Sometimes big data turn out not to be representative of the whole population. For example, Groves (2016) 2 argues that big data often contain few variables and extracting their value requires linkages to other data; furthermore, they lack representativeness. Social media or any other internet-based sources of big data also usually lack full coverage of the population of interest.
The availability of massive amounts of data increases the chances of finding an exceptionally good fit in sample when one estimates any model, but a very poor performance out of sample. Big data are harvested from different technical sources and change with consumers’ preferences. Therefore, the parameters estimated using these data can be subject to different forms of instability.