Agency, 90 Tottenham Court road, London W1P 9HE (Fax:+44 171 436 .... 3 In a limited number of cases the GGDC database also provides estimates of capital stock. ... Even in advanced countries, adjustments for the underground economy ...... Labour productivity and unit labour cost, total economy, 1960-1977, 1990, US$.
EMPLOYMENT PAPER 2000/5
Productivity and unit labour cost comparisons: a data base
Bart van Ark Erik Monnikhof
Employment Sector International Labour Office Geneva
Copyright © International Labour Organization 2000
ISBN 92-2-112176-3
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Contents Foreword..........................................................................................................................................1 1. Introduction.................................................................................................................................1 2. Measures of output, labour inputs and labour compensation.......................................................2 3. Currency conversion factors ........................................................................................................8 4. Groningen Growth and Development Centre DataBase ............................................................13 5. Some comparisons of productivity and unit labour cost............................................................14 6. Research agenda ........................................................................................................................21 Appendix I .....................................................................................................................................22 References......................................................................................................................................31
Foreword In 1997, a collaborative effort involving the ILO, experts from the Organisation for Economic Cooperation and Development (OECD) and several national statistical offices was undertaken to complete the selection and refinement of indicators for a 1999 Key Indicators of the Labour Market (KILM) project. The KILM project was designed with two objectives: (1) to develop a set of labour market indicators; and (2) to widen the availability of the indicators to monitor new employment trends so as to arm policy-makers with the proper tools for decision-making in labour market policies. The indicators were chosen based on three criteria: conceptual relevance, data availability and comparability across countries and regions. The resulting set of 18 indicators was designed to satisfy the ever-increasing demands of governments and the social partners for timely, accurate and accessible information on the world’s labour markets. One measure that generates continual interest world-wide is the measure of labour productivity. Economic growth in a country or a sector can be linked either to increased employment or to more effective work of those who are employed, the latter of which can be captured in the measurement of labour productivity. The understanding of what drives labour productivity, be it the accumulation of machinery, improvements in physical and institutional infrastructures, streamlining of human capital, the generation of new technologies, etc., is important for formulating policies to support economic growth. The obvious first criterion of policy formulation, however, is accurate and comparable data. The KILM database includes data series for both labour productivity and unit labour costs. The second measure, unit labour costs, represents a direct link between productivity and the cost of labour used in generating output. This paper, prepared by researchers of the Groningen Growth and Development Centre at the University of Groningen in the Netherlands, presents the background information on data sources and methodologies used for the KILM measures. Some discussion focussed on the data estimates for the 31 countries included in the total economy series and the 23 countries included in the manufacturing series. Finally, the paper sets out the research agenda for future work on KILM productivity measures.
Werner Sengenberger Director Employment Strategy Department
1. Introduction This paper presents background information on data sources and methodologies on measures of labour productivity and unit labour cost, as presented in Chapter 6 of the Key Indicators of the Labour Market (KILM) database of the International Labour Office as KILM 17.1 The KILM database is meant to provide timely and accurate information on labour markets developments across the world. The first KILM publication covers labour market indicators, including labour force participation rates, unemployment, working hours, educational attainment, wages and productivity for a wide range of countries since 1980. A separate CD-ROM was released with data for intermediate years and underlying basic data. The KILM database will be updated on a regular basis through the KILM website and future publications.2 The two major variables in KILM 17 are labour productivity and unit labour cost. The estimates include 31 countries for the total economy (see Table 1) and 23 countries for manufacturing (see Table 2). The measures mostly cover the period 1980-1997, even though in some cases date only run to 1995 or 1996. Labour productivity is defined as the gross domestic product or value added per person employed or, when data on working hours were available, per hour worked. The measures are provided as indices (based on 1980=100) which only measures changes from the reference year, but in most cases also in US dollars. The US dollarbased estimates of labour productivity are obtained on the basis of purchasing power parities for the total economy and unit value ratios for manufacturing. Labour cost per unit of output (in short, unit labour cost) is defined as nominal labour compensation divided by real value added. Total labour compensation includes wage compensation and other labour costs such as employers’ contributions to social security and pension schemes and labour cost of the selfemployed. Unit labour costs are provided as indices (based on 1980=100) and in US dollars. In the latter case labour compensation is converted to US dollars on the basis of the official market exchange rates. The actual construction of the output, labour input and compensation measures and the way these are combined into our key measures of labour productivity and unit labour cost is discussed in more detail in Section 2. A unique feature of KILM 17 is that the indicators are provided not only in terms of indices but also as levels expressed in US dollars. This adds substantially to the usefulness of these indicators for international comparisons. The labour productivity measure in US dollars is corrected for differences in relative prices between countries using purchasing power parities (for the total economy) or unit value ratios (for manufacturing). Section 3 deals specifically with the estimates of purchasing power parities and unit value ratios. Section 4 of the paper gives a brief discussion of the underlying data sources for KILM 17. Data are largely derived from the Groningen Growth and Development Centre (GGDC) Database, which contains internationally comparable information on growth and levels of output, population and labour input.3 In addition the GGDC Database employs the purchasing power parities and unit value ratios to convert output to a common currency. For KILM 17, we separately developed measures of total labour compensation, mostly derived from national
1
ILO (1999), Key Indicators of the Labour Market 1999, Chapter 6: Labour productivity and unit labour costs indicator, Geneva. 2
The KILM website is located at http://www.ilo.org/kilm.
3
In a limited number of cases the GGDC database also provides estimates of capital stock. The GGDC database is regularly updated and extended and can be consulted at: http://www.eco.rug.nl/ggdc/homeggdc.html
2
accounts, which are consistent with the output and labour input data from the GGDC Database.4 Sources are provided on a country-by-country basis in the Appendix of this paper. Finally, in Section 5 we discuss some of the results on labour productivity and unit labour cost. In the concluding section we set the research agenda for future work on KILM 17.
2. Measures of output, labour inputs and labour compensation Chart 1 provides an overview of the major inputs to obtain internationally comparable measures of labour productivity and unit labour cost. The variables in the grey-shaded boxes are derived from the other variables that in turn are obtained from sources described below and in the appendix. The key variables that are briefly discussed here are output, labour inputs and labour compensation. Output is defined as “gross value added” (or, in national accounts terms, “gross domestic product”), which is the total domestic production value minus the value of purchased intermediate inputs. These variables are primarily obtained from national accounts statistics which are calculated according to a common conceptual framework, the System of National Accounts. The extent to which this can compensate for differences in the nature and quality of available statistics, in particular for developing countries, is unclear. In particular, international comparisons of real GDP have become more troublesome during recent years. Firstly, as the share of services in output has increased, distinguishing between price and quantity components of the value of output has become increasingly difficult. This is partly because of the lack of primary statistics for services, such as censuses and price surveys. In addition, it is conceptually more difficult to define the quantity of a particular service delivered than the quantity of a tangible good (Griliches, 1992). This problem of increasing proportions of poorly measured services is common to all countries. It is of particular concern in international comparisons because individual countries tend to follow their own procedures in estimating services output. Moreover, because the shares of services vary across national economies, the impact of the problem is not uniform. A second problem is that the weighting systems used to aggregate individual goods and services into GDP measures at constant prices are not fully harmonized. Several advanced countries - including, most recently, the United States - are now producing annually chained series for GDP. Because this procedure relies on very recent component weights, it is preferred for statistical as well theoretical reasons. On the other hand, there are still a substantial number of countries that use 5- or even 10-year base weights in developing their national accounts. These differences strongly affect the comparability of the time series of real GDP, as longer base periods lead to an overstatement of growth rates when (as is usual) observations for the first year of the period are used as GDP component weights. A third problem, one that becomes particularly important when low-income countries are included in the analysis, is undercoverage of output measures due to neglect of large parts of the informal economy. Even in advanced countries, adjustments for the underground economy can differ substantially, and the effect on GDP estimates can be as much as 15 to 20 per cent. (Maddison, 1996).
4
For an earlier study of unit labour cost comparisons using this type of data for the G-5 (France, Germany, Japan, the United Kingdom vis-à-vis the United States), see van Ark (1995, 1996).
3
Chart 1 - Stylized Structure of Data Base for Comparisons of Labour Productivity and Unit Labour Cost Imputed Total Labour Compensation per Unit of Gross Value Added in US Dollars Gross Value Added per Employee-Hour
Annual Hours per Employee
Gross Value Added per Employee
Employees (wage and salary earners)
Employee Compensation per Unit of Gross Value Added in US Dollars
Gross Value Added in US dollars (constant prices) Gross Value Added per Person Employed
All persons Employed
Gross Value Added per Person Employed-Hour
Annual Hours per Person Employed
Purchasing Power Parity
Gross Value Added in National Currency (constant prices)
Total Employee Compensation in US Dollars
Exchange Rates
Total Employee Compensation in National Currency
Employee Compensation per Unit of Gross Value Added in National Currency Imputed Total Labour Compensation per Unit of Gross Value Added in National Currency
Note: Unshaded boxes are basic variables; shaded boxes are derivatives.
4
The estimates in this paper are still based on guidelines laid down in the old United Nations System of National Accounts (SNA) of 1968. Since 1999 many countries have begun to apply guidelines from the new 1993 System of National Accounts. The new SNA implies substantial changes, including strong recommendations to switch to chain-linked volume series, the introduction of a broader concept on investment, including expenditure on software, changes in the treatment of taxes and subsidies, and increased coverage of the “grey” economy. However, countries are still at different stages in implementing the 1993 SNA. In some cases the introduction of the 1993 SNA has caused very substantial adjustments to GDP levels in OECD countries, ranging from between 0.3 per cent for Belgium to 7.4 per cent for the Republic of Korea (OECD, 1999 and 2000). The impact on growth rates is still unclear as the periods over which the changes have been implemented differ across countries, with most countries, not going further back than the late 1980s. Many non-OECD countries have not yet implemented the SNA 1993 guidelines at all. Labour input in KILM 17 refers to the number of persons employed and where possible also to annual working hours. Estimates of employment are for the average number of persons with one or more paid jobs during the year. Unfortunately, even conceptually, labour accounts are not as well harmonized as are national accounts, although a small number of countries provide employment estimates within the national accounts framework. For most countries employment estimates are derived from labour force or population surveys. Using these sources in combination with those from the national accounts assumes that the same population of establishments is covered in both countries. With an adjustment for self-employed persons, which may introduce part of the “grey” economy into the labour measures, this assumption may not hold, in particular not for developing countries. Comprehensive estimates of annual working hours are difficult to obtain and their international comparability is limited. For example, hours often refer to paid hours rather than hours actually worked. For a small number of countries in KILM 17, including Canada, the United Kingdom and the United States, estimates of hours actually worked (as opposed to hours paid) could be directly obtained on the basis of labour force survey information. However, the international comparability of these estimates is questionable. For most other countries we therefore made use of some variant of the “component method” to arrive at hours actually worked.5 This method begins with a measure of paid hours or “usual” hours, which is supplemented with estimates of “unusual” working hours (such as overtime) and various types of hours not worked, including vacation and holidays, absences due to sickness and part-time work. Estimates for use with the component method generally are obtained by combining information on paid employee hours from establishment surveys and information on working hours of self-employed and unpaid family workers from labour force surveys. We followed Maddison (1980, 1991) by using as much as possible hours estimates based on the component method. This has particularly large consequences for the estimates of annual working hours in the United States, for which our estimate of 1,615 hours per person employed in 1996, which is updated from Maddison’s 1992-estimate of 1,589 hours (Maddison, 1995), is about 340 hours below the US estimate reported by OECD (1998), and which is derived from the Current Population Survey in the United States (and subsequently reproduced in KILM 6. Hours of work). This large difference requires further investigation, but for this moment we use the lower “component method” estimate because of its greater international comparability.6
5
See, for example, OECD (1998, p. 185) for OECD countries. See Maddison (1980) and van Ark (1993) for a detailed description of this method. 6
For further discussion, see van Ark and McGuckin (1999)
5
As Chart 1 shows the measures of output and labour input in principle provide us with four possible measures of labour productivity, namely gross value added per person employed (in 1990 US $), per hour worked (in 1990 US $), per person employed (1980 = 100), and per hour worked (1980 = 100). In practice we were mostly able to obtain measures of value added per hour worked, although in some cases no measure of working hours could be obtained for manufacturing. In other cases, in particular for non-OECD countries, the measure of working hours mostly only covers employees. In those cases we often assumed working hours per employee were representative for those of a self-employed person, so that we could still provide a measure of gross value added per person-employed hour. Total labour compensation is also derived from national accounts statistics. The advantage of using the national accounts is that the definition of compensation is the most comprehensive. It is meant to include not only gross wages and salaries of employees, but also labour costs paid by employers. However, national accounts measures of labour costs refer to employee compensation only, and therefore do not include the compensation of self-employed persons which is by definition part of other income, including income on capital, etc. Hence, as Chart 1 shows the unit labour cost measure is in first instance expressed as employee compensation per unit of output. To obtain a measure of total labour compensation per unit of output, we needed to impute the labour income for self-employed persons assuming the same labour compensation per employee and per self-employed person. The latter estimate could be obtained when measures of employees as well as total persons employed were available. In contrast to the productivity measures, the labour compensation measures were expressed in current prices and not adjusted for relative price differences between country. As a result the unit labour cost measure is constructed from a numerator (labour compensation) in nominal terms and a denominator (output) in real terms. This apparent contrast can be understood when interpreting the unit labour cost measure as an indicator of cost competitiveness. It then adequately represents the current cost of labour per “quantity unit” of output produced. Similarly for comparisons across countries, labour compensation was converted to US dollars on the basis of exchange rates. For this purpose the unit labour cost equation can be written as the ratio of nominal labour compensation per hour worked and real labour productivity per hour worked: ULC
X (U )
X(X) / ER XU LCH = X(X) / PPP XU OH
(1)
where ERXU is the exchange rate between country X and the United States, PPPXU is the purchasing power parity (or unit value ratio) between country X and the United States, LCHX(X) are the labour cost per hour in country X in prices of X and OHX(X) is output (value added) per hour in country X in prices of country X. Equation (1) can be rewritten to decompose the difference in unit labour cost between country X and country U into three components, i.e., the difference in nominal labour cost per person, the difference in nominal labour productivity (that is unadjusted for differences in price levels) and the differences in relative price levels: X
log( ULCX(U) - ULCU ) = log(
X
LCH OH - LCHU ) - log( XU - OHU ) - log( ERXU - PPPXU ) XU ER ER
(2)
All these three measures contribute in their own way to differences in cost competitiveness between the two countries. The measure of PPPs and unit value ratios are discussed in more detail in the next section. Tables 1 and 2 show the availability of the underlying data on output in US dollars, labour input (persons employed or working hours) and labour compensation for the countries
6
included in KILM 17. In most cases the key variables were available to calculate output per hour worked in US$ and total labour compensation per unit of output in US$ were available. However, in a limited number of cases we had to rely on alternative measures. For example, for some countries (Philippines, Brazil, Chile, Colombia and Venezuela) only labour compensation for employees could be obtained and no adjustment to total labour compensation was possible. Secondly, in some cases (Austria, Denmark, Greece, Portugal, Philippines, Thailand and Mexico) manufacturing value added could not be converted to US dollars due to a lack of a currency conversion factor, so that we can only provide estimates on productivity and unit labour cost on the basis of national currency estimates. Finally, for the manufacturing estimates of Korea, Taiwan-China, Philippines and Mexico and for the total economy-estimate of Hong Kong-China, a wage index instead of full compensation was used. This latter type of measure is less useful for the purpose of constructing unit labour cost estimates than the figures based on compensation obtained from national accounts for several reasons. Firstly, wage or earnings indices do not cover all labour cost, as these exclude employers’ contributions. Secondly, these indices often refer to particular types of workers or particular economic activities. In particular, the agricultural sector is usually not covered by wage statistics. For this reason, this proxy measure is usually not applied beyond the manufacturing sector.7
7
As an exception, a proxy wage measure was also used for the total economy in the case of Hong Kong, China, given the negligible size of its agricultural sector.
7
Table 1: Country
Availability of underlying data for KILM 17 (1999), total economy GDP in Persons Hours per Total labour Employee Wage 1990 US$ employed person compensation compensation index employed in US$ in US$ Major Europe Austria X X X X Belgium X X X X Denmark X X X X Finland X X X X France X X X X Germany (West) X X X X Greece X X X X Ireland X X X X Italy X X X X Netherlands X X X X Portugal X X X X Spain X X X X Sweden X X X X United Kingdom X X X X Major non-Europe Australia X X X X Canada X X X X Japan X X X X United States X X X X Asia and the Pacific Eastern Asia Hong Kong, X X X X China Korea, Republic X X X X of Taiwan, China X X X South-central Asia India X X Sri Lanka X X South-eastern Asia Indonesia X X Philippines X X X Thailand X X Latin America and The Caribbean Brazil X X X X Chile X X X X Colombia X X X X Mexico X X X X Venezuela X X X X Source: See ILO ( 1999), table 17a)
8
Table 2 – Availability of underlying data for KILM 17 (1999), manufacturing Country
GDP in 1990 US$
Major Europe Austria Belgium X Denmark Finland X France X Germany (West) X Greece Netherlands X Portugal Spain X Sweden X United Kingdom X Major non-Europe Australia X Canada X Japan X United States X Asia and the Pacific Eastern Asia Korea, Republic of X Taiwan, China X South-central Asia India X South-eastern Asia Indonesia X Philippines Thailand Latin America and the Caribbean Mexico See ILO (1999), table 17b
Persons employed
X X X X X X X X X X X X
Hours per person employed
Total labour compensation in US$
X X X X
X X X X X
X
X
GDP in own currency (constant prices)
Wage index
X X
X X X X
X X
X X X X
X X X X
X X X X
X X
X X
X
X X
X X X X
X X
X
X
X
X
3. Currency conversion factors Much of the work on international comparisons is based on comparisons of growth rates across countries. This reduces measurement errors from methodological differences between countries because many of these errors remain relatively constant over time and therefore drop out when the growth rate is calculated.8 An important element of the work for KILM 17 is the use of currency conversion factors to express all indicators in US dollars. In this way comparisons can be made not only over time but also across space. For output comparisons, use of market exchange rates does not take account of differences in relative price levels across countries. Hence the use of purchasing power-adjusted exchange rates is a fundamental component of the level comparisons pursued for this project. Purchasing power parities (PPPs) are the amount of a country’s currency that is required to purchase a standard set of goods and services worth one unit of the currency of another (base) country. When converting output measured in one currency into the currency of another country, PPPs take account of the price differences between the countries. 8
Maddison (1996) suggests that over the past 40 to 50 years differences between growth measures of OECD countries are due to non-comparability of the measure and “…less than 0.2% a year should probably not be regarded as significant.” p. 30.
9
For comparisons of total economy output, purchasing power parities for GDP can be used. The use of purchasing power parities has a long history going back to work done at the OECD during the 1950s (Gilbert and Kravis, 1954; Gilbert and Associates, 1958). Since 1975, the construction of PPPs has been a regular aspect of the statistical programs of international agencies such as Eurostat, OECD, the United Nations and the World Bank.9 PPPs are estimated for 251 expenditure categories and aggregated to total GDP. An important feature of the PPP estimates since the 1970s is that the aggregation procedures are such that multilateral comparisons between groups of countries can be made. Hence the results are transitive, so that, for example, a comparison of the US/Germany PPP with the Germany/France PPP gives the same result as the U.S/France PPP. For European countries, purchasing power parities are now estimated on an annual basis, and for the non-European OECD countries estimates are provided on a three-year basis (1990, 1993, 1996, etc.).10 For non-OECD countries, benchmark estimates are provided on a more irregular basis. For most Asian countries, PPP estimates can be obtained for 1975 (from Kravis, Heston and Summer, 1982), 1980 (from United Nations, 1986) and 1985 (from United Nations, 1994), whereas for Latin American countries the 1975-round was the latest from which PPP estimates can be obtained. Maddison implicitly obtained 1990 PPPs by updating the GDP in US$ for the benchmark year to 1990 using the real GDP trend in the given country and the GDP deflator for the United States: GDPX(U)90 = GDPX(U)t * REALGDPX90/t * DEFLU90/t
(3)
where GDPX(U)t represents GDP of country X in US dollars in year t, REALGDPX90/t represents the real GDP index of country X between year t and 1990, and DEFLU90/t the GDP deflator of the United States between year t and 1990. By dividing 1990 GDP in US dollars through the 1990 GDP in national currencies of country, the implicit 1990 PPP is obtained. For KILM 17 we applied Maddison’s 1990 PPPs for total GDP that made it possible to cover the widest possible sample of countries in a consistent way for a most recent year.11 The total economy PPPs are all aggregated using the Geary-Khamis method. This implies that purchasing power parities are simultaneously developed with so-called international prices. The Geary-Khamis PPPs give weights to countries according to their size measured in terms of gross national product (GNP). For example, in application of this method, the GDP of the United States counts for approximately 5 times as much in the determination of international prices as that of India and about 7.5 times as much as that of Brazil.12 (See table 3)
9
See, for example, Kravis, Heston and Summers (1982), Eurostat (1983, 1988), OECD (1996, 1999), United Nations (1986, 1994). 10
The latest PPP estimates for OECD countries are now benchmarked on 1996 (OECD, 1999). See the GGDC website for regular updates of GDP estimates on the basis of the latest PPP estimates (http://www.eco.rug.nl/ggdcc/homeggdc.html). van Ark and McGuckin (1999) provide comparisons of PPPadjusted estimates of per capita income and labour productivity for OECD and non-OECD countries. 11
See Heston and Summers (1991) for a review of the PPP-adjusted estimates of the Penn World Tables, which are converted at 1985 PPPs. 12
An alternative method that is nowadays mostly used in the OECD countries aggregates PPPs on the basis of the EKS (Eltetö, Köves and Sculz) method. EKS PPPs are basically geometric averages of binary PPPs (which are not individually transitive). This means that they represent averages that do not account for differences in country size. For a review of PPP methods, see Hill (1982). For updates, recent development and references to
10
PPP estimates have been criticized for many reasons, as set out in recent reports by Castles (1997) and Ryten (1999). Indeed the precise nature of the price surveys can differ across countries. The pricing procedures have been criticized for lack of comparability and reflection of the specified items between countries. Furthermore, the multilateral character of the estimates is affected by the fact that the PPPs are, in fact, estimated for six different regions, which are “globalized” with particular interregional (binary) links. Finally, within each of the regions the aggregation procedures of the PPPs differ. For example, within the European Union, country PPPs are unweighted for size of GDP, whereas the PPPs for non-European OECD countries are combined with those for the European Union by weighting for size of GDP. For manufacturing, appropriate currency conversion factors are more difficult to obtain than for the total economy, as there are no specific international surveys of producer prices. For a limited number of countries in Europe, North America and Asia, measures of manufacturing unit value ratios are obtained on the basis of industry of origin method by the ICOP (International Comparisons of Output and Productivity) research group at the Groningen Growth and Development Centre (GGDC) at the University of Groningen.13 With this method, industry-specific purchasing power parities are obtained from ratios of unit values. The unit values represent sales values divided by quantities for similar products or product groups, derived from national production censuses or industry surveys, which are matched between countries. The unit value ratios are weighted at product and industry output values and then used to convert manufacturing output to US dollars. In contrast to the total economy PPPs the unit value ratios for manufacturing are of a bilateral nature. The ICOP project now covers about 30 countries in Asia, East and West Europe, and North and South America. Comparisons of manufacturing output and productivity are disaggregated into 16 manufacturing branches and are available for almost all of these countries.14 The manufacturing unit value ratios (UVRs) used for KILM 17 were obtained for 1987 and updated to 1990 on the basis of the ratio of the 1990/1987 deflators of each country relative to the United States (see table 3). With the exception of Spain and the United Kingdom, the differences between the total economy PPPs and the manufacturing UVRs are rather small for the OECD economies. However, for the non-OECD countries, manufacturing UVRs are substantially higher than those for the total economy, confirming the stylized fact that relative prices of non-manufacturing goods are much lower than those of manufactured goods in low-income countries.
methodological studies, see the (http://www.oecd.org/std/ppp/pps.htm).
OECD
website
on
purchasing
power
parities
13
An earlier pioneering industry-of-origin study of comparative output and productivity is Paige and Bombach (1959). 14
In addition, ICOP estimates are available for agriculture and (for a limited number of countries) for particular service sectors. See the ICOP website at http://www.eco.rug.nl/ggdc/icop.html, which also includes a list of ICOP and ICOP-related publications and reports since 1983.
11
Table 3. Purchasing power parities for total economy unit value ratios for manufacturing, national currency to US dollar, 1990. Purchasing Power Unit Value Ratio Parity (1990) (1990) Major Europe Austria Belgium Denmark Finland France Germany (West) Greece Ireland Italy Netherlands Portugal Spain Sweden United Kingdom Major non-Europe Australia Canada Japan United States Asia and the Pacific Eastern Asia Hong Kong, China Korea, Republic of Taiwan, China South-central Asia India Sri Lanka South-eastern Asia Indonesia Philippines Thailand Latin America and the Caribbean Brazil Chile Colombia Mexico Venezuela
13.90 38.36 8.70 6.22 6.45 2.05 129.55 0.688 1384 2.08 91.7 105.7 8.98 0.587
Exchange Rate (1990)
139.0 8.39 0.720
11.37 33.42 6.19 3.82 5.45 1.62 158.51 0.605 1198 1.82 142.6 101.9 5.92 0.563
1.35 1.27 185.3 1.00
1.51 1.29 152.8 1.00
1.28 1.17 144.8 1.00
5.84 481.1 21.5
631.15 28.2
7.79 707.8 26.9
42.05 5.67 6.99 2.10
2.21
4.88 7.55
11.66
17.50 40.06
468 7.53 8.54
1599
1843 24.31 25.59
40.3 110.0 127.2 1.43 14.2
68.3 305.1 502.3 2.80 46.9
Source: Total economy PPPs for OECD countries are obtained from Maddison (1995), Table C-6. For nonOECD countries PPPs are implicitly obtained from updated GDP in US$ for earlier benchmark (see text and Maddison, 1995) and are kindly provided by Maddison. Manufacturing unit value ratios are from various ICOP studies: Belgium from Soete (1984); Finland and Sweden from Maliranta (1994); France from van Ark and Kouwenhoven (1994); Germany from van Ark and Pilat (1993); Netherlands from Kouwenhoven (1993); Spain/UK (1984) from van Ark (1995a), linked to UK/USA (1987) from van Ark (1992); Australia from Pilat, Rao and Shepherd (1993); Canada from de Jong (1996); Korea and Japan from Pilat (1994); India, Indonesia and Taiwan from Timmer (1999). In most cases the PPPs are updated to 1990 using manufacturing price deflators from national accounts.
12
The UVR-method for manufacturing faces three major problems that affect the comparability of the estimates across countries:15 1) Unit value ratios are based on a limited sample of items, and rather far-reaching assumptions are employed concerning their representativity for non-measured price relatives. For example, in manufacturing where the average percentage of output covered by unit value ratios is between 15 and 45 per cent, it is usually assumed that UVRs for matched items within a manufacturing branch are representative for nonmatched items. 2) Comparisons of unit values are affected by differences in product mix, because production censuses often include output values for product groups rather than for specified products. In international comparisons the problem aggravates because of the lack of a harmonized product coding system, so that items need to be further aggregated in order to obtain a correct match between countries. 3) UVRs need to be adjusted for differences in product quality across countries. This problem can be particularly serious for international comparisons, as the frequency of so-called "unique products" (which are products which are only observed in one case) is higher than for comparisons over time. It has been suggested that pricing of narrowly specified items, which is, for example, applied in the GDP PPP approach, is superior to the use of unit values and that expenditure PPPs should therefore also be used for industry of origin comparisons. In some cases, GDP PPPs have been applied to individual sectors or industries which assumes that differences in price levels are equal across industries.16 A more sophisticated method is to select expenditure PPPs for representative items that are allocated to specific industries. One problem with this so-called "proxy PPP method" is that it is based on market prices for final products. In a comparison between Japan and the United States, Jorgenson and Kuroda (1990) applied PPPs that were "peeled off" for indirect taxes and transport and trade margins. Hooper (1996) went a step further and adjusted the expenditure PPPs for import and export prices: "output PPPs" should of course include prices of exported goods but exclude those of imported goods. As Hooper acknowledges, the latter step is difficult and, in particular in open economies, might introduce a lot of noise in the estimates. The most important problem of the “proxy PPP” approach for industry of origin comparisons is that it does not cover intermediate products, which in manufacturing account for at least one third of output. Whichever concept of PPP or UVR is chosen, the main problem in industry of origin comparisons is that ideally one requires a currency conversion factor not only for output but also for inputs. Preferably industry productivity should be measured as gross output per unit of input. In contrast ICOP comparisons apply output-weighted unit value ratios to value added. This may be referred to as the “single deflation” method, which implicitly uses one and the same UVR for output and for intermediate inputs. The reason why this relatively simple method still has useful application in international comparisons is due to measurement problems related to the prices of intermediate inputs. Earlier attempts to change ICOP studies from “single deflation” to “double deflation” (i.e., deducting UVR-deflated intermediate inputs from UVR-deflated gross output) led to volatile results because the estimates were sensitive to the weights used in the index. Moreover, adequate measurement of the value and quantities of intermediate inputs
15
For more detail on how these problems are dealt with see van Ark (1993, 1996a). van Ark (1993) can also be downloaded in full from http://www.eco.rug.nl/ggdc/icop.html. 16
See, for example, Dollar and Wolff (1993).
13
requires larger coverage percentages for inputs than for output, as in one and the same industry the output is more homogeneous than inputs. In particular, when intermediate inputs make up a large part of gross output, small measurement errors show up strongly in the end results of value added (in the ICOP case) or in the contribution of intermediate inputs to gross output in case double deflation is applied. Hence the deflation problem is not any less serious in using the proxy PPP approach for productivity measures than in a "double deflation" procedure. In practice, therefore, the single deflation method still provides more robust results for international comparisons than the double deflation method when applied to either value added or to the separate estimation of intermediate input PPPs or UVRs.
4. Groningen Growth and Development Centre DataBase The data for KILM 17 are largely derived from the Groningen Growth and Development Centre (GGDC) Database at the University of Groningen (the Netherlands). The GGDC has long-standing expertise in development and analysis of data on productivity performance, in particular on comparisons of levels of productivity by sector and industry. The GGDC Database consists of three subsets of data, namely the GGDC Total Economy Database, the GGDC Sectoral Database and the ICOP Industry Database. All three databases have been used for KILM 17 with KILM 17 consisting of an additional measure of labour compensation to obtain unit labour cost.17 Real GDP and labour input data for the total economy are derived from the GGDC Total Economy Database. The GGDC Total Economy Database is strongly rooted in the work of Angus Maddison. For most countries movements in GDP and population before 1990, as well benchmark year estimates on employment and hours, are derived from Maddison (1995) as well as some of Maddison’s other publications. Maddison’s estimates of Geary-Khamis purchasing power parities for 1990 were used to convert output to US dollars.18 Maddison’s own series often go back well into the 19th century, so that one can link these historical series to the series presented in the GGDC Total Economy Database. Manufacturing output and labour input is taken from the GGDC Sectoral Database, which consists of series on real GDP in national currencies, employment and, in some cases, annual working hours for ten sectors of the economy and 20 countries in Asia and the OECD area from 1950 onwards.19 The unit value ratios are taken from the ICOP database which is described in more detail in the previous section. The basic sources used are best described by making a distinction between countries that are members of the OECD and those that are not.20 For OECD countries, indicated in KILM 17
17
Underlying data on KILM 17 from 1980 onwards can be derived from the KILM CD-ROM. Data further backwards to 1950 are available on the GGDC website: http://www.eco.rug.nl/ggdc/Dseries/dataseries.html. Both datasets are updated on a regular basis. 18
See the GGDC website (http:/www.eco.rug.nl/ggdc/Dseries/dataseries.html) for GDP estimates of OECD countries using more recent purchasing power parities, based on the benchmark year, 1993. 19
The ten sectors of the economy are: agriculture, mining, manufacturing, construction, public utilities, retail and wholesale trade, transport and communication, finance and business services, other market services and government services. See van Ark (1996b) for a description and discussion of OECD data. 20
A full overview of data sources is provided in appendix A.
14
in the “major Europe” and "major non-Europe" categories, value added and labour compensation is mostly obtained from the OECD, National Accounts, Volumes I and II (annual issues). Employment is mostly taken from OECD, Labour Force Statistics (annual issues). These data, originally obtained from national statistical offices and, where possible, harmonized for differences in concepts and industry classification, have been supplemented, where necessary, with national accounts and labour force statistics obtained directly from the individual countries. For some countries, the database of the US Bureau of Labour Statistics (BLS) was used, in particular on employment and on data for manufacturing.21 The estimates of working hours were obtained from various sources. Maddison (1995) provides benchmark estimates of annual working hours for most OECD countries and a significant number of nonOECD countries. These were complemented with movements on hours derived from the OECD Employment Outlook (annual issues) and the BLS database.22 For the non-OECD countries, the national accounts and labour statistics publications of individual countries were often taken as the point of departure. The statistics from these sources were supplemented with statistics from international organizations such as the World Bank, the Asian Development Bank, the United Nations Statistical Office and the International Labour Organization.23 Furthermore, estimates on GDP and employment from Maddison (1995) were used to obtain consistent benchmark estimates in 1990 US dollars. Where possible, labour compensation is obtained from the national accounts so that value added (GDP) and labour cost are compatible. However, the national accounts of many developing countries do not provide estimates of labour compensation. In a limited number of cases, a separate measure of unit labour costs is provided which is based on wage or earnings indices derived from the ILO Yearbook of Labour Statistics.
5. Some comparisons of productivity and unit labour cost24 The results on productivity and unit labour cost are presented in the 1999 Key Indicators fo the Labour Market for 1980 and 1990 to 1996 or 1997. The KILM CD-ROM provides data on an annual basis since 1980 as well as underlying data on output, labour input and labour compensation. It is also possible to link these data with those from the GGDC Database going back to 1960 for most non-OECD countries and to 1950 for many OECD countries. Table 4 provides the growth rates of labour productivity for the total economy and manufacturing back to 1960 divided into three sub-periods. The growth estimates show, amongst other things, the relatively rapid growth of labour productivity during the period 1960 21
BLS databases on Foreign labor statistics and Manufacturing unit labor cost can be accessed through http://stats.bls.gov/datahome.htm. 22
While it is not possible to fully assess which working hours estimates are “best,” the data produced by Maddison are largely based on the component method, as described in Section 2, and have been adjusted where possible to improve international comparability. However, a final judgment cannot be made before more detailed work in this field is carried out. For a more detailed assessment of the impact of working hours estimates on international comparisons of output and productivity, see van Ark and McGuckin (1999). 23
World Bank: World Development Indicators (various issues); Asian Development Bank: Key Indicators of Developing Asian and Pacific Countries (annual issues); United Nations: National Accounts Statistics (annual issues); and ILO: Yearbook of Labour Statistics (annual issues). 24
See also ILO (1999), Chapter 6.
15
to 1973, and the even more rapid productivity growth in manufacturing. This period is nowadays characterised as the “Golden Era” of the twentieth century. During these days many countries in the OECD league (in particular those in Europe and Japan) were realizing much of the “catch up” potential which arose following the two World Wars and were benefiting from rapid technological diffusion from the United States (Maddison, 1991; Crafts and Toniolo, 1996). The Japanese economy, which started from a relatively low level of productivity (see table 5) showed the fastest productivity growth, running into 2-digit annual growth rates for the period 1960 to 1973. The growth performance during this period was slower for most countries in Asia and Latin America. Most of these countries remained either relatively closed to international trade or faced unfavourable terms of trade, particularly when exports were dominated by primary products. In the present country sample only the Republic of Korea and Taiwan-China entered a phase of industrialization which was accompanied by productivity growth. Industrialization in these countries was characterized by a mix of export-orientation towards labour intensive goods accompanied by import substitution of more capital-intensive commodities. Between 1973 and 1987 growth in OECD countries slowed down substantially. In most cases the growth rates were half or even less that of the “Golden Era”. The breakdown of the international monetary arrangements of Bretton Woods, which had provided much stability to international macroeconomic relations during the 1950s and 1960s, and the oil crises of the 1970s, were responsible for part of the growth slowdown. However, the continued slowdown during the much of the 1980s must be attributed to underperformance of OECD economies because of orthodox economic policies characterized by tight monetary policies and large government budget cuts and a painful industrial restructuring with a large rise in unemployment. The period 1973 to 1987 is characterized by much diversity across the countries in Asia and Latin America. The Republic of Korea and Taiwan-China continued to show rapid productivity growth, and some Southeast Asian countries followed the same industrialization path. In contrast, Latin America was hit by one of the worst debt crises in their history, causing zero or negative growth in productivity for most of the 1980s. Since the mid 1980s growth performance of the OECD countries has been characterized by more diversity than before. Indeed the coefficient of variation (i.e., the standard deviation of the growth rates divided by the mean) of the labour productivity growth rates for the OECD countries increased from 0.34 for 1973 to 1987 to 0.41 for 1987 to 1997. Some countries such as Denmark, France, Ireland and Portugal have shown an accelerated productivity growth since 1987, but other countries such as Austria, France, the Netherlands, Spain, Sweden and the United Kingdom have experienced a substantive slowdown. There are indications of different success rates in structural reform policies that may account for varying success rates of these countries. Manufacturing productivity growth has mostly been faster during this period than for the total economy. One reason for this is probably the greater effect of new technologies on manufacturing productivity growth. The other reason is that the increasing share of service sector in the economies of OECD countries accounts for much of the slower growth at the total economy level. Both reasons also play a role in accounting for the relatively large growth differential between manufacturing and the total economy for the United States compared to OECD economies. Among the lower income countries, productivity growth rates remained high among East Asian countries and accelerated substantially in other Asian countries including India, Indonesia and Thailand. The performance among Latin American countries was much more mixed, partly depending on the success of structural market reforms since the 1980s and the degree of isolation from financial crises. Table 5 shows the relative levels of labour productivity and unit labour cost in 1980, 1987 and 1997 for the total economy. Productivity gaps narrowed among OECD countries, as the coefficient of variation declined from 0.225 in 1980 to 0.182 in 1997. Indeed most
16
countries improved labour productivity relative to the United States, in particular Finland, Ireland and the East Asian countries. In 1987, the United States was still the productivity leader, but by 1997 two countries in the present sample, France and the Netherlands, showed higher levels of output per hour than the United States in 1997. Some countries in Latin America (Mexico and Venezuela) experienced a widening of the productivity gap with the United States. In manufacturing, less productivity convergence among OECD countries took place (table 6).25 Some countries (Belgium and Finland) overtook the US productivity level in manufacturing by several percentage points, but others even showed some divergence (for example, Australia and Canada). East Asian industrializing countries, like Korea and Taiwan, showed considerable catching up to the US level of manufacturing productivity but still were at not more than one third of the US productivity level by 199726. The unit labour cost data, which are presented in the last columns of tables 5 and 6 show substantially more variation that the productivity estimates. This is due to the fact that the unit labour cost indicators are influenced by diverse factors like hourly compensation, productivity and the US dollar exchange rate. Except for the poorest OECD economies (for example, Greece and Portugal) and for Japan, unit labour costs levels were higher for most OECD countries relative to the United States. However, the unit labour cost gap relative to the United States was smallest in 1987, when the dollar-exchange rate was relatively high and therefore labour in other countries relative to US was cheap. For manufacturing, one of the most striking observations is the rapid rise in unit labour cost in Japan, from 70 per cent of the US level to over 120 per cent in 1996, which was also higher than in most European countries except Germany (West), Sweden and the United Kingdom. The high Japanese level of unit labour costs is related to the comparatively low productivity level for the total economy and the rapid appreciation of the yen since 1990.
25
This table substitutes for figures published in KILM 17b (ILO, 1999). For that publication manufacturing UVRs were accidentally updated to 1990 on the basis of the current value index of each country relative to the United States. In this table we correctly carried out the updating of the UVRs on the basis of the manufacturing deflator relative to the United States. In most cases this implied that the correct UVRs came out lower and therefore the relative productivity levels are higher than those published in ILO (1999). The corrected Table 17b is also shown in the appendix to this paper. 26
It should be emphasized that these estimates of relative productivity levels differ, in some cases, substantially from those directly be obtained for the ICOP Industry Database. This is due to the fact that the ICOP comparisons are originally based on output and employment information from production censuses or industrial surveys. These sources often provide more disaggregated information than the national accounts and ensure that output and input information are derived from the same primary source. However, production censuses and industrial surveys often provide no full coverage of all manufacturing activities, including those of the smallest firms (see, e.g., van Ark, 1993; Timmer, 1999). Another difference between the estimates of manufacturing productivity presented in KILM 17b and those in the ICOP Industry Database is that we updated the UVRs for KILM 17b to 1990, whereas they were left at the benchmark year in ICOP.
17
Table 4. Annual growth rates of labour productivity, total economy and manufacturing, 1960-1997
Country
Total economy GDP per person employed 1960- 1973- 19871973 1987 1997
Major Europe Austria Belgium Denmark Finland France Germany (West) Greece Ireland Italy Netherlands Portugal Spain Sweden United Kingdom Major non-Europe Australia Canada Japan United States Asia and the Pacific Eastern Asia Hong Kong, China Korea, Republic of Taiwan, China South-central Asia India Sri Lanka South-eastern Asia
GDP per person hour worked 1960- 1973- 19871973 1987 1997
19601973
5.2 4.3 3.4 4.7 4.3 4.0 6.6 5.0 5.8 3.2 6.5 8.0 3.5 2.8
1.8 2.0 1.3 2.0 2.1 1.8 1.6 3.0 2.2 1.2 0.9 3.0 1.1 1.7
1.4 1.9 1.9 2.7 1.4 2.0 1.2 4.0 2.2 1.1 1.8 1.5 2.2 1.3
2.3 2.5 8.1 2.3
1.4 0.9 2.7 0.7
1.7 0.8 1.9 1.1
1.5
4.7
3.8
(a)
4.1
(a)
4.8
5.3
5.1
(a)
5.6
(a)
6.6
5.2
5.0
(a)
6.1
(b)
2.0 0.3
1.6 3.6
4.0 3.8
(b) (b)
(a) (a)
(a)
(a)
(a)
Manufacturing Value added per person employed 1973- 198719601987 1997 1973
5.9 5.5 5.0 6.1 5.0 5.2 7.1 5.5 7.8 4.5 7.2 8.1 4.7 3.8
2.6 3.0 1.6 2.2 3.1 2.6 2.4 3.9 2.6 2.9 1.5 3.7 1.6 2.3
1.3 1.8 2.1 2.8 1.6 2.7 1.6 4.5 2.3 1.7 2.1 1.8 1.4 1.7
3.7 2.9 2.1 5.8 3.2 2.2 15.5
(b) (a) (a) (a) (b)
5.5 6.3 5.1
4.9 2.0 2.2
6.5 7.7 9.7 6.4 1.9
1.8 2.0 4.0 4.5 0.1
2.1 1.4 0.9 4.9 3.1
(a) (b) (a) (a) (a)
2.5 2.9 9.1 2.7
1.7 1.4 2.9 1.2
1.7 0.8 2.5 1.0
2.5 3.5 12.8 2.0
0.9 2.5 7.1 4.0
1.8 1.9 2.8 2.9
(a)
12.3
9.8
7.8
(a)
5.8
(a)
4.6
(b)
4.3
2.8
2.3
-1.9
Value added per person hour worked 1973- 19871987 1997
(a)
(a) (a)
6.9
5.4
2.8
5.3 6.2 5.8
4.3 3.5 2.6
3.2 3.2
(a) (a)
7.8
3.6
2.6
(a)
8.4 7.1 4.7
7.8 2.7 3.2
4.1 3.6
(a) (a)
3.2 4.8 11.3 3.6
2.8 1.9 4.5 2.4
1.4 1.8 4.1 2.7
(a)
6.3
8.6
(a)
6.3
(b)
2.4
3.8
(a) (a)
18
Indonesia 2.2 0.6 5.3 (b) 2.7 Philippines 2.3 0.2 0.6 (b) Thailand 4.8 3.1 7.9 (a) Latin America and the Caribbean Brazil 4.0 1.1 0.5 (a) 0.7 (a) 5.2 1.9 Chile 1.7 0.1 3.5 (a) 3.3 (a) Colombia 2.5 1.3 1.8 (a) 1.8 (a) Mexico 3.7 1.1 -3.1 -2.7 (a) 6.0 4.4 Venezuela 0.5 -1.8 -1.9 (a) -1.8 (a) (a) 1987-1996; (b) 1987-1995 Source: GGDC Total Economy Database, Sectoral Database and ICOP Industry Database. See Appendix for http://www.eco.rug.nl/ggdc/Dseries/dataseries.html.
3.9 0.9 4.3
3.2
(b) (b) (a)
(a)
3.1
1.5
4.2
-0.3
3.0
-0.1
1980-1997. Pre-1980 see source descriptions on
19
Table 5.
Labour productivity and unit labour cost, total economy, 1960-1977, 1990, US$ GDP per person employed
Country
1980
1987
1997
GDP per person hour worked 1980
1987
1997
Unit labour cost per unit of output 1980 1987 1996
Major Europe 32,154 34,866 40,020 23.00 25.70 28.90 0.478 0.644 0.938 Austria 36,849 40,737 49,187 22.70 25.00 29.90 0.622 0.644 0.954 Belgium 30,009 33,183 40,214 17.50 19.90 24.60 0.596 0.733 1.031 Denmark 25,719 30,314 39,722 14.50 18.20 24.00 0.573 0.784 0.919 Finland 36,850 42,194 47,958 22.20 27.40 32.20 0.570 0.627 0.858 France 35,073 38,458 46,100 20.30 23.20 30.30 0.567 0.674 0.938 Germany (West) 26,257 26,477 29,868 13.90 14.80 17.40 0.347 0.384 0.683 Greece 24,290 29,808 44,253 12.90 16.80 26.00 0.550 0.660 0.730 Ireland 30,200 33,038 41,010 19.00 21.60 27.10 0.419 0.591 0.736 Italy 35,276 37,725 41,453 22.30 27.20 32.20 0.586 0.609 0.805 Netherlands 20,123 21,852 26,203 11.00 12.50 15.40 0.266 0.297 0.490 Portugal 29,711 35,439 41,138 14.40 18.00 21.60 0.458 0.476 0.708 Spain 29,331 32,910 40,741 20.20 22.40 25.70 0.717 0.747 1.058 Sweden 29,166 34,747 38,890 18.30 22.30 26.40 0.478 0.499 0.712 United Kingdom Major non-Europe 32,283 35,582 42,263 19.90 21.80 25.70 0.498 0.487 0.689 Australia 35,361 39,142 42,384 20.50 23.40 25.30 0.415 0.509 0.623 Canada 27,666 33,256 39,434 13.80 16.50 21.20 0.523 0.882 1.225 Japan 41,034 44,610 49,905 25.50 27.70 30.70 0.453 0.601 0.776 United States Asia and the Pacific Eastern Asia 9.80 13.70 19.60 Hong Kong, 23,220 31,800 44,412 China 11,430 18,066 28,166 4.50 6.90 11.30 0.336 0.331 0.632 Korea, Republic of 15,176 21,499 33,438 5.90 8.50 13.70 Taiwan, China South-central Asia 2,638 3,156 4,325 India 7,223 8,441 11,384 Sri Lanka South-eastern Asia 5,350 5,266 7,961 Indonesia 7,364 5,910 6,192 Philippines 4,943 6,028 9,103 Thailand Latin America and the Caribbean 14,427 13,765 14,366 7.27 7.20 7.72 (a) (a) (a) Brazil 19,184 17,681 24,143 9.90 9.00 12.06 (a) (a) (a) Chile 13,476 14,711 17,232 6.50 7.40 8.73 (a) (a) (a) Colombia 17,099 18,096 13,169 8.34 8.80 6.88 0.500 0.186 0.350 Mexico 32,368 29,406 24,795 16.21 15.30 12.98 (a) (a) (a) Venezuela (a) Unit labour cost levels for these countries are only provided in terms of employee cost per unit of output and therefore are not comparable to the other figures, which represent total labour compensation per unit of output. Source: GGDC Total Economy Database. See Appendix.
20
Table 6. Labour productivity and unit labour cost, manufacturing, 1960-1996, 1990 US$ GDP per person employed
GDP per person hour worked
Unit labour cost per unit of output 1980 1987 1996
Country 1980 1987 1996 1980 1987 1996 Major Europe Belgium 30,581 41,657 55,600 20.1 27.7 36.5 0.83 0.71 0.84 Finland 24,353 34,491 57,430 14.1 20.4 35.2 0.60 0.70 0.70 France 33,373 38,407 50,926 19.5 23.8 31.5 0.64 0.71 0.85 Germany 33,680 36,577 44,471 19.6 22.3 29.4 0.62 0.78 1.14 (West) Netherlands 27,678 34,428 41,569 17.7 23.6 29.6 0.68 0.70 0.82 Spain 19,916 28,367 30,703 Sweden 25,283 32,054 49,398 17.6 21.5 30.9 0.82 0.79 0.93 United 17,793 25,718 33,753 10.3 14.6 20.1 0.84 0.81 0.96 Kingdom Major non-Europe Australia 26,109 30,842 36,070 13.6 15.8 18.0 0.63 0.57 0.85 Canada 30,469 37,524 45,428 16.0 19.4 23.1 0.51 0.59 0.67 Japan 32,613 43,668 56,127 15.0 19.9 28.5 0.40 0.62 0.84 United States 37,714 50,844 65,966 20.3 26.6 33.7 0.57 0.62 0.69 Asia and the Pacific Eastern Asia Korea, 8,994 14,436 28,437 3.3 5.2 10.9 0.32 0.33 0.45 Republic of Taiwan, China 11,644 16,764 27,850 4.4 6.7 10.9 South-central Asia India 1,675 2,333 3,342 South-eastern Asia Indonesia 2,233 3,358 4,547 Note: This table substitutes for figures published in KILM 17b (ILO, 1999). For that publication manufacturing UVRs were accidentally updated to 1990 on the basis of the current value index of each country relative to the United States. In this table we correctly carried out the updating of the UVRs on the basis of the manufacturing deflator relative to the United States. In most cases this implied that the correct UVRs came out lower and therefore the relative productivity levels are higher than those published in 1999 KILM. The corrected table 17b is also shown in the appendix to this paper. Source: GGDC Sectoral Database and ICOP Industry Database. See Appendix
Similar data on productivity and unit labour cost were recently made available by other scholars including the World Bank (1999) and Golub (1999). The World Development Indicators 1999 include wages and productivity measures for manufacturing for a wide range of countries. However, the measures are all converted to US dollars on the basis of the average exchange rate for each year (World Bank, 1999, Table 2.6). Golub (1999) provides productivity and unit labour cost data for a smaller set of 14 countries, including the G-5 (France, Germany, Japan, United Kingdom, United States), 7 major Asian countries (India, Indonesia, Korea, Malaysia, Philippines, Singapore and Thailand) and 2 Latin American countries (Chile and Mexico), most of which are also in KILM 17. Golub’s results largely confirm those of KILM 17. In particular, he emphasizes that relative levels of unit labour cost are much closer between countries than those of labour productivity and compensation separately, as differences in the relative levels of both indicators more or less offset each other. Despite similar outcomes, however, Golub’s dataset differs in many respects from KILM. Firstly, Golub’s estimates are only for manufacturing. Secondly, he does not provide estimates of output per hour worked but only output per person employed. Thirdly,
21
in converting manufacturing output, Golub makes use of purchasing power parity for producer durables obtained from the Penn World Tables (see Summers and Heston, 1991). Fourthly, Golub makes use of “real product wages” which are earnings deflated by the value-added deflator for manufacturing and converted to US dollar at the market exchange rate in the base year. This is, therefore, not exactly a nominal index as used in KILM. Finally, labour compensation, obtained from UNIDO, does not include employer contributions to social insurance.
6. Research agenda For future versions of the productivity and unit labour cost database for KILM, priority will be given to expanding the estimates to more countries than the current sample of 66 countries in the Groningen Growth and Development Database, of which 31 countries are included in KILM 17 so far. Estimates of total labour compensation and manufacturing unit value ratios are the current bottlenecks in extending the database. Secondly, presently research activity in this field focuses on extending estimates to service sectors of the economy. ICOP-type studies for services have been carried out by Pilat (1994) for Japan and Korea and by Mulder (1999) for Brazil and Mexico. Productivity level estimates for transport and communication and for wholesale and retail trade are compiled by van Ark, Monnikhof and Mulder (1999) for Canada, France, Germany, the Netherlands and the United States and are currently extended to another ten to 15 countries. Finally, estimation of total factor productivity growth and levels is also needed. Among other things this requires internationally consistent series of capital stock and capital flows and of human capital. Lack of reliable data in combination with the sensitivity of the procedures seriously limits the number of countries for which one can derive reliable estimates of the capital stock (Nehru and Dhareshwar, 1993). Many studies, in particular those that made use of cross-country regressions, have used investment-output ratios as a proxy for the change in the capital stock.27 Scholars that constructed capital stock estimates either reverted to wealth surveys that value the capital stock in place at user value or construct estimates based on the perpetual inventory method (PIM) which are obtained by cumulating investment data using assumptions concerning the life time of assets and the depreciation pattern. Such series are still available for a limited number of countries and need to be further extended.28 Moreover, for sectoral estimation of total factor productivity levels a detailed input-output framework is required to measure substitution effects between inputs and flows between sectors,29 as well as the adoption of a growth accounting framework. 27
This procedure assumes that marginal and average capital-output ratios are the same, which is a particularly unrealistic assumption for rapidly industrializing economies which are often characterised by relatively low capital-output ratios in combination with high rates of capital accumulation (Fukuda and Toya, 1999). 28
The PIM approach has been applied in two international datasets that aimed to include as many countries as possible, namely the World Bank dataset on physical capital (Nehru and Dhareshwar, 1993) and the Penn World Tables (Summers and Heston, 1991). The series from both datasets involve very substantial measurement problems, as the estimates are either based on indirect procedures, such as using investment/GDP ratios (Penn World Tables) or rough methods to derive a reliable benchmark estimates for the stock (World Bank dataset). Maddison (1995a) provided PIM estimates for six advanced countries, which is extended by O’Mahony (1996, 1999) for sectoral estimates. Timmer and van Ark (2000) provide comparable PIM estimates of the capital stock for Taiwan, China and the Republic of Korea. 29
See, for example, Jorgenson (1995).
22
Appendix I Detailed source descriptions The full reference is given only the first time it is mentioned.
Total Economy Data (KILM 17a) Austria: GDP in 1990 US$: 1980-1990 from A. Maddison (1995), Monitoring the World Economy, 1980-1992 (OECD Development Centre); 1991-1996 extrapolated from 1990 with GDP trend from OECD, National Accounts Vol. I; 1997 from OECD Online website. Persons employed: 1984-1994 from OECD, Labour Force Statistics; 1995-1997 extrapolated from 1990 with employment trend from OECD, Economic Outlook; 1980-1983 linearly interpolated between 1979 (from A. Maddison (1982), Phases of Capitalist Development, Oxford University Press) and 1984 figure. Hours worked: 1979 from Maddison (1982); 1987 from A. Maddison (1991), Dynamic Forces in Capitalist Development (Oxford University Press); 1992 from Maddison (1995); years in between are linearly interpolated; 1992-1997 kept constant at 1992 level. Labour compensation: 1980-1996 from OECD, National Accounts, Vol. I. Belgium: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1996 extrapolated from 1990 with GDP trend from OECD, National Accounts Vol. I; 1997 from OECD Online website). Persons employed: 1980-1993 from OECD, Labour Force Statistics; 1994-1997 extrapolated from 1993 with employment trend from OECD, Economic Outlook. Hours worked: 1979 from Maddison (1982); 1987 from Maddison (1991); 1990 from A. Maddison (1996), "Macroeconomic Accounts for European Countries", in B. van Ark and N.F.R. Crafts, eds., Quantitative Aspects of Postwar European Economic Growth (Cambridge University Press); 1992 from Maddison (1995); years in between are linearly interpolated; 1992-1997 kept constant at 1992 level. Labour compensation: 1980-1996 from OECD, National Accounts, Vol. I. Denmark: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1996 extrapolated from 1990 with GDP trend from OECD, National Accounts, Vol. I; 1997 from OECD Online website. Persons employed: 1980-1996 from OECD, Labour Force Statistics; 1997 extrapolated from 1996 with employment trend from OECD, Economic Outlook. Hours worked: 1979 from Maddison (1982); 1987 from Maddison (1991); 1990 from A. Maddison (1996); 1992 from Maddison (1995); years in between are linearly interpolated; 1992-1997 kept constant at 1992 level. Labour compensation: 1980-1996 from OECD, National Accounts, Vol. I. Finland: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1996 extrapolated from 1990 with GDP trend from OECD, National Accounts, Vol. I; 1997 from OECD Online website. Persons employed: 1980-1996 from OECD, Labour Force Statistics; 1997 extrapolated from 1996 with employment trend from OECD, Economic Outlook. Hours worked: 1979 from Maddison (1982); 1987 from Maddison (1991); 1992 from Maddison (1995); years in between are linearly interpolated; 19921997 based on trend in OECD, Employment Outlook. Labour compensation: 1980-1996 from OECD, National Accounts, Vol. I. France: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1996 extrapolated from 1990 with GDP trend from OECD, National Accounts, Vol. I; 1997 from OECD Online website. Persons employed: 1980-1996 from OECD, Labour Force Statistics; 1997 extrapolated from 1995 with employment trend from OECD, Economic Outlook. Hours worked: 1980-1996 from INSEE, Comptes et Indicateurs Économiques. Rapport sur les comptes de la Nation; 1997 based on trend in OECD, Employment Outlook. Labour compensation: 1980-1992 from INSEE, Comptes et Indicateurs Économiques; 1992-1996 from OECD, Economic Outlook.
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Germany, Federal Republic of (Western): GDP in 1990 US$: 1980-1990 from Maddison (1995); 19911997 extrapolated from 1990 with GDP trend from Statistisches Bundesamt, Volkswirtschaftliches Gesamtrechnungen. Persons employed: Statistisches Bundesamt, Volkswirtschaftliches Gesamtrechnungen. Hours worked: Institut fuer Arbeidsmarkt und Berufsforschung, Arbeitszeit und Arbeitsvolumen in Deutschland. Labour compensation: Statistisches Bundesamt, Volkswirtschaftliches Gesamtrechnungen. Greece: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1996 extrapolated from 1990 with GDP trend from OECD, National Accounts, Vol. I; 1997 from OECD Online website. Persons employed: 1980-1995 from OECD, Labour Force Statistics; 1996-1997 extrapolated from 1996 with employment trend from OECD, Economic Outlook. Hours worked: 1980-1992 based on linear interpolation between 1973 and 1992 from Maddison (1995); 1992-1997 kept constant at 1992 level. Labour compensation: 1980-1996 from OECD, National Accounts, Vol. I. Ireland: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1996 extrapolated from 1990 with GDP trend from OECD, National Accounts, Vol. I; 1997 from OECD Online website. Persons employed: 1980-1996 from OECD, Labour Force Statistics; 1997 extrapolated from 1996 with employment trend from OECD, Economic Outlook. Hours worked: 1980-1992 based on linear interpolation between 1973 and 1992 from Maddison (1995); 1992-1997 kept constant at 1992 level. Labour compensation: 1980-1996 from OECD, National Accounts, Vol. I. Italy: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1996 extrapolated from 1990 with GDP trend from OECD, National Accounts, Vol. I; 1997 from OECD Online website. Persons employed: 1987-1996 from OECD, Labour Force Statistics, but increased by 17.6% to match the upward adjustment in the Italian national accounts in 1982 to allow for “underground employment” (see Maddison, 1996); 1980-1986 backwardly extrapolated from 1987 on the basis of civilian employment (US concept) from Bureau of Labor Statistics website; 1997 extrapolated from 1996 with employment trend from OECD, Economic Outlook. Hours worked: 1979 from Maddison (1982); 1987 from Maddison (1991); 1990 from Maddison (1996); 1992 from Maddison (1995); years in between are linearly interpolated; 1992-1994 based upon trend in OECD, Employment Outlook; 1994-1997 kept constant at 1994 level. Labour compensation: 1980-1996 from OECD, National Accounts, Vol. I. Netherlands: GDP in 1990 US$: 1990 from Maddison (1995); 1980-1996 extrapolated from 1990 with GDP trend from Centraal Bureau voor de Statistiek, Nationale Rekeningen. Persons employed: Centraal Bureau voor de Statistiek, Arbeidsrekeningen. Hours worked: 1980-1987 on the basis of linear interpolation between 1979 and 1987; 1979 obtained from 1973-1979 according to Maddison (1982) linked to 1973 from Maddison (1995); 1987-1997 from Centraal Bureau voor de Statistiek, Arbeidsrekeningen. Labour compensation: Centraal Bureau voor de Statistiek, Nationale Rekeningen. Portugal: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1996 extrapolated from 1990 with GDP trend from OECD, National Accounts, Vol. I; 1997 from OECD Online website. Persons employed: 1980-1996 from OECD, Labour Force Statistics; 1997 extrapolated from 1996 with employment trend from OECD, Economic Outlook. Hours worked: 1980-1992 based on linear interpolation between 1973 and 1992 from Maddison (1995); 1992-1994 based upon trend in OECD, Employment Outlook; 1994-1997 kept constant at 1994 level. Labour compensation: 1980-1996 from OECD, National Accounts, Vol. I. Spain: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1996 extrapolated from 1990 with GDP trend from OECD, National Accounts, Vol. I; 1997 from OECD Online website. Persons employed: 1980-1996 from OECD, Labour Force Statistics; 1997 extrapolated from 1995 with employment trend from OECD, Economic Outlook. Hours worked: 1979 from Maddison (1982); 1987 from Maddison (1991); 1990 from Maddison (1996); 1992 from Maddison (1995); years in between are linearly interpolated; 1992-1997 based upon trend in OECD, Employment Outlook. Labour compensation: 1980-1996 from OECD, National Accounts, Vol. I.
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Sweden: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1996 extrapolated from 1990 with GDP trend from OECD, National Accounts, Vol. I; 1997 from OECD Online website. Persons employed: 1980-1996 from Bureau of Labor Statistics website; 1997 extrapolated from 1996 with employment trend from OECD, Economic Outlook. Hours worked: 1979 from Maddison (1982); 1987 from Maddison (1991); 1990 from Maddison (1996); 1992 from Maddison (1995); years in between are linearly interpolated; 1992-1997 based upon trend in OECD, Employment Outlook. Labour compensation: 1980-1996 from OECD, National Accounts, Vol. I. United Kingdom: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1996 extrapolated from 1990 with GDP trend from OECD, National Accounts, Vol. I; 1997 from OECD Online website. Persons employed: 1980-1996 from Bureau of Labor Statistics website; 1997 extrapolated from 1995 with employment trend from OECD, Economic Outlook. Hours worked: 1980-1987 on the basis of linear interpolation between 1979 and 1987; 1979 obtained from 1973-1979 according to Maddison (1982) linked to 1973 from Maddison (1995); 1987 from Maddison (1991); 1990 from Maddison (1996); 1992 from Maddison (1995); years in between are linearly interpolated; 1992-1997 based upon trend in OECD, Employment Outlook. Labour compensation: 1980-1996 from Government Statistical Service, National Accounts, 1997. Australia: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1996 extrapolated from 1990 with GDP trend from OECD, National Accounts, Vol. I; 1997 from OECD Online website. Persons employed: 1980-1996 from Bureau of Labor Statistics website; 1997 extrapolated from 1995 with employment trend from OECD, Economic Outlook. Hours worked: 1979 from Maddison (1982); 1987 from Maddison (1991); 1990 from Maddison (1996); 1992 from Maddison (1995); years in between are interpolated, from 1983-1987 using trend in man hours from OECD, National Accounts, Vol. II; 19921997 based upon trend in OECD, Employment Outlook. Labour compensation: 1980-1996 from OECD, National Accounts, Vol. I. Canada: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1996 extrapolated from 1990 with GDP trend from OECD, National Accounts, Vol. I; 1997 from OECD Online website. Persons employed: 1980-1996 from Bureau of Labor Statistics website; 1997 extrapolated from 1995 with employment trend from OECD, Economic Outlook. Hours worked: 1979 from Maddison (1982); 1987 from Maddison (1991); 1990 from Maddison (1996); 1992 from Maddison (1995); years in between are linearly interpolated; 1981-1996 based upon trend in OECD, Employment Outlook; 1997 kept constant at 1996 level. Labour compensation: 1980-1996 from OECD, National Accounts, Vol. I. Japan: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1996 extrapolated from 1990 with GDP trend from OECD, National Accounts, Vol. I; 1997 from OECD Online website. Persons employed: 1980-1996 from OECD, Labour Force Statistics; 1997 extrapolated from 1996 with employment trend from OECD, Economic Outlook. Hours worked: 1980-1990 from D. Pilat, (1994), The Economics of Rapid Growth: the Experience of Japan and Korea, Edward Elgar; 1990-1996 from Ministry of Labour, Monthly Report on the Labour Force Survey. 1997 kept constant at 1996 level. Labour compensation: 1980-1995 from OECD, National Accounts, Vol. I; 1996 from OECD, Economic Outlook. United States: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1996 extrapolated from 1990 with GDP trend from OECD, National Accounts, Vol. I; 1997 from OECD Online website. Persons employed: 1980-1996 from Bureau of Labor Statistics website; 1997 extrapolated from 1995 with employment trend from OECD, Economic Outlook; Hours worked: 1980-1987 on the basis of linear interpolation between 1979 and 1987; 1979 obtained from 1973-1979 according to Maddison (1982) linked to 1973 from Maddison (1995); 1987 from Maddison (1991); 1990 from Maddison (1996); 1992 from Maddison (1995); years in between are linearly interpolated; 1992-1997 based upon trend in OECD, Employment Outlook. Labour compensation: 1980-1996 from US Department of Commerce, National Income and Product Accounts.
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Hong Kong, China: GDP in 1990 US$: 1990 from Maddison (1995); 1980-1996 extrapolated from 1990 with GDP trend from Asian Development Bank, Key Indicators of Developing Asian and Pacific Countries. Persons employed: 1980-1996 from Asian Development Bank, Key Indicators of developing Asian and Pacific Countries. Hours worked: 1973 and 1992 from N. Crafts (1997), "Economic Growth in East Asia and Western Europe since 1950: Implications for Living Standards", National Institute Economic Review, No. 4; years in between are linearly interpolated; 1992-1997 based upon the yearly trend in the earlier series. Wage index: daily wage rate for wage earners in non-agricultural activities from ILO, Yearbook of Labour Statistics. Korea, Republic of: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1996 extrapolated from 1990 with GDP trend from Asian Development Bank, Key Indicators of Developing Asian and Pacific Countries. Persons employed: 1980-1996 from OECD, Labour Force Statistics. Hours worked: 1980-1990 from Pilat (1994); 1991-1996 trend linked to 1990 from Ministry of Labour, Yearbook of Labour Statistics. Labour compensation: 1980-1982 from Bank of Korea, National Accounts, 1990; 1983-1996 from OECD, National Accounts, Vol. I. Taiwan, China: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1996 extrapolated from 1990 with GDP trend from Asian Development Bank, Key Indicators of Developing Asian and Pacific Countries. Persons employed: 1980-1996 from Asian Development Bank, Key Indicators of Developing Asian and Pacific Countries. Hours worked: 1980-1995 from DOBAS, Monthly Bulletin of Earnings and Productivity Statistics; 1996 kept constant at 1995 level. India: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1996 extrapolated from 1990 with GDP trend from Asian Development Bank, Key Indicators of Developing Asian and Pacific Countries. Persons employed: 1980 and 1990 on the basis of labour force figures from the population census. Interpolated and extrapolated from 1990 with population growth rates. Sri Lanka: GDP in 1990 US$: 1990 from Maddison (1995); 1980-1996 extrapolated from 1990 with GDP trend from Asian Development Bank, Key Indicators of Developing Asian and Pacific Countries. Persons employed: 1980-1996 from Asian Development Bank, Key Indicators of Developing Asian and Pacific Countries. Indonesia: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1996 extrapolated from 1990 with GDP trend from Asian Development Bank, Key Indicators of Developing Asian and Pacific Countries. Persons employed: 1980-1996 from Asian Development Bank, Key Indicators of Developing Asian and Pacific Countries. Philippines: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1996 extrapolated from 1990 with GDP trend from Asian Development Bank, Key Indicators of Developing Asian and Pacific Countries. Persons employed: 1980-1989 from National Statistical Coordination Board, Philippine Statistical Yearbook; 1990-1995 from Asian Development Bank, Key Indicators of Developing Asian and Pacific Countries. Labour compensation: 1980-1989 from National Statistical Coordination Board, Philippine Statistical Yearbook; 1990-1995 extrapolated from 1990 with United Nations, National Account Statistics. Thailand: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1995 extrapolated from 1990 with GDP trend from Asian Development Bank, Key Indicators of Developing Asian and Pacific Countries. Persons employed: 1980-1995 from Asian Development Bank, Key Indicators of Developing Asian and Pacific Countries. Brazil: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1994 extrapolated from 1990 with GDP trend from A. Hofman (1998), Latin American Economic Development: A Casual Analysis in Historical Perspective, Groningen Growth and Development Centre, monograph series no. 3.; 19941996 extrapolated from IBGE, Annuario Estadistico do Brasil. Persons employed: 1980, 1989, 1990
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and 1994 from Hofman (1998); years in between are interpolated and 1995-1996 is extrapolated from 1994 using trend from N. Mulder, The Economic Performance of Services in Brazil, Mexico and the USA. in Comparative Perspective, Groningen Growth and Development Centre, Monograph Series, No. 4. Hours worked: 1980, 1989, 1990 and 1994 from Hofman (1998); years in between are linearly interpolated; 1994-1996 kept constant at 1994 level. Labour compensation: 1980-1996 from United Nations ECLAC database. Chile: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1994 extrapolated from 1990 with GDP trend from Hofman (1998); 1994-1996 from United Nations, Statistical Yearbook of Latin America. Persons employed: 1980, 1989, 1990 and 1994 from Hofman (1998); years in between are interpolated and 1995-1996 is extrapolated from 1994 using trend from ILO, Yearbook of Labour Statistics; 1996 estimated using the average growth rate over the period 1990-1995. Hours worked: 1980, 1989, 1990 and 1994 from Hofman (1998); years in between linearly interpolated; 1994-1996 kept constant at 1994 level. Labour compensation: 1980-1996 from United Nations ECLAC database. Colombia: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1994 extrapolated from 1990 with GDP trend from Hofman (1998); 1994-1996 from United Nations, Statistical Yearbook of Latin America. Persons employed: 1980, 1989, 1990 and 1994 from Hofman (1998); years in between are interpolated and 1995-1996 is extrapolated from 1994 using trend from ILO, Yearbook of Labour Statistics. Hours worked: 1980, 1989, 1990 and 1994 from Hofman (1998); years in between linearly interpolated; 1994-1996 kept constant at 1994 level. Labour compensation: 1980-1996 from United Nations, Statistical Yearbook of Latin America. Mexico: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1994 extrapolated from 1990 with GDP trend from Hofman, (1998); 1995-1996 extrapolated from 1994 from OECD, National Accounts, Vol. I; 1997 from OECD Online website. Persons employed: 1980 and 1990-1996 from OECD, Labour Force Statistics; 1981-1989 interpolated using trend for 7 main cities from INEGI, Annuaire Estadistico de los Estados Unidos Mexicanos, 1994; 1997 extrapolated from 1996 from OECD, Economic Outlook. Hours worked: 1980, 1989, 1990 and 1994 from Hofman (1998); years in between linearly interpolated; 1994-1996 kept constant at 1994 level. Labour compensation: 1980-1996 from OECD, National Accounts, Vol. I. Venezuela: GDP in 1990 US$: 1980-1990 from Maddison (1995); 1991-1994 extrapolated from 1990 with GDP trend from Hofman (1998); 1995-1996 extrapolated from 1994 from United Nations, Statistical Yearbook of Latin America. Persons employed: 1980, 1989, 1990 and 1994 from Hofman (1998); years in between are interpolated and 1995 is extrapolated from 1994 using trend from ILO, Yearbook of Labour Statistics; 1996 kept constant at 1995 level. Hours worked: 1980, 1989, 1990 and 1994 from Hofman (1998); years in between linearly interpolated; 1994-1996 kept constant at 1994 level. Labour compensation: 1980-1996 from United Nations ECLAC database.
Manufacturing data (KILM 17b) Austria: Manufacturing GDP in constant national currency: 1980-1996 from OECD, National Accounts, Vol. II. Persons employed: 1980-1996 from OECD, National Accounts, Vol. II. Belgium: Manufacturing GDP in constant national currency: 1980-1997 from Bureau of Labor Statistics, Foreign Labor Statistics (underlying data); conversion to US$ on the basis of ICOP Unit Value Ratio for 1987, provided by A. Soete, and converted to 1990 level with manufacturing GDP deflator derived from OECD, National Accounts, Vol. II. Persons employed: 1980-1997 from Bureau of Labor Statistics, Foreign Labor Statistics (underlying data). Hours worked: 1987 figure provided by A. Soete; trend in hours from 1980-1997 from Bureau of Labor Statistics, Foreign Labor Statistics (website). Labour compensation: 1980-1997 from Bureau of Labor Statistics, Foreign Labor Statistics (underlying data).
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Denmark: Manufacturing GDP in constant national currency: 1980-1995 from OECD, National Accounts, Vol. II. Persons employed: 1980-1995 from OECD, National Accounts, Vol. II. Labour compensation: 1980-1995 from OECD, National Accounts, Vol. II. Finland: Manufacturing GDP in constant national currency: 1980-1996 from OECD, National Accounts, Vol. II. Persons employed: 1980-1996 from OECD, National Accounts, Vol. II. Hours worked: 1987 level estimate from M. Maliranta (1994), Comparative Levels of Labour Productivity in Swedish, Finnish and American Manufacturing, Helsinki School of Economics, mimeographed and converted to 1990 level with manufacturing GDP deflator derived from OECD, National Accounts, Vol. II. Persons employed: 1980-1996 trend from OECD, National Accounts, Vol. II. Labour compensation: 1980-1996 from OECD, National Accounts, Vol. II. France: Manufacturing GDP in constant national currency: 1980-1996 from OECD, National Accounts, Vol. II; conversion to US$ on the basis of ICOP Unit Value Ratio for 1987 from B. van Ark and R. Kouwenhoven (1994), "La productivité du secteur manufacturier français en comparaison internationale", Économie Internationale, no. 60, CEPII, Paris, and converted to 1990 level with manufacturing GDP deflator derived from INSEE, Comptes et Indicateurs Economiques, 1998. Persons employed: 1980-1995 from OECD, National Accounts, Vol. II; 1996 from INSEE, Comptes et Indicateurs Economiques, 1998. Hours worked: 1980-1996 from INSEE, Comptes et Indicateurs Economiques, 1998. Labour compensation: 1980-1996 from Bureau of Labor Statistics, Foreign Labor Statistics (underlying data). Germany, Federal Republic of (Western): Manufacturing GDP in constant national currency: 19801996 from Statistisches Bundesamt, Volkswirtschaftliches Gesamtrechnungen; conversion to US$ on the basis of ICOP Unit Value Ratio for 1987 from B. van Ark and D. Pilat (1993), Cross Country Productivity Levels: Differences and Causes, Brookings Papers on Economic Activity (Microeconomics 2), 1993, pp. 1-69, and converted to 1990 level with manufacturing GDP deflator derived from Statistisches Bundesamt, Volkswirtschaftliches Gesamtrechnungen. Persons employed: 1980-1996 from Statistisches Bundesamt, Volkswirtschaftliches Gesamtrechnungen. Hours worked: 1980-1996 from Institut fuer Arbeidsmarkt und Berufsforschung, Arbeitszeit und Arbeitsvolumen in Deutschland. Labour compensation: 1980-1996 from Bureau of Labor Statistics, Foreign Labor Statistics (underlying data). Greece: Manufacturing GDP in constant national currency: 1980-1995 from OECD, National Accounts, Vol. II. Persons employed: 1980-1995 from OECD, National Accounts, Vol. II. Netherlands: Manufacturing GDP in constant national currency: 1980-1996 from Centraal Bureau voor de Statistiek, Nationale Rekeningen; conversion to US$ on the basis of ICOP Unit Value Ratio for 1987 from R. Kouwenhoven, Analysing Dutch Manufacturing Productivity, 1993, and converted to 1990 level with manufacturing GDP deflator derived from Centraal Bureau voor de Statistiek, Nationale Rekeningen. Persons employed: 1980-1987 trend from adjusted employment series provided by Centraal Bureau voor de Statistiek, which were linked to estimates for 1987-1994 from Centraal Bureau voor de Statistiek, Arbeidsrekeningen; 1995-1996 trend linked to 1994 on the basis of Centraal Bureau voor de Statistiek, Enquete Beroepsbevolking. Hours worked: 1987 benchmark based on Centraal Bureau voor de Statistiek, Sociaal-Economische Maandstatistiek; 1980-1994 trend on the basis of contractual hours from Centraal Bureau voor de Statistiek, Arbeidsrekeningen; 1995-1996 linked to 1994 on the basis of series provided by Centraal Plan Bureau. Labour compensation: 1980-1996 from Centraal Bureau voor de Statistiek, Nationale Rekeningen. Portugal: Manufacturing GDP in constant national currency: 1980-1995 from OECD, National Accounts, Vol. II. Persons employed: 1980-1995 from OECD, National Accounts, Vol. II. Spain: Manufacturing GDP in constant national currency: 1980-1996 from OECD, National Accounts,
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Vol. II; conversion to US$ on the basis of ICOP Unit Value Ratio for 1992 from ICOP/LCRA project (University of Groningen), and converted to 1990 level with manufacturing GDP deflator derived from OECD, National Accounts, Vol. II. Persons employed: 1980-1996 from OECD, National Accounts, Vol. II. Sweden: Manufacturing GDP in constant national currency: 1980-1996 from OECD, National Accounts, Vol. II; conversion to US$ on the basis of ICOP Unit Value Ratio for 1987 from M. Maliranta (1994), converted to 1990 level with manufacturing GDP deflator derived from OECD, National Accounts, Vol. II. Persons employed: 1980-1994 from OECD, National Accounts, Vol. II; 1995-1996 trend linked to 1994 on the basis of trend from Bureau of Labor Statistics, Foreign Labor Statistics (underlying data). Hours worked: 1987 benchmark from Maliranta (1994); 1980-1996 trend from Bureau of Labor Statistics, Foreign Labor Statistics (website). Labour compensation: 1980-1996 from Bureau of Labor Statistics, Foreign Labor Statistics (underlying data). United Kingdom: Manufacturing GDP in constant national currency: 1980-1992 from OECD, National Accounts, Vol. II; 1993-1996 trend linked to 1992 from Government Statistical Office, National Accounts, 1997; conversion to US$ on the basis of ICOP Unit Value Ratio for 1987 from B. van Ark (1992). "Comparative Productivity in British and American Manufacturing", National Institute Economic Review, November, and converted to 1990 level with manufacturing GDP deflator derived from OECD, National Accounts, Vol. II. Persons employed: 1980-1992 from OECD, National Accounts, Vol. II; 1993-1996 from Government Statistical Office, National Accounts, 1997. Hours worked: 1987 benchmark from van Ark (1992); 1980-1996 trend from Bureau of Labor Statistics, Foreign Labor Statistics (website). Labour compensation: 1980-1996 from Bureau of Labor Statistics, Foreign Labor Statistics (underlying data). Australia: Manufacturing GDP in constant national currency: 1980-1996 from OECD, National Accounts, Vol. II; conversion to US$ on the basis of ICOP Unit Value Ratio for 1987 from D. Pilat, D.S. Prasada Rao and W. Shepherd (1993), Comparison of Real Output, Productivity Levels and Purchasing Power in Australia/US Manufacturing 1970-1989, COPPAA Research Paper, No. 1, Centre for the Study of Australia-Asia Relations, Griffith University, Brisbane, and converted to 1990 level with manufacturing GDP deflator derived from OECD, National Accounts, Vol. II. Persons employed: 1980-1996 from OECD, National Accounts, Vol. II. Hours worked: 1980-1983 from Pilat, Rao and Shepherd (1993); 1984-1996 linked to 1983 based upon trend from OECD, National Accounts, Vol. II. Labour compensation: 1980-1996 from OECD, National Accounts, Vol. II. Canada: Manufacturing GDP in constant national currency: 1980-1996 from OECD, National Accounts, Vol. II; conversion to US$ on the basis of ICOP Unit Value Ratio for 1987 from G. de Jong (1997), Canada’s Post-war Manufacturing Performance: a Comparison with the United States, Groningen Growth and Development Centre Research Memorandum, GD-32, and converted to 1990 level with manufacturing GDP deflator derived from OECD, National Accounts, Vol. II. Persons employed: 19801997 from Bureau of Labor Statistics, Foreign Labor Statistics (underlying data). Hours worked: 1987 benchmark from De Jong (1996); 1980-1997 trend from Bureau of Labor Statistics, Foreign Labor Statistics (website). Labour compensation: 1980-1997 from Bureau of Labor Statistics, Foreign Labor Statistics (underlying data). Japan: Manufacturing GDP in constant national currency: 1980-1996 from EPA, Annual Report on the National Accounts; conversion to US$ on the basis of ICOP Unit Value Ratio for 1987 from D. Pilat (1994), The Economics of Rapid Growth: The Experience of Japan and Korea, Edward Elgar Ltd., and converted to 1990 level with manufacturing GDP deflator derived from EPA, Annual Report on the National Accounts. Persons employed: 1980-1996 from EPA, Annual Report on the National Accounts. Hours worked: 1980-1996 from Ministry of Labour, Monthly Report on the Labour Force Survey. Labour compensation: 1980-1996 from Bureau of Labor Statistics, Foreign Labor Statistics (underlying data).
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United States: Manufacturing GDP in constant national currency: 1980-1996 from US Department of Commerce, National Income and Product Accounts, with 1980-1987 at fixed 1982 weights, and 19871996 at 1992 chained weights. Persons employed: 1980-1996 from US Department of Commerce, National Income and Product Accounts. Hours worked: 1987 benchmark from B. van Ark (1993), International Comparisons of Output and Productivity. Manufacturing Productivity Performance of Ten Countries from 1950 to 1990, Monograph Series No. 1, Groningen Growth and Development Centre. 1980-1996 trend from US Department of Commerce, National Income and Product Accounts. Labour compensation: 1980-1997 from Bureau of Labor Statistics, Foreign Labor Statistics (underlying data). Korea, Republic of: Manufacturing GDP in constant national currency: 1980-1996 from Bank of Korea, National Accounts; conversion to US$ on the basis of ICOP Unit Value Ratio for 1987 from D. Pilat (1994), The Economics of Rapid Growth: The Experience of Japan and Korea, Edward Elgar Ltd., and converted to 1990 level with manufacturing GDP deflator derived from Bank of Korea, National Accounts. Persons employed: 1980-1990 from EPB, Annual Report on the Economically Active Population; 1991-1996 trend linked to 1990 from OECD, Labour Force Statistics. Hours worked: 1980-1996 from Ministry of Labor, Report on the Monthly Labor Survey. Labour compensation: 19801982 from Bank of Korea, National Accounts, 1990; 1983-1995 from OECD, National Accounts, Vol. I1; 1996 linked to 1995 from Bureau of Labor Statistics, Foreign Labor Statistics (underlying data). Wage trend: 1980-1996 trend in monthly earnings of employees ILO, Yearbook of Labour Statistics. Taiwan, China: Manufacturing GDP in constant national currency: 1980-1996 from DOBAS, National Income in Taiwan; conversion to US$ on the basis of ICOP Unit Value Ratio for 1987 from M. Timmer, (1998), Catch-up Patterns in Newly Industrializing Countries: an International Comparison of Manufacturing Productivity in Taiwan, 1961-1993, Groningen Growth and Development Centre Research Memorandum, GD-40, and converted to 1990 level with manufacturing GDP deflator derived from DOBAS, National Income in Taiwan. Persons employed: 1980-1996 from DOBAS, Monthly Bulletin of Labour Statistics. Hours worked: 1987 benchmark from Timmer (1998); 1980-1996 trend from DOBAS, Monthly Bulletin of Earnings and Productivity Statistics. Wage trend: 1980-1996 trend in monthly earnings from DOBAS, Monthly Bulletin of Earnings and Productivity Statistics. India: Manufacturing GDP in constant national currency: 1980-1995 from Central Statistical Office, National Accounts; conversion to US$ on the basis of ICOP Unit Value Ratio for 1983-84 from A. Szirmai and M. Timmer (1997), Growth and Divergence in Manufacturing Performance in South and East Asia, Groningen Growth and Development Centre Research Memorandum, GD-37, and converted to 1990 level with manufacturing GDP deflator derived from Central Statistical Office, National Accounts. Persons employed: 1980 and 1990 on the basis of labour force in the population census. Interpolated and extrapolated from 1990 with population growth rates. Indonesia: Manufacturing GDP in constant national currency: 1980-1995 based on Asian Development Bank, Key Indicators of Developing Asian and Pacific Countries; conversion to US$ on the basis of ICOP Unit Value Ratio for 1987 from Szirmai and Timmer (1997), and converted to 1990 level with manufacturing GDP deflator derived from Asian Development Bank, Key Indicators of Developing Asian and Pacific Countries. Persons employed: 1980-1995 from Asian Development Bank, Key Indicators of Developing Asian and Pacific Countries. Philippines: GDP in constant national currency: 1980-1989 from National Statistical Coordination Board, Philippine Statistical Yearbook; 1990-1995 from Asian Development Bank, Key Indicators of Developing Asian and Pacific Countries. Persons employed: 1980-1989 from National Statistical Coordination Board, Philippine Statistical Yearbook; 1990-1995 from Asian Development Bank, Key Indicators of Developing Asian and Pacific Countries. Wage trend: 1980-1993 trend in wage rates per day from ILO, Yearbook of Labour Statistics.
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Thailand: GDP in constant national currency: 1980-1996 from Asian Development Bank, Key Indicators of Developing Asian and Pacific Countries. Persons employed: 1980-1985 from N. Vanderveen (1987), Postwar Economic Growth and Structural Change in Thailand, University of Groningen (mimeographed); 1986-1996 trend from United Nations, Statistical Yearbook. Mexico: GDP in constant national currency: 1980-1996 from INEGI, Cuentas Nacionales de Mexico. Persons employed: 1980-1996 from N. Mulder, The Economic Performance of Services in Brazil, Mexico and the USA. in Comparative Perspective, Groningen Growth and Development Centre, Monograph Series, No. 4. Wage trend: 1980-1996 trend in earnings per month from ILO, Yearbook of Labour Statistics.
31
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OECD (1999, 2000), National Accounts Main Aggregates, Volume I, Paris. O’Mahony, M. (1996), ‘Measures of Fixed Capital Stocks in the Post-war Period: a Five Country Study’, in B. van Ark and N.E.R. Crafts (eds.) Quantitative Aspects of Post war European Growth, Cambridge: Cambridge University Press, pp. 165-214. O’Mahony, M. (1999), Britain’s Relative Productivity Performance 1950-1996, National Institute of Economic and Social Research, London. Paige, D. and G. Bombach (1959), A Comparison of National Output and Productivity, OEEC, Paris. Pilat, D. (1994), The Economics of Rapid Growth. The Experience of Japan and Korea, Edward Elgar Publishers, Aldershot. Pilat, D., D.S. Prasasa Rao and W.F. Shepherd (1993), "Australia and United States Manufacturing. A Comparison of Real Output, Productivity Levels and Purchasing Power, 1970-1989", COPPAA Series, no. 1, Centre for the Study of Australia-Asia Relations, Griffith University, Brisbane, Australia. Ryten, J. (1998), The evaluation of the International Comparison Project (ICP), Consultant Report for the International Monetary Fund, United Nations and World Bank (downloadable from http://www.un.org/Depts/unsd/sna/icp/icprep.htm). Soete, A. (1994), “The Evolution of the Competitiveness of the Belgian Manufacturing Industry in the Long Run, 1880-1990”, paper presented at the Economics Department of the Catholic University Leuven. Summers, R. and A. Heston (1991), "The Penn World Table (March 5): An Expanded Set of International Comparisons, 1950-1988", Quarterly Journal of Economics, May. Timmer, M.P. (1999), The Dynamics of Asian Manufacturing. A Comparative Perspective, ECIS. Forthcoming with Edward Elgar Publishers, Aldershot. Timmer, M.P. and B. van Ark (2000), “Capital Formation and Productivity Growth in South Korea and Taiwan: Realising the Catch-Up Potential in a World of Diminishing Returns”, University of Groningen, mimeographed. United Nations (1986), World Comparisons of Purchasing Power and Real Product for 1980, New York. United Nations ( 1994), World Comparisons of Real Gross Domestic Product and Purchasing Power 1985, New York. World Bank (1999), World Development Indicators 1999, Washington D.C.
Table 17b.
Labour productivity and unit labour costs, manufacturing (revised) (figures in italics indicate changes compared to publication in KILM 17b) Year
Labour productivity Value added Value added Value added Value added per person per person per hour per hour employed employed worked worked (1990 US $) (1980 = 100) (1990 US $) (1980 = 100)
Unit labour costs Labour Labour compensation compensation per unit of per unit of output on US output on US dollar basis (1990 US $)
Developed (industrialized) countries Major Europe Austria 1980 1990 1991 1992 1993 1994 1995 1996 Belgium 1980 30581 1990 46583 1991 46812 1992 47248 1993 48425 1994 52575 1995 51736 1996 52543 1997 55600 Denmark
1980 1990 1991 1992 1993 1994
100 141 146 149 152 162 165 172 100 152 153 155 158 172 169 172 182 100 105 107 110 116 118
20.13 30.24 30.94 31.23 32.49 34.34 34.16 34.55 36.49
100.0 150.2 153.7 155.1 161.4 170.6 169.7 171.6 181.3
0.83 0.83 0.84 0.93 0.87 0.89 1.04 1.00 0.84
Labour compensation per unit of output on national dollar basis currency basis (1980 = 100) (1980 = 100)
Wages or earnings per unit of output on US dollar basis
Note No.
(1980 = 100)
100.0 99.8 101.4 111.9 105.1 107.0 125.6 120.8 101.1
100.0 114.1 118.4 123.0 124.4 122.4 126.6 127.9 123.7
1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2
100.0 155.7 153.4 165.4 147.9 153.6
100.0 171.0 174.1 177.2 170.2 173.4
3 3 3 3 3 3
1995 1980 1990 1991 1992 1993 1994 1995 1996 France 1980 1990 1991 1992 1993 1994 1995 1996 Germany, Federal 1980 Republic of (Western) 1990 1991 1992 1993 1994 1995 1996 Finland
Greece
Netherlands
1980 1990 1991 1992 1993 1994 1995 1980 1990 1991 1992
24353 39113 37627 42413 47836 53525 56113 57430 33373 43747 43635 44247 44992 48399 49946 50926 33680 39565 40462 40048 38979 41945 43202 44471
118 100 161 155 174 196 220 230 236 100 131 131 133 135 145 150 153 100 118 120 119 116 125 128 132
27678 36367 36404 36676
100 336 398 445 613 665 688 100 131 132 133
14.06 23.85 23.86 27.04 30.21 33.05 34.37 35.16 19.45 27.15 27.04 27.30 27.99 30.16 30.97 31.55 19.62 24.92 25.66 25.20 25.30 27.22 28.19 29.44
17.71 25.46 25.58 25.69
100.0 169.6 169.6 192.3 214.8 235.0 244.4 250.0 100.0 139.6 139.0 140.3 143.9 155.0 159.2 162.2 100.0 127.0 130.8 128.4 128.9 138.7 143.6 150.0
100.0 143.7 144.4 145.1
0.60 0.94 0.94 0.78 0.57 0.59 0.74 0.70 0.64 0.79 0.80 0.87 0.83 0.80 0.88 0.85 0.62 0.91 0.92 1.04 1.04 1.03 1.19 1.14
0.68 0.75 0.76 0.85
181.9 100.0 155.5 155.4 129.2 94.6 98.3 121.7 115.4 100.0 123.5 125.5 136.7 129.1 125.3 137.1 133.6 100.0 146.9 147.8 168.3 168.0 167.6 192.3 184.3
100.0 110.3 111.2 124.0
180.8 100.0 159.4 168.5 155.2 144.9 137.7 142.4 142.1 100.0 159.2 167.5 171.2 173.0 164.6 161.9 161.7 100.0 130.6 134.8 144.6 152.8 149.6 151.6 152.6
3 3 3 3 3 3 3 3 3 4 4 4 4 4 5 4 6 7 7 7 7 7 7 7 7
100.0 101.0 104.6 109.7
1 1 1 1 1 1 1 9 9 9 9
Portugal
Spain
Sweden
United Kingdom
Major non-Europe Australia
1993 1994 1995 1996 1980 1990 1991 1992 1993 1994 1995 1980 1990 1991 1992 1993 1994 1995 1996 1980 1990 1991 1992 1993 1994 1995 1996 1980 1990 1991 1992 1993 1994 1995 1996
36830 40463 41004 41569
25.97 28.59 29.03 29.65
146.6 161.4 163.9 167.4
0.82 0.78 0.86 0.82
119.8 114.2 126.5 120.7
112.0 104.5 102.1 102.3
19916 28877 29609 30639 31337 33394 31125 30703 25283 34291 34534 36661 40110 44778 48022 49398 17793 28187 28623 29659 31162 32604 32878 33753
133 146 148 150 100 110 110 118 117 117 126 100 145 149 154 157 168 156 154 100 136 137 145 159 177 190 195 100 158 161 167 175 183 185 190
17.64 22.81 23.00 24.22 25.83 27.99 29.73 30.87 10.30 16.71 17.26 17.87 18.87 19.60 19.61 20.05
100.0 129.3 130.4 137.3 146.4 158.7 168.6 175.0 100.0 162.3 167.6 173.5 183.2 190.3 190.4 194.7
0.82 1.05 1.11 1.15 0.80 0.78 0.84 0.93 0.84 1.00 1.07 1.08 0.93 0.94 0.98 0.96
100.0 127.3 134.9 139.5 97.6 94.3 101.7 112.7 100.0 119.2 126.8 128.1 110.0 111.1 116.0 114.4
100.0 178.1 192.8 192.0 179.5 172.0 171.5 178.7 100.0 156.0 167.2 169.8 170.4 168.8 171.0 170.5
9 9 10 10 1 1 1 1 1 1 1 11 11 11 11 11 11 11 11 12 12 12 12 12 12 13 13 14 14 14 14 15 15 15 15
1980
26109
100
13.59
100.0
0.63
100.0
100.0
16
Canada
Japan
United States
Asia and the Pacific Eastern Asia
1990 1991 1992 1993 1994 1995 1996
32282 33110 33625 35153 35735 36282 36070
124 127 129 135 137 139 138
16.39 16.91 17.08 17.52 17.66 18.04 17.96
120.6 124.4 125.7 129.0 130.0 132.8 132.1
0.75 0.76 0.73 0.67 0.73 0.77 0.85
119.2 120.8 116.4 106.7 116.2 123.5 135.5
174.0 176.7 180.6 178.8 181.1 189.7 197.3
17 17 17 17 17 17 17
1980 1990 1991 1992 1993 1994 1995 1996 1997 1980 1990 1991 1992 1993 1994 1995 1996 1980 1990 1991 1992 1993 1994 1995 1996
30469 39220 38862 40886 43087 43926 44985 44188 45428 32613 52438 53177 51578 50099 50658 54706 56127 37714 52614 52514 54249 56111 59952 63481 65966
100 129 128 134 141 144 148 145 149 100 161 163 158 154 155 168 172 100 140 139 144 149 159 168 175
16.04 20.22 20.15 21.16 21.99 22.29 22.93 22.48 23.10 15.00 24.66 25.54 25.54 25.44 25.73 27.66 28.51 20.30 27.40 27.50 28.20 28.80 30.30 32.40 33.70
100.0 126.1 125.6 131.9 137.1 139.0 143.0 140.2 144.0 100.0 164.4 170.2 170.2 169.6 171.5 184.4 190.1 100.0 134.8 135.6 138.6 141.5 149.2 159.5 165.7
0.51 0.75 0.81 0.78 0.70 0.65 0.65 0.69 0.67 0.40 0.59 0.65 0.71 0.85 0.94 0.98 0.84 0.57 0.68 0.71 0.73 0.74 0.72 0.69 0.69
100.0 147.2 159.3 151.7 136.3 128.0 127.9 134.2 131.9 100.0 148.3 162.8 180.2 215.5 236.7 246.4 210.8 100.0 119.5 125.3 128.5 129.4 125.6 121.3 120.1
100.0 147.0 156.1 156.9 150.5 149.5 150.1 156.5 156.3 100.0 94.7 96.6 100.7 105.7 106.7 102.2 101.2 100.0 119.5 125.3 128.5 129.4 125.6 121.3 120.1
18 18 18 18 18 18 18 18 19 20 20 20 20 20 20 20 20 21 22 22 22 22 22 22 22
Korea, Republic of
Taiwan, China
South-central Asia India
South-eastern Asia Indonesia
Philippines
1980 1990 1991 1992 1993 1994 1995 1996 1980 1990 1991 1992 1993 1994 1995 1996
8994 17113 18358 19951 21745 23798 25940 28437 11644 19187 20908 21694 23143 24460 26306 27850
100 190 204 222 242 265 288 316 100 165 180 186 199 210 226 239
3.30 6.48 7.02 7.72 8.39 9.20 9.94 10.90 4.40 7.92 8.64 8.96 9.54 10.09 10.88
100.0 196.3 212.8 233.9 254.2 278.8 301.1 330.1 100.0 180.0 196.6 203.9 217.1 229.4 247.4
0.32 0.48 0.49 0.46 0.44 0.43 0.45 0.45
100.0 152.1 153.8 146.0 138.9 137.2 143.4 142.1
100.0 177.2 185.6 187.5 183.5 181.7 182.1 188.1
100.0 211.7 230.6 245.4 249.7 263.4 265.7 271.9 100.0 222.8 227.5 257.6 246.1 247.6 242.8 230.2
1980 1990 1991 1992 1993 1994 1995
1675 2669 2504 2567 2745 2984 3342
100 159 149 153 164 178 199
28 28 29 29 29 29 29
1980 1990 1991 1992 1993 1994 1995 1980 1990 1991 1992
2233 3543 3793 4022 4210 3833 4547
100 159 170 180 189 172 204 100 99 90 83
30 30 30 30 30 30 30 31 32 32 32
100.0 502.2 624.6 754.7
23 24 25 25 25 25 25 26 27 27 27 27 27 27 27 27
Thailand
1993 1994 1995 1980 1990 1991 1992 1993 1994 1995 1996
87 87 94 100 125 126 135 137 154 156 148
748.7
32 32 32 33 34 34 34 34 34 34 34
Latin America and the Caribbean Latin America Mexico 1980 100 100.0 35 1990 101 8769.9 35 1991 104 10780.3 35 1992 108 12678.5 35 1993 113 13535.3 35 1994 120 12863.6 35 1995 121 14533.3 35 1996 125 17188.4 35 This Table is a revised version of KILM 17b. All level estimates have been changed because of a correction in the updating of Unit Value Rations to 1990 (see Section 3 of this paper).
