Sorting and Selection with Imprecise Comparisons

In experimental psychology, the method of paired comparisons was proposed as a means for ranking preferences amongst n elements of a human subject. The method requires performing all (n2) comparisons then sorting elements according to the number of wins. The large number of comparisons is performed to counter the potentially faulty decision-making of the human subject, who acts as an imprecise comparator. We consider a simple model of the imprecise comparisons: there exists some δ> 0 such that when a subject is given two elements to compare, if the values of those elements (as perceived by the subject) differ by at least δ, then the comparison will be made correctly; when the two elements have values that are within δ, the outcome of the comparison is unpredictable. This δ corresponds to the just noticeable difference unit (JND) or difference threshold in the psychophysics literature, but does not require the statistical assumptions used to define this value. In this model, the standard method of paired comparisons minimizes the errors introduced by the imprecise comparisons at the cost of (n2) comparisons. We show that the same optimal guarantees can be achieved using 4 n 3/2 comparisons, and we prove the optimality of our method. We then explore the general tradeoff between the guarantees on the error that can be made and number of comparisons for the problems of sorting, max-finding, and selection. Our results provide close-to-optimal solutions for each of these problems.Engineering and Applied Science

Evaluating the Employment Impact of Business Incentive Programs in EU Disadvantaged Areas. A case from Northern Italy

Business incentive programs have been increasingly popular within the EU as regional economic development tools to promote employment growth in areas with severely distressed and/or declining socio-economic conditions. Reliable evidenced on the effective net employment impact of such initiatives are greatly needed to help refining future intervention as, to these days, European policy makers' decisions can mostly be supported only by monitoring and survey analyses. This paper proposes a method of analysis to assess the employment impact of the business incentive initiatives implemented in the EU areas with declining industrial production (EU 'Objective 2' areas). The proposed method is a comparison-group evaluation approach that uses panels of employment data aggregated by geographic areas (similarly to the evaluation approach successfully adopted by recent studies of the US Enterprise Zone Programs). Details of the proposed method of analysis are illustrated through an empirical application: the evaluation of the business incentive program co-funded by the European Regional Development Fund in the 'Objective 2' areas of the Piedmont region (Italy). Results from such application prove the effectiveness and the robustness of the proposed method for impact evaluation analyses with longitudinal data, and highlight how the Piedmont's business incentive program did not significantly affect employment in the 'Objective 2 areas'.

Does it pay to attend a prestigious university?

This paper provides evidence of heterogeneity in the returns to higher education in the UK. Attending the most prestigious universities leads to a wage premium of up to 6% for males. The rise in participation in higher education also led to a greater sorting of students and an increase in the returns to quality. These results somehow justify the recent introduction of top-up fees. Additionally, identification strategy matters and OLS estimates may be severely biased. However, our estimates, based on propensity score matching, are imprecise due to the thinness of the common support.Higher Education Quality, Tuition fees

Constrained Job Matching: Does Teacher Job Search Harm Disadvantaged Urban Schools?

Search theory suggests that early career job changes lead to better matches that benefit both workers and firms, but this may not hold in teacher labor markets characterized by salary rigidities, barriers to entry, and substantial differences in working conditions. Of particular concern to education policy makers is the possibility that teacher turnover adversely affects the quality of instruction in schools serving predominantly disadvantaged children. Although such schools experience higher turnover on average than others, the impact on the quality of instruction depends crucially on whether it is the more productive teachers who are more likely to depart. The absence of direct measures of productivity typically hinders efforts to measure the effect of turnover on worker quality. In the case of teachers, however, the availability of matched panel data of students and teachers enables the isolation of the contributions of teachers to achievement. The empirical analysis reveals that teachers who remain in their school tend to outperform those who leave, particularly those who exit the Texas public schools entirely. Moreover, this gap appears to be larger for schools serving predominantly low income students, evidence that high turnover is not nearly as damaging as many suggest.teacher turnover

Analysis of the potentials of multi criteria decision analysis methods to conduct sustainability assessment

Sustainability assessments require the management of a wide variety of information types, parameters and uncertainties. Multi criteria decision analysis (MCDA) has been regarded as a suitable set of methods to perform sustainability evaluations as a result of its flexibility and the possibility of facilitating the dialogue between stakeholders, analysts and scientists. However, it has been reported that researchers do not usually properly define the reasons for choosing a certain MCDA method instead of another. Familiarity and affinity with a certain approach seem to be the drivers for the choice of a certain procedure. This review paper presents the performance of five MCDA methods (i.e. MAUT, AHP, PROMETHEE, ELECTRE and DRSA) in respect to ten crucial criteria that sustainability assessments tools should satisfy, among which are a life cycle perspective, thresholds and uncertainty management, software support and ease of use. The review shows that MAUT and AHP are fairly simple to understand and have good software support, but they are cognitively demanding for the decision makers, and can only embrace a weak sustainability perspective as trade-offs are the norm. Mixed information and uncertainty can be managed by all the methods, while robust results can only be obtained with MAUT. ELECTRE, PROMETHEE and DRSA are non-compensatory approaches which consent to use a strong sustainability concept, accept a variety of thresholds, but suffer from rank reversal. DRSA is less demanding in terms of preference elicitation, is very easy to understand and provides a straightforward set of decision rules expressed in the form of elementary “if … then …” conditions. Dedicated software is available for all the approaches with a medium to wide range of results capability representation. DRSA emerges as the easiest method, followed by AHP, PROMETHEE and MAUT, while ELECTRE is regarded as fairly difficult. Overall, the analysis has shown that most of the requirements are satisfied by the MCDA methods (although to different extents) with the exclusion of management of mixed data types and adoption of life cycle perspective which are covered by all the considered approaches