My name is Pedro H. Chaves Maia, and I work as a researcher at the Institute for Mobility and Social Development and as a lecturer at the EPGE Brazilian School of Economics and Finance.
My research agenda focuses on spatial economics. In specific, I work on the implications of urban accessibility and resilience for economic growth and the welfare of city residents. I leverage big data and GIS applications to assess spatially disaggregated infrastructure effects.
- Urban and Regional Economics
- Transport Economics
- Development Economics
- Environmental Economics
I mostly work using Python and Julia. It follows an overview of the packages and models I have either made or reproduced, and that may prove useful to others!
| Project | Language | Notes | Status |
|---|---|---|---|
| df-compress | Python | A Python package to compress pandas dataframes akin to Stata's compress command |
Testing |
| Model | Language | Notes | Status |
|---|---|---|---|
| Redding and Rossi-Hansberg (2017) | Julia | Replicates Redding and Rossi-Hansberg (2017) implementation of the Helpman (1998) model in Julia | Completed |
| Monte, Redding and Rossi-Hansberg (2018) | Julia | Replicates Seidel and Wickerath (2020) implementation of the Monte, Redding, and Rossi-Hansberg (2018) model in Julia | Completed |
| Ahfeldt et al. (2015) | Julia | Replicates the canonical QSE model from Ahlfeldt et al. (2015) in Julia | Ongoing |
