This is a repository of the side projects I worked on or currently working on. Shoot me a line if you would like to see samples of my professional work. The projects are either written in R, Python, STATA, or Eviews. The goal of the projects is to uncover interesting behavioral economics and data science/statistical modelling answers. A typical project consist of conducting experiments, finding and cleaning data, analysis, visualization, and conclusion. Click on the projects to see snippets of analysis and code.
- Demonstration of behavioral economic experiments, game theory, and other economic games using oTree.
- Programmed in Python and oTree; environment in Heroku and PostgresSQL; analysis in R and STATA.
- Custom program to perform experiment on 500 students in a laboratory setting
- Research focus on information asymmetry reduction with behavioral economic methods
- Uses multi-unit Vickrey auction, reward elicitation, and information asymmetry treatments
- Keywords(Python, Heroku app, Behavioral Economics)
- Implemented latest methods of machine learning techniques and econometrics, and particularly for estimating causal effects.
- Most interested in cross-fold validation methods, LASSO, and ML in experiments.
- For empirical economists.
- Keywords(R, econometrics)
- Fitted power-law and log-normal distribution to Behavioral Econonomics users.
- Crawled Twitter to find 20000 random user and fitted power law distribution to users' friends count and followers count.
- Keywords(R, TwitteR, Power-law, Log-normal)
- Network graph of Facebook messages
- Keywords(R, network, igraph, facebook message)
