Resources for empirical economics in Julia

I am currently learning Julia in a graduate course. I have some previous experience with R and Stata so I already have some needs that this course does not seem to cover. Here is my collection of potentially useful Julia tools for empirical economists. This post is a reference for myself but it could be potentially useful to others. It is a living document: I will edit it when I find better resources. Feel free to suggest more resources in the comment section.

Introductions to Julia

Here is an introductory example to install Julia and get working with data quickly. Another relatively comprehensive tutorial shows more that can be done with Julia. I am using Juno in Atom at the moment.

Empirical tools

1. Preparing data

A tutorial for playing with dataframes, including RegExp and renaming things. Another data munging tutorial, with extensive treatment of NA values. 

Since in R, I have trouble working with large data (my RAM is probably not enough and RStudio crashes when I work with large datasets). 

2. Analysis

I was happy to find a linear regression workflow tutorial in Julia with a machine learning perspective, but seems accessible to a labor economist. 

Logistic regression in Julia (tensorflowjulia) is a tutorial with heavy machine learning tone which seems quite complex. Logistic regression in Julia (geeks for geeks) is another tutorial which looks a bit simpler.

I would really like to find a FE logit in Julia as I was hoping to speed up some calculations from Stata (comparisons of Julia with R and Stata suggests it could run much faster in most cases). However, since the language is only existing since 2009, it seems that it is lacking in niche econometric packages. 

Generalized FE in Julia.

3. Generating Latex output

Linear fixed effect models and GLM can be exported to latex tables using RegressionTables. Other tables can be exported using TexTables. some community examples can be found here. 

Latexify turns Julia expression into latex code! 

Gadfly is useful for visualisation. PGFPlotsX claims to be great with saving to tex, pdf, svg, and png, also showing results in Juno, VSCode-julia or Jupyter. Here is a comparison of three major visualization libraries in Julia. 

Theory 

Playing with job search models in Julia. The website includes more macroeconomics goodness but for my purposes the search models seem the most immediately useful.