1 An Update on KLEMS data at Statistics Canada Wulong Gu Micro Economic Analysis Division Statistics Canada May 13, 2008 Presentation to the 2008 World Congress on National Accounts and Economic Performance Measures for Nations

2 Industry Productivity Database (KLEMS) u A new experimental industry productivity database (KLEMS) was released in June u The database for the first time provides time series data for output and inputs including capital (K), labour (L), energy (E), materials (M) and purchased services (S) based on the new North American Classification system back to 1961.

3 Access to Industry Productivity Database (KLEMS) u Available from CANSIM: Statistics Canada social economic statistics database. –Table provides a series for the aggregate business sector and major sub-sectors, from 1961 to the most recent year –Table provides series at a detailed NAICS industry level, from 1961 to the most recent the input-output tables –Table provides series at a detailed SIC industry level, from 1961 to u Available at most universities (member of Data Liberation Initiative) –KLEMS at the most detailed level of industry aggregation. u Available from free internet publication: The Canadian Productivity Accounts: Data (Statistics Canada Catalogue no X)

4 Additional KLEMS data to be released soon u The data on hours worked and labour compensation by types of workers and industries will be released this year. u The data on investment, capital stock and capital service by asset and industries will be released, expected this year. –The issue of confidentiality for asset-level investment data need to be resolved. u The Canadian KLEMS data has been sent to EU KLEMS and to be released soon.

5 Outline for the remainder of the talk u An overview of the KLEMS database at Statistics Canada u The findings from the KLEMS database at Statistics Canada. –Sources of aggregate productivity growth in Canada, and –Canada-US. comparison of productivity growth. u The preliminary findings from the Canadian KLEMS data that was sent to EU KLEMS.

6 The KLEMS database and MFP at Statistics Canada u Statistics Canada produces productivity statistics as part of a regular production program. –It is not something done as in some other countries, as an occasional research exercise. u The production process for the Canadian Productivity Accounts is embedded within the System of National Accounts. –The Canadian Productivity Accounts play an important role as an integrator of data from different sources within the agency.

7 Importance of the KLEMS database and MFP measures u MFP measures in the database are often used to assess the rate of technological progress. u The database was developed to examine the sources of output growth: the contributions of capital, labour and the residual MFP. u The database is used to examine the sources of labour productivity growth: investment and capital deepening, education and labour compositional changes, and the residual MFP and technical progress. u The industry database allows us to identify the industry origins of economic and productivity growth in the aggregate business sector.

8 Output and intermediate input measures for the KLEMS database u Output is valued at basic prices, and intermediate inputs are valued at purchaser prices. u We have produced three measures of MFP based on three different output measures: gross output, sectoral output and value added. u The data sources for output measures at the industry level are the annual input/output tables.

9 Labour Input for the KLEMS database u The labour input takes into account the effect of compositional changes of hours worked by education, experience, and the class of workers. u Labour input = hours worked * labour composition

10 Labour composition u Various household surveys are used for estimating labour composition: –Census of Populations; –Labour Force Survey (LFS); –Survey of Labour and Income Dynamics (SLID); and –Survey of Consumer Finance (SCF).

11 Capital input for the KLEMS database u The capital input takes into account the effect of compositional changes of different types of capital assets. u Estimates of aggregate capital services for the business sector are constructed using the “bottom-up approach” involving –estimation of capital stock; –aggregation of capital stock of various asset types within each industry to estimate industry capital services; and –aggregation of capital services across industries to derive capital services in the business sector.

12 User cost of capital services u The user cost of capital approach for estimating capital services in Canada has the following features: –Endogenous rate of return specification (vs. exogenous rate of return) –Takes into account a large number of tax parameters in Canada

13 u Findings from the KLEMS database at Statistics Canada

14 Substantial changes in the structure of capital u There has been a long-term shift towards M&E and away from structures, land and inventories in the business sector. u In the M&E category, investment in information and communications technologies (ICTs) have increased most rapidly.

15 Substantial changes in the composition of labour u There have also been dramatic changes in the educational characteristics of the labour force. –The proportion of workers with only a high school education has declined steadily, while the percentage with postsecondary degrees has risen.

16 Sources of labour productivity growth u Over the period , annual labour productivity growth was 2.0%. –Capital deepening: 50% of the labour productivity growth. –Labour compositional changes: a quarter of labour productivity growth in the business sector. –MFP: the remaining quarter of labour productivity growth.

17 The importance of ICT for labour productivity growth u During the 1960s and early 1970s, ICTs accounted for only a small portion of the contribution that the growth in capital services made to the growth in labour productivity. u However, during the 1990s and into the new millennium, ICTs accounted for most of the total contribution of capital to labour productivity growth.

18 Industry sources of aggregate productivity growth u The manufacturing sector was the most important contributor to aggregate productivity growth. u A number of services sectors, such as wholesale and retail trade industries, and information and communication industries also experienced rapid productivity growth.

19 Canada-US comparisons of productivity growth based on data from Statistics Canada and the BLS u Over , labour productivity in the two countries grew at about the same rate. –But Canadian growth exceeded that of the United States up to the early 1980s. –Since then U.S. labour productivity growth has exceeded Canadian growth. The gap has widened particularly after 2000.

20 Canada-US comparisons of productivity growth based on data from Statistics Canada and the BLS u The sources of labour productivity growth in the two countries differ. –Investment and skill upgrading are more important sources in Canada. –MFP growth (the residual often referred to as technological progress) was larger in the United States. u The lower relative labour productivity growth in Canada in recent years is mostly due to slower MFP growth. Investment played a minor role.

21 u The preliminary findings from the Canadian KLEMS data that was sent to EU KLEMS

22 Differences in methodologies between EU and Canada KLEMS u Difference in capital input estimates –Asset details that are used for calculating capital services differ between the two databases. 11 asset in EU KLEMS and 30 assets in Canadian KLEMS. –Land and inventories are not included in EU KLEMS, but included in Can KLEMS. –The depreciation rates differ in the two databases. Depreciation rates are higher in the Canadian KLEMS database, especially for structures. u Differences in labour input estimates –The number of workers types differ: 18 types of workers in EU KLEMS, 56 types of workers in Canadian KLEMS u Differences in industry coverage –Total economy vs. business sector

23 The history of Canadian productivity growth based on the Canadian data sent to EU KLEMS u The Canadian data sent to the EU KLEMS show a similar history of labour and multifactor productivity growth for Canada as the data in the Canadian KLEMS at Statistics Canada to to 2004 The Canadian market sector, EU KLEMS Labour productivity Real GDP Hours worked Multifactor productivity The Canadian business sector, CANSIM Labour productivity Real GDP Hours worked Multifactor productivity

24 Canada-US comparisons of market-sector productivity growth, based on data in EU KLEMS U.S. Canada GDP growth Contribution of labour input Contribution of capital input Contribution of ICT capital Contribution of non-ICT capital TFP growth Labour productivity growth

25 Canada-US comparisons of productivity growth based on data in EU KLEMS u The Canadian and U.S. data in EU KLEMS show similar relative productivity performance in the two countries as the official data from the statistical agencies in the two countries. –labour productivity growth in the Canadian market sector was lower than that in the U.S. after 1981, and –much of the difference was due to slower TFP growth in Canada

26 The industry sources of Canada-US productivity growth differences, u Canada had slower TFP growth in 18 out of the 30 industries in the EU KLEMS for the period 1981 to –The largest difference is in the electrical and optical equipment manufacturing. u Canada had slower labour productivity growth in 18 out of the 31 industries in the EU KLEMS for the period. u A lot more to be learned from EU KLEMS on how Canadian productivity performance is compared to that of the U.S. and EU countries.

27 u A lot more will be learned from the EU KLEMS on how Canadian productivity performance is compared to that of the U.S. and EU countries.