The factor structure of the U.S. economy appears to change over time. Unlike previous studies which suggest this is due to permanent structural breaks in factor loadings, I argue instead that the volatility and persistence of factor processes undergo recurring changes related to the business cycle. To capture this, I develop a two-step Markov-switching static factor estimation procedure and apply it to a well-studied U.S. macroeconomic data set. I find strong support for Markov-switching in the factors processes, with switching variances being most dominant. Conditional on Markov-switching factor processes, tests for regime-dependent factor loadings show only moderate evidence of change. Overall, the results support regime-dependent factor processes as the main explanation for the diverging number of estimated factors in empirical applications and challenge the global linearity assumption implicit in large dimensional factor models of the U.S. economy.