THE ESTIMATION OF FAIR PRICES OF TRADED GOODS FROM OUTLIER-FREE TRADE DATA

The JRC develops and applies innovative statistical methods needed by the European Anti-fraud Office and its partners in the EU Member States for the protection of the financial interests of the European Union. JRC's work focuses on several Customs commercial fraud-control problems. Among them, the evasion of (ad valorem) import duties, VAT fraud and trade-based money laundering relate to the misdeclaration of the trade price and are addressed via the statistical detection of price outliers in EU trade data. The detection of price outliers has been proven useful in a-posteriori controls conducted by EU customs services on relatively recent transactions. The price outlier detection procedure, when applied to appropriate trade datasets, produces outliers-free data on which reliable estimates can be calculated for the market prices of the traded products: these estimates are called “fair prices”. These estimates can be used as a support to the determination of the customs value at the moment of the customs formalities or for post-clearance checks. This report presents the fair price estimation method and its relation with the price outliers’ detection approach.JRC.G.2-Global security and crisis managemen

Predicting Students’ Financial Knowledge from Attitude towards Finance

Attitude towards finance and financial attitude are very different constructs. Despite the popularity of the latter, it has recently been subject to criticism. Following Di Martino & Zan (2010), the former explicitly considers emotions and beliefs (about self and finance) and the mutual relationship between them. At present, there is a paucity of evidence on how ‘attitude toward finance’ may impact financial knowledge: this is a new area of inquiry in academic literature. Research is at a preliminary stage, although the jigsaw of financial literacy is receiving greater attention worldwide. This study measures individual attitudes towards finance and determines the effects of this profile on financial knowledge level. It uses about 500 economics students in Italy as sample respondents. It is based on a structured questionnaire survey as a data collection method. The data is analysed using Structural Equation Modeling. A significant positive correlation is found between financial knowledge and attitude toward finance. The direction of causality is found to be from attitude toward finance to financial knowledge, and this finding suggests that attitude toward finance can play an important role in financial education. Among the various dimensions of attitude toward finance, emotional disposition towards finance, and secondly, the self-confidence level, are the most influential factors on economic students’ financial knowledge level. Gender is also found to be closely correlated to both financial knowledge and attitude toward finance. Findings mainly suggest the importance of attitude toward finance on financial knowledge. For policymakers, the results of this study could indicate new ways of solving the financial illiteracy problem

fsdaSAS: a package for robust regression for very large datasets including the batch forward search

The forward search (FS) is a general method of robust data fitting that moves smoothly from very robust to maximum likelihood estimation. The regression procedures are included in the MATLAB toolbox FSDA. The work on a SAS version of the FS originates from the need for the analysis of large datasets expressed by law enforcement services operating in the European Union that use our SAS software for detecting data anomalies that may point to fraudulent customs returns. Specific to our SAS implementation, the fsdaSAS package, we describe the approximation used to provide fast analyses of large datasets using an FS which progresses through the inclusion of batches of observations, rather than progressing one observation at a time. We do, however, test for outliers one observation at a time. We demonstrate that our SAS implementation becomes appreciably faster than the MATLAB version as the sample size increases and is also able to analyse larger datasets. The series of fits provided by the FS leads to the adaptive data-dependent choice of maximally efficient robust estimates. This also allows the monitoring of residuals and parameter estimates for fits of differing robustness levels. We mention that our fsdaSAS also applies the idea of monitoring to several robust estimators for regression for a range of values of breakdown point or nominal efficiency, leading to adaptive values for these parameters. We have also provided a variety of plots linked through brushing. Further programmed analyses include the robust transformations of the response in regression. Our package also provides the SAS community with methods of monitoring robust estimators for multivariate data, including multivariate data transformations

The Robust Estimation of Monthly Prices of Goods Traded by the European Union

The general problem addressed in this document is the estimation of “fair” import prices from international trade data. The work is in support to the determination of the customs value at the moment of the customs formalities, to establish how much duty the importer must pay, and the post-clearance checks of individual transactions. The proposed approach can be naturally extended to the analysis of export flows and used for other purposes, including general market analyses. The Joint Research Centre of the European Commission has previously addressed (Arsenis et al., 2015) the trade price estimation problem by considering data for fixed product, origin and destination over a multiannual time period, typically of 3 or 4 years, leading to price estimates that are specific for each EU Member State. This report illustrates a different model whereby each price estimate is calculated on a monthly basis, using data for fixed time (month), product and origin. The approach differentiates between trades originated from different third countries and it is therefore particularly useful to monitor trends and anomalies in specific EU trade markets. These Estimated European Monthly Prices are publishes every month by the Joint Research Centre in a dedicated section of the THESEUS website (https://theseus.jrc.ec.europa.eu), accessible by authorized users of the EU and Member States services. The section, called Monthly Fair Prices, also shows the time evolution of worldwide price estimates computed with the same approach by fixing only time and product.JRC.I.3-Text and Data Minin

Simulating mixtures of multivariate data with fixed cluster overlap in FSDA library

We extend the capabilities of MixSim, a framework which is useful for evaluating the performance of clustering algorithms, on the basis of measures of agreement between data partitioning and flexible generation methods for data, outliers and noise. The peculiarity of the method is that data are simulated from normal mixture distributions on the basis of pre-specified synthesis statistics on an overlap measure, defined as a sum of pairwise misclassification probabilities. We provide new tools which enable us to control additional overlapping statistics and departures from homogeneity and sphericity among groups, together with new outlier contamination schemes. The output of this extension is a more flexible framework for generation of data to better address modern robust clustering scenarios in presence of possible contamination. We also study the properties and the implications that this new way of simulating clustering data entails in terms of coverage of space, goodness of fit to theoretical distributions, and degree of convergence to nominal values. We demonstrate the new features using our MATLAB implementation that we have integrated in the Flexible Statistics for Data Analysis (FSDA) toolbox for MATLAB. With MixSim, FSDA now integrates in the same environment state of the art robust clustering algorithms and principled routines for their evaluation and calibration. A spin off of our work is a general complex routine, translated from C language to MATLAB, to compute the distribution function of a linear combinations of non central $$\chi ^2$$?2 random variables which is at the core of MixSim and has its own interest for many test statistics

Contribution of Protease-activated Receptors 1 and 4 and Glycoprotein Ib-IX-V in the Gi-independent Activation of Platelet Rap1B by Thrombin

Thrombin activates human platelets through three different membrane receptors, the protease-activated receptors PAR-1 and PAR-4 and the glycoprotein Ib (GPIb)-IX-V complex. We investigated the contribution of these three receptors to thrombin-induced activation of the small GTPase Rap1B. We found that, similarly to thrombin, selective stimulation of either PAR-1 or PAR-4 by specific activating peptides caused accumulation of GTP-bound Rap1B in a dose-dependent manner. By contrast, in PAR-1- and PAR-4-desensitized platelets, thrombin failed to activate Rap1B. Thrombin, PAR-1-, or PAR-4-activating peptides also induced the increase of intracellular Ca(2+) concentration and the release of serotonin in a dose-dependent manner. We found that activation of Rap1B by selected doses of agonists able to elicit comparable intracellular Ca(2+) increase and serotonin release was differently dependent on secreted ADP. In the presence of the ADP scavengers apyrase or phosphocreatine-phosphocreatine kinase, activation of Rap1B induced by stimulation of either PAR-1 or PAR-4 was totally inhibited. By contrast, thrombin-induced activation of Rap1B was only minimally affected by neutralization of secreted ADP. Concomitant stimulation of both PAR-1 and PAR-4 in the presence of ADP scavengers still resulted in a strongly reduced activation of Rap1B. A similar effect was also observed upon blockade of the P2Y12 receptor for ADP, as well as in P2Y12 receptor-deficient human platelets, but not after blockade of the P2Y1 receptor. Activation of Rap1B induced by thrombin was not affected by preincubation of platelets with the anti-GPIbalpha monoclonal antibody AK2 in the absence of ADP scavengers or a P2Y12 antagonist but was totally abolished when secreted ADP was neutralized or after blockade of the P2Y12 receptor. Similarly, cleavage of the extracellular portion of GPIbalpha by the cobra venom mocarhagin totally prevented Rap1B activation induced by thrombin in the presence of apyrase and in P2Y12 receptor-deficient platelets. By contrast, inhibition of MAP kinases or p160ROCK, which have been shown to be activated upon thrombin binding to GPIb-IX-V, did not affect agonist-induced activation of Rap1B in the presence of ADP scavengers. These results indicate that although both PAR-1 and PAR-4 signal Rap1B activation, the ability of thrombin to activate this GTPase independently of secreted ADP involves costimulation of both receptors as well as binding to GPIb-IX-V

Tools for Monitoring Robust Regression in SAS IML Studio: S, MM, LTS, LMS and Especially the Forward Search

This report focuses on robust regression tools that are at the core of a JRC system for the routine generation and dissemination of EU import prices and the detection of patterns of anti-fraud relevance in large volumes of trade. These tools have been implemented in SAS in the context of a project supported by the Hercule III program of the European Commission. Although the development framework is very specific to anti-fraud, the applicability of the SAS package is much wider and the underlying models (that are by the academic co-authors of the report) are very general. The forward search (FS) is a general method of robust data fitting that moves smoothly from very robust to maximum likelihood estimation. The regression procedures are already included in a MATLAB toolbox, FSDA, developed by the same authors of this report. The work on a SAS version of the FS originates from the need for the analysis of large data sets expressed by law enforcement services operating in the European Union that can use our SAS software for detecting data anomalies that may point to fraudulent customs returns. The series of fits provided by the FS leads to the adaptive data-dependent choice of highly efficient robust estimates. It also allows monitoring of residuals and parameter estimates for fits of differing robustness. Our SAS package applies the idea of monitoring to several robust estimators for regression for a range of values of breakdown point or nominal efficiency, leading to adaptive values for these parameters. Examples in the report are for S estimation and, not included in FSDA, for Least Median of Squares (LMS) and Least Trimmed Squares (LTS) regression. Specific to our SAS implementation, we describe the approximations used to provide fast analyses of large datasets using a FS with batches. We also present examples of robust transformations of the response in regression. Further, our package provides the SAS community with methods of monitoring robust estimators for multivariate data, including multivariate data transformations.JRC.I.3-Text and Data Minin

breastfeeding in breast cancer survivors pattern behaviour and effect on breast cancer outcome

Abstract Little is known regarding the safety and feasibility of breastfeeding in women with a history of breast cancer. We have performed a survey among breast cancer patients who completed their pregnancy following breast cancer management to examine their lactation behaviours and its effect on breast cancer outcome. Out of 32 women identified, 20 were reachable and accepted to take the questionnaire. Ten women initiated breastfeeding, 4 stopped within one month and 6 had long-term success with a median period of 11 months (7–17 months). The latter were all previously subjected to breast conserving surgery and received qualified lactation counselling at delivery. The main reasons for not initiating breastfeeding were "uncertainty regarding maternal safety" and "a priori unfeasibility" expressed either by the obstetrician or by the oncologist. At a median follow-up of 48 months following delivery, all 20 women were alive with two relapses; one in each group (i.e., lactating and non-lactating). This analysis adds to the limited available evidence on the feasibility and safety of breastfeeding in breast cancer survivors. Proper fertility and survivorship counselling is crucial and requires more attention in breast cancer clinics