Measure Of Technological Progress Research Articles

Forschungs- und Entwicklungsaktivitäten in der Potenzialschätzung berücksichtigen

AbstractPotential output is a measure of the longer-term production possibilities of an economy. Since this quantity cannot be observed directly, it must be determined on the basis of assumptions from existing data. The use of a production function was established in the European Commission’s procedure for calculating potential output. However, it is important to capture all drivers of economic growth. In the current EU procedure, total factor productivity (TFP), which is interpreted as a measure of technological progress, is assumed to be exogenous. This means that key drivers of economic growth, in particular research and development (R&D) activities, are not explicitly taken into account. An extension of the production function approach can be derived from the theory of endogenous growth. This would improve the theoretical basis of the potential output estimates.

Technological change and inequality in the very long run

Abstract In this paper we investigate the impact of technological change on inequality in the presence of a landed elite using a standard unified growth model. We measure inequality by the ratio between land rent and wages and show that, before the onset of the fertility transition, technological progress increased inequality directly through land-biased technological change and indirectly through increasing population growth. The fertility transition and the child quantity-quality trade-off eventually disabled the Malthusian mechanism, and technological progress triggered education and benefited workers. If the elasticity of substitution between land and labor is sufficiently high, the rent-wage ratio declines such that inequality is hump-shaped in the very long run. We use the publication of new farming book titles as a measure of technological progress in agriculture, and provide evidence for technology-driven inequality in Britain between 1525 and 1895. We confirm these results for a panel of European countries over the period 1265–1850 using agricultural productivity as a measure of technology. Finally, using patents in the period 1800–1980, we find a technology-driven inequality reversal around the onset of the fertility transition.

Technological Change and Inequality in the Very Long Run

In this paper we investigate the impact of technological change on inequality in the presence of a landed elite using a standard unified growth model. We measure inequality by the ratio between land rent and wages and show that, before the onset of the fertility transition, technological progress increased inequality directly through land-biased technological change and indirectly through increasing population growth. The fertility transition and the child quantity-quality trade-off eventually disabled the Malthusian mechanism, and technological progress triggered education and benefited workers. If the elasticity of substitution between land and labor is sufficiently high, the rent-wage ratio declines such that inequality is hump-shaped in the very long run. We use the publication of new farming book titles as a measure of technological progress in agriculture, and provide evidence for technology-driven inequality in Britain between 1525 and 1895. We confirm these results for a panel of European countries over the period 1265–1850 using agricultural productivity as a measure of technology. Finally, using patents in the period 1800–1980, we find a technology-driven inequality reversal around the onset of the fertility transition.

Measuring the Diffusion of Technologies Through International Trade

Technological advancements affect economic growth, income distribution and levels of unemployment. However, quantifying the pace of technological diffusion is problematic. This paper develops a new measure of technological progress by estimating the high-skill content of imports using industry-level, bilateral trade data. Intuitively, during periods of trade liberalization, a higher skill content embodied within imports will lead to a faster change in the arrival rate of new technologies. Trade accelerated since the 1980s and with that came a diffusion of new technologies into developing countries. By utilizing the industry-level trade data in conjunction with the high-skill factor content of each industry, a measure of technological diffusion is developed using a theoretically consistent gravity model. This measure is highly correlated with other measures of technological progress and provides a new data set for a large number of both developed and developing countries. How the high-skill content of imports increased is analyzed for countries across the development spectrum. This measure of technological progress is applied to income inequality. It significantly increases inequality, consistent with theoretical expectations, and provides an additional avenue in how to measure technological progress.

Effects of R&D Subsidies on Regional Economic Dynamics: Evidence from Chinese Provinces

We investigate the impact of research and development (R&D) subsidies on R&D inputs of large- and medium-sized firms and on additional innovation and economic activities in Chinese provinces. A panel vector autoregressive (VAR) model and corresponding impulse response function (IRF) analysis allow us to differentiate between direct and indirect effects, which add up to total effects. We find that an increase of R&D subsidies significantly decreases private R&D investments, although there is a significant positive effect on the R&D personnel employed in firms. We interpret these findings as a partial crowding-out effect because public funds substitute some private funds while total R&D inputs still increase. Complementarily, we find a positive secondary effect on the provincial patent activity, our measure of technological progress. Interestingly, we also find potentially unintended effects of R&D subsidies on increases in the investment rate in physical capital and residential buildings. Although R&D subsidies fail to incentivise private R&D expenditures, firms increase total R&D inputs, and provincial economies benefit from secondary effects on technological progress and capital deepening.

The Contribution of Wheat to Australian Agriculture from 1861 to 1939

The influence of agriculture on Australia's nineteenth and twentieth century economic development is well known. While wool's contribution is rightly celebrated, the contribution of agricultural crops has received less attention. This paper focuses on one major staple, wheat, from 1861 to 1939. Both patent data and a new measure of technological progress, the cumulative number of wheat varieties tested for local adoption, are used to quantify the contribution of agricultural innovation to growth. We find innovation in this sector made an important contribution to the growth of total factor productivity over the period.

Correction for variations in capacity utilization in the measurement of productivity growth: A non-parametric approach

The multifactor productivity growth estimate published by statistical agencies should be corrected for the effect of the short run variations in capacity utilization for such estimate to be a measure of technological progress. But such correction is not normally made as the rate of capacity utilization is often not observed. This paper develops a nonparametric approach for adjusting multifactor productive growth measure for variation in capacity utilization over time. In the approach developed here, the capital utilization measure is derived from the economic theory of production and is estimated by comparing the ex-post return with the ex-ante expected return on capital. The approach offers a practical solution that can be used by statistical agencies to adjust for capacity utilization in their multifactor productivity growth measure. The nonparametric approach is implemented using the data for the manufacturing sector from the Canadian Productivity Program of Statistics Canada, and is found to correct for the bias from the variation in capacity utilization in that sector.

Technological change in industrial development. A case study of the Korean man-made fibres industry

This research is concerned with the role of technological change in the process of industrial development. The principal focus is on the man-made fibres sector and the role of technological change as a driving force for industrial development. Different measures of technological change are considered, and both quantitative and qualitative approaches to its analysis are discussed. Among these, total factor productivity (TFP) is introduced as a convenient measure of technological progress and the measurement is used to consider data in the Korean context. The contribution of technological change is considered in terms of technology spillovers from the man-made fibres sector to other realms of the economy.

An empirical evaluation of the technology cycle time indicator as a measure of the pace of technological progress in superconductor technology

The technology cycle time indicator (TCT) is a new measure of technological progress. The TCT is the median age of the patents cited on the front page of a patent document. The measure assumes that the more recent the age of the cited patents, the more quickly one generation of inventions is replacing another. The main purpose of the study was to evaluate the TCT in a dynamic context to determine how accurately it measures the pace of technological progress. This study found the trend in TCT changed abruptly from gradually increasing (slowing in cycle time) to steadily decreasing (speeding up in cycle time) following the discovery of high-temperature superconductors. The methodology prescribed in this study could potentially be used in assessing the pace of progress for different technologies or different nations in the same technology.

Short Run Comovement, Persistent Shocks and the Business Cycle / Eine empirische Analyse der Wirkung kurz- und langfristiger Schocks im Konjunkturzyklus

Summary Following standard real business cycle theory, long run economic growth and short run business cycle fluctuations are attributed to a series of productivity shocks propagated by the economic system which is assumed to be in a rational expectations equilibrium. Characterizing the technical progress as the common stochastic trend we are able to investigate the short and long run effects of the productivity shocks using a cointegrated system. From the empirical analysis it emerges that the long run relationship between the system variables can be traced back to a single permanent component which is interpreted as a measure of technological progress. The short run dynamic impact of the permanent innovations is investigated using the empirical impulse response functions. It turns out that the permanent shocks are able to explain a substantial portion of business cycle fluctuations.

Technology Adoption over the Life Cycle and Aggregate Technological Progress

Technology becomes useful only when individuals adopt it for productive activity. The manner in which adoption occurs is therefore important for a complete understanding of the evolution of technological change. We study a model with exogenously occurring technological progress and endogenous adoption of it. Individuals with N-period lives optimally allocate their time between leisure, work and adoption of new technology. We show that optimal behavior is characterized by a sequence of four phases of life which, described in their order of occurrence, are: (1) adoption only (schooling); (2) work and adoption (career path); (3) work but no adoption (end-of-work-life easing); (4) no work or adoption (retirement). The presence of the third phase, a period in which older workers choose not to adopt new technology, has several implications for the effects of changes in aggregate exogenous technology. Among these is the implication that a wave of innovation will have a smaller effect when the number of workers in this phase is relatively large. This is tested using patent data as a proxy for innovation and the Solow residual as a measure of technological progress; some support for this proposition is found. The model also implies that older (third phase) workers will appear more productive because each hour of non-leisure time will be devoted entirely to productive work, rather than being divided between work and technology adoption time. The data provides some support for this proposition as well: measured productivity is positively correlated with the relative size of the oldest cohort of workers.