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- Au lendemain de la crise financière de 2008, un nombre significatif de pays ont réduit leurs dépenses publiques d’éducation. Malgré l’augmentation du PIB dans la plupart des pays de l’OCDE entre 2009 et 2010, les dépenses publiques au titre des établissements d’enseignement ont chuté dans un tiers d’entre eux.
- Entre 2009 et 2011, les salaires des enseignants ont été soit gelés, soit réduits dans 12 des 25 pays de l’OCDE qui disposent de données, ce qui pourrait avoir pour effet de décourager les étudiants très performants qui souhaitaient embrasser cette carrière.
- La demande d’enseignement et de formation est en constante augmentation alors même que les mesures d’austérité font pression sur les ressources allouées à l’éducation. Dans les années à venir, les établissements d’enseignement devront obtenir davantage de résultats, mais avec des moyens plus restreints.
This paper describes the key characteristics of high-risk/high-reward research (HRHR), which has gained considerable interest from policy makers as a way to promote the development of new, ‘out-of-the-box’ ideas. It identifies three dimensions that are accentuated in HRHR research: higher levels of basicness, generality and novelty. These knowledge characteristics are commonly associated with market failure and research that requires public investment because it has large spill-overs, long time horizons and high levels of uncertainty. This is illustrated with examples of specific discoveries embedding each knowledge characteristic and the application of appropriate quantitative measures. The paper concludes with the computation and demonstration of an indicator of novelty that may be particularly well suited for the monitoring and evaluation of HRHR research policies.
This paper uses a new measure of human capital, which distinguishes both quality and quantity components, to estimate the long-term effect of the COVID-19-related school closures on aggregate productivity through the human capital channel. Productivity losses build up over time and are estimated to range between 0.4% and 2.1% after 45 years, for 12 weeks and 2 years of school closure, respectively. These results appear to be broadly consistent with earlier findings in the literature. Two opposing effects might influence these estimates. Online teaching would lower economic costs while learning losses in tertiary education (not considered here) would inflate them. Policies aimed at improving the quality of education and adult training will be needed to offset or, at least, alleviate the impact of the pandemic on human capital.
This paper evaluates the link between educational policies and i) student performance and ii) macroeconomic measures of productivity. The analysis has two stages. First, using the 2015 and 2018 PISA databases, it quantifies the relationship between student test scores and the characteristics of students taking the tests, their school environment and national educational systems. Second, assuming that these relationships reflect the effect of different characteristics/policies on student test performance, the second stage converts the latter into an estimated effect on macroeconomic measures of productivity using a new measure of human capital as an intermediary variable. This new measure of human capital, devised in previous OECD work, combines student test scores and mean years of schooling with estimated elasticities that suggest the former is more important. The analysis shows a positive association between spending on education and student test scores, but only for levels of student expenditure below the OECD median, suggesting scope for currently low-spending countries to raise student performance with potential gains to long-run productivity. Boosting participation in early childhood education as well as improving teacher quality is found to generate large aggregate productivity gains. There are significant, but smaller, macroeconomic gains for many countries from limiting grade repetition and ability grouping across all subjects as well as increasing the accountability of schools. Finally, the results provide evidence for income inequality having a major influence on productivity through a human capital channel.
Socio-economic cost-benefit analysis (CBA) is a powerful framework that can be very useful to governments making investment decisions. However the standard application of transport CBA has room for improvement. This paper describes efforts to improve the quality of transport CBA and its applicability to decision making. Three areas are addressed in detail: strategies for making the most of CBA, valuing and forecasting reliability benefits, and capturing wider economic impacts. The report is based on the papers and discussions at a Roundtable meeting of 30 experts held in Paris in November 2015. Roundtable participants took the view that a multi-faceted approach is needed to address the shortfalls; CBA theory and practice need to be gradually expanded to incorporate more impacts in the rigorous valuation and forecasting framework; and CBA results need to be more effectively linked to other criteria in the broader decision-making framework, including by bringing in a more diverse evidence base.
This paper presents a progress report on the Economics and Statistics Department's applied general equilibrium model -- the WALRAS model. This model has been developed with the explicit objective of quantifying the economy-wide effects of agricultural policies in OECD countries. The common specification of the model for the major OECD agricultural trading countries/regions (Australia, Canada, EEC, Japan, New Zealand and the United States) is described in detail. Results are presented for some preliminary simulations of the effects of removing the 1979-81 levels of agricultural assistance in these countries/regions. The initial results relate only to unilateral liberalisation experiments with the unlinked country/region models, with no account being taken of feedback effects through changes in world agricultural prices and trade volumes ...
Industrial policy has resurfaced prominently in academic and policy discussions in the wake of major shocks and long-term trends. However, quantifying industrial strategies across countries remains difficult. The ‘Quantifying Industrial Strategies’ (QuIS) project measures industrial policy expenditures by gathering and harmonising publicly available data, based on a new methodology. This report summarises the composition of industrial strategies in the first nine participating countries in terms of expenditures, priorities, and policy instruments for the period 2019-21. The report finds that industrial policies are sizeable, with 1.5% of GDP in grants and tax expenditures, and with an important heterogeneity across countries in terms of strategic priorities; industrial strategies mainly rely on sectoral instruments, representing on average 29% of grants and tax expenditures; and green instruments are important and rose significantly in six out of nine countries between 2019 and 2021.
Industrial policy is sparking renewed interest across OECD member countries and partner economies. However, amidst an increasing number of objectives for industrial policy, and despite the availability of information on countries’ strategies and plans, it remains difficult to properly measure and compare resources spent on industrial policies and identify countries’ strategic priorities. The lack of a cross-country comparable source of information on resources dedicated to industrial policy partly results from the absence of a common methodology to account for industrial policy expenditures.
This paper provides a new methodology for reporting industrial policy expenditure in a comparable way across countries.
It is the first deliverable of the “Quantifying Industrial Strategies” project, which aims at measuring industrial policy expenditures across OECD countries and will gather harmonised data on industrial policy expenditures, their composition, and their mode of delivery.
Innovation is key to reducing the environmental impacts of plastics. However, literature is generally lacking in the field of environmentally relevant plastics innovation. This paper develops an innovative conceptual framework to document and map environmentally relevant plastics innovation. Using this framework, it develops plastics innovation metrics using patents and trademarks to quantify trends over time, across countries, and to establish preliminary empirical links between policies and innovation outcomes.
Plastic waste prevention and recycling innovation has increased slightly more rapidly than overall plastics innovation. In contrast, innovation in bioplastics have witnessed a significant slowdown in recent years. Another key finding of this analysis is that environmentally relevant plastics innovation is concentrated in OECD countries and China and that top inventor countries are not specialized in the same technologies. Finally, the patent analysis shows some empirical evidence that recycling regulations may have triggered innovative activity in plastic recycling.
This paper presents a new methodology for the quantification of qualitative survey data. Traditional conversion methods, such as the probability approach of Carlson and Parkin (1975) or the time-varying parameters model of Seitz (1988), require very restrictive assumptions concerning the expectations formation process of survey respondents. Above all, the unbiasedness of expectations, which is a necessary condition for rationality, is imposed. Our approach avoids this assumptions. The novelty lies in the way the boundaries inside of which survey respondents expect the variable under consideration to remain unchanged are determined. Instead of deriving these boundaries from the statistical properties of the reference time-series (which necessitates the unbiasedness assumption), we directly queried them from survey respondents by a special question in the Ifo World Economic Survey. The new methodology is then applied to expectations about the future development of inflation obtained from the Ifo World Economic Survey.
In this paper, we develop a likelihood approach for quantification of qualitative survey data on expectations and perceptions and we propose a new test for expectation consistency (unbiasedness). Our quantification scheme differs from existing methods primarily by using prior information (perhaps derived from economic theory or well established empirical relations) on the underlying process driving the variable of interest. To investigate the properties of our novel quantification scheme and to analyze the size and power properties of the new expectation consistency test, we perform Monte Carlo simulation studies. Overall, the simulation results are very encouraging and show that efficiency gains from including prior information can be substantial relative to existing quantification schemes. Finally, we provide an empirical illustration...