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Abstract
As it takes time and effort to learn how to fully utilise new technology and realise its maximum potential productivity gain, adoption of new technology tends to reduce productivity temporarily, even though the potential productivity gain in the long run outweighs this short run loss. This paper points to such “learning cost” in technology upgrading as a potential explanation of the following two “productivity puzzles” reported in the Information Technology (IT) literature and in the studies of East Asian economic growth. First, in the 1980s, US companies made enormous IT investments, but little productivity gain was observed. Second, Total Factor Productivity (TFP) growth of “Newly Industrialising Countries” (NICs) in East Asia was mediocre in spite of the impressive investment drive in those countries. A simple model of optimal intervals for technology upgrading with learning cost is developed. This model predicts that a company with higher frequency in technology upgrading will tend to have higher market value even with lower current profitability. An empirical study using unbalanced panel data of 1,031 US companies from 1986 to 1995 supports this prediction. Extending the scope from firm-level to industry-level, the paper estimates the magnitude of industry-wide learning-by-doing effects using annual data on 15 sub-industries in the Japanese machinery manufacturing sector from 1955 to 1990. The results show that industry-wide learning-by-doing was strong in low-tech industries where technological change was relatively slow, while it was insignificant in high-tech industries which experienced rapid technological evolution. It is also observed in the US and Japanese manufacturing industries that TFP growth tends to decrease with faster capital accumulation. This negative correlation is reproduced in simulations based on the extended model of learning cost. Apprendre à pleinement utiliser une nouvelle technologie et achever son gain potentiel de productivité demandent du temps et des efforts. Pour ces raisons, l’adoption d’une nouvelle technologie tend à baisser temporairement la productivité même si le gain de productivité à long terme dépasse cette perte à court terme. Cette étude présente l’existence des “coûts d’apprentissage” comme une explication potentielle à deux paradoxes de la productivité relevés dans les études concernant les technologies informatiques ainsi que celles portant sur la croissance économique en Asie de l’Est. Premier paradoxe: en dépit des investissements énormes par les firmes américaines pendant les années 80, il en a résulté peu de gain de productivité. Second paradoxe: la croissance de la productivité totale des facteurs (TFP) dans les nouveaux pays industrialisés (NPI) de l’Asie de l’Est a été médiocre malgré leur taux d’investissements exceptionnellement élevé. On modélise, dans cette étude, l’adoption de nouvelles technologies sous l’hypothèse des coûts d’apprentissage, et on obtient, dans ce cadre, son intervalle optimal. Le modèle prévoit que l’adoption technologique plus fréquente tend à augmenter la valeur de marché des firmes même si elle baisse la rentabilité courante. A l’aide des données de panel sur 1031 firmes américaines pour la période 1986-95, une étude économétrique nous permet de confirmer la prévision du modèle. Pour étendre l’analyse, on estime aussi l’amplitude des effets de l’apprentissage par pratique (learning by doing) au niveau des branches industrielles. Pour ce faire, on utilise les données annuelles (1955-1990) pour 15 branches japonaises fabriquant des machines. Les résultats montrent que l’apprentissage par pratique est plus important pour le gain de productivité dans les industries à basse technologie où les changements techniques sont relativement lents, alors qu’il occupe une place non significative dans les industries à haute technologie ayant connu une évolution technologique rapide. Par ailleurs, on trouve aussi que le taux de croissance de TFP tend à diminuer avec une accumulation de capital plus rapide dans les industries manufacturières américaines et japonaises. Cette corrélation négative est aussi reproduite par les simulations basées sur le modèle élargi des coûts d’apprentissage.
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Cited by:
- Khayyat, Nabaz T. & Lee, Jongsu & Lee, Jeong-Dong, 2014.
"How ICT Investment Influences Energy Demand in South Korea and Japan?,"
MPRA Paper
55454, University Library of Munich, Germany.
- Elena Ketteni, 2009.
"Information technology and economic performance in U.S industries,"
Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 42(3), pages 844-865, August.
- Yuxi Chen & Mengting Zhang & Chencheng Wang & Xin Lin & Zhijie Zhang, 2023.
"High-Tech Industrial Agglomeration, Government Intervention and Regional Energy Efficiency: Based on the Perspective of the Spatial Spillover Effect and Panel Threshold Effect,"
Sustainability, MDPI, vol. 15(7), pages 1-29, April.
- Elena Ketteni & Theofanis Mamuneas & Panos Pashardes, 2013.
"ICT and Energy Use: Patterns of Substitutability and Complementarity in Production,"
Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 7(1), pages 63-86, June.
More about this item
Keywords
productivité totale des facteurs;
technologie;
technology;
total factor productivity;
All these keywords.
JEL classification:
- D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
- F43 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Economic Growth of Open Economies
- O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
- O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
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