BAIPERRON Procedure (revised)

[TomDoan]

Attached is a revised procedure file for the Bai-Perron structural break analysis. This has been substantially updated, and now includes a table with test statistics for different numbers of breaks (TESTS option), and a full table of the final regression (PRINT option). This now includes 95% confidence interval on the break dates. Note that the CI's on the break dates can be very sensitive to the methods used for calculating long-run variances, particularly since partitions can be fairly (or even very) short.

Note that this requires RATS 7.3 or later.

In May 2011, we corrected an error in the calculation of the BIC which could affect close decisions in the number of breaks.

baiperron.src

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@BaiPerron( options ) depvar start end
# list of regressors

Options: MINSPAN = shortest distance between two breaks [number of regressors]
MAXBREAKS = maximum breaks allowed [2]
NFIX=number of regressors which are fixed over time[0]
ITERS=maximum number of iterations[20]. (Matters only if NFIX>0)
[PRINT]/NOPRINT Controls printing of the final regression and breakpoints
TESTS/[NOTESTS] Controls printing of the table of BIC, LWZ and F tests
for choosing the number of breaks.

Supplementary Card: list of regressors with the fixed regressors (if any) listed first

For an example, see http://www.estima.com/forum/viewtopic.php?f=30&t=501.

[irfansystem]

While replicating the results, I observed that the standard errors related to the coefficients are not same as mentioned by Bai Perron (2003)...plz see table 1 and section 3....., what could be the cause. Where as using the same data on R (structural break package)...surprisingly I am having the exact results as indicated by Bai Perron.
Second, could we produce the graphs of BIC as on page 3 of the same paper.

[TomDoan]

While replicating the results, I observed that the standard errors related to the coefficients are not same as mentioned by Bai Perron (2003)...plz see table 1 and section 3....., what could be the cause. Where as using the same data on R (structural break package)...surprisingly I am having the exact results as indicated by Bai Perron.
Second, could we produce the graphs of BIC as on page 3 of the same paper.

The standard errors in Bai-Perron are computed using HAC. I'm not convinced that that's a good idea since the partitions can be rather short, making accurate estimation of HAC standard errors rather unlikely.

[Aktar]

Hello,

Is the procedure shaped for testing no break versus one break?

i find a supF(1|0) very high (1640) for a sample of 444 obs. (pure structural change model). Given the number of observations and the shape of my serie (REER between 1975 to 2010), a high probability of rejected the null (zero break) should be normal... but 1600 is maybe too high no? (even if critical value is near to 30).

Thank you very much

[TomDoan]

It can be used for 0 vs 1, though @APBREAKTEST would give you greater information on that. Bai-Perron is a more efficient way to search for two or more breaks---at one break, it's basically the same calculation as in @APBREAKTEST and similar procedures.

Regarding the observed statistic, that's high but certainly not unreasonable. However, a break statistic that large would probably be associated with an obvious (to the eye) break in the data.