{"title":"Re-examining the effect of heat and water stress on agricultural output growth: How is Sub-Saharan Africa different?","authors":"Uchechukwu Jarrett, Yvonne Tackie","doi":"10.1111/agec.12830","DOIUrl":"10.1111/agec.12830","url":null,"abstract":"<p>We examine the impact of climate driven heat and water stress on aggregate crop production growth, paying particular attention to the Sub-Saharan Africa (SSA) region as opposed to studies with a global or Non SSA focus. Using gridded data on temperature and precipitation, which is crop weighted and averaged to the national level, we generate measures of stressors that capture average temperature and precipitation shocks, and extreme punctuated events like dry spells and heat waves for 38 countries in Sub Saharan Africa between 1979 and 2016. We find in general that compared to estimates with a global or non SSA focus, the detrimental effect of increased annual temperature has been overstated, while the damage caused by shorter-term extremes like dry spells and heat waves has been understated. This implies that region specific analysis is key in developing a more comprehensive understanding of climate change. Such analyses are pivotal for climate policy development allowing for more spatially efficient allocation of limited financial resources, and greater accuracy in estimating adaptation effects.</p>","PeriodicalId":50837,"journal":{"name":"Agricultural Economics","volume":"55 3","pages":"515-530"},"PeriodicalIF":4.1,"publicationDate":"2024-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/agec.12830","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140839075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christopher N. Boyer, Karen L. DeLong, Andrew P. Griffith, Charles C. Martinez
{"title":"Factors influencing United States cattle producers use of livestock risk protection","authors":"Christopher N. Boyer, Karen L. DeLong, Andrew P. Griffith, Charles C. Martinez","doi":"10.1111/agec.12838","DOIUrl":"10.1111/agec.12838","url":null,"abstract":"<p>United States cattle producers have various government-sponsored programs to protect against weather and disease related risks, but livestock risk protection (LRP) insurance is the only program that protects against price risk. However, adoption of LRP insurance is low even though cattle price declines are the primary cause of economic loss, and LRP premium subsidies have recently been increased. Therefore, the objective of this study is to explore how informational nudges about receiving an indemnity payment, LRP contract characteristics, and individual risk preferences affect the use of LRP. Producer survey results were estimated using a Cragg model to determine the factors affecting producers’ likelihood of purchasing LRP and the number of head they would insure. Producers were more likely to purchase 100% LRP coverage and would also insure more head at 100% coverage when compared to lower coverage levels. We found providing information on the probability of receiving an indemnity did not impact LRP purchasing decisions. However, counter to expectations, producers were more likely to buy LRP when the randomly provided cattle prices in the survey were successively increasing each month, and if participants considered themselves more willing to take risks in their cattle operation. Results provide insights into behavioral factors affecting LRP participation which could help inform future insurance policies.</p>","PeriodicalId":50837,"journal":{"name":"Agricultural Economics","volume":"55 4","pages":"677-689"},"PeriodicalIF":4.5,"publicationDate":"2024-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/agec.12838","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140838724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Paolo Libenzio Brignoli, Alessandro Varacca, Cornelis Gardebroek, Paolo Sckokai
{"title":"Machine learning to predict grains futures prices","authors":"Paolo Libenzio Brignoli, Alessandro Varacca, Cornelis Gardebroek, Paolo Sckokai","doi":"10.1111/agec.12828","DOIUrl":"10.1111/agec.12828","url":null,"abstract":"<p>Accurate commodity price forecasts are crucial for stakeholders in agricultural supply chains. They support informed marketing decisions, risk management, and investment strategies. Machine learning methods have significant potential to provide accurate forecasts by maximizing out-of-sample accuracy. However, their inherent complexity makes it challenging to understand the appropriate data pre-processing steps to ensure proper functionality. This study compares the forecasting performance of Long Short-Term Memory Recurrent Neural Networks (LSTM-RNNs) with classical econometric time series models for corn futures prices. The study considers various combinations of data pre-processing techniques, variable clusters, and forecast horizons. Our results indicate that LSTM-RNNs consistently outperform classical methods, particularly for longer forecast horizons. In particular, our findings demonstrate that LSTM-RNNs are capable of automatically handling structural breaks, resulting in more accurate forecasts when trained on datasets that include such shocks. However, in our setting, LSTM-RNNs struggle to deal with seasonality and trend components, necessitating specific data pre-processing procedures for their removal.</p>","PeriodicalId":50837,"journal":{"name":"Agricultural Economics","volume":"55 3","pages":"479-497"},"PeriodicalIF":4.1,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140302867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dela-Dem Doe Fiankor, Bernhard Dalheimer, Daniele Curzi, Onno Hoffmeister, Bernhard Brümmer
{"title":"Does it matter how we ship the good apples out? On specific tariffs, transport modes, and agricultural export prices","authors":"Dela-Dem Doe Fiankor, Bernhard Dalheimer, Daniele Curzi, Onno Hoffmeister, Bernhard Brümmer","doi":"10.1111/agec.12829","DOIUrl":"10.1111/agec.12829","url":null,"abstract":"<p>Free-on-board (FOB) export prices for identical products from the same origin often differ across destinations, even when accounting for the trade costs and attributes of the destination country. One explanation for this observed price difference is per-unit trade costs, and the ability of exporters to vary their markups and/or product quality. Using a novel dataset that details trade flows between countries by mode of transport, we estimate the transport mode-specific effect of a per-unit trade cost, specifically specific tariffs, on the FOB export prices of agricultural products. We find an elasticity of specific tariffs to export prices of 1.8%. However, the estimates are heterogeneous across modes of transport. The elasticity of specific tariffs to export prices is 2% for air transport, 5% for road transport, and .3% for sea cargo. Since the observed positive export price effect can reflect product quality differences or markups, we account for the quality element and find that for a given product quality, markups increase with increasing specific tariffs. This form of price discrimination is less pronounced for higher-quality products that are predominantly shipped by air.</p>","PeriodicalId":50837,"journal":{"name":"Agricultural Economics","volume":"55 3","pages":"498-514"},"PeriodicalIF":4.1,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/agec.12829","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140154928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Silas Ongudi, Djiby Thiam, Mario J. Miranda, Sam Abdoul
{"title":"The direct and indirect effects of cash transfer program on the consumption of nutrients: Evidence from Kenya","authors":"Silas Ongudi, Djiby Thiam, Mario J. Miranda, Sam Abdoul","doi":"10.1111/agec.12827","DOIUrl":"10.1111/agec.12827","url":null,"abstract":"<p>How does the receipt of a cash transfer impact consumption of nutrients, vitamins, and minerals in households? To answer this question, we use a randomized controlled trial dataset from Hunger Safety Net Program (HSNP) with 9,246 households spread across the four districts (Turkana, Marsabit, Wajir, and Mandera) of Kenya. In the experiment, HSNP treated households received a bi-monthly cash transfer of about United States of America Dollar (USD) 20 relative to households in control sub-locations. Using difference in-difference specification, we find that HSNP poor beneficiary households in treated households increased (by approximately 96%, 50%, and 61%) the consumption of vitamins A, C, and beta carotene, respectively compared to those in control sub-locations. Moreover, HSNP non-poor, non-beneficiary households residing in treated sub-locations increased (by about 70% and 46%) the consumption of vitamin A and Beta carotene, respectively compared to those in control sub-locations. In addition, HSNP-poor beneficiary households in treated sub-locations sourced most of their nutrients, vitamins, and minerals from the market. We rule out alternative pathways that could potentially increase consumption and conclude that a rise in consumption amongst HSNP non-poor, non-beneficiary households is due to sharing of HSNP transfer amongst social network members.</p>","PeriodicalId":50837,"journal":{"name":"Agricultural Economics","volume":"55 3","pages":"454-478"},"PeriodicalIF":4.1,"publicationDate":"2024-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/agec.12827","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140097553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Investigating the economic impact of climate change on agriculture in Iran: Spatial spillovers matter","authors":"Sayed Morteza Malaekeh, Layla Shiva, Ammar Safaie","doi":"10.1111/agec.12821","DOIUrl":"10.1111/agec.12821","url":null,"abstract":"<p>In this study, we enhance our understanding of the economic impacts of climate change on agriculture in Iran to provide further information for moving Iran's climate policy forward by linking farmland net revenue to novel climatic and non-climatic variables. We take advantage of spatial panel econometrics to better circumvent omitted factors extraneous to the agricultural sector and to develop a more reliable and consistent model when data are inherently spatial. In contrast to conventional panel studies which relied on year-to-year weather observations, we exploit a hybrid approach to compromise between the disadvantages and advantages of longer-term cross-sectional analysis and shorter-term panel models. We estimate the potential impacts of climate change on agriculture under several global warming scenarios based on the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6). We find that (I) farmlands’ net revenues are projected to decline by 8%–19% and 14%–51% by 2050 and 2080; (II) the distributional impacts of climate change would highly depend on climate zones and geographical locations; (III) a few counties might benefit from climate changes; (IV) finally, failing to account for spatial spillovers when they are present leads to a misspecified model.</p>","PeriodicalId":50837,"journal":{"name":"Agricultural Economics","volume":"55 3","pages":"433-453"},"PeriodicalIF":4.1,"publicationDate":"2024-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140097554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Price support policy and market price dynamics: The case of Indian wheat","authors":"Ashutosh K. Tripathi","doi":"10.1111/agec.12825","DOIUrl":"10.1111/agec.12825","url":null,"abstract":"<p>The study investigates the effect of price support policies on market price distribution and its dynamics in the Indian wheat market. The analysis uses a quantile autoregression model that provides a flexible representation of price dynamics and the 2001–2020 monthly wholesale market price data. The analysis is conducted conditional on the net stock level held in the previous period. The results reveal that the net purchase by the government prevented very low market prices for wheat but resulted in price spikes. It has a price-enhancing effect as well. The associated moments of price distribution show that public stockholding reduced variation in market price distribution. However, the government's release of stock did not prevent price rises. Findings show that dynamic adjustments tend to be qualitatively different across regimes. Government intervention in the grain market reduced stability through dynamic adjustments in wheat market prices. The results have policy implications for India and other countries in Southeast Asia in the context of the WTO's negotiations on public stockholdings and using public stockholdings as an instrument in addressing price volatility and food shortages.</p>","PeriodicalId":50837,"journal":{"name":"Agricultural Economics","volume":"55 2","pages":"412-427"},"PeriodicalIF":4.1,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140054867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Impact of the Ruble exchange rate regime and Russia's war in Ukraine on wheat prices in Russia","authors":"Stanislav Yugay, Linde Götz, Miranda Svanidze","doi":"10.1111/agec.12822","DOIUrl":"10.1111/agec.12822","url":null,"abstract":"<p>We assess exchange rate pass-through when the Ruble exchange rate was managed in comparison with when it became free-floating. Estimates of the error correction model for milling wheat prices suggest exchange rate pass-through to be strongest in Russia's North Caucasus, the region closest to the Black Sea ports, and weakest in the remote regions of Volga and West Siberia since the Ruble exchange rate became free-floating in 2014. In contrast, we find Russian regional wheat prices and the Ruble/USD exchange rate not cointegrated when the exchange rate was managed. Further, feed wheat (Class 5) is only weakly integrated compared to wheat Classes 3 and 4 for human consumption. With Russia's invasion of Ukraine, exchange rate pass-through to Russian wheat prices has decreased sharply. Thus, the Ukraine war drives the disintegration of Russia's wheat sector from international markets and adds to the risks of supply chain disruption and geopolitical risks, which may increase export supply volatility. To strengthen trade resilience, countries that are dependent on wheat imports should diversify their import sources.</p>","PeriodicalId":50837,"journal":{"name":"Agricultural Economics","volume":"55 2","pages":"384-411"},"PeriodicalIF":4.1,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/agec.12822","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140097714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Impact of farm subsidies on global agricultural productivity","authors":"Abdullah Mamun","doi":"10.1111/agec.12823","DOIUrl":"10.1111/agec.12823","url":null,"abstract":"<p>The agriculture sector receives substantial fiscal subsidies in various forms, including through programs that are linked to production and others that are decoupled. As the sector has reached the technology frontier in production over the last three decades or so, particularly in high- and middle-income countries, it is intriguing to investigate the impact of subsidies on productivity at aggregate level. This study examines the impact of subsidies on productivity growth in agriculture globally using a long time series on the nominal rate of assistance for 42 countries that covers over 80% of agricultural production. The econometric results show heterogenous effects from various subsidy instruments depending on the choice of productivity measure. Regression results suggest a strong positive effect of input subsidies on both output growth and labor productivity. A positive but relatively small impact of output subsidies is found on output growth only.</p>","PeriodicalId":50837,"journal":{"name":"Agricultural Economics","volume":"55 2","pages":"346-364"},"PeriodicalIF":4.1,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140046465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On the willingness to pay for food sustainability labelling: A meta-analysis","authors":"Giovanna Piracci, Emilia Lamonaca, Fabio Gaetano Santeramo, Fabio Boncinelli, Leonardo Casini","doi":"10.1111/agec.12826","DOIUrl":"10.1111/agec.12826","url":null,"abstract":"<p>Sustainability labelling is an extremely complex, multifaceted, and debated topic. Through a systematic and meta-analytical approach, we disentangled the informative contents of environmental and social labels and investigated their effect on the consumer willingness to pay for food products. The premium prices for sustainability labels are largely heterogeneous depending on the information disclosed. Generic and specific messages seem not to differ in terms of consumer acceptance. Not all facets are equally important as social issues tend to be less considered. Policy interventions should combine hard and soft measures to holistically achieve sustainability in the food system.</p>","PeriodicalId":50837,"journal":{"name":"Agricultural Economics","volume":"55 2","pages":"329-345"},"PeriodicalIF":4.1,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140036274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}