Measuring the depreciation of intangibles using Search Volume Data

John Lourenze Poquiz

Discussion Papers from Economic Statistics Centre of Excellence

Abstract: This study introduces a novel methodology to estimate the depreciation of intangible assets, specifically focusing on software and creative originals, using data from Google Search Volume (GSV), commonly referred to as Google Trends. Depreciation, in this context, is understood as a manifestation of obsolescence. As intangible assets become obsolete, their ability to generate revenues diminishes relative to the time of their introduction. GSV provides a practical means to gauge the popularity of products generated by these assets, as a surge in internet searches indicates their relevance. The decline in search activity over time is directly associated with the concept of obsolescence, aligning with economic depreciation principles. In our analysis, we employ Poisson Pseudo-Maximum-Likelihood (PPML) and negative binomial regressions to estimate the rate of decline of GSV results for a sample of software and movie titles. Our findings reveal a depreciation rate for s oftware originals ranging from 13.4 to 19.4 percent. This is lower than the estimates employed by statistical agencies, which is around 20 to 25 percent. Estimates for movies are comparable to estimates by statistical agencies, notably the US and Germany. We also find that if we apply the depreciation rates we generated from this methodology to the estimation of capital stock, TFP growth for the Information and Communication industry would be higher for non-crisis years, particularly from 1996 to early 2008, and again from 2011 to the end of 2016.

Keywords: Intangibles; depreciation; SNA; capital stock; Google Trends (search for similar items in EconPapers)
JEL-codes: C80 E01 E22 O34 O47 (search for similar items in EconPapers)
Date: 2025-02-06
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.repository-escoe.com/id/eprint/59/1/ESCoE%20DP%202025-02.pdf

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eoe:escoed:escoe-dp-2025-02

Access Statistics for this paper

More papers in Discussion Papers from Economic Statistics Centre of Excellence Economic Statistics Centre of Excellence, Melbourne House, Aldwych, WC2B 4PJ. Contact information at EDIRC.
Bibliographic data for series maintained by Communications Manager ().