The exact nature of the relationship between economic conditions and the performance of the stock market has been a subject of much controversy, and some proposed models to explain the equity premium puzzle make concrete claims about this connection which we might hope to test.
An important case is a class of models which involve "long-run risk". According to these models, what primarily drives stock market crashes is news about the long-run, and it just so happens that often short-run economic performance gives us the best clues about long-run risks, which leads to the observed pattern of correlation between stock market performance and the business cycle. However, according to long-run risk models this connection is only incidental, and a potential change in the properties of the GDP or consumption time series (such as a change in autocorrelation or conditional heteroskedasticity) can upend it entirely.
This question, along with its sibling question, is intended to test this class of models by eliciting the beliefs of Metaculites about the tightness of the connection between market crashes or tumultous market episodes and current macroeconomic events.
What will be the US unemployment rate after the next market crash happens?
This question resolves as the civilian unemployment rate reported by the BLS in units of percentages 6 months after the first month in which the S&P 500 closes below 70% of its previous all-time peak value in any given trading day that month. The peak value is the all-time peak, not the peak in that specific month; and there doesn't need to be a 30% decline within the space of one month, just a 30% overall fall from the previous all-time peak value.
To illustrate with an example, if the S&P 500 closes below 70% of its previous peak close value in March 2032, this question would resolve as the civilian unemployment rate reported by the BLS for September 2032.
If the S&P 500 never falls below 70% of its previous peak value until the resolution date of the question, the question resolves ambiguously.