arXiv 8 Nov 2022 · Econometrics · publishedJournal of Econometrics (2025) · 2 citations (OpenAlex)
arXiv:2211.04027 · PDF · DOI · OpenAlex · Extracted main text
This paper develops valid bootstrap inference methods for the dynamic short panel threshold regression. We demonstrate that the standard nonparametric bootstrap is inconsistent for the first-differenced generalized method of moments (GMM) estimator. The inconsistency arises from an $n^{1/4}$-consistent non-normal asymptotic distribution of the threshold estimator when the true parameter lies in the continuity region of the parameter space, which stems from the rank deficiency of the approximate Jacobian of the sample moment conditions on the continuity region. To address this, we propose a grid bootstrap to construct confidence intervals for the threshold and a residual bootstrap to construct confidence intervals for the coefficients. They are shown to be valid regardless of the model's continuity. Moreover, we establish a uniform validity for the grid bootstrap. A set of Monte Carlo experiments demonstrates that the proposed bootstraps improve upon the standard nonparametric bootstrap. An empirical application to a firm investment model illustrates our methods.
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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 | Hansen, B. E (1999) Threshold effects in non-dynamic panels: Estimation, testing, and inference | 1.000 | 7 | 3 | 100% |
| 2 | Seo, M. H. and Shin, Y (2016) Dynamic Panels With Threshold Effect and Endogeneity self | 0.897 | 18 | 7 | 72% |
| 3 | Kim, S., Kim, Y. J., and Seo, M. H (2019) Estimation of Dynamic Panel Threshold Model Using Stata self | 0.843 | 5 | 4 | 60% |
| 4 | Dovonon, P. and Hall, A. R (2018) The asymptotic properties of gmm and indirect inference under second-order identification | 0.811 | 4 | 2 | 100% |
| 5 | Dovonon, P. and Goncalves, S (2017) Bootstrapping the GMM overidentification test under first-order underidentification | 0.737 | 3 | 2 | 100% |
| 6 | Fazzari, S. M., Hubbard, R. G., Petersen, B. C., Blinder, A. S., and… (1988) Financing Constraints and Corporate Investment | 0.644 | 2 | 2 | 100% |
| 7 | Hall, P. and Horowitz, J. L (1996) Bootstrap Critical Values for Tests Based on Generalized-Method-of-Moments Estimators | 0.644 | 2 | 2 | 100% |
| 8 | Hansen, B. E (1999) The Grid Bootstrap and the Autoregressive Model | 0.644 | 2 | 2 | 100% |
| 9 | Hidalgo, J., Lee, J., and Seo, M. H (2019) Robust Inference for Threshold Regression Models self | 0.644 | 2 | 2 | 100% |
| 10 | Miao, K., Su, L., and Wang, W (2020) Panel threshold regressions with latent group structures | 0.644 | 2 | 2 | 100% |
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