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Willingness to pay for renewables : insights from a meta-analysis of choice experiments

Cerdá Tena, Emilio; López-Otero, Xiral; Quiroga, Sonia; … - In: Energy economics 130 (2024), pp. 1-11

Persistent link: https://www.econbiz.de/10014559152

The role of green energy stock market in forecasting China's crude oil market : an application of IIS approach and sparse regression models

Khan, Faridoon; Muhammadullah, Sara; Arshian Sharif; … - In: Energy economics 130 (2024), pp. 1-15

Persistent link: https://www.econbiz.de/10014559200

Supervised kernel principal component analysis for forecasting

Fang, Puyi; Gao, Zhaoxing; Tsay, Ruey S. - In: Finance research letters 58 (2023) 1, pp. 1-7

Persistent link: https://www.econbiz.de/10014581032

Financial technology as a heterogeneous driver of carbon emission reduction in China : evidence from a novel sparse quantile regression

Chen, Weijie; Wang, Jie; Ye, Yafen - In: Journal of innovation & knowledge : JIK 9 (2024) 2, pp. 1-13

fintech and carbon emissions reduction, we employ an innovative sparse support vector quantile regression to explore the …

Persistent link: https://www.econbiz.de/10014581130

Labour Market Performance of Immigrants: New Evidence from Linked Administrative Data

Kaya, Ezgi - 2024

Using administrative data from the Annual Survey of Hours and Earnings linked to the 2011 Census of England and Wales, this paper explores the labour market performance of first-generation immigrants and compares it to that of UK-born employees. By focusing on various labour market outcomes and...

Persistent link: https://www.econbiz.de/10014514474

Should moderated regressions include or exclude quadratic terms? : present both! : then apply our linear algebraic analysis to identify the preferable specification

Kalnins, Arturs - In: Organizational research methods : ORM 27 (2024) 1, pp. 29-63

Persistent link: https://www.econbiz.de/10014581620

Out of shape : the implications of (extremely) nonnormal dependent variables

Certo, S. Trevis; Raney, Kristen; Albader, Latifa; … - In: Organizational research methods : ORM 27 (2024) 2, pp. 195-222

Persistent link: https://www.econbiz.de/10014581654