Economists and psychologists have recently been developing new theories of decision making under uncertainty that can accommodate the observed violations of standard statistical decision theoretic axioms by experimental subjects. We propose a procedure which finds a collection of decision rules that best explain the behavior of experimental subjects. The procedure is a combination of maximum likelihood estimation of the rules together with an implicit classification of subjects to the various rules, and a penalty for having too many rules. We apply our procedure to data on probabilistic updating by subjects in four different universities. We get remarkably robust results which show that the most important rules used by the subjects (in order of importance) are Bayes ' s rule, a representativeness rule (ignoring the prior), and to a lesser extent, conservatism (over-weighting the prior).

In March 2020, the SARS-CoV-2 virus outbreak was declared as a world pandemic by the World Health Organization (WHO). The only measures for controlling the outbreak are testing and isolation of infected cases. Molecular real-time polymerase chain reaction (PCR) assays are very sensitive but require highly equipped laboratories and well-trained personnel. In this study, a rapid point-of-need detection method was developed to detect the RNA-dependent RNA polymerase (RdRP), envelope protein (E), and nucleocapsid protein (N) genes of SARS-CoV-2 based on the reverse transcription recombinase polymerase amplification (RT-RPA) assay. RdRP, E, and N RT-RPA assays required approximately 15 min to amplify 2, 15, and 15 RNA molecules of molecular standard/reaction, respectively. RdRP and E RT-RPA assays detected SARS-CoV-1 and 2 genomic RNA, whereas the N RT-RPA assay identified only SARS-CoV-2 RNA. All established assays did not cross-react with nucleic acids of other respiratory pathogens. The RT-RPA assay’s clinical sensitivity and specificity in comparison to real-time RT-PCR (n = 36) were 94 and 100% for RdRP; 65 and 77% for E; and 83 and 94% for the N RT-RPA assay. The assays were deployed to the field, where the RdRP RT-RPA assays confirmed to produce the most accurate results in three different laboratories in Africa (n = 89). The RPA assays were run in a mobile suitcase laboratory to facilitate the deployment at point of need. The assays can contribute to speed up the control measures as well as assist in the detection of COVID-19 cases in low-resource settings.

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Economists and psychologists have recently been developing new theories of decision making under uncertainty that can accommodate the observed violations of standard statistical decision theoretic axioms by experimental subjects. We propose a procedure which finds a collection of decision rules that best explain the behavior of experimental subjects. The procedure is a combination of maximum likelihood estimation of the rules together with an implicit classification of subjects to the various rules, and a penalty for having too many rules. We apply our procedure to data on probabilistic updating by subjects in four different universities. We get remarkably robust results which show that the most important rules used by the subjects (in order of importance) are Bayes ' s rule, a representativeness rule (ignoring the prior), and to a lesser extent, conservatism (over-weighting the prior).

SUMMARYRecent studies have stressed the importance of privatization and openness to foreign competition for bank efficiency and economic growth. We study bank efficiency in Turkey, an emerging economy with great heterogeneity in bank types and ownership structures. Earlier studies of Turkish banking had three limitations: (i) excessive reliance on cost-function frontier analyses, wherein volume of loans is a measure of banking output; (ii) pooling all banks or imposing ad hoc heterogeneity assumptions; and (iii) lack of a comprehensive panel data set for proper analysis of productivity and heterogeneity. We use an estimation-classification procedure to find likelihood-driven classification of bank technologies in an 11-year panel. In addition, we augment traditional cost-frontier analysis with a labour-efficiency analysis. We conclude that state banks are not particularly inefficient overall, but that they do utilize labour inefficiently. This partially supports recent calls for privatization. We also conclude that special finance houses (or Islamic banks) utilize the same technology as conventional domestic banks, and do so relatively efficiently. This suggests that they do not cause harm to the financial system. Finally, we conclude that foreign banks utilize a different technology from domestic ones. This suggests that one should not overstate their value to the financial sector.