AN INTERNATIONAL PERSPECTIVE ON THE PRODUCTIVITY PARADOX

Transcription

1 Productivity Symposium 2 July 2013 Wellington, New Zealand AN INTERNATIONAL PERSPECTIVE ON THE PRODUCTIVITY PARADOX Alain de Serres Head of Structural Surveillance Division, Economics Department, OECD Joint work with Naomitsu Yashiro and Hervé Boulhol

2 Outline of presentation Nature of the productivity paradox The direct contribution of physical and human capital The role of knowledge-based capital and its growing importance as a source of productivity The role of geographic distance and its impact through international trade Summing-up 2

3 Per capita income and productivity of NZL has been underperforming against major OECD countries Growth performance indicators for New Zealand Gap to a benchmark of 16 OECD countries GDP per capita GDP per hour worked GDI per capita

4 Observed GDP per capita gap in 2009 (in %) 70 Based on comparative policy settings covering many areas NZL income should be higher Observed gap in GDP/capita relative to OECD average versus the gap predicted from various structural policies, 2009 LUX USA FRA GRC NOR BEL SWE FIN AUT ESP IRL CHE ISL DEU JPN DNK NLD CAN ITA GBR KOR NZL -30 PRT Overall GDP per capita gap predicted by the framework (in %) Note: The predicted GDP per capita gap is computed on the basis of estimated impact of various structural policies (ex: product market regulation, labour protection legislation) from past OECD studies. Source: Barnes, S. et al. (2011), The GDP Impact of Reform: A Simple Simulation Framework, OECD Economics Department Working Papers, No. 834, OECD Publishing. 4

5 Outline of presentation Nature of the productivity paradox The direct contribution of physical and human capital The role of knowledge-based capital and its growing importance as a source of productivity The role of geographic distance and its impact through international trade Summing-up 5

6 Using a simple framework to shed light on the sources of the gap A simple econometric analysis based on the Solow framework as developed by Mankiw, Romer and Weil (1992) and which considers physical and human capital. Per capita income level is a function of investments rate in physical capital, level of human capital and the rate of population growth: ln y it = α 1 α lns Kit+ β 1 α lnh it α 1 α ln(n it + g + δ) + f i + f t + e it This function is estimated from a panel of 20 OECD countries between Estimation includes country and time fixed effects and controls for first-order serial correlation. 6

7 Both human and physical capital contributes significantly to per capita income. Dependent variable: (1) (2) (3) (4) GDP per capita Investment rate *** *** *** *** (0.0222) (0.0210) (0.0206) (0.0227) Human capital (Years *** *** *** *** of schooling) (0.0713) (0.0602) (0.0570) (0.0703) Population growth (0.0303) (0.0258) (0.0254) (0.0275) Business R&D/GDP *** *** *** (0.0116) (0.0111) (0.0145) Trade Openess ** (0.0195) Weighted sum of Market and Supplier *** (0.0199) Access Country fixed effects Yes Yes Yes Yes Time fixed effects Yes Yes Yes Yes R squared N

8 Most of the per capita income gap is found in the country fixed effects Contribution to deviation of GDP per capita against 20 OECD country average ( ) 50% 40% 30% 20% 10% 0% -10% -20% Country fixed effects Human capital Physical capital Actual GDP per capita Predicted GDP capita -30% -40% -50% -60% NOR USA IRL CHE NLD CAN AUT DNK BEL DEU GBR SWE AUS FRA FIN JPN ITA ESP NZL PRT 8

9 percentage point Investment rates in physical capital have been comparable to those in other countries though lower than in Australia 15 Non-residential business investments as share of GDP NZL minus other countries AUS CAN SWE USA DNK

10 NZL has narrowed the gap in human capital vis-à-vis selected English-speaking and Nordic countries 30% Human capital (Average years of schooling) NZL minus other countries 20% 10% 0% -10% AUS CAN SWE USA DNK -20% -30% 10

11 The downward trend in labour productivity is mostly reflected in what can be loosely interpreted as MFP 0.40 Country fixed effects + residuals from MRW regression NZL and selected countries AUS CAN NZL SWE USA DNK Downward trend more pronounced after 1990 if good labour market performance was taken into account 11

12 Outline of presentation Nature of the productivity paradox The direct contribution of physical and human capital The role of knowledge-based capital and its growing importance as a source of productivity The role of geographic distance and its impact through international trade Summing-up 12

13 Investment intensity, percentage of value added An important factor missing from the basic Solow framework: Knowledge-based capital Investments in tangible and intangible capital as percentage of business sector value-added 30% 25% 20% 15% 10% 5% 0% Tangible capital Computerised information Innovative Property Economic Competencies Investment in KBC (a.k.a intangible assets) is becoming increasingly important 13

14 NZL s intensity in government and business R&D is lowest among advanced OECD countries Others Higher education R&D Government intramural R&D Business R&D Gross R&D Note: 2009 except for Australia s value for government and higher education R&D is that of Source: OECD Main Science and Technology Indicators 14

15 The augmented Solow regression indicates a significant and positive contribution by R&D to per capita income Dependent variable: (1) (2) (3) (4) GDP per capita Investment rate *** *** *** *** (0.0222) (0.0210) (0.0206) (0.0227) Human capital (Years *** *** *** *** of schooling) (0.0713) (0.0602) (0.0570) (0.0703) Population growth (0.0303) (0.0258) (0.0254) (0.0275) Business R&D/GDP *** *** *** (0.0116) (0.0111) (0.0145) Trade Openess ** (0.0195) Weighted sum of Market and Supplier *** (0.0199) Access Country fixed effects Yes Yes Yes Yes Time fixed effects Yes Yes Yes Yes R squared N

16 However, R&D still explains only a small fraction of per capita income difference 50% Contribution to deviation of GDP per capita against 20 OECD country average ( ) 40% 30% 20% 10% 0% -10% -20% Country fixed effect R&D Human Capital Physical capital Actual GDP per capita Predicted GDP capita -30% -40% -50% NOR USA IRL CHE NLD CAN AUT DNK BEL DEU GBR SWE AUS FRA FIN JPN ITA ESP NZL PRT 16

17 Country fixed effects (deviation from mean) With limited time variation, the contribution of R&D to income level may be largely embodied in country fixed effects 40% Country fixed effects from base MRW regression versus average R&D intensity 30% 20% country FE = *R&D R2=0.234 t= % 0% -10% % -30% NZL -40% Business R&D/GDP (average over ) Note: Country fixed effects are those obtained from the baseline MRW regression. 17

18 Taking into account such R&D driven component of country fixed effect suggests larger role by R&D Contribution to deviation of GDP per capita against 20 OECD country average ( ) 50% 40% 30% 20% 10% 0% Country fixed effect not predicted by R&D Country fixed effect predicted by R&D Human capital Physical capital -10% -20% Actual GDP per capita Predicted GDP capita -30% -40% -50% -60% NOR USA IRL CHE NLD CAN AUT DNK BEL DEU GBR SWE AUS FRA FIN JPN ITA ESP NZL PRT 18

19 Incorporating R&D reduces NZL s MFP gap vis-à-vis OECD average by between 3 and 10% points Country fixed effect plus residual from MRW regression under various settings AUS_base AUS_R&D augumented model AUS_R&D controlled FE NZL_base NZL_R&D augumented model NZL_R&D controlled FE USA_base USA_R&D augumented model USA_R&D controlled FE 19

20 There is more to innovation than R&D, especially in a country with a highly developed service sector Trademarks abroad per capita 500 LUX CHE 100 ISL CAN 10 1 SVK CHL MEX ARG ZAF TUR POL BRA RUS CHN BRIICS SAU PRT GRC CZE ESP NZL AUS SVN ITA EST HUN IRL DNK GBR ISR USA NLD AUT DEU NOR FRA OECD FIN EU27 BEL KOR SWE JPN IDN IND Axes in logarithmic scale Triadic patent families per capita NZL compares relatively well in trademarks 20

21 But the share of total trademarks related to services is relatively low Service-related trademarks applications at USPTO and OHIM (Office for Harmonization in Internal Market),OECD and BRIICS, and (Percentage of total trademark applications at OHIM and USPTO) % While NZL ranks better on trademarks, the share related to services is relatively low 21

22 percentage point ICT capital is considered an important driver of innovation in services 3 Investments in ICT capital as share of GDP The gap between NZL and selected countries AUS CAN SWE USA DNK -2-3 ICT investment has generally been low compared to other countries (except CAN) even though NZL has narrowed the gap in the 2000s 22

23 Organisational capital is key to make the best of ICT investment: reallocation within firms Average management quality score in the manufacturing sector; selected countries Notes: The overall management score is an average of responses to 18 survey questions that are designed to reveal the extent to which firms: i) monitor what goes on inside the firm and use this information for continuous improvement ii) set targets and track outcomes; and iii) effectively utilise incentive structures (e.g. promote and rewarding employees based on performance). The estimates in the right panel are calculated from the difference in management score between each country and the United States and the estimated coefficient on the management score term in a firm level regression of sales on management scores, capital and employment. The sample is based on medium-sized firms, ranging from 50 to employees. Source: Andrews, D. and C. Criscuolo (2013), Knowledge-Based Capital, Innovation and Resource Allocation, OECD Economics Department Working Papers, No

24 Poorly-managed firms survive better in NZL than in the US market Frequency 120 New Zealand United States Management score The distribution of firms according to the quality of their management: low pressures from competition and financial markets? 24

25 Realising the growth potential of KBC requires the smooth reallocation of tangible resources across firms and sectors Additional capital attracted by a firm that increases its patent stock by 10% The estimated impact of various policies on the responsiveness of the firm investment to patenting % Minimum (USA) Maximum (Sweden) Minimum (Sweden) New Zealand Minimum (GBR) New Zealand Minimum (Norway) New Zealand Maximum (New Zealand) 2.0 New Zealand New Zealand Maximum (Portugal) Minimum (Greece) Maximum (Italy) Maximum (Slovak republic) Maximum (Italy) Minimum (Austria) 0.0 Stringency of Employment Protection Legislation Access to Early Stage VC Regulation of professional services Barriers to Trade & Investment Cost of Bankruptcy Legislation for Entrepreneurs Strength of Investor Rights Source: Figures for New Zealand are inferred from the coefficient estimates in Andrews, D., C. Criscuolo and C. Menon (2013), Do Resources Flow to Innovative Firms: Cross-Country Evidence from Firm Level Data, OECD Economics Department Working Papers, forthcoming. 25

26 Outline of presentation Nature of the productivity paradox The direct contribution of physical and human capital The role of knowledge-based capital and its growing importance as a source of productivity The role of geographic distance and its impact through international trade Summing-up 26

27 NZL s trade intensity (adjusted for size) is low by international standards goods and services trade as a share of GDP (%) 300 LUX EST SVN SVK IRL HUN CZE BEL NLD ISL AUT DNK CHE SWE FIN ISR PRT NOR CHL NZL GRC POL AUS ESP KOR CAN MEX ITA GBR FRA TUR JPN DEU Regression line (excluding Luxembourg) USA log(gdp) (value, measured in PPP, 2005 million USD) Trade intensity is still influenced by distance 27

28 Low trade openness is likely to have negative consequence on NZL s per capita income Dependent variable: (1) (2) (3) (4) GDP per capita Investment rate *** *** *** *** (0.0222) (0.0210) (0.0206) (0.0227) Human capital (Years *** *** *** *** of schooling) (0.0713) (0.0602) (0.0570) (0.0703) Population growth (0.0303) (0.0258) (0.0254) (0.0275) Business R&D/GDP *** *** *** (0.0116) (0.0111) (0.0145) Trade Openess ** (0.0195) Weighted sum of Market and Supplier *** (0.0199) Access Country fixed effects Yes Yes Yes Yes Time fixed effects Yes Yes Yes Yes R squared N Trade matters for growth through stronger competitive pressures and higher returns to scale 28

29 The access to market is much lower for AUS and NZL and had not yet improved by the mid-2000s 8.5 Redding-Venables index of market and supplier access AUS CAN DNK NZL SWE USA The gap could be narrowed by a shift in trade flows towards closer partners 29

30 The impact of geographic disadvantage is found to have a significant impact on income Dependent variable: (1) (2) (3) (4) GDP per capita Investment rate *** *** *** *** (0.0222) (0.0210) (0.0206) (0.0227) Human capital (Years *** *** *** *** of schooling) (0.0713) (0.0602) (0.0570) (0.0703) Population growth (0.0303) (0.0258) (0.0254) (0.0275) Business R&D/GDP *** *** *** (0.0116) (0.0111) (0.0145) Trade Openess ** (0.0195) Weighted sum of Market and Supplier *** (0.0199) Access Country fixed effects Yes Yes Yes Yes Time fixed effects Yes Yes Yes Yes R squared N

31 Remoteness explains a substantial portion of NZL negative country fixed effects 50% Contribution to deviation of GDP per capita against 20 OECD country average ( ) 40% 30% 20% 10% 0% -10% -20% Country fixed effect Market and Supplier access R&D Human capital Physical capital Actual GDP per capita Predicted GDP capita -30% -40% -50% NOR USA IRL CHE NLD CAN AUT DNK BEL GBR SWE AUS FRA FIN JPN ITA ESP NZL PRT 31

32 Incorporating market access along with R&D reduces NZL MFP gap against OECD average by up to 17% points 40% Country fixed effects and residual from MRW regression under various settings AUS_base 30% AUS_R&D 20% 10% 0% -10% -20% AUS_R&D + Market and supplier access NZL_base NZL_R&D NZL_R&D + Market and supplier access USA_base USA_R&D -30% USA_R&D + Market and supplier access -40% 32

33 Incorporating market access along with R&D contribution in country fixed effects reduces NZL s MFP gap by about 25 PP 0.4 Country fixed effects and residual from MRW regression under various settings 0.3 NZL_base 0.2 NZL_R&D controlled FE NZL_MASA with R&D controlled FE USA_base -0.1 USA_R&D controlled FE USA_MASA with R&D controlled FE An upper bound estimate!!! 33

34 NZL could export more to Latin America and part of Asia and less to Northern Europe Difference between actual and estimated shares of total exports to country 5.0 AUS 3.0 NZL Source: Bosquet and Boulhol (2013): What is really puzzling about the distance puzzle? 34

35 No evidence could be found that better market access boosts the returns to R&D or human capital. Dependent variable: (1) (2) (3) (4) (5) log GDP per capita Investment rate *** *** *** *** *** (0.0222) (0.0210) (0.0206) (0.0227) (0.0227) Human capital (Years of *** *** *** *** *** schooling) (0.0713) (0.0602) (0.0570) (0.0703) (0.0741) Population growth (0.0303) (0.0258) (0.0254) (0.0275) (0.0276) Business R&D/GDP *** *** *** (0.0116) (0.0111) (0.0145) Trade Openess ** (0.0195) Weighted sum of Market and Supplier Access *** (0.0199) Human capital interacted with urban agglomeration Country fixed effects Yes Yes Yes Yes Yes Time fixed effects Yes Yes Yes Yes Yes *** (0.0694) R squared Number of observations But the estimates provide tentative evidence that urban concentration increases returns to human capital 35

36 Summing-up Distance to market, the gap in innovation and good integration of low-skilled workers can potentially explain between half and twothirds of the 30 per cent productivity gap Boosting innovation especially in services may require better reallocation of resources both within and across firms Within firms: adapting business practices to new technology: stronger pressures from competition and financial markets Across firms: improving access to early stage venture capital and easing regulation in professional services Distance cannot be changed but its impact can be minimised Ensure that regulation is as conducive to low transport costs (relatively high regulatory barriers to competition in air transport and telecoms) Strengthen trade links with markets close(r) to home 36

37 SYMPOSIUM: UNPICKING NEW ZEALAND S PRODUCTIVITY PARADOX 2 July 2013, Oceania, Te Papa Tongarewa