Introduction and data Sample Clauses

Introduction and data. The aim of this section of the report is to provide a regression analysis drawing on the findings from the sectoral indexes of reserves of activities developed for the present study (see Section 3.2), and to examine the impact of reserved activities on sectoral performance. A key consideration is the extent to which through statistical analysis, market restrictions in access to professions are impacting on the performance of the sectors within study scope measured in terms of the following variables: productivity, employment, turnover, value added and firm size. The focus is on professional services (and also on other types of business services), and on the construction and tourism sectors. It should however be mentioned that there are limits to the regression analysis in this study in the sense that they are not based on a fully specified economic model. For instance, the average labour productivity of a sector will depend on additional factors such as the level of technology used, the wage paid in the sector (incentives) and the skills of the workforce. Thus, we are not able to test strictly causal relationships, and the results should therefore be interpreted with caution. However, within the regression analysis, it is possible to control for common unobserved sector and country influences, by including ‘dummy variables’ for sectors and countries. These variables filter out common trends within sectors across and within Member States and across sectors respectively. A common trend at the Member State level might be that the average firm size in a particular country is higher in all sectors than the average in the sample over all countries, due to factors other than the presence of an exclusive or shared reserved of activities (captured in each of the three sectoral RA indexes). As an example for a common sector trend, consider that the sector ‘Other business services’ might possibly use a better production technology or a better knowledge stock than other sectors in all countries under investigation. This may lead to higher average labour productivity in this sector. The most detailed sectoral data classification source for the 13 EU countries is Eurostat’s Structural Business Statistics (SBS) database. This contains data on the number of enterprises, turnover, employees, personnel costs, productivity, value added and operating surplus. XXXX Rev. 2 data at a 4-digit level is available for 2008 covering all 13 countries of this study. The match between r...
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  • Introduction and Purpose The Kentucky Community and Technical College System (KCTCS) and the Kentucky Department of Education (KDE) mutually support the attainment of dual credit coursework for high school students. This Memorandum of Understanding (MOU) underscores the dedication of both agencies to improving the educational attainment of Kentucky citizens and reinforces the collaboration necessary to achieve this level of success. Improving the educational attainment of Kentucky citizens is key to ensuring the State’s long-term success. The State commits significant resources across the educational spectrum to develop and implement strategies to address this critical issue. Providing secondary students dual credit opportunities is a proven educational strategy with the capacity to complement and maximize the chances of success of our educational initiatives. Effective dual credit systems have impacts both at the secondary and postsecondary levels and provide the opportunity for collaboration. Participants are expected to know and follow current and future versions of Dual Credit Policies established by the Kentucky Council on Postsecondary Education found at: xxxx://xxx.xx.xxx/policies/dualcredit.html. Should policies change during the academic year, KCTCS may request support in meeting those changes outside the scope of this document.

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