USE OF ECOMMERCE DATA International comparisons and a

USE OF ECOMMERCE DATA International comparisons and a micro-perspective Michael Polder, OECD-STI/EAS Business Statistics User Event: How E-commerce is changing the shape of business, October 8 2015, BIS conference centre, London, UK

Overview • A sketch of messages from recent OECD publications • From statistics to economic analysis: – Using ICT survey micro-data to investigate the relation between • E-commerce and competition • E-commerce, innovation, and productivity – Cross-country analysis with micro-data

A new STI Scoreboard coming up… 2015 To be released October 20

Sketches from recent OECD publications • Relative to broadband website, e-commerce adoption is still fairly low • … and there is substantial variation between countries Highest % Lowest 1 st and 3 rd quartiles Average 100 80 60 40 20 0 Broadband Website E-purchases E-sales

Sketches from recent OECD publications • Magnitude of cross-border e-commerce is limited • … pointing at serious obstacles to ‘go international’

Sketches from recent OECD publications • Magnitude of cross-border e-commerce is limited • … similarly for online purchases by individuals • … pointing at a lack of confidence and trust

Sketches from recent OECD publications • Online purchases by individuals are up… • But still substantial country variation • … and a gap between young and old All 25 -44 year-olds 65 -74 year-olds 2007 FI N FR A N ZL AU T JP N KO R IS L BE L IR L C AN O EC D SV K SV N PO L C ZE ES P IS R G R C H U N PR T IT A ES T C H L TU R M EX H E N LD AU S SW E N O R LU X U SA C N K EU D D G BR % 90 80 70 60 50 40 30 20 10 0

Sketches from recent OECD publications • A new development: ‘m-commerce’ and ‘m-payment’ • Increasing importance and policy interest • … But measurement?

Sketches from recent OECD publications Relatively few firms are engaging in e-commerce … especially cross-border e-commerce Likewise, few individuals buy online from abroad However, overall, online purchasing is increasing … although a significant age gap remains Overall there is still a substantial amount of cross-country variation in the adoption of e-commerce by both firms and households

Use of e-commerce data for economic analysis • ICT usage by enterprises • Relation of e-commerce with – Competition – Innovation – Productivity • Need firm-level analysis – It is (too) often forgotten that the micro-data underlying national statistics is a valuable product!

E-commerce and competition • Background – Consequences of online trading: • Lower search cost • Lower transaction cost • Markets become more transparant – E. g. Brynjolfsson and Smith (2000, Management Science): “Frictionless markets” • Increases (price) competition • Motivates firms to operate cost efficiently

E-commerce and competition • Data (Netherlands only) – – ICT usage and e-commerce enterprise survey Structural Business Statistics Innovation Survey Period: 2002 -2010

E-commerce and competition •

E-commerce and competition •

E-commerce and competition Markups lower in manufacturing relative to services, which indicates stronger competition in manufacturing Source: CBS (2015), ICT and Economic Growth.

E-commerce and competition Increases in e-sales and ecommerce in general have significantly lowered markups, in all sectors Source: CBS (2015), ICT and Economic Growth.

E-commerce and competition • Background – Innovation is a driver of economic growth – Crépon-Duguet-Mairesse (CDM): • Firms invest in R&D (innovation input) • … this leads to knowledge generation (product innovation) • … which ultimately results in increased business performance (productivity) – Variations: • Griffith et al. (2004): product and process innovation • Brynjolfsson et al: ICT investments and complementary organizational changes

E-commerce, innovation and productivity Innovation input • R&D • ICT Innovation output • • Product Process Organisational E-commerce Performance • productivity

E-commerce, innovation and productivity Innovation input • R&D • ICT Innovation output • • Performance Product Process Organisational E-commerce • productivity

E-commerce and competition • Data (Netherlands only) – – ICT usage and e-commerce enterprise survey Structural Business Statistics Innovation Survey Period: 2004 -2010

E-commerce, innovation and productivity Manufacturing PRODUCT coef PROCESS coef ORGANIZATIONAL coef E-COMMERCE coef product innovation -- 0, 447 *** 0, 100 * 0, 112 *** process innovation 0, 447 *** -- 0, 425 *** -0, 032 * organizational innovation 0, 100 ** 0, 425 *** -- 0, 036 e-commerce innovation 0, 112 *** -0, 032 * 0, 036 -- broadband intensity 0, 160 -0, 105 0, 424 *** R&D performer 1, 315 *** 0, 428 *** -0, 008 -- -- Services PRODUCT coef PROCESS coef ORGANIZATIONAL coef E-COMMERCE coef product innovation -- 0, 626 *** 0, 239 *** 0, 106 *** process innovation 0, 626 *** -- 0, 459 *** 0, 055 *** organizational innovation 0, 239 *** 0, 459 *** -- 0, 062 *** e-commerce innovation 0, 106 *** 0, 055 *** 0, 062 *** broadband intensity 0, 427 *** R&D performer 1, 134 *** -0, 054 0, 640 *** -- 0, 257 *** -- 0, 074 * --

E-commerce, innovation and productivity • In terms of productivity gains: e-commerce and process innovation complement each other – That is: combination of both leads greater increase in productivity than the sum of their effects in isolation • Same for e-commerce and organizational innovation • Combination of product innovation with e-commerce does not have any excess productivity gains in manufacturing, and leads to lower gains in services (substitutes) Manufacturing product process organizational e-commerce n. s. COMP Services product process organizational e-commerce SUBS COMP

Cross-country analysis using micro-data • Background: – Comparability of micro-level studies – What is the impact of institutional setting, regulation, and policy? – Lack of available cross-country micro-data

Cross-country analysis using micro-data Source: Bartelsman, Hagsten and Polder (2015), forthcoming

Cross-country analysis using micro-data • ESSNet projects on data linking and ICT impact (ICT Impact, ESSLimit, ESSLait) • 14 participating NSOs • ‘Micro-moments database’ – Indicators based on ‘micro-aggregated’ data – … from linked EC, IS, PS, trade databases – … going beyond usual breakdowns of aggregate data • Moreover: harmonized ‘distributed’ microdatasets at various NSOs allow for remote execution type of empirical analysis

Cross-country analysis using micro-data Source: Bartelsman, Hagsten and Polder (2015), forthcoming

Cross-country analysis using micro-data • Examples: – Dispersion of productivity growth and ICT • Productivity growth by country × time × industry • … and ICT vs non-ICT intensive firms – Resource allocation: • Employment growth by by country × time × industry • … and by quartile of the firm-level productivity growth distribution

Cross-country analysis using micro-data • Examples: – Dispersion of productivity growth and ICT • Productivity growth by country × time × industry • … and ICT vs non-ICT intensive firms – Resource allocation: • Employment growth by by country × time × industry • … and by quartile of the firm-level productivity growth distribution

Cross-country analysis using micro-data

Selected data issues International comparability is in general hampered by differences in • surveys between EU and non-EU and/or non-OECD countries • frequency of the survey • voluntary or compulsory nature of the survey • coverage of subsamples, especially in small countries • reference and recall periods • treatment of outliers and multinationals • ranges recorded in surveys • sectoral coverage • …

Data issues Micro-data analysis benefits from • Increased coverage of firms over time • Coordination of sampling design between surveys (e. g. innovation and ICT) • Stability of definitions and concepts over time • Harmonization of definition and concepts across surveys • Increased international harmonization allows the analysis of micro-data in a cross-country setting

Thank you for listening Any Questions? ?