Sequentially Estimating the Structural Equation by Power Transformation

Jaedo Choi, Jin Seo Cho () and Hyungsik Moon ()

No 2020rwp-162, Working papers from Yonsei University, Yonsei Economics Research Institute

Abstract: This study provides an econometric methodology to test for a linear structural relationship among economic variables. For this, we propose the so-called distance-difference (DD) test statistic and show that it has omnibus power against arbitrary nonlinear structural relationships. If the DD test statistic rejects the linear model hypothesis, a sequential testing procedure assisted by the DD test statistic can consistently estimate the degree of polynomial function that arbitrarily approximates the nonlinear structural equation. Using extensive Monte Carlo simulations, we confirm the DD test’s finite sample properties and compare its performance with the sequential testing procedure assisted by the J-test statistic and moment selection criteria. Finally, we empirically investigate the structural relationship between the log wage and work experience years using Card’s (1995) National Longitudinal Survey data and affirm their inferential results by our methodology.

Keywords: GMM estimation; Model linearity testing; Model specification testing; Gaussian stochastic process; Sequential testing procedure; Wage equation (search for similar items in EconPapers)
JEL-codes: C12 C13 C26 C52 J24 J31 (search for similar items in EconPapers)
Pages: 44pages
Date: 2020-02
New Economics Papers: this item is included in nep-ecm
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Journal Article: SEQUENTIALLY ESTIMATING THE STRUCTURAL EQUATION BY POWER TRANSFORMATION (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:yon:wpaper:2020rwp-162

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