{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/137574"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/137574","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Modeling Food Commodity Prices and Market Dynamics","abstract":"This dissertation examines two distinct but related drivers of food commodity prices: global climate shocks and regional transportation costs. The first chapter, \"Exploring the Dynamics of the El Niño Southern Oscillation and Food Commodity Prices,\" investigates how ENSO-related weather anomalies influence the prices of wheat, corn, rice, and soybean products. Using data from 1980–2022 and nonlinear econometric methods (Smooth Transition Autoregressive and Smooth Transition Vector Error Correction models), the analysis uncovers asymmetric effects of ENSO shocks. A ±1.5°C deviation in ENSO-related temperatures generates price shifts of 10–20 percent. Warmer El Niño phases tend to depress prices, while cooler La Niña phases raise them. These dynamics matter most for low-income food-deficit countries (LIFDCs), where higher prices exacerbate food insecurity. The second chapter, \"Down the Mississippi: How Barge Rates Affect Corn Basis,\" turns to transportation and spatial market linkages in the U.S. corn market. Using weekly data from 2014 to 2024 across 14 Mississippi River markets, a Spatial Durbin Model with spatial and time fixed effects reveals that higher barge freight rates reduce local corn basis values by roughly five cents per bushel per one-dollar increase in barge rates. Rising barge costs, driven by factors such as river depth and diesel prices, also generate spillovers that transmit price effects to neighboring markets. Together, the two studies show how food commodity prices are shaped both by global climate variability and by regional supply chain constraints. The findings highlight the importance of policies that strengthen resilience to climate shocks while also addressing transportation bottlenecks in agricultural markets.","abstract_html":"This dissertation examines two distinct but related drivers of food commodity prices: global climate shocks and regional transportation costs. The first chapter, "Exploring the Dynamics of the El Niño Southern Oscillation and Food Commodity Prices," investigates how ENSO-related weather anomalies influence the prices of wheat, corn, rice, and soybean products. Using data from 1980–2022 and nonlinear econometric methods (Smooth Transition Autoregressive and Smooth Transition Vector Error Correction models), the analysis uncovers asymmetric effects of ENSO shocks. A ±1.5°C deviation in ENSO-related temperatures generates price shifts of 10–20 percent. Warmer El Niño phases tend to depress prices, while cooler La Niña phases raise them. These dynamics matter most for low-income food-deficit countries (LIFDCs), where higher prices exacerbate food insecurity. The second chapter, "Down the Mississippi: How Barge Rates Affect Corn Basis," turns to transportation and spatial market linkages in the U.S. corn market. Using weekly data from 2014 to 2024 across 14 Mississippi River markets, a Spatial Durbin Model with spatial and time fixed effects reveals that higher barge freight rates reduce local corn basis values by roughly five cents per bushel per one-dollar increase in barge rates. Rising barge costs, driven by factors such as river depth and diesel prices, also generate spillovers that transmit price effects to neighboring markets. Together, the two studies show how food commodity prices are shaped both by global climate variability and by regional supply chain constraints. The findings highlight the importance of policies that strengthen resilience to climate shocks while also addressing transportation bottlenecks in agricultural markets.","abstract_has_math":false,"creators":["Quaye, Leonard-Allen Amarh"],"institution":"Virginia Tech","degree_name":"Doctor of Philosophy","degree_level":"doctoral","degree_discipline":"Economics, Agriculture and Life Sciences","degree_department":"Economics","school":null,"contributors":[],"advisors":[],"committee_chairs":["Stewart, Shamar L."],"committee_members":["Holmes, Chanita","Neill, Clinton L.","Isengildina Massa, Olga","Wang, Le"],"year":2025,"date_issued":"2025-08-26","date_published":"2025-08-26","updated_at":"2026-07-22T22:19:19Z","subjects":["Weather anomalies","food commodity prices","corn basis","Mississippi River","barge freight rates"],"languages":["en"],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:44529"],"render_values":[{"text":"vt_gsexam:44529","href":null,"code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/10919/137574","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Stewart, Shamar L."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Holmes, Chanita","Neill, Clinton L.","Isengildina Massa, Olga","Wang, Le"]},{"key":"dc:contributor.department","label":"Department","values":["Economics"]},{"key":"dc:creator","label":"Author","values":["Quaye, Leonard-Allen Amarh"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-08-27T08:00:50Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2025-08-27T08:00:50Z"]},{"key":"dc:date.issued","label":"Date","values":["2025-08-26"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Economics, Agriculture and Life Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Weather anomalies","food commodity prices","corn basis","Mississippi River","barge freight rates"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:44529"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10919/137574"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This dissertation examines two distinct but related drivers of food commodity prices: global climate shocks and regional transportation costs. The first chapter, \"Exploring the Dynamics of the El Niño Southern Oscillation and Food Commodity Prices,\" investigates how ENSO-related weather anomalies influence the prices of wheat, corn, rice, and soybean products. Using data from 1980–2022 and nonlinear econometric methods (Smooth Transition Autoregressive and Smooth Transition Vector Error Correction models), the analysis uncovers asymmetric effects of ENSO shocks. A ±1.5°C deviation in ENSO-related temperatures generates price shifts of 10–20 percent. Warmer El Niño phases tend to depress prices, while cooler La Niña phases raise them. These dynamics matter most for low-income food-deficit countries (LIFDCs), where higher prices exacerbate food insecurity. The second chapter, \"Down the Mississippi: How Barge Rates Affect Corn Basis,\" turns to transportation and spatial market linkages in the U.S. corn market. Using weekly data from 2014 to 2024 across 14 Mississippi River markets, a Spatial Durbin Model with spatial and time fixed effects reveals that higher barge freight rates reduce local corn basis values by roughly five cents per bushel per one-dollar increase in barge rates. Rising barge costs, driven by factors such as river depth and diesel prices, also generate spillovers that transmit price effects to neighboring markets. Together, the two studies show how food commodity prices are shaped both by global climate variability and by regional supply chain constraints. The findings highlight the importance of policies that strengthen resilience to climate shocks while also addressing transportation bottlenecks in agricultural markets."]},{"key":"dc:description.abstractgeneral","label":"General Abstract","values":["This dissertation examines two distinct forces that influence the price of food: global weather patterns and the cost of transporting crops along the Mississippi River. The first chapter examines the El Niño-Southern Oscillation (ENSO), a recurring climate pattern that disrupts weather patterns worldwide. Using over 40 years of data, the study shows that ENSO can shift food prices by 10–20 percent. El Niño years, which are warmer, generally have lower prices, while La Niña years, which are cooler, push them higher. This matters most for low-income food-deficit countries, where even modest increases in staple food prices make it harder for families to afford enough to eat. The second chapter focuses on corn markets in the U.S. along the Mississippi River. Farmers rely on barges to move corn down the river to export terminals. When river levels are low or diesel prices rise, barge transportation becomes more expensive. The research finds that every one-dollar increase in barge freight rates reduces the price farmers receive (the corn basis) by about five cents per bushel. These costs don't just stay local but spill over into nearby markets along the river as well. Together, the studies show that food prices respond both to global climate shifts and to local transportation challenges. Addressing food security requires tackling both building resilience to weather disruptions and improving the efficiency of supply chains that connect farmers to markets."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Doctor of Philosophy"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:title","label":"Title","values":["Modeling Food Commodity Prices and Market Dynamics"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Stewart, Shamar L."],"dc:contributor.committeemember":["Holmes, Chanita","Neill, Clinton L.","Isengildina Massa, Olga","Wang, Le"],"dc:contributor.department":["Economics"],"dc:creator":["Quaye, Leonard-Allen Amarh"],"dc:date.accessioned":["2025-08-27T08:00:50Z"],"dc:date.available":["2025-08-27T08:00:50Z"],"dc:date.issued":["2025-08-26"],"dc:description.abstract":["This dissertation examines two distinct but related drivers of food commodity prices: global climate shocks and regional transportation costs. The first chapter, \"Exploring the Dynamics of the El Niño Southern Oscillation and Food Commodity Prices,\" investigates how ENSO-related weather anomalies influence the prices of wheat, corn, rice, and soybean products. Using data from 1980–2022 and nonlinear econometric methods (Smooth Transition Autoregressive and Smooth Transition Vector Error Correction models), the analysis uncovers asymmetric effects of ENSO shocks. A ±1.5°C deviation in ENSO-related temperatures generates price shifts of 10–20 percent. Warmer El Niño phases tend to depress prices, while cooler La Niña phases raise them. These dynamics matter most for low-income food-deficit countries (LIFDCs), where higher prices exacerbate food insecurity. The second chapter, \"Down the Mississippi: How Barge Rates Affect Corn Basis,\" turns to transportation and spatial market linkages in the U.S. corn market. Using weekly data from 2014 to 2024 across 14 Mississippi River markets, a Spatial Durbin Model with spatial and time fixed effects reveals that higher barge freight rates reduce local corn basis values by roughly five cents per bushel per one-dollar increase in barge rates. Rising barge costs, driven by factors such as river depth and diesel prices, also generate spillovers that transmit price effects to neighboring markets. Together, the two studies show how food commodity prices are shaped both by global climate variability and by regional supply chain constraints. The findings highlight the importance of policies that strengthen resilience to climate shocks while also addressing transportation bottlenecks in agricultural markets."],"dc:description.abstractgeneral":["This dissertation examines two distinct forces that influence the price of food: global weather patterns and the cost of transporting crops along the Mississippi River. The first chapter examines the El Niño-Southern Oscillation (ENSO), a recurring climate pattern that disrupts weather patterns worldwide. Using over 40 years of data, the study shows that ENSO can shift food prices by 10–20 percent. El Niño years, which are warmer, generally have lower prices, while La Niña years, which are cooler, push them higher. This matters most for low-income food-deficit countries, where even modest increases in staple food prices make it harder for families to afford enough to eat. The second chapter focuses on corn markets in the U.S. along the Mississippi River. Farmers rely on barges to move corn down the river to export terminals. When river levels are low or diesel prices rise, barge transportation becomes more expensive. The research finds that every one-dollar increase in barge freight rates reduces the price farmers receive (the corn basis) by about five cents per bushel. These costs don't just stay local but spill over into nearby markets along the river as well. Together, the studies show that food prices respond both to global climate shifts and to local transportation challenges. Addressing food security requires tackling both building resilience to weather disruptions and improving the efficiency of supply chains that connect farmers to markets."],"dc:description.degree":["Doctor of Philosophy"],"dc:format.medium":["ETD"],"dc:identifier.other":["vt_gsexam:44529"],"dc:identifier.uri":["https://hdl.handle.net/10919/137574"],"dc:language.iso":["en"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["Weather anomalies","food commodity prices","corn basis","Mississippi River","barge freight rates"],"dc:title":["Modeling Food Commodity Prices and Market Dynamics"],"dc:type":["Dissertation"],"thesis:degree_discipline":["Economics, Agriculture and Life Sciences"],"thesis:degree_level":["doctoral"],"thesis:degree_name":["Doctor of Philosophy"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:19:19Z"}