Dennis Kristensen, Young Jun Lee
arXiv 10 Apr 2019 · Econometrics
arXiv:1904.05209 · PDF · Extracted main text
We develop a novel asymptotic theory for local polynomial extremum estimators of time-varying parameters in a broad class of nonlinear time series models. We show the proposed estimators are consistent and follow normal distributions in large samples under weak conditions. We also provide a precise characterisation of the leading bias term due to smoothing, which has not been done before. We demonstrate the usefulness of our general results by establishing primitive conditions for local (quasi-)maximum-likelihood estimators of time-varying models threshold autoregressions, ARCH models and Poisson autogressions with exogenous co--variates, to be normally distributed in large samples and characterise their leading biases. An empirical study of US corporate default counts demonstrates the applicability of the proposed local linear estimator for Poisson autoregression, shedding new light on the dynamic properties of US corporate defaults.
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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 | Bardet, J.-M., P. Doukhan, and O. Wintenberger (2022) Contrast estimation of time-varying infinite memory processes | 1.000 | 11 | 3 | 100% |
| 2 | Fan, J., N. E. Heckman, and M. P. Wand (1995) Local polynomial kernel regression for generalized linear models and quasi-likelihood functions | 1.000 | 7 | 3 | 100% |
| 3 | Agosto, A., G. Cavaliere, D. Kristensen, and A. Rahbek (2016) Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX) | 0.976 | 14 | 3 | 93% |
| 4 | Dahlhaus, R., S. Richter, and W. B. Wu (2019) Towards a general theory for nonlinear locally stationary processes | 0.950 | 14 | 4 | 86% |
| 5 | Dahlhaus, R. and S. Subba Rao (2006) Statistical inference for time-varying ARCH processes | 0.874 | 5 | 2 | 100% |
| 6 | Truquet, L (2019) Local stationarity and time-inhomogeneous markov chains | 0.811 | 4 | 2 | 100% |
| 7 | Truquet, L (2020) A perturbation analysis of markov chains models with time-varying parameters | 0.737 | 3 | 2 | 100% |
| 8 | Doukhan, P. and O. Wintenberger (2008) Weakly dependent chains with infinite memory | 0.693 | 6 | 3 | 33% |
| 9 | Vazquez-Abad, F. J. and H. J. Kushner (1992) Estimation of the derivative of a stationary measure with respect to a control parameter | 0.511 | 2 | 2 | 50% |
| 10 | Newey, W. K. and D. McFadden (1994) Large sample estimation and hypothesis testing | 0.511 | 2 | 2 | 50% |
Showing the top 10 of 31 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Indirect Inference for Locally Stationary Models | 0.811 | 4 | 2 |
| 2 | A new GARCH model with a deterministic time-varying intercept | 0.511 | 2 | 2 |
| 3 | Testing parametric additive time-varying GARCH models | 0.405 | 1 | 1 |