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on Efficiency and Productivity |
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Issue of 2019‒11‒04
eight papers chosen by |
| By: | Ksenia Gonchar (National Research University Higher School of Economics, Moscow); Maria Kristalova (Bremen University and Friedrich-Schiller-University Jena) |
| Abstract: | This paper studies how innovation strategies of Russian manufacturing firms affect various features of firm performance. A multi stage model is used, which relates the firm's decision to undertake R&D to its innovation output, technical efficiency, labor productivity, and growth. We also include imports into the knowledge production function, because catching up economies may adopt technologies embodied in imported hardware. Additionally, we link productivity and innovation output to survival. We find that both types of knowledge input - R&D and imports - strongly determine innovation. Innovations yield the strongest performance return in the case of catching up to technological frontier. Product innovation is more beneficial than process innovation in all performance features except for labor productivity. However, higher efficiency does not improve the growth rates or survival time of manufacturing firms. Taken together, these results show that innovation is not uniformly rewarded across all features of firm performance. |
| Keywords: | innovation, productivity, growth, survival, Russia |
| JEL: | C30 D24 O30 |
| Date: | 2019–02–25 |
| URL: | http://d.repec.org/n?u=RePEc:jrp:jrpwrp:2019-001&r=all |
| By: | Camilla Mastromarco (Dipartimento di Scienze dell'Economia, Universita degli Studi del Salento.); Lèopold Simar (Institut de Statistique, Biostatistique et Sciences Actuarielles, Universite Catholique de Louvain.); Valentin Zelenyuk (School of Economics and Centre for Efficiency and Productivity Analysis (CEPA) at The University of Queensland, Australia) |
| Abstract: | In this paper, we merge two streams of literature: nonparametric methods to estimate frontier efficiency of an economy, which allows us to develop a new measure of output gap, and nonparametric methods to estimate probability of an economic recession. To illustrate the new framework we use quarterly data for Italy from 1995 to 2019, and find that our model, using either nonparametric or the linear probit model is able to provide useful insights |
| Keywords: | Output Gap, Robust Nonparametric Frontier, Generilized Nonparametric Quasi-Likelihood Method, Italian recession. |
| JEL: | C5 C14 C13 C32 D24 E37 O4 |
| URL: | http://d.repec.org/n?u=RePEc:qld:uqcepa:141&r=all |
| By: | Schmöller, Michaela |
| JEL: | E20 E24 E60 O40 O41 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:vfsc19:203598&r=all |
| By: | Barany, Zsofia; Siegel, Christian |
| JEL: | O41 O33 J24 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:vfsc19:203596&r=all |
| By: | Bräuer, Richard; Mertens, Matthias; Slavtchev, Viktor |
| Abstract: | This study analyses empirically the effects of import competition on firm productivity (TFPQ) using administrative firm-level panel data from German manufacturing. We find that only import competition from high-income countries is associated with positive incentives for firms to invest in productivity improvement, whereas import competition from middle- and low-income countries is not. To rationalise these findings, we further look at the characteristics of imports from the two types of countries and the effects on R&D, employment and sales. We provide evidence that imports from high-income countries are relatively capital-intensive and technologically more sophisticated goods, at which German firms tend to be relatively good. Costly investment in productivity appears feasible reaction to such type of competition and we find no evidence for downscaling. Imports from middle- and low-wage countries are relatively labour-intensive and technologically less sophisticated goods, at which German firms tend to generally be at disadvantage. In this case, there are no incentives to invest in innovation and productivity and firms tend to decline in sales and employment. |
| Keywords: | productivity,multi-product firms,import competition |
| JEL: | D22 D24 F10 F14 F60 F61 L25 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:iwhdps:202019&r=all |
| By: | Mette Asmild (Department of Food and Resource Economics, University of Copenhagen); Arne Henningsen (Department of Food and Resource Economics, University of Copenhagen); Dorte Kronborg (Center for Statistics, Department of Finance, Copenhagen Business School); Anders Rønn-Nielsen (Center for Statistics, Department of Finance, Copenhagen Business School) |
| Keywords: | DEA, Returns to scale, Hypothesis test, Inference |
| JEL: | C12 C14 C44 C61 D24 |
| Date: | 2019–10 |
| URL: | http://d.repec.org/n?u=RePEc:foi:wpaper:2019_07&r=all |
| By: | Kumari, Priyanka; Singh, K M; Kumar, Anjani; Ahmad, Nasim |
| Abstract: | The present investigation has been carried out to analyze the agricultural output growth and contribution of different components to the output growth in the state of Bihar in the recent past decades. Results of the analysis depicted mixed trend in growth rates of area under different crops in the state. The production growth has been found positive for most of the crops due to enhancement of productivity of the crops. Adoption of modern technology like; use of fertilizers, irrigation and quality seeds helped augmenting the productivity. Net sown area and net irrigated area observed declining trend which may be major concern for increasing agricultural production in Bihar. Researcher efforts therefore need to intensify further development of high yielding varieties suitable for different agro-climatic zones of the state. Shift of cropping pattern towards potato, sugarcane and other horticultural crops has also attributed to the output growth. It is alarming that the growth rates of productivity have declined for overall period for most of the crops except wheat, Pegionpea (arhar), oil seeds and potato as compared to period-II under investigation. This is somewhat matter of great concern, when all efforts are towards increasing yields with the help of implementation of new cultivation technologies. This situation warrants the researchers and policy makers and stakeholders to identify the factors responsible for low productivity as there is negligible possibility to enhance arable area in the state, only the enhancement in yield can contribute to the agricultural growth of the state. |
| Keywords: | Agricultural output, Cropping pattern, Decomposition, Trend analysis, area, Production, Productivity |
| JEL: | Q1 Q11 Q18 |
| Date: | 2019–08–14 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:96678&r=all |
| By: | Gornig, Martin; Schiersch, Alexander |
| JEL: | R11 R12 R15 D24 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:vfsc19:203597&r=all |