I understand that if there are correlated effects i.e. (one of) our explanatory variables are correlated with unobserved heterogeneity $\alpha_{i}$ then there will be omitted variable bias. Because this $\alpha_{i}$ affects the dependent variable and is correlated to our explanatory variable. Therefore, it's important to account for time-invariant unobserved heterogeneity in a fixed effects regression.
What I am struggling with is why should we also include time fixed effects (i.e. year fixed effects for example). There might be a national policy in a specific year that affects all 50 US states in a given year. This could cause a shock on the dependent variable. But must these national policies not be somehow correlated to at least one of the explanatory variables to cause inconsistent estimates? Can somebody maybe name an example for more intuition where this is the case?
Thank you in advance.