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This paper studies empirically the relationship between the sources of knowledge, innovation and productivity in Knowledge Intensive Business Services using French micro data and sheds some new light on the production of knowledge and on effects of innovative output on firm productivity. Both an innovation function and a production function augmented with dummy endogenous innovation are estimated. Three estimators which control for endogeneity of the dummy innovation are employed: the first is a maximum likelihood estimator of the equations' system while the other two are built in the instrumental variables framework. These estimators give useful complementary information because of the usual efficiency-robustness tradeoff comparing system-equations and single-equation estimators. We find that innovation is frequent in Knowledge Intensive Business Services and has a strong and positive effect on productivity. As in manufacturing, the main determinant of innovation is formal knowledge resulting from R&D or from acquisitions of equipment, patents or licenses.

This paper estimates the impact of pollution abatement investments on the production technology of firms by pursuing two new directions. First, we take advantage of recent econometric developments in productivity, efficiency analysis and nonparametric kernel regression by adopting a conditional nonparametric frontier analysis. Second, we focus not only on the average effect but also search for potential nonlinearities. We provide new results suggesting that pollution abatement capital affects with a bell-shaped fashion technological catch-up (inefficiency distribution) and does not affect technological change (shifts in the frontier). These results have relevant implications both for modeling and for the purposes of advice on environmentally friendly policy.

This study shows that the survival rate of new plants depends on their spatial location. A panel dataset of French plants, observed between 1993 and 2002, provides annual samples of more than 300,000 new plants, each plant being defined as rural, periurban, urban or located in the Paris region. A survival model is developed, introducing the location variable alongside the usual survival determinants, such as size, industry and period. Estimation results clearly show that it is easier to create a new plant in urban areas, particularly in the Paris region, but less difficult to survive in rural ones. Agglomeration forces may explain the first result, and the intensity of local competition variable, the second. However, even once the local competition effect is controlled, rural new plants still exhibit significantly higher survival rates. The entrepreneurial theory of opportunity may help to understand such a result. The density of population, activities and information offer more opportunities to start an activity, but also to quit it once it has been created.

The aim of our paper is to analyse the determinants of the innovation propensity of the firm. Among the numerous works devoted to this subject, the interest of our research is, firstly, to use a direct measurement of innovation, instead of the usual proxies, as R&D expenditures and patents statistics, secondly, to emphasise the role of labour factor quality as a major determinant of innovation. We first build a definition of labour factor quality, based on a double dimension: individual skill level and functional distribution of jobs inside the firm. At the end we consider that each job category can be involved in the innovation process, at the different steps of it: conception, decision, implementation. To explain the innovation propensity at the firm level, our logit model takes into account four explanatory dimensions: the quality of labour factor employed inside the firm, the firm structural characteristics (as size, for instance), the sectoral market structures and, finally, the quality of labour factor employed inside the firm sector, as a proxy for the R&D spillover effect. We use some individual firms data, including a direct measurement of innovation, that distinguished between several types: radical vs. incremental and product vs. process vs. organisational innovation. The French food industries with its 500.000 employees and 42 sectors, mostly composed of small firms, are our empirical field. The results emphasise the influence of the usual firm structure variables. Firm size, particularly, is very clearly positively related to the innovation propensity. At the same time, some more original facts appears, such as the influence of firm status: after controlling the sectoral influence, co-operative firms seem to innovate less than private ones. Labour factor quality appears to play a very significant role by itself, but mostly, helps us to analyse and specify the influence of other variables on innovation. At the end, it shows that innovation is a multiphase process, and that the relative importance of each phase greatly depends on the kind of innovation that is considered. Conception is the most important phase in the radical innovation case, which greatly involves formally high-skilled job categories as R&D employees or engineers. At the same time, the implementation phase, which seems to be particularly important in the incremental innovation case, emphasises the role of the intermediate categories know-how. At the end we can say that small industrial firms appear to be less innovative for two reasons: the usual scale effect argument is correct only in the process innovation case in relation to the capital intensity level. In some other cases as radical innovation, small firms are less innovative because of their job structure and particularly because of the lack of formal scientific capabilities (as the R&D personnel's one).

This paper analyses the spatial heterogeneity of labour demand. Our main assumption is that for each location there is a combination of factors which is the most efficient, given the endowment of the location in terms of technology access and the relative cost of factors. We estimate our model using a panel of more than 1000 industrial firms over a six-year period. The contribution of skilled labour is emphasised in the firms located in urban areas, unskilled labour in rural firms, and capital in periurban units. The functional distribution of jobs also plays a discriminating role: direct production and similar functions seem to be more concentrated in periurban and rural areas, whereas tertiary functions are clearly assigned to urban units. We then make conclusions as to the existence of different technical paths of growth, with high productivity growth and a dramatic decline of demand for unskilled labour in urban areas, and the maintenance of a labour-intensive method of production in rural areas.

Despite the strong resilience of the French food industry during the recent economic crisis, the bankruptcy rate for this sector has dramatically increased since 2010. This paper focuses on the economic and financial determinants of firm exit due to bankruptcy in the French food industry and compares them with those for other manufacturing industries. Based on a large sample of firm-level data for the period 2001–2012, we show that the bankruptcy risk pattern differs between food industry firms and other manufacturing firms. Firm productivity is an important determinant of a firm’s probability of going bankrupt; productivity begins deteriorating 3 years before a failure. Controlling for firm productivity, we also show that credit cost has a positive and significant impact on the probability of bankruptcy. However, we observe smaller effect of credit cost on firms’ bankruptcy risk. In contrast, productivity appears to have an important beneficial effect on bankruptcy risk reduction.

Using a panel of more than 3,100 French corporate groups' affiliates and parent companies, we estimate a production function model where we enable the productivity of a firm to depend on the knowledge produced by the R&D activities of the other companies in the group. We find indeed that a firm's productivity may significantly be enhanced thanks to the R&D capital of the other affiliates. This enhancement can be estimated to be, for the corporate group as a whole, between 30% and 40% of the \"usual\" estimate of the direct impact of firms' R&D expenses on their own productivity. However, this effect differs depending on whether the firm itself conducts some R&D or not. In case it does, the other affiliates' R&D does not appear to impact significantly on its own performances: those depend only on its proper R&D activity. At the opposite, the other affiliates' R&D has a very significant effect on the productivity of firms which do not conduct any R&D. These results emphasize the existence of group spillovers, which differ from the usual industry or geographical spillovers. In particular, they do not seem to require an \"R&D based absorptive capacity\" to pre-exist and they are clearly the result of an explicit strategy, defined at the group level. Finally, these results might lead to revise upwards our estimates of the private returns on R&D investments. Nous utilisons un panel de plus de 3100 firmes appartenant à un groupe pour estimer une fonction de production au sein de laquelle la productivité d'une firme dépend notamment de son capital de connaissance. Ce dernier est une fonction, non seulement de l'activité de R&D réalisée en propre par la firme, mais également de l'activité de R&D effectuée au sein des autres entreprises appartenant au même groupe de sociétés. L'impact de cette dernière composante apparaît très significativement positif, et la valeur du coefficient qui lui est associé représente entre 30 et 40% du coefficient associé aux propres dépenses de R&D de la firme. La valeur obtenue varie selon que la firme conduit ou non sa propre activité de R&D. Lorsque la firme réalise elle—même une activité de R&D, l'impact de l'activité de R&D conduite au sein des autres firmes du groupe n'influe que peu sur le niveau de la productivité de la firme. Par contre, lorsque la firme n'effectue pas elle—même de R&D, la contribution apportée par la R&D conduite dans d'autres firmes du même groupe devient très significativement positive. Ces résultats concluent donc à l'existence d'un véritable effet spillover de groupe à l'instar des effets spillovers sectoriels ou géographiques déjà connus. Toutefois, les modalités de ces effets de spillovers diffèrent de celles usuellement mises en évidence. Alors que les effets sectoriels et géographiques constituent des externalités qui ne peuvent être captées que par les firmes qui font elles—mêmes de la R&D, et développent ainsi leur capacité d'absorption, les spillovers de groupe apparaissent comme l'expression d'une véritable stratégie entre entreprises parentes, destinée notamment à faire profiter des effets de la R&D commune les unités qui n'en conduisent pas elles—mêmes. Au total, ces résultats conduisent à réviser largement en hausse les estimations habituelles du taux de rendement privé (au sein d'un groupe de sociétés) de l'investissement en R&D.

Despite the strong resilience of the French food industry during the recent economic crisis, the bankruptcy rate for this sector has dramatically increased since 2010. This paper focuses on the economic and financial determinants of firm exit due to bankruptcy in the French food industry and compares them with those for other manufacturing industries. Based on a large sample of firm level data for the period 2001-2012, we show that the bankruptcy risk pattern differs between food industry firms and other manufacturing firms. Firm productivity is an important determinant of a firm's probability of going bankrupt; productivity begins deteriorating 3 years before a failure. Controlling for firm productivity, we also show that credit cost has a positive and significant impact on the probability of bankruptcy. However, firm financing conditions have a lower effect on bankruptcy than productivity.

This paper estimates the impact of pollution abatement investments on the production technology of firms by pursuing two new directions. First, we take advantage of recent econometric developments in productivity, effciency analysis and nonparametric kernel regression by adopting a conditional nonparametric frontier analysis. Second, we focus not only on the average effect but also search for potential nonlinearities. We provide new results suggesting that pollution abatement capital affects with a bell-shaped fashion technological catch-up (ineffciency distribution) and does not affect technological change (shifts in the frontier). These results have relevant implications both for modeling and for the purposes of advice on environmentally friendly policy.