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Towards Productivity Comparisons Using the KLEMS Approach: an Overview of Sources and Methods

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Towards Productivity Comparisons Using the KLEMS Approach: an Overview of Sources and Methods Towards Productivity Comparisons using the KLEMS Approach: An Overview of Sources and Methods Marcel Timmer Groningen Growth and Development Centre and The Conference Board July 2000 Acknowledgements This report is a feasibility study into an international productivity project using the KLEM growth accounting methodology. It could not have been written without the help of many people. Thanks are due to Bart van Ark, Robert McGuckin, Mary O'Mahony and Dirk Pilat who provided me with helpful comments on earlier drafts of this report. During my visit to the Kennedy School of Government, Harvard University, Mun Ho, Kevin Stiroh and Dale Jorgenson provided me with many insights into the theories and empirical applications of the KLEM-methodology. Discussions with Frank Lee, Wulong Gu and Jianmin Tang (Industry Canada), René Durand (Statistics Canada) and Svend E. Hougaard Jensen, Anders Sørensen, Mogens Fosgerau and Steffen Andersen of the Center of Economic and Business Research (CEBR) provided further insights and new ideas. At the meeting of the KLEM-research consortium on 9 and 10 December at the Centre of Economic and Business Research (CEBR), Copenhagen, consortium members provided me with relevant information, references on ongoing projects and helpful suggestions.Their help is gratefully acknowledged. Prasada Rao (University of New England) is thanked for his advice on the section on purchasing power parities. Finally, the Conference Board is acknowledged for financing the preparation of this report. 1 TABLE OF CONTENTS EXECUTIVE SUMMARY 3 1. INTRODUCTION 5 2. EXISTING DATA SOURCES AND PREVIOUS RESEARCH 7 3. INPUT-OUTPUT TABLES 11 4. LABOUR INPUT 17 4.1 Hours worked 18 4.2 Labour costs 20 4.3 Proposed Cross-Classification for Labour Input 22 5. CAPITAL INPUT 23 5.1 Capital Stock 23 5.2 Rental prices 26 5.3 Proposed Classification for Capital Input 27 6. PURCHASING POWER PARITIES (PPPs) 39 7. SUMMARY AND CONCLUSIONS 32 APPENDIX I INDUSTRIAL CLASSIFICATIONS 33 APPENDIX II.1 OUTLINE OF JORGENSON APPROACH TO CAPITAL INPUT MEASUREMENT 36 APPENDIX II.2 INTERPOLATION TECHNIQUES 38 APPENDIX III COUNTRY EXPERIENCES WITH IMPLEMENTING KLEM 39 Appendix III.1 The Canadian Experience 39 Appendix III.2 The Danish Experience 41 Appendix III.3 Country Status Reports 44 REFERENCES 51 2 EXECUTIVE SUMMARY Growth accounting provides an indispensable instrument to assess the importance of the changes in patterns of economic growth, productivity and competitiveness as shown, for example, by recent research into the effects of ICT on growth. To study patterns of input substitution, technical change and structural change, an international KLEM-type database is indispensable. A KLEM database provides detailed sectoral data on output, capital (K), labour (L), intermediate inputs (M) and energy (E). Recently, a proposal has been put forward by nine European research institutes and universities to construct a KLEM dataset for European countries. This report discusses the feasibility of this project and describes the requirements with respect to the level of detail of the dataset. Numerous data sources and studies exist from which data for this project can be drawn. These are discussed here, focussing on four classes of data: input-output tables, labour accounts, capital flow matrices and purchasing power parities. For the input-output tables, the OECD input-output table database provides the best starting point. For the labour accounts, a combination of Eurostat’s Labour Force Survey and Labour Cost Survey and the earnings surveys of the Luxembourg Income Studies Project is recommended. For capital input, use can be made of capital flow matrices database by the OECD. Annual output and input data from the national accounts can be exploited to develop the full dataset. For the purchasing power parities, a combination of data from the International Comparisons Project (ICP), Eurostat PRODCOM database and data from the International Comparisons of Output and Productivity Project (ICOP) can be made. To ensure international comparability, the report suggests a set of minimal requirements to which each national data set must adhere. The period of study starts in 1970. For input-output tables, a list of 31 industries based on the NACE rev 1 classification is proposed, and a conceptual framework similar to the one used by OECD (1995). For labour input the following cross-classification is suggested: by sex, by 4 types of education (university level and above, non-university tertiary education, upper secondary and below upper secondary education) and 4 age classes (below 25 years, 25-34, 35-54 and more than 54). Capital input should be subdivided in at least 4 types of assets: residential structures, non-residential structures, high-tech equipment (consisting of computers and peripheral equipment, communications equipment, instruments and photocopy and related instruments) and low-tech equipment (all other machinery and transport equipment). This is summarised in the table below. 3 Table 1 Proposed Minimal Requirements of European KLEM database Gross output Industries (according to NACE rev 1.) 31 industries Intermediate inputs Industries (according to NACE rev 1.) 31 industries Labour input (hours worked) 32 types - sex (male/female) 2 types - educational attainment (university level and above (> 16 years of schooling), 4 types non-university tertiary education (> 14 ), upper secondary (>12) and below upper secondary education (< 12)) - age classes (-24, 25-34, 35-54, 55+) 4 types Capital input (capital services) 4 types - residential building, non-residential building, high-tech equipment and low-tech equipment 4 1. INTRODUCTION Aim of the KLEM data project for Europe In the past decades, important changes in the pattern of economic growth in OECD countries have taken place. Recent changes in growth, productivity and employment may be interpreted as a movement towards the so-called knowledge-based economy (OECD 1996, 1999b). Currently, output and employment are expanding fast in high-technology industries such as computers and electronics, as well as knowledge-based services such as financial and other business services. More and more resources are spent on the production and development of new technologies, in particular on information and communication technology. Computers and related equipment are now the fastest growing component of tangible investments. At the same time, a polarisation in European labour markets is taking place as skilled labour is increasing its demand, whereas demand for low-skilled workers is falling. Growth accounting provides an indispensable instrument to assess the importance of these changes in economic growth, productivity and competitiveness. Most clearly this appears from recent research into the effects of ICT on growth (Jorgenson and Stiroh 1999, Schreyer 2000, van Ark 2000). Following the pioneering work of Solow, Kendrick, Denison and Jorgenson in developing growth accounting techniques, many growth accounting studies have been performed over the past decades (Maddison 1987, Hulten 2000). Apart from national studies, international comparisons have also been provided in particular by Denison, Jorgenson and Maddison. Most of these studies have been restricted to aggregate analyses of value added, labour input and capital input. However, a more detailed analysis is warranted when processes of structural change and input substitution have to be assessed. The use of value added measures and aggregate input measures is not satisfactorily because it not only ignores the substitution possibilities between the primary inputs capital (K) and labour (L), and energy (E) and intermediate materials (M), but also between various types of capital (e.g. ICT-capital and non-ICT-capital) and labour (e.g. skilled and unskilled). Jorgenson, Gollop and Fraumeni were the first scholars to outline and apply the basic KLEM-methodology for detailed industry-level analysis of productivity growth in the post-war US economy, which eventually evolved in their seminal 1987 publication. Over the past years, KLEM studies have been carried out in various European countries, including Denmark, Germany, the Netherlands and the United Kingdom, and new work is embarked upon in these countries and elsewhere in Europe (see section 2 and Appendix III). However, so far little attention has been paid to the international comparability of the work undertaken in the various countries. The primary aim of the European KLEM project is to arrive at an internationally comparable data-set for a KLEM-type analysis of productivity growth for eight European countries: Denmark, Finland, France, Germany, Italy, Netherlands, Spain and 5 United Kingdom.1 At a later stage, this European dataset will be linked with a Canada-Japan- USA database to allow for international comparisons. The latter database is currently developed under the aegis of Jorgenson and associates, and sponsored by Industry Canada and MITI. Preliminary results for the Canada-US part are already available (see e.g. Lee and Tang, 1999). The importance of the dataset is clear from the large range of possible applications. It will provide measures of output and productivity growth, structural change and input substitution which are internationally comparable across a wide range of countries. The data set can be used to analyse the issues of sectoral employment growth patterns, efficiency of factor allocation, processes of factor substitution, skill-biases in technological change, etc. In addition, the dataset,
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