The economic contribution of the “C” in ICT: Evidence from OECD countries

Numerous studies have documented the contribution of ICT to growth. Less has been done on the contribution of communications technology, the “C” in ICT. We construct an international dataset of fourteen OECD countries and present contributions to growth for each ICT asset (IT hardware, CT equipment and software) using alternative ICT deflators. Using each country’s deflator we find that the contribution of CT capital deepening to productivity growth is lower in the EU than the US. Thus we ask: is that lower contribution due to a lower rate of CT investment or differing sources and methods for measurement of price change? We find that: (a) there are still considerable disparities in measures of ICT price change across countries; (b) in terms of growth-accounting, price harmonisation has a greater impact on the measured contributions of IT hardware and software in the EU relative to the US, than that of CT equipment; over 1996–2013, harmonising investment prices explains just 15% of the gap in the EU CT contribution relative to the US, compared to 25% for IT hardware; (c) over 1996–2013, CT capital deepening accounted for 0.11% pa (6% as a share) of labour productivity growth (LPG) in the US, compared to 0.03% pa (2.5% of LPG) in the EU-13 when using national accounts deflators; and (d) using OECD harmonised deflators, the figure for the EU-13 is raised to 0.04% pa (4% of LPG).     

THE TREATMENT OF INTANGIBLE RESOURCES AS CAPITAL

The author describes the results of his current research designed to measure total investment, tangible and intangible, and the derived capital stocks for the U.S., 1929–1966. With respect to total investment, the estimates show a marked increase in its ratio to GNP. All of the increase occurs in the intangible component comprising R & D, education and training, health, and mobility. The increase was concentrated in the government sector, although households increased the proportion of disposable personal income devoted to total investment.
Consistent with the relative investment trends, the stock of intangible capital grew considerably faster than the tangible stock. The growth of total capital stocks was somewhat less than that of GNP, however, in both current and constant prices. Thus, the rate of return on total capital rose somewhat over the period. Average rates of return on human and nonhuman capital were closely similar.
In real terms, the growth of total capital stocks accounted for two-thirds of the growth in real GNP, 1929–1966. One-third of the growth is attributed to residual forces, chiefly economies of scale, changes in inherent quality of human and natural resources, changes in values and motivations, and changes in rates of utilization of capacity.
The growth of the ratio of real intangible stocks to real tangible stocks accounted for less than half of the increase in total factor productivity 1929–1966. This is significantly less than the contribution of intangibles as estimated by Denison, and the author adduces several reasons why his estimates may understate the contribution. Nevertheless, it seems that the net effect of the residual forces enumerated above must also have made a substantial contribution to the growth of tangible factor productivity and real GNP over the 37-year period.     

Evidence on the impact of R&D and ICT investments on innovation and productivity in Italian firms

Both research and development (R&D) and information and communication technology (ICT) investment have been identified as sources of relative innovation underperformance in Europe vis-à-vis the USA. In this article, we investigate the R&D and ICT investment at the firm level in an effort to assess their relative importance and to what extent they are complements or substitutes. We use data on a large unbalanced panel data sample of Italian manufacturing firms constructed from four consecutive waves of a survey of manufacturing firms, to estimate a version of the CDM model of R&D, innovation, and productivity [Crépon–Duguet–Mairesse 1998. Research, innovation and productivity: An econometric analysis at the firm level. Economics of Innovation and New Technology 7, no. 2: 115–58] that has been modified to include ICT investment and R&D as the two main inputs into innovation and productivity. We find that R&D and ICT are both strongly associated with innovation and productivity, with R&D being more important for innovation, and ICT investment being more important for productivity. For the median firm, rates of return to both investments are so high that they suggest considerably underinvestment in both these activities. We explore the possible complementarity between R&D and ICT in innovation and production, but find none, although we do find complementarity between R&D and worker skill in innovation.     

Information and Communication Technology (ICT) and Singapore’s economic growth

Singapore’s remarkable success in economic development has been strongly associated with the country’s vigorous efforts to embrace the Information and Communication Technology (ICT) revolution to promote economic growth. This study provides a comprehensive investigation of the contributions of ICT to Singapore’s economic growth during the 1990–2008 period. It documents three key findings. First, there is a strong positive association between the intensity of ICT use and value-added and labor productivity growth at the sector level. Second, ICT investment contributed approximately 1 percentage point to Singapore’s GDP during 1990–2008, and its role in driving economic growth has become increasingly important over time. Third, the contribution of the ICT manufacturing sector to Singapore’s growth was notable, but it was on the decline and faced difficult restructuring challenges. This paper also provides valuable policy lessons and strategic insights for governments in both developed and developing countries that aspire to embrace ICT to promote economic growth.     

Computers And Growth

The purpose of this paper is to describe the impact of investment in computers on the growth of the U.S. economy. The economic literature on computers is relatively rich in information on the decline in computer prices and the growth of computer investment. Constant quality price indices for computers have been included in the U.S. National Income and Product Accounts (NIPA) since 1986. These indices employ state of the art methodology to capture the rapid evolution of computer technology.

While the annual inflation rate for overall investment has been 3.66 percent for the period 1958 to 1992, computer prices have declined by 19.13 percent per year! Similarly, overall investment grew at 3.82 percent, while investment in computers increased at an astounding 44.34 percent! These familiar facts describe growth in the output of computers. The objective of this paper is to complete the picture by analyzing the growth of computer services as inputs.

In a pioneering paper Bresnahan (1986) has focused on pecuniary externalities arising from the rapid decline in computer prices. Griliches (1992, 1994) has emphasized the distinction between pecuniary and nonpecuniary externalities in the impact of computer investment on growth. This paper is limited to pecuniary externalities or the impact of reductions in computer prices on the substitution of computer services for other inputs. As Griliches (1992) points out, this is an essential first step in identifying nonpecuniary externalities or ‘spill-overs’ through the impact of a decline in computer prices on productivity growth. ^{* *}Brynjolfsson (1993) has proveded a detailed survey of studies of nonpecuniary externalities or ‘spill overs’. Recent studies include those of Brynjolfsson and Hitt (1994a, 1994b) and Lichtenberg (1993).

In two important papers Stephen D. Oliner (1993, 1994) has introduced a model of computer technology that greatly facilitates the measurement of computer services as inputs. In this paper we estimate computer stocks and flows of computer services for all forms of computer investment included in NIPA. We construct estimates of computer services parallel to NIPA data on computer investment by combining these data with information on computer inventories. For example, the International Data Corporation (IDC) Census of Computer Processors includes an annual inventory of processors in the U.S.

In Section 1 we present data on investment in computers and constant quality price indices from NIPA. These data incorporate important innovations in modeling computer technology stemming from a joint study by IBM and the Bureau of Economic Analysis (BEA) completed in 1985. This study utilized a ‘hedonic’ methodology for constructing an econometric model of computer prices that accurately reflects rapid changes in computer technology. This methodology generates an index of computer prices that holds the quality of computers constant.

In Section 2 we present the model of computer services originated by Oliner (1993,1994). This differs in important respects from the model of capital services used in the previous studies of U.S. economic growth surveyed by Jorgenson (1989,1990). The model employed in previous studies is based on the decline in productive capacity with the chronological age of a capital good. Oliner assumes that computers maintain their productive capacity until they are retired. Decline in productive capacity occurs only through removal of used computers from the inventory through retirement.

In Section 3 we construct estimates of stocks of computers that incorporate IDC data on computer inventories and derive the implied flow of computer services. While output of computer investments has grown very rapidly, the input of computer services has grown even faster. The price of these services has declined at 23.22 percent per year over the period 1958 to 1992, while the input of these services has grown at 52.82 percent! This is prima facie evidence of an important role for computer price declines as a source of pecuniary externalities.

In Section 4 we combine computer services with the services of other types of capital to produce a measure of capital input into the U.S. economy. We link this with labor input to obtain the contributions of both inputs to U.S. economic growth, arriving at the growth of productivity as a residual. We find that the contribution of computer services to input into the U.S. economy is far more important than the contribution of computer investments to output. This is a significant step toward resolution of the Solow paradox: ‘We see computers everywhere except in the productivity statistics. ^{* *}Robert M. Solow, quoted by Brynjolfsson (1993). Declines in computer prices generate very sizable pecuniary externalities through the substitution of computer services for other inputs. By contrast Solow focuses on nonpecuniary externalities that would appear as productivity growth.

In Section 5 we conclude that information on inventories of computers is critical in quantifying the role of computer services as inputs. The constant quality price indices for computers incorporated into NIPA are also essential. A price index for computers that reflects only general trends in inflation would result in a highly distorted perspective on the growth of GDP and capital services, especially during the past decade. To capture the contribution of all forms of investment to U.S. economic growth, similar price indices should be included in NIPA for capital goods with rapidly evolving technologies, as proposed by Gordon (1990).

The long term goal should be a unified system of income. product, and wealth accounts, like that proposed by Laurits Christensen and Jorgenson (1973) and Jorgenson (1980). This incorporates capital stocks, capital services, and their prices. Achieving this goal will necessitate much greater elaboration of the accounting system described in Section 3. These accounts would incorporate data on prices and quantities of investment, stocks of assets, and capital services for all forms of capital employed in the U.S. economy.     

ICT-specific technological progress in the United Kingdom

This paper analyses the impact of rapid technological change in the information and communications technology (ICT) sector on economic growth in the United Kingdom. We find that technological progress specific to the ICT sector accounts for around 20–30% of long-run labor productivity growth. We demonstrate that a permanent increase in the growth rate of ICT-specific technological progress will increase the investment expenditure share of GDP but lower the aggregate depreciation rate, while an increase in the return to investment in ICT will increase both the expenditure share and the depreciation rate.     

ICT AND EUROPE's PRODUCTIVITY PERFORMANCE: INDUSTRY-LEVEL GROWTH ACCOUNT COMPARISONS WITH THE UNITED STATES

In this paper we present a new industry-level database to analyze sources of growth in four major European countries: France, Germany, Netherlands and the United Kingdom (EU-4), in comparison with the United States for the period 1979–2000. Aggregate labor productivity growth is decomposed into industry-level contributions of labor quality, ICT and non-ICT capital deepening and TFP. A small set of service industries is mainly responsible for the acceleration in ICT capital deepening in both regions, but their contribution to growth is lower in the EU-4 than in the U.S. TFP in these ICT-intensive services accelerated in the U.S. in the 1990s, but not in Europe. In addition, widespread deceleration in non-ICT capital deepening in the EU-4 has led to a European labor productivity slowdown.     

ICT and Productivity in Europe and the United States Where Do the Differences Come From?

In this paper we analyse labour productivity growth in 51 industriesin European countries and the United States. Using shift-sharetechniques we identify the industries in which the U.S. is leadingmost strongly. With a detailed decomposition analysis we identifywhether the sources of the U.S. advantage are due to fasterproductivity growth, higher industry productivity levels relativeto the country aggregate, different employment shares or fasterchange in employment shares of rapidly growing industries. Theresults show that U.S. productivity has grown faster than inthe EU because of a larger employment share in the ICT producingsector and faster productivity growth in services industriesthat make intensive use of ICT. Wholesale and retail trade andthe financial securities industry account for most of the differencein aggregate productivity growth between the EU and the U.S.(JEL N10, O47, O57)     

Technology Adoption Costs and Productivity Growth: The Transition to Information Technology

Using two panels of U.S. manufacturing industries, this paper estimates capital adjustment costs from 1961 to 1996. I find that from 1974–1983 adjustment costs rose sharply—they more than doubled from about 3% of output to around 7%. Moreover, this increase is specifically associated with a shift to investment in information technology. But such large adoption costs imply that the Solow residual mismeasures productivity growth: Adoption costs are resource costs representing an unmeasured investment. I find that when this investment is included, productivity grew about 0.4% per annum faster than official measures during the 1970's and early 1980's, reducing the size of the productivity “slowdown.” Indeed, estimated productivity growth rates were roughly the same from 1974–1988 as from 1949–1973. Thus technology transitions critically affect productivity growth measurement. Journal of Economic Literature Classification Numbers: O30, O47, E22.     

Information And Communication Technology And The Measurement Of Volume Output And Final Demand - A Five-Country Study

Information and communication technology (ICT) products have undergone rapid technical change. Where quality improvements occur, they should be reflected in official price and quantity indices, otherwise there is a tendency to over-estimate price movements and under-estimate volume changes of ICT products. Statistical offices deal with this issue but the degree and nature of quality-adjustment of price indices of ICT products varies considerably between OECD countries. The present study simulates measurement effects on key economic variables (real output, private final consumption, government expenditure, investment, exports and imports) and productivity, under the assumption that the price indices of ICT products are fully quality-adjusted. The paper draws on a large selection of empirical studies to identify differences between quality-adjusted and unadjusted price changes and uses detailed information from input-output tables to assess their weights in final demand. Effects on GDP and its components are quantified for five selected OECD countries.     

ICT spillovers and productivity in Canada: provincial and industry analysis

Research on the effect of information and communication technology (ICT) on productivity in developed countries is already extensive, but the spillover and time-varying effects of ICT investment across economic activities have been only minimally explored. This paper investigates the impacts of ICT and its spillovers on productivity in Canada, focusing on heterogeneity across provinces and industries over time. The panel data estimation model includes 10 provinces with diverse economic activities for the period 1990–2008, and the two-digit level industries for the period 1981–2008. The findings show that ICT has a positive impact on labour productivity, but the effects vary significantly across provinces, industries, and time. Specifically, while provinces with higher shares of manufacturing and services in their GDP have reaped the benefits of ICT investment, other provinces primarily dependent on natural resources and agriculture are lagging behind. The industry-level analysis also reveals that manufacturing and services industries have benefited from ICT investment much more than primary sector industries. The results further indicate that ICT investment in the USA, a major trading partner, has spilled over to some Canadian provinces and industries and that the overall ICT effects are stabilized in those ICT-intensive provinces and industries.     

ESTIMATES OF INTANGIBLE INVESTMENT BY INDUSTRY AND PRODUCTIVITY GROWTH IN JAPAN

In estimating intangible investment in Japan at the industry level, we find a high intangible investment/gross value added ratio in the information technology (IT) sector and negative growth rates in intangible capital in 13 industries over the decade from 2000. When we examine the impacts of intangible investment on total factor productivity growth, we find a significant and positive effect on total factor productivity growth in the market economy. In a revised estimation that considers intertemporal knowledge spillovers, the estimated rate of return on intangibles in the IT sector is quite high after the IT revolution. The results imply that intangible assets have been underinvested in the IT sector.     

The productivity paradox and the new economy: The Spanish case

This paper studies the impact of the information and communication technologies (ICT) on economic growth in Spain using a dynamic general equilibrium approach. Contrary to previous works, we use a production function with six different capital inputs, three of them corresponding to ICT assets. Calibration of the model suggests that the contribution of ICT to Spanish productivity growth is very relevant, whereas the contribution of non-ICT capital has been even negative. Additionally, over the sample period 1995–2002, we find a negative TFP growth and productivity growth. These results together aim at the hypothesis that the Spanish economy could be placed within the productivity paradox.     

Labour quality in Taiwan: measurement and contribution to economic growth

This article compiles labour input indices that capture both employment changes and quality improvement of labour in Taiwan, from 1994 to 2011. Up to 77.19% of average annual labour input growth is from quality improvement. Further decomposition reveals that the most important source of growth is educational attainment, followed by age structure. Moreover, we find that Taiwan’s average annual GDP growth rate does not result from capital investment but from the contribution of a stable labour input to economic growth. Taiwan is a newly industrialized country, but because of the diminishing returns to capital, the catch-up effect has been slower than hoped. Additional capital investment has a relatively small effect on productivity, and the main source of the continuous economic growth rate is from labour quality, especially from highly skilled human capital. Making good use of these human resources creates a stable source of sustained economic growth.     

Explaining Japan's Unproductive Two Decades

Using industry‐ and micro‐level data, this paper examines why Japan's productivity growth has been slow for such a long time and how it can be accelerated in the future. Japan's capital–gross domestic product ratio continued to increase after 1991, and this increase in the capital–gross domestic product ratio must have contributed to the decline in the rate of return on capital in Japan by decreasing the marginal productivity of capital. On the other hand, Japan's accumulation of information and communication technology capital and intangible investment was very slow. Compared with large firms, which enjoyed an acceleration in the total factor productivity growth in recent years, Japanese small‐ and medium‐sized enterprises were left behind in information and communication technology capital and intangible investment, and their productivity growth has been very low. Furthermore, as large firms expanded their supply chains globally and relocated their factories abroad, research and development spillovers from large firms to small‐ and medium‐sized enterprises seem to have declined.     

Lagging productivity growth: Measurement,technology, and shock effects

One of the most important problems about which economists have professional knowledge is lagging productivity growth. After illustrating some significant developments this paper addresses three questions: (1) To what extent does R&;D activity drive productivity growth, (2) how do alternative measures of productivity affect the conclusions and (3) how did the oil price shocks and the increased openness of the U.S. economy affect productivity growth? After removing the influence of the extremely dynamic computer industry, average manufacturing industry productivity in the U.S. throughout the 80s grew at a disappointing pace. And it didn't improve in the most dynamic industries. But there is good news as well. First, part of the 1970s productivity slump is clearly attributable to the 1973–74 oil price shock. Second and more important, technological innovation does not appear to have lost its power in driving productivity growth forward. Indeed there is evidence of stronger and more consistent productivity effects from R&;D investment during the 1980s, although the exact channels through which R&;D enhances manufacturing sector productivity are left in doubt. Estimates of the role inter-industry technology flows play are sensitive to aggregation and the conventions used to construct the industry price deflators underlying productivity measures.     

Long term implications of the ICT revolution: Applying the lessons of growth theory and growth accounting

How big a boost to long run growth can countries expect from the ICT revolution? I use the results of growth accounting and the insights from a two-sector growth model to answer this question. A two-sector rather than a one-sector model is required because of the very rapid rate at which the prices of ICT products have fallen in the past and are expected to fall in the future. According to the two-sector model, the main boost to growth comes from ICT use, not ICT production. Even a country with zero ICT production can benefit via improving terms of trade. I quantify this effect for 15 European and 4 non-European countries, using the EU KLEMS database. The ICT intensity of production (the ICT income share) is much lower in many European countries than it is in the United States or Sweden. Nevertheless the contribution to long run growth stemming from even the current levels of ICT intensity is substantial: about half a per cent per annum on average in these 19 countries. If ICT intensity reached the same level as currently in the U.S. or Sweden, this would add a further 0.2 percentage points per annum to long run growth.     

CAPITAL AGGREGATION IN THE PRESENCE OF OBSOLESCENCE-INDUCING TECHNICAL CHANGE

The major question addressed is the treatment of capital embodied technical progress. Should Obsolescence be deducted to calculate a net stock, or should quality adjustments be made in each vintage of new capital, or both, or neither? In order to estimate the contribution of new investment to growth it is necessary to use a capital stock where different vintages are weighted in proportion to their marginal products. The commonly used gross capital measures do not do this, because they do not allow for the higher marginal product of more modern capital. Such an allowance for capital embodied technical progress can be made either by quality adjusting new capital or by incorporating obsolescence into the valuation of the old capital (but not both). However, even if new capital incorporates an allowance for improved quality, it will still be necessary to revalue the old capital. Frequently, a reasonable approximation to the net capital stock results from a linear decline in quasi-rents and can be approximated by published estimates of the stock of capital net of straight line depreciation. Steady technical progress will not lead to the commonly used exponential service decline functions. To avoid overestimating the return to investment when technology changes it will be necessary to use information on capital embodied technical change to revalue old capital, rather than to change the price indices for new capital.     

Computer Price Indices and International Growth and Productivity Comparisons

Methodologies to derive price indices for information and communication technology (ICT) products vary between national statistical offices. This may lead to significant differences in measured price changes for these products and there has been concern about the international comparability of volume growth rates of GDP between several OECD countries. This article discusses the possible consequences for measures of economic growth of replacing one set of price indices by another one in the framework of national accounts. It is argued that the issue of ICT deflators cannot be dealt with in isolation and several other factors have to be taken into account, in particular whether ICT products are final or intermediate products, whether they are imported or domestically produced and whether national accounts are set up with fixed or chain weighted index numbers. Overall, results point to modest effects at the aggregate GDP level but may be more significant when it comes to component measures such as volume growth of investment, or of output in a particular industry.     

Project Matching and Overcapacity in China

Based on the features of China’s project investment, we consider the formation of production capacity as a matching behavior between local governments and investment enterprises. Using the search and matching model, we illustrate that the excess capacity in China mainly results from the asymmetry between the gains from and contribution to the project matching: The capacity will be excessive when the proportion of local governments’ return exceeds its contribution to the project, and the more unbalanced the return–contribution relationship, the more severe the overcapacity. Meanwhile, we test this theoretical prediction based on a quasi-natural experiment: the reform of administrative approval system. The empirical results show that the reduction of the local governments’ return–contribution ratio will significantly raise the capacity utilization rate and mitigate the overcapacity. Industry-specific regression results further indicate that governments’ return–contribution asymmetry is more prominent in industries dominated by state-owned enterprises, high-monopoly industries, heavy industries, and industries with serious overcapacity. This paper offers a novel mechanism of overcapacity, a theoretical criterion for judging optimal capacity, and some new regulatory tools with the micro foundation.