Education policy and national income distribution: New evidence from recent cross -country data

In the mid 19th century, Horace Mann insisted that a broad provision of public schooling should take precedence over the liberal education of an elite group. In that regard, his generation constructed a state sponsored common schooling enterprise to educate the masses. More than 100 years later, the institution of public schooling fails to maintain an image fully representative of the ideals of equity and inclusion. Critical theory in educational thought associates the dominant practice of functional schooling with maintenance of the status quo, an unequal distribution of financial, political, and social resources. This study examined the empirical basis for the association of public schooling with the status quo using the most recent and comparable cross-country income inequality data. Multiple regression analysis evaluated the possible relationship between national income inequality change over the period 1985-2005 and variables representative of national measures of education supply in the prior decade. The estimated model of income inequality development attempted to quantify the relationship between education supply factors and subsequent income inequality developments by controlling for economic, demographic, and exogenous factors. The sample included all nations with comparable income inequality data over the measurement period, N = 56. Does public school supply affect national income distribution? The estimated model suggested that an increase in the average years of schooling among the population age 15 years or older, measured over the period 1975-1985, provided a mechanism that resulted in a more equal distribution of income over the period 1985-2005 among low and lower-middle income nations. The model also suggested that income inequality increased less or decreased more in smaller economies and when the percentage of the population age < 15 years grew more slowly over the period 1985-2000. In contrast, this study identified no significant relationship between school supply changes measured over prior periods and income inequality development over the period 1985-2005 among upper-middle and high income nations.

Cross-country data on the quantity of schooling: a selective survey and some quality measures

We survey a number of papers that have focused on the construction of cross-country data sets on average years of schooling. We discuss the construction of the different series, compare their profiles and construct indicators of their information content. The discussion focuses on a sample of OECD countries but we also provide some results for a large non-OECD sample.

Developing Linked Data Applications

Publishing Linked Data SPARQL Graph Store Protocol Linked Data Platform Reflection on Data Publishing

Influence-matrix diagnostic of a data assimilation system

The influence matrix is used in ordinary least-squares applications for monitoring statistical multiple-regression analyses. Concepts related to the influence matrix provide diagnostics on the influence of individual data on the analysis - the analysis change that would occur by leaving one observation out, and the effective information content (degrees of freedom for signal) in any sub-set of the analysed data. In this paper, the corresponding concepts have been derived in the context of linear statistical data assimilation in numerical weather prediction. An approximate method to compute the diagonal elements of the influence matrix (the self-sensitivities) has been developed for a large-dimension variational data assimilation system (the four-dimensional variational system of the European Centre for Medium-Range Weather Forecasts). Results show that, in the boreal spring 2003 operational system, 15% of the global influence is due to the assimilated observations in any one analysis, and the complementary 85% is the influence of the prior (background) information, a short-range forecast containing information from earlier assimilated observations. About 25% of the observational information is currently provided by surface-based observing systems, and 75% by satellite systems. Low-influence data points usually occur in data-rich areas, while high-influence data points are in data-sparse areas or in dynamically active regions. Background-error correlations also play an important role: high correlation diminishes the observation influence and amplifies the importance of the surrounding real and pseudo observations (prior information in observation space). Incorrect specifications of background and observation-error covariance matrices can be identified, interpreted and better understood by the use of influence-matrix diagnostics for the variety of observation types and observed variables used in the data assimilation system. Copyright © 2004 Royal Meteorological Society

How does employment density influence individuals’ wages? : A micro data approach.

We estimate the effect of employment density on wages in Sweden in a large geocoded data set on individuals and workplaces. Employment density is measured in four circular zones around each individual’s place of living. The data contains a rich set of control variables that we use in an instrumental variables framework. Results show a relatively strong but rather local positive effect of employment density on wages. Beyond 5 kilometers the effect becomes negative. This might indicate that the effect of agglomeration economies falls faster with distance than the effects of congestion.

A Reuse-based Lightweight Method for Developing Linked Data Ontologies and Vocabularies

The uptake of Linked Data (LD) has promoted the proliferation of datasets and their associated ontologies for describing different domains. Par-ticular LD development characteristics such as agility and web-based architec-ture necessitate the revision, adaption, and lightening of existing methodologies for ontology development. This thesis proposes a lightweight method for ontol-ogy development in an LD context which will be based in data-driven agile de-velopments, existing resources to be reused, and the evaluation of the obtained products considering both classical ontological engineering principles and LD characteristics.

Finite element modeling of motor vehicles. Protocol for developing INGRID data input desks for DYNA3D computer code. Final report.

Federal Highway Administration, Office of Safety and Traffic Operations Research Development, McLean, Va.

Country data book.

All participating countries.--Austria.--Belgium-Luxemburg.--Denmark.--France.--Germany (Fed. Rep.)--Greece.--Iceland.--Ireland.--Italy.--Netherlands.--Norway.--Portugal.--Sweden.--Turkey.--United Kingdom.

Management influence on the design of data processing systems, a case study.

Mode of access: Internet.

How does social security affect economic growth? Evidence from cross-country data

This paper investigates how social security interacts with growth and growth determinants (savings, human capital investment, and fertility). Our empirical investigation finds that the estimated coefficient on social security is significantly negative in the fertility equation, insignificant in the saving equation, and significantly positive in the growth and education equations. By contrast, the estimated coefficient on growth is insignificant in the social security equation. The results suggest that social security may indeed be conducive to growth through tipping the trade-off between the number and quality of children toward the latter.

Developing a Data-Driven Classification of South Florida Plant Communities

A comprehensive, broadly accepted vegetation classification is important for ecosystem management, particularly for planning and monitoring. South Florida vegetation classification systems that are currently in use were largely arrived at subjectively and intuitively with the involvement of experienced botanical observers and ecologists, but with little support in terms of quantitative field data. The need to develop a field data-driven classification of South Florida vegetation that builds on the ecological organization has been recognized by the National Park Service and vegetation practitioners in the region. The present work, funded by the National Park Service Inventory and Monitoring Program - South Florida/Caribbean Network (SFCN), covers the first stage of a larger project whose goal is to apply extant vegetation data to test, and revise as necessary, an existing, widely used classification (Rutchey et al. 2006). The objectives of the first phase of the project were (1) to identify useful existing datasets, (2) to collect these data and compile them into a geodatabase, (3) to conduct an initial classification analysis of marsh sites, and (4) to design a strategy for augmenting existing information from poorly represented landscapes in order to develop a more comprehensive south Florida classification.