arXiv 27 Jul 2023 · Econometrics
arXiv:2307.15151 · PDF · DOI · OpenAlex · Extracted main text
We consider Wald type statistics designed for joint predictability and structural break testing based on the instrumentation method of Phillips and Magdalinos (2009). We show that under the assumption of nonstationary predictors: (i) the tests based on the OLS estimators converge to a nonstandard limiting distribution which depends on the nuisance coefficient of persistence; and (ii) the tests based on the IVX estimators can filter out the persistence under certain parameter restrictions due to the supremum functional. These results contribute to the literature of joint predictability and parameter instability testing by providing analytical tractable asymptotic theory when taking into account nonstationary regressors. We compare the finite-sample size and power performance of the Wald tests under both estimators via extensive Monte Carlo experiments. Critical values are computed using standard bootstrap inference methodologies. We illustrate the usefulness of the proposed framework to test for predictability under the presence of parameter instability by examining the stock market predictability puzzle for the US equity premium.
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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 | Kasparis, I., Andreou, E., and Phillips, P. C (2015) Nonparametric predictive regression | 1.000 | 6 | 4 | 100% |
| 2 | Gonzalo, J. and Pitarakis, J.-Y (2012) Regime-specific predictability in predictive regressions | 1.000 | 5 | 4 | 100% |
| 3 | Phillips, P. C. and Lee, J. H (2016) Robust econometric inference with mixed integrated and mildly explosive regressors | 1.000 | 5 | 3 | 100% |
| 4 | Andrews, D. W (1993) Tests for parameter instability and structural change with unknown change point | 0.950 | 14 | 7 | 86% |
| 5 | Phillips, P. C. and Lee, J. H (2013) Predictive regression under various degrees of persistence and robust long-horizon regression | 0.928 | 4 | 3 | 100% |
| 6 | Kostakis, A., Magdalinos, T., and Stamatogiannis, M. P (2015) Robust econometric inference for stock return predictability | 0.843 | 4 | 4 | 75% |
| 7 | Georgiev, I., Harvey, D. I., Leybourne, S. J., and Taylor, A. R (2018) Testing for parameter instability in predictive regression models | 0.843 | 4 | 3 | 75% |
| 8 | Hansen, B. E (2000) Testing for structural change in conditional models | 0.843 | 4 | 3 | 75% |
| 9 | Phillips, P. C. and Magdalinos, T (2009) Econometric inference in the vicinity of unity | 0.817 | 11 | 5 | 55% |
| 10 | Gonzalo, J. and Pitarakis, J.-Y (2017) Inferring the predictability induced by a persistent regressor in a predictive threshold model | 0.737 | 3 | 2 | 100% |
Showing the top 10 of 60 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Break-Point Date Estimation for Nonstationary Autoregressive and Predictive Regression Models | 0.874 | 7 | 2 |
| 2 | Limit Theory under Network Dependence and Nonstationarity | 0.585 | 3 | 1 |