Data Sources 2019-20

Data Sources 2019-20

The 2019-20 MTF Challenge focuses on how changes to the climate and water access could impact the agricultural industry. There are many great data sources for this challenge; however, only one data set is required for your projects.  The Primary Data Set below should be used in all projects. Additional Supporting Data Sets are provided for your optional use. While some teams may find the supporting data sets useful, others may not. It is up to you to determine how you want to add supporting data into your projects. Teams are not limited to these data sets either. You can expand your project by finding data and information of your own beyond these sources. Check out the information about each data set below and start testing your hands at finding and exploring the data that will make your project shine!

Primary Data Set

USDA Risk Management Agency

The Risk Management Agency of the USDA provides publicly accessible information about federal crop insurance policies including details on cause of loss, liability, subsidy, indemnity, and more. MTF Challenge Teams should use this information to model how future losses could be affected by changes in the climate or water access. Data from this source can be viewed in multiple ways each with their own unique benefits and challenges:

View Cause of Loss Files: this page provides annual files including the cause of loss. These files are very large because they include data on all crops from all counties in whole country. So you will have to view each year’s file on its own, and gather the data that is important to your project into your own spreadsheet. It is critical that teams know this data shows insurance policies that HAD A LOSS ONLY. It does not include all insurance policies.

Cause of Loss Viewer: this link provides access to the cause of loss data in a visual format. It also allows you to download the data in a spreadsheet, but does not let you take multiple cause of losses at once. So you will have to download each cause of loss separately, but it still may be a good way of accessing the data. This is the same data as is accessed in the Cause of loss Files, so it shows policies that HAD A LOSS ONLY.

Report Generator: this page is a great way to access the insurance claims and it is very important for projects because it includes ALL CROP INSURANCE POLICIES, not just ones with a loss. The only issue with accessing data this way is that it doesn’t include monthly information, only annual summaries. So teams may want to combine this information with more detailed information from the cause of loss files.

 

USDA Risk Management Agency

Supporting Data Sets

Climate Forecast Information
U.S. Global Change Program

This organization from the federal government provides great resources to help teams understand what changes are expected in the climate. It is key for teams to know in this challenge that they are NOT expected to model changes to the climate themselves. They are expected to take existing forecasts and develop their own model of how those changes could affect the sector of the agricultural industry they are studying. Checkout these links to the Global Change program to learn about specific ways climate scientists are expecting things to change, but don’t feel limited to just these resources:

Learn Climate Change Fundamentals: The Forth National Climate Assessment linked here has a ton of information in it, so you will have to do a little research to find what is important for your project, but the good thing about it is there are easy to navigate chapters where you can go directly to the information you would like to learn more about.

Learn more about Climate Change Forecast Scenarios: this is another link to the information in the Forth National Climate Assessment with easy to navigate chapters so you can see information about specific ways the climate is changing. For example, things that may be relevant for this MTF Challenge theme could be: Chapter 6 Temperature Change, Chapter 7 Precipitation Change, Chapter 8 Droughts, Floods, and Wildfire, and Chapter 9 Extreme Storms. However, teams should not feel limited to just this information. It is important to find what matters for your project!

 

U.S. Global Change Research Program

Historic Climate Data
NOAA Climate at a Glance

The National Oceanic and Atmospheric Administration (NOAA) provides a great way to access historic climate data including precipitation, temperature, drought indexes, and more. While it is not required to use historic climate data in your projects, some teams may find it beneficial to model relationships between historic trends and their crop insurance data from the primary data set for this challenge.

View Historic Climate Data: the data here can be viewed by state, county, or other divisions. Depending on your project you can look at particular historic trends and see if this could be useful in your project. The data can be exported to a spreadsheet to be analyzed in more detail.

 

NOAA Climate at a Glance

Actuaries Climate Index

Actuarial organizations in the US and Canada created this index to help monitor climate trends and educate people on the potential impacts of a changing climate. The index could be used in MTF Challenge projects to help identify relationships with past trends and the risks of changing climate factors. 

View Actuaries Climate Index: the data on this website is easily downloadable as an excel spreadsheet. There are also good descriptions of what the data is included in the “guided tour” of the site. This may be a good place to start if you are interested in exploring this site as a supporting data set for your project.

Actuaries Climate Index

Agricultural Production Information
USDA National Agricultural Statistics Service

The National Agricultural Statistics Service of the USDA provides information on all crop production values across the country. Because there is so much data here, sometimes you need to do a little searching to find what data is actually good versus what may not really work. While it is not critical to use this data, some teams may want to use it in conjunction with information from the USDA RMA to model how future changes could impact their crops.

Quick Stats data access portal: the data here can be useful in gathering information about the # of acres planted, yield, production, price received, and many other items related to the crops your teams are studying. You can use this portal to search through data about each crop and filter down to the county level often – though it may take some time exploring the data to find which values have data to that level.

 

U.S. Global Change Research Program

Water Access Information Sources
Multiple Sites

Water access is an important part of agriculture. There are many different aspects of the water system that may be interesting for teams to explore as part of their project. While none of these sources are required, you may find it interesting to explore some of these connections.

CUAHSI Hydrology Fundamentals: this site provides a lot of information about hydrology and the water system. There is also a data portal where you can explore various values from water monitoring stations across the country.

Drought.Gov Data and Tools: this site provides valuable information about droughts across the country. There are maps and other data products that may be valuable to some teams.

Water footprints: this site provides information and data about how much water it takes to produce each type of crop. 

CUAHSI website about water access and hydrology.

Contact

The Actuarial Foundation, a 501(c)(3) organization, is the philanthropic organization for the actuarial industry in the United States. The Foundation promotes lifelong math education and financial literacy through its learning resources and scholarships. The Modeling the Future Challenge is managed in partnership with The Institute of Competition Sciences. If you are interested in getting involved as a volunteer or have any questions about registering a team in the competition, contact us using the email or phone below.

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