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Franziska Schulz

Personal Details

First Name:Franziska
Middle Name:
Last Name:Schulz
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RePEc Short-ID:psc549
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Terminal Degree:2017 Center for Applied Statistics and Econometrics (CASE); Humboldt-Universität Berlin (from RePEc Genealogy)

Affiliation

(34%) Center for Applied Statistics and Econometrics (CASE)
Humboldt-Universität Berlin

Berlin, Germany
http://www.case.hu-berlin.de/
RePEc:edi:cahubde (more details at EDIRC)

(33%) Sonderforschungsbereich 649: Ökonomisches Risiko
Wirtschaftswissenschaftliche Fakultät
Humboldt-Universität Berlin

Berlin, Germany
http://sfb649.wiwi.hu-berlin.de/
RePEc:edi:sohubde (more details at EDIRC)

(33%) Institut für Statistik und Ökonometrie (ISÖ)
Wirtschaftswissenschaftliche Fakultät
Humboldt-Universität Berlin

Berlin, Germany
http://ise.wiwi.hu-berlin.de/
RePEc:edi:ishubde (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Brenda López Cabrera & Franziska Schulz, 2016. "Time-Adaptive Probabilistic Forecasts of Electricity Spot Prices with Application to Risk Management," SFB 649 Discussion Papers SFB649DP2016-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  2. Brenda Lopez Cabrera & Franziska Schulz, 2014. "Forecasting Generalized Quantiles of Electricity Demand: A Functional Data Approach," SFB 649 Discussion Papers SFB649DP2014-030, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  3. Brenda López Cabrera, & Franziska Schulz,, 2013. "Volatility linkages between energy and agricultural commodity prices," SFB 649 Discussion Papers SFB649DP2013-042, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

Articles

  1. Brenda López Cabrera & Franziska Schulz, 2017. "Forecasting Generalized Quantiles of Electricity Demand: A Functional Data Approach," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 127-136, January.
  2. López Cabrera, Brenda & Schulz, Franziska, 2016. "Volatility linkages between energy and agricultural commodity prices," Energy Economics, Elsevier, vol. 54(C), pages 190-203.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Brenda Lopez Cabrera & Franziska Schulz, 2014. "Forecasting Generalized Quantiles of Electricity Demand: A Functional Data Approach," SFB 649 Discussion Papers SFB649DP2014-030, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Petra Burdejová & Wolfgang K. Härdle, 2019. "Dynamic semi-parametric factor model for functional expectiles," Computational Statistics, Springer, vol. 34(2), pages 489-502, June.
    2. van der Meer, D.W. & Shepero, M. & Svensson, A. & Widén, J. & Munkhammar, J., 2018. "Probabilistic forecasting of electricity consumption, photovoltaic power generation and net demand of an individual building using Gaussian Processes," Applied Energy, Elsevier, vol. 213(C), pages 195-207.
    3. Li, Z. & Hurn, A.S. & Clements, A.E., 2017. "Forecasting quantiles of day-ahead electricity load," Energy Economics, Elsevier, vol. 67(C), pages 60-71.
    4. Tran, Ngoc M. & Burdejová, Petra & Ospienko, Maria & Härdle, Wolfgang K., 2019. "Principal component analysis in an asymmetric norm," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 1-21.
    5. Shih-Kang Chao & Wolfgang K. Härdle & Chen Huang, 2016. "Multivariate Factorisable Sparse Asymmetric Least Squares Regression," SFB 649 Discussion Papers SFB649DP2016-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. Hu, Junjie & López Cabrera, Brenda & Melzer, Awdesch, 2021. "Advanced statistical learning on short term load process forecasting," IRTG 1792 Discussion Papers 2021-020, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    7. Xu, Xiuqin & Chen, Ying & Goude, Yannig & Yao, Qiwei, 2021. "Day-ahead probabilistic forecasting for French half-hourly electricity loads and quantiles for curve-to-curve regression," Applied Energy, Elsevier, vol. 301(C).
    8. Kei Hirose & Keigo Wada & Maiya Hori & Rin-ichiro Taniguchi, 2020. "Event Effects Estimation on Electricity Demand Forecasting," Energies, MDPI, vol. 13(21), pages 1-20, November.
    9. Fabio Bellini & Bernhard Klar & Alfred Müller, 2018. "Expectiles, Omega Ratios and Stochastic Ordering," Methodology and Computing in Applied Probability, Springer, vol. 20(3), pages 855-873, September.
    10. Brenda López Cabrera & Franziska Schulz, 2016. "Time-Adaptive Probabilistic Forecasts of Electricity Spot Prices with Application to Risk Management," SFB 649 Discussion Papers SFB649DP2016-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Klaus Ackermann & Simon D Angus & Paul A Raschky, 2020. "Estimating Sleep and Work Hours from Alternative Data by Segmented Functional Classification Analysis, SFCA," SoDa Laboratories Working Paper Series 2020-04, Monash University, SoDa Laboratories.
    12. Klaus Ackermann & Simon D. Angus & Paul A. Raschky, 2020. "Estimating Sleep & Work Hours from Alternative Data by Segmented Functional Classification Analysis (SFCA)," Papers 2010.08102, arXiv.org.

  2. Brenda López Cabrera, & Franziska Schulz,, 2013. "Volatility linkages between energy and agricultural commodity prices," SFB 649 Discussion Papers SFB649DP2013-042, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Tule, Moses K. & Salisu, Afees A. & Chiemeke, Charles C., 2019. "Can agricultural commodity prices predict Nigeria's inflation?," Journal of Commodity Markets, Elsevier, vol. 16(C).
    2. Rangga Handika & Rangga Handika & Sigit Triandaru, 2016. "Is the Best Generalized Autoregressive Conditional Heteroskedasticity(p,q) Value-at-risk Estimate also the Best in Reality? An Evidence from Australian Interconnected Power Markets," International Journal of Energy Economics and Policy, Econjournals, vol. 6(4), pages 814-821.
    3. Poeschel, Friedrich, 2012. "Assortative matching through signals," VfS Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 62061, Verein für Socialpolitik / German Economic Association.
    4. Urom, Christian & Anochiwa, Lasbrey & Yuni, Denis & Idume, Gabriel, 2019. "Asymmetric linkages among precious metals, global equity and bond yields: The role of volatility and business cycle factors," The Journal of Economic Asymmetries, Elsevier, vol. 20(C).
    5. Chemkha, Rahma & BenSaïda, Ahmed & Ghorbel, Ahmed & Tayachi, Tahar, 2021. "Hedge and safe haven properties during COVID-19: Evidence from Bitcoin and gold," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 71-85.
    6. Naeem, Muhammad Abubakr & Hasan, Mudassar & Arif, Muhammad & Suleman, Muhammad Tahir & Kang, Sang Hoon, 2022. "Oil and gold as a hedge and safe-haven for metals and agricultural commodities with portfolio implications," Energy Economics, Elsevier, vol. 105(C).
    7. Geert Dhaene & Piet Sercu & Jianbin Wu, 2022. "Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 868-887, May.
    8. Zhang, Dayong & Broadstock, David C., 2020. "Global financial crisis and rising connectedness in the international commodity markets," International Review of Financial Analysis, Elsevier, vol. 68(C).
    9. Chang, Chia-Lin & McAleer, Michael & Wang, Yu-Ann, 2018. "Modelling volatility spillovers for bio-ethanol, sugarcane and corn spot and futures prices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1002-1018.
    10. Julyerme M. Tonin & Carlos M. R. Vieira & Rui M. de Sousa Fragoso & João G. Martines Filho, 2020. "Conditional correlation and volatility between spot and futures markets for soybean and corn," Agribusiness, John Wiley & Sons, Ltd., vol. 36(4), pages 707-724, October.
    11. Xian, Hui & Gregory, Colson & Michael, Wetzstein, 2015. "Impact of nonrenewable on renewable energy: The case of wood pellets," 2015 Annual Meeting, January 31-February 3, 2015, Atlanta, Georgia 196833, Southern Agricultural Economics Association.
    12. Śmiech, Sławomir & Papież, Monika & Fijorek, Kamil & Dąbrowski, Marek A., 2019. "What drives food price volatility? Evidence based on a generalized VAR approach applied to the food, financial and energy markets," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 13, pages 1-32.
    13. Zhengyi Dong, 2019. "Does the Development of Bioenergy Exacerbate the Price Increase of Maize?," Sustainability, MDPI, vol. 11(18), pages 1-16, September.
    14. Dahl, Roy Endré & Oglend, Atle & Yahya, Muhammad, 2020. "Dynamics of volatility spillover in commodity markets: Linking crude oil to agriculture," Journal of Commodity Markets, Elsevier, vol. 20(C).
    15. Vo, Long Hai & Le, Thai-Ha, 2021. "Eatery, energy, environment and economic system, 1970–2017: Understanding volatility spillover patterns in a global sample," Energy Economics, Elsevier, vol. 100(C).
    16. Ting-Ting Sun & Chi-Wei Su & Ran Tao & Meng Qin, 2021. "Are Agricultural Commodity Prices on a Conventional Wisdom with Inflation?," SAGE Open, , vol. 11(3), pages 21582440211, August.
    17. Shahzad, Farrukh & Bouri, Elie & Mokni, Khaled & Ajmi, Ahdi Noomen, 2021. "Energy, agriculture, and precious metals: Evidence from time-varying Granger causal relationships for both return and volatility," Resources Policy, Elsevier, vol. 74(C).
    18. Anthony N. Rezitis & Gregor Kastner, 2021. "On the joint volatility dynamics in dairy markets," Papers 2104.12707, arXiv.org.
    19. Sima Siami-Namini, 2019. "Volatility Transmission Among Oil Price, Exchange Rate and Agricultural Commodities Prices," Applied Economics and Finance, Redfame publishing, vol. 6(4), pages 41-61, July.
    20. Bouri, Elie & Lucey, Brian & Saeed, Tareq & Vo, Xuan Vinh, 2021. "The realized volatility of commodity futures: Interconnectedness and determinants#," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 139-151.
    21. Chia-Lin Chang & Michael McAleer & Yu-Ann Wang, 2016. "Modelling volatility spillovers for bio-ethanol, sugarcane and corn," Documentos de Trabajo del ICAE 2016-03, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    22. Karel Janda & Ladislav Kristoufek, 2019. "The relationship between fuel and food prices: Methods, outcomes, and lessons for commodity price risk management," CAMA Working Papers 2019-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    23. Makkonen, Adam & Vallström, Daniel & Uddin, Gazi Salah & Rahman, Md Lutfur & Haddad, Michel Ferreira Cardia, 2021. "The effect of temperature anomaly and macroeconomic fundamentals on agricultural commodity futures returns," Energy Economics, Elsevier, vol. 100(C).
    24. Umar, Zaghum & Jareño, Francisco & Escribano, Ana, 2021. "Agricultural commodity markets and oil prices: An analysis of the dynamic return and volatility connectedness," Resources Policy, Elsevier, vol. 73(C).
    25. Jebabli, Ikram & Roubaud, David, 2018. "Time-varying efficiency in food and energy markets: Evidence and implications," Economic Modelling, Elsevier, vol. 70(C), pages 97-114.
    26. Luo, Jiawen & Ji, Qiang, 2018. "High-frequency volatility connectedness between the US crude oil market and China's agricultural commodity markets," Energy Economics, Elsevier, vol. 76(C), pages 424-438.
    27. Ding, Shusheng & Cui, Tianxiang & Zheng, Dandan & Du, Min, 2021. "The effects of commodity financialization on commodity market volatility," Resources Policy, Elsevier, vol. 73(C).
    28. M. Thenmozhi & Shipra Maurya, 2020. "Crude Oil Volatility Transmission Across Food Commodity Markets: A Multivariate BEKK-GARCH Approach," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 20(2), pages 131-164, August.
    29. Monika Roman & Aleksandra Górecka & Joanna Domagała, 2020. "The Linkages between Crude Oil and Food Prices," Energies, MDPI, vol. 13(24), pages 1-18, December.
    30. Hau, Liya & Zhu, Huiming & Huang, Rui & Ma, Xiang, 2020. "Heterogeneous dependence between crude oil price volatility and China’s agriculture commodity futures: Evidence from quantile-on-quantile regression," Energy, Elsevier, vol. 213(C).
    31. Anthony N. Rezitis & Gregor Kastner, 2021. "On the joint volatility dynamics in international dairy commodity markets," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 65(3), pages 704-728, July.
    32. José César Cruz Junior & Daniel H D Capitani & Rodrigo L F Silveira, 2018. "The effect of Brazilian corn and soybean crop expansion on price and volatility transmission," Economics Bulletin, AccessEcon, vol. 38(4), pages 2273-2283.
    33. Hernandez, Jose Areola & Shahzad, Syed Jawad Hussain & Uddin, Gazi Salah & Kang, Sang Hoon, 2019. "Can agricultural and precious metal commodities diversify and hedge extreme downside and upside oil market risk? An extreme quantile approach," Resources Policy, Elsevier, vol. 62(C), pages 588-601.
    34. Vo, D.H. & Vu, T.N. & Vo, A.T. & McAleer, M.J., 2018. "Modelling the Relationship between Crude Oil and Agricultural Commodity Prices," Econometric Institute Research Papers EI2019-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    35. Filip, Ondrej & Janda, Karel & Kristoufek, Ladislav & Zilberman, David, 2019. "Food versus fuel: An updated and expanded evidence," Energy Economics, Elsevier, vol. 82(C), pages 152-166.
    36. Pal, Debdatta & Mitra, Subrata K., 2017. "Time-frequency contained co-movement of crude oil and world food prices: A wavelet-based analysis," Energy Economics, Elsevier, vol. 62(C), pages 230-239.
    37. Zhu, Bo & Lin, Renda & Deng, Yuanyue & Chen, Pingshe & Chevallier, Julien, 2021. "Intersectoral systemic risk spillovers between energy and agriculture under the financial and COVID-19 crises," Economic Modelling, Elsevier, vol. 105(C).
    38. James Ming Chen & Mobeen Ur Rehman, 2021. "A Pattern New in Every Moment: The Temporal Clustering of Markets for Crude Oil, Refined Fuels, and Other Commodities," Energies, MDPI, vol. 14(19), pages 1-58, September.
    39. Han, Liyan & Jin, Jiayu & Wu, Lei & Zeng, Hongchao, 2020. "The volatility linkage between energy and agricultural futures markets with external shocks," International Review of Financial Analysis, Elsevier, vol. 68(C).
    40. Krzysztof Drachal, 2019. "Analysis of Agricultural Commodities Prices with New Bayesian Model Combination Schemes," Sustainability, MDPI, vol. 11(19), pages 1-23, September.
    41. Chen, James Ming & Rehman, Mobeen Ur & Vo, Xuan Vinh, 2021. "Clustering commodity markets in space and time: Clarifying returns, volatility, and trading regimes through unsupervised machine learning," Resources Policy, Elsevier, vol. 73(C).
    42. Faruk Urak & Abdulbaki Bilgic & Gürkan Bozma & Wojciech J. Florkowski & Erkan Efekan, 2022. "Volatility in Live Calf, Live Sheep, and Feed Wheat Return Markets: A Threat to Food Price Stability in Turkey," Agriculture, MDPI, vol. 12(4), pages 1-24, April.
    43. Khalfaoui, Rabeh & Baumöhl, Eduard & Sarwar, Suleman & Výrost, Tomáš, 2021. "Connectedness between energy and nonenergy commodity markets: Evidence from quantile coherency networks," Resources Policy, Elsevier, vol. 74(C).
    44. Sergio Adriani David & Claudio M. C. Inácio & José A. Tenreiro Machado, 2019. "Ethanol Prices and Agricultural Commodities: An Investigation of Their Relationship," Mathematics, MDPI, vol. 7(9), pages 1-25, August.
    45. Cheng, Sheng & Cao, Yan, 2019. "On the relation between global food and crude oil prices: An empirical investigation in a nonlinear framework," Energy Economics, Elsevier, vol. 81(C), pages 422-432.
    46. Taghizadeh-Hesary, Farhad & Rasoulinezhad, Ehsan & Yoshino, Naoyuki, 2019. "Energy and Food Security: Linkages through Price Volatility," Energy Policy, Elsevier, vol. 128(C), pages 796-806.
    47. Yahya, Muhammad & Oglend, Atle & Dahl, Roy Endré, 2019. "Temporal and spectral dependence between crude oil and agricultural commodities: A wavelet-based copula approach," Energy Economics, Elsevier, vol. 80(C), pages 277-296.
    48. Mukhlis MUKHLIS & Raja MASBAR & Sofyan SYAHNUR & M. Shabri Abd. MAJID, 2020. "Dynamic Causalities Between World Oil Price And Indonesia’S Cocoa Market: Evidence From The 2008 Global Financial Crisis And The 2011 European Debt Crisis," Regional Science Inquiry, Hellenic Association of Regional Scientists, vol. 0(2), pages 217-233, June.
    49. Tiwari, Aviral Kumar & Khalfaoui, Rabeh & Solarin, Sakiru Adebola & Shahbaz, Muhammad, 2018. "Analyzing the time-frequency lead–lag relationship between oil and agricultural commodities," Energy Economics, Elsevier, vol. 76(C), pages 470-494.
    50. Saghaian, Sayed H. & Nemati, Mehdi & Walters, Cory G. & Chen, Bo, 2017. "Asymmetric Price Volatility Interaction between U.S. Food and Energy Markets," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258240, Agricultural and Applied Economics Association.
    51. Wei Su, Chi & Wang, Xiao-Qing & Tao, Ran & Oana-Ramona, Lobonţ, 2019. "Do oil prices drive agricultural commodity prices? Further evidence in a global bio-energy context," Energy, Elsevier, vol. 172(C), pages 691-701.
    52. Zingbagba, Mark & Nunes, Rubens & Fadairo, Muriel, 2020. "The impact of diesel price on upstream and downstream food prices: Evidence from São Paulo," Energy Economics, Elsevier, vol. 85(C).
    53. Ji, Qiang & Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Risk spillover between energy and agricultural commodity markets: A dependence-switching CoVaR-copula model," Energy Economics, Elsevier, vol. 75(C), pages 14-27.
    54. Maitra, Debasish & Guhathakurta, Kousik & Kang, Sang Hoon, 2021. "The good, the bad and the ugly relation between oil and commodities: An analysis of asymmetric volatility connectedness and portfolio implications," Energy Economics, Elsevier, vol. 94(C).
    55. Balcilar, Mehmet & Gabauer, David & Umar, Zaghum, 2021. "Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach," Resources Policy, Elsevier, vol. 73(C).
    56. Xianfang Su & Huiming Zhu & Xinxia Yang, 2019. "Heterogeneous Causal Relationships between Spot and Futures Oil Prices: Evidence from Quantile Causality Analysis," Sustainability, MDPI, vol. 11(5), pages 1-17, March.
    57. Kang, Sang Hoon & McIver, Ron & Yoon, Seong-Min, 2017. "Dynamic spillover effects among crude oil, precious metal, and agricultural commodity futures markets," Energy Economics, Elsevier, vol. 62(C), pages 19-32.
    58. Siami-Namini, Sima & Hudson, Darren, 2017. "Volatility Spillover Between Oil Prices, Us Dollar Exchange Rates And International Agricultural Commodities Prices," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252845, Southern Agricultural Economics Association.
    59. Ahmad, Wasim & Hernandez, Jose Arreola & Saini, Seema & Mishra, Ritesh Kumar, 2021. "The US equity sectors, implied volatilities, and COVID-19: What does the spillover analysis reveal?," Resources Policy, Elsevier, vol. 72(C).
    60. Rehman, Mobeen Ur & Bouri, Elie & Eraslan, Veysel & Kumar, Satish, 2019. "Energy and non-energy commodities: An asymmetric approach towards portfolio diversification in the commodity market," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    61. Jihed Majdoub & Salim Ben Sassi & Azza Bejaoui, 2021. "Can fiat currencies really hedge Bitcoin? Evidence from dynamic short-term perspective," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 789-816, December.
    62. Pal, Debdatta & Mitra, Subrata K., 2019. "Correlation dynamics of crude oil with agricultural commodities: A comparison between energy and food crops," Economic Modelling, Elsevier, vol. 82(C), pages 453-466.
    63. Mitra, Subrata Kumar & Bhatia, Vaneet & Jana, R.K. & Charan, Parikshit & Chattopadhyay, Manojit, 2018. "Changing value detrended cross correlation coefficient over time: Between crude oil and crop prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 671-678.

Articles

  1. Brenda López Cabrera & Franziska Schulz, 2017. "Forecasting Generalized Quantiles of Electricity Demand: A Functional Data Approach," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 127-136, January.
    See citations under working paper version above.
  2. López Cabrera, Brenda & Schulz, Franziska, 2016. "Volatility linkages between energy and agricultural commodity prices," Energy Economics, Elsevier, vol. 54(C), pages 190-203.
    See citations under working paper version above.Sorry, no citations of articles recorded.

More information

Research fields, statistics, top rankings, if available.

Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ENE: Energy Economics (2) 2015-02-28 2016-10-02. Author is listed
  2. NEP-FOR: Forecasting (2) 2015-02-28 2016-10-02. Author is listed
  3. NEP-RMG: Risk Management (2) 2013-09-24 2016-10-02. Author is listed
  4. NEP-AGR: Agricultural Economics (1) 2013-09-24. Author is listed

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