Database: Financial Education & Outcomes across States

An open-access database offers historical information on states’ spending on financial education and predicted outcomes.

by Joseph de la Torre DwyerShaun FieldBennett Attaway
May 3, 2021

From 2019 to 2020, Knology built an extensive database as part of our research into financial education spending at the state level, as well as financial health outcomes for individuals living in those states. To build the database, we expanded existing datasets and also gathered data that had not yet been centralized. The database features information on states’ mandates or legislation for financial education for middle and high school students, which we collected from previous studies, legal records, and web searches. To capture non-profit organizations’ investments in financial education, we received invaluable data and support from the Council for Economic Education. For information about financial health outcomes, we used data from the United States Federal Reserve’s annual Survey of Household Economics and Decisionmaking. For a full description of our methods for constructing the database, see our project report.

Database Components

To support researchers and policy makers, we have made this database free to use in two formats: a CSV file and an R Package. The database contains eleven complementary datasets. Here is an overview of each dataset:

State Year Financial Education National Center for Charitable Statistics (NCCSAY) - This dataset, NCCSAY, (where “AY” stands for All Years) provides historical total expenses for organizations in Urban Institute’s National Center for Charitable Statistics database of private charities and private foundations that provide direct services in financial education. With this information, users can estimate total expenses by financial education nonprofits.

Other Financial Education Activities - This dataset provides a snapshot of financial education activities we found in 2019 when looking at lists of resources curated by state boards of education. Specifically, this dataset features state-funded programs, even if the providers were non-profits instead of public schools. It offers users a rough sketch of the financial education landscape that can be factored into calculating states’ spending on K-12 education programs.

Public School Spending - This dataset contains the mean financial education course time and spending per student for all 50 states. These variables are contained in the State Year Financial Education Requirements dataset (see below). However, Public School Spending does not contain columns documenting required courses, amount of course content related to financial education, etc. Rather, this dataset provides the calculation of means for users’ convenience.

Pooled Survey of Household Economics and Decisionmaking, 2013 – 2021 (SHEDAY) - This dataset, SHEDAY, (where “AY” stands for All Years) provides a user with pooled responses to annual SHED survey data from 2013-2021. Overall, the dataset provides almost 60,000 records. This dataset also includes four scales that we constructed in order to test our hypotheses. This enables users to build statistical models using pooled SHED data or even use our scales.

State Public Schools Data 2017 - This dataset provides key information that we used to generate the inputs for our analysis of financial education impact on outcomes in the U.S. Federal Reserve’s Survey of Household Economics and Decisionmaking (SHED). This dataset enables users to add control variables to financial education models or harmonize spending estimates and financial education course duration across states.

State Year Economic and Demographic Data - This dataset provides control variables that we used in our analysis. This includes information by state and year, such as gross state product, population, and partisan control of the state legislature and governorship. This enables researchers to make statements such as, “our findings account for the different economic conditions in Texas vs. Illinois.”

State Year Financial Education Academic Standards - This dataset provides the historical academic content standards, by state, for social studies, economics, and financial education. It enables users to estimate exposure to financial education through the public school system.

State Year Financial Education IRS 990 Forms - This dataset provides historical Council for Economic Education program service expenses, by state. With this information, users can estimate nonprofit direct spending on financial education. This type of spending includes investments in teacher training initiatives or student programs, but does not cover educators’ salaries.

State Year Financial Education Requirements - This dataset provides all of the historical state graduation requirements we found to establish which subjects and courses a high school graduate would have been exposed to. This dataset enables users to track the changes in requirements from the early 1990s to 2020, depending on the state.

Urban and Schmeiser 2015 - This dataset provides a timeline of historical economics and financial education mandates by state. It helps users determine when mandates went into effect in each state in order to support modeling impacts and testing hypotheses.

Urban and Schmeiser 2020 - This dataset provides a user with an updated and further cleaned timeline of historical financial education mandates by state (relative to Urban and Schmeiser 2015). This dataset further equips users with information about when mandates went into effect in each state for modeling impacts and testing hypotheses.

The R Package

With so many datasets and a few functions to manipulate them, we needed a way to hold all of the pieces together. We created an R Package, KnologyFinEdStateSpending, that facilitates other researchers’ use of the data to fit their own research needs. R is an open-source software used for statistical computation and graphics development (read more about R software). In R, “packages are the fundamental units of reproducible R code. They include reusable R functions, the documentation that describes how to use them, and sample data,” all in a structure and with a set of conventions that aid researcher productivity (read more about R packages).

Let’s Put It to Work

The database is an opportunity for researchers, advocates, and other stakeholders to draw connections between different types of financial education spending and future outcomes for individuals. There are two ways to access the database:

R Package
Use this button to access the database’s R Package, which includes data, codebooks, citations, and scripts.

CSV Files
Use this button to access the database with comma separated value (CSV) files. This file includes a separate CSV file for each of the datasets.

About the Project

From 2019 to 2020, Knology led A New History of Investment in Financial Education across the United States, a research initiative funded by the National Endowment for Financial Education® (NEFE) and supported by a range of experts. Knology built a robust database of historical spending on financial education across all 50 states, as well as outcomes of that spending. The team then used the database to study how investments in financial education through public schools and non-profits contributed to indicators of financial health for U.S. residents, such as retirement savings and financial fragility. If you have questions about this project, contact Shaun Field ( The researchers who developed this database are grateful to our colleagues who also contributed to it: Nezam Aradalan, Rupu Gupta, Nicole LaMarca, Kathryn Nock, and Rebecca Joy Norlander.

The National Endowment for Financial Education is the independent, centralizing voice providing leadership, research, and collaboration to advance financial well-being. Find out more about NEFE at

Photo credit: David Pupaza on Unsplash.

I really like these datasets, they are vey useful. I wish these introductions to each dataset were a little bit more specific though. For example. Regarding the dataset ""Public School Spending"" I'm not entirely sure what metric the mean total time is considering. It wouldn't make sense for it to be hours since a total of .02 hours doesn't make sense. Same thing with the other variable, spending course credits per student, what does it mean? How can a school spend over 40 credits on a student if they only need about 26 to graduate? If a credit is a class, why would students take the class more than once? I wish the introductions were more specific. Is there anyone I can email to ask about this? Let me know!
By Marton Mezei
On Wednesday, September 20, 2023
Join the Conversation
What did you think of this? How did you use it? Is there something else we should be thinking of?
Support research that has a real world impact.