cointsmall 1.0.4
- Bug fix: the critical values did not come from Trinh (2022). The
model “o” table was shifted by one regressor (the m = 1 row held the
Dickey-Fuller values of a single series), and the tables for one and two
breaks were not the published response surfaces. The 5% critical values
are now computed from the response surfaces in Table 13 of Trinh (2022),
for m = 1, 2, 3 regressors; they reproduce Table 1 of the paper.
- Bug fix: the p-value was extrapolated from these tables and could
exceed 1 (16.29 in one test case). Trinh (2022) publishes the 5%
quantile only, so
pvalue, cv01 and
cv10 are now NA, level must be 5,
and cointsmall_cv() stops for other levels or more than
three regressors.
- The author of the methodology is Jerome Trinh; the reference is
corrected, and the contributor entry in Authors@R, which named another
person and did not correspond to any contributed code, is removed.
- The ADF* statistic and break dates are unchanged; they agree with
the Stata command cointsmall (SSC) on the same data.
cointsmall 1.0.3
- Removed a DOI wrongly attached to the MacKinnon (2010) working
paper; the citation text is unchanged. No changes to code.
cointsmall 1.0.0
Features
cointsmall(): Main function for cointegration tests
with structural breaks in small samples
cointsmall_combined(): Combined testing procedure
evaluating all model specifications
cointsmall_cv(): Function to retrieve critical values
for different model configurations
Model Specifications
- Model “o”: No structural break (standard Engle-Granger test)
- Model “c”: Break in constant only (Gregory-Hansen style level
shift)
- Model “cs”: Break in constant and slope (regime change model)
Supported Options
- 0, 1, or 2 structural breaks
- Break date selection via minimum ADF statistic or minimum SSR
- Adjustable trimming parameter for break date search
- Automatic lag selection for ADF test using BIC
- Small-sample adjusted critical values via response surface
methodology
References
- Based on Trinh (2022) “Testing for cointegration with structural
changes in very small sample”