Mario P. Rothfelder, Otilia Boldea
arXiv 20 Jul 2022 · Econometrics · 3 citations (OpenAlex)
arXiv:2207.10076 · PDF · DOI · OpenAlex · Extracted main text
We show by simulation that the test for an unknown threshold in models with endogenous regressors - proposed in Caner and Hansen (2004) - can exhibit severe size distortions both in small and in moderately large samples, pertinent to empirical applications. We propose three new tests that rectify these size distortions. The first test is based on GMM estimators. The other two are based on unconventional 2SLS estimators, that use additional information about the linearity (or lack of linearity) of the first stage. Just like the test in Caner and Hansen (2004), our tests are non-pivotal, and we prove their bootstrap validity. The empirical application revisits the question in Ramey and Zubairy (2018) whether government spending multipliers are larger in recessions, but using tests for an unknown threshold. Consistent with Ramey and Zubairy (2018), we do not find strong evidence that these multipliers are larger in recessions.
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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 | Caner, M. and B. E. Hansen (2004) Instrumental variable estimation of a threshold model | 1.000 | 6 | 3 | 100% |
| 2 | Ramey, V. A. and S. Zubairy (2018) Government spending multipliers in good times and in bad: Evidence from U.S. historical data | 0.874 | 5 | 2 | 100% |
| 3 | Mammen, E (1993) Bootstrap and wild bootstrap for high-dimensional linear models | 0.737 | 3 | 2 | 100% |
| 4 | Owyang, M., V. Ramey, and S. Zubairy (2013) Are government spending multipliers greater during periods of slack? Evidence from twentieth-century historical data | 0.737 | 3 | 2 | 100% |
| 5 | Hansen, B. E (1996) Inference when a nuisance parameter is not identified under the null hypothesis | 0.721 | 8 | 4 | 38% |
| 6 | Antoine, B. and O. Boldea (2015) Inference in linear models with structural changes and mixed identification strength | 0.644 | 2 | 2 | 100% |
| 7 | Boldea, O., A. Cornea-Madeira, and A. R. Hall (2019) Bootstrapping structural change tests self | 0.644 | 2 | 2 | 100% |
| 8 | Gonzalo, J. and J.-Y. Pitarakis (2002) Estimation and model selection based inference in single and multiple threshold models | 0.644 | 2 | 2 | 100% |
| 9 | Hansen, B. E (2000) Sample splitting and threshold estimation | 0.644 | 2 | 2 | 100% |
| 10 | Yu, P. and P. C. B. Phillips (2018) Threshold Regression with Endogeneity | 0.585 | 3 | 1 | 100% |
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