Determinants of linear judgment: A meta-analysis of lens model studies

The mathematical representation of Brunswik s lens model has been usedextensively to study human judgment and provides a unique opportunity to conduct ameta-analysis of studies that covers roughly five decades. Specifically, we analyzestatistics of the lens model equation (Tucker, 1964) associated with 259 different taskenvironments obtained from 78 papers. In short, we find on average fairly high levelsof judgmental achievement and note that people can achieve similar levels of cognitiveperformance in both noisy and predictable environments. Although overall performancevaries little between laboratory and field studies, both differ in terms of components ofperformance and types of environments (numbers of cues and redundancy). An analysisof learning studies reveals that the most effective form of feedback is information aboutthe task. We also analyze empirically when bootstrapping is more likely to occur. Weconclude by indicating shortcomings of the kinds of studies conducted to date, limitationsin the lens model methodology, and possibilities for future research.

Solving heterogeneous-agent models by projection and perturbation

The paper proposes a numerical solution method for general equilibrium models with a continuum of heterogeneous agents, which combines elements of projection and of perturbation methods. The basic idea is to solve first for the stationary solutionof the model, without aggregate shocks but with fully specified idiosyncratic shocks. Afterwards one computes a first-order perturbation of the solution in the aggregate shocks. This approach allows to include a high-dimensional representation of the cross-sectional distribution in the state vector. The method is applied to a model of household saving with uninsurable income risk and liquidity constraints. The model includes not only productivity shocks, but also shocks to redistributive taxation, which cause substantial short-run variation in the cross-sectional distribution of wealth. If those shocks are operative, it is shown that a solution method based on very few statistics of the distribution is not suitable, while the proposed method can solve the model with high accuracy, at least for the case of small aggregate shocks. Techniques are discussed to reduce the dimension of the state space such that higher order perturbations are feasible.Matlab programs to solve the model can be downloaded.

Essays in general equilibrium asset pricing

ABSTRACT : Research in empirical asset pricing has pointed out several anomalies both in the cross section and time series of asset prices, as well as in investors' portfolio choice. This dissertation aims to discover the forces driving some of these "puzzling" asset pricing dynamics and portfolio decisions observed in the financial market. Through the dissertation I construct and study dynamic general equilibrium models of heterogeneous investors in the presence of frictions and evaluate quantitatively their implications for financial-market asset prices and portfolio choice. I also explore the potential roots of puzzles in international finance. Chapter 1 shows that, by introducing jointly endogenous no-default type of borrowing constraints and heterogeneous beliefs in a dynamic general-equilibrium economy, many empirical features of stock return volatility can be reproduced. While most of the research on stock return volatility is empirical, this paper provides a theoretical framework that is able to reproduce simultaneously the cross section and time series stylized facts concerning stock returns and their volatility. In contrast to the existing theoretical literature related to stock return volatility, I don't impose persistence or regimes in any of the exogenous state variables or in preferences. Volatility clustering, asymmetry in the stock return-volatility relationship, and pricing of multi-factor volatility components in the cross section all arise endogenously as a consequence of the feedback between the binding of no-default constraints and heterogeneous beliefs. Chapters 2 and 3 explore the implications of differences of opinion across investors in different countries for international asset pricing anomalies. Chapter 2 demonstrates that several international finance "puzzles" can be reproduced by a single risk factor which captures heterogeneous beliefs across international investors. These puzzles include: (i) home equity preference; (ii) the dependence of firm returns on local and foreign factors; (iii) the co-movement of returns and international capital flows; and (iv) abnormal returns around foreign firm cross-listing events in the local market. These are reproduced in a setup with symmetric information and in a perfectly integrated world with multiple countries and independent processes producing the same good. Chapter 3 shows that by extending this framework to multiple goods and correlated production processes; the "forward premium puzzle" arises naturally as a compensation for the heterogeneous expectations about the depreciation of the exchange rate held by international investors. Chapters 2 and 3 propose differences of opinion across international investors as the potential resolution of several international finance `puzzles'. In a globalized world where both capital and information flow freely across countries, this explanation seems more appealing than existing asymmetric information or segmented markets theories aiming to explain international finance puzzles.

Building a Social Accounting Matrix within the ESA95 Framework: Obtaining a Dataset for Applied General Equilibrium Modelling

This research provides a description of the process followed in order to assemble a "Social Accounting Matrix" for Spain corresponding to the year 2000 (SAMSP00). As argued in the paper, this process attempts to reconcile ESA95 conventions with requirements of applied general equilibrium modelling. Particularly, problems related to the level of aggregation of net taxation data, and to the valuation system used for expressing the monetary value of input-output transactions have deserved special attention. Since the adoption of ESA95 conventions, input-output transactions have been preferably valued at basic prices, which impose additional difficulties on modellers interested in computing applied general equilibrium models. This paper addresses these difficulties by developing a procedure that allows SAM-builders to change the valuation system of input-output transactions conveniently. In addition, this procedure produces new data related to net taxation information.

Parents' willingness to pay for diminishing children's pain during blood sampling.

BACKGROUND: Blood sampling is a frequent medical procedure, very often considered as a stressful experience by children. Local anesthetics have been developed, but are expensive and not reimbursed by insurance companies in our country. We wanted to assess parents' willingness to pay (WTP) for this kind of drug. PATIENTS AND METHODS: Over 6 months, all parents of children presenting for general (GV) or specialized visit (SV) with blood sampling. WTP was assessed through three scenarios [avoiding blood sampling (ABS), using the drug on prescription (PD), or over the counter (OTC)], with a payment card system randomized to ascending or descending order of prices (AO or DO). RESULTS: Fifty-six responses were collected (34 GV, 22 SV, 27 AO and 29 DO), response rate 40%. Response distribution was wide, with median WTP of 40 for ABS, 25 for PD, 10 for OTC, which is close to the drug's real price. Responses were similar for GV and SV. Median WTP amounted to 0.71, 0.67, 0.20% of respondents' monthly income for the three scenarios, respectively, with a maximum at 10%. CONCLUSIONS: Assessing parents' WTP in an outpatient setting is difficult, with wide result distribution, but median WTP is close to the real drug price. This finding could be used to promote insurance coverage for this drug.

Building a Social Accounting Matrix within the ESA95 Framework: Obtaining a Dataset for Applied General Equilibrium Modelling

This research provides a description of the process followed in order to assemble a "Social Accounting Matrix" for Spain corresponding to the year 2000 (SAMSP00). As argued in the paper, this process attempts to reconcile ESA95 conventions with requirements of applied general equilibrium modelling. Particularly, problems related to the level of aggregation of net taxation data, and to the valuation system used for expressing the monetary value of input-output transactions have deserved special attention. Since the adoption of ESA95 conventions, input-output transactions have been preferably valued at basic prices, which impose additional difficulties on modellers interested in computing applied general equilibrium models. This paper addresses these difficulties by developing a procedure that allows SAM-builders to change the valuation system of input-output transactions conveniently. In addition, this procedure produces new data related to net taxation information.

Assessment of the COOP charts with and without pictures in a Swiss population.

OBJECTIVES: This study aimed to assess the validity of COOP charts in a general population sample, to examine whether illustrations contribute to instrument validity, and to establish general population norms. METHODS: A general population mail survey was conducted among 20-79 years old residents of the Swiss canton of Vaud. Participants were invited to complete COOP charts, the SF-36 Health Survey; they also provided data on health service use in the previous month. Two thirds of the respondents received standard COOP charts, the rest received charts without illustrations. RESULTS: Overall 1250 persons responded (54%). The presence of illustrations did not affect score distributions, except that the illustrated 'physical fitness' chart drew greater non-response (10 vs. 3%, p < 0.001). Validity tests were similar for illustrated and picture-less charts. Factor analysis yielded two principal components, corresponding to physical and mental health. Six COOP charts showed strong and nearly linear relationships with corresponding SF36 scores (all p < 0.001), demonstrating concurrent validity. Similarly, most COOP charts were associated with the use of medical services in the past month. Only the chart on 'social support' partly deviated from construct validity hypotheses. Population norms revealed a generally lower health status in women and an age-related decline in physical health. CONCLUSIONS: COOP charts can be used to assess the health status of a general population. Their validity is good, with the possible exception of the 'social support' chart. The illustrations do not affect the properties of this instrument.

The influence of drinking pattern, at individual and aggregate levels, on alcohol-related negative consequences.

AIM: To determine the extent drinking patterns (at the individual and country level) are associated with alcohol-related consequences over and above the total alcohol the person consumes. METHODS: Hierarchical linear models were estimated based on general population surveys conducted in 18 countries participating in the GENACIS project. RESULTS: In general, the positive association between drinking pattern scores and alcohol-related consequences was found at both the individual and country levels, independent of volume of drinking. In addition, a significant interaction effect indicated that the more detrimental the country's drinking pattern, the less steep the association between the volume of drinking and its consequences. CONCLUSION: Drinking patterns have an independent impact on consequences over and above the relationship between volume and consequences.

Stochastic models and numerical algorithms for a class of regulatory gene networks.

Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.

Are niche-based species distribution models transferable in space?

Aim To assess the geographical transferability of niche-based species distribution models fitted with two modelling techniques. Location Two distinct geographical study areas in Switzerland and Austria, in the subalpine and alpine belts. Methods Generalized linear and generalized additive models (GLM and GAM) with a binomial probability distribution and a logit link were fitted for 54 plant species, based on topoclimatic predictor variables. These models were then evaluated quantitatively and used for spatially explicit predictions within (internal evaluation and prediction) and between (external evaluation and prediction) the two regions. Comparisons of evaluations and spatial predictions between regions and models were conducted in order to test if species and methods meet the criteria of full transferability. By full transferability, we mean that: (1) the internal evaluation of models fitted in region A and B must be similar; (2) a model fitted in region A must at least retain a comparable external evaluation when projected into region B, and vice-versa; and (3) internal and external spatial predictions have to match within both regions. Results The measures of model fit are, on average, 24% higher for GAMs than for GLMs in both regions. However, the differences between internal and external evaluations (AUC coefficient) are also higher for GAMs than for GLMs (a difference of 30% for models fitted in Switzerland and 54% for models fitted in Austria). Transferability, as measured with the AUC evaluation, fails for 68% of the species in Switzerland and 55% in Austria for GLMs (respectively for 67% and 53% of the species for GAMs). For both GAMs and GLMs, the agreement between internal and external predictions is rather weak on average (Kulczynski's coefficient in the range 0.3-0.4), but varies widely among individual species. The dominant pattern is an asymmetrical transferability between the two study regions (a mean decrease of 20% for the AUC coefficient when the models are transferred from Switzerland and 13% when they are transferred from Austria). Main conclusions The large inter-specific variability observed among the 54 study species underlines the need to consider more than a few species to test properly the transferability of species distribution models. The pronounced asymmetry in transferability between the two study regions may be due to peculiarities of these regions, such as differences in the ranges of environmental predictors or the varied impact of land-use history, or to species-specific reasons like differential phenotypic plasticity, existence of ecotypes or varied dependence on biotic interactions that are not properly incorporated into niche-based models. The lower variation between internal and external evaluation of GLMs compared to GAMs further suggests that overfitting may reduce transferability. Overall, a limited geographical transferability calls for caution when projecting niche-based models for assessing the fate of species in future environments.

Genetic associations in the detection of QTLs for wheat spike-related traits

The objective of this work was to assess the genetic diversity and population structure of wheat genotypes, to detect significant and stable genetic associations, as well as to evaluate the efficiency of statistical models to identify chromosome regions responsible for the expression of spike-related traits. Eight important spike characteristics were measured during five growing seasons in Serbia. A set of 30 microsatellite markers positioned near important agronomic loci was used to evaluate genetic diversity, resulting in a total of 349 alleles. The marker-trait associations were analyzed using the general linear and mixed linear models. The results obtained for number of allelic variants per locus (11.5), average polymorphic information content value (0.68), and average gene diversity (0.722) showed that the exceptional level of polymorphism in the genotypes is the main requirement for association studies. The population structure estimated by model-based clustering distributed the genotypes into six subpopulations according to log probability of data. Significant and stable associations were detected on chromosomes 1B, 2A, 2B, 2D, and 6D, which explained from 4.7 to 40.7% of total phenotypic variations. The general linear model identified a significantly larger number of marker-trait associations (192) than the mixed linear model (76). The mixed linear model identified nine markers associated to six traits.

Forecasting tourism demand to Catalonia: neural networks vs. time series models

The increasing interest aroused by more advanced forecasting techniques, together with the requirement for more accurate forecasts of tourismdemand at the destination level due to the constant growth of world tourism, has lead us to evaluate the forecasting performance of neural modelling relative to that of time seriesmethods at a regional level. Seasonality and volatility are important features of tourism data, which makes it a particularly favourable context in which to compare the forecasting performance of linear models to that of nonlinear alternative approaches. Pre-processed official statistical data of overnight stays and tourist arrivals fromall the different countries of origin to Catalonia from 2001 to 2009 is used in the study. When comparing the forecasting accuracy of the different techniques for different time horizons, autoregressive integrated moving average models outperform self-exciting threshold autoregressions and artificial neural network models, especially for shorter horizons. These results suggest that the there is a trade-off between the degree of pre-processing and the accuracy of the forecasts obtained with neural networks, which are more suitable in the presence of nonlinearity in the data. In spite of the significant differences between countries, which can be explained by different patterns of consumer behaviour,we also find that forecasts of tourist arrivals aremore accurate than forecasts of overnight stays.

Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and pareto filters

Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the ethanol production in the fermentation of Saccharomyces cerevisiae.

Supergravity models of (3+1)-dimensional QCD

The most general black M5-brane solution of eleven-dimensional supergravity (with a flat R4 spacetime in the brane and a regular horizon) is characterized by charge, mass and two angular momenta. We use this metric to construct general dual models of large-N QCD (at strong coupling) that depend on two free parameters. The mass spectrum of scalar particles is determined analytically (in the WKB approximation) and numerically in the whole two-dimensional parameter space. We compare the mass spectrum with analogous results from lattice calculations, and find that the supergravity predictions are close to the lattice results everywhere on the two dimensional parameter space except along a special line. We also examine the mass spectrum of the supergravity Kaluza-Klein (KK) modes and find that the KK modes along the compact D-brane coordinate decouple from the spectrum for large angular momenta. There are however KK modes charged under a U(1)×U(1) global symmetry which do not decouple anywhere on the parameter space. General formulas for the string tension and action are also given.

Prevalence of iodine inadequacy in Switzerland assessed by the estimated average requirement cut-point method in relation to the impact of iodized salt.

OBJECTIVE: To assess the iodine status of Swiss population groups and to evaluate the influence of iodized salt as a vector for iodine fortification. DESIGN: The relationship between 24 h urinary iodine and Na excretions was assessed in the general population after correcting for confounders. Single-day intakes were estimated assuming that 92 % of dietary iodine was excreted in 24 h urine. Usual intake distributions were derived for male and female population groups after adjustment for within-subject variability. The estimated average requirement (EAR) cut-point method was applied as guidance to assess the inadequacy of the iodine supply. SETTING: Public health strategies to reduce the dietary salt intake in the general population may affect its iodine supply. SUBJECTS: The study population (1481 volunteers, aged ≥15 years) was randomly selected from three different linguistic regions of Switzerland. RESULTS: The 24 h urine samples from 1420 participants were determined to be properly collected. Mean iodine intakes obtained for men (n 705) and women (n 715) were 179 (sd 68.1) µg/d and 138 (sd 57.8) µg/d, respectively. Urinary Na and Ca, and BMI were significantly and positively associated with higher iodine intake, as were men and non-smokers. Fifty-four per cent of the total iodine intake originated from iodized salt. The prevalence of inadequate iodine intake as estimated by the EAR cut-point method was 2 % for men and 14 % for women. CONCLUSIONS: The estimated prevalence of inadequate iodine intake was within the optimal target range of 2-3 % for men, but not for women.