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Statistics of Heteroscedastic Extremes

Citations

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Cited by:

  1. John H. J. Einmahl & Fan Yang & Chen Zhou, 2021. "Testing the Multivariate Regular Variation Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 907-919, October.
  2. Einmahl, John & Ferreira, Ana & de Haan, Laurens & Neves, C. & Zhou, C., 2020. "Spatial Dependence and Space-Time Trend in Extreme Events," Other publications TiSEM ae5818cd-f071-4275-9577-d, Tilburg University, School of Economics and Management.
  3. Chen, Yu & Ma, Mengyuan & Sun, Hongfang, 2023. "Statistical inference for extreme extremile in heavy-tailed heteroscedastic regression model," Insurance: Mathematics and Economics, Elsevier, vol. 111(C), pages 142-162.
  4. Einmahl, John & He, Y., 2022. "Extreme Value Inference for General Heterogeneous Data," Other publications TiSEM fd8dd91c-086f-40e6-ac29-3, Tilburg University, School of Economics and Management.
  5. Hou, Yanxi & Leng, Xuan & Peng, Liang & Zhou, Yinggang, 2024. "Panel quantile regression for extreme risk," Journal of Econometrics, Elsevier, vol. 240(1).
  6. Nicolau, João & Rodrigues, Paulo M.M. & Stoykov, Marian Z., 2023. "Tail index estimation in the presence of covariates: Stock returns’ tail risk dynamics," Journal of Econometrics, Elsevier, vol. 235(2), pages 2266-2284.
  7. Alois Guger & Silvia Rocha-Akis, 2016. "Redistribution by the State in Austria," WIFO Bulletin, WIFO, vol. 21(11), pages 100-115, September.
  8. Demichelis, Francesca & Fiore, Silvia & Pleissner, Daniel & Venus, Joachim, 2018. "Technical and economic assessment of food waste valorization through a biorefinery chain," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 38-48.
  9. Robert, Christian Y., 2022. "Testing for changes in the tail behavior of Brown–Resnick Pareto processes," Stochastic Processes and their Applications, Elsevier, vol. 144(C), pages 312-368.
  10. Jacek Wójcik, 2017. "Consequences of the Cognitive Digital Divide on the Consumer Market," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 44, pages 69-80.
  11. Wittenberg, Raphael & Sharpin, Luke & McCormick, Barry & Hurst, Jeremy, 2017. "The ageing society and emergency hospital admissions," Health Policy, Elsevier, vol. 121(8), pages 923-928.
  12. Einmahl, John & He, Y., 2022. "Extreme Value Inference for General Heterogeneous Data," Discussion Paper 2022-017, Tilburg University, Center for Economic Research.
  13. Dominković, D.F. & Bačeković, I. & Ćosić, B. & Krajačić, G. & Pukšec, T. & Duić, N. & Markovska, N., 2016. "Zero carbon energy system of South East Europe in 2050," Applied Energy, Elsevier, vol. 184(C), pages 1517-1528.
  14. Ahmed, Hanan, 2022. "Extreme value statistics using related variables," Other publications TiSEM 246f0f13-701c-4c0d-8e09-e, Tilburg University, School of Economics and Management.
  15. Magdeldin, Mohamed & Kohl, Thomas & Järvinen, Mika, 2017. "Techno-economic assessment of the by-products contribution from non-catalytic hydrothermal liquefaction of lignocellulose residues," Energy, Elsevier, vol. 137(C), pages 679-695.
  16. Joos, Michael & Staffell, Iain, 2018. "Short-term integration costs of variable renewable energy: Wind curtailment and balancing in Britain and Germany," Renewable and Sustainable Energy Reviews, Elsevier, vol. 86(C), pages 45-65.
  17. Li, Wei & Lu, Can & Ding, Yi & Zhang, Yan-Wu, 2017. "The impacts of policy mix for resolving overcapacity in heavy chemical industry and operating national carbon emission trading market in China," Applied Energy, Elsevier, vol. 204(C), pages 509-524.
  18. Brook T. Russell & Whitney K. Huang, 2021. "Modeling short‐ranged dependence in block extrema with application to polar temperature data," Environmetrics, John Wiley & Sons, Ltd., vol. 32(3), May.
  19. Kang, Sang Hoon & Islam, Faridul & Kumar Tiwari, Aviral, 2019. "The dynamic relationships among CO2 emissions, renewable and non-renewable energy sources, and economic growth in India: Evidence from time-varying Bayesian VAR model," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 90-101.
  20. Nicoletti, Giuseppe & von Rueden, Christina & Andrews, Dan, 2020. "Digital technology diffusion: A matter of capabilities, incentives or both?," European Economic Review, Elsevier, vol. 128(C).
  21. Cui, Hengxin & Tan, Ken Seng & Yang, Fan & Zhou, Chen, 2022. "Asymptotic analysis of portfolio diversification," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 302-325.
  22. Everard, Mark & Longhurst, James & Pontin, John & Stephenson, Wendy & Brooks, Joss, 2017. "Developed-developing world partnerships for sustainable development (2): An illustrative case for a payments for ecosystem services (PES) approach," Ecosystem Services, Elsevier, vol. 24(C), pages 253-260.
  23. Powell, Robert J. & Vo, Duc H. & Pham, Thach N. & Singh, Abhay K., 2017. "The long and short of commodity tails and their relationship to Asian equity markets," Journal of Asian Economics, Elsevier, vol. 52(C), pages 32-44.
  24. Pinchasik, Daniel Ruben & Hovi, Inger Beate, 2017. "A CO2-fund for the transport industry: The case of Norway," Transport Policy, Elsevier, vol. 53(C), pages 186-195.
  25. Einmahl, John & He, Y., 2020. "Unified Extreme Value Estimation for Heterogeneous Data," Discussion Paper 2020-025, Tilburg University, Center for Economic Research.
  26. Einmahl, John & He, Y., 2020. "Unified Extreme Value Estimation for Heterogeneous Data," Other publications TiSEM dfe6c38c-823b-4394-b4fd-a, Tilburg University, School of Economics and Management.
  27. Yaolan Ma & Bo Wei & Wei Huang, 2020. "A nonparametric estimator for the conditional tail index of Pareto-type distributions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(1), pages 17-44, January.
  28. Ljungberg, Anders, 2016. "Marginal cost-pricing in the Swedish transport sector – An efficient and sustainable way of funding local and regional public transport in the future?," Research in Transportation Economics, Elsevier, vol. 59(C), pages 159-166.
  29. Einmahl, John & Zhou, C., 2024. "Tail Copula Estimation for Heteroscedastic Extremes," Discussion Paper 2024-003, Tilburg University, Center for Economic Research.
  30. Lu, Ying & Prato, Carlo G. & Sipe, Neil & Kimpton, Anthony & Corcoran, Jonathan, 2022. "The role of household modality style in first and last mile travel mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 158(C), pages 95-109.
  31. Fuchs, Johann & Hummel, Markus & Hutter, Christian & Gehrke, Britta & Wanger, Susanne & Weber, Enzo & Weigand, Roland & Zika, Gerd, 2016. "IAB-Prognose 2016: Beschäftigung und Arbeitskräfteangebot so hoch wie nie (IAB forecast 2016: Employment and labour supply are higher than ever before)," IAB-Kurzbericht 201606, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  32. Andrea Kunnert, 2016. "Leistbarkeit von Wohnen in Österreich. Operationalisierung und demographische Komponenten," WIFO Studies, WIFO, number 58932.
  33. Einmahl, John & Zhou, C., 2024. "Tail Copula Estimation for Heteroscedastic Extremes," Other publications TiSEM 6bcb09c5-8b19-48b8-9320-b, Tilburg University, School of Economics and Management.
  34. Schweiger, Gerald & Rantzer, Jonatan & Ericsson, Karin & Lauenburg, Patrick, 2017. "The potential of power-to-heat in Swedish district heating systems," Energy, Elsevier, vol. 137(C), pages 661-669.
  35. Borozan, Djula, 2018. "Regional-level household energy consumption determinants: The european perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 347-355.
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