Digital Dark Matter and the Economics of Apache
Researchers have long hypothesized that spillovers from government, university, and private company R&D contribute to economic growth, but these contributions may be difficult to measure when they take a non-pecuniary form. The growth of networking devices and the Internet in the 1990s and 2000s magnified these challenges, as illustrated by the deployment of the descendent of the NCSA HTTPd server, otherwise known as Apache. This study asks whether this experience could produce measurement issues in standard productivity analysis, specifically omission and attribution issues, and, if so, whether the magnitude is large enough to matter. The study develops and analyzes a novel data set consisting of a 1% sample of all outward-facing web servers used in the United States. We find that use of Apache potentially accounts for a mismeasurement of somewhere between $2 billion and $12 billion, which equates to between 1.3% and 8.7% of the stock of prepackaged software in private fixed investment in the United States. We argue that these findings point to a large potential undercounting of "digital dark matter" and related IT spillovers from university and federal funding.
Keywords: Measurement and Metrics;
Research and Development;