Page 1 Digital Transformations A Research Programme at London Business School Funded by the Leverhulme Trust “Why is there no New Economy in Old Europe?” OR “The Networked Computer” By Leonard Waverman, LBS and Melvyn Fuss, University of Toronto.

Page 2 The Purpose of This Research  Macro-economic and sectoral level views of the impact of ICT:  Macro-economic and sectoral level views of the impact of ICT: Complements the detailed industry and firm- level views of the impact of ICT.  Quantifying and explaining the aggregate effect of ICT crucial to understanding significance of ICT.

Page 3  Why is there a “productivity pop” in some countries, post-1995, but not others?  What is the role of IC (Computers) and T (Telecoms) in the productivity divergence between the US and (most of) Europe?  What is the role of interactions between telecoms and computers in generating externalities from ICT capital? This is the concept of the “networked computer.”  Can an econometric approach provide better answers than growth accounting? “Why is There no New Economy in Old Europe?” Our Research Questions.

Page 4 WHY? Motivation for our research

Page 5 What’s Different about this Research?  We use an econometric approach, allowing for non- linearities and network effects in the use of ICTs and Telecoms.  Control for two-way causality between productivity/income and use of ICTs.  Try to capture interactions between PCs and Telecoms.  Give telecom sector its due.

Page 6 Our Model: A Production Function Approach  We model output (or output per hour) as a function of capital, effective ICT capital, and labour: –Y=AH al KAP NI aNI [G(KAP ICT,PEN,PCI,DIG)] aIT e at*t –G(.) is the real effective ICT capital stock –Telecom and PC penetration, Digitalisation are characteristics of the stock, which raise its effectiveness.  Telecom and PC penetration are determined endogenously in the model through demand and supply equations.  An “investment” equation translates ICT investment into diffusion/penetration/characteristics.

Page 7 The Model: Data and Estimation issues  Model the level of output/productivity in 17 OECD countries (EU-14, US, Canada, Australia) for  Data from ITU, and the Growth Accounting database from the Groningen Growth and Development Centre.  Supply and demand equations allow us to correct for reverse causality between income and ICT diffusion.  Can either use fixed effects (exploit panel structure of dataset) for an equation with output level as the LHS, or use productivity on LHS. –Correct for, or eliminate, country size issues.

Page 8 Econometric Considerations  Used GMM estimation for system of equations- similar to 3SLS, but corrected for heteroscedasticity and autocorrelation.  A few econometric issues: –Time series dimension of the data raises some complications. –Country-level fixed effects dummies “explain” a lot about level of output.  Moved from fixed effects to a pooled model with output/hour as the dependent variable.

Page 9 Estimation Results  Parameters in the Labour Productivity Equation: Parameter Estimate Std Err t Value Pr > |t| a <.0001 ak <.0001 ak+al+aICT <.0001 aICT AMed*PCI aHIGH*PCI aPEN aPCI aT

Page 10 Results: Interpretation and Discussion  Coefficient on ICT capital suggests higher marginal product for ICT capital than non-ICT capital –Evaluated at sample mean the marginal product of ICT capital is 2.14 times that of non-ICT capital.  PC and telecom penetration have positive impact on productivity. –Coefficients on MED and HIGH estimate the impact of interaction between PC penetration and telecom network modernisation.  Time trend is slightly negative and significant. Suggests time- series econometric issues.  Other equations (e.g., PC demand, telecom demand) generally perform well.

Page 11 Sources of Labour Productivity Differences, 2003 United States versus EU, Canada and Australia

Page 12 ICT Contribution to US/EU Productivity Gap, 2003 ICT “over-explains” EU/US productivity gap (0.15/0.7 or 210 percent!), partially compensated for by non- ICT factors

Page 13 ICT Contribution to US/Canada Productivity Gap, 2003 ICT explains roughly 50 percent (0.10/0.20) of the US/Canada productivity gap, scale factors also important.

Page 14 France leads US in productivity on per hour basis- but not on a per capita basis. ICT reduces French advantage by 14 percent, so with more ICT and better use of ICT, France could close the living standards gap without working longer hours. France versus the US: ICT reduces French lead

Page 15 Findings  Econometric results suggest that ICT differences between US and Canada/EU/Australia explain a good deal of the difference in productivity levels.  Our results capture impact of both ICT investment and the spread of ICT into the wider economy.  Impact of “networking” between PCs and the telecom network should be important, but hard to capture econometrically.  PC intensity might be proxy for spread of ICT into wider economy- in which case US has a big lead.  US business more willing to reorganise itself around technology?

Page 16 US Leads in Investment AND Usage Europe lags US and other countries in both ICT capital stock AND the spread of ICT

Page 17 Major EU Economies are Major Laggards Some smaller European economies show US-like ICT intensity, but the major economies lag in adoption and investment.

Page 18 Policy Implications  Increased ICT investment has two productivity- increasing effects: –Capital deepening. –Translates into higher usage and usage spillovers.  So EU and Canada need to both increase investment and ensure investment translates into diffusion/usage.  Effectiveness of investment affected by: –Government Regulation. –Firm Managerial Practices. –Complementary capital- worker skills, training etc.  Macro level studies invariably lead us back to micro level answers- focus of other research on this project.