Welfare benefits and the rate of unemployment: some evidence from the European Union in the last thirty years

Our objective in this paper is to re-examine the hypothesis that welfare benefits may be responsi-ble for the observed differences in cross- country unemployment rates and test its validity by using panel data from 19 countries over the 1970-2000 period. For this purpose, we set up a general equi-librium model encompassing the private and public sectors of the economy, where the government comes to the relief of the unemployed by increasing the welfare benefits per man. From this model, we extract an unemployment rate equation. The results that emerge from the empirical analysis sug-gest that social benefits per man may indeed adversely influence the rate of unemployment in EU-15. But the results change significantly when the EU member states are classified as high-, low- and average unemployment countries. In particular, we find that, whereas unemployment benefits exert perceptible positive influences in the high and average unemployment sub-groups, their influence in the low unemployment sub-group is nil. This finding, in conjunction with the evi-dence that the unemployment rate is invariant with respect to social benefits in USA and Canada, leads us to the conclusion that some EU countries may have to restructure their welfare systems, so as to reduce welfare benefits in favour of greater labour market flexibility and self-reliance on the part of workers.unemployment rate, welfare benefits, European Union

The spatial and temporal patterns of declared personal income across Greece: 2001-8

The paper studies the income mosaic of Greece at the local community level, from the time the country joined the EMU to time the international crisis reached its shores. It econometrically isolates the impact of past average income and the size of income-filing population, as well as the annual effects; and tries to explain in terms of demographic, educational, and other attributes of the population, as well as geographic features, the number of times (years) that local income exceed the level predicted. To the extent the residuals are produced by unknown (missing) variables, their sub-regional and cross-regional patterns offer clues in the direction of formulating better, spatially targeted interventions. There is a real need for policy suggestions that stretch the funds permitted by the fiscal straitjacket to go further in pulling the country out of the recession. Overall, the paper provides a better understanding of the internal heterogeneity of Greece, the sub-national operation of the economy, and the generation and distribution of personal income

Functional Economies Or Administrative Units in Greece: What Difference Does It Make for Policy?

The paper provides the 2001 income mosaic of Greece at the local (municipal and postcode) level, and econometrically isolates a number of territorial, demographic, and occupational factors on declared income formation, on the basis of which it makes a number of policy proposals. The disaggregate nature of the data facilitates the construction of alternative spatial models that are juxtaposed to the regional framework on the basis of which national and E.U. sub-national convergence and prosperity plans are devised, implemented, and assessed. A specification based on the existing regional framework provides an inferior econometric fit, which, in turn, suggests that the economy does not operate according to the country's administrative divisions but rather according to local-specific factors and transportation linkages, as is the case in a fragmented land united by its trans-portation network. Accordingly, if income disparities are larger within administrative regions rather than across regions, it might make more sense if regional economic development policy were con-ducted within a functional-area framework rather the current administrative-region framework. Suited for themes A, C, E, Q

Agent-Based Distributed Learning Applied to Fraud Detection

Inductive learning and classification techniques have been applied in many problems in diverse areas. In this paper we describe an AI-based approach that combines inductive learning algorithms and meta-learning methods as a means to compute accurate classification models for detecting electronic fraud. Inductive learning algorithms are used to compute detectors of anomalous or errant behavior over inherently distributed data sets and meta-learning methods integrate their collective knowledge into higher level classification models or "meta-classifiers". By supporting the exchange of models or "classifier agents" among data sites, our approach facilitates the cooperation between financial organizations and provides unified and cross-institution protection mechanisms against fraudulent transactions. Through experiments performed on actual credit card transaction data supplied by two different financial institutions, we evaluate this approach and we demonstrate its utility

Cost-based Modeling for Fraud and Intrusion Detection: Results from the JAM Project

We describe the results achieved using the JAM distributed data mining system for the real world problem of fraud detection in financial information systems. For this domain we provide clear evidence that state-of-the-art commercial fraud detection systems can be substantially improved in stopping losses due to fraud by combining multiple models of fraudulent transaction shared among banks. We demonstrate that the traditional statistical metrics used to train and evaluate the performance of learning systems (i.e. statistical accuracy or ROC analysis) are misleading and perhaps inappropriate for this application. Cost-based metrics are more relevant in certain domains, and defining such metrics poses significant and interesting research questions both in evaluating systems and alternative models, and in formalizing the problems to which one may wish to apply data mining technologies. This paper also demonstrates how the techniques developed for fraud detection can be generalized and applied to the important area of intrusion detection in networked information systems. We report the outcome of recent evaluations of our system applied to tcpdump network intrusion data specifically with respect to statistical accuracy. This work involved building additional components of JAM that we have come to call, MADAM ID (Mining Audit Data for Automated Models for Intrusion Detection). However, taking the next step to define cost-based models for intrusion detection poses interesting new research questions. We describe our initial ideas about how to evaluate intrusion detection systems using cost models learned during our work on fraud detection

Distributed Data Mining: The JAM system architecture

This paper describes the system architecture of JAM (Java Agents for Meta-learning), a distributed data mining system that scales up to large and physically separated data sets. An earlyversion of the JAM system was described in Stolfo-et-al-97-KDD-JAM. Since then, JAM has evolved both architecturally and functionally and here we present the final design and implementation details of this system architecture. JAM is an extensible agent-based distributed data mining system that supports the remote dispatch and exchange of agents among participating datasites and employs meta-learning techniques to combine the multiple models that are learned. One of JAM's target applications is fraud and intrusion detection in financial information systems. A brief description of this learning task and JAM's applicability and summary results are also discussed

Identifying spatial labor markets in Greece from the 2001 travel- to- work patterns.

The article examines inter-municipal commuting flows in Greece, collected via the 2001 Census, and delineates the country’s labor market areas (LMAs). It finds that the LMAs of Athens (3.9 million inhabitants) and Thessaloniki (1.1 million) exceed the homonymous urban-planning complexes by 8 and 15 times, respectively. These LMAs, along with the LMAs of Patras (245 thousand) and Iraklion (233 thousand), host about half the country’s population. Another thirty-eight clusters of municipalities and eight self-contained municipalities of 20-184 thousand inhabitants jointly host a quarter of the country’s population. The picture is complemented by the presence of ten clusters of municipalities and 607 selfcontained municipalities with smaller populations. Overall, the article advances our understanding of how the country functions at the sub-national level

Estimating household demand for olive oil in Greece

The paper estimates the monthly household demand for olive oil in Greece byeconometrically analysing in a two-stage Heckman framework, cross-sectionalmicroeconomic data solicited via the Household Budget Survey of 2011. It findsthat quantity increases as (a) its price decreases, and (b) income or the quantity ofseed oil, olive pomace oil, and margarine increase. Spatial, seasonal, and a coupleof nationality (origin) effects are detected. Price elasticity is estimated at 1.5-1.7,which suggests that conditions are to some degree favourable towards theformationof a profit maximising monopoly exerting market power in Greece

Large fire disaster and the regional economy: the 2007 case of the Peloponnese

The article explores the evolution of annual personal incomes in the Peloponnese, in southern Greece, at the disaggregated (local community) level from 2001 to 2010, i.e., before and after the 2007 fires, in order to better understand the medium-term economic effects of these fires in the burned and other areas of the region outside the fire path. The paper considers a number of econometric approaches and ends up engaging in a series of cross-sectional regressions of income-filer figures and average incomes to study the situation year after year. Findings indicate that, by and large, no inordinate drop or rise in average income figures or income-filer numbers is detected in the aftermath of the fires, especially in the communities damaged by them

Timing of Anterior Cruciate Ligament (ACL) reconstruction

Background: Anterior Cruciate Ligament (ACL) ruptures are common but the ideal timing for ACL reconstruction following injury is unclear. Objectives: To determine if there is a relationship between timing from ACL rupture to surgery and clinical, functional and patient-reported outcomes. To explore the feasibility of collecting clinicians’ views on ACL reconstruction timing. Design and methods: A systematic review of five databases to identify studies investigating outcomes following different timing of reconstruction surgery and a pilot vignette study to identify variations in clinical decisions about timing of surgery in four different case scenarios. Results: Systematic review: Ten studies were identified, only one was a randomised controlled trial. There appeared to be no difference in outcomes between early ( 6months) ACL reconstruction. The two studies on functional and/or patient reported outcomes had conflicting findings, with the trial suggesting no difference between early or delayed reconstruction. The studies had limited evidence about the relationship between timing of surgery and patient characteristics. Pilot Vignette study: The pilot vignette study had a response rate of 45% but a high question completion rate. There was clinical variation in timing between surgeons and across patient groups, but none recommended delayed surgery (>6 months). Conclusions: Given the potential deleterious effects of meniscal and chondral injuries on knee function, delays of more than 6 months in patients deemed suitable for ACL surgery are not recommended, but there is some evidence that these delays are not common in practice. Further research on timing of ACL reconstruction should focus on shorter time-frames, functional and patient-reported outcomes, and the influence of patient characteristics, as available evidence is limited, inconsistent and of low quality. A vignette study seems feasible to provide insights on clinical decisions and guide current practice and future research