Is Digitalization Driving Domestic Inflation?

Abstract

This paper examines the extent to which digitalization—measured by a new proxy based on IP addresses allocations per country—has influenced inflation dynamics in a sample of 36 advanced and emerging economies over 2000-2017. Phillips curve estimates show that digitalization has a statistically significant negative effect on inflation in the short run. Its economic impact is not large but has increased since 2012 and mainly operates through a cost/competition channel. Principal components and cointegration analysis further suggest digitalization is a key driver of lower trend inflation.

Digitalisation: Channels, Impacts and Implications for Monetary Policy in the Euro Area

“…They estimate that changes in the share of online purchases of goods and services in the retail sector between 2010 and 2015 mechanically lowered inflation in the retail sector by about 0.1 percentage points each year. Along the same lines, Csonto et al (2019) obtain Phillips curve estimates showing statistically significant negative short-run effects of digitalisation on inflation. They find that the effect of digitalisation on inflation is not large but has increased since 2012 and mainly operates through a cost/competition channel.…”

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“…At the same time, the Internet has been found to have a significant and positive impact on economic growth (Noh andYoo 2008, Salahuddin andAlam 2016). Other contributions have considered the impact of the Internet on international trade (Xing 2018, Meijers 2014, Vemuri and Siddiqi 2009, Baunsgaard and Keen 2010, foreign direct investment inflows (Choi 2003) and inflation (Yi and Choi 2005, Csonto et al 2019 -who use the same data on IPv4 and IPv6 address allocations as the present study to construct a digitalization index in order to examine the impact of digitalization on inflation). Looking at ICT and income inequality, Richmond and Triplett (2018) examine panel data covering 109 countries over the period 2001-2014 and find that the impact of ICT on income inequality varies by type of the type of ICT considered, whereby increases in fixed broadband subscriptions are associated on average with increases in income inequality, while increases in mobile phone subscriptions are associated on average with decreases in income inequality, with the former effect larger than the latter.…”

“…Thirdly, where no allocation has been recorded, it does not definitively mean that no connected devices are being used in a particular jurisdiction. However, these caveats are not of sufficient concern to invalidate the usage of the data as a proxy (as also argued in Csonto et al 2019).…”

“…Data on IPv4 and IPv6 allocations is provided by the Asia-Pacific Network Information Centre (APNIC) which has data for almost 200 countries and territories with data on IPv4 from 1990 and on IPv6 from 2009data is available on a monthly basis. While Csonto et al (2019) use high frequency data (monthly) to construct an index of digitalization based on growth rates per country, for the purposes of the present study, we use annual data (i.e., the number of IP addresses as of 1 January (or closest available date) each year 3 as the macroeconomic data is frequently only available on an annual basis.…”

“…Digitalization is our primary variable of interest and as discussed previously is a measure of the number of IP addresses (IPv4 and IPv6) allocated per capita. This variable has been used in Csonto et al (2019). On the one hand, digitalization should have a positive effect on tax revenue via the direct and indirect channels.…”