The role of education attention on high-tech markets in an emerging economy: Evidence from QQR and NCQ techniques

Wang Gao and Hongwei Zhang

Technological Forecasting and Social Change, 2024, vol. 207, issue C

Abstract: This study employs quantile-on-quantile regression (QQR) and nonparametric causality-in-quantile (NCQ) methods to investigate the asymmetric impact and predictability of education attention on China's high-tech markets. The QQR results reveal a significant positive impact of education attention on high-tech market returns, with asymmetric across volatile and stable market situations. Specifically, basic education attention boosts performance in advanced manufacturing and new energy sectors, vocational and continuing education attention excel during market upturns in biotechnology and environmental industries, and higher education attention could serve as a strong hedge against the high-tech market downturns. Moreover, education attention significantly influences the volatility of high-tech market under normal conditions, uncovering a significant source of market risk sensitivity. The NCQ results highlight the effectiveness of education attention as a predictor for the high-tech market, particularly for aerospace and national defense, new materials, and semiconductor sectors, prominently evident in medium or high quantiles. These findings offer novel insights for investors and policymakers regarding asset pricing and management decisions.

Keywords: High-tech; Education attention; Quantile-on-quantile; Nonparametric causality-in-quantiles (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:207:y:2024:i:c:s0040162524004013

DOI: 10.1016/j.techfore.2024.123603

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