1. Silvia Dal Bianco London Metropolitan University FIRST WORLD CONGRESS OF COMPARATIVE ECONOMICS Rome 25-27 June 2015

2. Overview (1) Empirical exercise that estimates MPK in Manufacturing industries Aim: assessing whether MPK differs among developing and developed countries WHEN we provide a better measurement of capital stock Motivation: novel information on world capital allocation in the context of the so-called premature de-industrialisation

3. Overview (2) Literature context Stylised evidence and RQ Exercise: Sample, Methodology, Data Sources Results Policy Implications

4. Literature streams/ context Comparative economic development and efficient allocation of world’s capital stock (Lucas 1990, AER; Hsieh and Klenow 2007, AER; Caselli and Feyrer 2007, QJE) Role of physical capital for development(Durlauf and Yusuf 2014, GD) Meas urement of the quality of physical capital given possibly differing vintage (Armenter and Lahiri 2006, FED NY; Boucekkine, de la Croix and Licandro 2011) Premature De-industrialisation (Rodrik, 2013, 2014, 2015)

5. Stylised evidence and RQ 1. Capital per worker is lower in developing countries than in advanced ones Does MPK exhibit the predictable pattern? Is MPK higher in LDCs? If yes: world capital stock misallocation due to credit mkt frictions If not: Lucas (1990); Hsieh and Klenow (2007); Caselli and Feyrer (2007) Any industry-specificity? 2. Premature De-industrialisation Any link between 1 and 2?

6. SF1 Capital per worker and development : Overall Economy Caselli and Feyrer 2007, QJE)

7. SF1 Capital per worker and development : Manufacturing

8. SF1 Capital per worker and development : Manufacturing Industries (1) Resource Based Low Technology

9. SF1 Capital per worker and development : Manufacturing Industries (2) Medium Technology High Technology

10. SF2: Premature De-industrialisation DEF: (...) countries are running out of industrialization opportunities sooner and at much lower levels of income compared to the experience of early industrializers, Rodrik (2015, IAS)

11. The exercise Net capital stock estimation employing two PIM specifications: 1. Exponential efficiency decay and no random service life (standard) 2. Delayed efficiency decay and random service life (takes into account the age-distribution of vintages) Calculation of MPK, under 1 and 2 Comparison of results obtained Sample: 52 countries, 28 developing and 24 developed Manufacturing Industries: 20 (3 digits ISIC Code Revision 2 Year: 1996

12. Countries and Sectors Data Sources: UNIDO Industrial Statistics Database 2004 at 3-digit level of ISIC Code (Revision 2), World Bank WDI and PWT 6.1

13. Perpetual Inventory Method

14. Empirical Implementation Exponential decay and no random service life: δ= 0.06 Delayed efficiency decay (β=0.5) and random service life (truncated normal density) Initial capital stock: Solow growth model (Steady State), first year 1965 Result: sector-specific capital stock series in 1996 PPP $, under the two hypotheses Reliable estimates from 1995

15. More on π j

16. MPK Calculation MPK=α (Y/K) α= capital share in GDP, backed from labour share (i.e. Industry specific wage bill over GDP) Y= MVA K PIM = Exponential decay and no random service life K BETA = Delayed efficiency decay and random service life

17. Results, ISIC 300

18. ISIC 311, 313, 314

19. ISIC 321, 322, 323, 324

20. ISIC 382

21. ISIC 383

22. Results MPK equalisation when the age distribution of investment goods is taken into account The lower the technological content of production, the more international credit mkt frictions matter The higher the technological content, the more factor complementarities matter Policy implications: 1. Aid in low tech sectors might work 2. Education in high tech 3. Premature de-industrialisation is well explained by technology in HT sectors while globalisation and trade (frictions) might explain the trajectories in LT industries

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