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| Content Provider | Springer Nature Link |
|---|---|
| Author | Dal Bianco, Silvia |
| Copyright Year | 2015 |
| Abstract | This paper employs the distribution dynamics framework for assessing labour productivity convergence, in the period 1980–1995, among 28 developed and developing countries, in different manufacturing compartments, identified as according to their research and development intensity. Three competing hypotheses are considered: absolute, conditional and club convergence. The key result of the analysis is twofold. First, consistently with very recent evidence, absolute convergence is found in manufacturing as a whole. Second, convergence tendencies are sector specific. In particular, club convergence characterizes traditional and medium- technology compartments, while the absolute one qualifies high-tech productions. Overall, these findings support the view that cross-country labour productivity convergence might be hindered by the sub-optimal structural reallocation from nonconvergence to convergence activities. Moreover, as the clustering dynamics in traditional and medium-tech sectors is related either to physical capital stock or technological development, laggard economies should purse ad hoc catching-up strategies. Finally, the result of high tech provides supportive evidence for the theory of dynamic comparative advantages. Thus, it seems desirable that emerging countries enter into technology-intense markets and that they develop the necessary capabilities for exploiting such endogenous advantages. |
| Starting Page | 623 |
| Ending Page | 659 |
| Page Count | 37 |
| File Format | |
| ISSN | 03777332 |
| Journal | Empirical Economics |
| Volume Number | 50 |
| Issue Number | 2 |
| e-ISSN | 14358921 |
| Language | English |
| Publisher | Springer Berlin Heidelberg |
| Publisher Date | 2015-02-28 |
| Publisher Place | Berlin, Heidelberg |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Convergence Clustering Manufacturing industries Distribution dynamics Econometrics Statistics for Business/Economics/Mathematical Finance/Insurance Economic Theory/Quantitative Economics/Mathematical Methods |
| Content Type | Text |
| Resource Type | Article |
| Subject | Statistics and Probability Social Sciences Economics and Econometrics |
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