasets, or exercises:

1. Fork the repo

2. Create a feature branch

3. Submit a pull request