Section 3 Rising productivity and the role of human capital and organization

Section 3 Rising productivity and the role of human capital and organization <Key points> 1. Productivity trends since the 1990s Since the late 1990s, labor productivity and total factor productivity (TFP) have risen rapidly in the United States (US) and elsewhere. In the US, the share of IT equipment in private capital stock almost doubled in the late 1990s, evidencing the rapid accumulation of IT capital stock. 2. Verification of progress in the diffusion of IT and productivity increase in Japan and the US in the late 1990s Although various issues arise in a rigorous evaluation of productivity, analyses suggest no particular discrepancy in productivity increase rates between Japan and the US, while economic growth disparity between Japan and the US may have possibly been caused by something other than IT investment. Looking at differences between industrial sectors in terms of productivity increases, the acceleration of these increases in the late 1990s not only in the durable goods industry, the category into which the IT manufacturing sector falls, but over a wide range of other industries, raises the possibility that IT user sectors such as financial insurance and retail could have driven this trend. In contrast to the US, increases in productivity in Japan following IT investment have been concentrated only in the IT manufacturing sector, indicating that such increases may not have expanded out to the IT user sector. There is, however, a need to take note of the continuing wide range of matters for investigation in comparing productivity trends at the industrial level. Corporate analysis in both Japan and the US showed that increasing productivity hinges on the parallel pursuit of not only IT investment but also human and organizational capital enhancement. As mentioned in the previous two sections, as the competitive environment changed with the progress of globalization in the late 1990s, a trend toward global disinflation emerged and the relationship between economic cycles and job creation changed. It is often pointed out that progress in the diffusion of information technology (IT) caused this change in the competitive environment. The effect of progress in the diffusion of IT has also become the center of discussions about the productivity 1 increases in the 1990s. This section will look at trends in productivity in and after the 1990s for countries including Japan. Although it has been established that progress in the diffusion of IT played a certain role in productivity increases, this section will attempt to verify that the status of human resources and organization in companies and the complementary relationship of these factors including the diffusion of IT have played a significant role in productivity increases. 1 Hereinafter the combination of labor productivity and total factor productivity is simply referred to as productivity. - 36 -

1. Productivity trends since the 1990s (1) Increase in productivity By comparing the trends in the rate of increase in labor productivity in each country in and after the 1980s (Fig. 1.3.1), one can see that the rate of increase in labor productivity generally narrowed in many countries in the early 1990s compared with the 1980s, and following this in the late 1990s, the increase rates continued to narrow in some countries (Germany, United Kingdom (UK)), while they started to expand in others (US, Japan, etc.). In 2002, after the burst of the so-called IT Bubble, the productivity increase rates expanded in almost all countries, and one can see that the productivity increase rate in the US in particular has been significantly higher than that in other countries since the late 1990s with the exception of one period (2001). 2 (%) Figure 1.3.1 Trends in rate of increase in labor productivity in each country 4.5 4.0 3.5 3.0 2.5 Japan US France Germany Japan UK 2.0 US 1.5 1.0 Average for OECD countries 0.5 0.0-0.5 Average for 1975-1985 Average for 1986-1990 Average for 1991-1995 Average for 1996-2000 2001 2002-1.0 Source: Economic Outlook (OECD). Comparing the rate of increase in multifactor productivity (MFP) (synonymous with total factor productivity (TFP)) in each country in the 1980s and 1990s (Fig. 1.3.2), one can see that there is a clear gap between countries in which MFP increase rates are accelerating and countries in which they are not. This indicates that the differences in the speed of technical progress expanded among the countries in the 1990s. In 2 Productivity increases accompanying rapid progress in the diffusion of IT in and after the 1980s in the US have not been confirmed, and the Solow Paradox (also known as the productivity paradox ), which says that productivity increases cannot be statistically confirmed despite large investments in IT, has been widely discussed. Answers to this paradox include the lack of IT investment theory, which says that the diffusion of IT did not progress as much as believed, the statistical flaw theory, which says that existing statistics do not capture accurately the diffusion of IT, and the effect manifestation lag theory, which says that a long time is needed before the effects of the diffusion of IT can be seen. Some point out, however, that because a productivity increase has been statistically confirmed in the US in the late 1990s as mentioned above, the discussions regarding the Solow Paradox are considered to be resolved for the time being. (Economic Planning Agency (2000)). - 37 -

the US in particular, the rate of increase in labor productivity accelerated in the late 1990s, and the MFP increase rate also expanded in the 1990s compared with the 1980s. According to the statistics shown in this figure, the MFP increase rate in the US was higher than that in Japan. 3.5 3.0 (%) Figure 1.3.2 Trends in MFP increase rate in each country Countries in which MFP increase rate accelerated Countries in which MFP increase rate decelerated 2.5 2.0 1.5 1980-1990 1990-2000 1.0 0.5 0.0 US Canada Australia Finland Germany France Japan Italy Note: Figures for Germany in 1991-2000 were calculated as 1990-2000. Figures for Australia, France, Italy and Japan in 1990-1999 were calculated as 1990-2000. Source: The Sources of Economic Growth in OECD Countries (OECD). As will be shown later, however, it is necessary to take note that the choice of evaluation method used significantly affects rigorous evaluation of productivity and its international comparisons. (2) Trends in the diffusion of IT The following looks at possible changes accompanying the rapid increase in labor productivity and MFP confirmed in and after the late 1990s, as shown above, centered on the US. In general discussions the cause of productivity increase is held as being related to the progress of the diffusion of IT. Comparing the amount of IT capital stock as a percentage of private capital stock (private corporate capital stock in the case of the US) in Japan and the US (Fig. 1.3.3), one can see that the amount of IT capital stock in Japan was approximately 52.7 trillion yen in 2001, 4.5 percent of its private capital stock, while the amount of IT capital stock in the US was approximately 1.25 trillion dollars, accounting for 12.1 percent of its private corporate capital stock. In the US, the share of IT equipment in private capital stock almost doubled in the late 1990s, evidencing the rapid accumulation of IT capital stock. - 38 -

15.0 (%) Figure 1.3.3 Trends in IT capital stock ratio in Japan and the US IT Capital stock ratio in Japan IT Capital stock ratio in the US 11.5 12.1 10.0 9.7 7.8 5.0 0.0 6.2 5.2 4.4 4.0 4.5 2.5 2.8 2.9 2.6 2.5 1.0 1.1 1.3 1.6 1.9 2.2 2.4 2.6 3.0 3.3 3.4 3.5 1.5 1.6 1.7 1.8 1.9 2.1 2.2 2.3 2.5 2.7 2.8 2.9 3.1 3.4 3.8 0.7 0.7 0.9 1980 1985 1990 1995 2000 (Year) Note: The figures for the US indicate the IT capital stock ratio in the private sector corporate capital stock. The figures for Japan indicate the IT capital stock ratio in the private sector capital stock. Also, in calculating the IT capital stock in the US, the amounts invested in independently developed software are excluded from the amounts invested in software. Source: FY2002 Survey on Economic Analysis of IT (Ministry of Public Management, Home Affairs, Posts and Telecommunications). 2. Verification of progress in the diffusion of IT and productivity increase in Japan and the US in the late 1990s (1) Verification of progress in the diffusion of IT and productivity increase on the macroeconomic level As shown above, there is a significant gap between Japan and the US in terms of the amount of IT investment as a percentage of the total amount of investment. IT investment, however, has an effect on the measurement of productivity, and there is a significant difference between official statistics in Japan and the US with regards to methods for measuring price changes in IT investment goods (computers, software and communications equipment) and the scope of IT investments in GDP. Thus, to compare accurately IT investment as well as productivity in Japan and the US, it is necessary to adjust for the differences between official statistics in both countries. 3 The following introduces analytical methods used by Motohashi (2003) in carrying out a comparative analysis of productivity increase in the late 1990s in Japan and the US, adjusting for the differences mentioned above. In the analysis, to compare accurately the increases in productivity in Japan and the US, adjustments are made to the data including (i) applying the same measurement methods used in the US when measuring price changes in IT investment goods in Japan and (ii) using the same scope of software investment as the US in measuring investment amount when calculating the GDP of Japan, because the amount of Japan s IT 3 In Figure 1.3.3 mentioned earlier, calculation was made while giving consideration to the differences between official statistics in Japan and the US, such as the exclusion of self-developed software from the investment amount of software investment in the US. - 39 -

investment is underestimated due to the fact that Japan s definition of software is narrower than that of the US in the official statistics. 4 Figure 1.3.4 shows a breakdown of the factors for the GDP growth rate in Japan and the US in 1990-1995 and 1995-2000, and analysis results of the contribution of IT in output (gross domestic product (GDP)) and input (gross domestic income (GDI)). Figure 1.3.4 Decomposition of the factors for GDP growth rate (%) Gross Domestic Product (GDP) Contribution of IT Contribution of non-it Gross Domestic Income (GDI) Contribution of IT capital services Contribution of non-it capital services Contribution of labor services Total Factor Productivity (TFP) Note: Each value is average growth rate during the surveyed period. Source: Motohashi (2003). Japan US 1990 1995 1995 2000 1990 1995 1995 2000 1.89 2.15 2.43 4.12 0.40 1.08 0.57 1.11 1.49 1.07 1.86 3.01 1.15 1.02 2.19 3.44 0.31 0.90 0.48 0.99 1.00 0.33 0.64 1.10-0.16-0.20 1.06 1.35 0.74 1.13 0.24 0.68 The analysis results indicate the following three points. First, (i) although total factor productivity (TFP) expanded in both Japan and the US in the late 1990s, the TFP increase rate in Japan is higher than that in the US. In addition, (ii) the contribution of IT investment to increasing output in Japan in the late 1990s rose approximately one percent, almost on the same level as that in the US. Meanwhile, (iii) the contribution of non-it sectors to GDP growth rate is substantially larger in the US than in Japan, and one can see that this is the cause of the differences in the GDP growth rate during these periods. In particular, the contribution of labor services is positive in the US while it is negative in Japan due to the differences in the handling of employment and wages in Japan and the US in the late 1990s. Because increases and decreases in labor services are thought to be linked with increases and decreases in human capital, which suggests that there is a high probability that the contribution of human capital increased in the US economy in the late 1990s while it decreased in Japan due to restructuring and other factors. Although various issues arise in a rigorous evaluation of productivity, these results alone suggest that no particular discrepancy in productivity increase rate between Japan and the US, as was introduced earlier, and economic growth disparity between Japan and the US may have possibly been caused by something other than IT investment. (2) Verification of progress in the diffusion of IT and productivity increase on the industrial level We will now look at the types of differences that exist between industrial sectors in Japan and the US in 4 Regarding the handling of software, in the National Income and Product Accounts (NIPA) in the US, not only ordered software, but also packaged software and self-developed software are included in the GDP as part of investment amounts. Therefore, in calculating the GDP in Japan this time, the investment amounts of packaged software and self-developed software in the corporate, government and household sectors have been estimated into the GDP as part of capital investment (Motohashi (2003)). - 40 -

terms of productivity increases. Specifically, we will attempt to verify: (i) whether there are differences in productivity increase rate among industries between sectors that manufacture IT equipment and those that are predominant users of IT equipment (and whether productivity increase is concentrated in the former type of sectors); and (ii) the level to which IT use has diffused in various industrial sectors. (a) The US We will first introduce the results of analysis done by the US Department of Commerce (2002) on the industrial level regarding the relationship between progress in the diffusion of IT and the increase in labor productivity in the US. In the analysis, the effect of IT on the rise in labor productivity is measured using the following methods. All industries are given a ranking based on IT use intensity, which is expressed in IT equipment (ITEQ: includes computers and peripherals, software and other information processing equipment) per full-time equivalent (FTE), and each industry s IT use intensity (ITEQ in each industry/fte in each industry) is calculated as a percentage of the average IT use intensity in all industries (ITEQ in all industries/fte in all industries). The industries are ranked according to IT use intensity and divided into an upper group (industries with a relatively high IT use intensity which contribute to 50 percent of GDP, hereinafter referred to as high IT intensity industries ) and a lower group (industries with a relatively low IT use intensity which contribute to 50 percent of GDP, hereinafter referred to as low IT intensity industries ). The contribution of these industries to the rate of increase in labor productivity (GDP/FTE) is then analyzed. Looking at the results in Figure 1.3.5, it is clear that high IT intensity industries contributed significantly more to productivity increase than did low IT intensity industries. One can thus see that whether or not an industry uses IT is a significant factor that affects the labor productivity increase rate. Figure 1.3.5 Productivity increase rate for the US non-agricultural business sector in IT use intensity High IT intensity industries 2.32 3.70 Low IT intensity industries 0.06 1.21 Acceleration rate of productivity growths in all industries 1.46% 1989-1995 1995-2000 All industries 1.02 2.48 0 1 2 3 4 % Note: US Estimates by the Economics and Statistics Administration based on data by US Bureau of Economic Analysis. Source: US Department of Commerce (2002). - 41 -

We will now look at an analysis of contributions to the acceleration of productivity increase rate by industry, classifying the industries less restrictively than above. The productivity increase of industries between 1989-1995 and 1995-2000 accelerated an average of 1.46 percent annually (= 2.48 percent - 1.02 percent), and one can see in Figure 1.3.6 that the durable goods industry, which includes the IT manufacturing sectors, contributed 0.27 percent. This figure, when calculated into the rate of contribution or level of contribution to the acceleration of productivity increase, only accounts for 18 percent of the total and one can thus see that the remaining 82 percent was contributed by productivity increase in industries besides the durable goods industry. According to the results of the analyses above, the acceleration of productivity increase in the late 1990s in the US was not only seen in the durable goods industry, that includes the IT manufacturing sectors, but over a wide range of other industries, which raises the possibility that IT user sectors such as financial insurance and retail could have driven this trend. 5 Figure 1.3.6 Contribution to the acceleration rate of productivity growths (by main industries in the non-agricultural corporate sector in the US, 1995-2000 over 1989-1995) Durable goods manufacturing Other service industries IT manufacturing sectors included 0.23 0.27 Finance industry 0.54 Retail Wholesale IT user sectors 0.30 0.41 Transportation, public works -0.09 Non-durable goods manufacturing Construction -0.06-0.05 Acceleration rate of productivity growths in all industries = 1.46% Mining -0.09-0.2-0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 Source: US Estimates by the Economics and Statistics Administration based on data by US Bureau of Economic Analysis. Original source: US Department of Commerce (2002). (b) Japan The following shows an industry-level analysis by the Ministry of Economy, Trade and Industry (METI) (2001) regarding the relationship between the progress in the diffusion of IT and productivity increase in Japan. This analysis of productivity classifies each entity investing in IT-related capital stock (here referred to as informatization-related capital stock, in accordance with terminology used by METI (2001)) into IT product manufacturers (general, electric and precision machinery industry) and IT infrastructure (communication industries) in the IT manufacturing sector and IT product users (manufacturing industries besides IT product manufacturers such as the steel industry and the chemical industry and non-manufacturing industries other than 5 Regarding this point, Farrell (2003) cited large productivity increases concentrated in the six industries of retail, securities, wholesale, semiconductors, computers and telecommunications. - 42 -

communications industries) in the IT user sector. Looking at the results shown in Figure 1.3.7, one can see that: (i) in the IT manufacturing sector there was a steady increase in both productivity and TFP accompanying an increase in the informatization-related capital stock ratio; while (ii) in the IT user sector the informationization-related capital stock ratio did not increase and TFP was flat, if not decreasing. Based on the results of the analysis above, it appears that there is a possibility that production efficiency and productivity increased in the IT manufacturing sector due to active IT investment, while they did not increase in the IT user sector due to an inadequate level of IT investment. Thus, a conclusion can be drawn from the above that, in contrast to the US, increases in productivity in Japan following IT investment have been concentrated only in the IT manufacturing sector, indicating that such increases may not have expanded to the IT user sector. 6 Figure 1.3.7 Analysis of factors for productivity by investors (Contribution ratio on a year-on-year basis, average for the period starting from the January-March quarter of 1995 until the July-September quarter of 2000) All industries IT product users IT product users IT infrastructure IT product (Manufacturing (Non-manufacturing (Communication manufacturers industries) industries) industries) (%) Year-on-year productivity ratio 1.51 6.18 1.29-0.21 15.88 Capital factors 1.02 2.13 0.94 0.72 3.75 Informatization-related capital factors 0.43 0.90 0.27 0.30 3.15 Hardware factors 0.25 0.63 0.17 0.21 0.60 Software factors 0.06 0.11 0.07 0.05 0.02 Communication equipment factors 0.11 0.16 0.03 0.03 2.39 General capital factors 0.59 1.23 0.68 0.43 0.59 Operation rate factors 0.17 0.41 0.06 TFP 0.32 3.64 0.29-0.93 12.14 Source: Analysis of All Industrial Activities (2001) (METI). In order to measure the effect of informatization on productivity, it is necessary to have an accurate grasp of output in each industry. It is difficult, however, to grasp qualitative improvements centered on the service industry, and there is a possibility that these evaluations of productivity are inadequate. 7 There is thus a need to take note that there continues to be a wide range of matters for investigation in comparing productivity trends at the industrial level. (3) Verification of progress in the diffusion of IT and productivity increase on the corporate level (a) The US In the above analysis of productivity on the macroeconomic and industrial levels, statistics regarding the US indicate that: (i) productivity increased in the late 1990s due to progress in the diffusion of IT and; (ii) not only the IT manufacturing sector but also the IT user sector made significant contributions to the productivity increase. In analyzing the extent to which IT use contributed to productivity increases of companies, it is necessary to look at not only IT investment, but also a variety of factors such as efforts by companies in the areas of human capital and organization. The following introduces an analysis by Bresnahan et al. (2000) which 6 Based on these results, Motohashi (2002) points out that productivity expanded in the IT manufacturing sector due to active IT investment, and although active IT investment was carried out in the IT user sector, this IT investment did not lead to an expansion in productivity because information systems were not utilized effectively. 7 Motohashi (2001). - 43 -

was carried out on the corporate level using the above approach in the US. Specifically, the analysis on the corporate level looks at the effect of IT (amount spent on procurement of computers), human capital (degree of proficiency and educational background of workers) and organizational capital (the level of decentralization in decision-making in corporate structure) 8 on productivity increase. In the analysis, data on individual companies were gathered using an ordinary database (Compustat firm data) as well as a questionnaire survey on senior human resources managers at approximately 300 major US companies. The analysis was carried out gathering data on human capital (the level of education of employees, degree of proficiency, etc.) and corporate structure (speed in decision making, situation regarding the system of teams, etc.) from each company. More specifically, looking at the correlation between IT, human capital and organizational capital (Fig. 1.3.8), it was confirmed that correlations exist in all combinations of these three factors. The analysis then looks at the extent to which relative levels of combinations of these three factors have an effect on productivity increase at the companies. According to this, it has been confirmed that: (i) when all three factors are at high levels, productivity is approximately seven percent higher than when the three factors are at average levels, (ii) when even one of the three factors are below average, even if the other two factors are higher than average, productivity is lower than when all of the factors are at average levels; and (iii) when all the factors are below average, productivity is close to the same level as when all of the factors are at average levels. Figure 1.3.8 Relationship between IT, human capital and corporate structures Human capital Degree of proficiency 0.06 0.17 Percentage of specialist personnel 0.21 Percentage of college graduates 0.30 0.12 0.05 0.21 0.28 0.34 IT investment Source: Bresnahan et al. (2000). 0.18 Flattening of corporate structures 8 See Chapter 2, Section 1 on page 92 for a detailed definition of human capital and organizational capital. - 44 -

These results suggest that to improve productivity, there is a need for complementarity in which human capital and organizational capital are developed in addition to the diffusion of IT, and even if the quality of only a portion of these factors is raised, productivity will not necessarily increase. (b) Japan An analysis by the Economic Planning Agency (2000) looks at complementarity in Japanese companies using the same methods as above. The analysis is a positive analysis looking at the relationship between IT, human capital and organizational capital through a questionnaire survey 9 and financial data of Japanese companies. 10 In the analysis, number of computers per person, percentage of university and graduate school graduates and degree of development of flattening are used as the representative indices for the diffusion of IT, human capital, and the state of corporate structure, respectively, and companies are categorized into either groups in which these indices are high relative to other companies in their industry or groups in which these indices are low relative to other companies in their industry. The indices are then paired, creating three categories of diffusion of IT and human capital, diffusion of IT and corporate structure and human capital and corporate structure, and the categories are divided further into four groups based on whether the two indices are high or low (e.g. a group in which the degree of the diffusion of IT is high, but human capital is low). Figure 1.3.9 indicates the added value of companies based on the grouping outlined above. Looking at Figure 1.3.9, one can see that in Japan, as in the US, there appears to be a mutually complementary relationship between the diffusion of IT, human capital and decentralization of corporate structures. It appears that in each combination, companies which made efforts in both factors had high productivity increases, while companies which made efforts in only one of the two factors in some cases had low productivity. 9 Responses were received from 482 companies. Of these, 139 were listed companies, 9 were over-the-counter companies and 334 were other companies. As for capital, 301 companies had capital of 100 million yen or more, 154 companies had capital of less than 100 million yen and 27 companies did not provide information regarding their capital. 10 Concerning corporate financial data, in an analysis of listed and over-the-counter companies (excluding financial and insurance companies) conducted by the Japan Economic Research Institute, data from survey sheets on added value, capital stock and numbers of employees were created and matching was carried out with data from survey sheets regarding the diffusion of IT, human capital and corporate structure obtained in the questionnaire survey mentioned above. The data, for which all the necessary variables were gathered and matching was possible, were limited, and the sample size in this analysis was 86. See Economic Planning Agency (2000) for details. - 45 -

Figure 1.3.9 Effects of the spread of IT, human capital, and flattening of corporate structures on TFP % 35 30 25 20 15 10 5 0 (Standard) (Standard) (Standard) -5-10 -15-20 high high high low low high low low high high high low low high low low high high high low low high low low (spread of IT x human capital) (spread of IT x corporate structures) (human capital x corporate structures) Note: *** in the graph means 1% significance, * means 10% significance. Areas where no statistically-significant results were obtained are left unmarked. Source: Policy Impact Analysis Report 2000 (Economic Planning Agency). As can be concluded from above, corporate analysis in both Japan and the US shows that increasing productivity hinges on the parallel pursuit of not only IT investment but also the enhancement of human capital and organizational capital. Chapter 2 looks in detail at the important role of human capital and organizational capital in increasing the value creation capability of companies. - 46 -