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Information matrix tests for switching regressions

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Abstract

The EM principle implies the moments underlying the information matrix test for switching regressions are the expectation given the data of the moments one would test if one knew the subpopulation each observation originated from. Thus, we identify components related to conditional heteroskedasticity, conditional and unconditional skewness, and unconditional kurtosis of regression residuals within each regime. Simulations indicate analytical expressions for the asymptotic covariance matrix of those moments adjusted for sampling variability in parameter estimators provide reliable finite sample sizes and good power against various alternatives, especially combined with the parametric bootstrap. We apply the test to cross-country convergence regressions.

Suggested Citation

  • Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2026. "Information matrix tests for switching regressions," Working Papers wp2026_2601, CEMFI.
    • Handle: RePEc:cmf:wpaper:wp2026_2601
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    JEL classification:

    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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