Directed technological change and productivity growth: the Italian evidence 1861-2010

Author(s):  
Cristiano Antonelli ◽  
Federico Barbiellini Amidei ◽  
Christophe Feder
2018 ◽  
Vol 67 (9) ◽  
pp. 1792-1815 ◽  
Author(s):  
Joko Mariyono

PurposeThe purpose of this paper is to investigate the productivity of rice production by decomposing the growth of total factor productivity (TFP) into four components: technological change, scale effects, technical and allocative efficiencies.Design/methodology/approachThis study employed an econometric approach to decompose TFP growth into four components: technological change, technical efficiency, allocative efficiency and scale effect. Unbalanced panel data used in this study were surveyed in 1994, 2004 and 2014 from 360 rice farming operations. The model used the stochastic frontier transcendental logarithm production technology to estimate the technology parameters.FindingsThe results indicate that the primary sources of TFP growth were technological change and allocative efficiency effects. The contribution of technical efficiency was low because it grew sluggishly.Research limitations/implicationsThis study has several shortcomings, such as very lowR2and the insignificant elasticity of labour presented in the findings. Another limitation is the limited time period panel covering long interval, which resulted in unbalanced data.Practical implicationsThe government should improve productivity growth by allocating more areas for rice production, which enhances the scale and efficiency effects and adjusting the use of capital and material inputs. Extension services should be strengthened to provide farmers with training on improved agronomic technologies. This action will enhance technical efficiency performance and lead to technological progress.Social implicationsAs Indonesian population is still growing at a significant rate and the fact that rice is the primary staple food for Indonesian people, the productivity of rice production should increase continually to ensure social security at a national level.Originality/valueThe productivity growth is decomposed into four components using the transcendental logarithm production technology based on farm-level data. The measure has not been conducted previously in Indonesia, even in rice-producing countries.


2010 ◽  
Vol 16 (2) ◽  
pp. 273-285 ◽  
Author(s):  
Laurent Botti ◽  
Walter Briec ◽  
Nicolas Peypoch ◽  
Bernardin Solonandrasana

2013 ◽  
Vol 19 (1) ◽  
pp. 116-143 ◽  
Author(s):  
Tailong Li ◽  
Shiyuan Pan ◽  
Heng-fu Zou

In a knowledge-based growth model where skilled workers are used in innovation and production, skill-biased technological change may lower average R&D productivity via an innovation possibilities frontier effect that eliminates scale effects. We show that skill-biased technological change increases the skill premium even if the elasticity of substitution between skilled and unskilled workers is less than two. Trade between developed countries promotes skill-biased technological change, thus raising wage inequality. Trade between developed and developing countries has differing effects: it induces relatively skill-replacing technological change and lowers wage inequality in the developed country but has the opposite effects in the developing country. Finally, we show that trade can stimulate or hurt economic growth.


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