High-Performance Computing

I am interested in high-performance computing applied to Economics. Particularly, I have spent time working on parallel and GPU computing applied to structural models.

Notes on Computational Methods for Economists:

(with Jesús Fernández-Villaverde and Pablo Guerrón-Quintana)

High-performance computing in Economics:

• High-performance computing in Economics
• Software engineering
• OS and basic utilities
• Concepts on programming languages
• Scientific computing languages
• Coding tools
• Programming paradigms
• The elements of programming style
• Data handling
• Web scraping
• Parallel programming

Perturbation:

• Perturbation methods I: basic results
• Perturbation methods II: general case
• Perturbation methods III: change of variables
• Perturbation methods IV: perturbing the value function
• Perturbation methods V: pruning

Other:

• Github repository for parallel computing examples on Matlab, Julia, R, Python, C++ (MPI and OpenMP), CUDA - life-cycle model
• Slides for package Rcpp presented at the Federal Reserve Bank of San Francisco - July, 2017

La Rama Ciudadana

During my spare time, I work on a project called La Rama Ciudadana, jointly with Rodrigo Azuero. We aim at contributing to national debates with relevant data and statistics through the use of scraping tools and data visualization.

Packages in R

I have developed two packages in R, joint with Rodrigo Azuero:

• gmapsdistance: This is a package that uses the Google Maps Distance Matrix API to compute the distance and travel time between multiple points. The distance is returned in meters and the time in seconds. Four different modes of transportation are allowed: "bicycling", "walking", "driving", "transit".

• Rtauchen: This package discretizes an AR(1) process following Tauchen (1986). A discrete Markov chain that approximates in the sense of weak convergence a continuous-valued univariate Autoregressive process of first order is generated. It is a popular method used in economics and in finance.

Presentations

• Graduate Student Seminar Series, FELS Policy Research Initiative, Philadelphia, PA - Nov. 2017
• George Washington University Student Research Conference in Economics, Washington D.C. - Apr. 2017
• 21st Annual LACEA Meeting, Medellín, Colombia - Nov. 2016

High-Performance Computing

I am interested in high-performance computing applied to Economics. Particularly, I have spent time working on parallel and GPU computing applied to structural models.

Notes on Computational Methods for Economists:

(with Jesús Fernández-Villaverde and Pablo Guerrón-Quintana)

High-performance computing in Economics:

• High-performance computing in Economics
• Software engineering
• OS and basic utilities
• Concepts on programming languages
• Scientific computing languages
• Coding tools
• Programming paradigms
• The elements of programming style
• Data handling
• Web scraping
• Parallel programming

Perturbation:

• Perturbation methods I: basic results
• Perturbation methods II: general case
• Perturbation methods III: change of variables
• Perturbation methods IV: perturbing the value function
• Perturbation methods V: pruning

Other:

• Github repository for parallel computing examples on Matlab, Julia, R, Python, C++ (MPI and OpenMP), CUDA - life-cycle model
• Slides for package Rcpp presented at the Federal Reserve Bank of San Francisco - July, 2017

La Rama Ciudadana

During my spare time, I work on a project called La Rama Ciudadana, jointly with Rodrigo Azuero. We aim at contributing to national debates with relevant data and statistics through the use of scraping tools and data visualization.

Packages in R

I have developed two packages in R, joint with Rodrigo Azuero:

• gmapsdistance: This is a package that uses the Google Maps Distance Matrix API to compute the distance and travel time between multiple points. The distance is returned in meters and the time in seconds. Four different modes of transportation are allowed: "bicycling", "walking", "driving", "transit".

• Rtauchen: This package discretizes an AR(1) process following Tauchen (1986). A discrete Markov chain that approximates in the sense of weak convergence a continuous-valued univariate Autoregressive process of first order is generated. It is a popular method used in economics and in finance.

Presentations

• Graduate Student Seminar Series, FELS Policy Research Initiative, Philadelphia, PA - Nov. 2017
• George Washington University Student Research Conference in Economics, Washington D.C. - Apr. 2017
• 21st Annual LACEA Meeting, Medellín, Colombia - Nov. 2016