Transportation Methods for Econometrics (TraME)

TraME (Transportation Methods for Econometrics) is a templated C++ library for solving problems of equilibrium computation and estimation in consumer demand and matching frameworks via the Mass Transportation Approach.

Features

Flexible, templated C++11 library
Built on the Armadillo C++ linear algebra library
Nonlinear optimization using OptimLib
Can link with Gurobi or GLPK
R interface: TraME-Rcpp

Several popular random utility specifications, as well as models with transferable, non-transferable, and imperfectly transferable utility
Numerous equilibrium solvers, including the iterative proportional fitting procedure (IPFP) and the deferred acceptance algorithm
Maximum likelihood- and moment matching-based estimation

Authors:

TraME Team: Alfred Galichon and Keith O'Hara
Contributors: Yifei Sun, Simon Weber

Download and Installation

The source code is available on GitHub.
To use the linear programming features TraME requires an installation of Gurobi or GLPK.

The library can be installed on Unix-alike systems via the standard ./configure && make method:

# clone TraME into the current directory
git clone https://github.com/TraME-Project/TraME ./trame
# build and install
cd ./trame
./configure -i "/usr/local" -p
make
make install

The last line will install TraME to /usr/local.

Configuration options: (see ./configure -h)

Primary

-h print help
-i install path; default: the build directory
-l specify a linear programming library to use;
for example -l glpk or -l gurobi
-m specify the BLAS and Lapack libraries to link against;
examples: -m "-lopenblas" or -m "-framework Accelerate"
-o compiler optimization options;
default: -O3 -march=native -ffp-contract=fast -flto -DARMA_NO_DEBUG
-p enable OpenMP parallelization features (recommended)

Secondary

-c a coverage build (used with Codecov)
-d a 'development' build
-g a debugging build (optimization flags set to -O0 -g)

Armadillo

TraME is built on the Armadillo C++ linear algebra library. The configure script will search for Armadillo files in the usual places: /usr/include, /usr/local/include, /opt/include, /opt/local/include. If the Armadillo header files are installed elsewhere, set the following environment variable before running configure:

export ARMA_INCLUDE_PATH=/path/to/armadillo

Otherwise the build script will download the required files from the Armadillo GitLab repository.