arXiv 1 Jun 2016 · Mathematics — Statistics Theory · publishedJournal of Econometrics (2018) · 13 citations (OpenAlex)
arXiv:1606.00092 · PDF · DOI · OpenAlex · Extracted main text
The issue addressed in this paper is that of testing for common breaks across or within equations of a multivariate system. Our framework is very general and allows integrated regressors and trends as well as stationary regressors. The null hypothesis is that breaks in different parameters occur at common locations and are separated by some positive fraction of the sample size unless they occur across different equations. Under the alternative hypothesis, the break dates across parameters are not the same and also need not be separated by a positive fraction of the sample size whether within or across equations. The test considered is the quasi-likelihood ratio test assuming normal errors, though as usual the limit distribution of the test remains valid with non-normal errors. Of independent interest, we provide results about the rate of convergence of the estimates when searching over all possible partitions subject only to the requirement that each regime contains at least as many observations as some positive fraction of the sample size, allowing break dates not separated by a positive fraction of the sample size across equations. Simulations show that the test has good finite sample properties. We also provide an application to issues related to level shifts and persistence for various measures of inflation to illustrate its usefulness.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Bai, J., Perron, P (1998) Estimating and testing linear models with multiple structural changes self | 1.000 | 6 | 3 | 100% |
| 2 | Bai, J (2000) Vector autoregressive models with structural changes in regression coefficients and in variance-covariance matrices | 0.956 | 8 | 4 | 88% |
| 3 | Bai, J., Lumsdaine, R. L., Stock, J. H (1998) Testing for and dating common breaks in multivariate time series | 0.941 | 12 | 5 | 83% |
| 4 | Qu, Z., Perron, P (2007) Estimating and testing structural changes in multivariate regressions self | 0.935 | 11 | 4 | 82% |
| 5 | Clark, T. E (2006) Disaggregate evidence on the persistence of consumer price inflation | 0.874 | 8 | 2 | 100% |
| 6 | Bai, J (1997) Estimation of a change point in multiple regression models | 0.644 | 2 | 2 | 100% |
| 7 | Eberhart, R., Kennedy, J (1995) A new optimizer using particle swarm theory | 0.644 | 2 | 2 | 100% |
| 8 | Hall, A. R., Han, S., Boldea, O (2012) Inference regarding multiple structural changes in linear models with endogenous regressors | 0.644 | 2 | 2 | 100% |
| 9 | Hansen, B. E (1992) Tests for parameter instability in regressions with I(1) processes | 0.644 | 2 | 2 | 100% |
| 10 | Kejriwal, M., Perron, P (2008) The limit distribution of the estimates in cointegrated regression models with multiple structural changes self | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 57 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Detecting Multiple Structural Breaks in Systems of Linear Regression Equations with Integrated and Stationary Regressors | 1.000 | 9 | 3 |
| 2 | Oracle Efficient Estimation of Structural Breaks in Cointegrating Regressions | 0.405 | 1 | 1 |