{"id":175898,"date":"2024-03-21T18:34:05","date_gmt":"2024-03-21T17:34:05","guid":{"rendered":"https:\/\/www.wifo.ac.at\/publication\/175898\/"},"modified":"2024-04-26T10:14:55","modified_gmt":"2024-04-26T08:14:55","slug":"robust-supply-chains-in-the-agri-food-industry-2","status":"publish","type":"publication","link":"https:\/\/www.wifo.ac.at\/en\/publication\/175898\/","title":{"rendered":"Robust Supply Chains in the Agri-food Industry"},"content":{"rendered":"","protected":false},"featured_media":0,"template":"","class_list":["post-175898","publication","type-publication","status-publish","hentry"],"acf":{"subtitle":"Forecasting Producers Prices for Crops in Austria","text":"Prices for agricultural products are critical for producers and consumer alike. On the producer side higher prices signal the degree of scarcity of a crop. Given a high price elasticity of supply, accurate and timely price forecasts for the main crops provide Austrian farmers with a valuable signal to shift land use towards more profitable crops, thus supporting the security of food supply in Austria. We apply three classes of time series models to producer prices of four popular crops in Austria: milling wheat, quality wheat, rapeseed, and maize. Using explanatory variables from futures markets and international organisations improves the model performance. The proposed forecasting cycles reflect the dates of decision making in sowing and harvesting each crop. We find that the Mallows Model Averaging method produces the smallest average forecast error, but a combined model forecast ranks best among all alternatives and beats both, individual model forecasts and the prices of matching futures contracts.","onlinedate":"2023-12-12 10:51:06","lang":"English","publication_series":"","publication_date":"20230731","publication_date_year":"","publication_date_full":true,"publication_num_pages":"30","keywords":"[]","jelcodes":"[]","related_publications":"[]","pdf":null,"zip":null,"link":"","monthly_report":false,"monthly_report_main":false,"monthly_report_volume":"","monthly_report_pages":"","monthly_report_pages_sort":"0","issue":"","journal":"","publisher":"","invisible":false,"external":false,"embargo_date":null,"types":[81966],"research_groups":[3500],"collaboration":"","persons":[3899],"persons_data":"[{\"personId\":3899,\"personName\":\"Thomas Url\",\"organisationNames\":[]}]","clients":[29818],"subclients":[],"partners":[],"topics":[],"host_publication_title":"","host_publication_subtitle":"","place_of_publication":"","host_publication_editors":"[]","type_description":"","output_media":"","chapter":"","article_number":"","citations":"{\"apa\":\"<div class=\\\"rendering rendering_researchoutput  rendering_researchoutput_apa rendering_bookanthology rendering_apa rendering_bookanthology_apa\\\"><span>Url, T.<\\\/span> (2023). <span><em>Robust Supply Chains in the Agri-food Industry: Forecasting Producers Prices for Crops in Austria<\\\/em><\\\/span>. WIFO.<\\\/div>\",\"vancouver\":\"<div class=\\\"rendering rendering_researchoutput  rendering_researchoutput_vancouver rendering_bookanthology rendering_vancouver rendering_bookanthology_vancouver\\\"><span>Url T<\\\/span>. <span class=\\\"title\\\"><span>Robust Supply Chains in the Agri-food Industry: <span class=\\\"subtitle\\\">Forecasting Producers Prices for Crops in Austria<\\\/span><\\\/span><\\\/span>. WIFO; 2023.<\\\/div>\",\"bibtex\":\"<div class=\\\"rendering rendering_researchoutput  rendering_researchoutput_bibtex rendering_bookanthology rendering_bibtex rendering_bookanthology_bibtex\\\"><div>@book{2cd86531a9974856a31859e95b064e5a,<\\\/div><div>  title    = \\\"Robust Supply Chains in the Agri-food Industry: Forecasting Producers Prices for Crops in Austria\\\",<\\\/div><div>  abstract = \\\"Prices for agricultural products are critical for producers and consumer alike. On the producer side higher prices signal the degree of scarcity of a crop. Given a high price elasticity of supply, accurate and timely price forecasts for the main crops provide Austrian farmers with a valuable signal to shift land use towards more profitable crops, thus supporting the security of food supply in Austria. We apply three classes of time series models to producer prices of four popular crops in Austria: milling wheat, quality wheat, rapeseed, and maize. Using explanatory variables from futures markets and international organisations improves the model performance. The proposed forecasting cycles reflect the dates of decision making in sowing and harvesting each crop. We find that the Mallows Model Averaging method produces the smallest average forecast error, but a combined model forecast ranks best among all alternatives and beats both, individual model forecasts and the prices of matching futures contracts.\\\",<\\\/div><div>  author   = \\\"Thomas Url\\\",<\\\/div><div>  year     = \\\"2023\\\",<\\\/div><div>  month    = jul,<\\\/div><div>  day      = \\\"31\\\",<\\\/div><div>  language = \\\"English\\\",<\\\/div><p>}<\\\/p><\\\/div>\",\"ris\":\"<div class=\\\"rendering rendering_researchoutput  rendering_researchoutput_ris rendering_bookanthology rendering_ris rendering_bookanthology_ris\\\"><p>TY  - BOOK<\\\/p><p>T1  - Robust Supply Chains in the Agri-food Industry<\\\/p><p>T2  - Forecasting Producers Prices for Crops in Austria<\\\/p><p>AU  - Url, Thomas<\\\/p><p>PY  - 2023\\\/7\\\/31<\\\/p><p>Y1  - 2023\\\/7\\\/31<\\\/p><p>N2  - Prices for agricultural products are critical for producers and consumer alike. On the producer side higher prices signal the degree of scarcity of a crop. Given a high price elasticity of supply, accurate and timely price forecasts for the main crops provide Austrian farmers with a valuable signal to shift land use towards more profitable crops, thus supporting the security of food supply in Austria. We apply three classes of time series models to producer prices of four popular crops in Austria: milling wheat, quality wheat, rapeseed, and maize. Using explanatory variables from futures markets and international organisations improves the model performance. The proposed forecasting cycles reflect the dates of decision making in sowing and harvesting each crop. We find that the Mallows Model Averaging method produces the smallest average forecast error, but a combined model forecast ranks best among all alternatives and beats both, individual model forecasts and the prices of matching futures contracts.<\\\/p><p>AB  - Prices for agricultural products are critical for producers and consumer alike. On the producer side higher prices signal the degree of scarcity of a crop. Given a high price elasticity of supply, accurate and timely price forecasts for the main crops provide Austrian farmers with a valuable signal to shift land use towards more profitable crops, thus supporting the security of food supply in Austria. We apply three classes of time series models to producer prices of four popular crops in Austria: milling wheat, quality wheat, rapeseed, and maize. Using explanatory variables from futures markets and international organisations improves the model performance. The proposed forecasting cycles reflect the dates of decision making in sowing and harvesting each crop. We find that the Mallows Model Averaging method produces the smallest average forecast error, but a combined model forecast ranks best among all alternatives and beats both, individual model forecasts and the prices of matching futures contracts.<\\\/p><p>M3  - Study<\\\/p><p>BT  - Robust Supply Chains in the Agri-food Industry<\\\/p><p>ER  - <\\\/p><\\\/div>\"}","scientific_assistance":"[\"Glauninger Ursula\",\"Schobert Cornelia\"]","scientific_review":"[\"Kaniovski Serguei\"]","version":"","release_date":null,"expiration_date":null,"surveyor":"","research_assistance":"","edv":"","additional_info_de":"","additional_info_en":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v28.0 (Yoast SEO v28.0) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Robust Supply Chains in the Agri-food Industry - WIFO<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.wifo.ac.at\/en\/publication\/175898\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Robust Supply Chains in the Agri-food Industry\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.wifo.ac.at\/en\/publication\/175898\/\" \/>\n<meta property=\"og:site_name\" content=\"WIFO\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/WIFOat\/\" \/>\n<meta property=\"article:modified_time\" content=\"2024-04-26T08:14:55+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.wifo.ac.at\/wp-content\/uploads\/2024\/05\/WIFO-Gebaeude-FotoAlexanderMueller-www.alexandermueller.at-IMG_6326-Bearbeitet-1.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1920\" \/>\n\t<meta property=\"og:image:height\" content=\"1280\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:site\" content=\"@WIFOat\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.wifo.ac.at\\\/en\\\/publication\\\/175898\\\/\",\"url\":\"https:\\\/\\\/www.wifo.ac.at\\\/en\\\/publication\\\/175898\\\/\",\"name\":\"Robust Supply Chains in the Agri-food Industry - 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