Endogenous business cycles and stabilization policies

The paper reports results on the effects of stylized stabilization policies on endogenously created fluctuations. A simple monetary model with intertemporally optimizing agents is considered. Fluctuations in output may occur due to fluctuations in labor supply which are again caused by volatile expectations which are ``self fulfilling'', i.e. correct given the model. It turns out that stabilization policies that are sufficiently countercyclical in the sense that government spending (on transfers or demand) depends sufficiently strongly negatively on GNP-increases can stabilize the economy at a monetary steadystate for an arbitrarily low degree of distortion of that steady state. Such stabilization has unambiguously good welfare effects and can be achieved without features such as positive lump sum taxation or negative income taxation as part of the stabilization policy.

Endogenous information structures

Many models in the economics literature deal with strategic situations withprivately informed agents. In those models the information structure isassumed to be exogenous and common knowledge. We consider whether suchmodels, and the results they produce, are robust with respect theendogenization of the information structure. The results depend on whetherinformation acquisition is secret or private, and on whether the strategicsituation involves simultaneous or sequential moves. In particular we findthat only when information is secretly acquired and moves are simultaneous,the results are fully robust. When information is acquired secretly butmoves are sequential additional equilibria may appear. Instead, privateinformation acquisition may make the equilibrium set smaller.

Validation procedures in radiological diagnostic models. Neural network and logistic regression

The objective of this paper is to compare the performance of twopredictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validation methods did not reveal statistically significant differences between LR and NN rules. The neural network classifier performs better than the one based on logistic regression. This advantage is well detected by three-fold cross-validation, but remains unnoticed when leave-one-out or bootstrap algorithms are used.

Unemployment insurance with endogenous search intensity and precautionary saving

A welfare analysis of unemployment insurance (UI) is performed in a generalequilibrium job search model. Finitely-lived, risk-averse workers smooth consumption over time by accumulating assets, choose search effort whenunemployed, and suffer disutility from work. Firms hire workers, purchasecapital, and pay taxes to finance worker benefits; their equity is the assetaccumulated by workers. A matching function relates unemployment, hiringexpenditure, and search effort to the formation of jobs. The model is calibrated to US data; the parameters relating job search effort to the probability of job finding are chosen to match microeconomic studies ofunemployment spells. Under logarithmic utility, numerical simulation shows rather small welfaregains from UI. Even without UI, workers smooth consumption effectivelythrough asset accumulation. Greater risk aversion leads to substantiallylarger welfare gains from UI; however, even in this case much of its welfareimpact is due not to consumption smoothing effects, but rather to decreased work disutility, or to a variety of externalities.

Fixed and random effects in Classical and Bayesian regression

This paper proposes a common and tractable framework for analyzingdifferent definitions of fixed and random effects in a contant-slopevariable-intercept model. It is shown that, regardless of whethereffects (i) are treated as parameters or as an error term, (ii) areestimated in different stages of a hierarchical model, or whether (iii)correlation between effects and regressors is allowed, when the sameinformation on effects is introduced into all estimation methods, theresulting slope estimator is also the same across methods. If differentmethods produce different results, it is ultimately because differentinformation is being used for each methods.

The importance of individual heterogeneity in the decomposition of measures of socioeconomic inequality in health: An approach based on quantile regression

This paper shows how recently developed regression-based methods for thedecomposition of health inequality can be extended to incorporateindividual heterogeneity in the responses of health to the explanatoryvariables. We illustrate our method with an application to the CanadianNPHS of 1994. Our strategy for the estimation of heterogeneous responsesis based on the quantile regression model. The results suggest that thereis an important degree of heterogeneity in the association of health toexplanatory variables which, in turn, accounts for a substantial percentageof inequality in observed health. A particularly interesting finding isthat the marginal response of health to income is zero for healthyindividuals but positive and significant for unhealthy individuals. Theheterogeneity in the income response reduces both overall health inequalityand income related health inequality.

Random measurement error and regression dilution bias.

Summary points: - The bias introduced by random measurement error will be different depending on whether the error is in an exposure variable (risk factor) or outcome variable (disease) - Random measurement error in an exposure variable will bias the estimates of regression slope coefficients towards the null - Random measurement error in an outcome variable will instead increase the standard error of the estimates and widen the corresponding confidence intervals, making results less likely to be statistically significant - Increasing sample size will help minimise the impact of measurement error in an outcome variable but will only make estimates more precisely wrong when the error is in an exposure variable

Expression and presentation of endogenous mouse mammary tumor virus superantigens by thymic and splenic dendritic cells and B cells.

Tolerance against superantigens (SAgs) encoded by endogenous mouse mammary tumor virus (Mtv) loci involves the intrathymic deletion of SAg-reactive T cells expressing a particular TCR V beta-chain, presumably upon presentation of the SAg by specialized APC. However, although the role of dendritic cells (DC) in the induction of tolerance against conventional Ags has been demonstrated, little is known about the role played by DC in tolerance induction against Mtv SAgs. Moreover, there is conflicting evidence concerning the capacity of DC to express and present Mtv SAgs. In this report we have analyzed the expression of Mtv SAgs in highly purified thymic and splenic DC and B cells by reverse transcriptase-PCR, using primers amplifying Mtv SAg-specific spliced mRNAs. DC express Mtv SAgs at levels comparable to B cells, but display a differential expression pattern of the various Mtv loci compared with B cells. Furthermore, our results show that DC are able to induce the deletion of SAg-reactive thymocytes in an in vitro assay, indicating that Mtv SAgs are functionally expressed on the DC surface. Collectively, our data are consistent with the hypothesis that DC play a role in the induction of intrathymic tolerance to Mtv SAgs.

Phenotypic switching in Pseudomonas brassicacearum involves GacS- and GacA-dependent Rsm small RNAs.

The plant-beneficial bacterium Pseudomonas brassicacearum forms phenotypic variants in vitro as well as in planta during root colonization under natural conditions. Transcriptome analysis of typical phenotypic variants using microarrays containing coding as well as noncoding DNA fragments showed differential expression of several genes relevant to secondary metabolism and of the small RNA (sRNA) genes rsmX, rsmY, and rsmZ. Naturally occurring mutations in the gacS-gacA system accounted for phenotypic switching, which was characterized by downregulation of antifungal secondary metabolites (2,4-diacetylphloroglucinol and cyanide), indoleacetate, exoenzymes (lipase and protease), and three different N-acyl-homoserine lactone molecules. Moreover, in addition to abrogating these biocontrol traits, gacS and gacA mutations resulted in reduced expression of the type VI secretion machinery, alginate biosynthesis, and biofilm formation. In a gacA mutant, the expression of rsmX was completely abolished, unlike that of rsmY and rsmZ. Overexpression of any of the three sRNAs in the gacA mutant overruled the pleiotropic changes and restored the wild-type phenotypes, suggesting functional redundancy of these sRNAs. In conclusion, our data show that phenotypic switching in P. brassicacearum results from mutations in the gacS-gacA system.

The influence of supplementary health insurance on switching behaviour: evidence from Swiss data.

This paper focuses on the switching behaviour of enrolees in the Swiss basic health insurance system. Even though the new Federal Law on Social Health Insurance (LAMal) was implemented in 1996 to promote competition among health insurers in basic insurance, there is limited evidence of premium convergence within cantons. This indicates that competition has not been effective so far, and reveals some inertia among consumers who seem reluctant to switch to less expensive funds. We investigate one possible barrier to switching behaviour, namely the influence of supplementary insurance. We use survey data on health plan choice (a sample of 1943 individuals whose switching behaviours were observed between 1997 and 2000) as well as administrative data relative to all insurance companies that operated in the 26 Swiss cantons between 1996 and 2005. The decision to switch and the decision to subscribe to a supplementary contract are jointly estimated.Our findings show that holding a supplementary insurance contract substantially decreases the propensity to switch. However, there is no negative impact of supplementary insurance on switching when the individual assesses his/her health as 'very good'. Our results give empirical support to one possible mechanism through which supplementary insurance might influence switching decisions: given that subscribing to basic and supplementary contracts with two different insurers may induce some administrative costs for the subscriber, holding supplementary insurance acts as a barrier to switch if customers who consider themselves 'bad risks' also believe that insurers reject applications for supplementary insurance on these grounds. In comparison with previous research, our main contribution is to offer a possible explanation for consumer inertia. Our analysis illustrates how consumer choice for one's basic health plan interacts with the decision to subscribe to supplementary insurance.

Prediction of 18-month survival in patients with primary myelodysplastic syndrome. A regression model and scoring system based on the combination of chromosome findings and the Bournemouth score.

The predictive potential of six selected factors was assessed in 72 patients with primary myelodysplastic syndrome using univariate and multivariate logistic regression analysis of survival at 18 months. Factors were age (above median of 69 years), dysplastic features in the three myeloid bone marrow cell lineages, presence of chromosome defects, all metaphases abnormal, double or complex chromosome defects (C23), and a Bournemouth score of 2, 3, or 4 (B234). In the multivariate approach, B234 and C23 proved to be significantly associated with a reduction in the survival probability. The similarity of the regression coefficients associated with these two factors means that they have about the same weight. Consequently, the model was simplified by counting the number of factors (0, 1, or 2) present in each patient, thus generating a scoring system called the Lausanne-Bournemouth score (LB score). The LB score combines the well-recognized and easy-to-use Bournemouth score (B score) with the chromosome defect complexity, C23 constituting an additional indicator of patient outcome. The predicted risk of death within 18 months calculated from the model is as follows: 7.1% (confidence interval: 1.7-24.8) for patients with an LB score of 0, 60.1% (44.7-73.8) for an LB score of 1, and 96.8% (84.5-99.4) for an LB score of 2. The scoring system presented here has several interesting features. The LB score may improve the predictive value of the B score, as it is able to recognize two prognostic groups in the intermediate risk category of patients with B scores of 2 or 3. It has also the ability to identify two distinct prognostic subclasses among RAEB and possibly CMML patients. In addition to its above-described usefulness in the prognostic evaluation, the LB score may bring new insights into the understanding of evolution patterns in MDS. We used the combination of the B score and chromosome complexity to define four classes which may be considered four possible states of myelodysplasia and which describe two distinct evolutional pathways.

Investigations on hydrogen isotope ratios of endogenous urinary steroids: reference-population-based thresholds and proof-of-concept.

Carbon isotope ratio (CIR) analysis has been routinely and successfully used in sports drug testing for many years to uncover the misuse of endogenous steroids. One limitation of the method is the availability of steroid preparations exhibiting CIRs equal to endogenous steroids. To overcome this problem, hydrogen isotope ratios (HIR) of endogenous urinary steroids were investigated as a potential complement; results obtained from a reference population of 67 individuals are presented herein. An established sample preparation method was modified and improved to enable separate measurements of each analyte of interest where possible. From the fraction of glucuronidated steroids; pregnanediol, 16-androstenol, 11-ketoetiocholanolone, androsterone (A), etiocholanolone (E), dehydroepiandrosterone (D), 5α- and 5β-androstanediol, testosterone and epitestosterone were included. In addition, sulfate conjugates of A, E, D, epiandrosterone and 17α- and 17β-androstenediol were considered and analyzed after acidic solvolysis. The obtained results enabled the calculation of the first reference-population-based thresholds for HIR of urinary steroids that can readily be applied to routine doping control samples. Proof-of-concept was accomplished by investigating urine specimens collected after a single oral application of testosterone-undecanoate. The HIR of most testosterone metabolites were found to be significantly influenced by the exogenous steroid beyond the established threshold values. Additionally, one regular doping control sample with an extraordinary testosterone/epitestosterone ratio of 100 without suspicious CIR was subjected to the complementary methodology of HIR analysis. The HIR data eventually provided evidence for the exogenous origin of urinary testosterone metabolites. Despite further investigations on HIR being advisable to corroborate the presented reference-population-based thresholds, the developed method proved to be a new tool supporting modern sports drug testing procedures.

Uncertainty Quantification with Support Vector Regression Prediction Models

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. The paper considers a data driven approach in modelling uncertainty in spatial predictions. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic features and describe stochastic variability and non-uniqueness of spatial properties. It is able to capture and preserve key spatial dependencies such as connectivity, which is often difficult to achieve with two-point geostatistical models. Semi-supervised SVR is designed to integrate various kinds of conditioning data and learn dependences from them. A stochastic semi-supervised SVR model is integrated into a Bayesian framework to quantify uncertainty with multiple models fitted to dynamic observations. The developed approach is illustrated with a reservoir case study. The resulting probabilistic production forecasts are described by uncertainty envelopes.

The costs of crossing paths and switching tasks between audition and vision.

Switching from one functional or cognitive operation to another is thought to rely on executive/control processes. The efficacy of these processes may depend on the extent of overlap between neural circuitry mediating the different tasks; more effective task preparation (and by extension smaller switch costs) is achieved when this overlap is small. We investigated the performance costs associated with switching tasks and/or switching sensory modalities. Participants discriminated either the identity or spatial location of objects that were presented either visually or acoustically. Switch costs between tasks were significantly smaller when the sensory modality of the task switched versus when it repeated. This was the case irrespective of whether the pre-trial cue informed participants only of the upcoming task, but not sensory modality (Experiment 1) or whether the pre-trial cue was informative about both the upcoming task and sensory modality (Experiment 2). In addition, in both experiments switch costs between the senses were positively correlated when the sensory modality of the task repeated across trials and not when it switched. The collective evidence supports the independence of control processes mediating task switching and modality switching and also the hypothesis that switch costs reflect competitive interference between neural circuits.