The answer to this specific question really depends on the priorities and objectives of your research. Most guides will say that if sampling is done without replacement and if the sample fraction is greater than 5%, a population correction is necessary. This is true because the central limit theorem does not hold for large sample densities and estimates will be large. Most IPUMS census samples meet those criteria: most are 10% samples taken without replacement. That said, census samples in IPUMS International are almost all very large, and the precision gained by correcting with finite population correction is likely not necessary. For studies of smaller sub-populations and or rarer phenomena, it could be more useful.
On top of all of this is a recent movement across the social sciences to not place too much emphasis on statistical significance, without an at least equal emphasis on social or economic significance. The March issue of The American Statistician discusses this detail (see the introduction to the issue here). Additionally the journal Nature recently published a note, cosigned by a long list of scientists from across many academic disciplines, discussing the perceived overemphasis on statistical significance.
Although I cannot give you a certain recommendation for whether you should or shouldn’t use a finite population correction, I hope these resources help.