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Semiparametric correction for endogenous truncation bias with Vox Populi based participation decision

Nir Billfeld, Moshe Kim

arXiv 17 Feb 2019 · Econometrics · publishedIEEE Access (2018) · 2 citations (OpenAlex)

arXiv:1902.06286 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We synthesize the knowledge present in various scientific disciplines for the development of semiparametric endogenous truncation-proof algorithm, correcting for truncation bias due to endogenous self-selection. This synthesis enriches the algorithm's accuracy, efficiency and applicability. Improving upon the covariate shift assumption, data are intrinsically affected and largely generated by their own behavior (cognition). Refining the concept of Vox Populi (Wisdom of Crowd) allows data points to sort themselves out depending on their estimated latent reference group opinion space. Monte Carlo simulations, based on 2,000,000 different distribution functions, practically generating 100 million realizations, attest to a very high accuracy of our model.

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Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
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Showing the top 10 of 57 scored citations.