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Spillovers from public intangibles

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Spillovers from public intangibles. Society for Economic Measurement Annual Conference July 2016. Thessaloniki

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Spillovers from public intangibles

  1. 1. Spillovers from public intangibles C. Corrado, (The Conference Board), New York J. Haskel, (Imperial College, CEPR and IZA), London C. Jona-Lasinio, (LUISS Lab and ISTAT), Rome Society for Economic Measurement Annual Conference 6-8 July 2016, Thessaloniki, Greece This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement No. 612774 Corrado, Haskel, Jona-Lasinio SPINTAN 1 / 20
  2. 2. Background • The public sector is a major investor in many intangible assets (e.g. education, training and R&D), as well as more tangible assets such as roads and telecoms infrastructure. The analysis of possible public sector spillovers to the private sector typically looks (in isolation) at three main public sector investments, in • (a) R&D • (b) education • (c) infrastructure, but there are of course many other assets. • Spillovers from public R&D to the market sector has been studied for Europe by for example Guellec and van Pottelsberghe (2002, and 2004), Salter and Martin (2002) and Park (1995). • One area of spillovers from the Public Sector that has attracted much attention is spillovers from general education to growth (Krueger and Lindahl, 2001; Bassanini and Scarpetta, 2002; Arnold et al. 2007; Inklaar, Timmer and van Ark, 2008; Dearden, Reed and van Reenen, 2006) • ......but there are very few studies of possible spillovers from a wider set of public intangibles to productivity growth. Corrado, Haskel, Jona-Lasinio SPINTAN 2 / 20
  3. 3. Knowledge based capital in the total economy correspondence for computer software, purchased investments in organizational capital, and function-specific worker capital (employer-provided training) is of course far closer. Table 3: Knowledge Capital in a Total Economy Market Sector Nonmarket Sector Computerized Information Information, Scientific, and Cultural Assets 1 Software 1 Software 2 Databases 2 Open data Innovative Property 3 R&D, broadly defined to 3 R&D, basic and applied science include all NPD costs 4 Entertainment & artistic originals 4 Cultural and heritage, including 5 Design arch. & eng. design 6 Mineral exploration 5 Mineral exploration Economic Competencies Societal Competencies 7 Brands 6 Brands 8 Organizational capital 7 Organizational capital (a) Manager capital (a) Professional and manager capital (b) Purchased organizational services (b) Purchased organizational services 9 Firm-specific human capital 8 Function-specific human capital (employer-provided training) (employer-provided training) Note—NPD=New Product Development, including testing and spending for new financial products and other services development not included in software or conventional science-based R&D. The circled items are rather di↵erent in a public sector context. Open data refers to in-Source: Corrado, Haskel, Jona-Lasinio (2014), SPINTAN Working Paper N.1 Corrado, Haskel, Jona-Lasinio SPINTAN 3 / 20
  4. 4. The scope of intangible assets used by the public sector: industries of interest laboratories, public parks and museums) in many countries; see table 1 below. The use of “mar- ket” vs. “nonmarket” groupings of industries is thus not precise because an industry can reflect activity carried out by a mix of producers, as is evident with NACE Section R and the larger section of which NACE Section MB is a part.4 Table 1: SPINTAN Industries of Interest nace nace section Industry title number MB Scientific research and development 72 O Public administration and defence; compulsory social security 84 P Education 85 QA Human health activities 86 QB Residential care and social work activities 87-88 R Creative, arts and entertainment activities; libraries, archives, museums and other cultural activities 90-91 Gambling and betting activities; sports activities and amusement and recreation activities 92-93 Note—NACE Rev. 2. Before we leave the subject of NACE-defined industries, it must be said that in some countries there are industries with significant government or nonmarket production besides those listed in table 1. These tend to be industries that engage in activities not germane to our topic areas, Besides Public administration and defence, other industries in the table contain a mix of market and nonmarket producers. Corrado, Haskel, Jona-Lasinio SPINTAN 4 / 20
  5. 5. Aim The analysis of spillovers from public Non R&D intangibles is a new territory to be explored looking at all the possible channels trough which market and nonmarket sectors interact. Thus we start investigating: • the synergies between nonmarket intangibles and business sector productivity performance and their impact on country’s economic growth. • complementarity/substitutability between market and nonmarket intangibles • the mechanisms through which nonmarket intangibles spillover to the private sector exploring the relation between market sector TFP growth and different measures of public sector knowledge creation using a cross-country-industry econometric analysis. Corrado, Haskel, Jona-Lasinio SPINTAN 5 / 20
  6. 6. Data • Database with multiple dimensions: country, industry, institutional sector, time • Tangible and intangible assets (NA, INTAN Invest and SPINTAN) • 20 industries (A-U Nace Rev 2), 1995-2013, so far 12 countries: • US • Big Northern Europe: DE, FR, UK • Scandinavian: DK FI, SE • Small Europe: AT, CZ, NL • Mediterranean: ES, IT Corrado, Haskel, Jona-Lasinio SPINTAN 6 / 20
  7. 7. Labor productivity growth and Market and Nonmarket Intangibles -.050.05 DlnHQ_mk -.05 0 .05 .1 .15 DlnK_intan_mk “FR” “DE”“SE” “DK”“FI” “UK”“IT” “ES” “NL” “AT” “US” Fitted values -.050.05 -.1 -.05 0 .05 .1 DlnK_intan_nm “FR” “DE” “SE” “DK” “FI” “UK” “IT” “ES” “NL” “AT” “US” Fitted values -.050.05 DlnHQ_mk -.05 0 .05 .1 DlnK_intan_xrdsf_mk “FR” “DE”“SE” “DK”“FI” “UK”“IT” “ES” “NL” “AT” “US” Fitted values -.050.05 -.2 -.1 0 .1 .2 DlnK_intan_xrdsf_nm “FR” “DE” “SE” “DK” “FI” “UK” “IT” “ES” “NL” “AT” “US” Fitted values Labor productivity vs Market and Nonmarket Intangibles Corrado, Haskel, Jona-Lasinio SPINTAN 7 / 20
  8. 8. Market and Nonmarket Intangibles and ICT: complements or substitutes? -.050.05.1.15 DlnK_intan_mk -.1 -.05 0 .05 .1 DlnK_intan_nm “FR” “DE”“SE” “DK”“FI” “UK”“IT” “ES” “NL” “AT” “US” Fitted values -.050.05.1 DlnK_intan_xrdsf_mk -.2 -.1 0 .1 .2 DlnK_intan_xrdsf_nm “FR” “DE”“SE” “DK”“FI” “UK”“IT” “ES” “NL” “AT” “US” Fitted values -.050.05.1.15 DlnK_rd_mk 0 .05 .1 .15 DlnK_rd_nm “FR” “DE” “SE” “DK” “FI” “ES” “IT” (firstnm) DlnK_rd_mk“NL” “AT” “US” 0.05.1.15.2.25 DlnK_ICT_isf_mk -.1 0 .1 .2 .3 DlnK_ICT_isf_nm “FR” “DE”“SE” “DK”“FI” “UK”“IT” “ES” “NL” “AT” “US” Fitted values Market and Nonmarket Intangibles Corrado, Haskel, Jona-Lasinio SPINTAN 8 / 20
  9. 9. TFP vs Market and Nonmarket Intangibles -.1-.050.05 Dln_TFP -.05 0 .05 .1 .15 DlnK_intan_mk “FR” “DE”“SE” “DK”“FI” “UK”“IT” “ES” “NL” “AT” “US” Fitted values -.1-.050.05 -.1 -.05 0 .05 .1 DlnK_intan_nm “FR” “DE” “SE” “DK” “FI” “UK” “IT” “ES” “NL” “AT” “US” Fitted values -.1-.050.05 Dln_TFP -.05 0 .05 .1 DlnK_intan_xrdsf_mk “FR” “DE”“SE” “DK”“FI” “UK”“IT” “ES” “NL” “AT” “US” Fitted values -.1-.050.05 -.2 -.1 0 .1 .2 (firstnm) DlnK_intan_xrdsf_nm “FR” “DE” “SE” “DK” “FI” “UK” “IT” “ES” “NL” “AT” “US” Fitted values TFP vs Market and Nonmarket Intangibles Corrado, Haskel, Jona-Lasinio SPINTAN 9 / 20
  10. 10. TFP and Market and Nonmarket R&D and ICT -.1-.050.05 Dln_TFP 0 .2 .4 .6 .8 DlnK_rd_mk “FR” “DE”“SE” “DK”“FI” “UK”“IT” “ES” “NL” “AT” “US” Fitted values -.1-.050.05 0 .05 .1 .15 DlnK_rd_nm “FR” “DE” “SE” “DK” “FI” “UK” “IT” “ES” “NL” “AT” “US” Fitted values -.1-.050.05 Dln_TFP 0 .05 .1 .15 .2 .25 DlnK_ICT_isf_mk “FR” “DE”“SE” “DK”“FI” “UK”“IT” “ES” “NL” “AT” “US” Fitted values -.1-.050.05 -.1 0 .1 .2 .3 DlnK_ICT_isf_nm “FR” “DE” “SE” “DK” “FI” “UK” “IT” “ES” “NL” “AT” “US” Fitted values TFP vs Market and Nonmarket R&D and ICT Corrado, Haskel, Jona-Lasinio SPINTAN 10 / 20
  11. 11. Empirical strategy 1 • We extend the time span of our previous work about spillovers from market sector intangible capital, where we looked at 10 major European countries, over the period 1998-2007 (Corrado, Haskel, Jona-Lasinio, 2014). • We founded evidence of productivity spillovers to increases in market sector intangible capital. • Our finding of growth spillovers to intangible capital was robust to whether R&D is included or excluded and with IV, consistently with an underlying mechanism producing a growth dividend to investments in non-R&D intangibles. Corrado, Haskel, Jona-Lasinio SPINTAN 11 / 20
  12. 12. Empirical strategy 2 Main steps: • Check for spillovers to intangibles over 1998-2013. Did the occurrence of the financial crisis affect (CHJL, 2014) results? • Investigate spillovers from nonmarket sector intangibles distinguishing between R&D and NonR&D intangible capital. Corrado, Haskel, Jona-Lasinio SPINTAN 12 / 20
  13. 13. Econometrics ∆ln(TFPc,t) = β1∆ln(KICT s,c,t) + β2∆ln(KNonICT s,c,t ) (1) + β3∆ln(Ri s,c,t) + β4∆ln(Ls,c,t) + β5∆ln(Xj s,c,t) + λc + λt + ηs,c,t . where s= market, nonmarket sector, i= intangible asset types and ∆ln(Xj ) are other controls depending on the sectoral and asset disaggregation. Corrado, Haskel, Jona-Lasinio SPINTAN 13 / 20
  14. 14. Econometric results: 1 (1) (2) (3) (4) (5) VARIABLES DlnK_NonICT -0.181* -0.207** -0.240** -0.286*** -0.294*** (0.108) (0.105) (0.106) (0.104) (0.103) DlnK_ICT_isf 0.060 0.022 0.021 0.024 0.049 (0.042) (0.044) (0.045) (0.042) (0.041) DlnK_intan 0.177*** 0.172** (0.068) (0.069) DlnK_intan_xrdsf 0.169*** 0.161*** (0.044) (0.043) DlnK_rd -0.045* (0.023) LD.DlnK_rd 0.056*** (0.021) D.DlnL -0.066 -0.077 (0.065) (0.064) LD.DlnL 0.023 0.028 0.031 (0.063) (0.062) (0.062) Observations 192 192 192 192 192 Number of ctrycode 12 12 12 12 12 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 DlnTFP Corrado, Haskel, Jona-Lasinio SPINTAN 14 / 20
  15. 15. Econometric results: 2 (1) (2) (3) (4) (5) VARIABLES DlnK_NonICT_mk -0.088 -0.042 -0.038 (0.126) (0.161) (0.165) DlnK_ICT_isf_mk -0.019 -0.060 -0.065 -0.060 -0.059 (0.046) (0.051) (0.051) (0.051) (0.052) DlnK_rd_mk -0.077 -0.114 -0.118 -0.121 -0.118 (0.078) (0.086) (0.088) (0.085) (0.086) DlnK_intan_xrdsf_mk 0.216*** 0.245*** 0.252*** 0.245*** 0.242*** (0.045) (0.047) (0.049) (0.046) (0.047) DlnL_mk -0.025 -0.005 -0.002 0.005 0.002 (0.058) (0.069) (0.069) (0.066) (0.067) DlnK_rd_nm 0.168** 0.173** 0.165** 0.171** (0.083) (0.083) (0.083) (0.084) DlnK_ICT_isf_nm 0.015 0.014 0.014 (0.036) (0.035) (0.035) DlnK_intan_xrdsf_nm -0.025 (0.042) Observations 158 158 158 158 158 Number of ctrycode 10 10 10 10 10 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 DlnTFP Corrado, Haskel, Jona-Lasinio SPINTAN 15 / 20
  16. 16. Summing up • Spillovers from Non R&D market intangibles are identified supporting previous findings (CHJL, 2014) • Coherently with existing empirical literature (Guellec and van Pottelsberghe (2002, and 2004)) our findings support the existence of spillovers from nonmarket R&D to market sector productivity. • Correlations between market and nonmarket intangibles are positive suggesting complementarities more relevant for Non R&D intangibles. Corrado, Haskel, Jona-Lasinio SPINTAN 16 / 20
  17. 17. Conclusions Policy challenges • A primary characteristic of intangible capital, widely supported by growth accounting exercises and macroeconomic studies, is to be growth-promoting. • This is because intangible investments likely generate spillovers to the economic system being non-rival and possibly non-excludable. Such spillovers, if they exist, might be within the private sector and/or between the public and private sector. • In the light of the prolonged productivity slowdown experienced by many advanced countries after the financial crisis, it would be vital to know which, if any, public sector intangibles had positive spillovers to the rest of the economy. Corrado, Haskel, Jona-Lasinio SPINTAN 17 / 20
  18. 18. Backup slides Corrado, Haskel, Jona-Lasinio SPINTAN 18 / 20
  19. 19. in progress... • As a first step, we will investigate the relationship between market sector labor productivity and public intangibles estimating a production function augmented with market and nonmarket sector intangible capital. ∆ln(Vs,c,t/Ls,c,t) = α1∆ln(KICT s,c,t/Ls,c,t) + α2∆ln(KNonICT s,c,t /Ls,c,t) (2) + α3∆ln(Rs,c,t/Ls,c,t) + λc + λt + ηs,c,t . Where s refers to market and to nonmarket sectors (s=mk, nm), c to the countries and t is time. λc + λt are country and time dummies. • We test equation (1) to check the linkages between market sector labor productivity growth and nonmarket sector intangibles accounting also for R&D and Non R&D intangible capital. Corrado, Haskel, Jona-Lasinio SPINTAN 19 / 20
  20. 20. in progress... • As a second step, we will analyze the complementary/substitute relationship between market and nonmarket intangibles distinguishing between R&D and NonR&D intangible capital. ∆ln(RZ mk,c,t/Lmk,c,t) = β1∆ln(KICT mk,c,t/Lmk,c,t) + β2∆ln(KNonICT mk,c,t /Lmk,c,t) (3) + β3∆ln(RZ mk,c,t/Lmk,c,t) + β4∆ln(RZ nm,c,t/Lnm,c,t) + β5∆ln(Xj s,c,t/Ls,c,t)) + λc + λt + ηs,c,t . where Z= total, NonR&D intangible capital and ∆ln(Xj ) are other controls (such as ∆ln(RR&D s,c,t ), ∆ln(Q/L)s,c,t ) depending on the dependent variable being total or NonR&D intangible capital. Corrado, Haskel, Jona-Lasinio SPINTAN 20 / 20

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