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Invited presentation at the Third World KLEMS conference organized by RIETI

Productivity Stagnation and Low Human Capital Investment in a Wealthy Economy: The Case of Italy. Invited presentation at the Third World KLEMS conference organized by RIETI and Harvard university , Department of Economics in Tokyo, 19-20 May 2014. Carlo Milana.

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Invited presentation at the Third World KLEMS conference organized by RIETI

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  1. Productivity Stagnation and Low Human Capital Investment in a Wealthy Economy: The Case of Italy Invitedpresentationat the Third World KLEMS conference organized by RIETI and Harvard university, Department of Economics in Tokyo, 19-20 May 2014 . Carlo Milana Birkbeck College, University of London E-mail: c.milana@bbk.ac.uk

  2. Overview I. Defining the productivity problem in Italy II. Measurement problems and proposed solution III. Empirical results VI. Concluding remarks

  3. Overview I. Defining the productivity problem in Italy II. Measurementproblems and proposedsolution III. Empiricalresults VI. Concludingremarks

  4. Table 1. Nominal tangible assets per capita

  5. 2000-2008

  6. 2000-2008

  7. Overview I. Defining the productivityproblem in Italy II. Measurement problems and proposed solution III. Empiricalresults VI. Concludingremarks

  8. Dale W. Jorgenson and Zvi Griliches (1967), “The Explanation of Productivity Change”, Review of Economic Studies 34: 249-283. Dale W. Jorgenson and Zvi Griliches (1971), “Divisia Index Numbers and Productivity Measurement”, Review of Income and Wealth , pp. 227-229, who wrote: “The main advantage of a chain index is the reduction of errors of approximation as the economy moves from one production configuration to another. […] The Laspeyres approximation to the Divisia index of total factor productivity was employed in our original study of productivity change (1967)” Samuelson and Swamy (1974, pp. 576) where it is stated that “Fisher missed the point made in Samuelson (1947, p. 151) that knowledge of a third situation can add information relevant to the comparison of two given situations” • Kruskal's Minimum Spanning Tree recently proposed. See • Hill, Robert J. (1999a), "Comparing Price Levels across Countries Using Minimum Spanning Trees", Review of • Economics and Statistics 81: 135-142. • Hill, Robert J. (1999b), "International Comparisons using Spanning Trees", in A. Heston and • R.E. Lipsey (eds.), International and Interarea Comparisons of Income, Output, and Prices, Studies in Income • and Wealth, Volume 61, NBER, Chicago: The University of Chicago Press. • Hill, Robert J. (2001), "Linking Countries and Regions using Chaining Methods and Spanning • Trees", prepared for the Joint World Bank-OECD Seminar on Purchasing Power Parities • Recent Advances in Methods and Applications, Washington, D.C., 30th January-2nd February, 2001. Related contributions Afriat’s minimum (maximum) path chained Laspeyers (Paasche) index numbers are very close to the following contributions combined together:

  9. The upperbound of the aggregate input priceindex with twoobservations Factor input 2 B A O Factor input 1

  10. Input 2 P ray C BL q1 L ray BP ....A Upper bound (Laspeyres-type) q0 Lower bound (Paasche-type) Keynes’ method of limits Input 1

  11. Factor input 2 B C O Factor input 1 Extending a bilateral comparison to a multilateral context (Afriat, 1981) A

  12. Input 2 P ray C Laspeyres limit BL q1 L ray Tight bounds q2 Paasche limit ....A Upper bound (Laspeyres-type) q0 Lower bound (Paasche-type) Samuelson-Afriat tight bounds = Input 1

  13. E B D F y1 y0 O Input x2 C Input x1 Misallocation within industry reduces productivity A

  14. . A1 A0 Between industry misallocation causes output loss Output y2 Output y1 Output y1 Output y1

  15. Methodology The search for meaningful economic measures The starting decomposition of the minimum costs are therefore obtained as cost-inefficiency parameter multiplied by observed total costs: The inefficiency parameter etis found in the interval simultaneously along the decomposition

  16. So that we have the following range of possible values: Laspeyres and Paasche matrices withAfriat’s tight upper and lower bound matrices

  17. Scale elasticity and misallocation effect Finding Afriat efficiency index for every i ≥ j where L and K are respectively the Laspeyres and Paasche indexes Finding the scale elasticity : where p is the output price and m is the pure profit margin

  18. Scale effects on TFP

  19. Decomposing TFP growth where Output index Actual input index = Efficiency input index ∙Afriat efficiency index Technical change index Scale effect index Potential gain in TFP level from removal of base-period “within” misallocation Marginal elasticity of scale

  20. Overview I. Defining the productivityproblem in Italy II. Measurementproblems and proposedsolution III. Empirical results VI. Concludingremarks

  21. Figure 11. Average growth rates of TFP, TC, and output loss due to misallocation, 1991-2010 (% p.a.)

  22. Overview I. Defining the productivityproblem in Italy II. Measurementproblems and proposedsolution III. Empiricalresults VI. Concluding remarks

  23. Concluding remarks In intercountry comparisons, Italy appears to lag behind in productivity levels and growth rates notwithstanding its rich endowment of tangible assets. In Italy, an underinvestment in human capital and other intangibles coupled with low rewards for high skilled labour had been part of misallocation of resources with a consistent output loss. A growth strategy based on the acceleration of investments in intangibles and particularly in human capital through education and professional skills seems the most appropriate solution of the Italian productivity problem.

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