Applied Economic Perspectives and Policy最新文献_第5页

Economics of herbicide-free crop production 无除草剂作物生产的经济效益

IF 3.3 2区经济学

Applied Economic Perspectives and Policy Pub Date : 2024-07-07 DOI: 10.1002/aepp.13461

Eileen Ziehmann, Niklas Möhring, Robert Finger

{"title":"Economics of herbicide-free crop production","authors":"Eileen Ziehmann, Niklas Möhring, Robert Finger","doi":"10.1002/aepp.13461","DOIUrl":"10.1002/aepp.13461","url":null,"abstract":"Ambitious pesticide policies aiming to reduce pesticide applications and risks have been introduced across Europe. Herbicides represent a major part of pesticide use, but the uptake of mechanical or agronomic alternatives remains low. We here explore underlying reasons and provide policy insights for supporting a transformation to herbicide-free production, accounting for both economic and agronomic drivers. We develop detailed extensions to an existing bio-economic modeling approach and use stochastic dominance analysis to assess the performance of non-chemical alternatives to herbicides under different production and market conditions exante. We apply our approach to Swiss wheat production and find that herbicide-free production is not viable without financial support, and thus requires additional per-hectare agri-environmental payments and price markups to be economically viable. We find that currently available support payments in Switzerland are sufficient in achieving economic viability of herbicide-free production. Moreover, we confirm the relevance of risk and risk preferences and identify a risk-reducing character of herbicide-free production systems with support payments. Our analysis provides insights on potential drivers, trade-offs, decision-making factors, and policies for a transition to non-chemical weed control.","PeriodicalId":8004,"journal":{"name":"Applied Economic Perspectives and Policy","volume":"46 4","pages":"1692-1716"},"PeriodicalIF":3.3,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aepp.13461","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141570525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Universal free school meals: Examining factors influencing adoption of the Community Eligibility Provision 普及免费校餐：研究影响采用社区资格规定的因素

IF 3.3 2区经济学

Applied Economic Perspectives and Policy Pub Date : 2024-07-03 DOI: 10.1002/aepp.13460

Pratyoosh Kashyap, Becca B. R. Jablonski

引用次数: 0

An evaluation of Congressional Budget Office's baseline projections of USDA mandatory farm and nutrition programs 评估国会预算办公室对美国农业部强制性农业和营养计划的基线预测

IF 3.3 2区经济学

Applied Economic Perspectives and Policy Pub Date : 2024-06-25 DOI: 10.1002/aepp.13457

Hari P. Regmi, Todd H. Kuethe

{"title":"An evaluation of Congressional Budget Office's baseline projections of USDA mandatory farm and nutrition programs","authors":"Hari P. Regmi, Todd H. Kuethe","doi":"10.1002/aepp.13457","DOIUrl":"10.1002/aepp.13457","url":null,"abstract":"The Congressional Budget Office (CBO) projections of USDA's mandatory farm and nutrition program outlays are important in shaping US agricultural policy. Using CBO projections and observed outcomes from 1985 through 2020, we examine the degree to which projections of farm, supplemental nutrition assistance program (SNAP), and child nutrition program outlays are unbiased, efficient, and informative. We find that projections for farm and child nutrition program outlays are unbiased, SNAP outlays are unbiased at short-term but are downward biased beyond a 3-year horizon. All three series of projections are inefficient. SNAP and child nutrition program outlay projections are informative up to a 5-year horizon, but the farm program outlay projections are informative for only a 1-year horizon. Disaggregated farm program data since 2008 suggests that the uninformativeness principally stems from conservation and commodity program projections. The findings may be valuable to CBO, as they continue to improve projections, and to projection users, in adjusting their expectations.","PeriodicalId":8004,"journal":{"name":"Applied Economic Perspectives and Policy","volume":"46 3","pages":"1214-1240"},"PeriodicalIF":3.3,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aepp.13457","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Farm Workforce Modernization Act and warnings from previous immigration reforms 农业劳动力现代化法》和以往移民改革的警示

IF 3.3 2区经济学

Applied Economic Perspectives and Policy Pub Date : 2024-06-19 DOI: 10.1002/aepp.13458

Diane Charlton

引用次数: 0

Correction to “Agricultural exports and retaliatory trade actions: An empirical assessment of the 2018/2019 trade conflict” 更正 "农产品出口和报复性贸易行动：2018/2019年贸易冲突的实证评估"

IF 3.3 2区经济学

Applied Economic Perspectives and Policy Pub Date : 2024-06-19 DOI: 10.1002/aepp.13459

引用次数: 0

Public agricultural research, political economy, and climate change: A literature review 公共农业研究、政治经济学和气候变化：文献综述

IF 3.3 2区经济学

Applied Economic Perspectives and Policy Pub Date : 2024-06-14 DOI: 10.1002/aepp.13455

Ruiqing Miao, Recep Ulucak, David Zilberman

引用次数: 0

Measuring the economic contribution of Agricultural and Applied Economics departments in the United States 衡量美国农业与应用经济学系的经济贡献

IF 3.3 2区经济学

Applied Economic Perspectives and Policy Pub Date : 2024-06-05 DOI: 10.1002/aepp.13454

Michael K. Adjemian, Raghav Goyal, Ron Mittelhammer, Dawn Thilmany

{"title":"Measuring the economic contribution of Agricultural and Applied Economics departments in the United States","authors":"Michael K. Adjemian, Raghav Goyal, Ron Mittelhammer, Dawn Thilmany","doi":"10.1002/aepp.13454","DOIUrl":"10.1002/aepp.13454","url":null,"abstract":"Agricultural and applied economists make substantial positive contributions to the domestic economy. Defining a measure of the true total value of their contributions is likely impossible, because so much about their efforts is difficult to comprehensively observe and quantitatively document. In this paper, we adopt a conservative approach to generating an estimate of the contributions ag and applied economists make to U.S. economic output and the associated welfare of society through their teaching, research, and outreach efforts. To conduct the analysis, we implemented a nationwide survey of Agricultural and Applied Economics (AAE) departments and developed a framework to calculate the value of their contributions to national income, or Gross Domestic Product (GDP). We estimate that AAE departments increase overall U.S. GDP by $2.6 billion, annually. Through its efforts to improve the human capital of its graduates, AAE teaching raises the (expected) national income by $2.2–$2.3 billion, while we value direct research and outreach contributions at $207 million and $146 million, respectively. Because we do not observe the opportunity cost of the resources used to generate those contributions, we do not claim to estimate a true net economic impact but rather attempt to quantify the gross economic contributions of the professional services AAE departments currently offer the economy. The values we provide—especially the research and extension estimates which are exceedingly difficult to measure—likely underestimate the true benefits AAE offers to the nation.","PeriodicalId":8004,"journal":{"name":"Applied Economic Perspectives and Policy","volume":"46 3","pages":"921-933"},"PeriodicalIF":3.3,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aepp.13454","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141381921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Have agricultural and applied economists lost sight of the land-grant mission? A textual analysis of Presidential Addresses and Invited Papers from 1919–2022 农业和应用经济学家是否忘记了赠地学院的使命？对 1919-2022 年总统演讲和特邀论文的文本分析

IF 3.3 2区经济学

Applied Economic Perspectives and Policy Pub Date : 2024-06-03 DOI: 10.1002/aepp.13456

Norbert L. W. Wilson, Natalie Hochhaus

引用次数: 0

Leveraging unsupervised machine learning to examine women's vulnerability to climate change 利用无监督机器学习研究妇女面对气候变化的脆弱性

IF 3.3 2区经济学

Applied Economic Perspectives and Policy Pub Date : 2024-06-01 DOI: 10.1002/aepp.13444

German Caruso, Valerie Mueller, Alexis Villacis

引用次数: 0

Using machine-learning methods in meta-analyses: An empirical application on consumer acceptance of meat alternatives 在荟萃分析中使用机器学习方法：消费者对肉类替代品接受度的经验应用

IF 3.3 2区经济学

Applied Economic Perspectives and Policy Pub Date : 2024-05-27 DOI: 10.1002/aepp.13446

Jiayu Sun, Vincenzina Caputo, Hannah Taylor

{"title":"Using machine-learning methods in meta-analyses: An empirical application on consumer acceptance of meat alternatives","authors":"Jiayu Sun, Vincenzina Caputo, Hannah Taylor","doi":"10.1002/aepp.13446","DOIUrl":"10.1002/aepp.13446","url":null,"abstract":"Meta-analyses are widely used in various academic fields, including applied economics. However, the high labor intensity involved in paper searching and small sample sizes remain two dominant limiting factors. We conducted a meta-analysis of studies on consumer preferences for plant-based and lab-grown meat alternatives using machine-learning techniques at both the data collection and the data analysis phases. We demonstrated that machine learning reduces the workload in the manual title-abstract screen phase by 69% accounting for 24% of total workload in data collection. We also found that machine learning improves out-of-sample of sample prediction accuracy by 48–78 percentage points when compared to econometric model. Notably, we showed that integrating machine learning can also improve the predictive performance of econometric methods, thereby improving their out-of-sample predictions. Our empirical findings further revealed that demand for meat alternatives is higher among younger consumers, especially when the products displayed benefit information.","PeriodicalId":8004,"journal":{"name":"Applied Economic Perspectives and Policy","volume":"46 4","pages":"1506-1532"},"PeriodicalIF":3.3,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aepp.13446","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141196744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0