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Andrés Riquelme

Biographic Data

ID4457528
NAMEAndrés Riquelme
GIVEN NAMESAndrés
FAMILY NAMERiquelme
SIGNATURERIQUELME A
AFFILIATIONSUniversity of Talca
ORCID0000-0003-1220-0926
VERIFIEDYes
TOTAL WORKS4
TOTAL CITATIONS1
AUTHOR COUNT4
EDITOR COUNT0
FIRST PUBLICATION YEAR2017
LATEST PUBLICATION YEAR2026
H-INDEX1
  • Does mining activity affects economic welfare in mining and neighboring districts? Evidence from Peru, 2003–2019

    Open Access•Elmer Sánchez Dávila, Andrés Riquelme•ARTICLE•Mineral Economics•2026

  • Multidimensional Poverty as a Determinant of Techno-Distress in Online Education

    Open Access•Alejandro Cataldo, Natalia Bravo-Adasme et al.•ARTICLE•International Journal of…•2025

    The rapid shift to online education during the COVID-19 pandemic exacerbated mental health risks for students, particularly those experiencing multidimensional poverty-a potential contributor to psychological distress in digital learning environments. This study examines how poverty-driven techno-distress (technology-related stress) impacts university students' mental health, focusing on 202 Chilean learners engaged in remote classes. Using parti…

  • Neo-liberalized Housing Policy and Urban Accessibility

    Open Access•Luis Vergara, Andrés Riquelme•ARTICLE•Journal of Housing and the Built…•2023•Cited by: 1•References: 14

  • Sharp Threshold Detection Based on Sup-Norm Error Rates in High-Dimensional Models

    Laurent Callot, Mehmet Caner et al.•ARTICLE•Journal of Business and Economic…•2017

    We propose a new estimator, the thresholded scaled Lasso, in high-dimensional threshold regressions. First, we establish an upper bound on the l∞ estimation error of the scaled Lasso estimator of Lee, Seo, and Shin. This is a nontrivial task as the literature on high-dimensional models has focused almost exclusively on l1 and l2 estimation errors. We show that this sup-norm bound can be used to distinguish between zero and nonzero coefficients at…

  • Neo-liberalized Housing Policy and Urban Accessibility

    Open Access•Luis Vergara, Andrés Riquelme•ARTICLE•Journal of Housing and the Built…•2023•Cited by: 1•References: 14

  • Sharp Threshold Detection Based on Sup-Norm Error Rates in High-Dimensional Models

    Laurent Callot, Mehmet Caner et al.•ARTICLE•Journal of Business and Economic…•2017

    We propose a new estimator, the thresholded scaled Lasso, in high-dimensional threshold regressions. First, we establish an upper bound on the l∞ estimation error of the scaled Lasso estimator of Lee, Seo, and Shin. This is a nontrivial task as the literature on high-dimensional models has focused almost exclusively on l1 and l2 estimation errors. We show that this sup-norm bound can be used to distinguish between zero and nonzero coefficients at…

  • Neo-liberalized Housing Policy and Urban Accessibility

    Open Access•Luis Vergara, Andrés Riquelme•ARTICLE•Journal of Housing and the Built…•2023•Cited by: 1•References: 14

  • Multidimensional Poverty as a Determinant of Techno-Distress in Online Education

    Open Access•Alejandro Cataldo, Natalia Bravo-Adasme et al.•ARTICLE•International Journal of…•2025

    The rapid shift to online education during the COVID-19 pandemic exacerbated mental health risks for students, particularly those experiencing multidimensional poverty-a potential contributor to psychological distress in digital learning environments. This study examines how poverty-driven techno-distress (technology-related stress) impacts university students' mental health, focusing on 202 Chilean learners engaged in remote classes. Using parti…

  • Does mining activity affects economic welfare in mining and neighboring districts? Evidence from Peru, 2003–2019

    Open Access•Elmer Sánchez Dávila, Andrés Riquelme•ARTICLE•Mineral Economics•2026

Political science (2 works) · Psychology (2 works) · Socioeconomic status (2 works) · Advanced Statistical Methods and Models (1 work) · Business (1 work) · Clinical Psychology (1 work) · Clinical Psychology (1 work) · Computer Science (1 work) · Coronavirus disease 2019 (COVID-19 (1 work) · COVID-19 and Mental Health (1 work)

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