Happy e-Inclusion? The Case of Romania

This paper investigates the determinants of adoption of ICT technology by households in Romania, using a probit model based on a time-series cross-section dataset. A particular attention is given to a few psycho-social factors in addition to the recognised role of usual socio-economic determinants, such as income, age, employment status, educational level or gender. The particular findings are that, together with an expected impact of the occupational status and of the educational level, the perceived wellbeing of individuals is one of the most important factors influencing the decision to acquire and use a PC at home. Gender does not seem to have the same importance as in other regions of the world and shows an opposite sign than elsewhere, whereas income influences the decision, but with a weaker effect.information and communications technology; e-inclusion; Probit model; Romania; determinants of PC use

Happy E-Inclusion? The Case of Romania

This paper investigates the determinants of adoption of ICT technology by households in Romania, using a probit model based on a time-series cross-section dataset. A particular attention is given to a few psycho-social factors in addition to the recognised role of usual socio-economic determinants, such as income, age, employment status, educational level or gender. The particular findings are that, together with an expected impact of the occupational status and of the educational level, the perceived wellbeing of individuals is one of the most important factors influencing the decision to acquire and use a PC at home. Gender doesn¿t seem to have the same importance as in other regions of the world and shows an opposite sign than elsewhere, whereas income influences the decision, but with a weaker effect. Keywords: Information and communications technology; E-Inclusion; Probit model; Romania; determinants of PC use JEL classification: O33, O52, L86JRC.DG.J.4-Information Societ

La inversión en I+D del sector privado en la UE y en otros países: un análisis comparativo basado en una clasificación del 2004 de la Comisión Europea

Este artículo presenta los principales resultados del primer “EU Industrial R&D Investment Scoreboard”, que muestra las primeras 500 compañías pertenecientes a la Unión Europea (UE) y las primeras 500 compañías no pertenecientes a la UE según su inversión en I+D. Después de una corta explicación de la definición y objetivos de este ejercicio, su contenido y sus principales conclusiones vienen junto con los resultados de otros análisis realizados dentro de La Comisión Europea, Dirección General, Centro Común de Investigación (CCI) Sevilla, mostrando la importancia del grado de concentración a nivel de compañía para la situación industrial de la I+D en general. Parece que hay una correlación entre la intensidad del crecimiento de I+D y el crecimiento de las ventas (netas) de las empresas. A pesar de una impresionante cantidad de inversión en I+D, la media general de la inversión en I+D de la muestra perteneciente a la UE es mucho menor que la de sus equivalentes. Esto está relacionado a una proporción menor de producción procedente de sectores con intensidad en I+D intrínseca alta, lo que se puede observar especialmente en compañías especializadas en IT hardware y también en servicios de software y para ordenadores. A pesar de que las cantidades de inversión en I+D son comparables para las grandes empresas, la proporción para empresas que están en medio y al final de la lista de “top-500 Scoreboard” es mucho menor en la UE que fuera de ella. Este análisis indica que los modelos y estructuras nacionales, regionales y sectoriales se desvían considerablemente de los de la media europea. Una sección entera del artículo esta dedicada a la comparación entre sectores de los indicadores de I+D. El problema de la concentración de la inversión en I+D entre compañías muy importantes que invierten en I+D viene investigada en mayor detalle, entre las empresas grandes, según el sector de actividad y según la localización. También se ha demostrado que la muestra de las compañías inversoras en I+D más importantes se puede caracterizar estadísticamente por heterocedasticidad. ____________________________________________This paper presents the main results from the 2004 EU Industrial R&D Investment Scoreboard, which lists the top 500 EU companies and the top 500 non-EU companies ranked by their R&D investment. After a short description of the definitions and objectives of the exercise, its content and main findings are shown together with results from other analyses performed within The European Common Directorate General, Joint Research (JRC) – Seville, showing the impact of the degree of concentration at the company’s level on the overall industrial R&D stance. There seems to be a correlation between R&D intensity growth and net sales growth. Despite a competitive total amount of R&D investment, the average overall R&D intensity of the sampled European Union companies is much smaller than for their non-EU counterparts. This is related to a smaller proportion of output from sectors with high intrinsic R&D intensity, which is particularly noticeable in IT Hardware and Software and Computer Services. Although R&D investment amounts are comparable for the biggest firms, the share of R&D performers at the middle and the bottom of the EU-500 Scoreboard is much smaller in the EU than in the non-EU. The analysis indicates that national, regional and sectoral patterns deviate considerably from the overall picture of the EU. An entire section of the paper is dedicated to an inter-sector comparison of R&D-related indicators. The issue of concentration of R&D investment among top companies investing in research is investigated in more detail, in large companies, by sector of activity and by location. It is also proved that the sample of top R&D investing companies is statistically characterised by heteroscedasticity

The "Dobrescu" Macromodel of the Romanian Transition Economy - Yearly and Monthly Forecast -

The paper presents the yearly and monthly forecast of the Romanian transition economy performed on the basis of the “Dobrescu” macromodel. * Source: Emilian DOBRESCU: Macromodels of the Romanian Transition Economy, third edition, Expert Publishing House, September 2000.macromodel, simulations, forecasting

Bioeconomy and sustainability: a potential contribution to the Bioeconomy Observatory

In response to the need for further clarifications concerning the emerging concept of the “bio-economy”, the present study scrutinizes this concept in order to better delineate its analytical scope. It also describes methodologies of potential relevance to evaluation and monitoring of the bio-economy. Although not directly intended to prepare the ground for the future EU Bio-economy Observatory (BISO), the material presented herein may also meaningfully inform the design of monitoring activities which will be undertaken within the BISO framework. The introductory section sheds some light on the bio-economy’s multi-dimensional nature, scope, drivers, challenges and economic potential. In order to clearly distinguish between their specific features and coverage, a comparative description of eco-industries versus the bio-economy is included here. The current EU policy approach to the bio-economy is sketched in the second section of this report. With the purpose of defining the bio-economy’s scope and its internal flows, the third section advances an integrated analytical perspective on the EU bio-economy. This perspective builds upon descriptions provided in the related Commission documents. Its potential use in support of the future Bio-economy Observatory is elaborated, together with several associated methodological aspects. In the fourth section, the datasets, methods and models which could be used for measuring and monitoring the bio-economy’s drivers, development and impact are identified and grouped into five inter-related methodological modules. Further methodological clarification is provided as to i) the need for complementing a sectoral approach to the bio-economy with other perspectives, including the product-chain approach, and ii) the usefulness of inventory data from the European Commission’s life-cycle based resource efficiency indicators. Other relevant data sources are also described. In addition, in light of the limited availability of statistical data on new bio-based products and processes, the need for further disaggregated product-level statistics for bio-based products and company-level research is also discussed. Current standardization and research activities on issues such as harmonization of sustainability certification systems for biomass production, conversion systems and trade, sustainability assessment of technologies, and environmental performance of products are reviewed in the fifth section. Based on the observation that it would be impossible to obtain all required data for bio-economy monitoring from official statistical sources, we propose in the sixth section a general-purpose questionnaire which could serve as a basis for prospective surveys. It is intended to be further refined and adjusted, in collaboration with the sector-relevant European technology platforms and industry associations and other relevant stakeholders, according to the specific profile of each sector, product group or firm type to be included in any future surveys.JRC.H.8-Sustainability Assessmen

Monitoring Industrial Research: Industrial R&D Economic and Policy Analysis Report 2006

This paper addresses a series of key policy questions in industrial R&D. It questions whether EU growth suffers from underinvestment in R&D, or whether the lack of R&D is a reflection of more general imperfections of the single market. It also elaborates on the finding that EU companies in sectors with traditionally high levels of R&D spend as much on R&D as their competitors. This is combined with evidence from surveys showing that lack of funding for R&D is not the most binding constraint for investing companies. It also builds on the notion that the internationalisation and outsourcing of R&D appears to carry on regardless of differences in government financial support. One conclusion, therefore, is that market-oriented reforms and complementary policies to improve the structure of the European economy may be more effective in raising R&D expenditures – and in generating growth through innovation – than direct incentives.JRC.J.3-Knowledge for Growt

Seasonal Variations in Mood and Behavior in Romanian Postgraduate Students

To our knowledge, this paper is the first to estimate seasonality of mood in a predominantly Caucasian sample, living in areas with hot summers and a relative unavailability of air conditioning. As a summer pattern of seasonal depression was previously associated with a vulnerability to heat exposure, we hypothesized that those with access to air conditioners would have a lower rate of summer seasonal affective disorder (SAD) compared to those without air conditioning. A convenience sample of 476 Romanian postgraduate students completed the Seasonal Pattern Assessment Questionnaire (SPAQ), which was used to calculate a global seasonality score (GSS) and to estimate the rates of winter- and summer-type SAD. The ratio of summer- vs. winter-type SAD was compared using multinomial probability distribution tests. We also compared the ratio of summer SAD in individuals with vs. without air conditioners. Winter SAD and winter subsyndromal SAD (S-SAD) were significantly more prevalent than summer SAD and summer S-SAD. Those with access to air conditioners had a higher, rather than a lower, rate of summer SAD. Our results are consistent with prior studies that reported a lower prevalence of summer than winter SAD in Caucasian populations. Finding an increased rate of summer SAD in the minority of those with access to air conditioners was surprising and deserves replication