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Testing for a Threshold in Models with Endogenous Regressors

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  • Mario P. Rothfelder
  • Otilia Boldea

Abstract

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.

Suggested Citation

  • Mario P. Rothfelder & Otilia Boldea, 2022. "Testing for a Threshold in Models with Endogenous Regressors," Papers 2207.10076, arXiv.org.
  • Handle: RePEc:arx:papers:2207.10076
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    Cited by:

    1. Rothfelder, Mario & Boldea, Otilia, 2016. "Testing for a Threshold in Models with Endogenous Regressors," Discussion Paper 2016-029, Tilburg University, Center for Economic Research.
    2. Zacharias Bragoudakis & Dimitrios Panas, 2021. "Investigating government spending multiplier for the US economy: empirical evidence using a triple lasso approach," Working Papers 292, Bank of Greece.

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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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