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on Efficiency and Productivity |
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Issue of 2012‒09‒09
four papers chosen by |
| By: | Kox, Henk L.M.; Leeuwen, George van |
| Abstract: | European business services has witnessed about two decades of virtual productivity stagnation. The paper investigates whether this is caused by weak dynamic market selection. The time pattern of scale-related inefficiencies is used as an indicator for the effectiveness of market selection. We use a DEA method to construct the productivity frontier by sub-sector and size class, for business services in 13 EU countries. From this we derive scale economies and their development over time. Between 1999 and 2005 we observe a persistence of scale inefficiencies and X-inefficiencies , with scale efficiency falling rather than growing over time. This indicates malfunctioning competitive selection. The time pattern of inefficiencies is significantly explained by regulatory policies that hamper entry and exit dynamics and labour adjustment, and by a lack of import penetration. The results suggest that policy reform and more market openness will have positive productivity effects. This holds for business services itself, but also wider, because of business services’ products are widely used as intermediary inputs in other parts of the European economy. |
| Keywords: | competition; scale economies; market contestability; regulation; EU; productivity |
| JEL: | L11 L8 D24 |
| Date: | 2012–09 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:41016&r=eff |
| By: | Andor, Mark; Hesse, Frederik |
| Abstract: | Based on the seminal paper of Farrell (1957), researchers have developed several methods for measuring efficiency. Nowadays, the most prominent representatives are nonparametric data envelopment analysis (DEA) and parametric stochastic frontier analysis (SFA), both introduced in the late 1970s. Since decades, researchers have been attempting to develop a method which combines the virtues - both nonparametric and stochastic - of these oldies. The recently introduced Stochastic non-smooth envelopment of data (StoNED) by Kuosmanen and Kortelainen (2010) is a promising method. This paper compares the StoNED method with the two oldies DEA and SFA and extends the initial Monte Carlo simulation of Kuosmanen and Kortelainen (2010) in two directions. Firstly, we consider a wider range of conditions. Secondly, we also consider the maximum likelihood estimator (ML) and the pseudolikelihood estimator (PL) for SFA and StoNED, respectively. We show that, in scenarios without noise, the rivalry is still between the oldies, while in noisy scenarios, the nonparametric StoNED PL now constitutes a promising alternative to the SFA ML. -- |
| Keywords: | efficiency,stochastic non-smooth envelopment of data (StoNED),data envelopment analysis (DEA),stochastic frontier analysis (SFA),monte carlo simulation |
| JEL: | C1 C5 D2 L5 Q4 |
| Date: | 2012 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:cawmdp:60&r=eff |
| By: | Alexander Vogel (Leuphana University Lueneburg, Germany); Joachim Wagner (Leuphana University Lueneburg, Germany) |
| Abstract: | This paper uses newly available data for German business services firms to test a hypothesis derived by Bustos (AER 2011) in a model that explains the decision of heterogeneous firms to export and to engage in R&D. Using a non-parametric test for first order stochastic dominance it is shown that, in line with this hypothesis, the productivity distribution of firms with exports and R&D dominates that of exporters without R&D, which in turn dominates that of firms that neither export nor engage in R&D. These results are in line with findings for firms from manufacturing industries. The model, therefore, seems to be useful to guide empirical work on the relation between exports, R&D and productivity for services firms, too. |
| Keywords: | Exports, R&D, productivity, business services firms, Germany |
| JEL: | F14 |
| Date: | 2012–08 |
| URL: | http://d.repec.org/n?u=RePEc:lue:wpaper:247&r=eff |
| By: | Yuezhou Cai, Aoife Hanley |
| Abstract: | Should inputs such as bank finance affect innovation in BRICS vs. developed countries similarly? Arguably these elasticities may depend on a country’s economic progress (Gerschenkron, 1962; Liu and White, 2001). Applying a combination of DEA and Tobit to a sample of 22 countries, we show how innovation (measured patents, scientific publications and high-tech sectoral output) responds favourably to private-sector R&D. No significant differences are recorded for BRICS countries. Differences emerge between BRICS and non-BRICS for the elasticity of innovative efficiency to banking inputs |
| Keywords: | BRICS countries, National Innovation System (NIS), innovation, DEA |
| JEL: | O30 |
| Date: | 2012–08 |
| URL: | http://d.repec.org/n?u=RePEc:kie:kieliw:1788&r=eff |