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Matthias Ritter

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.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:

    Mentioned in:

    1. Forecasting the weather using the market
      by Economic Logician in Economic Logic on 2013-02-21 21:06:00

Working papers

  1. Kionka, Marlene & Odening, Martin & Plogmann, Jana & Ritter, Matthias, 2021. "Measuring Liquidity in Agricultural Land Markets," 2021 Conference, August 17-31, 2021, Virtual 315234, International Association of Agricultural Economists.

    Cited by:

    1. Appel, Franziska & Balmann, Alfons & Filler, Günther & Jänicke, Clemens & Odening, Martin & Schmidt, Lorenz, 2023. "Stellungnahme zum Entwurf des Gesetzes zum Erhalt und zur Verbesserung der brandenburgischen Agrarstruktur," FORLand Project Publications 334725, University of Natural Resources and Applied Life Sciences, Vienna, Department of Economics and Social Sciences.
    2. Maximilian Humpesch & Stefan Seifert & Alfons Balmann & Silke Hüttel, 2022. "How does tenancy affect farmland prices? Effects of lease status, lease term and buyer type," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 83(2), pages 242-263, September.

  2. Pates, Nicholas J. & Kim, GwanSeon & Mark, Tyler B. & Ritter, Matthias, 2020. "Windfalls or wind falls? The Local Effects of Turbine Development on US Agricultural Land Values," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304611, Agricultural and Applied Economics Association.

    Cited by:

    1. Marvin Schütt, 2024. "Wind Turbines and Property Values: A Meta-Regression Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(1), pages 1-43, January.

  3. Plogmann, Jana & Mußhoff, Oliver & Odening, Martin & Ritter, Matthias, 2020. "Farm growth and land concentration," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304514, Agricultural and Applied Economics Association.

    Cited by:

    1. Lars Isenhardt & Stefan Seifert & Silke Hüttel, 2023. "Tenant Favoritism and Right of First Refusals in Farmland Auctions: Competition and Price Effects," Land Economics, University of Wisconsin Press, vol. 99(2), pages 302-324.
    2. Valtiala, Juho & Niskanen, Olli & Torvinen, Mikael & Riekkinen, Kirsikka & Suokannas, Antti, 2023. "The relationship between agricultural land parcel size and cultivation costs," Land Use Policy, Elsevier, vol. 131(C).
    3. Luise Meissner & Lisa Kappenberg & Oliver Musshoff, 2022. "An Analytical Framework for Evaluating Farmland Market Regulation: Examining the German Land Transaction Law," Land, MDPI, vol. 11(10), pages 1-12, October.
    4. Hu, Zhenhua & Song, Gaohui & Hu, Ziyue & Fang, Jiaqi, 2024. "An improved dynamic game analysis of farmers, enterprises and rural collective economic organizations based on idle land reuse policy," Land Use Policy, Elsevier, vol. 140(C).
    5. Willem K. Korthals Altes, 2023. "Access to Land: Markets, Policies and Initiatives," Sustainability, MDPI, vol. 15(6), pages 1-20, March.
    6. Kionka, Marlene & Odening, Martin & Plogmann, Jana & Ritter, Matthias, 2021. "Measuring Liquidity in Agricultural Land Markets," 2021 Conference, August 17-31, 2021, Virtual 315234, International Association of Agricultural Economists.
    7. Plogmann, Jana & Mußhoff, Oliver & Odening, Martin & Ritter, Matthias, 2020. "Farm growth and land concentration," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304514, Agricultural and Applied Economics Association.
    8. Marii Rasva & Evelin Jürgenson, 2022. "Europe’s Large-Scale Land Acquisitions and Bibliometric Analysis," Agriculture, MDPI, vol. 12(6), pages 1-13, June.
    9. Jänicke, Clemens & Balmann, Alfons & Müller, Daniel, 2024. "Wem gehört das Land?," FORLand Project Publications 344853, University of Natural Resources and Applied Life Sciences, Vienna, Department of Economics and Social Sciences.
    10. Burchfield, Emily & Ferro, Marco & Hüttel, Silke & Lakes, Tobia Maike & Leonhardt, Heidi & Niedermayr, Andreas & Rissing, Andrea & Seifert, Stefan & Wesemeyer, Maximilian, 2024. "Towards a comprehensive analysis of agricultural land systems: What can we see with publicly available datasets in the EU and US?," FORLand Working Papers 30 (2024), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    11. Chiarella, Cristina & Meyfroidt, Patrick & Abeygunawardane, Dilini & Conforti, Piero, 2023. "Balancing the trade-offs between land productivity, labor productivity and labor intensity," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 52(10), pages 1618-1634.

  4. Ritter, Matthias & Huttel, Silke & Odening, Martin & Seifert, Stefan, 2019. "Revisiting The Relationship Between Land Price And Parcel Size," 2019 Conference (63rd), February 12-15, 2019, Melbourne, Australia 285062, Australian Agricultural and Resource Economics Society (AARES).

    Cited by:

    1. Ritter, Matthias & Hüttel, Silke & Odening, Martin & Seifert, Stefan, 2019. "Revisiting the relationship between land price and parcel size," FORLand Working Papers 08 (2019), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    2. Pates, Nicholas J. & Kim, GwanSeon & Mark, Tyler B. & Ritter, Matthias, 2020. "Windfalls or wind falls? The Local Effects of Turbine Development on US Agricultural Land Values," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304611, Agricultural and Applied Economics Association.

  5. Plogmann, Jana & Mußhoff, Oliver & Odening, Martin & Ritter, Matthias, 2019. "What Moves the German Land Market? A Decomposition of the Land Rent-Price Ratio," 165th Seminar, April 4-5, 2019, Berlin, Germany 288444, European Association of Agricultural Economists.

    Cited by:

    1. Johanna Jauernig & Stephan Brosig & Silke Hüttel, 2023. "Profession and residency matter: Farmers' preferences for farmland price regulation in Germany," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(3), pages 816-834, September.
    2. Graubner, Marten & Hüttel, Silke, 2024. "Rental and sale prices of agricultural lands under spatial competition," FORLand Working Papers 29 (2024), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    3. Schaak, Henning & Mußhoff, Oliver, 2020. "A geoadditive distributional regression analysis of the local relationship of land prices and land rents in Germany," FORLand Working Papers 20 (2020), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    4. Plogmann, Jana & Mußhoff, Oliver & Odening, Martin & Ritter, Matthias, 2019. "What Moves the German Land Market? A Decomposition of the Land Rent-Price Ratio," 165th Seminar, April 4-5, 2019, Berlin, Germany 288444, European Association of Agricultural Economists.
    5. Marten Graubner & Silke Hüttel, 2024. "Rental and sale prices of agricultural lands under spatial competition," Letters in Spatial and Resource Sciences, Springer, vol. 17(1), pages 1-12, December.
    6. Grau, Aaron & Jasic, Svetlana & Ritter, Matthias & Odening, Martin, 2019. "The impact of production intensity on agricultural land prices," FORLand Working Papers 09 (2019), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".

  6. Grau, Aaron & Odening, Martin & Ritter, Matthias, 2018. "Land price diffusion across borders: The case of Germany," FORLand Project Publications 275487, University of Natural Resources and Applied Life Sciences, Vienna, Department of Economics and Social Sciences.

    Cited by:

    1. Lars Isenhardt & Stefan Seifert & Silke Hüttel, 2023. "Tenant Favoritism and Right of First Refusals in Farmland Auctions: Competition and Price Effects," Land Economics, University of Wisconsin Press, vol. 99(2), pages 302-324.
    2. Seifert, Stefan & Hüttel, Silke, 2020. "Common values and unobserved heterogeneity in farmland auctions in Germany," FORLand Working Papers 21 (2020), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    3. Marques, Felipe César & Telles, Tiago Santos, 2023. "Spatial effects are determinants of agricultural land prices in Brazil," Revista de Economia e Sociologia Rural (RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 61(3), January.
    4. Aaron Grau & Martin Odening & Matthias Ritter, 2020. "Land price diffusion across borders – the case of Germany," Applied Economics, Taylor & Francis Journals, vol. 52(50), pages 5446-5463, October.
    5. Mateusz Tomal & Agata Gumieniak, 2020. "Agricultural Land Price Convergence: Evidence from Polish Provinces," Agriculture, MDPI, vol. 10(5), pages 1-20, May.
    6. Barbara Kutkowska & Tomasz Szuk & Stanislaw Minta & Hanna Adamska, 2024. "Land productivity in the EU in the context of financial support through direct subsidies," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 70(9), pages 436-445.
    7. Grau, Aaron & Jasic, Svetlana & Ritter, Matthias & Odening, Martin, 2019. "The impact of production intensity on agricultural land prices," FORLand Working Papers 09 (2019), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    8. Emma Bruno & Rosalia Castellano & Gennaro Punzo & Luca Salvati, 2023. "Towards diverging land prices in agricultural districts? Evidence from Italy before and after the great crisis," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 69(3), pages 119-127.

  7. Yang, Xinyue & Odening, Martin & Ritter, Matthias, 2018. "The Spatial and Temporal Diffusion of Agricultural Land Prices," FORLand Project Publications 275485, University of Natural Resources and Applied Life Sciences, Vienna, Department of Economics and Social Sciences.

    Cited by:

    1. Ritter, Matthias & Hüttel, Silke & Odening, Martin & Seifert, Stefan, 2020. "Revisiting the relationship between land price and parcel size in agriculture," Land Use Policy, Elsevier, vol. 97(C).
    2. Cord-Friedrich von Hobe & Marius Michels & Oliver Musshoff, 2021. "German Farmers’ Perspectives on Price Drivers in Agricultural Land Rental Markets—A Combination of a Systematic Literature Review and Survey Results," Land, MDPI, vol. 10(2), pages 1-22, February.
    3. Ritter, Matthias & Hüttel, Silke & Odening, Martin & Seifert, Stefan, 2019. "Revisiting the relationship between land price and parcel size," FORLand Working Papers 08 (2019), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    4. Pavel Ciaian & Edoardo Baldoni & d'Artis Kancs & Dusan Drabik, 2020. "The Capitalization of Agricultural Subsidies into Land Prices," EERI Research Paper Series EERI RP 2020/09, Economics and Econometrics Research Institute (EERI), Brussels.
    5. Kvartiuk, Vasyl & Herzfeld, Thomas & Bukin, Eduard, 2022. "Decentralized public farmland conveyance: Rental rights auctioning in Ukraine," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 114.
    6. Kionka, Marlene & Odening, Martin & Plogmann, Jana & Ritter, Matthias, 2021. "Measuring Liquidity in Agricultural Land Markets," 2021 Conference, August 17-31, 2021, Virtual 315234, International Association of Agricultural Economists.
    7. Marques, Felipe César & Telles, Tiago Santos, 2023. "Spatial effects are determinants of agricultural land prices in Brazil," Revista de Economia e Sociologia Rural (RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 61(3), January.
    8. Aaron Grau & Martin Odening & Matthias Ritter, 2020. "Land price diffusion across borders – the case of Germany," Applied Economics, Taylor & Francis Journals, vol. 52(50), pages 5446-5463, October.
    9. Mateusz Tomal & Agata Gumieniak, 2020. "Agricultural Land Price Convergence: Evidence from Polish Provinces," Agriculture, MDPI, vol. 10(5), pages 1-20, May.
    10. Jarmila Lazíková & Ľubica Rumanovská & Ivan Takáč & Piotr Prus & Alexander Fehér, 2021. "Regional Differences of Agricultural Land Market in Slovakia: A Challenge for Sustainable Agriculture," Agriculture, MDPI, vol. 11(4), pages 1-20, April.
    11. Song, Malin & Xie, Qianjiao & Chen, Jiandong, 2022. "Effects of government competition on land prices under opening up conditions: A case study of the Huaihe River ecological economic belt," Land Use Policy, Elsevier, vol. 113(C).
    12. Grau, Aaron & Jasic, Svetlana & Ritter, Matthias & Odening, Martin, 2019. "The impact of production intensity on agricultural land prices," FORLand Working Papers 09 (2019), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".

  8. Ritter, Matthias & Helbing, Georg & Shen, Zhiwei & Odening, Martin, 2017. "Estimating Location Values of Agricultural Land," 57th Annual Conference, Weihenstephan, Germany, September 13-15, 2017 261985, German Association of Agricultural Economists (GEWISOLA).

    Cited by:

    1. Ritter, Matthias & Hüttel, Silke & Odening, Martin & Seifert, Stefan, 2020. "Revisiting the relationship between land price and parcel size in agriculture," Land Use Policy, Elsevier, vol. 97(C).
    2. Kolbe, Jens & Schulz, Rainer & Wersing, Martin & Werwatz, Axel, 2019. "Land value appraisal using statistical methods," FORLand Working Papers 07 (2019), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    3. Ritter, Matthias & Hüttel, Silke & Odening, Martin & Seifert, Stefan, 2019. "Revisiting the relationship between land price and parcel size," FORLand Working Papers 08 (2019), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    4. Jens Kolbe & Rainer Schulz & Martin Wersing & Axel Werwatz, 2019. "Bodenwertermittlung mit statistischen Methoden [Land value appraisal using statistical methods]," Zeitschrift für Immobilienökonomie (German Journal of Real Estate Research), Springer;Gesellschaft für Immobilienwirtschaftliche Forschung e. V., vol. 5(1), pages 131-154, November.
    5. Myrna, Olena, 2023. "Competition in online land lease auctions in Ukraine: Reduced-form estimation," Land Use Policy, Elsevier, vol. 125(C).
    6. Xin, Liangjie & Li, Xiubin, 2019. "Rental rates of grain land for consolidated plots and their determinants in present-day China," Land Use Policy, Elsevier, vol. 86(C), pages 421-426.

  9. Ritter, Matthias & Deckert, Lars, 2015. "Site assessment, turbine selection, and local feed-in tariffs through the wind energy index," SFB 649 Discussion Papers 2015-046, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Hoz, Jordi de la & Martín, Helena & Montalà, Montserrat & Matas, José & Guzman, Ramon, 2018. "Assessing the 2014 retroactive regulatory framework applied to the concentrating solar power systems in Spain," Applied Energy, Elsevier, vol. 212(C), pages 1377-1399.
    2. Khalifa Mohammed Al-Sobai & Shaligram Pokharel & Galal M. Abdella, 2020. "Perspectives on the Capabilities for the Selection of Strategic Projects," Sustainability, MDPI, vol. 12(19), pages 1-20, October.
    3. Wen, Yi & Kamranzad, Bahareh & Lin, Pengzhi, 2021. "Assessment of long-term offshore wind energy potential in the south and southeast coasts of China based on a 55-year dataset," Energy, Elsevier, vol. 224(C).
    4. González-Aparicio, I. & Monforti, F. & Volker, P. & Zucker, A. & Careri, F. & Huld, T. & Badger, J., 2017. "Simulating European wind power generation applying statistical downscaling to reanalysis data," Applied Energy, Elsevier, vol. 199(C), pages 155-168.
    5. Ali Mostafaeipour & Mostafa Rezaei & Mehdi Jahangiri & Mojtaba Qolipour, 2020. "Feasibility analysis of a new tree-shaped wind turbine for urban application: A case study," Energy & Environment, , vol. 31(7), pages 1230-1256, November.
    6. Moiz, Abdul & Kawasaki, Akiyuki & Koike, Toshio & Shrestha, Maheswor, 2018. "A systematic decision support tool for robust hydropower site selection in poorly gauged basins," Applied Energy, Elsevier, vol. 224(C), pages 309-321.
    7. Nansheng Pang & Mengfan Nan & Qichen Meng & Siyang Zhao, 2021. "Selection of Wind Turbine Based on Fuzzy Analytic Network Process: A Case Study in China," Sustainability, MDPI, vol. 13(4), pages 1-17, February.
    8. Hain, Martin & Kargus, Tobias & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2022. "An electricity price modeling framework for renewable-dominant markets," Working Paper Series in Production and Energy 66, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    9. Alina Wilke & Zhiwei Shen & Matthias Ritter, 2021. "How Much Can Small-Scale Wind Energy Production Contribute to Energy Supply in Cities? A Case Study of Berlin," Energies, MDPI, vol. 14(17), pages 1-20, September.
    10. Marinić-Kragić, Ivo & Vučina, Damir & Milas, Zoran, 2019. "Concept of flexible vertical-axis wind turbine with numerical simulation and shape optimization," Energy, Elsevier, vol. 167(C), pages 841-852.
    11. Henckes, Philipp & Knaut, Andreas & Obermüller, Frank & Frank, Christopher, 2018. "The benefit of long-term high resolution wind data for electricity system analysis," Energy, Elsevier, vol. 143(C), pages 934-942.
    12. Allen, D.J. & Tomlin, A.S. & Bale, C.S.E. & Skea, A. & Vosper, S. & Gallani, M.L., 2017. "A boundary layer scaling technique for estimating near-surface wind energy using numerical weather prediction and wind map data," Applied Energy, Elsevier, vol. 208(C), pages 1246-1257.
    13. Díaz, Guzmán & Coto, José & Gómez-Aleixandre, Javier, 2019. "Levelized income loss as a metric of the adaptation of wind and energy storage to variable prices," Applied Energy, Elsevier, vol. 238(C), pages 1179-1191.
    14. Hou, Jin & Xu, Peng & Lu, Xing & Pang, Zhihong & Chu, Yiyi & Huang, Gongsheng, 2018. "Implementation of expansion planning in existing district energy system: A case study in China," Applied Energy, Elsevier, vol. 211(C), pages 269-281.
    15. Olena Myrna & Martin Odening & Matthias Ritter, 2019. "The Influence of Wind Energy and Biogas on Farmland Prices," Land, MDPI, vol. 8(1), pages 1-14, January.
    16. Salcedo-Sanz, S. & García-Herrera, R. & Camacho-Gómez, C. & Aybar-Ruíz, A. & Alexandre, E., 2018. "Wind power field reconstruction from a reduced set of representative measuring points," Applied Energy, Elsevier, vol. 228(C), pages 1111-1121.
    17. Lu, Yuehong & Zhang, Xiao-Ping & Huang, Zhijia & Lu, Jinli & Wang, Dong, 2019. "Impact of introducing penalty-cost on optimal design of renewable energy systems for net zero energy buildings," Applied Energy, Elsevier, vol. 235(C), pages 106-116.
    18. Miguel Á. Rodríguez-López & Emilio Cerdá & Pablo del Rio, 2020. "Modeling Wind-Turbine Power Curves: Effects of Environmental Temperature on Wind Energy Generation," Energies, MDPI, vol. 13(18), pages 1-21, September.
    19. Helbing, Georg & Ritter, Matthias, 2018. "Deep Learning for fault detection in wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 189-198.
    20. Henckes, Philipp & Frank, Christopher & Küchler, Nils & Peter, Jakob & Wagner, Johannes, 2020. "Uncertainty estimation of investment planning models under high shares of renewables using reanalysis data," Energy, Elsevier, vol. 208(C).
    21. Ahmadpour, Ali & Mokaramian, Elham & Anderson, Simon, 2021. "The effects of the renewable energies penetration on the surplus welfare under energy policy," Renewable Energy, Elsevier, vol. 164(C), pages 1171-1182.
    22. Hain, Martin & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2017. "An Electricity Price Modeling Framework for Renewable-Dominant Markets," Working Paper Series in Production and Energy 23, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    23. Yılmaz Balaman, Şebnem & Scott, James & Matopoulos, Aristides & Wright, Daniel G., 2019. "Incentivising bioenergy production: Economic and environmental insights from a regional optimization methodology," Renewable Energy, Elsevier, vol. 130(C), pages 867-880.
    24. Reinhold Lehneis & Daniela Thrän, 2023. "Temporally and Spatially Resolved Simulation of the Wind Power Generation in Germany," Energies, MDPI, vol. 16(7), pages 1-16, April.

  10. Odening, Martin & Ritter, Matthias & Hüttel, Silke, 2015. "The term structure of land lease rates," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 201664, Agricultural and Applied Economics Association.

    Cited by:

    1. Johanna CHOUMERT & Pascale PHELINAS, 2015. "Farmland Rental Values in GM Soybean Areas of Argentina: Do Contractual Arrangements Matter?," Working Papers 201532, CERDI.
    2. Shuai Zhou & Guangqing Chi, 2022. "Farmland Rental: The Impacts of Household Demographics and Livelihood Strategies in China," Land, MDPI, vol. 11(8), pages 1-18, August.
    3. Kuethe, Todd H. & Bigelow, Daniel P., 2018. "Bargaining Power in Farmland Rental Markets," 2018 Annual Meeting, August 5-7, Washington, D.C. 274113, Agricultural and Applied Economics Association.

  11. Ritter, Matthias & Deckert, Lars, 2015. "Site assessment, turbine selection, and local feed-in tariffs through the wind energy index," SFB 649 Discussion Papers 2015-046, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Hoz, Jordi de la & Martín, Helena & Montalà, Montserrat & Matas, José & Guzman, Ramon, 2018. "Assessing the 2014 retroactive regulatory framework applied to the concentrating solar power systems in Spain," Applied Energy, Elsevier, vol. 212(C), pages 1377-1399.
    2. Khalifa Mohammed Al-Sobai & Shaligram Pokharel & Galal M. Abdella, 2020. "Perspectives on the Capabilities for the Selection of Strategic Projects," Sustainability, MDPI, vol. 12(19), pages 1-20, October.
    3. Wen, Yi & Kamranzad, Bahareh & Lin, Pengzhi, 2021. "Assessment of long-term offshore wind energy potential in the south and southeast coasts of China based on a 55-year dataset," Energy, Elsevier, vol. 224(C).
    4. González-Aparicio, I. & Monforti, F. & Volker, P. & Zucker, A. & Careri, F. & Huld, T. & Badger, J., 2017. "Simulating European wind power generation applying statistical downscaling to reanalysis data," Applied Energy, Elsevier, vol. 199(C), pages 155-168.
    5. Ali Mostafaeipour & Mostafa Rezaei & Mehdi Jahangiri & Mojtaba Qolipour, 2020. "Feasibility analysis of a new tree-shaped wind turbine for urban application: A case study," Energy & Environment, , vol. 31(7), pages 1230-1256, November.
    6. Moiz, Abdul & Kawasaki, Akiyuki & Koike, Toshio & Shrestha, Maheswor, 2018. "A systematic decision support tool for robust hydropower site selection in poorly gauged basins," Applied Energy, Elsevier, vol. 224(C), pages 309-321.
    7. Nansheng Pang & Mengfan Nan & Qichen Meng & Siyang Zhao, 2021. "Selection of Wind Turbine Based on Fuzzy Analytic Network Process: A Case Study in China," Sustainability, MDPI, vol. 13(4), pages 1-17, February.
    8. Hain, Martin & Kargus, Tobias & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2022. "An electricity price modeling framework for renewable-dominant markets," Working Paper Series in Production and Energy 66, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    9. Alina Wilke & Zhiwei Shen & Matthias Ritter, 2021. "How Much Can Small-Scale Wind Energy Production Contribute to Energy Supply in Cities? A Case Study of Berlin," Energies, MDPI, vol. 14(17), pages 1-20, September.
    10. Marinić-Kragić, Ivo & Vučina, Damir & Milas, Zoran, 2019. "Concept of flexible vertical-axis wind turbine with numerical simulation and shape optimization," Energy, Elsevier, vol. 167(C), pages 841-852.
    11. Henckes, Philipp & Knaut, Andreas & Obermüller, Frank & Frank, Christopher, 2018. "The benefit of long-term high resolution wind data for electricity system analysis," Energy, Elsevier, vol. 143(C), pages 934-942.
    12. Allen, D.J. & Tomlin, A.S. & Bale, C.S.E. & Skea, A. & Vosper, S. & Gallani, M.L., 2017. "A boundary layer scaling technique for estimating near-surface wind energy using numerical weather prediction and wind map data," Applied Energy, Elsevier, vol. 208(C), pages 1246-1257.
    13. Díaz, Guzmán & Coto, José & Gómez-Aleixandre, Javier, 2019. "Levelized income loss as a metric of the adaptation of wind and energy storage to variable prices," Applied Energy, Elsevier, vol. 238(C), pages 1179-1191.
    14. Hou, Jin & Xu, Peng & Lu, Xing & Pang, Zhihong & Chu, Yiyi & Huang, Gongsheng, 2018. "Implementation of expansion planning in existing district energy system: A case study in China," Applied Energy, Elsevier, vol. 211(C), pages 269-281.
    15. Olena Myrna & Martin Odening & Matthias Ritter, 2019. "The Influence of Wind Energy and Biogas on Farmland Prices," Land, MDPI, vol. 8(1), pages 1-14, January.
    16. Salcedo-Sanz, S. & García-Herrera, R. & Camacho-Gómez, C. & Aybar-Ruíz, A. & Alexandre, E., 2018. "Wind power field reconstruction from a reduced set of representative measuring points," Applied Energy, Elsevier, vol. 228(C), pages 1111-1121.
    17. Lu, Yuehong & Zhang, Xiao-Ping & Huang, Zhijia & Lu, Jinli & Wang, Dong, 2019. "Impact of introducing penalty-cost on optimal design of renewable energy systems for net zero energy buildings," Applied Energy, Elsevier, vol. 235(C), pages 106-116.
    18. Miguel Á. Rodríguez-López & Emilio Cerdá & Pablo del Rio, 2020. "Modeling Wind-Turbine Power Curves: Effects of Environmental Temperature on Wind Energy Generation," Energies, MDPI, vol. 13(18), pages 1-21, September.
    19. Helbing, Georg & Ritter, Matthias, 2018. "Deep Learning for fault detection in wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 189-198.
    20. Henckes, Philipp & Frank, Christopher & Küchler, Nils & Peter, Jakob & Wagner, Johannes, 2020. "Uncertainty estimation of investment planning models under high shares of renewables using reanalysis data," Energy, Elsevier, vol. 208(C).
    21. Ahmadpour, Ali & Mokaramian, Elham & Anderson, Simon, 2021. "The effects of the renewable energies penetration on the surplus welfare under energy policy," Renewable Energy, Elsevier, vol. 164(C), pages 1171-1182.
    22. Hain, Martin & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2017. "An Electricity Price Modeling Framework for Renewable-Dominant Markets," Working Paper Series in Production and Energy 23, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    23. Yılmaz Balaman, Şebnem & Scott, James & Matopoulos, Aristides & Wright, Daniel G., 2019. "Incentivising bioenergy production: Economic and environmental insights from a regional optimization methodology," Renewable Energy, Elsevier, vol. 130(C), pages 867-880.
    24. Reinhold Lehneis & Daniela Thrän, 2023. "Temporally and Spatially Resolved Simulation of the Wind Power Generation in Germany," Energies, MDPI, vol. 16(7), pages 1-16, April.

  12. Pieralli, Simone & Ritter, Matthias & Odening, Martin, 2015. "Efficiency of Wind Power Production and its Determinants," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205415, Agricultural and Applied Economics Association.

    Cited by:

    1. Sonja Germer & Axel Kleidon, 2019. "Have wind turbines in Germany generated electricity as would be expected from the prevailing wind conditions in 2000-2014?," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-16, February.
    2. Xiaoyan Sun & Wenwei Lian & Hongmei Duan & Anjian Wang, 2021. "Factors Affecting Wind Power Efficiency: Evidence from Provincial-Level Data in China," Sustainability, MDPI, vol. 13(22), pages 1-17, November.
    3. Hain, Martin & Kargus, Tobias & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2022. "An electricity price modeling framework for renewable-dominant markets," Working Paper Series in Production and Energy 66, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    4. Matthias Ritter & Simone Pieralli & Martin Odening, 2017. "Neighborhood Effects in Wind Farm Performance: A Regression Approach," Energies, MDPI, vol. 10(3), pages 1-16, March.
    5. Carlini, Federico & Christensen, Bent Jesper & Datta Gupta, Nabanita & Santucci de Magistris, Paolo, 2023. "Climate, wind energy, and CO2 emissions from energy production in Denmark," Energy Economics, Elsevier, vol. 125(C).
    6. Tuka N Fattal, 2018. "Increasing Wind Turbine Efficiency," International Journal of Technology and Engineering Studies, PROF.IR.DR.Mohid Jailani Mohd Nor, vol. 4(4), pages 120-131.
    7. Yanwei Jing & Hexu Sun & Lei Zhang & Tieling Zhang, 2017. "Variable Speed Control of Wind Turbines Based on the Quasi-Continuous High-Order Sliding Mode Method," Energies, MDPI, vol. 10(10), pages 1-21, October.
    8. Hain, Martin & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2017. "An Electricity Price Modeling Framework for Renewable-Dominant Markets," Working Paper Series in Production and Energy 23, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    9. Ritter, Matthias & Pieralli, Simone & Odening, Martin, 2016. "Neighborhood effects in wind farm performance: An econometric approach," SFB 649 Discussion Papers 2016-012, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    10. Bent Jesper Christensen & Nabanita Datta Gupta & Paolo Santucci de Magistris, 2021. "Measuring the impact of clean energy production on CO2 abatement in Denmark: Upper bound estimation and forecasting," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 118-149, January.

  13. Pieralli, Simone & Ritter, Matthias & Odening, Martin, 2015. "Efficiency of wind power production and its determinants," SFB 649 Discussion Papers 2015-004, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Sonja Germer & Axel Kleidon, 2019. "Have wind turbines in Germany generated electricity as would be expected from the prevailing wind conditions in 2000-2014?," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-16, February.
    2. Xiaoyan Sun & Wenwei Lian & Hongmei Duan & Anjian Wang, 2021. "Factors Affecting Wind Power Efficiency: Evidence from Provincial-Level Data in China," Sustainability, MDPI, vol. 13(22), pages 1-17, November.
    3. Hain, Martin & Kargus, Tobias & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2022. "An electricity price modeling framework for renewable-dominant markets," Working Paper Series in Production and Energy 66, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    4. Matthias Ritter & Simone Pieralli & Martin Odening, 2017. "Neighborhood Effects in Wind Farm Performance: A Regression Approach," Energies, MDPI, vol. 10(3), pages 1-16, March.
    5. Carlini, Federico & Christensen, Bent Jesper & Datta Gupta, Nabanita & Santucci de Magistris, Paolo, 2023. "Climate, wind energy, and CO2 emissions from energy production in Denmark," Energy Economics, Elsevier, vol. 125(C).
    6. Tuka N Fattal, 2018. "Increasing Wind Turbine Efficiency," International Journal of Technology and Engineering Studies, PROF.IR.DR.Mohid Jailani Mohd Nor, vol. 4(4), pages 120-131.
    7. Yanwei Jing & Hexu Sun & Lei Zhang & Tieling Zhang, 2017. "Variable Speed Control of Wind Turbines Based on the Quasi-Continuous High-Order Sliding Mode Method," Energies, MDPI, vol. 10(10), pages 1-21, October.
    8. Hain, Martin & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2017. "An Electricity Price Modeling Framework for Renewable-Dominant Markets," Working Paper Series in Production and Energy 23, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    9. Ritter, Matthias & Pieralli, Simone & Odening, Martin, 2016. "Neighborhood effects in wind farm performance: An econometric approach," SFB 649 Discussion Papers 2016-012, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    10. Bent Jesper Christensen & Nabanita Datta Gupta & Paolo Santucci de Magistris, 2021. "Measuring the impact of clean energy production on CO2 abatement in Denmark: Upper bound estimation and forecasting," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 118-149, January.

  14. Shen, Zhiwei & Ritter, Matthias, 2015. "Forecasting volatility of wind power production," SFB 649 Discussion Papers 2015-026, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Erick López & Carlos Valle & Héctor Allende & Esteban Gil & Henrik Madsen, 2018. "Wind Power Forecasting Based on Echo State Networks and Long Short-Term Memory," Energies, MDPI, vol. 11(3), pages 1-22, February.
    2. Li, Dan & Jiang, Fuxin & Chen, Min & Qian, Tao, 2022. "Multi-step-ahead wind speed forecasting based on a hybrid decomposition method and temporal convolutional networks," Energy, Elsevier, vol. 238(PC).
    3. Zonggui Yao & Chen Wang, 2018. "A Hybrid Model Based on A Modified Optimization Algorithm and An Artificial Intelligence Algorithm for Short-Term Wind Speed Multi-Step Ahead Forecasting," Sustainability, MDPI, vol. 10(5), pages 1-33, May.
    4. Akbal, Yıldırım & Ünlü, Kamil Demirberk, 2022. "A univariate time series methodology based on sequence-to-sequence learning for short to midterm wind power production," Renewable Energy, Elsevier, vol. 200(C), pages 832-844.
    5. Wang, Xiaodi & Hao, Yan & Yang, Wendong, 2024. "Novel wind power ensemble forecasting system based on mixed-frequency modeling and interpretable base model selection strategy," Energy, Elsevier, vol. 297(C).
    6. Wasilewski, J. & Baczynski, D., 2017. "Short-term electric energy production forecasting at wind power plants in pareto-optimality context," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 177-187.
    7. Ren, Guorui & Wan, Jie & Liu, Jinfu & Yu, Daren, 2019. "Spatial and temporal assessments of complementarity for renewable energy resources in China," Energy, Elsevier, vol. 177(C), pages 262-275.
    8. Hugo T. V. Gouveia & Murilo A. Souza & Aida A. Ferreira & Jonata C. de Albuquerque & Otoni Nóbrega Neto & Milde Maria da Silva Lira & Ronaldo R. B. de Aquino, 2023. "Application of Augmented Echo State Networks and Genetic Algorithm to Improve Short-Term Wind Speed Forecasting," Energies, MDPI, vol. 16(6), pages 1-15, March.
    9. Bonou, Alexandra & Laurent, Alexis & Olsen, Stig I., 2016. "Life cycle assessment of onshore and offshore wind energy-from theory to application," Applied Energy, Elsevier, vol. 180(C), pages 327-337.
    10. Sherzod N. Tashpulatov, 2021. "The Impact of Regulatory Reforms on Demand Weighted Average Prices," Mathematics, MDPI, vol. 9(10), pages 1-15, May.
    11. Lucheroni, Carlo & Boland, John & Ragno, Costantino, 2019. "Scenario generation and probabilistic forecasting analysis of spatio-temporal wind speed series with multivariate autoregressive volatility models," Applied Energy, Elsevier, vol. 239(C), pages 1226-1241.
    12. Fu, Yang & Zheng, Zeyu, 2020. "Volatility modeling and the asymmetric effect for China’s carbon trading pilot market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    13. Dokur, Emrah & Erdogan, Nuh & Salari, Mahdi Ebrahimi & Karakuzu, Cihan & Murphy, Jimmy, 2022. "Offshore wind speed short-term forecasting based on a hybrid method: Swarm decomposition and meta-extreme learning machine," Energy, Elsevier, vol. 248(C).
    14. Gong, Xu & Wen, Fenghua & Xia, X.H. & Huang, Jianbai & Pan, Bin, 2017. "Investigating the risk-return trade-off for crude oil futures using high-frequency data," Applied Energy, Elsevier, vol. 196(C), pages 152-161.
    15. Ren, Guorui & Wan, Jie & Liu, Jinfu & Yu, Daren, 2020. "Spatial and temporal correlation analysis of wind power between different provinces in China," Energy, Elsevier, vol. 191(C).
    16. Liu, Liuchen & Zhu, Tong & Pan, Yu & Wang, Hai, 2017. "Multiple energy complementation based on distributed energy systems – Case study of Chongming county, China," Applied Energy, Elsevier, vol. 192(C), pages 329-336.
    17. Ahmed, Adil & Khalid, Muhammad, 2018. "An intelligent framework for short-term multi-step wind speed forecasting based on Functional Networks," Applied Energy, Elsevier, vol. 225(C), pages 902-911.
    18. Ahmed, Adil & Khalid, Muhammad, 2019. "A review on the selected applications of forecasting models in renewable power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 9-21.
    19. Sherzod N. Tashpulatov, 2021. "Modeling and Estimating Volatility of Day-Ahead Electricity Prices," Mathematics, MDPI, vol. 9(7), pages 1-11, March.
    20. Fu, Wenlong & Zhang, Kai & Wang, Kai & Wen, Bin & Fang, Ping & Zou, Feng, 2021. "A hybrid approach for multi-step wind speed forecasting based on two-layer decomposition, improved hybrid DE-HHO optimization and KELM," Renewable Energy, Elsevier, vol. 164(C), pages 211-229.
    21. Danyan Wen & Mengxi He & Yaojie Zhang & Yudong Wang, 2022. "Forecasting realized volatility of Chinese stock market: A simple but efficient truncated approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 230-251, March.

  15. Ritter, Matthias & Shen, Zhiwei & López Cabrera, Brenda & Odening, Martin & Deckert, Lars, 2014. "Designing an index for assessing wind energy potential," SFB 649 Discussion Papers 2014-052, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Li, Jiale & Yu, Xiong (Bill), 2018. "Onshore and offshore wind energy potential assessment near Lake Erie shoreline: A spatial and temporal analysis," Energy, Elsevier, vol. 147(C), pages 1092-1107.
    2. Lledó, Ll. & Torralba, V. & Soret, A. & Ramon, J. & Doblas-Reyes, F.J., 2019. "Seasonal forecasts of wind power generation," Renewable Energy, Elsevier, vol. 143(C), pages 91-100.
    3. Engelhorn, Thorsten & Müsgens, Felix, 2018. "How to estimate wind-turbine infeed with incomplete stock data: A general framework with an application to turbine-specific market values in Germany," Energy Economics, Elsevier, vol. 72(C), pages 542-557.
    4. Melzer, Awdesch & Härdle, Wolfgang Karl & López Cabrera, Brenda, 2017. "Pricing Green Financial Products," SFB 649 Discussion Papers 2017-020, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Ramirez Camargo, Luis & Gruber, Katharina & Nitsch, Felix, 2019. "Assessing variables of regional reanalysis data sets relevant for modelling small-scale renewable energy systems," Renewable Energy, Elsevier, vol. 133(C), pages 1468-1478.
    6. Ritter, Matthias & Deckert, Lars, 2015. "Site assessment, turbine selection, and local feed-in tariffs through the wind energy index," SFB 649 Discussion Papers 2015-046, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    7. Shen, Zhiwei & Ritter, Matthias, 2016. "Forecasting volatility of wind power production," Applied Energy, Elsevier, vol. 176(C), pages 295-308.
    8. Laudari, R. & Sapkota, B. & Banskota, K., 2018. "Validation of wind resource in 14 locations of Nepal," Renewable Energy, Elsevier, vol. 119(C), pages 777-786.
    9. Alina Wilke & Paul J.J. Welfens, 2020. "Urban Wind Energy Production Potential: New Opportunities," EIIW Discussion paper disbei287, Universitätsbibliothek Wuppertal, University Library.
    10. Tajeddin, Alireza & Fazelpour, Farivar, 2016. "Towards realistic design of wind dams: An innovative approach to enhance wind potential," Applied Energy, Elsevier, vol. 182(C), pages 282-298.
    11. Hain, Martin & Kargus, Tobias & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2022. "An electricity price modeling framework for renewable-dominant markets," Working Paper Series in Production and Energy 66, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    12. Matthias Ritter & Simone Pieralli & Martin Odening, 2017. "Neighborhood Effects in Wind Farm Performance: A Regression Approach," Energies, MDPI, vol. 10(3), pages 1-16, March.
    13. Díaz, Guzmán & Coto, José & Gómez-Aleixandre, Javier, 2019. "Levelized income loss as a metric of the adaptation of wind and energy storage to variable prices," Applied Energy, Elsevier, vol. 238(C), pages 1179-1191.
    14. Mohamed Elnaggar & Ezzaldeen Edwan & Matthias Ritter, 2017. "Wind Energy Potential of Gaza Using Small Wind Turbines: A Feasibility Study," Energies, MDPI, vol. 10(8), pages 1-13, August.
    15. Wolfgang Karl Härdle & Brenda López Cabrera & Awdesch Melzer, 2021. "Pricing wind power futures," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 1083-1102, August.
    16. Zhang, Yi & Cheng, Chuntian & Yang, Tiantian & Jin, Xiaoyu & Jia, Zebin & Shen, Jianjian & Wu, Xinyu, 2022. "Assessment of climate change impacts on the hydro-wind-solar energy supply system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    17. Murthy, K.S.R. & Rahi, O.P., 2016. "Preliminary assessment of wind power potential over the coastal region of Bheemunipatnam in northern Andhra Pradesh, India," Renewable Energy, Elsevier, vol. 99(C), pages 1137-1145.
    18. Hain, Martin & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2017. "An Electricity Price Modeling Framework for Renewable-Dominant Markets," Working Paper Series in Production and Energy 23, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    19. Gualtieri, G., 2022. "Analysing the uncertainties of reanalysis data used for wind resource assessment: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).

  16. Cao, Xiaofeng & Okhrin, Ostap & Odening, Martin & Ritter, Matthias, 2014. "Modelling spatiotemporal variability of temperature," SFB 649 Discussion Papers 2014-020, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Monbet, Valérie & Ailliot, Pierre, 2017. "Sparse vector Markov switching autoregressive models. Application to multivariate time series of temperature," Computational Statistics & Data Analysis, Elsevier, vol. 108(C), pages 40-51.
    2. Ostap Okhrin & Stefan Trück, 2015. "Editorial to the special issue on Applicable semiparametrics of computational statistics," Computational Statistics, Springer, vol. 30(3), pages 641-646, September.

  17. Cao, Xiaofeng & Okhrin, Ostap & Odening, Martin & Ritter, Matthias, 2014. "Modelling spatiotemporal variability of temperature," SFB 649 Discussion Papers 2014-020, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Monbet, Valérie & Ailliot, Pierre, 2017. "Sparse vector Markov switching autoregressive models. Application to multivariate time series of temperature," Computational Statistics & Data Analysis, Elsevier, vol. 108(C), pages 40-51.
    2. Ostap Okhrin & Stefan Trück, 2015. "Editorial to the special issue on Applicable semiparametrics of computational statistics," Computational Statistics, Springer, vol. 30(3), pages 641-646, September.

  18. López Cabrera, Brenda & Odening, Martin & Ritter, Matthias, 2013. "Pricing rainfall derivatives at the CME," SFB 649 Discussion Papers 2013-005, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Poeschel, Friedrich, 2012. "Assortative matching through signals," IAB-Discussion Paper 201215, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    2. Nelson Christopher Dzupire & Philip Ngare & Leo Odongo, 2019. "Pricing Basket Weather Derivatives on Rainfall and Temperature Processes," IJFS, MDPI, vol. 7(3), pages 1-14, June.
    3. Bressan, Giacomo Maria & Romagnoli, Silvia, 2021. "Climate risks and weather derivatives: A copula-based pricing model," Journal of Financial Stability, Elsevier, vol. 54(C).
    4. Evarest Emmanuel & Berntsson Fredrik & Singull Martin & Yang Xiangfeng, 2018. "Weather derivatives pricing using regime switching model," Monte Carlo Methods and Applications, De Gruyter, vol. 24(1), pages 13-27, March.
    5. Andrea Martínez Salgueiro & Maria-Antonia Tarrazon-Rodon, 2021. "Weather derivatives to mitigate meteorological risks in tourism management: An empirical application to celebrations of Comunidad Valenciana (Spain)," Tourism Economics, , vol. 27(4), pages 591-613, June.
    6. Andrea Martínez Salgueiro & Maria-Antonia Tarrazon-Rodon, 2020. "Approaching rainfall-based weather derivatives pricing and operational challenges," Review of Derivatives Research, Springer, vol. 23(2), pages 163-190, July.

  19. López Cabrera, Brenda & Odening, Martin & Ritter, Matthias, 2013. "Pricing rainfall derivatives at the CME," SFB 649 Discussion Papers 2013-005, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Poeschel, Friedrich, 2012. "Assortative matching through signals," IAB-Discussion Paper 201215, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    2. Nelson Christopher Dzupire & Philip Ngare & Leo Odongo, 2019. "Pricing Basket Weather Derivatives on Rainfall and Temperature Processes," IJFS, MDPI, vol. 7(3), pages 1-14, June.
    3. Bressan, Giacomo Maria & Romagnoli, Silvia, 2021. "Climate risks and weather derivatives: A copula-based pricing model," Journal of Financial Stability, Elsevier, vol. 54(C).
    4. Evarest Emmanuel & Berntsson Fredrik & Singull Martin & Yang Xiangfeng, 2018. "Weather derivatives pricing using regime switching model," Monte Carlo Methods and Applications, De Gruyter, vol. 24(1), pages 13-27, March.
    5. Andrea Martínez Salgueiro & Maria-Antonia Tarrazon-Rodon, 2021. "Weather derivatives to mitigate meteorological risks in tourism management: An empirical application to celebrations of Comunidad Valenciana (Spain)," Tourism Economics, , vol. 27(4), pages 591-613, June.
    6. Andrea Martínez Salgueiro & Maria-Antonia Tarrazon-Rodon, 2020. "Approaching rainfall-based weather derivatives pricing and operational challenges," Review of Derivatives Research, Springer, vol. 23(2), pages 163-190, July.

  20. Härdle, Wolfgang Karl & López-Cabrera, Brenda & Ritter, Matthias, 2012. "Forecast based pricing of weather derivatives," SFB 649 Discussion Papers 2012-027, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Füss, Roland & Mahringer, Steffen & Prokopczuk, Marcel, 2013. "Electricity Derivatives Pricing with Forward-Looking Information," Working Papers on Finance 1317, University of St. Gallen, School of Finance.
    2. López Cabrera, Brenda & Odening, Martin & Ritter, Matthias, 2013. "Pricing rainfall futures at the CME," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4286-4298.
    3. G. Geoffrey Booth & Sanders S. Chang, 2017. "Domestic exchange rate determination in Renaissance Florence," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 11(3), pages 405-445, September.
    4. Cobuloglu, Halil I. & Büyüktahtakın, İ. Esra, 2015. "Food vs. biofuel: An optimization approach to the spatio-temporal analysis of land-use competition and environmental impacts," Applied Energy, Elsevier, vol. 140(C), pages 418-434.
    5. Sinha, Pankaj & Nagarnaik, Ankit & Raj, Kislay & Suman, Vineeta, 2016. "Forecasting United States Presidential election 2016 using multiple regression models," MPRA Paper 74641, University Library of Munich, Germany, revised 17 Oct 2016.
    6. López Cabrera, Brenda & Odening, Martin & Ritter, Matthias, 2013. "Pricing rainfall derivatives at the CME," SFB 649 Discussion Papers 2013-005, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    7. Groll, Andreas & López-Cabrera, Brenda & Meyer-Brandis, Thilo, 2016. "A consistent two-factor model for pricing temperature derivatives," Energy Economics, Elsevier, vol. 55(C), pages 112-126.
    8. Peng Li, 2021. "The Valuation of Weather Derivatives Using One Sided Crank–Nicolson Schemes," Computational Economics, Springer;Society for Computational Economics, vol. 58(3), pages 825-847, October.

  21. Ritter, Matthias & Musshoff, Oliver & Odening, Martin, 2012. "Minimizing geographical basis risk of weather derivatives using a multi-site rainfall model," 123rd Seminar, February 23-24, 2012, Dublin, Ireland 122527, European Association of Agricultural Economists.

    Cited by:

    1. Ceballos, Francisco, 2016. "Estimating spatial basis risk in rainfall index insurance: Methodology and application to excess rainfall insurance in Uruguay," IFPRI discussion papers 1595, International Food Policy Research Institute (IFPRI).
    2. López Cabrera, Brenda & Odening, Martin & Ritter, Matthias, 2013. "Pricing rainfall futures at the CME," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4286-4298.
    3. Matthieu Stigler & David Lobell, 2024. "Optimal index insurance and basis risk decomposition: an application to Kenya," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(1), pages 306-329, January.
    4. Schmidt, Lorenz & Odening, Martin & Schlanstein, Johann & Ritter, Matthias, 2022. "Exploring the weather-yield nexus with artificial neural networks," Agricultural Systems, Elsevier, vol. 196(C).
    5. Cao, Xiaofeng & Okhrin, Ostap & Odening, Martin & Ritter, Matthias, 2014. "Modelling spatiotemporal variability of temperature," SFB 649 Discussion Papers 2014-020, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    6. López Cabrera, Brenda & Odening, Martin & Ritter, Matthias, 2013. "Pricing rainfall derivatives at the CME," SFB 649 Discussion Papers 2013-005, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    7. Goodrich, Brittney K. & Davidson, Kelly A., . "Enrollment in Pasture, Rangeland, and Forage Rainfall Index Insurance: Awareness Matters," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 49(2).
    8. Doms, Juliane, 2017. "Put, call or strangle? About the challenges in designing weather index insurances to hedge performance risk in agriculture," 57th Annual Conference, Weihenstephan, Germany, September 13-15, 2017 261990, German Association of Agricultural Economists (GEWISOLA).
    9. Hang Gao & Shuohua Yang & Xinli Liu, 2024. "Managing Basis Risks in Weather Parametric Insurance: A Quantitative Study of Diversification and Key Influencing Factors," Papers 2409.16599, arXiv.org.

  22. Ritter, Matthias & Mußhoff, Oliver & Odening, Martin, 2010. "Meteorological forecasts and the pricing of weather derivatives," SFB 649 Discussion Papers 2010-043, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Rui Zhou & Johnny Siu-Hang Li & Jeffrey Pai, 2019. "Pricing temperature derivatives with a filtered historical simulation approach," The European Journal of Finance, Taylor & Francis Journals, vol. 25(15), pages 1462-1484, October.
    2. Füss, Roland & Mahringer, Steffen & Prokopczuk, Marcel, 2013. "Electricity Derivatives Pricing with Forward-Looking Information," Working Papers on Finance 1317, University of St. Gallen, School of Finance.
    3. López Cabrera, Brenda & Odening, Martin & Ritter, Matthias, 2013. "Pricing rainfall futures at the CME," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4286-4298.
    4. Ritter, Matthias, 2012. "Can the market forecast the weather better than meteorologists?," SFB 649 Discussion Papers 2012-067, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. López Cabrera, Brenda & Odening, Martin & Ritter, Matthias, 2013. "Pricing rainfall derivatives at the CME," SFB 649 Discussion Papers 2013-005, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    6. Härdle, Wolfgang Karl & López-Cabrera, Brenda & Ritter, Matthias, 2012. "Forecast based pricing of weather derivatives," SFB 649 Discussion Papers 2012-027, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    7. Groll, Andreas & López-Cabrera, Brenda & Meyer-Brandis, Thilo, 2016. "A consistent two-factor model for pricing temperature derivatives," Energy Economics, Elsevier, vol. 55(C), pages 112-126.

  23. Ritter, Matthias & Mußhoff, Oliver & Odening, Martin, 2010. "Meteorological forecasts and the pricing of weather derivatives," SFB 649 Discussion Papers 2010-043, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Rui Zhou & Johnny Siu-Hang Li & Jeffrey Pai, 2019. "Pricing temperature derivatives with a filtered historical simulation approach," The European Journal of Finance, Taylor & Francis Journals, vol. 25(15), pages 1462-1484, October.
    2. Füss, Roland & Mahringer, Steffen & Prokopczuk, Marcel, 2013. "Electricity Derivatives Pricing with Forward-Looking Information," Working Papers on Finance 1317, University of St. Gallen, School of Finance.
    3. López Cabrera, Brenda & Odening, Martin & Ritter, Matthias, 2013. "Pricing rainfall futures at the CME," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4286-4298.
    4. Ritter, Matthias, 2012. "Can the market forecast the weather better than meteorologists?," SFB 649 Discussion Papers 2012-067, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. López Cabrera, Brenda & Odening, Martin & Ritter, Matthias, 2013. "Pricing rainfall derivatives at the CME," SFB 649 Discussion Papers 2013-005, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    6. Härdle, Wolfgang Karl & López-Cabrera, Brenda & Ritter, Matthias, 2012. "Forecast based pricing of weather derivatives," SFB 649 Discussion Papers 2012-027, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    7. Groll, Andreas & López-Cabrera, Brenda & Meyer-Brandis, Thilo, 2016. "A consistent two-factor model for pricing temperature derivatives," Energy Economics, Elsevier, vol. 55(C), pages 112-126.

Articles

  1. Plogmann, Jana & Mußhoff, Oliver & Odening, Martin & Ritter, Matthias, 2022. "Farmland sales under returns and price uncertainty," Economic Modelling, Elsevier, vol. 117(C).

    Cited by:

    1. Ting Du & Chao Li & Zhaolin Wang, 2023. "Spatial Differentiation and Influencing Mechanisms of Farmland Transfer Rents in Mountainous Areas: Evidence from Chongqing and Its Surrounding Areas," Land, MDPI, vol. 12(3), pages 1-19, March.

  2. Plogmann, Jana & Mußhoff, Oliver & Odening, Martin & Ritter, Matthias, 2022. "Farm growth and land concentration," Land Use Policy, Elsevier, vol. 115(C).
    See citations under working paper version above.
  3. Schmidt, Lorenz & Odening, Martin & Schlanstein, Johann & Ritter, Matthias, 2022. "Exploring the weather-yield nexus with artificial neural networks," Agricultural Systems, Elsevier, vol. 196(C).

    Cited by:

    1. Nordmeyer, Eike Florenz & Danne, Michael & Musshoff, Oliver, 2023. "Can satellite-retrieved data increase farmers' willingness to insure against drought? – Insights from Germany," Agricultural Systems, Elsevier, vol. 211(C).

  4. Alina Wilke & Zhiwei Shen & Matthias Ritter, 2021. "How Much Can Small-Scale Wind Energy Production Contribute to Energy Supply in Cities? A Case Study of Berlin," Energies, MDPI, vol. 14(17), pages 1-20, September.

    Cited by:

    1. Yi Song Liu & Tan Yigitcanlar & Mirko Guaralda & Kenan Degirmenci & Aaron Liu & Michael Kane, 2022. "Leveraging the Opportunities of Wind for Cities through Urban Planning and Design: A PRISMA Review," Sustainability, MDPI, vol. 14(18), pages 1-78, September.

  5. Balmann, Alfons & Graubner, Marten & Müller, Daniel & Hüttel, Silke & Seifert, Stefan & Odening, Martin & Plogmann, Jana & Ritter, Matthias, 2021. "Market Power in Agricultural Land Markets: Concepts and Empirical Challenges," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 70(04), January.

    Cited by:

    1. Seifert, Stefan & Wolff, Saskia & Hüttel, Silke, 2023. "Eco-Efficiency of Agricultural Landscapes--Insights from North Rhine-Westphalia, Germany," GEWISOLA 63rd Annual Conference, Goettingen, Germany, September 20-22, 2023 344236, GEWISOLA.
    2. Kvartiuk, Vasyl & Bukin, Eduard & Herzfeld, Thomas, 2024. "“For whoever has will be given more”? Land rental decisions and technical efficiency in Ukraine," Land Use Policy, Elsevier, vol. 146(C).
    3. Marten Graubner & Silke Hüttel, 2024. "Rental and sale prices of agricultural lands under spatial competition," Letters in Spatial and Resource Sciences, Springer, vol. 17(1), pages 1-12, December.

  6. Marlene Kionka & Martin Odening & Jana Plogmann & Matthias Ritter, 2021. "Measuring liquidity in agricultural land markets," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 82(4), pages 690-713, September.
    See citations under working paper version above.
  7. Ritter, Matthias & Hüttel, Silke & Odening, Martin & Seifert, Stefan, 2020. "Revisiting the relationship between land price and parcel size in agriculture," Land Use Policy, Elsevier, vol. 97(C).

    Cited by:

    1. Lars Isenhardt & Stefan Seifert & Silke Hüttel, 2023. "Tenant Favoritism and Right of First Refusals in Farmland Auctions: Competition and Price Effects," Land Economics, University of Wisconsin Press, vol. 99(2), pages 302-324.
    2. Valtiala, Juho & Niskanen, Olli & Torvinen, Mikael & Riekkinen, Kirsikka & Suokannas, Antti, 2023. "The relationship between agricultural land parcel size and cultivation costs," Land Use Policy, Elsevier, vol. 131(C).
    3. Plogmann, Jana & Mußhoff, Oliver & Odening, Martin & Ritter, Matthias, 2022. "Farmland sales under returns and price uncertainty," Economic Modelling, Elsevier, vol. 117(C).
    4. Maximilian Humpesch & Stefan Seifert & Alfons Balmann & Silke Hüttel, 2022. "How does tenancy affect farmland prices? Effects of lease status, lease term and buyer type," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 83(2), pages 242-263, September.
    5. Stefan Seifert & Christoph Kahle & Silke Hüttel, 2021. "Price Dispersion in Farmland Markets: What Is the Role of Asymmetric Information?," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(4), pages 1545-1568, August.
    6. Robert Finger & Carola Grebitus & Arne Henningsen, 2023. "Replications in agricultural economics," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 45(3), pages 1258-1274, September.
    7. Isenhardt, Lars & Seifert, Stefan & Hüttel, Silke, 2021. "On the price effect of a right of first refusal in farmland auctions," 61st Annual Conference, Berlin, Germany, September 22-24, 2021 317062, German Association of Agricultural Economists (GEWISOLA).
    8. Pham Phuong Nam & Bui Nguyen Hanh & Phan Thi Thanh Huyen & Nguyen Le Thuc Anh & Duong Thuy Ninh, 2023. "Accumulation and Concentration of Agricultural Land: A Case Study in Gia Binh District, Bac Ninh Province, Vietnam," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 7(7), pages 761-776, July.
    9. Pates, Nicholas J. & Kim, GwanSeon & Mark, Tyler B. & Ritter, Matthias, 2020. "Windfalls or wind falls? The Local Effects of Turbine Development on US Agricultural Land Values," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304611, Agricultural and Applied Economics Association.
    10. Stefan Seifert & Silke Hüttel, 2023. "Is there a risk of a winner’s curse in farmland auctions?," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 50(3), pages 1140-1177.
    11. Kvartiuk, Vasyl & Herzfeld, Thomas & Bukin, Eduard, 2022. "Decentralized public farmland conveyance: Rental rights auctioning in Ukraine," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 114.
    12. Henning Schaak & Luise Meissner & Oliver Musshoff, 2023. "New insights on regional differences of the farmland price structure: An extended replication study on the parcel size–price relationship," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 45(3), pages 1427-1449, September.
    13. Kionka, Marlene & Odening, Martin & Plogmann, Jana & Ritter, Matthias, 2021. "Measuring Liquidity in Agricultural Land Markets," 2021 Conference, August 17-31, 2021, Virtual 315234, International Association of Agricultural Economists.
    14. Myrna, Olena, 2023. "Competition in online land lease auctions in Ukraine: Reduced-form estimation," Land Use Policy, Elsevier, vol. 125(C).
    15. Roberts, Shane & Brooks, Kathleen & Nogueira, Lia & Walters, Cory G., 2022. "The role of quality characteristics in pricing hard red winter wheat," Food Policy, Elsevier, vol. 108(C).
    16. Burcu Aksu & Suleyman Karaman, 2022. "Estimating the effect of a land parcel index using hedonic price analysis," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 68(11), pages 427-433.
    17. Doan, Quang Cuong, 2023. "Determining the optimal land valuation model: A case study of Hanoi, Vietnam," Land Use Policy, Elsevier, vol. 127(C).
    18. Seifert, Stefan & Hüttel, Silke & Werwatz, Axel, 2023. "Organic cultivation and farmland prices: Does certification matter?," FORLand Working Papers 28 (2023), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    19. Clayton, Helena & Hingee, Kassel L. & Chancellor, Will & Lindenmayer, David & van Dijk, Albert & Vardon, Michael & Boult, Chris, 2024. "Private benefits of natural capital on farms across an endangered ecoregion," Ecological Economics, Elsevier, vol. 218(C).

  8. Aaron Grau & Martin Odening & Matthias Ritter, 2020. "Land price diffusion across borders – the case of Germany," Applied Economics, Taylor & Francis Journals, vol. 52(50), pages 5446-5463, October.
    See citations under working paper version above.
  9. Helbing, Georg & Ritter, Matthias, 2020. "Improving wind turbine power curve monitoring with standardisation," Renewable Energy, Elsevier, vol. 145(C), pages 1040-1048.

    Cited by:

    1. Pengfei Zhang & Zuoxia Xing & Shanshan Guo & Mingyang Chen & Qingqi Zhao, 2022. "A New Wind Turbine Power Performance Assessment Approach: SCADA to Power Model Based with Regression-Kriging," Energies, MDPI, vol. 15(13), pages 1-15, July.
    2. Davide Astolfi & Francesco Castellani & Andrea Lombardi & Ludovico Terzi, 2021. "Multivariate SCADA Data Analysis Methods for Real-World Wind Turbine Power Curve Monitoring," Energies, MDPI, vol. 14(4), pages 1-18, February.
    3. Wang, Bohan & Deng, Ziwei & Zhang, Baocheng, 2022. "Simulation of a novel wind–wave hybrid power generation system with hydraulic transmission," Energy, Elsevier, vol. 238(PB).
    4. Wang, Peng & Li, Yanting & Zhang, Guangyao, 2023. "Probabilistic power curve estimation based on meteorological factors and density LSTM," Energy, Elsevier, vol. 269(C).
    5. Bórawski, Piotr & Bełdycka-Bórawska, Aneta & Jankowski, Krzysztof Jóżef & Dubis, Bogdan & Dunn, James W., 2020. "Development of wind energy market in the European Union," Renewable Energy, Elsevier, vol. 161(C), pages 691-700.
    6. Miguel Á. Rodríguez-López & Emilio Cerdá & Pablo del Rio, 2020. "Modeling Wind-Turbine Power Curves: Effects of Environmental Temperature on Wind Energy Generation," Energies, MDPI, vol. 13(18), pages 1-21, September.
    7. Han, Shuang & Qiao, Yanhui & Yan, Ping & Yan, Jie & Liu, Yongqian & Li, Li, 2020. "Wind turbine power curve modeling based on interval extreme probability density for the integration of renewable energies and electric vehicles," Renewable Energy, Elsevier, vol. 157(C), pages 190-203.

  10. Plogmann, Jana & Mußhoff, Oliver & Odening, Martin & Ritter, Matthias, 2020. "What Moves the German Land Market? A Decomposition of the Land Rent-Price Ratio," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 69(01).
    See citations under working paper version above.
  11. Xinyue Yang & Martin Odening & Matthias Ritter, 2019. "The Spatial and Temporal Diffusion of Agricultural Land Prices," Land Economics, University of Wisconsin Press, vol. 95(1), pages 108-123.
    See citations under working paper version above.
  12. Olena Myrna & Martin Odening & Matthias Ritter, 2019. "The Influence of Wind Energy and Biogas on Farmland Prices," Land, MDPI, vol. 8(1), pages 1-14, January.

    Cited by:

    1. Ritter, Matthias & Hüttel, Silke & Odening, Martin & Seifert, Stefan, 2020. "Revisiting the relationship between land price and parcel size in agriculture," Land Use Policy, Elsevier, vol. 97(C).
    2. Cord-Friedrich von Hobe & Marius Michels & Oliver Musshoff, 2021. "German Farmers’ Perspectives on Price Drivers in Agricultural Land Rental Markets—A Combination of a Systematic Literature Review and Survey Results," Land, MDPI, vol. 10(2), pages 1-22, February.
    3. Ritter, Matthias & Hüttel, Silke & Odening, Martin & Seifert, Stefan, 2019. "Revisiting the relationship between land price and parcel size," FORLand Working Papers 08 (2019), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    4. Akca, Mehmet Sadik & Sarikaya, Omer Visali & Doker, Mehmet Fatih & Ocak, Fatih & Kirlangicoglu, Cem & Karaaslan, Yakup & Satoglu, Sule Itir & Altinbas, Mahmut, 2023. "A detailed GIS based assessment of bioenergy plant locations using location-allocation algorithm," Applied Energy, Elsevier, vol. 352(C).
    5. Vergara, Felipe & Lakes, Tobia Maike, 2019. "Maizification of the landscape for biogas production? Identifying the likelihood of silage maize for biogas in Brandenburg from 2008-2018," FORLand Working Papers 16 (2019), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    6. Pates, Nicholas J. & Kim, GwanSeon & Mark, Tyler B. & Ritter, Matthias, 2020. "Windfalls or wind falls? The Local Effects of Turbine Development on US Agricultural Land Values," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304611, Agricultural and Applied Economics Association.
    7. Xueqing Yang & Yang Liu & Mei Wang & Alberto Bezama & Daniela Thrän, 2021. "Identifying the Necessities of Regional-Based Analysis to Study Germany’s Biogas Production Development under Energy Transition," Land, MDPI, vol. 10(2), pages 1-20, February.
    8. Tanner, Sophia & Burnett, Wesley & Maguire, Karen & Winikoff, Justin, 2024. "Blown Away: The Influence of Wind Farms on Agricultural Land Values," 2024 Annual Meeting, July 28-30, New Orleans, LA 343970, Agricultural and Applied Economics Association.
    9. Johanna Jauernig & Stephan Brosig & Silke Hüttel, 2023. "Profession and residency matter: Farmers' preferences for farmland price regulation in Germany," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(3), pages 816-834, September.
    10. Zhongcheng Yan & Feng Wei & Xin Deng & Chuan Li & Yanbin Qi, 2021. "Does Land Expropriation Experience Increase Farmers’ Farmland Value Expectations? Empirical Evidence from the People’s Republic of China," Land, MDPI, vol. 10(6), pages 1-23, June.
    11. Chun-Chang Lee & Yi-Xin Chen & Yun-Ling Wu & Wen-Chih Yeh & Chih-Min Liang, 2020. "Multilevel Analysis of the Pressure of Agricultural Land Conversion, Degree of Urbanization and Agricultural Land Prices in Taiwan," Land, MDPI, vol. 9(12), pages 1-21, November.
    12. Marques, Felipe César & Telles, Tiago Santos, 2023. "Spatial effects are determinants of agricultural land prices in Brazil," Revista de Economia e Sociologia Rural (RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 61(3), January.
    13. Myrna, Olena, 2023. "Competition in online land lease auctions in Ukraine: Reduced-form estimation," Land Use Policy, Elsevier, vol. 125(C).
    14. Giovanni Ottomano Palmisano & Annalisa De Boni & Rocco Roma & Claudio Acciani, 2021. "Influence of Wind Turbines on Farmlands’ Value: Exploring the Behaviour of a Rural Community through the Decision Tree," Sustainability, MDPI, vol. 13(17), pages 1-25, August.
    15. Qi, Yuan & Hou, Yuchen & Li, Yaoyao & Li, Luyue & Zhang, Jiaqing & Chang, Yuyang & Zhu, Daolin, 2023. "The price gap between state-owned and collective farmlands: Evidence from Xinjiang and Heilongjiang, China," Land Use Policy, Elsevier, vol. 124(C).

  13. Helbing, Georg & Ritter, Matthias, 2018. "Deep Learning for fault detection in wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 189-198.

    Cited by:

    1. Do Ngoc Tuyen & Tran Manh Tuan & Le Hoang Son & Tran Thi Ngan & Nguyen Long Giang & Pham Huy Thong & Vu Van Hieu & Vassilis C. Gerogiannis & Dimitrios Tzimos & Andreas Kanavos, 2021. "A Novel Approach Combining Particle Swarm Optimization and Deep Learning for Flash Flood Detection from Satellite Images," Mathematics, MDPI, vol. 9(22), pages 1-20, November.
    2. Samuel-Soma M. Ajibade & Festus Victor Bekun & Festus Fatai Adedoyin & Bright Akwasi Gyamfi & Anthonia Oluwatosin Adediran, 2023. "Machine Learning Applications in Renewable Energy (MLARE) Research: A Publication Trend and Bibliometric Analysis Study (2012–2021)," Clean Technol., MDPI, vol. 5(2), pages 1-21, April.
    3. Wang, Anqi & Pei, Yan & Qian, Zheng & Zareipour, Hamidreza & Jing, Bo & An, Jiayi, 2022. "A two-stage anomaly decomposition scheme based on multi-variable correlation extraction for wind turbine fault detection and identification," Applied Energy, Elsevier, vol. 321(C).
    4. Chen, Wanqiu & Qiu, Yingning & Feng, Yanhui & Li, Ye & Kusiak, Andrew, 2021. "Diagnosis of wind turbine faults with transfer learning algorithms," Renewable Energy, Elsevier, vol. 163(C), pages 2053-2067.
    5. Jorge Maldonado-Correa & Sergio Martín-Martínez & Estefanía Artigao & Emilio Gómez-Lázaro, 2020. "Using SCADA Data for Wind Turbine Condition Monitoring: A Systematic Literature Review," Energies, MDPI, vol. 13(12), pages 1-21, June.
    6. Pang, Yanhua & He, Qun & Jiang, Guoqian & Xie, Ping, 2020. "Spatio-temporal fusion neural network for multi-class fault diagnosis of wind turbines based on SCADA data," Renewable Energy, Elsevier, vol. 161(C), pages 510-524.
    7. Annalisa Santolamazza & Daniele Dadi & Vito Introna, 2021. "A Data-Mining Approach for Wind Turbine Fault Detection Based on SCADA Data Analysis Using Artificial Neural Networks," Energies, MDPI, vol. 14(7), pages 1-25, March.
    8. Francisco Bilendo & Angela Meyer & Hamed Badihi & Ningyun Lu & Philippe Cambron & Bin Jiang, 2022. "Applications and Modeling Techniques of Wind Turbine Power Curve for Wind Farms—A Review," Energies, MDPI, vol. 16(1), pages 1-38, December.
    9. Chatterjee, Joyjit & Dethlefs, Nina, 2021. "Scientometric review of artificial intelligence for operations & maintenance of wind turbines: The past, present and future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    10. Cristian Velandia-Cardenas & Yolanda Vidal & Francesc Pozo, 2021. "Wind Turbine Fault Detection Using Highly Imbalanced Real SCADA Data," Energies, MDPI, vol. 14(6), pages 1-26, March.
    11. Valerio Francesco Barnabei & Fabrizio Bonacina & Alessandro Corsini & Francesco Aldo Tucci & Roberto Santilli, 2023. "Condition-Based Maintenance of Gensets in District Heating Using Unsupervised Normal Behavior Models Applied on SCADA Data," Energies, MDPI, vol. 16(9), pages 1-15, April.
    12. Marc-Alexander Lutz & Stephan Vogt & Volker Berkhout & Stefan Faulstich & Steffen Dienst & Urs Steinmetz & Christian Gück & Andres Ortega, 2020. "Evaluation of Anomaly Detection of an Autoencoder Based on Maintenace Information and Scada-Data," Energies, MDPI, vol. 13(5), pages 1-18, February.
    13. Majdi Mansouri & Khaled Dhibi & Hazem Nounou & Mohamed Nounou, 2022. "An Effective Fault Diagnosis Technique for Wind Energy Conversion Systems Based on an Improved Particle Swarm Optimization," Sustainability, MDPI, vol. 14(18), pages 1-11, September.
    14. Mohammad Reza Shadi & Hamid Mirshekali & Rahman Dashti & Mohammad-Taghi Ameli & Hamid Reza Shaker, 2021. "A Parameter-Free Approach for Fault Section Detection on Distribution Networks Employing Gated Recurrent Unit," Energies, MDPI, vol. 14(19), pages 1-15, October.
    15. Jin, Zhenglei & Xu, Qifa & Jiang, Cuixia & Wang, Xiangxiang & Chen, Hao, 2023. "Ordinal few-shot learning with applications to fault diagnosis of offshore wind turbines," Renewable Energy, Elsevier, vol. 206(C), pages 1158-1169.
    16. Adaiton Oliveira-Filho & Ryad Zemouri & Philippe Cambron & Antoine Tahan, 2023. "Early Detection and Diagnosis of Wind Turbine Abnormal Conditions Using an Interpretable Supervised Variational Autoencoder Model," Energies, MDPI, vol. 16(12), pages 1-21, June.
    17. Richter, Lucas & Lehna, Malte & Marchand, Sophie & Scholz, Christoph & Dreher, Alexander & Klaiber, Stefan & Lenk, Steve, 2022. "Artificial Intelligence for Electricity Supply Chain automation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    18. Cui, Bodi & Weng, Yang & Zhang, Ning, 2022. "A feature extraction and machine learning framework for bearing fault diagnosis," Renewable Energy, Elsevier, vol. 191(C), pages 987-997.
    19. Richmond, M. & Sobey, A. & Pandit, R. & Kolios, A., 2020. "Stochastic assessment of aerodynamics within offshore wind farms based on machine-learning," Renewable Energy, Elsevier, vol. 161(C), pages 650-661.
    20. Mohammad Mahdi Forootan & Iman Larki & Rahim Zahedi & Abolfazl Ahmadi, 2022. "Machine Learning and Deep Learning in Energy Systems: A Review," Sustainability, MDPI, vol. 14(8), pages 1-49, April.
    21. Wang, Anqi & Qian, Zheng & Pei, Yan & Jing, Bo, 2022. "A de-ambiguous condition monitoring scheme for wind turbines using least squares generative adversarial networks," Renewable Energy, Elsevier, vol. 185(C), pages 267-279.
    22. Feng Gao & Xiaojiang Wu & Qiang Liu & Juncheng Liu & Xiyun Yang, 2019. "Fault Simulation and Online Diagnosis of Blade Damage of Large-Scale Wind Turbines," Energies, MDPI, vol. 12(3), pages 1-16, February.
    23. Jianjun Chen & Weihao Hu & Di Cao & Bin Zhang & Qi Huang & Zhe Chen & Frede Blaabjerg, 2019. "An Imbalance Fault Detection Algorithm for Variable-Speed Wind Turbines: A Deep Learning Approach," Energies, MDPI, vol. 12(14), pages 1-15, July.
    24. Qiang Zhao & Kunkun Bao & Jia Wang & Yinghua Han & Jinkuan Wang, 2019. "An Online Hybrid Model for Temperature Prediction of Wind Turbine Gearbox Components," Energies, MDPI, vol. 12(20), pages 1-20, October.
    25. Antonio Lorenzo-Espejo & Alejandro Escudero-Santana & María-Luisa Muñoz-Díaz & Alicia Robles-Velasco, 2022. "Machine Learning-Based Analysis of a Wind Turbine Manufacturing Operation: A Case Study," Sustainability, MDPI, vol. 14(13), pages 1-25, June.
    26. Jorge De La Cruz & Eduardo Gómez-Luna & Majid Ali & Juan C. Vasquez & Josep M. Guerrero, 2023. "Fault Location for Distribution Smart Grids: Literature Overview, Challenges, Solutions, and Future Trends," Energies, MDPI, vol. 16(5), pages 1-37, February.
    27. Panagiotis Korkos & Jaakko Kleemola & Matti Linjama & Arto Lehtovaara, 2022. "Representation Learning for Detecting the Faults in a Wind Turbine Hydraulic Pitch System Using Deep Learning," Energies, MDPI, vol. 15(24), pages 1-17, December.

  14. Matthias Ritter & Simone Pieralli & Martin Odening, 2017. "Neighborhood Effects in Wind Farm Performance: A Regression Approach," Energies, MDPI, vol. 10(3), pages 1-16, March.

    Cited by:

    1. Francis Oloo & Kamran Safi & Jagannath Aryal, 2018. "Predicting Migratory Corridors of White Storks, Ciconia ciconia , to Enhance Sustainable Wind Energy Planning: A Data-Driven Agent-Based Model," Sustainability, MDPI, vol. 10(5), pages 1-22, May.
    2. Böhme, Gustavo S. & Fadigas, Eliane A. & Gimenes, André L.V. & Tassinari, Carlos E.M., 2018. "Wake effect measurement in complex terrain - A case study in Brazilian wind farms," Energy, Elsevier, vol. 161(C), pages 277-283.
    3. Mohamed Elnaggar & Ezzaldeen Edwan & Matthias Ritter, 2017. "Wind Energy Potential of Gaza Using Small Wind Turbines: A Feasibility Study," Energies, MDPI, vol. 10(8), pages 1-13, August.

  15. Ritter, Matthias & Deckert, Lars, 2017. "Site assessment, turbine selection, and local feed-in tariffs through the wind energy index," Applied Energy, Elsevier, vol. 185(P2), pages 1087-1099.
    See citations under working paper version above.
  16. Helbing, Georg & Shen, Zhiwei & Odening, Martin & Ritter, Matthias, 2017. "Estimating Location Values of Agricultural Land," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 66(3), September.
    See citations under working paper version above.
  17. Mohamed Elnaggar & Ezzaldeen Edwan & Matthias Ritter, 2017. "Wind Energy Potential of Gaza Using Small Wind Turbines: A Feasibility Study," Energies, MDPI, vol. 10(8), pages 1-13, August.

    Cited by:

    1. Osvaldo Rodriguez-Hernandez & Manuel Martinez & Carlos Lopez-Villalobos & Hector Garcia & Rafael Campos-Amezcua, 2019. "Techno-Economic Feasibility Study of Small Wind Turbines in the Valley of Mexico Metropolitan Area," Energies, MDPI, vol. 12(5), pages 1-26, March.
    2. Heyam Al-Najjar & Christoph Pfeifer & Rafat Al Afif & Hala J. El-Khozondar, 2022. "Performance Evaluation of a Hybrid Grid-Connected Photovoltaic Biogas-Generator Power System," Energies, MDPI, vol. 15(9), pages 1-22, April.
    3. Alina Wilke & Paul J.J. Welfens, 2020. "Urban Wind Energy Production Potential: New Opportunities," EIIW Discussion paper disbei287, Universitätsbibliothek Wuppertal, University Library.
    4. Alina Wilke & Zhiwei Shen & Matthias Ritter, 2021. "How Much Can Small-Scale Wind Energy Production Contribute to Energy Supply in Cities? A Case Study of Berlin," Energies, MDPI, vol. 14(17), pages 1-20, September.
    5. Altun, Ayse Fidan & Kilic, Muhsin, 2020. "Design and performance evaluation based on economics and environmental impact of a PV-wind-diesel and battery standalone power system for various climates in Turkey," Renewable Energy, Elsevier, vol. 157(C), pages 424-443.
    6. Diego Calabrese & Gioacchino Tricarico & Elia Brescia & Giuseppe Leonardo Cascella & Vito Giuseppe Monopoli & Francesco Cupertino, 2020. "Variable Structure Control of a Small Ducted Wind Turbine in the Whole Wind Speed Range Using a Luenberger Observer," Energies, MDPI, vol. 13(18), pages 1-23, September.
    7. Hamza S. Abdalla Lagili & Aşkın Kiraz & Youssef Kassem & Hüseyin Gökçekuş, 2023. "Wind and Solar Energy for Sustainable Energy Production for Family Farms in Coastal Agricultural Regions of Libya Using Measured and Multiple Satellite Datasets," Energies, MDPI, vol. 16(18), pages 1-53, September.

  18. Silke Hüttel & Matthias Ritter & Viacheslav Esaulov & Martin Odening, 2016. "Is there a term structure in land lease rates?," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 43(1), pages 165-187.

    Cited by:

    1. Danne, Michael & Buchholz, Matthias & Musshoff, Oliver, 2019. "An experimental analysis of German farmers’ decisions to buy or rent farmland," 165th Seminar, April 4-5, 2019, Berlin, Germany 288295, European Association of Agricultural Economists.
    2. Cord-Friedrich von Hobe & Marius Michels & Oliver Musshoff, 2021. "German Farmers’ Perspectives on Price Drivers in Agricultural Land Rental Markets—A Combination of a Systematic Literature Review and Survey Results," Land, MDPI, vol. 10(2), pages 1-22, February.
    3. Marten Graubner, 2018. "Lost in space? The effect of direct payments on land rental prices," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(2), pages 143-171.
    4. Johanna CHOUMERT & Pascale PHELINAS, 2015. "Farmland Rental Values in GM Soybean Areas of Argentina: Do Contractual Arrangements Matter?," Working Papers 201532, CERDI.
    5. Kvartiuk, Vasyl & Herzfeld, Thomas & Bukin, Eduard, 2022. "Decentralized public farmland conveyance: Rental rights auctioning in Ukraine," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 114.
    6. Myrna, Olena, 2023. "Competition in online land lease auctions in Ukraine: Reduced-form estimation," Land Use Policy, Elsevier, vol. 125(C).
    7. Graubner, Marten & Hüttel, Silke, 2024. "Rental and sale prices of agricultural lands under spatial competition," FORLand Working Papers 29 (2024), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    8. Kuethe, Todd H. & Bigelow, Daniel P., 2018. "Bargaining Power in Farmland Rental Markets," 2018 Annual Meeting, August 5-7, Washington, D.C. 274113, Agricultural and Applied Economics Association.
    9. Plogmann, Jana & Mußhoff, Oliver & Odening, Martin & Ritter, Matthias, 2019. "What Moves the German Land Market? A Decomposition of the Land Rent-Price Ratio," 165th Seminar, April 4-5, 2019, Berlin, Germany 288444, European Association of Agricultural Economists.
    10. Marten Graubner & Silke Hüttel, 2024. "Rental and sale prices of agricultural lands under spatial competition," Letters in Spatial and Resource Sciences, Springer, vol. 17(1), pages 1-12, December.
    11. Olena Myrna & Martin Odening & Matthias Ritter, 2019. "The Influence of Wind Energy and Biogas on Farmland Prices," Land, MDPI, vol. 8(1), pages 1-14, January.
    12. Kualwik, Jacek, 2016. "Selected problems of farmland valuation and setting rents for its lease," Problems of Agricultural Economics / Zagadnienia Ekonomiki Rolnej 252639, Institute of Agricultural and Food Economics - National Research Institute (IAFE-NRI).
    13. Grau, Aaron & Jasic, Svetlana & Ritter, Matthias & Odening, Martin, 2019. "The impact of production intensity on agricultural land prices," FORLand Working Papers 09 (2019), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    14. Olena Myrna, 2022. "Lower price increases, the bounded rationality of bidders, and underbidding concerns in online agricultural land auctions: The Ukrainian case," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(3), pages 826-844, September.
    15. Laura Onofri & Samuele Trestini & Fateh Mamine & Jason Loughrey, 2023. "Understanding agricultural land leasing in Ireland: a transaction cost approach," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 11(1), pages 1-20, December.

  19. Shen, Zhiwei & Ritter, Matthias, 2016. "Forecasting volatility of wind power production," Applied Energy, Elsevier, vol. 176(C), pages 295-308.
    See citations under working paper version above.
  20. Ritter, Matthias & Shen, Zhiwei & López Cabrera, Brenda & Odening, Martin & Deckert, Lars, 2015. "Designing an index for assessing wind energy potential," Renewable Energy, Elsevier, vol. 83(C), pages 416-424.
    See citations under working paper version above.
  21. Xiaofeng Cao & Ostap Okhrin & Martin Odening & Matthias Ritter, 2015. "Modelling spatio-temporal variability of temperature," Computational Statistics, Springer, vol. 30(3), pages 745-766, September.
    See citations under working paper version above.
  22. Pieralli, Simone & Ritter, Matthias & Odening, Martin, 2015. "Efficiency of wind power production and its determinants," Energy, Elsevier, vol. 90(P1), pages 429-438.
    See citations under working paper version above.
  23. M. Ritter & O. Mußhoff & M. Odening, 2014. "Minimizing Geographical Basis Risk of Weather Derivatives Using A Multi-Site Rainfall Model," Computational Economics, Springer;Society for Computational Economics, vol. 44(1), pages 67-86, June.
    See citations under working paper version above.
  24. López Cabrera, Brenda & Odening, Martin & Ritter, Matthias, 2013. "Pricing rainfall futures at the CME," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4286-4298.

    Cited by:

    1. Ceballos, Francisco, 2016. "Estimating spatial basis risk in rainfall index insurance: Methodology and application to excess rainfall insurance in Uruguay," IFPRI discussion papers 1595, International Food Policy Research Institute (IFPRI).
    2. Rui Zhou & Johnny Siu-Hang Li & Jeffrey Pai, 2019. "Pricing temperature derivatives with a filtered historical simulation approach," The European Journal of Finance, Taylor & Francis Journals, vol. 25(15), pages 1462-1484, October.
    3. Ritter, Matthias & Musshoff, Oliver & Odening, Martin, 2012. "Minimizing geographical basis risk of weather derivatives using a multi-site rainfall model," 123rd Seminar, February 23-24, 2012, Dublin, Ireland 122527, European Association of Agricultural Economists.
    4. Melzer, Awdesch & Härdle, Wolfgang Karl & López Cabrera, Brenda, 2017. "Pricing Green Financial Products," SFB 649 Discussion Papers 2017-020, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Tong, Zhigang & Liu, Allen, 2021. "A censored Ornstein–Uhlenbeck process for rainfall modeling and derivatives pricing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    6. Karl Härdle, Wolfgang & López-Cabrera, Brenda & Teng, Huei-Wen, 2015. "State price densities implied from weather derivatives," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 106-125.
    7. Härdle, Wolfgang Karl & Osipenko, Maria, 2017. "Dynamic valuation of weather derivatives under default risk," SFB 649 Discussion Papers 2017-005, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    8. Edimilson Costa Lucas & Wesley Mendes Da Silva & Gustavo Silva Araujo, 2017. "Does Extreme Rainfall Lead to Heavy Economic Losses in the Food Industry?," Working Papers Series 462, Central Bank of Brazil, Research Department.
    9. Bertrand, Jean-Louis & Parnaudeau, Miia, 2019. "Understanding the economic effects of abnormal weather to mitigate the risk of business failures," Journal of Business Research, Elsevier, vol. 98(C), pages 391-402.
    10. Simona Franzoni & Cristian Pelizzari, 2021. "Rainfall option impact on profits of the hospitality industry through scenario correlation and copulas," Annals of Operations Research, Springer, vol. 299(1), pages 939-962, April.
    11. Wolfgang Karl Härdle & Brenda López Cabrera & Awdesch Melzer, 2021. "Pricing wind power futures," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 1083-1102, August.
    12. Wolfgang Karl Härdle & Maria Osipenko, 2017. "A Dynamic Programming Approach for Pricing Weather Derivatives under Issuer Default Risk," IJFS, MDPI, vol. 5(4), pages 1-18, October.
    13. Peng Li, 2021. "The Valuation of Weather Derivatives Using One Sided Crank–Nicolson Schemes," Computational Economics, Springer;Society for Computational Economics, vol. 58(3), pages 825-847, October.
    14. Truong, Chi & Trück, Stefan, 2016. "It’s not now or never: Implications of investment timing and risk aversion on climate adaptation to extreme events," European Journal of Operational Research, Elsevier, vol. 253(3), pages 856-868.
    15. Ragnhild Noven & Almut Veraart & Axel Gandy, 2015. "A Lévy-driven rainfall model with applications to futures pricing," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(4), pages 403-432, October.

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