sou · GQB3118d4 · 2003-01-01 00:00:00 — It is, of course, possible that a fast-growing high-tech sector brings with it additional data prob- 24Yet another difficulty when it comes to computing the factor shares is that Swedish firms have occasionally been allowed to reduce their current tax payments. For example, additional tax rules have been introduced from 1980 through 1993 to subsidize firms mainly in the service sector by allowing rescheduling of tax payments equivalent to up to 20 percent of total wage costs. 25Note that data availability often have a strong bearing on the actual variable definitions in empirical studies of this kind. A very broad measure of capital may, for example, include capital outlays on tangible (physical) assets as well as human capital in the sense of education attainment, on-the-job training, and research and development activities. lems.26 The theoretical ideal should be input measures adjusted for quality differences as well as utilization rates.27 A final limitation is that the data do not include information on intermediate inputs, such as energy, materials, and business services. This lack of infor- mation precludes a gross output formulation of equation (2.6). Yet another data issue is the possibility that it may take some time for capital inputs to generate output. To allow for such delay, equation (2.6) can be modified somewhat to include lagged input variables. The questions addressed in this article have some important impli- cations for the economy as a whole. Consider for example the question whether productivity gains have occurred in the universe of industries or just in a few of them. If productivity increases are general, the productivity revival is probably more robust than would otherwise have been the case. In addition, if the productivity increase is general, the resulting income and economic gains are distributed more or less evenly over all industries. The distribution of income – either directed evenly to all industries or just to a few of them – directly affects the well being of the employees. The work reported in this section focuses on the benchmark growth- accounting relationship as described by equations (2.6) and (2.9). These expressions split labor productivity growth into capital deepening, in the sense of capital per hours worked, and total fac- tor productivity growth. This exercise raises a few questions that, in one way or another, have been considered earlier. One concerns the nature of the data and the construction of the relevant vari- 26For discussions of other problems as regards the measurement of the productivity contri- bution of computers at the macroeconomic level, see and (1988), and Siegel (1997). 27Many studies have identified the problems associated with measuring of factor inputs. Examples are Bernanke and Parkinson (1991) who considered difficulties in the measure- ment of labor input when analyzing procyclical labor productivity in U.S. manufacturing, and Griliches (1994) who argued that measurement difficulties may be a major cause of the slow progress in our understanding of productivity growth. Moreover, due to difficulties in measuring input utilization rates, Benhabib and Jovanovic (1991) treated capital as well as labor as unobservable in some regressions. In particular, the short time series data imply that it is diffi- cult to distinguish between cycle and trend productivity growth. Another shortcoming is that input quality and utilization rates are not accounted for. Furthermore, the benchmark equations implic- itly assume returns to scale, which may or may not hold. However, it may certainly be a reasonable approximation, espe- cially over longer time periods. The equations also allow for pa- rameters varying over time and across sectors. In the analysis pre- sented below, all cost shares are computed according to equation (3.3) – hence, these shares vary over time and between sectors. In the appendix, I have experimented with shares over time. Another issue is, as mentioned in the introduction, the question of whether or not there appears to be an empirical link between ICT use (rather than production) and gains in total factor produc- tivity. The answer to this question determines if ICT-related capi- tal deepening should be characterized as productive or unproduc- tive. Indeed, during the 1990s, firms invested heavily in ICT in the hope of improving profits and productivity. Potential gains from ICT could be realized through a number of channels, such as pro- ductive spillovers and network effects due to faster information flows within (and between) firms. If investments in high-tech equipment really result in total productivity gains, one would ex- pect to see a link between high-tech investment and gains in total factor productivity across industries. Such a link would allow indi- vidual industries, and hence the economy as a whole, to produce more output and thus implies a true economic benefit from the high-tech revolution. The present analysis cannot, unfortunately, shed much light on this issue due to data limitations (too short time series data). It is worth mentioning here that one possibility is that high-tech equipment may merely be used to reallocate the market share be- tween the competing firms – for example when a traditional store loses business to an on-line business – or it may increase on-the- job consumption – for example, when workers play video games. Sizeable training and support costs that go along with high-tech capital outlays may also limit the productivity gains. If all of these counteracting effects are large enough, one might not see a positive link between high-tech investments and total factor productivity gains. Table 4 Accounting for productivity growth in –1999 Business (ISIC 01-95) Growth in hours worked (9) ICT share in ALP growth Note: In 1999 the business sector accounted for 70.8 (69.3) percent of total current value GDP (hours worked) in the Swedish economy. The ICT share in ALP growth is computed as the ICT capital deepening divided by the growth of ALP. Source: Statistics and the authors calculations. Table 4 presents the growth-accounting results for the period 1994–1999. The first two lines show the growth in output and the growth in hours worked. The third line is the growth rate of out- put per hour worked (i.e., the labor productivity growth), which can be calculated in the table by subtracting the growth rate of la- bor hours in the second line from the growth rate of output in the first line. Labor productivity growth, in turn, can be expressed as the sum of capital deepening (line 4), which is the growth in capital per hour multiplied by capitals share in total factor costs and total factor productivity growth (line 8). , the growth rate of out- put per hour minus a fraction of the growth rate of capital per hour equals total factor productivity growth. Capital deepening is in turn split into buildings-related deepening (line 5), machinery- related deepening exclusive of ICT (line 6), and ICT-related deep- ening (line 7). Thus, the sum of lines (5), (6), and (7) equals line (4). The second to last line (line 8) is total factor productivity, which is productivity growth based on a weighted average of sev- eral inputs – in this case labor and capital with weights based on the share of each input in total factor costs. The last line (line 9) is the ICT share in labor productivity growth, computed as the ICT capi- tal deepening in line (7) divided by the growth of labor pro- ductivity in line (3). The main conclusions from Table 4 are as follows. First, annual TFP growth was especially strong in 1994 and 1995 (3.8 and 4.9 percent, respectively), which probably has to do in part with cycli- cal forces – remember that escaped from a large recession in the middle of the 1990s. Second, the contribution from aggre- gate capital deepening to labor productivity growth is negative in 1994, 1995, 1998, and 1999. 5 shows that buildings-related capital deepening drives this result. A negative contribution to pro- ductivity growth from aggregate capital deepening is a rather un- common empirical finding, especially over longer periods of time. One possible reason for why capital per hours worked declined in 1994–1995 is that it represents a surge in working hours in the af- termath of the 1991–93 recession years (that is, this is a cyclical effect).28 Other potential explanations include various difficulties concerning, in particular, the measurement of capital inputs. For example, capital per hours worked may fall as a result of the im- plicit assumptions that are made in the construction of the data as regards the capital depreciation rate and the price of capital. Both a higher assumed computer hardware and software depreciation rate and an underestimation of the true quality-adjusted price decline of computer hardware and software will lead to an underestimation of the growth rate of computer capital, which, in turn, will drive down the capital-labor ratio. Third, the productivity contribution from high-tech equipment has accelerated during the period – from 0.03 percentage points in 1994 to 0.19 percentage points in 1999 (see line 7). These numbers imply that the contribution from high-tech capital deepening to labor productivity growth has increased from 1.3 percent in 1994 to 10.5 percent in 1999 (see line 9) – hence the importance of high-tech equipment for aggregate productivity growth has increased over the period. The labor productivity growth in the business sector thus appears to be driven by rising high-tech-related capital deepening as well as total factor produc- tivity growth. Using the standard cost shares (i.e., 0.7 for labors 28 The contribution from machinery exclusive of ICT was negative in 1994 and 1995 (-0.72 and -0.45), which reflect large increases in hours worked after the end of the 1991–93 reces- sion. Then, as the business cycle returned to normal, investments in machinery exclusive of ICT started to increase more than hours, leaving a positive contribution from machinery- related (exclusive of ICT) capital deepening. share and 0.3 for capitals share) moderates this contribution to 0.7 percent 1994 and 6.2 percent 1999 (see the appendix). Table 5 Accounting for productivity growth in –1999 Goods (ISIC 01-45) Growth in hours worked (9) ICT share in ALP growth Note: In 1999 the goods sector accounted for 27.0 (28.8) percent of total current value GDP (hours worked) in the Swedish economy. Its share of value-added (hours worked) in the business sector was 38.1 (41.6) percent. The ICT share in ALP growth is computed as the ICT capital deepening divided by the growth of ALP. Source: Statistics and the authors calculations. Bilaga 5 SOU 2002:118 Table 6 Accounting for productivity growth in –1999 Services (ISIC 50-95) Growth in hours worked (9) ICT share in ALP growth Note: In 1999 the service sector accounted for 43.9 (40.5) percent of total current value GDP (hours worked) in the Swedish economy. Its share of value-added (hours worked) in the business sector was 61.9 (58.4) percent. The ICT share in ALP growth is computed as the ICT capital deepening divided by the growth of ALP. Note also that the annual average ICT share in ALP growth over the period 1994–99 is highly affected by the negative ALP growth in 1999; the median value of the ICT share from 1994–99 is 3.84 percent, and the ICT share from 1994–98 is 5.31 percent. Source: Statistics and the authors calculations. Table 7 Accounting for productivity growth in –1999 Manufacturing (ISIC 15-37) Growth in hours worked (9) ICT share in ALP growth Note: In 1999 the manufacturing sector accounted for 19.1 (18.4) percent of total current value GDP (hours worked) in the Swedish economy. Its share of value-added (hours worked) in the business sec- tor was 27.0 (26.6) percent. The ICT share in ALP growth is computed as the ICT capital deepening divided by the growth of ALP. Source: Statistics and the authors calculations. Table 8 Accounting for productivity growth in –1999 Information and () (ISIC 30, 313, 32, 331, 642, 72) Growth in hours worked (9) ICT share in ALP growth Source: In 1999 the ICT sector accounted for 5.6 (4.1) percent of total current value GDP (hours worked) in the Swedish economy. Its share of value-added (hours worked) in the business sector was 8.0 (5.9) percent. The ICT share in ALP growth is computed as the ICT capital deepening divided by the growth of ALP. Source: Statistics and the authors calculations. Tables 5–8 repeat this exercise for the goods sector, services sector, manufacturing sector, and ICT sector, respectively. Upon first ex- amination of these tables, there are several main findings. In par- ticular, the productivity contribution from aggregate capital deep- ening is typically negative (the only exception is the manufacturing sector). Furthermore, the productive contribution from the use of high-tech equipment is in general positive and has accelerated over the period. The exception here – disregard for the moment the ser- vices sector in 1999 – is, interestingly, the high- tech sector in itself (the high-tech share in labor productivity growth averages –6.8 percent). This probably has to do with massive increases in hours worked in this sector.29 Another possibility is, as already men- tioned, that high-tech capital might be underestimated. It is also interesting to note that TFP growth has been exceptionally high in the high-tech sector throughout the time period, an annual average of 13.5 percent as compared with 5.2 percent in total manufactur- 29 Note that in the ICT sector the productivity contribution from machinery exclusive of ICT is nonetheless typically positive (the annual average is 0.2 percentage points) despite large increases in hours in this sector. This suggests massive investments in machinery exclu- sive of ICT during the period. ing (c.f. Tables 7 and 8).30 The growth in labor productivity in the high-tech sector, in turn, averaged slightly more than 11 percent per year over the period – reflecting an increase in output growth of almost 19 percent per year and an increase in hours worked of slightly more than 7.5 percent. However, the size of this sector is small, implying that there is only a limited impact from labor pro- ductivity growth in this sector on economy-wide productivity growth. , to sum up, the key empirical finding in this section is that the Swedish productivity revival of the 1990s – as measured by the growth of labor productivity – is in part a result of a growing high-tech sector: I find sizeable total factor productivity growth in high-tech producing sectors and capital deepening associated with high-tech equipment elsewhere. The analysis moreover indicates a rising importance of high-tech equipment as a normal input in the production process, and the fact that the contribution of other capital goods has declined may in fact indicate a switch from tradi- tional capital into high-tech capital. The potential for this substitu- tion is likely to vary between the sectors – conceivably the ability to switch is largest for services, while in the manufacturing sector high-tech capital is typically complementary to traditional capital inputs. Much scope remains, however, to distinguish between cyclical and structural productivity gains. Bearing in mind that es- caped from a large recession in the middle of the 1990s, this dis- tinction between fluctuation and trend seems crucial. to data limitations, however, I leave this to future work. Another issue is causality. Even though the exercise above suggests that high-tech capital investments improve productivity growth, it could also be the other way around – strong productivity growth would then lead to investments in high-tech capital. Data limitations preclude a closer analysis of this as well.31 In the 1990s, a number of business economists launched what came to be known as the new paradigm (new era) economics. As regu- larly stated, this new doctrine abandoned the old idea that the 30Note that parts of the ICT sector lie in the manufacturing sector. 31In order to determine the causality between high-tech investments and productivity, time- series econometrics is called for, and, accordingly, longer time series are needed. threat of inflation would limit the possibilities for sustained eco- nomic growth. According to this view, rapid productivity growth together with increased competition and global integration would imply that even considerable growth rates would not cause any in- flationary pressures. This opinion is often casually referred to as something that has to do with the new economy. The present analysis obviously relates to the above in that it investigates the productivity contribution from high-tech capital. It does not, how- ever, go into any details as regards the variety of new era defini- tions that circulate among economists nor does it in any way speculate about the future of the new era and its likely effects in general on society as a whole. This lies outside the scope of the analysis. In contrast, the growth-accounting framework in the present analysis implicitly assumes traditional economic forces – and as long as the output from this exercise is sensible and easy to comprehend there is no need for tentative conjectures. Yet, taken at face value, although the results from the growth account- ing exercise, saying both that total factor productivity growth has been very large in the high-tech producing sector and that high- tech capital deepening has been important elsewhere, is qualita- tively in line with what most people would probably expect, one could perhaps raise objections against the magnitudes of these ef- fects. This is where a deeper analysis and discussion of all the usual and novel measurement difficulties associated with factor inputs is called for. This is for future work. While allowing for preliminary data on high-tech capital and the subse- quent feedback from experienced economists, the Commission on the Review of Economic Statistics makes a promising attempt to improve parts of the official statistics in . The present ana- lysis exemplifies what can be accomplished using rather simple means and identifies some data issues that deserve additional atten- tion. For example, the negative productivity contribution from ag- gregate capital deepening raises a few questions concerning the construction of the capital data: if the high-tech capital deprecia- tion rate is too high or if the price decline of high-tech capital is too low, the growth rate of high-tech capital will be underesti- mated. This would hence drive down the ratio of high-tech capital to worked hours, leading to a smaller contribution to labor produc- tivity growth from high-tech capital deepening (and perhaps also from aggregate capital deepening). For a closer look at the implicit assumptions that are made in the construction of the current data as regards the development of high-tech prices, see Figure 3 and Table 9. The average annual price decline of computer hardware is, according to Figure 3, about 10 per cent during the period 1986 through 1993. The price decline for telecommunications equipment is somewhat smaller during this period. The price decline of high- tech capital was less pronounced during the period 1994–1999. Ta- ble 9 shows that ICT prices declined by about 6 percent per year from 1994 through 1999. The GDP deflator increased by about 1.8 percent per year. Although these price changes may perhaps look reasonable, it would be interesting to see both in-depth compari- sons with corresponding international prices and further work on the true cost of computer power and quality adjusted high-tech prices. Annual price change (Investment Price Index). C O M P U T E R S Note: The price series are obtained implicitly by dividing nominal values with real values for the economy as a whole. Thus, the series show annual price changes of economy-wide pur- chases of computers, ICT, and telecommunications equipment, respectively. The data used in the present study do not explicitly include price changes for computers and telecommuni- cations equipment after 1993 (i.e., even though these price series are implicit in all calcu- lations, they are not explicitly available to the author), and no data on price changes for the ICT aggregate are available before 1994. Throughout this study, ICT is defined to include computer hardware, software, and telecommunications equipment. Source: Statistics and the authors calculations. Table 9 Current value of output and output price Note: Values denotes current output values in billions of current SEK. Prices are obtained by dividing current value output with real output normalized to one in 1993. Source: Statistics and authors calculations. Another related issue is the size of the residual in the growth account- ing exercise (this part is labeled total factor productivity growth and captures what is left of labor productivity growth after control- ling for capital and labor inputs). An underestimation of the growth of factor inputs leads inevitably to an overestimation of the resi- dual. The current effort by Statistics to produce new data on high-tech capital is promising. The ambition is that a mutually reward- ing collaboration between the producer and users of data will in the end lead both to fast progress in the production of this kind of data and to a better knowledge of the underpinnings of the Swedish productivity revival of the 1990s. In addition, this joint work will also hopefully set a new standard in data production. To summarize, the key empirical finding of this study is that Swed- ish labor productivity growth in the 1990s has increased in part as a result of massive investments in high-tech capital. The underlying forces seem to be pure technological improvements in the produc- tion of high-tech assets that have lowered the relative price and in- duced massive high-tech capital outlays. These high-tech invest- ments have contributed immediately to labor productivity gains through high-tech-related capital deepening. high-tech capi- tal can work for a while, but sooner or later computer hardware and software as well as telecommunications equipment will run into diminishing returns (as will any production factor) – there are hence real limitations to this development. The finding of large to- tal factor productivity growth in high-tech producing sectors and capital deepening associated with high-tech capital elsewhere re- flects traditional economic forces such as technological change and factor input substitution. Whether or not high-tech capital use is productive in the sense of improving also total factor productivity growth is still an open question – this analysis does not shed any light on this issue, due to data limitations (too short time series data). The channels through which high-tech equipment logically can boost total factor produc- tivity are many – for example, the usual productive spillovers im- plying that investors can benefit from embodied knowledge in capital as well as novel network effects stemming from enhanced information exchange among actors with comparable communica- tion equipment. Many caveats remain, however. One is the procyclical behavior of productivity. Since productivity tends to move with overall eco- nomic activity the Swedish productivity resurgence may in fact, as discussed in this article, merely reflect output growing faster than trend growth. The current analysis does not try to guess how much of the productivity surge of the 1990s reflects improvements in the underlying trend and how much is attributable to cyclical forces.