arXiv 10 Oct 2021 · Econometrics
arXiv:2110.04847 · PDF · DOI · OpenAlex · Extracted main text
We propose consistent nonparametric tests of conditional independence for time series data. Our methods are motivated from the difference between joint conditional cumulative distribution function (CDF) and the product of conditional CDFs. The difference is transformed into a proper conditional moment restriction (CMR), which forms the basis for our testing procedure. Our test statistics are then constructed using the integrated moment restrictions that are equivalent to the CMR. We establish the asymptotic behavior of the test statistics under the null, the alternative, and the sequence of local alternatives converging to conditional independence at the parametric rate. Our tests are implemented with the assistance of a multiplier bootstrap. Monte Carlo simulations are conducted to evaluate the finite sample performance of the proposed tests. We apply our tests to examine the predictability of equity risk premium using variance risk premium for different horizons and find that there exist various degrees of nonlinear predictability at mid-run and long-run horizons.
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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 | Delgado, M. A., W. G. Manteiga, et al (2001) Significance testing in nonparametric regression based on the bootstrap | 1.000 | 5 | 3 | 100% |
| 2 | Su, L. and H. L. White (2012) Conditional independence specification testing for dependent processes with local polynomial quantile regression | 0.843 | 5 | 4 | 60% |
| 3 | Bouezmarni, T., J. V. Rombouts, and A. Taamouti (2012) Nonparametric copula-based test for conditional independence with applications to granger causality | 0.843 | 3 | 3 | 100% |
| 4 | Su, L. and H. White (2007) A consistent characteristic function-based test for conditional independence | 0.843 | 3 | 3 | 100% |
| 5 | Su, L. and H. White (2008) A nonparametric hellinger metric test for conditional independence | 0.843 | 3 | 3 | 100% |
| 6 | Wang, X., Y. Hong, et al (2018) Characteristic function based testing for conditional independence: A nonparametric regression approach | 0.843 | 3 | 3 | 100% |
| 7 | Rosenblatt, M (1975) A quadratic measure of deviation of two-dimensional density estimates and a test of independence | 0.644 | 2 | 2 | 100% |
| 8 | Stinchcombe, M. B. and H. White (1998) Consistent specification testing with nuisance parameters present only under the alternative | 0.511 | 2 | 1 | 100% |
| 9 | Bakirov, N. K., M. L. Rizzo, and G. J. Székely (2006) A multivariate nonparametric test of independence | 0.405 | 1 | 1 | 100% |
| 10 | Blum, J. R., J. Kiefer, and M. Rosenblatt (1961) Distribution free tests of independence based on the sample distribution function | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 38 scored citations.