As part of my research, I contribute to the development of packages for statistical software and compile datasets.

## Software

• The R package glmhdfe implements a fast estimation procedure of generalized linear models with high dimensional fixed effects. The package makes use of a convenient property of some combinations of error term distributions and link functions, where the fixed effects have — conditional on all other estimated parameters — an explicit solution.

Install from Github via the remotes package:


install.packages("remotes")
remotes::install_github("julianhinz/R_glmhdfe")


A Stata implementation is coming soon. For more details and usage examples check out the R_glmhdfe Github repository and the technical note.

• Please cite:
Separating the Wheat from the Chaff: Fast Estimation of GLMs with High-Dimensional Fixed Effects, mimeo. European University Institute, March 2019.
• gravity.distances
• The R package gravity.distances provides distances between geographic entities — such as countries, US states or Canadian provinces — that are consistent with the gravity equation in international economics.

To install the package in R, simply run the following commands:


install.packages("remotes")
remotes::install_github("julianhinz/gravity.distances")


For more details and usage examples check out the respective Github repositories:

• Please cite:
The view from space: Theory-based time-varying distances in the gravity model, Kiel Working Paper, 2059. Kiel Institute for the World Economy, Kiel, 2017-07-29.

## Datasets

• Gravity Distances data
• Time-varying aggregate distances between 193 countries computed using nighttime lights data as weights, for the years 1992–2012.

• Countries to countries (Version 1.0): rds, csv, dta

For more detailed data, including θs ranging from -2 to +1 and distances between other geographic entities (currently US states, Canadian provinces), the use of the R package gravity.distances is highly recommended.

• Please cite:
The view from space: Theory-based time-varying distances in the gravity model, Kiel Working Paper, 2059. Kiel Institute for the World Economy, Kiel, 2017-07-29.