Sepideh Mosaferi, Mark S. Kaiser
arXiv 1 Nov 2021 · Econometrics · 1 citations (OpenAlex)
arXiv:2111.00972 · PDF · DOI · OpenAlex · Extracted main text
This article develops nonparametric cointegrating regression models with endogeneity and semi-long memory. We assume that semi-long memory is produced in the regressor process by tempering of random shock coefficients. The fundamental properties of long memory processes are thus retained in the regressor process. Nonparametric nonlinear cointegrating regressions with serially dependent errors and endogenous regressors driven by long memory innovations have been considered in Wang and Phillips (2016). That work also implemented a statistical specification test for testing whether the regression function follows a parametric form. The limit theory of test statistic involves the local time of fractional Brownian motion. The present paper modifies the test statistic to be suitable for the semi-long memory case. With this modification, the limit theory for the test involves the local time of the standard Brownian motion and is free of the unknown parameter d. Through simulation studies, we investigate the properties of nonparametric regression function estimation as well as test statistic. We also demonstrate the use of test statistic through actual data sets.
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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 | Wang, Q. and Phillips, P. C. B (2016) Nonparametric cointegrating regression with endogeneity and long memory | 0.874 | 21 | 5 | 67% |
| 2 | Wang, Q. and Phillips, P. C. B (2009) Asymptotic theory for local time density estimation and nonparametric cointegrating regression | 0.794 | 8 | 3 | 50% |
| 3 | Hardle, W. and Mammen, E (1993) Comparing nonparametric versus parametric regression fits | 0.737 | 3 | 2 | 100% |
| 4 | Sabzikar, F., McLeod, A. I. and Meerschaert, M. M (2019) Parameter estimation for ARTFIMA time series | 0.737 | 3 | 2 | 100% |
| 5 | Karlsen, H. A., Myklebust, T. and Tjstheim, D (2007) Nonparametric estimation in a nonlinear cointegration type model | 0.644 | 2 | 2 | 100% |
| 6 | Wang, Q. and Phillips, P. C. B (2009) Structural nonparametric cointegrating regression | 0.575 | 7 | 2 | 29% |
| 7 | Jeganathan, P (2004) Convergence of functionals of sums of r.v.s to local times of fractional stable motions | 0.511 | 2 | 2 | 50% |
| 8 | Sabzikar, F. and Surgailis, D (2018) Invariance principles for tempered fractionally integrated processes | 0.511 | 2 | 2 | 50% |
| 9 | Gao, J., King, M., Lu, Z. and Tjstheim, D (2009) Specification testing in nonlinear and nonstationary time series autoregression | 0.511 | 2 | 1 | 100% |
| 10 | Mosaferi, S., Kaiser, M. S. and Nordman, D. J (2024) Properties of test statistics for nonparametric cointegrating regression functions based on subsamples self | 0.511 | 2 | 1 | 100% |
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