Assistant Professor of Economics

University of Oklahoma

Research Affiliate

Institute for the Study of Labor (IZA)

**Social**

Email

Scholar

ORCID

RePEc

GitHub

Twitter

LinkedIn

**Contact:**

Department of Economics

University of Oklahoma

322 CCD1, 308 Cate Center Drive

Norman, OK 73072

- Introduction to Julia for economists: Slides from a short presentation that introduces Julia.
- QuantEcon's notebook gallery, which includes a few of my notebooks introducing data analysis and optimization in Julia.
- My Github repository, which introduces basic econometric models in Julia.

`summarize.m`: Mimics Stata's`summarize`command.`normalMLE.m`: Estimates normal linear regression with heteroskedastic errors by maximum likelihood.`applyRestr.m`: Allows for easy parameter restrictions in optimization problems (co-writen with Jared Ashworth).`clogit.m`: Estimates conditional logit regression by maximum likelihood (co-writen with Jared Ashworth).`ologit.m`: Estimates the ordered logit model by maximum likelihood.`EM algorithm example`: Code to generate data and estimate simple versions of the EM algorithm for estimation of models with discrete type-specific unobserved heterogeneity.

- Cape Town: a Beamer slide theme for LaTeX presentations.
- Poster: a LaTeX poster example.
- jole.bst: a BibTeX style file for formatting citations according to the style of the
*Journal of Labor Economics*. - CV template: a template for producing a CV in LaTeX (PDF output)

- Introduction to machine learning for social scientists: Slides from a short presentation that outlines what machine learning is and how social scientists can benefit from using its methods.
- Practical tips for machine learning practitioners, via Pedro Domingos.
- The Master Algorithm, written by Pedro Domingos.