Total factor productivity, catch-up and technological congruence in Italy, 1861–2010

2021 ◽  
pp. 231-257
Author(s):  
Cristiano Antonelli ◽  
Christophe Feder
2017 ◽  
Vol 1 (4) ◽  
pp. 175
Author(s):  
Prosenjit Das

Aim: India has emerged as one of the most favoured destinations in the global Information Technology (IT) outsourcing market. On the other hand, the IT industry has been playing an instrumental role in transforming India’s image from a low income-backward nation to a knowledge-based economy.  Furthermore, the role of IT industry has been pivotal in putting India on a higher growth path. In addition, India’s IT industry has been showing robust performance in revenue earning, particularly in export revenue. However, the performance of this industry is likely affected by some recent global phenomena, such as 2008’s subprime crisis originated in the US, uncertainties in changes in H1-B visa rules, Britain’s exit from the EU, automation etc. There are other factors, like exchange rate volatility, emerging competition from other low-cost outsourcing destination countries, are also posing threat to India’s IT-outsourcing business. Against this backdrop, it is crucial to analyse the sustainability of performance of Indian IT industry. Thus, the present study aims at assessing the performance of Indian IT industry and evaluating the determinants of performance thereafter.Design / Research methods: To realize the objectives of the study, firm level data has been collected from the Centre for Monitoring Indian Economy (CMIE) Prowess database. For empirical analysis, we have applied a two-stage method. In the first-stage, we have used Data Envelopment Analysis (DEA) based Malmquist Productivity Index (MPI) to evaluate the Total Factor Productivity Growth (TFPG) of Indian IT industry during the period from 2004-05 to 2014-15. For this purpose, a balanced panel consists of 70 IT firms has been considered. Further, the TFPG has been decomposed into three components, viz. Catch-up, frontier-shift, and scale efficiency change (SEC). Consequently, in the second-stage, three random-effects panel regression models are considered to investigate the determinants of TFPG, catch-up, and frontier-shift separately. Conclusions / findings: During the study period, the average TFP and frontier-shift has been improved. On the other hand, catch up effect is found to have declined. The variables, such as export intensity, salaries and wages intensity have positive and statistically significant impact on the catch-up and frontier-shift. Export intensity has positive impact on TFPG. Age of the firms has positive impact on catch-up and TFPG. Salaries and wages intensity has positive impact on TFPG. On an average, the firms which spent on research and Development (R&D) have experienced improvement in TFPG and frontier-shift. The public limited firms performed better than their private counterparts in terms of catch-up, frontier-shift, and TFPG. The non-group firms have performed better than the group firms in case of catch-up. On the other hand, on an average, the firms exhibiting decreasing Returns to Scale (DRS) are found to have registered deterioration in catch-up and TFPG with respect to the benchmark firms which are exhibiting Constant Returns to Scale (CRS). The firms exhibiting Increasing Returns to Scale (IRS) have shown improvement in catch-up and TFPG over the benchmark CRS firms. The impact of the US subprime crisis has been negative on catch-up, frontier-shift, and TFPG. The firms, which have spent on royalty, have experienced improvement in catch-up and TFPG. Originality / value of the article: So far in our knowledge, not so many studies of this kind have been done in the arena of empirical research pertains to the IT industry, especially in a developing country like India. Moreover, we have not found any study that covers the span of the dataset considered in the present study. In addition to this, the present study has employed a random-effects panel model to accommodate a number of time-invariant dummy variables which would not be possible in case of a fixed-effects panel model incorporated by some previous studies of this genre.Implications of the research: The identification of the determinants of TFPG and its components would help the stakeholders and policy makers of the IT industry to formulate appropriate policies which could mitigate the risks faced by the industry on one hand, and stimulate the forces that would enhance the growth of this industry on the other. For instance, to mitigate future risks, Indian IT industry should reduce its dependence on the US and UK markets. Besides, it should explore new markets in the EU, and other emerging economies where opportunities are plenty. To maintain India’s robust global position in the long run, Government of India should play the key role in providing world class infrastructure and telecommunication facilities to its IT industry. In addition to this, Government needs to rationalise and simplify the existing Indian labour law to facilitate the business of IT industry. Various stakeholders along with the Government should put necessary efforts to develop the domestic IT market as there exists ample of opportunities in future. Keywords: information technology industry, data envelopment analysis, Malmquist productivity index, random-effects model, total factor productivity, catch-up, frontier-shift, India. JEL: C23, C61, L86, O47


2012 ◽  
Vol 1 (1) ◽  
pp. 1 ◽  
Author(s):  
Carlos Alberto Zuniga Gonzalez

This paper develops a new measure of total factor productivity growth in agricultural Production which incorporates Bio Economic components effects.The new measure is called the Bio Economic-Oriented Total Factor Productivity (BTFP) index, and incorporates components of Bio Economic as liquid biofuels. BTFP measure changes in Bio Economic efficiency and can be decomposed into bio economy efficiency change (BEC), and Bio Economic technological change (BTC) components.An empirical analysis, involving 7 Central American countries-level during 1980-2007, is provided using DEA methods. The results have shown a positive annual growth in bio economy total factor productivity of 1.1 percent.  This change is explained by 0.03 percent per year in the bio economy efficiency change (or bio economy catch-up) and bio economy technical change (or bio ethanol frontier-shift) is providing 0.09 percent.


2019 ◽  
pp. 262-284
Author(s):  
Khuong Vu ◽  
Kris Hartley

The term ‘nation learning’ describes consistent and strategic cross-sector efforts to identify pathways towards economic catch-up. This chapter examines the global dynamics of national-level catch-up between 1995 and 2015 to gain insights into the relevance of nation-learning efforts. Over this period, most developing Asian countries made significant progress on catch-up. Focusing on their experience, the study finds capital accumulation and growth in total factor productivity to be crucial determinants of catch-up performance. However, some countries have lagged in promoting capital accumulation (Pakistan, Malaysia, and the Philippines) and total factor productivity (Vietnam, Indonesia, and Bangladesh). Focusing on these determinants, the chapter generates insights into relevant aspects of nation-learning efforts. Enablers of nation learning include pressures, leadership vision, and absorptive capacity; obstacles include the costs of learning and ‘status-quo bias’.


Author(s):  
Shixiong Cheng ◽  
Jiahui Xie ◽  
De Xiao ◽  
Yun Zhang

Since air pollution is an important factor hindering China’s economic development, China has passed a series of bills to control air pollution. However, we still lack an understanding of the status of environmental efficiency in regard to air pollution, especially PM2.5 (diameter of fine particulate matter less than 2.5 μm) pollution. Using panel data on ten major Chinese city groups from 2004 to 2016, we first estimate the environmental efficiency of PM2.5 by epsilon-based measure (EBM) meta-frontier model. The results show that there are large differences in PM2.5 environmental efficiency between cities and city groups. The cities with the highest environmental efficiency are the most economically developed cities and the city group with the highest environmental efficiency is mainly the eastern city group. Then, we use the meta-frontier Malmquist EBM model to measure the meta-frontier Malmquist total factor productivity index (MMPI) in each city group. The results indicate that, overall, China’s environmental total factor productivity declined by 3.68% and 3.49% when considering or not the influence of outside sources, respectively. Finally, we decompose the MMPI into four indexes, namely, the efficiency change (EC) index, the best practice gap change (BPC) index, the pure technological catch-up (PTCU) index, and the frontier catch-up (FCU) index. We find that the trend of the MMPI is consistent with those of the BPC and PTCU indexes, which indicates that the innovation effect of the BPC and PTCU indexes are the main driving forces for productivity growth. The EC and FCU effect are the main forces hindering productivity growth.


Sign in / Sign up

Export Citation Format

Share Document