Introduction

On this website we collect notes on how to use R/C++ programming to solve quantitative economic models with heterogeneous agents. The ultimate aim is to produce a book with all the content we gather - we encourage contributions from others!

We think the content presented here could be useful for economics grad students and researchers who want to solve computationally intensive economics models. We don't target any particular subfield of economics (like finance, or macro), but we show by way of fully worked examples how one can combine R and C++ or fortran to compute large scale problems.

Many economists seem to think that computationally intensive is another way of saying use fortran. Whilst our agenda is not to prove anyone wrong here, we do want to illustrate that there are serious alternatives to using plain fortran. We will try to flesh out the pros and cons of each approach.

The main motivation for this book lies in the fact that we think there is a shortage of books that help implementing solutions for computational economics. Beware that this book is not a substitute to any of the excellent existing contributions on computational economics, like Ken Judd's book, Adda and Cooper or Fackler and Miranda, to name but a few. However, we feel that there is space for a more hands on approach, with actual working computer code instead of pseudo code illustrations. Economics students and researchers spend a lot of time making things work, many times on problems that others have solved before. We want to make a small contribution to alleviate this inefficiency.

A similar but extremely accomplished book is Quantitative Economics by John Stachurski and Thomas J. Sargent. Their book uses the python language which we also really like. We hope that the notes we present here can complement the content of their book with applications focused on the use of R/C++.

Finally, we would like to refer to several other R-related publications which may be useful:

Thanks for stopping by, Thibaut & Florian.