Agribusiness & Applied Economics Report最新文献

{"title":"Results of the North Dakota Land Valuation Model for the 2021 Agricultural Real Estate Assessment","authors":"Ronald H. Haugen","doi":"10.22004/AG.ECON.313163","DOIUrl":"https://doi.org/10.22004/AG.ECON.313163","url":null,"abstract":"","PeriodicalId":356449,"journal":{"name":"Agribusiness & Applied Economics Report","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124948861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimating Rail and Truck Carrier Operation Cost for Transporting North Dakota Grain Freight, 2015-2017","authors":"Elvis Ndembe, D. A. Bangsund, N. Hodur","doi":"10.22004/AG.ECON.305223","DOIUrl":"https://doi.org/10.22004/AG.ECON.305223","url":null,"abstract":"","PeriodicalId":356449,"journal":{"name":"Agribusiness & Applied Economics Report","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131078695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Economic Impacts of Cloud Seeding on Agricultural Crops in North Dakota","authors":"D. A. Bangsund, N. Hodur","doi":"10.22004/AG.ECON.291806","DOIUrl":"https://doi.org/10.22004/AG.ECON.291806","url":null,"abstract":"","PeriodicalId":356449,"journal":{"name":"Agribusiness & Applied Economics Report","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124151200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors Influencing the Gulf and Pacific Northwest (PNW) Soybean Export Basis: An Exploratory Statistical Analysis","authors":"D. W. Bullock, W. Wilson","doi":"10.22004/AG.ECON.288512","DOIUrl":"https://doi.org/10.22004/AG.ECON.288512","url":null,"abstract":"Growth in the export marketing of soybeans has drawn attention to the basis volatility in these market channels. Indeed, there has been greater growth in soybean exports compared to other commodities and this is due in part to the growth of exports to China. Concurrently, there has been substantial volatility in the basis at the primary U.S. export locations: the U.S. Gulf and the Pacific Northwest (PNW). This variability is caused by traditional variables affecting the basis but is also influenced by shipping costs, international competition, and inter-port relationships. Further, there seems to be distinct seasonal patterns that vary across marketing years. The purpose of this study is to examine the impact of supply/demand, export competition and logistical variables on both the average level and seasonality of U.S. export basis values for the 2004/05 through 2015/16 marketing years (September through August for U.S. soybeans). This study examines the impact of a wide range of supply, demand, transportation, and other market variables upon both the average level and seasonality (by marketing year) of the basis at the two major U.S. export locations, Gulf and Pacific Northwest (PNW). The explanatory dataset contains more variables (27) than observations (12 marketing years from 1994/95 through 2015/16); therefore, it presents challenges from both a sparsity and a multicollinearity perspective. To address these issues, a statistical regression technique, called partial least squares (PLS) is utilized. This technique has advantages over using principal components regression (PCR) since derivation of the components is directed towards maximizing the covariance between the dependent (Y) and explanatory (X) variable sets rather than just explaining the variance of X. Seasonality is investigated in this study utilizing agglomerative hierarchal clustering (AHC) to group similar marketing years by seasonal pattern called seasonal analogs. These seasonal analogs were then related to the explanatory variable set using a two-sample statistical test (Lebart, Morineau and Piron 2000) that compares the means of a subset and its parent set to explain the impact of the explanatory variables. The results indicate that the average market year level of the basis is primarily influenced by export competition from Brazil and export demand – particularly from China; however, domestic demand (soybean crush) also has some influence. Rail transportation costs to both the Gulf and PNW have an influence on the basis level; however, barge and ocean freight rates appear to not have a significant influence on the level of the basis. Application of AHC resulted in the identification of 5 and 4 distinct analogs (over the 12 marketing years in the dataset) for the Gulf and PNW respectively. Application of the two-sample mean difference tests to the analogs indicate that the seasonal pattern of the export basis is more heavily influenced by internal logistical conditions (late ","PeriodicalId":356449,"journal":{"name":"Agribusiness & Applied Economics Report","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127074109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Economic Impact of USWBSI’s Scab Initiative to Reduce FHB","authors":"W. Wilson, Gregory Mckee, W. Nganje, Bruce Dahl, D. A. Bangsund","doi":"10.22004/AG.ECON.264672","DOIUrl":"https://doi.org/10.22004/AG.ECON.264672","url":null,"abstract":"Fusarium Head Blight (FHB) has led to major economic losses for wheat and barley producers. Deoxynivalenol (DON) is a mycotoxin associated with FHB. Grain products and feed grain contaminated with DON (commonly known as vomitoxin) are subject to FDA advisory limits and as a result, end-users place restrictions on their use. This has led to steep price discounts, as well as higher risks for producers and grain merchandisers. Varietal research has led to the development of varieties that are resistant to moderately resistant to FHB. Also, studies indicate combinations of genetic resistance, fungicides, and some management practices (combine settings, tillage practices, etc.) can be used to decrease losses due to FHB. These approaches were developed beginning in 1997, with the introduction of the United States Wheat and Barley Scab Initiative (USWBSI). However, the detailed economic impact of the initiative (combined genetic resistance, fungicide uses, and some management practices) are yet to be estimated. The purpose of this study was to estimate the economic impact of reducing FHB on cereal producers, traders and handlers, and processors. To do so we developed a number of economic models, analyzed extensive data, and conducted surveys of wheat flour millers, barley maltsters, and grain handlers. Taken together these procedures allow us to make an assessment of 1) the cost to these industries of FHB; 2) the impact of mitigating strategies on yields and DON levels; 3) the marketing practices of the supply chain; 4) the impact of the Scab Initiative on reducing yield losses; 5) the return on investment of the Scab Initiative; and 6) the secondary impact of the initiative. In general, the results indicate some important findings regarding the Scab Initiative can be deduced from this study. One is that the DON problem has improved. However, it has not been eliminated and remains a temporally and spatially sporadic problem. Second, while there are a number of risk mitigation tools, and all of these prospectively have impacts of reducing the impact of DON, two are particularly important. One is fungicide use, which has increased from virtually nil in the 1990s’ to being applied to 70-80% of the cereals planted. This is substantial, and at a high cost, but, also is effective though not perfect. The second is the development and adoption of resistant varieties. The statistical analysis reported here documents the importance of these, though the effect varies across classes. 1 Funding source for this project was the USDA/ARS SCAB Initiative, and titled Economic Impact of USWBI’s Impact on Reducing FHB. 2 Authorship is shared viii This study estimates the return on investment to the research expenditures of the Scab Initiative which has spent $76 million over its life, including in-kind contributions. For both wheat and barley, the NPV of net savings from reduced production loss ranges from $5.3 - 5.4 billion over the period 1993-2014. For every $1 invested","PeriodicalId":356449,"journal":{"name":"Agribusiness & Applied Economics Report","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131532236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Economic Contribution of Horse Racing to North Dakota in 2016","authors":"Elvis Ndembe, N. Hodur, D. A. Bangsund, R. Coon","doi":"10.22004/ag.econ.264415","DOIUrl":"https://doi.org/10.22004/ag.econ.264415","url":null,"abstract":"","PeriodicalId":356449,"journal":{"name":"Agribusiness & Applied Economics Report","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126471526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wind Energy Industry's Contribution to the North Dakota Economy in 2016","authors":"Randal C. Coon, N. Hodur, D. A. Bangsund","doi":"10.22004/AG.ECON.263766","DOIUrl":"https://doi.org/10.22004/AG.ECON.263766","url":null,"abstract":"","PeriodicalId":356449,"journal":{"name":"Agribusiness & Applied Economics Report","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134369167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"2017 Outlook of the U.S. and World Wheat Industries, 2017-2026","authors":"Richard D. Taylor","doi":"10.22004/AG.ECON.262199","DOIUrl":"https://doi.org/10.22004/AG.ECON.262199","url":null,"abstract":"This report evaluates the U.S. and world wheat markets for the 2017-2026 time period using the Global Wheat Policy Simulation Model. This analysis is based on a series of assumptions about general economic conditions, agricultural policies, weather conditions, and technological change. Both the U.S. and world wheat economies are predicted to remain soft for the next ten years. World demand for both common and durum wheat are expected to remain stable however the large supplies of 2014, 2015 and 2016 will continue to pressure the market. The high price levels in 2010, 2011 and early 2012 will not be maintained because they are the result of a small wheat crop in 2010 and 2012 in the Former Soviet Union (FSU) and Argentina in 2012. The lower price levels for all commodities will also impact the wheat market. It is expected that wheat production in the FSU will return to normal in the future. World trade volumes of both durum and common wheat are expected to expand, but trade volume of common wheat may grow faster than that of durum wheat.","PeriodicalId":356449,"journal":{"name":"Agribusiness & Applied Economics Report","volume":"114 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121764913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Economic Impact of North Dakota's Ethanol Industry in Fiscal year 2015","authors":"Randal C. Coon, N. Hodur, D. A. Bangsund","doi":"10.22004/ag.econ.260094","DOIUrl":"https://doi.org/10.22004/ag.econ.260094","url":null,"abstract":"","PeriodicalId":356449,"journal":{"name":"Agribusiness & Applied Economics Report","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133217841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"2017 Outlook of the U.S. and World Sugar Markets, 2016-2026","authors":"Richard D. Taylor","doi":"10.22004/AG.ECON.256036","DOIUrl":"https://doi.org/10.22004/AG.ECON.256036","url":null,"abstract":"This report evaluates the U.S. and world sugar markets for 2016-2026 using the Global Sugar Policy Simulation Model. This analysis is based on assumptions that general economic conditions, agricultural policies, population growth, weather conditions, and technological changes remain at the long-run conditions. Both the U.S. and world sugar economies are predicted to remain constant over the next ten years. World sugar prices increased from 18.7 cents/lb in 2009 to 27.0 cents/lb in 2010 and 32.0 cents/lb in 2011 before falling to 16.8 cents/lb in 2014, and 13.4 cents/lb in 2015. Prices increased to 16.6 cents/lb in 2016. World sugar production increased 3.0% in 2016 while consumption increased by less than 1%. World sugar prices are expected to decrease to 13.7 cents/lb by 2026. The U.S. wholesale price of sugar is projected to increase from 30.6 cents/lb in 2016 to near 33.1 cents/lb by 2026. It is projected that Mexican exports to the United States will increase from 1.60 million metric tons in 2016 to 1.93 million metric tons in 2026. World trade volumes of sugar are expected to increase throughout the forecast period.","PeriodicalId":356449,"journal":{"name":"Agribusiness & Applied Economics Report","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115240932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}