Abstract
The demand for letters is in decline because of electronic (e)-substitution. However, there is limited published information on the detail and extent to which the cumulative impact of e-substitution has reduced letter volumes. This chapter provides estimates of the degree to which e-substitution has reduced the demand for B2C business letters in the UK overall and by content type, sender group and age group of recipients. Volumes for such traffic in 2016 are estimated to have been about 40% of the level they would have reached if there had been no e-substitution and the extent to which it has taken place has been highly uneven across different segments of business mail. ANOVA estimates suggest that of the factors examined to account for differences in e-substitution the age of recipients was by far the most important and in a distant second place was the interaction of content-sender factors.
The views expressed in this chapter are those of the authors and do not necessarily reflect those of the organizations to which they are affiliated. We are grateful for comments on an earlier version of this article by Aleksander Rutkowski and the editors.
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- 1.
An alternative approach would have been to have identified variables that can be directly associated with e-substitution. However, as noted by Jarosik et al. (2013, p. 203), models including time trends tended to contain better properties and diagnostic test statistics than those including Internet and broadband penetration rates. This may be because the dynamic impact of technology related letter substitution is unlikely to be reflected within the properties of a single direct variable and time trends may be a better proxy for the net impact of numerous and overlapping technology effects. Further discussion on this issue is contained in Rodriguez et al. (2016).
- 2.
Although the equation estimated was for the volume of commercial mail and the traffic measure included relatively small amounts of publishing material and lightweight packets, it is considered a good proxy for both total and overall B2C business mail volumes.
- 3.
This value is towards the upper end of the range of the values in the two hypothetical scenarios for the rate of advance of e-substitution presented in Rodriguez et al. (2017, p. 46) of 0.42 in the “low rate of advance scenario” and 0.33 in the “high rate of advance scenario”.
- 4.
The estimated cumulative impact of price on E t by 2016 was to reduce it from 0.42 to 0.39. The main reason for this relatively small difference is that the two letter price elasticities used to inform our analysis were low, as informed by Rodriguez et al. (2016, Table 1, p. 4). In particular, the analysis assumed a real letter own-price elasticity of −0.13 and a real telecommunication price elasticity (acting as a substitute price effect) of 0.18. Therefore only a small proportion of the change in real letter and telecommunication prices, which themselves tend to be low, are estimated to impact letter volumes.
- 5.
For example, in 2016 business mail volumes in the UK were around 60% of their level in 2001.
- 6.
Respondents in the survey completed a detailed diary each day and recorded information on the number of items of mail sent and received, the content of the mail (by content type) and its origin (by sender group). Information was also recorded on the characteristics of the respondent including their age group. The survey is operated by an outside market research company and was given to a panel sample of about 1500 households, with 1200 reporting each month and weighted to reflect population characteristics. The business mail outputs of the survey are periodically checked against Royal Mail customer and product data information for consistency and are deemed by business experts to be broadly representative. However, as these data are from a survey, they are subject to sampling error and noise and the results reported in the current paper are best viewed as indicative of main trends.
- 7.
As the estimated impact of the effect of price changes on letter volumes was estimated to be relatively small (see footnote 4) the analysis was simplified by including this effect within E t .
- 8.
Consistent with Veruete-McKay et al. (2011), population enters (2) separately in order to reflect the impact of delivery point growth on demand while the impact of population on total economic activity is embodied in the GDP term. The demographic variable in Veruete-McKay et al. to capture delivery point growth is the number of households and population is used in the current chapter as a proxy, given the lack of published disaggregated annual data in the UK on the number of households.
- 9.
- 10.
If we had adopted the expression referred to in footnote 9, expression (4) would have taken the form \( {E}_{st}={E}_t.\left(\frac{a_{st}}{a_{s,t=0}}\right).\left(\frac{{\left(1+{G}_t\right)}^g}{{\left(1+{G}_{st}\right)}^{g_s}}\right).\left(\frac{{\left(1+{P}_t\right)}^p}{{\left(1+{P}_{st}\right)}^{p_s}}\right) \) and estimates for E st would be marginally different. A range of estimates found the differences to E st to move the third decimal point or in most cases the fourth or fifth.
- 11.
As noted, these estimates of e-substitution by age group of recipient were derived using population data. Broadly similar results were obtained using instead more limited household data as the demographic measure in expression (3). In particular, estimates using household data from the decennial censuses of 2001 and 2011 (the only source of data in the UK on the number of households at the level of disaggregation required for these estimates) were within ±0.03 of those contained in Fig. 1 for each age group in 2011.
- 12.
Definitions of mail as reported by OIG. For example, between 2001 and 2016 the percentage change in transactional mail received by households with a head aged 25–34 was −58%; −49%, aged 35–44; −41%, aged 45–54; −36%, aged 55–64; and only −25% for those aged 65+ (OIG, 2018b, p. 8).
- 13.
For details about ANOVA models see for example Cameron and Trivedi (2010).
- 14.
A similar conclusion can be drawn when examining the age-content equivalent of Fig. 2.
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Cazals, C., Magnac, T., Rodriguez, F., Soteri, S. (2018). To What Extent Has E-Substitution Impacted the Demand for Letters and Which Factors Are Constraining Its Advance. In: Parcu, P., Brennan, T., Glass, V. (eds) New Business and Regulatory Strategies in the Postal Sector. Topics in Regulatory Economics and Policy. Springer, Cham. https://doi.org/10.1007/978-3-030-02937-1_20
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