What affects MFP in the long-run? Evidence from Canadian industries

1. What affects MFP in the long-run? Evidence from Canadian industries Danny Leung and Yi Zheng Bank of Canada, Research Department Structural Studies May 2008 The views expressed in this presentation are those of the authors. No responsibility should be attributed to the Bank of Canada.

2. Motivation • Changes in labour productivity growth driven by changes in MFP • Recent interest in ICT as a determinant of MFP, results mixed • Sensitive to assumptions on timing • Difficulty in accounting for other variables • Two above issues are not exclusive to ICT

3. Contribution • Evaluate possible determinants of MFP using Canadian industry-level data • Adopt an econometric methodology that allows the estimation of the long-run effects of the determinants of MFP • Examine the main determinants of MFP in the same framework

4. Preview of Results • In the long-run, ICT capital services seem to have a small positive effect on MFP • In recent years, the impact of ICT has been stronger, but not instantaneous • Outsourcing and trade openness also influence MFP positively • The impact of competition is unexpectedly negative

5. Variables Considered • ICT – general purpose technology, facilitates organizational change that raises MFP • R&D – innovation, imitation, spillover; generally not fully accounted for in measured MFP • FDI – efficient conduit of technological transfer • Trade – tech. transfer, competition, economies of scale through expanded markets • Outsourcing & offshoring – specialization, economies of scale, firm turnover, restructuring • Competition –its relation with innovation is ambiguous • Public infrastructure – “omitted” capital

6. The Model (1) • ARDL • Reparameterized to ECM

7. The Model (2) • The Pooled Mean Group Estimator • Pesaran et al (1999) • Constrains long-run parameters to be identical, but allows short-run coefficients and error variances to differ across groups • Traditional dynamic fixed effect model restricts all coefficients to be the same • Estimating each equation separately may not be feasible given sample size

8. The Data (1) • Twelve 2-digit NAICS industries (covering all of business sector), 1976-2003 • MFP – from Canadian productivity accounts (CPA) • ICT capital services, CPA • R&D measures (1987-2003), various sources • Own-industry R&D stock (RD) • R&D spill-over; weighted R&D stock of suppliers (SRD) • R&D intensity (RDI)

9. The Data (2) • Public infrastructure (infra_g) or mass infrastructure (infra_m) - Stock of engineering capital owned by gov’t or infra_g plus engineering capital of transportation and utilities sectors, CANSIM • Outsourcing – intermediate inputs costs over nominal gross output, CPA • Global trade openness – nominal world imports and exports over world GDP, IMF • Markup • price over average variable cost –nominal output over labour, energy and materials costs, CPA • price over average cost – from production function estimation with unobserved component, Leung (2008)

10. ICT

11. Own R&D capital

12. Spill-over R&D capital

13. Public infrastructure

14. Mass infrastructure

15. Outsourcing

16. Trade openness

17. Markup (P/AVC)

18. Unit Root Test (1) • Im, Pesaran and Shin (2003), ADF • H0: series from each industry contain unit root • Ha: fraction of series are stationary with heterogenous coefficients • Hadri (2000) • H0: series are stationary • Pesaran (2003), CADF • IPS test that relaxes assumption of cross-sectional independence between industries

19. Unit Root Test (2)

20. Unit Root Test (3)

21. Cointegration (1) • Pedroni (1999, 2004), residual-based tests with null of no cointegration • four “panel” tests with alternative that residuals have homogeneous autoregressive coefficient • three “group” tests with alternative without homogeneity assumption • General-to-specific approach • Variables dropped one at a time from relationship to see if null is still rejected • Most parsimonious specification includes MFP, ICT capital, outsourcing, trade openness, and markup

22. Cointegration (2)

23. PMG Results – Long Run (1)

24. PMG Results – Long Run (2) • Impact of ICT is small • Effect of outsourcing is positive • Effect of trade openness is positive • Higher competition (lower markup) has a negative effect on MFP • Inverted U-shaped relation between competition and innovation

25. PMG Results – Long Run (3) • Resonable fit • No evidence of non-normal errors, Jarque-Bera test • Two of twelve industries exhibit heteroskedasticity, Breush-Pagan test • Breush-Godfrey test of serial correlation and RESET test indicate a possibility of missing variables for certain industries

26. PMG Results – Short Run • Speed of adjustment is -0.4 on average • 95% of a deviation from long-run equilibrium corrected in 5 years • Average coefficients on current and lagged growth rates of ICT are negative, but statistically insignificant • Sum of short-run ICT coefficients is negative and significant in retail trade and manufacturing

27. Dynamic Decomposition (1) • It is possible to decompose MFP growth into contributions by factor • assuming speed adjustment is the same for all factors and assuming equilibrium in the initial period

28. Dynamic Decomposition (2)

29. Concluding Remarks • The long-run impact of ICT is small, but its contribution to recent MFP growth in some industries is large • Outsourcing and global trade openness have a positive effect on MFP in the long-run • The effect of competition in MFP is negative