As a Statistician for Decision Innovation Solutions, Jing Tang is responsible for analyzing agricultural data to help clients to make better strategic business decisions, and to assist co-workers improve model prediction and model estimation preference.Jing works with clients and coworkers on data cleaning, modeling estimation, optimization, prediction, machine learning, and risk analysis, as well as providing reliable analysis results. So far, she has been involved in several projects, such as using the prices of soybean oil, corn, and heating oil to predict yellow grease price, optimizing different factors’ conditions to increase yields coming from byproducts.Jing comes from Beijing, the capital of China. She earned a Bachelor degree in Food Science and Technology at the Beijing Business and Technology University (BTBU), and obtained a M.S. degree in Food Science at the University of Missouri (MU), Columbia. Currently, Jing is enrolled as a Statistics student at MU. Jing has the ability to combine both science and statistics knowledge together and to assist clients and colleagues in analyzing data, especially in the agricultural industry.
“Planting progress has been slowed by relatively frequent and relatively heavy rains throughout April and May.”, said DIS chief economist, David Miller, on May 24, 2019. (Blog is originally posted here) These abnormal weather events affected a number of rivers with flooding in the Midwest area, which led to delays in the corn planting process.
The US Energy Information Administration (EIA) published Monthly Biodiesel Production Report on June 28th. In this article, we will conduct a descriptive analysis of pure biodiesel (B100) production and its feedstocks usage back to 2014. EIA reported 152 million gallons pure biodiesel was produced in this April, which was 11 million gallons more compared with March 2019, and 9 million gallons more compared with April 2018.
Within the past twenty years, the flow of information has exponentially increased, largely due to advancements in technology and adoption of social media. The speed at which issues are first manifested to when they are noticed on a large scale has increased.
From our previous article, we compared the attitudes from the different perspectives of American and Chinese regard to the trade war (trade talks) since March of 2018. After the last round negotiation on February 15th, 2019, President Trump has delayed tariffs scheduled for March 1st on Chinese goods because they are “moving along nicely with Trade discussions”, said in his tweet.
The trade war (trade talks) between the US and China started in March of 2018. Intensity of the trade talks increased until the G-20 summit in Argentina on December 1st, 2018. After the two presidents met, they announced a moratorium in regard to trade issues like tariffs on certain products, intellectual property, market access, etc. and set a three-month negotiation period.
Our last article has emphasized that a good understanding of corn and soybean yields are important for the State of Iowa. So, we conducted a series of studies to analyze how to utilize crop condition ratings for forecasting Iowa corn and soybean yield. From the last article we know using the Final Crop Good and Excellent Condition Ratings to forecast Corn and Soybean Yield for the State of Iowa is a good approach.
In this series of articles, we studied the relationship between the crop progress Good and Excellent condition ratings and the corn and soybean yields for the State of Iowa from 1986 to 2018. The final condition rating is a good predictor to forecast the Trend Adjusted (TA) Yield for both corn and soybeans; to have more details check the first article of the series.
US corn and soybean production in 2018 is estimated to be 14.6 billion bushels and 4.6 billion bushels, respectively. Iowa is ranked first in the United States for corn production and second in soybean production according to the USDA state ranking report published in May 2018.
In Iowa, the harvesting season for both corn and soybean is underway. “U.S. farmers are expecting higher production of soybeans, while expecting a slightly decreasing corn production”, saying by the Newsletter from USDA published on Aug 10th, 2018.
Nowadays, more and more people pay attention to data and information and how to use them in a proper way. Analyzing data includes not only collecting raw data but also how to convert the numbers to inform a company's strategy and decision making. A small improvement in data analysis can lead to a big financial return for companies.
For the first dataset, gasoline's price is higher than ethanol price, the correlation between daily ethanol price and gasoline price
The Chinese government indicated that the expected fuel ethanol production will be 4 million Metric tons (1.339 billion gallons) per year during the 13th Five-Year Plan. In 2017, ethanol production stands for 2.6 million tons (0.871 billion gallons) per year, increased 0.5 million tons (0.167 billion gallons) per year, from 2.1 million tons (0.703 billion gallons) in 2016.
We have done an analysis to understand the relationship among monthly average ethanol prices versus ethanol ending stocks, corn prices, and gasoline prices. The major finding was that all of three predictors, i.e., ethanol ending stocks, corn prices, and gasoline prices, have statistically significant influences on monthly average ethanol prices.
The Chinese government recently indicated that the expected ethanol production will be 4 million tons (1.2314 billion gallons) per year for the next five years. Current ethanol production in China stands at 2.1 million tons (0.646 billion gallons) per year.
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