EDIT: if you understand effective genome size as "mappable" genome size, than Devon is right, of course.
Assemblies only will provide you with a good size estimate if they are of really high quality. This is usually only the case for either model organisms or small, bacterial genomes.
Assemblies of larger genomes such as plant, animals etc., and in particular draft genomes usually do not contain a complete representation of a single haplogenome - which you would need to get your size estimate right. The reasons are that assembly algorithms usually cannot resolve all repeats and centromeric/telomeric regions, and also are prone to generate multiple sequences for different alleles of the the same region.
In my opinion, there are two better approaches:
1) Use the experimentally determined nuclear DNA (e.g. www.genomesize.com) content to calculate the haploid genome size. DNA content in pg can be directly converted into a bp estimate.
2) Use a k-mer based approaches to estimate the genome sizes form a high coverage NGS data set of your organism
The simplest method is to just subtract the number of Ns from the total length of the genome. That will over estimate things, but since a real number is read length/pair vs. single end/insert size dependent, this is a simpler and quicker approximation.
In programs like MACS, the effective genome size is used to compute statistics of mapped reads with respect to the size of the genome covered by reads. Such size varies depending on read length and mapping strategy. With mapping strategy I just mean whether multi-mapping reads are kept or discarded. This can introduce a difference of about 20% in human and mouse effective genomes sizes.
If multi-mapping reads (reads that map to multiple positions) are kept then the strategy given by Devon can be used because all positions in the genome can be covered by reads excepts for stretches of NNNs.
Otherwise, the best way to compute the effective genome size is to add up all positions being covered by reads or, if you are using a model organism you can use this table although is a bit outdated as they used reads of length 30.