Power-law distributions, the h-index, and Google Scholar (GS) citations: a test of their relationship with economics Nobelists

This paper comprises an analysis of whether Google Scholar (GS) can construct documentary sets relevant for the evaluation of the works of researchers. The researchers analyzed were two samples of Nobelists in economics: an original sample of five laureates downloaded in September, 2011; and a validating sample of laureates downloaded in October, 2013. Two methods were utilized to conduct this analysis. The first is distributional. Here it is shown that the distributions of the laureates' works by total GS citations belong within the Lotkaian or power-law domain, whose major characteristic is asymptote or " tail " to the right. It also proves that this asymptote is conterminous with the laureates' h-indexes, which demarcate their core oeuvre. This overlap is proof of both the ability of GS to form relevant documentary sets and the validity of the h-index. The second method is semantic. This method shows that the extreme outliers at the right tip of the tail—a signature feature of the economists' distributions—are not random events but related by subject to contributions to the discipline for which the laureates were awarded this prize. Another interesting finding is the important role played by working papers in the dissemination of new economic knowledge.