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A Jackknife Model Averaging Analysis of RMB Misalignment Estimates

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  • Yin-Wong Cheung
  • Wenhao Wang
Abstract
We adopt the Jackknife Model Averaging (JMA) technique to conduct a meta-regression analysis of 925 renminbi (RMB) misalignment estimates generated by 69 studies. The JMA method accounts for model selection and sampling uncertainties, and allows for non-nested model specifications and heteroskedasticity in assessing effects of study characteristics. The RMB misalignment estimates are found to be systematically affected by the choices of data, the theoretical setup and the empirical strategy, in addition to publication attributes of these studies. These study characteristic effects are quite robust to the choice of benchmark study characteristics, to alternative model averaging methods including the heteroskedasticity-robust Mallows approach, the information criterion approach, and the Bayesian model averaging. In evaluating the probabilistic property of RMB misalignment estimates implied by hypothetical composites of study characteristics, we find the evidence of a misaligned RMB, in general, is weak.

Suggested Citation

  • Yin-Wong Cheung & Wenhao Wang, 2019. "A Jackknife Model Averaging Analysis of RMB Misalignment Estimates," CESifo Working Paper Series 7840, CESifo.
    • Handle: RePEc:ces:ceswps:_7840
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    Keywords

    frequentist model average; meta-analysis; Mallows criterion; Bayesian model averaging; publication biases;
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    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics

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