Get Julia-ready!

What are Julia and Jupyter?

Econometrics is all about using data to answer real-world economic questions. To do this well, we need to be able to work with data—loading it, cleaning it, visualising it, and running statistical analyses on it.

While you could do some of this in spreadsheets, modern econometric work involves datasets and methods that quickly outgrow what Excel can handle. That’s where coding comes in. We’ll be doing all our coding in Julia. Don’t worry if you’ve never coded before, we’ll teach everything from scratch.

What is Julia!? Well, Julia’s awesome! Enough said. The way we interact with Julia is through so-called Jupyter notebooks. Our friends from quantecon.org explain:

What are Jupyter notebooks?

Jupyter notebooks are one of the many possible ways to interact with Julia and the scientific libraries.

They use a browser-based interface to Julia with

The ability to write and execute Julia commands.
Formatted output in the browser, including tables, figures, animation, etc.
The option to mix in formatted text and mathematical expressions.

Because of these features, Jupyter is now a major player in the scientific computing ecosystem.

(referenced from here) where I swapped out all instances of “Python” with “Julia”.

I hear you ask: Sounds awesome, but how in the world do I get started with Jupyter!?

We strongly recommend that you use Jupyter from inside VS Code! What is VS Code? VS Code is a free, open-source code editor.

This guide will walk you through installing Julia and setting up Visual Studio Code (VSCode) as your development environment for this course. You’ll learn how to work with Jupyter notebooks in VSCode, which is how you’ll complete all labs and assignments.

Installing Julia

Step 1: Download Julia

Go to the official Julia downloads page: https://julialang.org/downloads/
Download the Current stable release for your operating system
- We recommend Julia 1.10 or newer (as of 2025, Julia 1.12 is current)
- Choose the appropriate installer for your system:
  - Windows: Download the 64-bit installer (.exe file)
  - macOS: Download the .dmg file (Intel or Apple Silicon depending on your Mac)

Note

If you’re unsure whether your system is 32-bit or 64-bit, it’s almost certainly 64-bit if your computer was made after 2010.

Linux users: Download the generic binary and follow the standard Julia installation procedure for your distribution.

Step 2: Install Julia

Windows

Run the downloaded .exe installer
Follow the installation wizard
Important: Check the box “Add Julia to PATH” during installation
Complete the installation

macOS

Open the downloaded .dmg file
Drag the Julia app to your Applications folder

To add Julia to your PATH:

Open Terminal

Run this command:

sudo mkdir -p /usr/local/bin
sudo ln -s /Applications/Julia-1.12.app/Contents/Resources/julia/bin/julia /usr/local/bin/julia

Enter your password when prompted

Note

Replace Julia-1.12 with your actual Julia version number.

Step 3: Verify Installation

Open a terminal (Command Prompt on Windows, Terminal on macOS/Linux) and type:

julia --version

You should see output like:

julia version 1.12.0

If you see this, Julia is successfully installed!

Setting Up Visual Studio Code

Step 1: Install VSCode

Download VSCode from: https://code.visualstudio.com/
Install it following the standard process for your operating system

Step 2: Install Required Extensions

Open VSCode
Click on the Extensions icon in the left sidebar (or press Ctrl+Shift+X / Cmd+Shift+X)
Install these two extensions:
1. Julia (by julialang) - The official Julia language extension
2. Jupyter (by Microsoft) - For notebook support

Step 3: Configure the Julia Extension

The extension should automatically detect your Julia installation. To verify:

Open VSCode settings (Ctrl+, / Cmd+,)
Search for “julia executable”
Ensure “Julia: Executable Path” points to your Julia binary
- Usually auto-detected
- If not, set it manually:
  - Windows: C:\Users\YourName\AppData\Local\Programs\Julia-1.12.0\bin\julia.exe
  - macOS: /Applications/Julia-1.12.app/Contents/Resources/julia/bin/julia

Step 4: Working with Jupyter Notebooks in VSCode

This is the primary way you’ll work in this course:

Open or create a notebook:
- File → New File → Jupyter Notebook
- Or open an existing .ipynb file from the course materials
- Save with .ipynb extension
Select the Julia kernel:
- Click “Select Kernel” in the top-right corner of the notebook
- Choose “Julia 1.12” (or your installed version)
- VSCode will start a Julia session in the background
Working with cells:
- Add a code cell: Click “+ Code” button or press B (when not editing)
- Add a markdown cell: Click “+ Markdown” or press M (when not editing)
- Run a cell: Click the play button (▶) or press Shift+Enter
- Run and move to next: Shift+Enter
- Run without moving: Ctrl+Enter / Cmd+Enter

That’s it! You’re ready to start working with Julia notebooks.

Installing Julia Packages

Julia has a built-in package manager that makes it easy to install and manage packages. This guide covers the essential commands you’ll need for this course.

Basic Package Installation

The easiest way to install packages is through Julia’s package manager.

Start Julia by typing julia in your terminal
Press the ] key to enter package mode (the prompt will change from julia> to pkg>)
Type add PackageName to install a package
Press backspace to return to normal Julia mode

Example:

julia> ]  # Press ] to enter pkg mode

(@v1.12) pkg> add Distributions
(@v1.12) pkg> add Plots
(@v1.12) pkg> add Optim

# Press backspace to exit pkg mode
julia>

Required Packages for This Course

For EMET8014, you’ll need the following packages:

Core Packages

pkg> add Distributions      # Statistical distributions
pkg> add Plots              # Data visualization
pkg> add StatsPlots         # Statistical plotting extensions
pkg> add Optim              # Optimization algorithms
pkg> add Roots              # Root finding
pkg> add Downloads          # Downloading files
pkg> add LinearAlgebra      # Linear algebra (built-in, usually pre-installed)
pkg> add Statistics         # Basic statistics (built-in, usually pre-installed)
pkg> add DelimitedFiles     # Reading CSV files (built-in)
pkg> add Random             # Random number generation (built-in)

Install them all at once like so:

pkg> add Distributions Plots StatsPlots Optim Roots

Note

The built-in packages (Downloads, LinearAlgebra, Statistics, DelimitedFiles, Random) are part of Julia’s standard library and typically don’t need explicit installation. However, if you encounter issues, you can still use pkg> add ... to ensure they’re available.

Using Packages

After installation, you need to load packages before using them in your code:

using Distributions
using Plots
using LinearAlgebra

The first time you use a package in a Julia session, it will take a moment to compile. Subsequent uses in the same session will be faster.

Working with Jupyter Notebooks

If you’re using Jupyter notebooks (recommended for this course), you can install packages directly in a notebook cell:

using Pkg
Pkg.add("Distributions")

Or use package mode by starting a cell with ]:

] add Distributions

Warning

When using package mode in Jupyter, you may need to restart the kernel after installing new packages for them to be available.

Note

There are other ways to run Julia and Jupyter notebooks that we won’t cover here, including:

Google Colab – free cloud-based Jupyter notebooks (limited Julia support, requires setup)
Anaconda – popular Python distribution that includes Jupyter (requires IJulia package for Julia kernel)
Binder – launches Jupyter notebooks directly from a GitHub repository
GitHub Codespaces – a full development environment in the cloud
JupyterHub – often used by universities to provide shared Jupyter servers
JupyterLab – a more advanced interface (included with Anaconda)

Feel free to explore these if you’re curious, but VSCode will serve you well for this course.