Code

psymonitor

With: Peter C.B. Phillips and Shuping Shi

psymonitor provides an accessible implementation of the popular real-time monitoring strategy proposed by Phillips, Shi and Yu (2015), along with a new bootstrap procedure designed to mitigate the potential impact of heteroskedasticity and to effect family-wise size control in recursive testing algorithms (Phillips and Shi, forthcoming). This methodology has been shown effective for bubble and crisis detection (PSY, 2015; Phillips and Shi, 2017) and is now widely used by academic researchers, central bank economists, and fiscal regulators.

[GitHub]

rtadfr

The R package rtadfr (Right Tailed ADF Tests with R) facilitates the Phillips, Wu, and Yu (2011) and Phillips, Shi, and Yu (2015) right tailed unit root tests for exuberance behavior. This package is planned to be the R equivalent of the rtadf EViews add-in (Caspi, 2017).

[GitHub]

experimentdatar

With: Susan Athey

The experimentdatar data package contains publicly available datasets that were used in Susan Athey and Guido Imbens’ course “Machine Learning and Econometrics” (AEA continuing Education, 2018). The datasets are conveniently packed for R users. 

[GitHub]

Rtadf

Rtadf is an EViews add-in that implements econometric tests for detecting asset price bubbles (Phillips, Wu, and Yu, 2011; Phillips, Shi, and Yu, 2015), based on right-tailed variations of the augmented Dickey-Fuller unit root test. It allows users to perform four types of tests (ADF, rolling ADF, sup ADF, and generalized sup ADF) to detect explosive behavior in time series data that may indicate bubbles. 

[Source code]