nep-agr New Economics Papers
on Agricultural Economics
Issue of 2021‒08‒30
103 papers chosen by



  1. Modelling environmental and climate ambition in the agricultural sector with the CAPRI model By BARREIRO HURLE Jesus; BOGONOS Mariia; HIMICS Mihaly; HRISTOV Jordan; PEREZ DOMINGUEZ Ignacio; SAHOO Amarendra; SALPUTRA Guna; WEISS Franz; BALDONI Edoardo; ELLEBY Christian
  2. Adoption of sustainable agricultural practices in the context of urbanisation and environmental stress – Evidence from farmers in the rural-urban interface of Bangalore, India By Preusse, Verena; Wollni, Meike
  3. IFAD Research Series Issues 66 - Can perceptions of reduction in physical water availability affect irrigation behaviour? Evidence from Jordan By Kafle, Kashi; Balasubramanya, Soumya
  4. Yield index insurance and farmers’ resilience in Ethiopia: Analysis using a farm-level crop and economic integrated simulation approach By Bizimana, Jean Claude; Bryant, Henry L.; Worqlul, Abeyou W.; Richardson, James W.
  5. Climate Risk and Planting Patterns: An Examination of the Direct and Indirect Effects of Changing Precipitation on the Behavior of Bangladeshi Farmers By Wheatley, W. Parker; Pede, Valerien O.; Khanam, Taznoore; Yamano, Takashi
  6. How Beliefs about Climate Change Adapt? An Assessment with a Natural Experiment By Lee, Seo Woo; Feng, Hongli; Hennessy, David A.
  7. Smart Specialisation in the Context of Blue Economy – Analysis of Desalination Sector By POST Jan; DE JONG Pieter; MALLORY Matt; DOUSSINEAU Mathieu; GNAMUS Ales
  8. Price, credit or uncertainty? Increasing small-scale irrigation in Ethiopia By Balasubramanya, Soumya; Buisson, Marie-Charlotte; Mitra, Archisman; Stifel, David
  9. Does Omitting Downstream Water Quality Change the Economic Benefits of Nutrient Reduction? Evidence from a Discrete Choice Experiment By Yau-Huo Shr; Wendong Zhang
  10. Measuring demand and network effects for a new technology to improve food safety among smallholder farmers in Sub-Saharan Africa By Arias-Granada, Yurani; Bauchet, Jonathan; Ricker-Gilbert, Jacob
  11. Are agri-environmental schemes boosting farm survival? By Lovén, Ida; Nordin, Martin
  12. Measuring the Impacts of Repurposing Agricultural Support on Global Agriculture By Laborde, David; Mamun, Abdullah A.; Martin, William J.; Piñeiro, Valeria; Vos, Rob
  13. Farm Labor Productivity and Mechanization By Hamilton, Stephen F.; Richards, Timothy J.; Shafran, Aric; Vasilaky, Kathryn
  14. Resolving the Reality Gap in Farm Regulation Voting Models By Hopkins, Kelsey A.; McKendree, Melissa G. S.; Schaefer, K. Aleks; Rice, Emma D.
  15. Climate shocks, agriculture, and migration in Nepal: Disentangling the interdependencies By Aslihan Arslan; Eva-Maria Egger; Erdgin Mane; Vanya Slavchevska
  16. Impact of CFAP and MFP Payments on Ag Production Loans By Martinez, Charles; Boyer, Christopher N.; Smith, Aaron; Yu, Tun-Hsiang E.; Rabinowitz, Adam N.
  17. The role of time preferences in the demand for safer food products: Evidence from Nigeria By Parkhi, Charuta M.; Liverpool-Tasie, Saweda; Caputo, Vincenzina
  18. Assessing and Improving USDA's Farm Income Baseline Projections By Regmi, Madhav; Featherstone, Allen M.; Briggeman, Brian C.; Subedi, Dipak
  19. Optimal quality gradation in organic labels: evidence from a structural econometrics model By Albert Scott, Francisco; Sesmero, Juan Pablo; Balagtas, Joseph V.
  20. Agri-food Products Live Streaming: Fad or A Rising Marketing Channel? By Yang, Zhengliang; Du, Xiaoxue; Hatzenbuehler, Patrick; Lu, Liang
  21. Exploring Changes in Local Food Purchasing Patterns during COVID-19: Insights from a Nationwide Consumer Survey By Edmondson, Hailey; Thilmany McFadden, Dawn D.; Jablonski, Becca B. R.
  22. Impacts of An African Swine Fever Outbreak in the United States: Implications on National and Iowa Agriculture By Carriquiry, Miguel A.; Elobeid, Amani E.; Hayes, Dermot J.; Swenson, David A.
  23. U.S. Milk Price Leadership Among Production Leaders By Hughes, Megan N.; Ma, Meilin; Mallory, Mindy L.; O'Connor, Kylie
  24. The Impact of Minimum Wage Shocks on Low-Skilled Workers in the United States: Evidence from the H-2A Visa Agricultural Guestworker Program By Rutledge, Zachariah; Richards, Timothy J.; Martin, Phillip; Castillo, Marcelo J.
  25. Impact of climate smart agriculture on food security: an agent-based analysis By Bazzana, Davide; Foltz, Jeremy D.; Zhang, Ying
  26. Does Environmental Information Motivate Sustainability? Evidence from a Randomized Control Experiment and Auction By Yim, Hyejin; Katare, Bhagyashree; Wetzstein, Michael E.; Park, Timothy A.; Wang, Hong Holly
  27. Knowledge for a warmer world: a patent analysis of climate change adaptation technologies By Hötte, Kerstin; Jee, Su Jung; Srivastav, Sugandha
  28. Roads, Trade, and Development: Evidence from the Agricultural Boom in Brazil By He, Xi; DePaula, Guilherme M.; Zhang, Wendong
  29. Longer run effects of one-time subsidy on adoption of a new agricultural technology: Evidence from a randomized control trial in Uganda By SHAH, MRUNAL; Ricker-Gilbert, Jacob; Omotilewa, Oluwatoba J.
  30. Freezing days matter in estimating the impacts of climate change on winter wheat yield By Da, Yabin; Xu, Yangyang; Yi, Fujin; McCarl, Bruce A.
  31. How do repeated violent shocks affect a country’s agricultural transformation?: The case of Colombia By Marcillo, Edgar; Useche, Maria P.; Reimão, Maira
  32. COMBATTING HARDENED SOILS FOR AGRICULTURAL PRODUCTIVITY: A PROPOSAL FOR MEASURING FARMER PREFERENCES FOR SOIL AND WATER CONSERVATION METHODS IN DOSSO, NIGER By Biedny, Christina; Mason, Nicole M.; Caputo, Vincenzina; Snapp, Sieglinde S.
  33. Cost Effectiveness of California’s Clean Air Act Agricultural Equipment Incentives By McCullough, Michael P.; Hamilton, Lynn L.; Walters, Cory G.
  34. Payments from Agricultural Conservation Programs and Cover Crop Adoption: Evidence from County-Level Panel Data in the U.S. Corn Belt By Park, Byungyul; Rejesus, Roderick M.; Aglasan, Serkan; Hagen, Stephen; Salas, William
  35. Economics of By-Product Feeds in Dairy Rations, With Implications for Resource Use and Environmental Consequences By Somerville, Scott; Hart, Jarrett; Sumner, Daniel A.
  36. Effect of Crop Insurance Participation on Farm Bankruptcies and Loan Delinquencies By Lee, Daemyung; Rejesus, Roderick M.; Aglasan, Serkan; Connor, Lawson; Dinterman, Robert
  37. Liberalization in Moderation: Analyzing Expanded Alcohol Retail in Three States By Palardy, Nathan P.; Costanigro, Marco; Cannon, Joseph P.; Bayham, Jude
  38. Designing Carbon Payments to Incentivize Energy-crop Based Carbon Sequestration and Mitigation: An Optimal Control Approach By Sharma, Bijay P.; Khanna, Madhu; Miao, Ruiqing
  39. The Pandemic, The Climate, and Productivity By C. A. K. Lovell
  40. Latent Class Modelling for a Robust Assessment of Productivity: Application to French Grazing Livestock Farms By K Hervé Dakpo; Laure Latruffe; Yann Desjeux; Philippe Jeanneaux
  41. Impact of Climate Change on Chemical Inputs: Evidence of Pesticide Usage from China By Yi, Fujin; Liu, Huilin; Quan, Quan
  42. Producer Beliefs and Conservation Decisions: The Impact of Perceived Water Security on Irrigation Technology Adoption By Blumberg, Joey; Goemans, Christopher; Manning, Dale
  43. Optimal Design of Vertical Coordination Strategies for Environmental Conservation Under Yield Uncertainty By Hughes, Megan N.; Reeling, Carson; Ma, Meilin
  44. Composite Indicators for Incorporating Environmental Externalities into On-farm Economic Decision-Making using Farm Management Information Systems By Gallagher, Nicholas; Mitchell, Paul D.; Ruark, Matt; Shelly, Kevin
  45. Conservation Strategies That Address Habitat Loss and Fragmentation: Implications for Forest Cover Change and Wildlife Behavior By Collins, Amy C.
  46. Global overview of hemp production and the market of hemp-derived CBD in the U.S. By Cruz, Julio C.; House, Lisa A.; Court, Christa D.; Blare, Trent D.
  47. Is there a Need for Grading Reform? Differences in Grading Patterns between Departments in the College of Agriculture and Life Sciences at Texas A&M By Mjelde, James; Yeritsyan, Anna
  48. Food Insecurity and Food Production Activities of Older Households By Berning, Joshua P.; Bayham, Jude; Bonanno, Alessandro; Cleary, Rebecca; Baishya, Pratiksha
  49. How Is Covid-19 Impacting US Household Food Spending? By Huang, Kuan-Ming; Etienne, Xiaoli L.; Sant'Anna, Ana Claudia
  50. Media Exposure and Midwestern Farmers' Responses to the U.S-China Trade War By Li, Minghao; He, Xi; Zhang, Wendong; Gbeda, James M.; Qu, Shuyang; Rodgriguez, Lulu
  51. Who Wins and Loses from a Food-Safety Incident: Evidence from the 2018 Romaine Lettuce E. coli Outbreak By Goodhue, Rachael E.; Kiesel, Kristin; Sexton, Richard J.; Spalding, Ashley
  52. Does the quality conscious consumer really exist? How attitude-based segmentation is reflected in stated and revealed preferences for food products with special quality characteristics By Grunert, Klaus G G.; Hesselberg, Julie
  53. Evaluating the Profitability of a Small Grain Enterprise and a Novel Pull Behind Combine for Small Scale Farming in Western Wisconsin By Howry, Sierra S.; Jungbluth, Angela; Ratliff, English L.
  54. Consumer valuation of and attitudes towards novel foods produced with NPETs: A review By Beghin, John; Gustafson, Christopher
  55. Groundwater permit trading and potential groundwater saving in Kansas By Ha, Sang Su; Sampson, Gabriel; Min, Doohong
  56. On the palm oil - biodiversity tradeoff: Environmental performance of smallholder producers By Dalheimer, Bernhard; Brambach, Fabian; Yanita, Mirawati; Kreft, Holger; Bruemmer, Bernhard
  57. Exploring the Relationship Between Grazing, Severe Drought, and Conservation Program Enrollment By Hensen, Reid; Mooney, Daniel F.; Hill, Alexandra E.; Fernandez-Gimenez, Maria
  58. Exchange Rate Volatility and Global Food Supply Chains By Sandro Steinbach
  59. What’s past is prologue? The effect of prior losses on agricultural risk management By Bryan, Calvin; Manning, Dale; Goemans, Christopher; Sloggy, Matthew R.
  60. New Mexico Livestock Producers' Interest with State Meat Inspection Program By Martinez, Dillen; Robinson, Chadelle R.H.; Miller, Maryfrances
  61. Adapting Nitrogen Management to Climate Change: Evidence from Field Experiments in Iowa By Choi, Eseul; DePaula, Guilherme M.; Kyveryga, Peter; Fey, Suzanne
  62. Impact of Energy Shocks on U.S. Agriculture: the REAP Model Approach By Bosch, Darrell J.; Zhang, Wei; Hu, Chenyang
  63. Food without Fire: Environmental and Nutritional Impacts from a Solar Cook Stove Field Experiment By McCann, Laura M.; Michler, Jeffrey D.; Estrada Carmona, Natalia; Raneri, Jessica; McCann, Laura E.
  64. Teaching Enterprise Budgets: Case Using Small Pull Behind Harvester for Small Scale Farming By Howry, Sierra S.; Ratliff, English L.; Jungbluth, Angela
  65. Food-borne Illnesses and Liability in the U.S. By Bahalou Horeh, Marziyeh; Elbakidze, Levan; Sant'Anna, Ana Cluadia
  66. What factors contribute to the efficiency of Midwest crop farmers? By Rocha, Adauto B.; Fulginiti, Lilyan E.; Perrin, Richard K.; Walters, Cory G.
  67. The Impact of Information and Communication Technology on the Productivity and Efficiency of Smallholder Farms in China By Kang, Shijia; Wimmer, Stefan; Sauer, Johannes
  68. Pesticide-free versus conventional farming: Determinants in vegetable production in Vietnam. By Tran, Lan T.; McCann, Laura M.; Skevas, Teo
  69. Does Land Endowment Impact Parental Educational Expectations? Evidence from Rural China By Zhang, Mengling; Chen, Zhaojiu; Wu, Feng
  70. Illinois Farmers' Beliefs about the Maximum Return to Nitrogen (MRTN) Recommendation By Sellars, Sarah C.; Schnitkey, Gary D.; Gentry, Laura F.; Paulson, Nick
  71. Is there a future for geographical indication labeling in the United States? By Lineback, Caitlinn; Caputo, Vincenzina; McKendree, Melissa G. S.; Kilders, Valerie
  72. Risk, Arbitrage, and Spatial Price Relationships: Insights from China’s Hog Market under the African Swine Fever By Delgado, Michael; Ma, Meilin; Wang, Hong Holly
  73. A Flexible Model of Food Security: Estimation and Implications for Prediction By Davis, Will; Gregory, Christian A.; Tchernis, Rusty
  74. Growth at Risk From Climate Change By Michael T. Kiley
  75. The grievances of a failed reform: Chilean land reform and conflict with indigenous communities By Jaimovich, Dany; Toledo, Felipe
  76. Heterogeneity in Farm Exit and Level of Government Payments: A Comparison between the Corn-Belt States and the US By Devkota, Satis; Subedi, Dipak; Todd, Jessica E.; Adhikari, Shyam
  77. Market power in food industry in selected EU Member States By NES Kjersti; COLEN Liesbeth; CIAIAN Pavel
  78. Comparing Structural Estimation of Use and Non-Use Values for Water Quality to Simpler ad hoc Approaches By Kim, Hyunjung; Herriges, Joseph A.; Lupi, Frank
  79. An Empirical Analysis of the Effectiveness of the US Tobacco Control Policies with Endogenous Polices and Prices By Heboyan, Vahé; Hovhannisyan, Vardges; Bakhtavoryan, Rafael; Kondaridze, Magdana
  80. Econometric Cost Models for Restoration Planning: An Application to Fish Passage Barriers in the Pacific Northwest By Van Deynze, Braeden; Fonner, Robert C.; Feist, Blake; Jardine, Sunny L.; Holland, Daniel S.
  81. Is Meat Too Cheap? Towards Optimal Meat Taxation By Funke, Franziska; Mattauch, Linus; van den Bijgaart, Inge; Godfray, Charles; Hepburn, Cameron; Klenert, David; Springmann, Marco; Treich, Nicholas
  82. Are Consumers Willing to Accept Gene Edited Fruit? An Application to Quality Traits for Fresh Table Grapes By Uddin, Azhar; Gallardo, Karina; Rickard, Bradley J.; Alston, Julian M.; Sambucci, Olena
  83. Censored demand system estimation By Grace Melo
  84. Identifying Threshold for Economically Optimal Disease Management: The Case of Tomato Bacterial Spot By Soto-Caro, Ariel; Wu, Feng; Vallad, Gary; Guan, Zhengfei
  85. Predicted Distributional Impacts of Climate Change Policy on Employment By Lynn Riggs; Livvy Mitchell
  86. U.S. agricultural banks’ efficiency under COVID-19 Pandemic conditions: A two-stage DEA analysis By Gao, Penghui; Secor, William; Escalante, Cesar L.
  87. Maladaptation of U.S. Corn and Soybean Yields to a Changing Climate By Yu, Chengzheng; Miao, Ruiqing; Khanna, Madhu
  88. ECONOMIC AND RISK PREMIUMS COMPARISON FOR RISK AVERSE DECISION MAKERS OF COTTON TILLAGE SYSTEMS WITH DIFFERENT IRRIGATION LEVELS AND PRODUCTIVY EFFICIENCY RATES By Abelló, Francisco; Ribera, Luis A.; DeLaune, Paul B.
  89. Outstanding in the Field: Impacts of Public Small Grains Breeding in Virginia By Garber, Benjamin F.; Alwang, Jeffrey; Norton, George W.
  90. Effects of social norm and educational interventions on household organics recycling: Evidence from two alternative curbside organics recycling programs By Heshmatpour, Masoumeh; Peterson, Hikaru Hanawa
  91. Sell It Now or Later? A Decision-making Model for Feeder Cattle Selling in New York State By Yan, Minhao; Schmit, Todd M.; Gomez, Miguel I.; Baker, Michael James
  92. Household Food Expenditures at Dollar Stores and Implications for Health, 2008-18 By Page, Elina T.; Feng, Wenhui; Saravana, Divya; Cash, Sean B.
  93. Consumer Preferences for Food Away from Home in a Multi-Choice Environment By Kilders, Valerie; Caputo, Vincenzina; Lusk, Jayson L.
  94. Empirical Modeling of the Risk and Determinants Associated with Food-Related Illnesses By Won, Sunjae; Goodwin, Barry K.; Boys, Kathryn A.
  95. The relative neglect of agriculture in Mozambique By João Z. Carrilho; Ines A. Ferreira; Rui N. Ribeiro; Finn Tarp
  96. Donations to Food Banks amidst the COVID-19 pandemic: Experiment on impulsive vs deliberate nudges By Lee, Sunyoung; Zhang, Yu Yvette; Nayga, Rodolfo M.
  97. Economic and Environmental Value of Screening for Herbicide Resistance in Barnyardgrass in Arkansas By Peterson-Wilhelm, Bailey; Durand-Morat, Alvaro; Nalley, Lawton L.; Norsworthy, Jason; Bagavathiannan, Muthukumar V.
  98. Choice variation by product and processing level – Consumer’s preferences for gene-edited food products under different information regimes By Caputo, Vincenzina; Kilders, Valerie; Lusk, Jayson L.
  99. Meal Kit Preferences during COVID-19 Pandemic: Exploring User-Generated Content with Natural Language Processing Techniques By Li, Ran; Xu, Yuetong; Chen, Jian; Qi, Danyi
  100. Current and future market applications of new genomic techniques By PARISI Claudia; RODRIGUEZ CEREZO Emilio
  101. Applying Artificial Intelligence in Agriculture: Evidence from Washington State Apple Orchards By Amin, Modhurima D.; Badruddoza, Syed; Mantle, Steve
  102. Temperature changes are associated with nonlinear effects on wheat yield in Pakistan By Rub, Abdur; Tack, Jesse B.; Barkley, Andrew P.
  103. Joint Estimation of Revealed Preference Site Selection and Stated Preference Choice Experiment Recreation Data Considering Attribute NonAttendance By Paul Hindsley; Craig E. Landry; Kurt Schnier; John C. Whitehead; Mohammadreza Zarei

  1. By: BARREIRO HURLE Jesus (European Commission - JRC); BOGONOS Mariia (European Commission - JRC); HIMICS Mihaly (European Commission - JRC); HRISTOV Jordan (European Commission - JRC); PEREZ DOMINGUEZ Ignacio (European Commission - JRC); SAHOO Amarendra (European Commission - JRC); SALPUTRA Guna (European Commission - JRC); WEISS Franz (European Commission - JRC); BALDONI Edoardo (European Commission - JRC); ELLEBY Christian (European Commission - JRC)
    Abstract: During the last 30 years, the Common Agricultural Policy has increased the importance given to improving the environmental and climate performance of the European agriculture, as confirmed by the Future CAP proposal. Furthermore, the Green Deal strategy outlined a comprehensive approach to facilitate the transition towards sustainable food systems that links in a holistic approach all actors in the system, a path sketched out in the Farm to Fork (F2F) and Biodiversity (BDS) Strategies. Reflecting this ambition, this report was a contribution to the 2030 Climate Target Plan impact assessment, based on one of the main models used by the European Commission for agricultural policy analysis (the CAPRI model), which can incorporate some of the policies put forward for accelerating the transition towards sustainable food systems. The report presents a modelled scenario of an ambitious implementation of the CAP reform proposals to measure the effects on EU agriculture including four quantitative targets put forward in the F2F and BDS strategies already reflected in the recommendations of the Commission to the Member States on their CAP Strategic Plans. These targets were selected as the ones with the greatest potential to affect agricultural environment and production. Moreover, those are the targets to which the CAP can provide specific contribution.The analysis includes a reduction of the risk and use of pesticides, a reduction of nutrient surplus, an increase of area under organic farming, and an increase of area for high-diversity landscape features. The impacts are modelled under three scenarios. One is a status quo scenario assuming no change in the CAP compared to its implementation during 2014-2020. The other two scenarios include a potential implementation of the CAP post 2020 legal proposal targeting these objectives, both with and without the targeted use of Next Generation EU funding.However, the report does not constitute an impact assessment of the strategies as such; the modelling scope does not include all of the strategies’ measures (e.g. food waste reduction targets, dietary shifts, organic action plan) which would alter the impacts reported. Not all policies that affect the transition are captured by this model. Other analytical approaches and tools are necessary to arrive at a more complete picture of the potential impacts of this transition. As these two strategies propose a comprehensive approach to move towards sustainable food systems, their inclusion requires additional assumptions to capture positive synergies between the different initiatives and additional tools to cover the limitations of the modelling approach used. Therefore, impacts should be considered representing an upper bound of the full impact of the strategies as they are partial in scope (mainly covering the supply side) and incomplete (as the required future changes in consumer behaviour are not captured in the model). Based on the assumptions made and taking into account the limitations of the analysis, modelling results indicate that reaching these four targets under the current CAP implementation achieves significant environmental benefits in the form of reductions in greenhouse gases and ammonia emissions as well as in gross nutrient surplus, though the extent in terms of positive environmental and economic benefits is not fully quantified. Results also show a decline in EU production and variations in prices and income for selected agricultural products, albeit in different degrees. This impact can be lowered by approximately one-fifth when a CAP implementation in line with the 2018 Legal Proposal and targeted to accelerate the transition to a more sustainable agriculture is assumed. The new CAP implementation also increases the positive performance of the agricultural sector in environmental terms. In both scenarios, the impacts on international markets are limited. In both scenarios, the potential to further reduce these impacts is underestimated by the fact that not all initiatives, measures and resulting synergies covered by the strategies are considered. For example, reductions in production associated with shift to organic agriculture could be mitigated with the implementation of the organic action plan. Lower livestock production could have less impact on prices and trade when accompanied by a shift towards more plant based diets and the reduction of food waste. The positive impact could also be enhanced via accelerated technological development and efficiency improvements likely to occur by 2030. Moreover, the exercise assumes that the EU acts alone. Because of this assumption, a significant part of the gains in terms of emissions in the EU is leaked to other world regions. However, as part of international climate agreements also non-EU countries have commitments to reduce GHG emissions, incorporating this to the analysis would reduce the leakage and negative impacts for the EU. Last, the report does not provide information on all the benefits derived from those targets for both the agricultural sector and the wider society, as these are not captured in the model. As such, the analysis presented is not intended to be used as the sole basis for decision-making and it would not be in any case appropriate for this purpose.The lessons learned from this report are important from a policy perspective. The agricultural sector will have to go through a challenging transition and this study – with all its limitations – shows the magnitude of the challenge. The report shows that, when it comes to the supply side, the Future CAP legal proposals provide opportunities for implementing the production-related targets of the Green Deal. By comparing the impact of four F2F and BDS strategies’ targets under an unchanged CAP and a CAP reflecting the ambitious implementation of its reform proposals the report identifies the potential impacts of the Future CAP proposal with respect to selected environmental indicators, production, income, prices and trade. However, the report also points towards areas where such a transition faces bigger challenges, for which we need effective instruments to support the sector during the transition. Some of these instruments are alreadt the focus of other complementary policy initiatives. Furthermore, it allows the identification of gaps where additional steps would be needed so that Green Deal targets are met and the transition towards sustainable food systems accelerated. Finally, the results confirm the need for global solutions to the global challenge of climate change.The report also highlights that the current modelling tools need improvements to help us prepare future impact assessments. Significant gaps exist in capturing in agro-economic models how the demand side of the food chain would respond to the required changes in demand and the supply side. Even when the analysis reported focuses on the supply side and captures most of its nuances in a satisfactory manner, some improvements are needed. For example, additional developments are needed to capture the positive feedback in yields resulting from the enhanced ecosystem services provided by improved biodiversity. In addition, while some technologies are captured in the model there are additional measures that could be introduced to further reduce the environmental impact of production; thus minimizing the trade-off between meeting targets and production impacts.In addition, the assumptions about the impacts on farm management and yields of the reduction in pesticide use and the increase in organic farming do not capture potential beneficial side effects beyond the agricultural sector (e.g. health benefits). These limitations are partly driven by the lack of comprehensive farm-level data, which results in the assessment of the relationship between farming activity and the environment in an aggregated regional level. The Commission’s proposal to move from a farm accountancy data network (FADN) to a farm sustainability data network (FSDN) will be instrumental in addressing these limitations as it would allow the better understanding of which practices work best, and within which regional and sector environment.As far as the demand side is concerned, this analysis does not incorporate the ambition related to food waste reduction, the move towards different diets or the demand side promotion of organic and sustainably produced food. Such changes would require the development of other modelling approaches incorporating assumptions on future consumer behavioural changes that cannot be captured with analyses of past consumer behaviour. In this area, data availability is an issue whose resolution would require the cooperation of the retail and processing industry. In addition, one also has to consider the magnitude of the scenario shocks (i.e. distance from baseline values to aspirational targets). Models are calibrated to a common vision of the future and their predictive performance may be decreased in extreme cases. When dealing with systemic changes, other research tools such as foresight and propective can be used in a complementary manner to inform some of the parameters that could reflect novel practices and busness models that could be developed by farmers to adapt to the new sustainable food systems paradigmAs part of its commitment to provide better scientific evidence for policy making, the JRC is working to improve knowledge on the effects (including potential co-benefits) of the measures implemented, develop the model to improve the representation of pesticides and organic farming, and explore avenues to incorporate the impact of food waste reductions and changes in diets. As for the latter, improvements on environmental and human health expected from the accelerated shift towards sustainable food systems need to be quantified using other tools. In addition, a comprehensive assessment should also incorporate a full food systems approach incorporating other phases of the food value chain and changes in consumer preferences and behaviour. The upcoming proposal for a legislative framework for sustainable food systems will require a comprehensive impact assessment. This impact assessment will have to be able to evaluate the ambition laid down for an enhanced environmental, climate and health performance of the EU’s agricultural sector as part of the broader food system. While agro-economic models will be an integral part of the tools for such an evaluation, the present exercise has identified areas where additional efforts are needed, especially in the need to capture the environment not only as a restriction for agricultural production but also as an input. The current modelling approach focuses on the trade-offs between environmental protection and agricultural production based on past experience, failing to capture the positive synergies that a better environment brings associated. These limitations are not specific to the CAPRI model. Other analyses that have looked into the impacts of some of the initiatives put forward in the strategies using other models (Beckman et al. 2020; Guyomard et al. 2020) also faced them. Ongoing research and analysis can shed light on more positive synergies associated with a better environmental footprint, thus improving the capacity of the model to capture the targets and using additional methods to estimate the benefits.
    Keywords: CAPRI Model, agricultural policy, environmental and climate ambition
    Date: 2021–07
    URL: http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc121368&r=
  2. By: Preusse, Verena; Wollni, Meike
    Keywords: International Development, Resource/Energy Economics and Policy, Community/Rural/Urban Development
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312690&r=
  3. By: Kafle, Kashi; Balasubramanya, Soumya
    Abstract: Frequent droughts and rapidly depleting groundwater reserves have deepened the water scarcity crisis in Jordan. Even though most farms use ‘water-saving’ technologies, groundwater depletion continues at an alarming rate. We investigate how perceptions of physical water availability in the past are related to farmers’ current irrigation behaviour – frequency of irrigation and methods used in determining irrigation need. Using primary data from a survey of 414 commercial farms in Mafraq and Azraq governorates, we find that respondents who perceived reduction in physical water availability and faced agricultural losses in the past irrigated more frequently and were more likely to use self-judgement in determining irrigation need. These relationships were more pronounced for smaller farms, farms with sandy soil, mono-cropping farms and farms where the owner was the manager. These effects were lower for farms that preferred internet-based and in-person approaches for receiving irrigation advice. In addition, while the frequency of irrigation was higher among stone-fruit farms, the probability of using self-judgement in determining irrigation need was higher in olive farms and vegetable farms. We argue that farmers’ irrigation behaviour must be considered for groundwater management policy and planning in Jordan.
    Keywords: Agribusiness, Agricultural and Food Policy, Food Security and Poverty
    Date: 2021–08–25
    URL: http://d.repec.org/n?u=RePEc:ags:unadrs:313230&r=
  4. By: Bizimana, Jean Claude; Bryant, Henry L.; Worqlul, Abeyou W.; Richardson, James W.
    Keywords: Agricultural and Food Policy, International Development, Risk and Uncertainty
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312815&r=
  5. By: Wheatley, W. Parker; Pede, Valerien O.; Khanam, Taznoore; Yamano, Takashi
    Keywords: International Development, Risk and Uncertainty, Agricultural and Food Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312720&r=
  6. By: Lee, Seo Woo; Feng, Hongli; Hennessy, David A.
    Keywords: Environmental Economics and Policy, Agricultural and Food Policy, Research Methods/Statistical Methods
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312918&r=
  7. By: POST Jan; DE JONG Pieter; MALLORY Matt; DOUSSINEAU Mathieu; GNAMUS Ales (European Commission - JRC)
    Abstract: The smart Specialisation strategy design and implementation offer to the territories in Europe a solid paradigm for developing effective innovation governance, improving innovation policy capacities, enhancing public-private partnerships, offering common platform for inter-regional cooperation activities and through that an operative engagement of stakeholders in the international value chains. The sustainable Smart Specialisation strategies framework can play a key role as enabler of a sustainable transformation of European economy towards the Green Deal by streamlining innovation activities around the value chains to reach the competitiveness edge of Europe vis-à-vis the rest of the world. The Blue Economy activities, by safeguarding the preservation of healthy oceans, seas and waters, represent an important component of the European Green Deal activities in the regions and Member States. One of the emerging blue economy sectors with considerable “greening” potential for a stable water supply in the ever growing areas with increasing water imbalances is the desalination sector. Besides its essential role in providing water in the areas suffering water shortages, lately seriously aggravated by the climate change impacts, the sector has a potential for creating of prosperity and employment in some territories of Europe through a combination of innovation based sustainable water, energy and chemical technologies, coupled with environmental and societal challenges. This report aims at analysing the sector from the innovation, the EU policy and regional perspectives - in the latter with examples of implementation of desalination technologies in the three types of regions with specific water supply issues across Europe, namely in the water scarce regions of the Southern Europe, in European Western and Northern regions, and in the specific case of island regions, where a stable water supply through desalination improves substantially the living conditions and local economy. Overall, the desalination sector provides a sustainable solution for agro-food systems and for integrated water provision and management in the water scarce areas, makes those often vulnerable territories more climate-resilient, efficient, cost-effective, and environmentally and socially sustainable, and contributes to climate adaptation by solving the water scarcity, food security, soil health by enhancing rainwater infiltration and water reuse, nutrition, health and well-being of population in these areas. Given the increasing climate change pressures, a holistic approach to address the global freshwater scarcity through sustainable innovative solutions is needed and the sector of desalination will be granted increasing protagonism in the endeavours to enhance territorial resilience, improve ecosystem services, biodiversity and a more sustainable agricultural production in Europe and beyond.
    Keywords: Smart Specialisation, Blue Economy, Desalination Sector
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc125905&r=
  8. By: Balasubramanya, Soumya; Buisson, Marie-Charlotte; Mitra, Archisman; Stifel, David
    Keywords: International Development, Agricultural and Food Policy, Teaching/Communication/Extension/Profession
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312900&r=
  9. By: Yau-Huo Shr; Wendong Zhang (Center for Agricultural and Rural Development (CARD))
    Abstract: Discrete choice experiments have been extensively used to value environmental quality; however, some important attributes may often be omitted due to design challenges. In the case of agricultural water pollution, omitting downstream water quality benefits could lead to biased estimates and misinterpretations of local water quality attributes presented in choice experiments. Using a split-sample design and a statewide survey of Iowa residents, we provide the first systematic evaluation of how households' willingness-to-pay for water quality improvement when downstream water quality benefits, hypoxic zone reduction in our case, are omitted. We find that omitting non-local water quality attributes significantly reduces the total economic value of nutrient reduction programs but does not bias the marginal willingness-to-pay for local water quality attributes. We also find suggestive evidence showing that such omission, in line with the theoretical prediction, only changes the preferences of respondents who are aware of the downstream impacts of plans that led to local water quality improvement. In addition, our results show that providing information on the non-local water quality benefits of nutrient reduction increases support for water quality improvement plans but only among local residents who are less informed on water quality issues.
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ias:cpaper:21-wp620&r=
  10. By: Arias-Granada, Yurani; Bauchet, Jonathan; Ricker-Gilbert, Jacob
    Keywords: International Development, Food Consumption/Nutrition/Food Safety, International Development
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312768&r=
  11. By: Lovén, Ida (AgriFood economics centre); Nordin, Martin (AgriFood economics centre)
    Abstract: A topical policy goal is to design agri-environmental schemes that not only protect the environment but also foster agricultural production. This paper contribute with new knowledge towards this ambition, exploring the role of agri-environmental schemes for farm survival. Employing rich farmlevel data on Swedish farms during 2001-2014, we explore farm survival using discrete-time hazard models and finds a significant association between agri-environmental schemes and farm survival. More specifically, the results suggests that participants are more likely to survive than farms without an agri-environmental scheme commitment and more extensive commitments favors increased survival up to a point when the commitment becomes too large in relation to other commitments and resources of the farm. Robustness analysis across subsamples of farms supports the finding that agri-environmental schemes are correlated with survival also for different groups of farms. Together, these results suggests that the agri-environmental schemes are important for farmers, and not only as a means to enable environmental protection. Consequently, this study contributes to policy, underlining the importance to encompass consequences beyond environmental concerns when assessing the overall benefits of the agri-environmental schemes.
    Keywords: agri-environmental schemes; farm survival; duration analysis; Sweden
    JEL: N50
    Date: 2020–08–21
    URL: http://d.repec.org/n?u=RePEc:hhs:luagri:2020_002&r=
  12. By: Laborde, David; Mamun, Abdullah A.; Martin, William J.; Piñeiro, Valeria; Vos, Rob
    Keywords: International Development, International Development, Environmental Economics and Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312847&r=
  13. By: Hamilton, Stephen F.; Richards, Timothy J.; Shafran, Aric; Vasilaky, Kathryn
    Keywords: Agricultural and Food Policy, Agribusiness, Productivity Analysis
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312678&r=
  14. By: Hopkins, Kelsey A.; McKendree, Melissa G. S.; Schaefer, K. Aleks; Rice, Emma D.
    Keywords: Agricultural and Food Policy, Agribusiness, Food Consumption/Nutrition/Food Safety
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312710&r=
  15. By: Aslihan Arslan; Eva-Maria Egger; Erdgin Mane; Vanya Slavchevska
    Abstract: Climate change is expected to increase the risk in agricultural production due to increasing temperatures and rainfall variability. Smallholders can adjust by diversifying income sources, including through migration. Most existing studies investigate whether households send a migrant after experiencing weather shocks, but the literature lacks evidence on migration as an ex-ante measure. In this paper, we disentangle the direct effect of weather shocks on income from agriculture from the effect of changing weather patterns over a few years on migration as a diversification strategy.
    Keywords: Climate change, Migration, Agriculture, Simultaneous equations, Nepal
    Date: 2021
    URL: http://d.repec.org/n?u=RePEc:unu:wpaper:wp-2021-131&r=
  16. By: Martinez, Charles; Boyer, Christopher N.; Smith, Aaron; Yu, Tun-Hsiang E.; Rabinowitz, Adam N.
    Keywords: Agricultural Finance, Agricultural and Food Policy, Agribusiness
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312689&r=
  17. By: Parkhi, Charuta M.; Liverpool-Tasie, Saweda; Caputo, Vincenzina
    Keywords: Food Consumption/Nutrition/Food Safety, Agribusiness, International Development
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312849&r=
  18. By: Regmi, Madhav; Featherstone, Allen M.; Briggeman, Brian C.; Subedi, Dipak
    Keywords: Agricultural Finance, Agricultural and Food Policy, Research Methods/Statistical Methods
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312655&r=
  19. By: Albert Scott, Francisco; Sesmero, Juan Pablo; Balagtas, Joseph V.
    Keywords: Marketing, Agricultural and Food Policy, Agribusiness
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312766&r=
  20. By: Yang, Zhengliang; Du, Xiaoxue; Hatzenbuehler, Patrick; Lu, Liang
    Keywords: Marketing, Agribusiness, Research Methods/Econometrics/Stats
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312633&r=
  21. By: Edmondson, Hailey; Thilmany McFadden, Dawn D.; Jablonski, Becca B. R.
    Keywords: Marketing, Agribusiness, Agricultural and Food Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312859&r=
  22. By: Carriquiry, Miguel A.; Elobeid, Amani E.; Hayes, Dermot J.; Swenson, David A.
    Keywords: International Relations/Trade, Marketing, Agricultural and Food Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312921&r=
  23. By: Hughes, Megan N.; Ma, Meilin; Mallory, Mindy L.; O'Connor, Kylie
    Keywords: Agricultural and Food Policy, Risk and Uncertainty, Marketing
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312803&r=
  24. By: Rutledge, Zachariah; Richards, Timothy J.; Martin, Phillip; Castillo, Marcelo J.
    Keywords: Agricultural and Food Policy, Community/Rural/Urban Development, Production Economics
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312698&r=
  25. By: Bazzana, Davide; Foltz, Jeremy D.; Zhang, Ying
    Keywords: Environmental Economics and Policy, International Development, Resource/Energy Economics and Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312665&r=
  26. By: Yim, Hyejin; Katare, Bhagyashree; Wetzstein, Michael E.; Park, Timothy A.; Wang, Hong Holly
    Keywords: Marketing, Agricultural and Food Policy, Research Methods/Statistical Methods
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312685&r=
  27. By: Hötte, Kerstin; Jee, Su Jung; Srivastav, Sugandha
    Abstract: Technologies help adapt to climate change but little systematic research about these technologies and their interaction with mitigation exists. We identify climate change adaptation technologies (CCATs) in US patent data to study the technological frontier in adaptation. We find that patenting in CCATs was roughly stagnant over the past decades. CCATs form two main clusters: (1) science-intensive CCATs related to agriculture, health and monitoring technologies; and (2) engineering-based for coastal, water and infrastructure adaptation. 25% of CCATs help in climate change mitigation, and we infer that synergies can be maximized through well designed policy. CCATs rely more on public R&D than other inventions, and CCAT patents are citing more science over time, indicating a growing relevance of research as a knowledge source for innovation. Policymakers can use these results to get greater clarity on where R&D support for CCATs can be directed.
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:amz:wpaper:2021-19&r=
  28. By: He, Xi; DePaula, Guilherme M.; Zhang, Wendong
    Keywords: International Development, Community/Rural/Urban Development, International Relations/Trade
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312818&r=
  29. By: SHAH, MRUNAL; Ricker-Gilbert, Jacob; Omotilewa, Oluwatoba J.
    Keywords: International Development, Research Methods/Statistical Methods, Risk and Uncertainty
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312870&r=
  30. By: Da, Yabin; Xu, Yangyang; Yi, Fujin; McCarl, Bruce A.
    Keywords: Environmental Economics and Policy, Food Consumption/Nutrition/Food Safety, International Development
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312638&r=
  31. By: Marcillo, Edgar; Useche, Maria P.; Reimão, Maira
    Keywords: Consumer/Household Economics, International Development, Community/Rural/Urban Development
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312746&r=
  32. By: Biedny, Christina; Mason, Nicole M.; Caputo, Vincenzina; Snapp, Sieglinde S.
    Keywords: Environmental Economics and Policy, International Development, Research Methods/Statistical Methods
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312722&r=
  33. By: McCullough, Michael P.; Hamilton, Lynn L.; Walters, Cory G.
    Keywords: Environmental Economics and Policy, Agricultural and Food Policy, Agribusiness
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312800&r=
  34. By: Park, Byungyul; Rejesus, Roderick M.; Aglasan, Serkan; Hagen, Stephen; Salas, William
    Keywords: Production Economics, Agricultural and Food Policy, Environmental Economics and Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312620&r=
  35. By: Somerville, Scott; Hart, Jarrett; Sumner, Daniel A.
    Keywords: Agricultural and Food Policy, Environmental Economics and Policy, Agribusiness
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312824&r=
  36. By: Lee, Daemyung; Rejesus, Roderick M.; Aglasan, Serkan; Connor, Lawson; Dinterman, Robert
    Keywords: Agricultural Finance, Risk and Uncertainty, Agricultural and Food Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312731&r=
  37. By: Palardy, Nathan P.; Costanigro, Marco; Cannon, Joseph P.; Bayham, Jude
    Keywords: Marketing, Agricultural and Food Policy, Agribusiness
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312911&r=
  38. By: Sharma, Bijay P.; Khanna, Madhu; Miao, Ruiqing
    Keywords: Resource/Energy Economics and Policy, Production Economics, Agricultural and Food Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312745&r=
  39. By: C. A. K. Lovell (The University of Queensland, Australia)
    Abstract: The pandemic depression and climate change have buffeted the global economy and more. The pandemic has caused the deepest depression in a century, has had a devastating impact on human health and morbidity, and has exacerbated global inequalities. Climate change has exacted its own economic toll, has had its own adverse impacts on human health and global inequalities, and continues to wreak havoc on the global environment. I survey the literatures exploring the two challenges as at mid-2021, separately and jointly because they interact. I survey the impacts of the pandemic on global value chains, on aggregate and business output and employment, and on productivity. I survey the impacts of climate change on aggregate and business adaptation, the last line of defence, on agriculture, where the impacts are particularly severe, on business, and on productivity. I continue with an exploration into the linkages between the two challenges, and efforts to decouple them through a wide range of green growth policies. Throughout I emphasise the important role played by management, at business, national and global levels, in allocating resources to counter the impacts of both challenges. I acknowledge that the pandemic and climate change are evolving, the former encouragingly rapidly until the unwelcome arrival of the Delta variant, and the latter depressingly slowly, and consequently this survey is aiming at a pair of moving targets.
    Keywords: pandemic, climate change, green growth, productivity, management
    JEL: O44 Q54 Q58
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:qld:uqcepa:165&r=
  40. By: K Hervé Dakpo (ECO-PUB - Economie Publique - AgroParisTech - Université Paris-Saclay - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, D-ERDW - Department of Earth Sciences [Swiss Federal Institute of Technology - ETH Zürich] - ETH Zürich - Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich]); Laure Latruffe (GREThA - Groupe de Recherche en Economie Théorique et Appliquée - UB - Université de Bordeaux - CNRS - Centre National de la Recherche Scientifique); Yann Desjeux (GREThA - Groupe de Recherche en Economie Théorique et Appliquée - UB - Université de Bordeaux - CNRS - Centre National de la Recherche Scientifique); Philippe Jeanneaux (VAS - VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement, Territoires - Territoires - AgroParisTech - VAS - VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement - AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - UCA - Université Clermont Auvergne)
    Abstract: Our objective is to extend the latent class stochastic frontier (LCSFM) model to compute productivity change, using the robust transitive productivity Fare-Primont index. The application is to three types of grazing livestock farms in France over the period 2002-2016. The LCSFM identified two classes of farms, intensive farms and extensive farms. Results indicate that productivity change and its components show only small differences between the LCSFM and the pooled model that does not account for heterogeneity. Differences across classes exist, but depend on farm type.
    Abstract: Notre objectif est d'étendre le modèle de frontière stochastique à classe de latence (LCSFM) pour calculer le changement de productivité, en utilisant l'indice de productivité transitif robuste de Fare-Primont. L'application porte sur trois types d'exploitations d'élevage herbivore en France sur la période 2002-2016. Le LCSFM a identifié deux classes d'exploitations, les exploitations intensives et les exploitations extensives. Les résultats indiquent que la variation de la productivité et ses composantes ne présentent que de faibles différences entre le LCSFM et le modèle groupé qui ne tient pas compte de l'hétérogénéité. Les différences entre les classes existent, mais dépendent du type d'exploitation.
    Keywords: Efficiency,Färe-Primont,France,Grazing livestock farms,Latent class stochastic frontier,Productivity
    Date: 2021–02–04
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-03280138&r=
  41. By: Yi, Fujin; Liu, Huilin; Quan, Quan
    Keywords: Environmental Economics and Policy, Research Methods/Statistical Methods, Risk and Uncertainty
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312853&r=
  42. By: Blumberg, Joey; Goemans, Christopher; Manning, Dale
    Keywords: Resource/Energy Economics and Policy, Production Economics, Risk and Uncertainty
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312796&r=
  43. By: Hughes, Megan N.; Reeling, Carson; Ma, Meilin
    Keywords: Environmental Economics and Policy, Agricultural and Food Policy, Institutional and Behavioral Economics
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312786&r=
  44. By: Gallagher, Nicholas; Mitchell, Paul D.; Ruark, Matt; Shelly, Kevin
    Keywords: Production Economics, Agricultural Finance, Research Methods/Statistical Methods
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312809&r=
  45. By: Collins, Amy C.
    Abstract: Habitat loss and fragmentation is currently the primary driver of biodiversity decline. Community forest management and wildlife crossing structures are two common conservation strategies applied to mitigate habitat loss and fragmentation. Community forest management is an approach that enables local communities to participate in forest management in order to reduce deforestation, and crossing structures are intended to mitigate the negative impacts of roads in fragmenting the landscape. To implement efficient design, their effectiveness needs to be examined using rigorous and appropriate methods. Herein, I assess the efficacy of each in the context of counterfactual assessments and baseline conditions. Using Pemba Island, Tanzania, as a case study, I monitor Community forest management, and use unprotected areas as the baseline. For wildlife crossing structures I examine structures along California highways, and use adjacent wildland areas absent of roads as the baseline. I employ methods such as remote sensing and hierarchical modeling to decipher forest cover change, wildlife movement, and behavioral responses within a fragmented habitat. I focus on particular anthropogenic stressors that may contribute to the efficacy of Community forest management and wildlife crossing structures, such as human population density, and light and noise pollution. The results offer solutions to the broader conservation community in how to evaluate the conservation tools we are currently utilizing. Furthermore, results guide the decision-making process for wildlife managers, practitioners, and agencies specific to these case studies and future conservation projects.
    Keywords: Life Sciences, road ecology, forest management, conservation
    Date: 2020–01–01
    URL: http://d.repec.org/n?u=RePEc:cdl:itsdav:qt94t1f52r&r=
  46. By: Cruz, Julio C.; House, Lisa A.; Court, Christa D.; Blare, Trent D.
    Keywords: Production Economics, Agricultural and Food Policy, Productivity Analysis
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312927&r=
  47. By: Mjelde, James; Yeritsyan, Anna
    Keywords: Teaching/Communication/Extension/Profession, Institutional and Behavioral Economics, Agricultural and Food Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312659&r=
  48. By: Berning, Joshua P.; Bayham, Jude; Bonanno, Alessandro; Cleary, Rebecca; Baishya, Pratiksha
    Keywords: Food Consumption/Nutrition/Food Safety, Consumer/Household Economics, Health Economics and Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312801&r=
  49. By: Huang, Kuan-Ming; Etienne, Xiaoli L.; Sant'Anna, Ana Claudia
    Keywords: Consumer/Household Economics, Food Consumption/Nutrition/Food Safety, Agricultural Finance
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312841&r=
  50. By: Li, Minghao; He, Xi; Zhang, Wendong; Gbeda, James M.; Qu, Shuyang; Rodgriguez, Lulu
    Keywords: International Relations/Trade, Agricultural and Food Policy, Marketing
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312684&r=
  51. By: Goodhue, Rachael E.; Kiesel, Kristin; Sexton, Richard J.; Spalding, Ashley
    Keywords: Food Consumption/Nutrition/Food Safety, Marketing, Agricultural and Food Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312897&r=
  52. By: Grunert, Klaus G G.; Hesselberg, Julie
    Keywords: Marketing, Research Methods/Statistical Methods, Agribusiness
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312642&r=
  53. By: Howry, Sierra S.; Jungbluth, Angela; Ratliff, English L.
    Keywords: Productivity Analysis, Marketing, Agricultural Finance
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312668&r=
  54. By: Beghin, John; Gustafson, Christopher
    Abstract: We review the emerging international body of evidence on attitudes and willingness to pay (WTP) for novel foods produced with New Plant Engineering Techniques (NPETs). NPETs include genome/gene editing, cisgenesis, intragenesis, RNA interference and others. These novel foods are often beneficial for the environment and human health and more sustainable under increasingly prevalent climate extremes. These techniques can also improve animal welfare and disease resistance when applied to animals. Despite these promising attributes, evidence suggests that many, but not all consumers, discount these novel foods relative to conventional ones. Our systematic review sorts out findings to identify conditioning factors which can increase the acceptance of and WTP for these novel foods in a significant segment of consumers. International patterns of acceptance are identified. We also analyze how information and knowledge interact with consumer acceptance of these novel foods and technologies. Heterogeneity of consumers across cultures and borders, and in attitudes towards science and innovation emerges as key determinants of acceptance and WTP. Acceptance and WTP tend to increase when beneficial attributes—as opposed to producer-oriented cost-saving attributes—are generated by NPETs. NPETs improved foods are systematically less discounted than transgenic foods. Most of the valuation elicitations are based on hypothetical experiments and surveys and await validation through revealed preferences in actual purchases in food retailing environments.
    Keywords: Consumer/Household Economics
    Date: 2021–08–24
    URL: http://d.repec.org/n?u=RePEc:ags:nbaesp:313220&r=
  55. By: Ha, Sang Su; Sampson, Gabriel; Min, Doohong
    Keywords: Resource/Energy Economics and Policy, Environmental Economics and Policy, Agricultural and Food Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312867&r=
  56. By: Dalheimer, Bernhard; Brambach, Fabian; Yanita, Mirawati; Kreft, Holger; Bruemmer, Bernhard
    Keywords: Environmental Economics and Policy, Productivity Analysis, International Development
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312750&r=
  57. By: Hensen, Reid; Mooney, Daniel F.; Hill, Alexandra E.; Fernandez-Gimenez, Maria
    Keywords: Production Economics, Agricultural and Food Policy, Resource/Energy Economics and Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312794&r=
  58. By: Sandro Steinbach
    Abstract: This paper analyzes the impact of exchange rate risk on global food supply chains. Although the theoretical literature suggests ambivalence regarding the sign and magnitude of this effect, most empirical studies indicate a negative association between exchange rate volatility and international trade flows. I contribute to the ongoing debate by investigating the relationship at the product-level using a sectoral gravity model and relying on detailed retrospective trade and exchange rate data for a balanced panel of 159 countries for 2001 to 2017. I study the relationship for 781 agricultural and food products and estimate the trade effects of short-run and long-run exchange rate volatility. My findings indicate significant heterogeneity in the trade effects of exchange rate risk. While the mean trade effects are positive for short-run and long-run volatility, these effects vary substantially according to product and industry characteristics. I find a positive association between exchange rate volatility and the trade effects for upstreamness and a negative association for downstreamness of the traded products. I show that the significant and adverse trade effects in earlier studies result from model misspecification and measurement errors. This research enhances the understanding of the implications of exchange rate volatility which is a primary source of international risk exposure for global food supply chains.
    JEL: F14 Q17
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:29164&r=
  59. By: Bryan, Calvin; Manning, Dale; Goemans, Christopher; Sloggy, Matthew R.
    Keywords: Agricultural and Food Policy, Institutional and Behavioral Economics, Risk and Uncertainty
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312784&r=
  60. By: Martinez, Dillen; Robinson, Chadelle R.H.; Miller, Maryfrances
    Keywords: Agribusiness, Agricultural and Food Policy, Teaching/Communication/Extension/Profession
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312658&r=
  61. By: Choi, Eseul; DePaula, Guilherme M.; Kyveryga, Peter; Fey, Suzanne
    Keywords: Environmental Economics and Policy, Production Economics, Risk and Uncertainty
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312893&r=
  62. By: Bosch, Darrell J.; Zhang, Wei; Hu, Chenyang
    Keywords: Resource/Energy Economics and Policy, Environmental Economics and Policy, Agricultural and Food Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312697&r=
  63. By: McCann, Laura M.; Michler, Jeffrey D.; Estrada Carmona, Natalia; Raneri, Jessica; McCann, Laura E.
    Keywords: International Development, Food Consumption/Nutrition/Food Safety, Resource/Energy Economics and Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312894&r=
  64. By: Howry, Sierra S.; Ratliff, English L.; Jungbluth, Angela
    Keywords: Teaching/Communication/Extension/Profession, Production Economics, Agribusiness
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312667&r=
  65. By: Bahalou Horeh, Marziyeh; Elbakidze, Levan; Sant'Anna, Ana Cluadia
    Keywords: Food Consumption/Nutrition/Food Safety, Agricultural and Food Policy, Health Economics and Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312822&r=
  66. By: Rocha, Adauto B.; Fulginiti, Lilyan E.; Perrin, Richard K.; Walters, Cory G.
    Keywords: Production Economics, Agricultural Finance, Community/Rural/Urban Development
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312854&r=
  67. By: Kang, Shijia; Wimmer, Stefan; Sauer, Johannes
    Keywords: Productivity Analysis, Marketing, Production Economics
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312920&r=
  68. By: Tran, Lan T.; McCann, Laura M.; Skevas, Teo
    Keywords: Institutional and Behavioral Economics, Production Economics, Environmental Economics and Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312886&r=
  69. By: Zhang, Mengling; Chen, Zhaojiu; Wu, Feng
    Keywords: Consumer/Household Economics, Community/Rural/Urban Development, Resource/Energy Economics and Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312641&r=
  70. By: Sellars, Sarah C.; Schnitkey, Gary D.; Gentry, Laura F.; Paulson, Nick
    Keywords: Agricultural Finance, Agricultural and Food Policy, Agribusiness
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312780&r=
  71. By: Lineback, Caitlinn; Caputo, Vincenzina; McKendree, Melissa G. S.; Kilders, Valerie
    Keywords: Marketing, Agricultural and Food Policy, International Relations/Trade
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312713&r=
  72. By: Delgado, Michael; Ma, Meilin; Wang, Hong Holly
    Keywords: Risk and Uncertainty, Agricultural and Food Policy, Institutional and Behavioral Economics
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312793&r=
  73. By: Davis, Will; Gregory, Christian A.; Tchernis, Rusty
    Keywords: Research Methods/Statistical Methods, Consumer/Household Economics, Food Consumption/Nutrition/Food Safety
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312666&r=
  74. By: Michael T. Kiley
    Abstract: How will climate change affect risks to economic activity? Research on climate impacts has tended to focus on effects on the average level of economic growth. I examine whether climate change may make severe contractions in economic activity more likely using quantile regressions linking growth to temperature. The effects of temperature on downside risks to economic growth are large and robust across specifications. These results suggest the growth at risk from climate change is large—climate change may make economic contractions more likely and severe and thereby significantly impact economic and financial stability and welfare.
    Keywords: Climate change; Risk management; GDP at Risk
    JEL: E23 O13 Q54 Q56
    Date: 2021–08–09
    URL: http://d.repec.org/n?u=RePEc:fip:fedgfe:2021-54&r=
  75. By: Jaimovich, Dany; Toledo, Felipe
    Abstract: This paper analyzes the effects of the Chilean land reform (1962-1973) on the intensity of the current indigenous self-determination conflict (1990-2016). The Mapuche were actively involved in the land reform process, and at least 150,000 hectares were expropriated in their favor. Nevertheless, the counter-reform process, after the 1973 military coup, almost fully reverted these expropriations. This failed land reform potentially created local grievances that may explain some aspects of the current social and political conflict in the region. To test this hypothesis, a unique geocoded plot-level database for the Araucania Region has been assembled. The results from OLS estimates suggest that plots involved in the land reform are more likely to be invaded and attacked. The effect is larger for plots located around indigenous reservations and those in which there was direct Mapuche participation during the land reform. To deal with potential endogeneity problems, we implement an instrumental variable identification strategy based on historical rainfall in the region. The IV estimates mostly confirm the main results. We show that the development of intensive forestry plantations after the land reform is a potential channel for explaining our results.
    Keywords: Land reform, conflict, indigenous people, Chile.
    JEL: D74 N46 O13 Q15
    Date: 2021–03–16
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:109136&r=
  76. By: Devkota, Satis; Subedi, Dipak; Todd, Jessica E.; Adhikari, Shyam
    Keywords: Agricultural Finance, Agricultural and Food Policy, Agribusiness
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312709&r=
  77. By: NES Kjersti (European Commission - JRC); COLEN Liesbeth; CIAIAN Pavel (European Commission - JRC)
    Abstract: This report provides an overview of various market power indicators within the food industry in selected Member States (MS) in the EU. In addition, the report aims to examine whether the alternative market power indicators are qualitatively comparable proxies to measure market power in the food industry and to discuss the potential implications for the EU’s directive on unfair trading practices (UTPs). The report analyses the market power in-depth for the year 2016 and studies its dynamics over the period 2006-2017 in the selected MS. The report considers four alternative measures of market power: the concentration ratio (CR4), the Herfindahl-Hirschman Index (HHI), markups as well as turnover size, which is the market power measure used in the EU’s UTP directive. The report analyses are based on the firm-level accounting data available from the Orbis database. Due to limited data availability in some countries, the report considers 10 MS for calculation of the CR4, HHI and turnover indicator, and 7 MS for estimation of markups. The analyses are carried out for different (more aggregated) sectors of the food industry—i.e., retail, wholesale and manufacturing—, as well as for disaggregated subsectors within the wholesale and manufacturing sectors.
    Keywords: food chain, unfair trading practices (UTP), market power
    Date: 2021–07
    URL: http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc125087&r=
  78. By: Kim, Hyunjung; Herriges, Joseph A.; Lupi, Frank
    Keywords: Environmental Economics and Policy, Resource/Energy Economics and Policy, Research Methods/Statistical Methods
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312882&r=
  79. By: Heboyan, Vahé; Hovhannisyan, Vardges; Bakhtavoryan, Rafael; Kondaridze, Magdana
    Keywords: Health Economics and Policy, Agricultural and Food Policy, Research Methods/Statistical Methods
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312914&r=
  80. By: Van Deynze, Braeden; Fonner, Robert C.; Feist, Blake; Jardine, Sunny L.; Holland, Daniel S.
    Keywords: Environmental Economics and Policy, Resource/Energy Economics and Policy, Production Economics
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312843&r=
  81. By: Funke, Franziska; Mattauch, Linus; van den Bijgaart, Inge; Godfray, Charles; Hepburn, Cameron; Klenert, David; Springmann, Marco; Treich, Nicholas
    Abstract: Livestock is known to play a significant role in climate change and to negatively impact global nitrogen cycles and biodiversity. However, economically efficient policies for regulating meat production and consumption are under-researched. In the absence of first-best policy instruments for the livestock sector, second-best consumption taxes on meat can address multiple environmental externalities simultaneously, while improving diet-related public health. Here, we review the empirical basis for the 'social costs of meat' and study rationales for regulatory efforts to tax meat in high-income countries from the perspective of public, behavioural and welfare economics: (i) multiple environmental externalities, (ii) adverse effects on one's own health, (iii) animal welfare, (iv) learning curves for 'alternative protein technologies', and (v) distributional effects. We conclude that meat is significantly underpriced and provide preliminary estimates of the environmental social costs associated with meat consumption. We identify several directions for future research towards optimal meat taxation.
    Date: 2021–03
    URL: http://d.repec.org/n?u=RePEc:amz:wpaper:2021-08&r=
  82. By: Uddin, Azhar; Gallardo, Karina; Rickard, Bradley J.; Alston, Julian M.; Sambucci, Olena
    Keywords: Agribusiness, Marketing, Productivity Analysis
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312852&r=
  83. By: Grace Melo (Texas A&M University)
    Abstract: We introduce the command quaidsce, a modified version of the estimation command provided by Poi (2008) to estimate the Almost Ideal Demand System proposed by Deaton and Muellbauer (1980) and extended by Banks et al. (1997) to allow for nonlinear demographic effects (through a price deflator for total expenditure) and nonlinear Engel curves (through a quadratic term of total expenditure). The command of Poi (2008) to estimate the Quadratic Almost Ideal Demand System (QUAIDS) is extended to a two-step censoring demand system. Postestimation tools calculate expenditure and price elasticities.
    Date: 2021–08–07
    URL: http://d.repec.org/n?u=RePEc:boc:scon21:23&r=
  84. By: Soto-Caro, Ariel; Wu, Feng; Vallad, Gary; Guan, Zhengfei
    Keywords: Production Economics, Agribusiness, Risk and Uncertainty
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312639&r=
  85. By: Lynn Riggs (Motu Economic and Public Policy Research); Livvy Mitchell (Motu Economic and Public Policy Research)
    Abstract: Efforts to reduce emissions to counter climate change are expected to have both costs and benefits, and these effects are likely to be unevenly distributed across the population. We examined the potential distributional impacts on employment in New Zealand from using different mitigation options (“pathways”) designed to achieve net zero emissions of long-lived gases and to reduce biogenic methane emissions by 24-47% by 2050. For the analysis, we developed the Distributional Impacts Microsimulation for Employment (DIM-E). DIM-E uses results from a computable general equilibrium (CGE) model, C-PLAN, to estimate which industries, workers and jobs are expected to be most affected by different options to achieve these reductions. Overall, our results are similar to those from previous research in that the net employment effects are predicted to be relatively small, though some industries will be more affected than others. Moreover, the top net negative and top net positive industries ranked fairly consistently across the four time periods and across the different pathways that were analysed. On the net positive side, transport industries tended to dominate the industry rankings, and in later periods, some agriculture industries also tended to rank highly (e.g., Dairy Cattle Farming and Sheep/Beef Farming). On the net negative side, various manufacturing industries tended to dominate the top ranks, though oil and gas extraction was also consistently ranked. We also found that very few groups of workers were negatively affected (in terms of the number of worker-jobs) by any of the proposed pathways especially over the long term.
    Keywords: Environmental Economics, Climate Change Mitigation, Distributional Impacts of Employment
    JEL: J01 Q52 R11
    Date: 2021–07
    URL: http://d.repec.org/n?u=RePEc:mtu:wpaper:21_07&r=
  86. By: Gao, Penghui; Secor, William; Escalante, Cesar L.
    Keywords: Agricultural Finance, Agribusiness, Productivity Analysis
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312923&r=
  87. By: Yu, Chengzheng; Miao, Ruiqing; Khanna, Madhu
    Keywords: Environmental Economics and Policy, Research Methods/Statistical Methods, Food Safety, Nutrition, and Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312624&r=
  88. By: Abelló, Francisco; Ribera, Luis A.; DeLaune, Paul B.
    Keywords: Risk and Uncertainty, Production Economics, Productivity Analysis
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312788&r=
  89. By: Garber, Benjamin F.; Alwang, Jeffrey; Norton, George W.
    Keywords: Productivity Analysis, Teaching/Communication/Extension/Profession, Production Economics
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312730&r=
  90. By: Heshmatpour, Masoumeh; Peterson, Hikaru Hanawa
    Keywords: Marketing, Research Methods/Statistical Methods, Environmental Economics and Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312871&r=
  91. By: Yan, Minhao; Schmit, Todd M.; Gomez, Miguel I.; Baker, Michael James
    Keywords: Agricultural Finance, Agribusiness, Marketing
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312674&r=
  92. By: Page, Elina T.; Feng, Wenhui; Saravana, Divya; Cash, Sean B.
    Keywords: Marketing, Food Consumption/Nutrition/Food Safety, Health Economics and Policy
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312791&r=
  93. By: Kilders, Valerie; Caputo, Vincenzina; Lusk, Jayson L.
    Keywords: Research Methods/Statistical Methods, Research Methods/Statistical Methods, Institutional and Behavioral Economics
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312694&r=
  94. By: Won, Sunjae; Goodwin, Barry K.; Boys, Kathryn A.
    Keywords: Food Consumption/Nutrition/Food Safety, Risk and Uncertainty, Agribusiness
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312798&r=
  95. By: João Z. Carrilho; Ines A. Ferreira; Rui N. Ribeiro; Finn Tarp
    Abstract: This paper explores agricultural performance of Mozambique, its institutional weaknesses, and the underlying factors that underpin an unsatisfactory performance during many decades. We point to the role of systemic political instability and violence combined with challenges to state legitimacy. Regional divides and lack of market integration continue to influence in a critical and all-encompassing manner.
    Keywords: Agriculture, Environment, Institutions, Agricultural policy, Productivity
    Date: 2021
    URL: http://d.repec.org/n?u=RePEc:unu:wpaper:wp-2021-135&r=
  96. By: Lee, Sunyoung; Zhang, Yu Yvette; Nayga, Rodolfo M.
    Keywords: Institutional and Behavioral Economics, Research Methods/Statistical Methods, Food Consumption/Nutrition/Food Safety
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312733&r=
  97. By: Peterson-Wilhelm, Bailey; Durand-Morat, Alvaro; Nalley, Lawton L.; Norsworthy, Jason; Bagavathiannan, Muthukumar V.
    Keywords: Production Economics, Environmental Economics and Policy, Productivity Analysis
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312774&r=
  98. By: Caputo, Vincenzina; Kilders, Valerie; Lusk, Jayson L.
    Keywords: Research Methods/Statistical Methods, Institutional and Behavioral Economics, Marketing
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312695&r=
  99. By: Li, Ran; Xu, Yuetong; Chen, Jian; Qi, Danyi
    Keywords: Marketing, Research Methods/Statistical Methods, Food Consumption/Nutrition/Food Safety
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312878&r=
  100. By: PARISI Claudia (European Commission - JRC); RODRIGUEZ CEREZO Emilio (European Commission - JRC)
    Abstract: This report presents a review of market applications of new genomic techniques (NGTs). For the purposes of this study, NGTs are defined as ‘techniques that are able to alter the genetic material of an organism, developed after the publication of EU Directive 2001/18/EC’.The study covers NGT applications in agri-food, industrial and medicinal sectors that have resulted in applications that are already being marketed (commercial stage), are at a confirmed pre-market development stage (pre-commercial stage) or are at a research and development (R & D) stage but showing market potential (advanced and early R & D stage). The scope includes the use of NGTs in any kind of plant, mushroom, animal or microorganism or in human cells.Data on NGT applications were collected from multiple sources, including information available online, consultation of experts and an ad hoc survey of public and private technology developers. The NGT applications identified were classified, using the information available, as being at the following development stages.NGTs, especially those based on clustered regularly interspaced short palindromic repeats (CRISPR), are being actively and increasingly used in all the sectors analysed. Currently, few NGT applications are marketed worldwide: one plant product, one microorganism for release into the environment and several microorganisms used for contained production of commercial molecules. There are, however, about 30 identified applications (in plants, animals and microorganisms) at a pre-commercial stage in the pipeline that could reach the market in the short term (within 5 years). In addition, the medicinal sector is actively using NGTs to tackle several human diseases, and in many cases applications have already reached patients, in phase I and phase I/II clinical trials.
    Keywords: New Genomic Techniques, Gene editing, CRISPR, Commercialization, Pipeline
    Date: 2021–04
    URL: http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc123830&r=
  101. By: Amin, Modhurima D.; Badruddoza, Syed; Mantle, Steve
    Keywords: Productivity Analysis, Research Methods/Statistical Methods, Agribusiness
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312764&r=
  102. By: Rub, Abdur; Tack, Jesse B.; Barkley, Andrew P.
    Keywords: International Development, Environmental Economics and Policy, Production Economics
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312781&r=
  103. By: Paul Hindsley; Craig E. Landry; Kurt Schnier; John C. Whitehead; Mohammadreza Zarei
    Abstract: We estimate demand models with revealed preference (RP) site selection and stated preference (SP) discrete choice experiment marine recreational fishing data. We combine RP data from the Marine Recreational Information Program (MRIP) creel survey with SP survey data from 2003/04. RP and SP data combination is motivated by two factors. Catch rate information in the RP data are often thin, and use of SP scenarios for changes in catch can improve variation while minimizing multicollinearity. The SP data can suffer from hypothetical bias, which often manifests itself as bias in the cost coefficient. There are eight SP trip decisions and one RP trip decision for each of 1928 anglers who provided enough information to be analyzed. Joint RP-SP generalized multinomial logit models are estimated. We find that the SP travel cost coefficient is much lower than the RP travel cost coefficient in absolute value, suggesting hypothetical bias in the SP data. This difference is reflected in the willingness to pay estimates, where the SP estimates for improved catch are much higher than the RP estimates. Attribute non-attendance (ANA) arises when survey respondents ignore choice experiment attributes. We use inferred ANA methods to identify respondents who may be ignoring the SP cost variable. The generalized multinomial logit model accounting for ANA is statistically preferred. The SP cost coefficient accounting for ANA is much higher in absolute value than the SP coefficient from the model that does not account for ANA. The ANA model indicates much more consistency between the RP and SP data. The smaller difference in the travel cost coefficients is also reflected in the willingness to pay estimates. Key Words:
    JEL: Q51 Q22 Q26
    Date: 2021
    URL: http://d.repec.org/n?u=RePEc:apl:wpaper:21-10&r=

General information on the NEP project can be found at https://nep.repec.org. For comments please write to the director of NEP, Marco Novarese at <director@nep.repec.org>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.