Context This dataset was built using the Philadelphia Federal Reserve's State Coincident Indices and the Bry-Boschan Method for business cycle dating. In the tradition of Owyang, Piger, et al. business cycles are calculated on the state level which provides interesting analysis opportunities for looking at recession timing for different regions or sectors present in different states. The MSA level data utilizes the Economic Coincident Indices available on the St. Louis FRED website and uses a variant of the non-parametric algorithm described in *Metro Business Cycles* (Arias et al. 2016) to date MSA level recessions. Content This data is from 1982 through 2018 and includes whether the economy is in a recession or not, with forward looking and backward looking data available for observations as well. Additionally, various FRED St. Louis series were joined, like the University of Michigan Consumer Sentiment Index and the Global Price of Brent Crude. The 2012 value added as a percent for different NAICS groups is included as well for sectoral analysis, although better data over time for this would prove beneficial. The industries file attempts to correct this, but has fewer years available. Acknowledgements Special thanks to the researchers at the Federal Reserve Banks of Philadelphia and St. Louis for collecting and making available much of the data that went into this dataset. Inspiration I was inspired by researchers that have attempted to take business cycle dating to the state and MSA level. Local business cycle dating methodologies allow for a more robust understanding of what goes into a recession and how sectoral composition can affect a state or MSA's "resilience" to recessions. This could have applications for weighting business cycle risk for companies based on geographic dispersion of customers, as well as local policymakers if local forecasting could be done successfully.