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Agricultural Economics: Agricultural Economics Research

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  • EIU.com Economic, demographic, consumption and industry data on 60 major countries worldwide and 11 regional aggregates. Included are detailed economic and industry forecasts for the next five years and longer-term economic projections.
  • UNdata The Statistics Division is committed to the advancement of the global statistical system. We compile and disseminate global statistical information, develop standards and norms for statistical activities, and support countries' efforts to strengthen their national statistical systems. We facilitate the coordination of international statistical activities and support the functioning of the UN Statistical Commission as the apex entity of the global statistical system. Statistical time series for countries from around the world covering a wide range of economic and socio-demographic topics. Descriptions of the international sources and definitions used in compiling the data are included.
  • Census Data: data.census.gov A product of the US Census, data.census.gov is the replacement for American FactFinder. It includes data from the American Community Survey, 2010 Decennial Census, Economic Census, County Business Patterns and more.
  • FRED - St. Louis Fed: Economic Data This site offers a wealth of economic data and information to promote economic education and enhance economic research. The widely used database FRED is updated regularly and allows 24/7 access to regional and national financial and economic data.
  • U.S. Bureau of Economic Analysis

Top Agricultural Economics Databases

  • AgEcon Search A database that indexes and electronically distributes full text reports of scholarly research in the field of agricultural and applied economics.
  • CAB Abstracts CAB Abstracts covers the significant research and development literature in the fields of agricultural engineering, applied economics and sociology, animal production, animal health, animal nutrition, aquaculture, biofuels, biosafety and bioterrorism, biotechnology, breeding, chemistry, climate change, crop science and grasslands, ecotourism, entomology, environmental science, food science and technology, forestry, genetics (molecular genetics, cytogenetics, population genetics, genomics), helminthology, horticultural science, human nutrition, invasive species, leisure and tourism (recreation), medicinal plants and pharmacology, microbiology, mycology, natural resources, land/water management, nematology, organic and sustainable agriculture, parasitology, plant pathology, plant protection, postharvest, protozoology, soil science, veterinary medicine, virology, waste management.
  • AGRICOLA Produced by the National Agricultural Library, AGRICOLA (AGRICultural OnLine Access) contains bibliographic records of materials acquired by the National Agricultural Library and cooperating institutions in agricultural and related sciences. Records come from the NAL Online Public Access Catalog and NAL's Article Citation Database. The catalog provides citations to books, serials, pamphlets, government documents, research reports, FAO and USDA publications, conference proceedings, and translations, patents, audiovisuals and technical reports. The article database provides citations to journal articles, book chapters, reports and reprints. Coverage includes: agricultural administration, laws and regulations, economics, education, training and extension, engineering and products; animal science; aquatic sciences; chemistry; energy as related to agriculture; entomology; feed science; food science and food products; forestry; general agriculture; geography, meteriology, climatology and history; home economics and human ecology; human nutrition; institutional food service; life sciences; natural resources management and environmental pollution; pesticides; plant diseases; plant science and production; rural sociology; soil science; veterinary medicine. Coverage from 1970 to the present.
  • EconLit with Full Text Abstracts, indexing, and full-text articles in all fields of economics, including capital markets, country studies, econometrics, economic forecasting, environmental economics, government regulations, labor economics, monetary theory, and urban economics.
  • USDA Economics, Statistics, and Market Information System The USDA Economics, Statistics, and Market Information System (ESMIS) is a collaborative project between Mann Library at Cornell University and several agencies of the U.S. Department of Agriculture. The system contains over 2500 reports and datasets.
  • Web of Knowledge Access the world's leading scholarly literature in the sciences, social sciences, arts, and humanities. Includes simultaneous access to Food & Science Technology Abstracts, BIOSIS, CAB Abstracts, and Zoological Records.
  • AgNIC Alliance The Agricultural Network Information Center (AgNIC) is a voluntary alliance of the National Agricultural Library (NAL), land-grant Universities and other agricultural organizations, in cooperation with citizen groups and government agencies.
  • OECD iLibrary OECD iLibrary is OECD's Online Library for Books, Papers and Statistics and the gateway to OECD's analysis and data. It replaces SourceOECD ... OECD iLibrary contains all the publications and datasets released by OECD (Organisation for Economic Cooperation and Development), International Energy Agency (IEA), Nuclear Energy Agency (NEA), OECD Development Centre, PISA (Programme for International Student Assessment), and International Transport Forum (ITF) since 1998.

Agricultural Economics Data Sources

  • World Bank Data The data catalog provides download access to over 2,000 indicators from World Bank sources.
  • CEIC Data Manager CEIC Data contains economic, industrial and financial time-series data. Our Global Database offers unprecedented coverage of 221 countries in Asia, Europe and Central Asia, Middle East, Africa and the Americas. EIC also offers 18 macro-economic concepts, and 1,400,000 time series. Data comes from analysts on the ground and the prime national and regional statistical agencies and major industrial data issuing organizations of each country covered. The CEIC Data Manager provides access to the entire CEIC database from within the Microsoft Excel spreadsheet application. Times-series can be directly retrieved from the database and imported into Excel for quick analysis.
  • USDA Economics, Statistics and Market Information System The USDA Economics, Statistics and Market Information System (ESMIS) is a collaborative project between Albert R. Mann Library at Cornell University and several agencies of the U.S. Department of Agriculture. It contains nearly 2500 reports and datasets
  • Census of Agriculture Conducted every five years by the U.S. Department of Agriculture's National Agricultural Statistics Service (NASS), the census of agriculture attempts to reach every agricultural operator in America through a mail survey. Data represent all agricultural operations, defined as any place which sold or normally would have sold more than $1,000 worth of agricultural products during the census year.
  • FAOStat A source of economic data for all types of agriculture around the world. Includes Trade, Production, Supply, Price, and other environmental data.
  • Quick Stats A source for economic data for U.S. Agricultural products and concepts. Data is available on the state, county, or local levels, and goes back to the 1850's.
  • Quandl A new source for free and open datasets. Includes financial, economic and social data.
  • Datastream Advance Provides comprehensive financial data on global securities, emerging markets and new instruments. Data can be structured by the user, compared and statistically manipulated using graphics, time series analysis and report generation programs. NOTE: You must use a dedicated Datastream terminal (in Mann library or the Johnson School Library) to access this resource.
  • Bloomberg The ultimate source of financial and economic data. NOTE: Bloomberg can only be used at designated terminals in Mann or the Johnson School's library.

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Agricultural Economics Research Review

research paper in agricultural economics

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Resource conservation technologies for sustainable development of agriculture: a case study in indian punjab.

research paper in agricultural economics

Trade-off between greenhouse gas emission tax and paddy production

Bearing fruit or falling flat the story of contract farming in india, marine fisheries insurance in india: retrospect and prospects in the context of climate change, sexed semen technology for cattle breeding: an interpretative review on its performance, and implications for india’s dairy economy, agricultural exports, agricultural imports and economic growth: evidence from china, essentially derived variety concept in plant variety rights protection system: underlying economic theories, and issues in implementation, agricultural development in recent decades and welfare challenges, temporal changes in crop diversification: a case study in a punjab village, information.

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  • World Bank Data Comprehensive set of data about development in countries around the globe, together with other datasets cited in the website's Data Catalog.
  • Environmental Studies Offers authoritative content on the development of emerging green technologies and discusses issues on the environment, sustainability and more. Topic, organization, and country portals form research centers around issues covering energy systems, health care, agriculture, climate change, population, and economic development.
  • CAB Abstracts Provides authoritative research information on agriculture, environment and related applied life sciences. Sources scanned selectively for records are: professional and trade journals (over 9,000), reports, bulletins, conference proceedings, symposia, workshops, scientific texts, technical and popular books, theses, annual reports and a few categories of patents and standards.

International Research

  • International Trade Center
  • U.S.D.A. Economics, Statistics and Market Systems The USDA Economics, Statistics and Market Information System (ESMIS) contains nearly 2,500 reports and datasets from several agencies of the U.S. Department of Agriculture (USDA). These materials cover U.S. and international agriculture and related topics. Most reports are text files that contain time-sensitive information. Most data sets are in spreadsheet format and include time-series data that are updated yearly.
  • World Development Indicators An analysis and visualization tool that contains collections of time series data on a variety of topics. Create queries, generate tables, charts, and maps; and easily save, embed, and share them.
  • CIA World Factbook The World Factbook provides information on the history, people, government, economy, geography, communications, transportation, military, and transnational issues for 267 world entities. Includes such environmentally related information as percentage of arable land, electricity consumption, drinking water source, and natural gas consumption.
  • PAIS International Bibliographic index with abstracts covering issues in the public debate through selective coverage of a wide variety of international sources including journal articles, books, government documents, statistical directories, grey literature, research reports, conference papers, web content, and more. Coverage 1972-present.
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research paper in agricultural economics

Declare: We are committed to disseminating the latest academic research results, adhering to publishing ethics and standards, and publishing high-quality articles. We accept and welcome oversight from scholars within the research community. If you find any problems or have concerns, please contact the editorial office at [email protected] . We will actively respond to your feedback and suggestions and continuously improve and enhance the quality and influence of the journal. We will reward scholars with positive suggestions. Thanks to all the scholars for their help and support.

Latest Articles

Machinery Adoption and Its Effect on Maize Productivity among Smallholder Farmers in Western Kenya: Evidence from the Chisel Harrow Tillage Practice

Edwin Mumah, Yangfen Chen, Yu Hong, Dickson Okello

Article ID: 983    DOI: https://doi.org/10.36956/rwae.v5i1.983

research paper in agricultural economics

Exploring Consumer Preferences for Locally Produced Wine in the Tanzanian Market: Evidence from Wine Consumers in Dodoma City

Nice Kimaro, Shauri Timothy, Yohana James Mgale

Article ID: 965    DOI: https://doi.org/10.36956/rwae.v5i1.965

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  • Resilience of Grain Storage Markets to Upheaval in Futures Markets 2842
  • Effects of Mixed Sowing of Chinese Milk Vetch (Astragalus sinicus L.) and Rape on Rice Yield and Soil Physical and Chemical Properties 2817
  • Border-rows Effect of Rape (Brassica napus L.) Intercropping with Milk Vetch (Astragalus sinicus L.) 2542

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Online ISSN: 2737-4785, Print ISSN: 2737-4777, Published by Nan Yang Academy of Sciences Pte. Ltd.

New Perspectives on Agricultural Economics, 2022-2026

The proposed initiative will involve four distinct research projects on different topics in agricultural economics. The topics will be selected each year on the basis of interests of ERS staff and some bearing on emerging or current policy issues. NBER research does not make policy recommendations, but provides background information and analysis that can inform policy decisions.

The proposed topic for the 2023 project is “Assessing the Distributional Impacts of Climate Change in the Agricultural Sector.” Climate change affects all aspects of the agricultural sector, from the production of food and fiber, through the choice of technology by producers, to the set of products that are available to consumers and the prices of those products. USDA is committed to understanding the consequences of climate change, as well as the impact of potential policy responses. Economic research on climate-related issues can advance this mission.

The 2023 project will focus on distributional impacts, because USDA is also committed to promoting equitable outcomes both in the impact of climate-related changes and in the design of policy responses. Doing so requires analysis and measurement of the effects of climate change in the agricultural sector on different groups in the population. These include producers and consumers, households in different income groups, racial and ethnic groups, those who live in different areas, and groups defined along other dimensions.

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Supported by the us department of agriculture grant #59-1000-2-0076, more from nber.

In addition to working papers , the NBER disseminates affiliates’ latest findings through a range of free periodicals — the NBER Reporter , the NBER Digest , the Bulletin on Retirement and Disability , the Bulletin on Health , and the Bulletin on Entrepreneurship  — as well as online conference reports , video lectures , and interviews .

15th Annual Feldstein Lecture, Mario Draghi, "The Next Flight of the Bumblebee: The Path to Common Fiscal Policy in the Eurozone cover slide

Agricultural Economics Research Association (India)

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Journal - AERR

AERA publishes the journal " Agricultural Economics Research Review (AERR)"

The Agricultural Economics Research Review (AERR) is the journal of the Agricultural Economics Research Association (India) and brings out two regular issues (June and December) and one conference issue every year.

AERR publishes original research related to issues on Agricultural Economics and Policy. The journal publishes original research articles, review papers, short communications, and book reviews on technology policy, impact assessment, agricultural institutions, agri-food policies, agri-financing, markets, trade, agri-infrastructure development, structural transformation, gender and environmental issues.

Agricultural Economics Research Review (AERR) is committed to ensuring the highest standards of publication ethics. All parties involved in the act of publishing (editors, authors, reviewers and the publisher) have to agree upon standards of ethical behavior.

We state the principles of Publication Ethics and Publication Malpractice Statement based on the Code of Conduct and Best Practice Guidelines for Journal Editors of the Committee on Publication Ethics – COPE ( Read the policy ). 

The journal is first reviewed by its Editoral Board and then sent out for peer review ( Read the Peer Review Policy ).

The journal AERR is being published since 1988 and the electronic version of the journal is available from 2006 on the website, for earlier versions you may contact us . 

ISSN: 0971-3441; Online ISSN 0974-0279

To submit the paper for publication to AERR journal read Guidelines to Author .

NAAS Journal Score AERR (2020): 5.90

AERR Google Scholar  : H Index- 48; i10 Index- 332 (as on September 2020)

Subscribe to the journal by becoming the member of AERA (India). The soft copies of the individual articles are also available on the website of AgEcon Search  and also at IndianJournals .

Click on view button to see the full content of the the Jounal and click on the link to view the full papers available at AgEcon search  

Author Guidelines

Past conferences.

UKnowledge

UKnowledge > Theses & Dissertations

Theses and Dissertations--Agricultural Economics

Theses/dissertations from 2023 2023.

Two Essays on Industrial Hemp Firms in the United States , Abraham Olakunle Ajibade

THREE ESSAYS ON THE U.S. BEEF SUPPLY CHAIN: PRODUCTION, MARKETING, AND PRICE DYNAMICS , Erdal Erol

CONSUMERS’ PREFERENCES AND WILLINGNESS TO PAY FOR VALUE-ADDED DAIRY PRODUCTS IN KENTUCKY - CONSIDERING PRICE, PROVENANCE, AND ENVIRONMENTAL PRODUCT ATTRIBUTES , Favour E. Esene

THREE ESSAYS ON HEALTH, FOOD, AND AGRICULTURAL ECONOMICS , Saber Feizy

Reclaiming Your Competitive Advantage , Mason T. Hamilton

Gambling on Growth: An Analysis of the Early Impact of Historical Horse Racing on Kentucky’s Thoroughbred Industry , Barrett W. Kerr

COMMUNITY SUPPORTED AGRICULTURE VALUES: A COMPARISON ACROSS GROUPS , Thomas B. Pierce

Theses/Dissertations from 2022 2022

DEMAND SYSTEM ANALYSIS OF BEER IN THE U.S. MARKET , Laxmi Devi Adhikari

THREE ESSAYS ON FOOD SAFETY AND PRIVATE FOOD SAFETY CERTIFICATIONS , Lijiao Hu

Spent Hemp as an Animal Feed and Vertical Price Transmission in US Hemp Value-Added Supply Chain , Solomon E. Odiase

Consumer Measures of Local Food System Performance and Shopping Behavior Across COVID , Azita Varziri

DEMAND ANALYSIS OF VIETNAMESE COFFEE IN THE U.S. , Leo Kyaw Zin

Theses/Dissertations from 2021 2021

KENTUCKY FOREST SECTOR: STRUCTURAL CHANGES AND ECONOMIC IMPACTS , Domena Attafuah Agyeman

TWO ESSAYS ON FOOD ENVIRONMENT, NUTRITION, AND FOOD INSECURITY , Suliman Abdulaziz Almojel

FARM LEVEL IMPACT OF ADOPTING MULTIPLE COMPONENT PRICING IN THE APPALACHIAN FMMO AND EVALUATING THE USMCA CANADIAN CREAM TRQ: A GSIM APPROACH , Luke Gregory Cummings

PRODUCTIVITY AND EFFICIENCY DIFFERENCE AMONG KENTUCKY GRAIN FARMS , Ahmed Yahya Hussein

Three Essays on Grocery Sales Taxes , Lingxiao Wang

THREE ESSAYS ON PRICE ANALYSIS AND INTERNATIONAL TRADE , Wei Zhang

THE GLOBAL ISSUE OF IMMIGRATION: A FOCUS ON ILLEGAL IMMIGRANTS FOR U.S. AGRICULTURE, REFUGEE IMMIGRANTS FOR GERMANY’S TRADE AND THE CLIMATE-INDUCED DIASPORA FROM LEAST DEVELOPED COUNTRIES , Yunzhe Zhu

Theses/Dissertations from 2020 2020

EXAMINING THE EFFECTS OF PUBLIC POLICIES AND ADDICTION ON PURCHASE OF TOBACCO PRODUCTS WITH CAUSAL INFERENCE AND MACHINE LEARNING METHODS , Xueting Deng

EVALUATING THE ECONOMIC COSTS AND LAND VALUE IMPLICATIONS OF IMPLEMENTING COVER CROPS IN KENTUCKY , Robert C. Ellis

OPTIMAL SUPPLEMENTAL COVERAGE OPTION CROP INSURANCE DECISION FOR KENTUCKY COMMODITY CROP PRODUCERS , Jerzy Z. Jaromczyk

THREE PERSPECTIVES ON INNOVATION IN EUROPEAN AGRICULTURE: FROM PUBLIC RESEARCH TO THE CIRCULAR ECONOMY , Michele Vollaro

CONSUMERS’ WILLINGNESS-TO-PAY FOR LOCAL SOURCING IN ALTERNATIVE RESTAURANT FORMATS , Mahla Zare Mehrjerdi

Theses/Dissertations from 2019 2019

THREE ESSAYS ON SAUDI ARABIA AGRICULTURAL MARKETS , Yosef Abdulrahman Alamri

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Announcing the NeurIPS 2023 Paper Awards 

Communications Chairs 2023 2023 Conference awards , neurips2023

By Amir Globerson, Kate Saenko, Moritz Hardt, Sergey Levine and Comms Chair, Sahra Ghalebikesabi 

We are honored to announce the award-winning papers for NeurIPS 2023! This year’s prestigious awards consist of the Test of Time Award plus two Outstanding Paper Awards in each of these three categories: 

  • Two Outstanding Main Track Papers 
  • Two Outstanding Main Track Runner-Ups 
  • Two Outstanding Datasets and Benchmark Track Papers  

This year’s organizers received a record number of paper submissions. Of the 13,300 submitted papers that were reviewed by 968 Area Chairs, 98 senior area chairs, and 396 Ethics reviewers 3,540  were accepted after 502 papers were flagged for ethics reviews . 

We thank the awards committee for the main track: Yoav Artzi, Chelsea Finn, Ludwig Schmidt, Ricardo Silva, Isabel Valera, and Mengdi Wang. For the Datasets and Benchmarks track, we thank Sergio Escalera, Isabelle Guyon, Neil Lawrence, Dina Machuve, Olga Russakovsky, Hugo Jair Escalante, Deepti Ghadiyaram, and Serena Yeung. Conflicts of interest were taken into account in the decision process.

Congratulations to all the authors! See Posters Sessions Tue-Thur in Great Hall & B1-B2 (level 1).

Outstanding Main Track Papers

Privacy Auditing with One (1) Training Run Authors: Thomas Steinke · Milad Nasr · Matthew Jagielski

Poster session 2: Tue 12 Dec 5:15 p.m. — 7:15 p.m. CST, #1523

Oral: Tue 12 Dec 3:40 p.m. — 4:40 p.m. CST, Room R06-R09 (level 2)

Abstract: We propose a scheme for auditing differentially private machine learning systems with a single training run. This exploits the parallelism of being able to add or remove multiple training examples independently. We analyze this using the connection between differential privacy and statistical generalization, which avoids the cost of group privacy. Our auditing scheme requires minimal assumptions about the algorithm and can be applied in the black-box or white-box setting. We demonstrate the effectiveness of our framework by applying it to DP-SGD, where we can achieve meaningful empirical privacy lower bounds by training only one model. In contrast, standard methods would require training hundreds of models.

Are Emergent Abilities of Large Language Models a Mirage? Authors: Rylan Schaeffer · Brando Miranda · Sanmi Koyejo

Poster session 6: Thu 14 Dec 5:00 p.m. — 7:00 p.m. CST, #1108

Oral: Thu 14 Dec 3:20 p.m. — 3:35 p.m. CST, Hall C2 (level 1) 

Abstract: Recent work claims that large language models display emergent abilities, abilities not present in smaller-scale models that are present in larger-scale models. What makes emergent abilities intriguing is two-fold: their sharpness, transitioning seemingly instantaneously from not present to present, and their unpredictability , appearing at seemingly unforeseeable model scales. Here, we present an alternative explanation for emergent abilities: that for a particular task and model family, when analyzing fixed model outputs, emergent abilities appear due to the researcher’s choice of metric rather than due to fundamental changes in model behavior with scale. Specifically, nonlinear or discontinuous metrics produce apparent emergent abilities, whereas linear or continuous metrics produce smooth, continuous, predictable changes in model performance. We present our alternative explanation in a simple mathematical model, then test it in three complementary ways: we (1) make, test and confirm three predictions on the effect of metric choice using the InstructGPT/GPT-3 family on tasks with claimed emergent abilities, (2) make, test and confirm two predictions about metric choices in a meta-analysis of emergent abilities on BIG-Bench; and (3) show how to choose metrics to produce never-before-seen seemingly emergent abilities in multiple vision tasks across diverse deep networks. Via all three analyses, we provide evidence that alleged emergent abilities evaporate with different metrics or with better statistics, and may not be a fundamental property of scaling AI models.

Outstanding Main Track Runner-Ups

Scaling Data-Constrained Language Models Authors : Niklas Muennighoff · Alexander Rush · Boaz Barak · Teven Le Scao · Nouamane Tazi · Aleksandra Piktus · Sampo Pyysalo · Thomas Wolf · Colin Raffel

Poster session 2: Tue 12 Dec 5:15 p.m. — 7:15 p.m. CST, #813

Oral: Tue 12 Dec 3:40 p.m. — 4:40 p.m. CST, Hall C2 (level 1)  

Abstract : The current trend of scaling language models involves increasing both parameter count and training dataset size. Extrapolating this trend suggests that training dataset size may soon be limited by the amount of text data available on the internet. Motivated by this limit, we investigate scaling language models in data-constrained regimes. Specifically, we run a large set of experiments varying the extent of data repetition and compute budget, ranging up to 900 billion training tokens and 9 billion parameter models. We find that with constrained data for a fixed compute budget, training with up to 4 epochs of repeated data yields negligible changes to loss compared to having unique data. However, with more repetition, the value of adding compute eventually decays to zero. We propose and empirically validate a scaling law for compute optimality that accounts for the decreasing value of repeated tokens and excess parameters. Finally, we experiment with approaches mitigating data scarcity, including augmenting the training dataset with code data or removing commonly used filters. Models and datasets from our 400 training runs are freely available at https://github.com/huggingface/datablations .

Direct Preference Optimization: Your Language Model is Secretly a Reward Model Authors: Rafael Rafailov · Archit Sharma · Eric Mitchell · Christopher D Manning · Stefano Ermon · Chelsea Finn

Poster session 6: Thu 14 Dec 5:00 p.m. — 7:00 p.m. CST, #625

Oral: Thu 14 Dec 3:50 p.m. — 4:05 p.m. CST, Ballroom A-C (level 2)  

Abstract: While large-scale unsupervised language models (LMs) learn broad world knowledge and some reasoning skills, achieving precise control of their behavior is difficult due to the completely unsupervised nature of their training. Existing methods for gaining such steerability collect human labels of the relative quality of model generations and fine-tune the unsupervised LM to align with these preferences, often with reinforcement learning from human feedback (RLHF). However, RLHF is a complex and often unstable procedure, first fitting a reward model that reflects the human preferences, and then fine-tuning the large unsupervised LM using reinforcement learning to maximize this estimated reward without drifting too far from the original model. In this paper, we leverage a mapping between reward functions and optimal policies to show that this constrained reward maximization problem can be optimized exactly with a single stage of policy training, essentially solving a classification problem on the human preference data. The resulting algorithm, which we call Direct Preference Optimization (DPO), is stable, performant, and computationally lightweight, eliminating the need for fitting a reward model, sampling from the LM during fine-tuning, or performing significant hyperparameter tuning. Our experiments show that DPO can fine-tune LMs to align with human preferences as well as or better than existing methods. Notably, fine-tuning with DPO exceeds RLHF’s ability to control sentiment of generations and improves response quality in summarization and single-turn dialogue while being substantially simpler to implement and train.

Outstanding Datasets and Benchmarks Papers

In the dataset category : 

ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation

Authors:  Sungduk Yu · Walter Hannah · Liran Peng · Jerry Lin · Mohamed Aziz Bhouri · Ritwik Gupta · Björn Lütjens · Justus C. Will · Gunnar Behrens · Julius Busecke · Nora Loose · Charles Stern · Tom Beucler · Bryce Harrop · Benjamin Hillman · Andrea Jenney · Savannah L. Ferretti · Nana Liu · Animashree Anandkumar · Noah Brenowitz · Veronika Eyring · Nicholas Geneva · Pierre Gentine · Stephan Mandt · Jaideep Pathak · Akshay Subramaniam · Carl Vondrick · Rose Yu · Laure Zanna · Tian Zheng · Ryan Abernathey · Fiaz Ahmed · David Bader · Pierre Baldi · Elizabeth Barnes · Christopher Bretherton · Peter Caldwell · Wayne Chuang · Yilun Han · YU HUANG · Fernando Iglesias-Suarez · Sanket Jantre · Karthik Kashinath · Marat Khairoutdinov · Thorsten Kurth · Nicholas Lutsko · Po-Lun Ma · Griffin Mooers · J. David Neelin · David Randall · Sara Shamekh · Mark Taylor · Nathan Urban · Janni Yuval · Guang Zhang · Mike Pritchard

Poster session 4: Wed 13 Dec 5:00 p.m. — 7:00 p.m. CST, #105 

Oral: Wed 13 Dec 3:45 p.m. — 4:00 p.m. CST, Ballroom A-C (level 2)

Abstract: Modern climate projections lack adequate spatial and temporal resolution due to computational constraints. A consequence is inaccurate and imprecise predictions of critical processes such as storms. Hybrid methods that combine physics with machine learning (ML) have introduced a new generation of higher fidelity climate simulators that can sidestep Moore’s Law by outsourcing compute-hungry, short, high-resolution simulations to ML emulators. However, this hybrid ML-physics simulation approach requires domain-specific treatment and has been inaccessible to ML experts because of lack of training data and relevant, easy-to-use workflows. We present ClimSim, the largest-ever dataset designed for hybrid ML-physics research. It comprises multi-scale climate simulations, developed by a consortium of climate scientists and ML researchers. It consists of 5.7 billion pairs of multivariate input and output vectors that isolate the influence of locally-nested, high-resolution, high-fidelity physics on a host climate simulator’s macro-scale physical state. The dataset is global in coverage, spans multiple years at high sampling frequency, and is designed such that resulting emulators are compatible with downstream coupling into operational climate simulators. We implement a range of deterministic and stochastic regression baselines to highlight the ML challenges and their scoring. The data (https://huggingface.co/datasets/LEAP/ClimSim_high-res) and code (https://leap-stc.github.io/ClimSim) are released openly to support the development of hybrid ML-physics and high-fidelity climate simulations for the benefit of science and society.   

In the benchmark category :

DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Authors: Boxin Wang · Weixin Chen · Hengzhi Pei · Chulin Xie · Mintong Kang · Chenhui Zhang · Chejian Xu · Zidi Xiong · Ritik Dutta · Rylan Schaeffer · Sang Truong · Simran Arora · Mantas Mazeika · Dan Hendrycks · Zinan Lin · Yu Cheng · Sanmi Koyejo · Dawn Song · Bo Li

Poster session 1: Tue 12 Dec 10:45 a.m. — 12:45 p.m. CST, #1618  

Oral: Tue 12 Dec 10:30 a.m. — 10:45 a.m. CST, Ballroom A-C (Level 2)

Abstract: Generative Pre-trained Transformer (GPT) models have exhibited exciting progress in capabilities, capturing the interest of practitioners and the public alike. Yet, while the literature on the trustworthiness of GPT models remains limited, practitioners have proposed employing capable GPT models for sensitive applications to healthcare and finance – where mistakes can be costly. To this end, this work proposes a comprehensive trustworthiness evaluation for large language models with a focus on GPT-4 and GPT-3.5, considering diverse perspectives – including toxicity, stereotype bias, adversarial robustness, out-of-distribution robustness, robustness on adversarial demonstrations, privacy, machine ethics, and fairness. Based on our evaluations, we discover previously unpublished vulnerabilities to trustworthiness threats. For instance, we find that GPT models can be easily misled to generate toxic and biased outputs and leak private information in both training data and conversation history. We also find that although GPT-4 is usually more trustworthy than GPT-3.5 on standard benchmarks, GPT-4 is more vulnerable given jailbreaking system or user prompts, potentially due to the reason that GPT-4 follows the (misleading) instructions more precisely. Our work illustrates a comprehensive trustworthiness evaluation of GPT models and sheds light on the trustworthiness gaps. Our benchmark is publicly available at https://decodingtrust.github.io/.

Test of Time

This year, following the usual practice, we chose a NeurIPS paper from 10 years ago to receive the Test of Time Award, and “ Distributed Representations of Words and Phrases and their Compositionality ” by Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, and Jeffrey Dean, won. 

Published at NeurIPS 2013 and cited over 40,000 times, the work introduced the seminal word embedding technique word2vec. Demonstrating the power of learning from large amounts of unstructured text, the work catalyzed progress that marked the beginning of a new era in natural language processing.

Greg Corrado and Jeffrey Dean will be giving a talk about this work and related research on Tuesday, 12 Dec at 3:05 – 3:25 pm CST in Hall F.  

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Reflections on the neurips 2023 ethics review process, neurips newsletter – november 2023.

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Agricultural and Resource Economics | Home

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Turning generational wisdom into a dream career in EWRE

Accelerated Master's Program student in Agricultural and Resource Economics recounts how she discovered her future career goals and how it has shaped her academic journey.

student_spotlight-Gracia.jpg

Roberta Gracia Student Spotlight 2024

First-generation college student; youngest of four. Arizona-born. Art. Books. Outdoors. 

This is how Roberta Gracia briefly describes herself and how she spends her free time, but when she isn't delving into her arts or going on weekend hikes with friends, she is head-first in her academics while maintaining a part-time job. 

Roberta Gracia is currently completing the Agricultural and Resource Economics Accelerated Master’s Program (AMP) while earning a B.S. in Environmental and Water Resource Economics (EWRE). The AMP pathway provides students the opportunity to complete traditional undergraduate and graduate degrees in 5 years instead of the common 4 years of undergrad and 2 years of a master’s program. After May 2024, Roberta will be a full-time graduate student and completing her final year of her master’s coursework. 

Discovering a Passion for Water Resources 

When deciding where to continue her education, Roberta's family had the largest influence on her. They provided undivided support and encouragement for her to attend the University of Arizona and to follow her passions. She explained, “My family has always supported me through everything and they have always believed that I could do anything I put my mind to.” 

Roberta initially planned to seek a chemical engineering major but she found EWRE to be a better fit. She was quickly accepted into AREC for the EWRE degree program and soon was eager to learn what this major had in store for her academic journey. She said, “At first, I wasn’t very happy that I didn’t go into chemical engineering, but after my first year at AREC, I realized that it was meant to be for me. Things always happen for a reason and I am forever grateful to be part of EWRE and AREC.” 

Roberta discovered what she wanted to do in her career at an early age– all because of a broken water pump. While spending time with her grandfather on an average day in Nogales, Sonora, he taught her how to fix and install a water pump. This led to her spending the whole summer working alongside her grandfather fixing water pumps, identifying areas that needed tending, and utilizing the water resources in the area to optimize the technique. She shared that her grandfather never studied or went to school for the work that he does, he simply taught himself by reading about the processes and learning as he goes. 

Roberta said, “My grandfather is the most important person in my life, and seeing him achieve all that he knows by only reading about it, inspired me to show him that if there is anyone who can follow his footsteps, it will be me. Having his support, his wise words, and his guidance have been the most important factor throughout my life.” 

Roberta’s family has been her moral compass since the very beginning. She shared her story of being raised by her grandparents and her single mother, and how they are still the most important people in her life to this day. With the continued support from her family, Roberta proudly shared that she’s made the Dean’s List every semester of her academic career, and she has exceptionally passed all of her courses while in AMP. 

Why choose an Accelerated Master’s Program? 

When asked what she found most rewarding, Roberta responded with the fact that she is saving herself a whole year by completing her degree with the AMP. A year that can now be filled with more strides towards her personal and career goals. 

Roberta said, “My main goal for my graduate career is to not give up. No matter how hard the process will get I want to be able to keep going and not give up midway. Like my grandfather once said, “Si alguien mas puede, porque tu no?” meaning ‘If someone else can, why can’t you? I live by this saying because it is true. Only you can stop yourself from getting to where you want to be.” 

She says the most challenging parts of completing the EWRE degree and the AMP are time management practices to accommodate her work and school schedules, securing financial aid, and learning coding. With such a busy academic schedule for both her undergraduate and graduate courses, maintaining a part-time job, and everyday life, it can be a workout juggling it all.  

Despite the challenges, Roberta has remained persistent and committed to her chosen path to completing two degrees. As the fourth individual to complete AREC’s AMP, Roberta has excelled in her academics and goes above and beyond in her support for the department, and promoting the program by advocating for new improvements to the program and visits classrooms to talk to prospective students. 

Advice from a successful AREC & AMP student for future Wildcats:

Take advantage of available faculty; to talk about assignments, projects, or just life. 

Take advantage of constructive feedback & mentorship. 

Consistently work on improving your time management skills; it’ll never be perfect. 

Welcome more math courses than are needed, and also complete coding classes.  

Make time for yourself to socialize; join clubs and organizations to meet new people.

Roberta explained that the AREC faculty is another reason that she strives with determination towards her goals and has continued strong throughout AMP. 

She explained, “I would like to thank [the faculty]. Professor Zuo , because of being in AREC 304, I decided to stay with this major and knew this was what I wanted as my career. Professor Aradhyula , for always being available and answering all my questions both in undergrad and graduate school. Professor Josephson , for supporting me and believing in me ever since my freshman year. Professor Rahman for being so joyful and making his classes ones that I wouldn't want to miss any day. Professor Thompson for helping me decide to pursue AMP. Lastly, Danielle Buhrow [Academic Advisor], has been through it all with me. I appreciate and can say she has a very special place in my heart because, without her support and guidance, I would not be this far into my career. Thank you all for always being there.” 

To learn more about degree programs in Agricultural and Resource Economics, click here .  

To learn more about the AREC Accelerated Master’s Programs, click here .  

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Herdwick shepherd James Rebanks working on his farm at Matterdale End in Cumbria.

Defra officials buried analysis showing dire financial prospects for hill farmers

Exclusive: FoI request reveals fears many would sell up if they saw assessment of post-Brexit farming payments scheme

Government officials have buried an analysis of the financial prospects for some of the most vulnerable farmers in the UK after realising it was almost entirely bad news, the Guardian can reveal.

The analysis was to have been part of an optimistic look at the financial situation for upland farmers, some of the poorest in the country, but minutes from meetings about the plans obtained through a freedom of information request have revealed concerns were raised about the negative findings.

Farming groups said it was “irresponsible” not to make the analysis public after FoI documents showed officials refused to publish it as ministers would not like it.

According to the minutes:

One official commented: “Could end up with no pathways to success at the end. We only want to publish if we have something which is positive to tell people.”

Government officials admitted that upland farmers were falling into financial crisis and might go out of business.

Officials feared that when upland farmers saw the data showing how much money they would make they would sell up.

Officials believed upland farmers were dismissive of the environment.

Many upland farmers only remain financially viable because of the EU-derived basic payment scheme (BPS), a system that will be completely phased out by 2027.

Post-Brexit farming payments schemes will be given to farmers who restore nature, but they are easier to access for those who own their land. Many upland farmers are commoners or tenants, and many of the most lucrative options under the BPS replacement, such as creating wildflower meadows, improving soil heath and reducing pesticide use, are geared towards lowland arable farms. This means upland farmers have feared losing BPS and being unable to make enough money under the new scheme to make ends meet.

To remedy this situation, ministers asked officials from the Department for Environment, Food and Rural Affairs in 2022 to draw up a “pathways to success scheme” for upland farmers in England to show different ways to make their farms profitable under the new scheme.

But at a series of meetings that year, officials raised concerns about the financial analysis and the scheme as a whole, and concluded it would be better not to publish them. Various reasons were given, with one official saying it was “a case of waiting for the political situation to settle”. Another said: “[it is] important we make sure ministers are happy with what we put out into the public environment – sensitivities around that.”

One official said in a meeting that they were waiting to find out from Defra “the number of people expected to go out of business”, and added that many would take the opportunity to reduce the size of their farm or sell up. However, they added: “Worry if you include land sales in options – dangerous option to promote. We should be focusing how to keep rural communities there.” Another official said: “Agree, that’s a capital not revenue income – personal choice. Not a pathway to success.”

Those at the meetings also believed that upland farmers, many of whom work in England’s national parks do not care about the environment: “A lot up until now be dismissive of the environmental side – challenge to get good engagement in that.”

Officials concluded: “We are not in a position to share economic analysis for the foreseeable, nor are we able to commit to a particular date where we can share the information.” The information still has not been shared with farmers or the public.

Julia Aglionby, a professor in practice at the University of Cumbria, chaired the Uplands Alliance, which represents hill farmers and upland land managers, while the pathways to success work with Defra was being undertaken. She said it was “irresponsible” to not publish the analysis.

“It was both disappointing and irresponsible of Defra not to publish modelling and impact assessments of their new ELM [environmental land management] policies for hill farmers. This lack of transparency understandably makes this vulnerable group of farmers worried,” Aglionby said.

“In the uplands there is a huge potential to deliver more for nature and climate adaptation while securing future livelihoods. Still over seven years since the Brexit referendum, Defra has not fully detailed their offer for the moors and commons. The promise of jam tomorrow is wearing thin.”

The minutes of the meetings revealed the dire situation for upland farmers. At one of the meetings, one official said: “Many upland farmers are heading rapidly into financial crisis and kneejerk-type survival reactions will do little to deliver anything of value in the longer term.”

They added: “The nature of the transition means that upland farming businesses are not seeing a future for themselves – upland farmers don’t understand the steps to run a thriving business.”

Tim Farron, the environment spokesperson for the Liberal Democrats, said the effects were already being seen by farmers in his Cumbria constituency, which contains many hill farms. “These shocking revelations confirm once and for all that this government know full well their diabolic rollout of new payments has been a disaster for upland farmers,” said Farron. “Family farms in my area have been decimated by this gross incompetence. We now risk losing a generation of family farmers, who not only put food on our table, but also act as custodians of the British countryside. This is a hammer blow for farming and the environment.”

Gavin Lane, the deputy president of the Country Land and Business Association, which represents owners of land, property and businesses in rural England and Wales , said: “Should upland farmers be forced to sell up, this will uproot long traditions and devastate local communities. Upland farmers want to help tackle the climate crisis, but need viable payment and a clear path forward.”

A Defra spokesperson said: “British upland farmers are critical to the success of our schemes. We reject the claims made about the pathways to success project and have taken what we learnt from the project to help develop policy to improve upland farming.

“We have just announced the biggest upgrade to our farming schemes since leaving the EU and have worked with upland farmers to increase payment rates, in many cases for those in existing agreements. We have also developed a new range of actions on moorland that farmers can be paid for, offering greater flexibility.

“There is something on offer for every type of farmer to support them to produce food sustainably while protecting nature and enhancing the environment and we continue to take on board feedback so that our schemes work in the best possible way.”

The National Farmers Union conference begins on Tuesday.

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