- A short introduction to Monte Carlo simulations using both R and Stata can be found here
- A Monte Carlo simulation of the Central Limit Theorem, as well as autocorrelation: Monte Carlo 1 (In Stata), Monte Carlo 1 (In R)
- Stata: A Monte Carlo simulation of "breaking" an instrumental variable approach: Monte Carlo 2
- Stata: A Monte Carlo simulation of the performance of the Zivot-Andrews unit root test under structural breaks: Monte Carlo 3
- Stata: Investigating the performance of a variety of panel unit root tests: Monte Carlo 4
- Some short code for canned bootstrap and jack-knife procedures in Stata (includes Monte Carlo simulations): Bootstrap, Jack-knife, Monte Carlo (In Stata)

- dynamac: Dynamic simulation and testing of single-equation autoregressive distributed lag (ARDL) models in R and Stata With Soren Jordan.

- dynsimpie: A Stata command to examine dynamic compositional dependent variables. With Amanda Rutherford and Guy D. Whitten. See also the corresponding Stata Journal article.

- Replication files for: Funk, Kendall D. and Andrew Q. Philips. 2018. "Representative budgeting: Women mayors and the composition of spending in local governments." Political Research Quarterly: 1-15.
- Replication files for: Philips, Andrew Q. 2018. "Have your cake and eat it too? Cointegration and dynamic inference from autoregressive distributed lag models." American Journal of Political Science: 62(1): 230-244.
- Replication files for: Lipsmeyer, Christine S., Andrew Q. Philips, Amanda Rutherford, and Guy D. Whitten. 2017. "Comparing dynamic pies: A strategy for modeling compositional variables in time and space." Political Science Research and Methods: 1-18.
- Replication files for: Philips, Andrew Q. 2016. "Seeing the forest through the trees: A meta-analysis of political budget cycles." Public Choice 168(3): 313-341.
- Replication files for: Philips, Andrew Q., Amanda Rutherford, and Guy D. Whitten. 2016. "Dynamic pie: A strategy for modeling trade-offs in compositional variables over time." American Journal of Political Science 60(1):268-283.