EViews 8 Multiple Breakpoint (Bai-Perron) Testing

12/20/13Home Products EViews 8 Multiple Breakpoint (Bai-Perron) Testing Pricing Downloads A dd-ins Registration Learning Resources Forums A bout/Contact Estimation Forecasting Statistical Analysis Graphics Data Management Simulation Multiple Breakpoint Testing in EViews 8 Tests for parameter instability and structural change in regression models have been an important part of applied econometric work dating back to C how (1960), who tested for regime change at a priori known dates using an F-statistic. To relax the requirement that the candidate breakdate be known, Quandt (1960) modified the C how framework to consider the F-statistic with the largest value over all possible breakdates. Andrews (1993) and Andrews and Ploberger (1994) derived the limiting distribution of the Quandt and related test statistics. More recently, Bai (1997) and Bai and Perron (1998, 2003a) provide theoretical and computational results that further extend the Quandt-Andrews framework by allowing for multiple unknown breakpoints. Breakpoint Testing Examples Least Squares Example Video Example Sequential Bai-Perron Video Example Global Bai-Perron L Breaks vs. None Video Example Global Inf ormation Criteria Video Example EViews 8 introduces these multiple breakpoint tests. Below are some examples of performing the tests in EViews. Note that these tests are closely related to breakpoint regression. Least Squares Example To illustrate the use of these tools in practice, we consider a simple model of the U.S. ex-post real interest rate from Garcia and Perron (1996) that is used as an example by Bai and Perron (2003 “Computation and Analysis of Multiple Structural Change Models,” Journal of Applied Econometrics, 6, 72–78.). The data, which consist of observations for the three-month treasury rate deflated by the C PI for the period 1961q1–1983q3, are provided in the series RATES in the workfile realrate.wf1. The regression model consists of a constant regressor, and allows for serial correlation that differs across regimes through the use of HAC covariance estimation. We allow up to 5 breaks in the model, and employ a trimming percentage of 15%. Since there are 103 observations in the sample, the trimming value implies that regimes are restricted to have at least 15 observations. Following Bai and Perron (2003), we begin by estimating the equation specification using least squares. Our equation specification consists of the dependent variable and a single (constant) regressor, so we enter rates c in the specification dialog. View a video example of this least squares example. www.eviews.com/EViews8/ev8ecmbreak_n.html 1/5 select View/Stability Diagnostics/ Multiple Breakpoint Test. We consider examples for three different approaches for multiple breakpoint testing with this equation. The estimation results should be as depicted below: To construct multiple breakpoint tests for this equation. we specify a quadratic spectral kernel based HAC covariance estimation using prewhitened residuals..html 2/5 . L) instructs EViews to perform sequential testing of l+1 versus l breaks using the methods outlined by Bai (1997) and Bai and Perron (1998). clicking on the HAC options button and filling out the dialog as shown: C lick on OK to accept the HAC settings. The kernel bandwith is determined automatically using the Andrews AR(1) method..eviews. from the equation menu.com/EViews8/ev8ecmbreak_n.12/20/13 EViews 8 Multiple Breakpoint (Bai-Perron) Testing Since we wish to allow for serial correlation in the errors. Sequential Bai-Perron The default Method setting (Sequential L+1 breaks vs. www. and then on OK to estimate the equation. The covariance options may be specified in the Equation Estimation dialog by selecting the Options tab. We do.12/20/13 EViews 8 Multiple Breakpoint (Bai-Perron) Testing View a video tutorial of the Bai-Perron Sequential example. 2. In this case. 1. The sequential test results indicate that there are three breakpoints: we reject the nulls of 0. breakpoint variables.05 significance level for the sequential testing. None To perform the Bai-Perron tests of l globally optimized breaks against the null of no structural breaks. C lick on OK to accept the test specification and display the test results. Global Bai-Perron L Breaks vs. Note that the test employs the same HAC covariance settings used in the original equation but assume regime specific error distributions: The middle section of the table presents the actual sequential test results: EViews displays the F-statistic.com/EViews8/ev8ecmbreak_n. We will leave these options at their default settings. however. and use the 0. There is a single regressor “C ” which we require to be in the list of breaking variables.html 3/5 .eviews. along with the corresponding UDmax and WDmax tests. The top portion of the dialog shows the test settings. since we only have the single. simply call up the dialog and www. along with the F-statistic scaled by the number of varying regressors (which is the same in this case. select the Allow error distributions to differ across breaks checkbox to allow for error heterogeneity. Again bear in mind that the results follow the EViews convention in defining breakdates to be the first date of the subsequent regime. employ a trimming percentage of 15%. but the test of 4 versus 3 breakpoints does not reject the null. varying regressor). and 2 breakpoints in favor of the alternatives of 1. The bottom portion of the output shows the estimated breakdates: EViews displays both the breakdates obtained from the original sequential procedure. and the Bai-Perron critical value for the scaled statistic. the dates do not change. including the test method. test options. By default. and 3 breakpoints. and those obtained following the repartition procedure. the tests allow for a maximum number of 5 breaks. and method of computing test covariances. which shows the test settings. www. The remaining lines show the individual test statistics (original. The top portion of the output. In both cases. weighted) along with the critical values for the scaled statistics. In each case. scaled. the maximized value clearly exceeds the critical value. the statistics far exceed the critical value so that we reject the null of no breaks.eviews.html 4/5 .” The middle portion of the output contains the test results: The first four lines summarize the results for different approaches to determining the number of breaks. We again leave the remaining settings at their default values with the exception of the Allow error distributions to differ across breaks checkbox which is selected. The only difference is a line identifying the test method as being “Bai-Perron tests of 1 to M globally determined breaks.12/20/13 EViews 8 Multiple Breakpoint (Bai-Perron) Testing change the Method drop-down to Global L breaks vs. The bottom of the portion shows the global optimizers for the breakpoints for each number of breaks: Note that the three-break global optimizers are the same as those obtained in the sequential testing example. C lick on OK to perform the test. The “Sequential” result is obtained by performing tests from 1 to the maximum number until we cannot reject the null. The maximized statistics both indicate the presence of a single break. The last two lines of output show the test results for double maximum statistics. the “Significant” result chooses the largest statistically significant breakpoint. This equivalence will not hold in general. The UDmax and WDmax results show the number of breakpoints as determined by application of the unweighted and weighted maximized statistics. is almost identical to the output for the previous example. so that we reject the null of no breaks in favor of the alternative of a single break. the multiple breakpoint test indicates that there are 5 breaks. Note that the values corresponding to the UDmax and WDmax statistics are shaded for easy identification. In both cases.com/EViews8/ev8ecmbreak_n. none : View a video tutorial of the Bai-Perron Global L Breaks test. and the values of the information criteria. Please include your serial number with all email correspondence. All Rights Reserved. © 2013 IHS Global Inc. see our About page. For additional contact information. the number of estimated coefficients. The remainder of the output shows.com.html 5/5 . for each break. C lick on OK to construct the table of results. www. Here we see the dialog when we select Global information criteria in the Method dropdown menu. we consider using information criteria to select the number of breaks.eviews. The top and bottom portions of the output are similar to the results seen previously so we focus only on the test summaries themselves: View a video tutorial of the Global Information Critera breakpoint test. For technical support please email [email protected]/EViews8/ev8ecmbreak_n. Note that there are no options for computing the coefficient covariances since this method does not require their calculation. The two summary rows show that both the Schwarz and the LWZ information criteria select 2 breaks. the optimized sum-of-squared residuals and likelihood.12/20/13 EViews 8 Multiple Breakpoint (Bai-Perron) Testing Global Information Criteria Lastly.com. The minimized Schwarz and LWZ values are shaded for easy identification. For sales information please email sales@eviews.