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Nick Bloom, Stanford & Centre for Economic Performance

It Ain’t What You Do It’s The Way That You Do I.T.: Investigating the Productivity Miracle using Multinationals* Bank of England, February 2006. Nick Bloom, Stanford & Centre for Economic Performance Raffaella Sadun, LSE & Centre for Economic Performance

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Nick Bloom, Stanford & Centre for Economic Performance

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  1. It Ain’t What You Do It’s The Way That You Do I.T.:Investigating the Productivity Miracleusing Multinationals*Bank of England, February 2006 Nick Bloom, Stanford & Centre for Economic Performance Raffaella Sadun, LSE & Centre for Economic Performance John Van Reenen, LSE & Centre for Economic Performance * The paper formerly known as: “Nobody does I.T. better”

  2. Recent US “productivity miracle” not occurred in Europe • Evidence is this is being driven by IT intensive sectors • But why only in US as IT globally available? • Three types of arguments proposed: • US geographic advantage (skills, land, planning, clean air…) • US good luck (first mover advantage) • US better management/organisation • We present a model and range of evidence supporting the third Overview (1)

  3. Model has three elements • IT prices falling rapidly • IT complementary with newer organisation/management • US “decentralized” first because lower labor regulations • Empirical evidence supporting this from three blocks • Macro evidence: fits the well-known macro data • Survey evidence: fits new organisational/management data • Micro evidence: fits new micro data • US MNEs more productive than non-US MNEs in UK • Higher US productivity due to higher returns to IT • Particularly in IT intensive sectors • Very robust and also true for US takeovers Overview (2)

  4. OUTLINE • Stylized facts and motivation • Model outline and predictions • Testing this on UK establishment level data

  5. US productivity is accelerating away from the EU

  6. This is driven by the US “productivity miracle”

  7. The “productivity miracle” appears linked to IT use Source: O’Mahony and Van Ark (2003)

  8. The US also started investing much more in IT…

  9. ….but not much more in non-IT capital

  10. All occurred as IT prices started to fall rapidly

  11. So what is behind the US “productivity miracle”? • Superior US geographic factors: • Greater supply of skilled/younger workers • Higher competition • Lower planning regulation but link to IT in mid 1990s and US MNEs in UK? • US good luck: • US firms invested in IT first but why don’t Europeans copy this • US firms better organised and managed: • Organisation/management important for the productivity of IT (Brynjolfsson, Bresnahan & Hitt, 2002) but are US firms better organised & managed?

  12. US and EU firms decentralization and managed Organizational devolvement Management practices European Firms European Firms US Firms US Firms Organizational devolvement(firms located in Europe) Management practices(firms located in Europe) Domestic Firms in Europe Domestic Firms in Europe Non-US MNEs in Europe Non-US MNEs in Europe US MNEsin Europe US MNEsin Europe Source: Bloom and Van Reenen (2005) survey of 732 firms in the US, UK, France and Germany. Differences between “US-multinational” and “Domestic” firms significant at 1% level in all panels except bottom left which is significant at the 10% level.

  13. Papers claims organisation/management the story Build simple model explaining the macro data • Centralized “Taylorism” complementary with traditional capital, decentralization complementary with IT • IT prices fall fast prompting firms to decentralize • US more flexibility in hiring/firing so decentralize first Test on panel of 7,500 UK establishment from 1995-2003 • US MNEs more productive than non-US MNEs • From higher productivity of IT in US MNEs v non-US MNEs • Particularly IT intensive sectors as in “Productivity Miracle” • US firms also more IT intensive • Robust to range of different measures and take-overs

  14. OUTLINE • Stylized facts and motivation • Model outline and predictions • Testing this on UK establishment level data

  15. Model is very simple – has three ingredients (1) Old-style “Taylorism” complementary with traditional capital, new-style “decentralization” complementary with IT Y = A Cα+λOXβ-λO π = Y- pcC - pxX where: Y=output, A=TFP, C=IT, O=decentralization, X=other factors and π=profit, pc price of IT and px price of other factors. (2) IT prices fall fast so firms want to decentralize quickly (3) Rapid decentralisation costly. Costs higher in EU than US Cost(ΔO) = ωi(Ot-Ot-1)2 where ωEU > ωUS

  16. Model – results Other simplifying assumptions: • Firms always optimising (no European “stupidity”) • Model “detrended”: • No baseline TFP growth • Deterministic • No other stochastics and IT price path known So fall in IT prices driving everything Solving the model • Unique continuous solution and policy correspondences • But need numerical methods for precise parameterisation1 • Very much work in progress 1 Full Matlab code on http://cep.lse.ac.uk/matlabcode/

  17. Prices assumed falling 15% until 1995, 30% after

  18. US decentralizes first due to lower adjustment costs Initially centralized “Taylorism” best US decentralizing as IT prices fall rapidly EU decentralizes later as more costly

  19. IT factor shares rise as US and EU decentralize US decentralizes so IT productivity rises EU decentralizes later so IT productivity rises later Note: IT input quantity always rising as IT price always falling

  20. Decentralized US obtains higher productivity Higher IT inputs lead to higher productivity, particularly in more decentralized US Note: Assumed baseline TFP equal in US and EU, with no TFP growth

  21. US also obtains higher productivity growth Growth from accumulation of IT and decentralisation US growth slows as decentralisation complete

  22. Model also makes other interesting predictions 1) Rising stock market values, particularly in US1 2) If IT also complementary skilled labor, then rising skilled/unskilled wage differential, particularly in US 1 Need to assume some returns to IT accrue to firms – i.e. imperfect competition

  23. Model – taking this to UK establishment data Need one additional assumption: • Multinationals like globally similar management and organisational structures • Easy to integrate managers, HR, software etc.. • Seems reasonable and is true for well-known firms (P&G, McKinsey, MacDonalds, Starbucks etc..) • Then US MNEs and EU MNEs in the UK adopt their parents organisational structure • Pay the adjustment cost for this for integration benefit

  24. OUTLINE • Stylized facts and motivation • Model outline and predictions • Testing this on UK establishment level data

  25. Why UK micro data is a good way to test explanations of the US “productivity miracle” • With just Macro data other possible explanations possible, i.e. • Weaker US retail planning laws and IT important for retail • Need to controlling for other factors, so look in 1 country. UK ideal: • 50% establishments foreign owned (10% US, 40% non-US) • Census data on IT in 7,500 establishment 1995-2003 • Covers manufacturing and services • Looking at this data find strong support for the better US • management/organisation story

  26. Data Productivity Estimation IT and Multinationals Conclusions and next steps

  27. Characteristics of IT Data Four ONS surveys (FAR, ABI, BSCI, QICE) combined to minimize missing observations (similar to LRD data): • Data on IT expenditures, • Combine with ABI data on output, materials, capital, employment, etc. • YEARS: From 1995 to 2003, but most of observations regard 2000-2003 (QICE) • SECTORS: Manufacturing and Services (Services data usually not available) • 22,736 observations

  28. IT Capital Stocks Estimates • Methodology Perpetual inventory method (PIM) to generate establishment level estimates of IT stocks • Assumptions • Initial Conditions • Depreciation rates • Deflators

  29. Methodological Choices

  30. Data Productivity Estimation IT and Multinationals Conclusions and next steps

  31. Econometric Methodology Estimate a standard Production Function (in logs): Where q = ln(Gross Output) a = ln(TFP) m = ln(Materials) l = ln(Labour) k = ln(Non-IT capital) it = ln(IT capital) z = Other controls (age, region, group)

  32. Investigating the impact of foreign ownership • TFP levels can depend on ownership status • Factor coefficients can also depend on ownership status In fact only IT coefficient varies significantly (table 2) US MNE Non-US MNE

  33. Other Econometric Issues • Unobserved “industry effects”, so all variables transformed in deviations from 4 digit industry mean (Klette, 1999) • Some specifications also include establishment fixed effects • All standard errors clustered for arbitrary serial correlation • Try to address endogeneity use GMM and Olley Pakes

  34. Data Productivity Estimation IT and Multinationals Conclusions and next steps

  35. Table 1: IT Coefficient by ownership status Note: All regression include firm clustered SE

  36. Some Robustness Checks (Table 2) • Try factors all varying by ownership – only IT different • Try alternative IT measure – US*IT interaction significant • Try translog functional form – US*IT interaction significant • Try IT share (IT cap /All cap) – US*IT interaction significant • Try using VA (not output) – US*IT interaction significant • Try US industry FDI control – US*IT interaction significant • Try skills controls – US*IT interaction significant

  37. Worried about unobserved heterogeneity? • Maybe US firms only buy plants with higher IT productivity? • Or maybe US firms only is certain sectors? • We control for 4-digit SIC industry • But could argue should divide further (5 or 6 digit)? • Or maybe some kind of other unobserved difference • Local skill supplies, type of product etc… • So test by looking at establishment take-overs by US firms

  38. Table 4: US Takeovers and IT Coefficients Note: All include fixed effects, estimated on the IT using sectors, firm clustered SE

  39. Table 5: US Takeovers and IT Investment US dummy significant higher than Non-US MNE dummy at 5% level Summarizing last 2 slides, after US takeover establishments: • Become more productive due to higher IT productivity • Invest significantly more in IT Note: All include fixed effects, estimated on the IT using sectors, firm clustered SE

  40. US “productivity miracle” matches a simple decentralisation model • IT changes optimal structure of the firm • So as IT prices fall firms want to restructure • Occurred in the US but much less in the EU (regulations) • Consistent with the macro, survey and micro evidence • Three predictions for US-EU growth gap going forwards • EU Optimist (EC) – EU firms will decentralize and catch-up • Moderate – ongoing technical change so permanent gap • EU Pessimist (me) – technical change accelerating so EU falling further and further behind US Conclusions

  41. Back Up

  42. BREAKDOWN OF INDUSTRIES (1 of 3)IT Intensive (Using Sectors)IT-using manufacturing18 Wearing apparel, dressing and dying of fur22 Printing and publishing29 Machinery and equipment31, excl. 313 Electrical machinery and apparatus, excluding insulated wire33, excl. 331 Precision and optical instruments, excluding IT instruments351 Building and repairing of ships and boats353 Aircraft and spacecraft352+359 Railroad equipment and transport equipment36-37 miscellaneous manufacturing and recyclingIT-using services51 Wholesale trades52 Retail trade65 Financial intermediation66 Insurance and pension funding67 Activities related to financial intermediation71 Renting of machinery and equipment73 Research and development741-743 Professional business services

  43. BREAKDOWN OF INDUSTRIES (2 of 3)Non- IT Intensive (Using Sectors)Non-IT intensive manufacturing15-16 Food drink and tobacco17 Textiles19 Leather and footwear20 wood21pulp and paper23 mineral oil refining, coke and nuclear24 chemicals25 rubber and plastics26 non-metallic mineral products27 basic metals28 fabricated metal products 34 motor vehiclesNon-IT Services50 sale, maintenance and repair of motor vehicles55 hotels and catering60 Inland transport61 Water transport62 Air transport 63 Supporting transport services, and travel agencies70 Real estate749 Other business activities n.e.c.75 Public Admin and welfare80 Education85 Health and Social Work90-93 Other community, social and personal services95 Private Household99 Extra-territorial organisationsNon-IT intensive other sectors01 Agriculture02 Forestry05 Fishing10-14 Mining and quarrying50-41 Utilities45 Construction

  44. BREAKDOWN OF INDUSTRIES (3 of 3)IT Producing SectorsIT Producing manufacturing30 Office Machinery313 Insulated wire321 Electronic valves and tubes322 Telecom equipment323 radio and TV receivers331 scientific instrumentsIT producing services64 Communications72 Computer services and related activity

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