When trying to identify or predict a recession in the US, economists typically reach for national data, which makes sense. The question they look to answer is how the country's economy is doing. That's led to a number of techniques, like the Sahm Rule, developed by former Fed economist Claudia Sahm in 2019: an empirical observation about unemployment, of when a recession has already started. Or a related type of calculation that Thomas Mertens, a vice president of economic research at the Federal Reserve Bank of San Francisco, recently shared, suggesting a way to identify that a recession was on its way.

Even more recently, researchers Kevin Kliesen and Cassandra Marks at the Federal Reserve Bank of St. Louis found another one, but this time not a view of national unemployment. Instead, the data is from the state level.

Another branch of the Fed — the Philadelphia regional bank — compiles state coincident indexes (SCIs). "The coincident indexes combine four state-level indicators to summarize current economic conditions in a single statistic," the bank writes. "The four state-level variables in each coincident index are nonfarm payroll employment, average hours worked in manufacturing by production workers, the unemployment rate, and wage and salary disbursements deflated by the consumer price index (U.S. city average). The trend for each state's index is set to the trend of its gross domestic product (GDP), so long-term growth in the state's index matches long-term growth in its GDP."