What is the difference between fixed effects and clustering?
Cluster-adjusted standard error take into account standard error but leave your point estimates unchanged (standard error will usually go up)! Fixed-effects estimation takes into account unobserved time-invariant heterogeneity (as you mentioned).
What are the cluster responsibilities?
A cluster coordinator is responsible for ensuring that his or her cluster fulfils its role (with regard to needs assessment, response planning, setting of strategies/approaches, provision of policy/operational guidance, coordination of field responses, inter-cluster engagement, information management, monitoring and …
When do you not need to cluster standard errors?
You want to say something about the association between schooling and wages in a particular population, and are using a random sample of workers from this population. Then there is no need to adjust the standard errors for clustering at all, even if clustering would change the standard errors.
When to use cluster robust error in inference?
In such settings default standard errors can greatly overstate estimator precision. Instead, if the number of clusters is large, statistical inference after OLS should be based on cluster-robust standard errors. We outline the basic method as well as many complications that can arise in practice.
When to cluster EHW and LZ standard errors?
Special case: even when the sampling is clustered, the EHW and LZ standard errors will be the same if there is no heterogeneity in the treatment effects.
When do you need to make a cluster adjustment?
The general rule is that you still need to cluster if either the sampling or assignment to treatment was clustered. However, the authors show that cluster adjustments will only make an adjustment with fixed effects if there is heterogeneity in treatment effects.