Do institutions and culture matter for business cycles?

We examine the relationship between institutions, culture and cyclical fluctuations for a sampleof 45 European, Middle Eastern and North African countries. Better governance is associated withshorter and less severe contractions and milder expansions. Certain cultural traits, such as lack ofacceptance of power distance and individualism, are also linked business cycle features. Businesscycle synchronization is tightly related to similarities in the institutional environment. Mediterraneancountries conform to these general tendencies.

The role of awareness, information gathering and processing in school choice

This paper studies the determinants of school choice, focusing on the role of information. Weconsider how parents' search efforts and their capacity to process information (i.e., tocorrectly assess schools) affect the quality of the schools they choose for their children. Usinga novel dataset, we are able to identify parents' awareness of schools in their neighborhoodand measure their capacity to rank the quality of the school with respect to the officialrankings. We find that parents education and wealth are important factors in determiningtheir level of school awareness and information gathering. Moreover, these search effortshave important consequences in terms of the quality of school choice.

Equivalence of piecewise-linear approximation and Lagrangian relaxation for network revenue management

The network revenue management (RM) problem arises in airline, hotel, media,and other industries where the sale products use multiple resources. It can be formulatedas a stochastic dynamic program but the dynamic program is computationallyintractable because of an exponentially large state space, and a number of heuristicshave been proposed to approximate it. Notable amongst these -both for their revenueperformance, as well as their theoretically sound basis- are approximate dynamic programmingmethods that approximate the value function by basis functions (both affinefunctions as well as piecewise-linear functions have been proposed for network RM)and decomposition methods that relax the constraints of the dynamic program to solvesimpler dynamic programs (such as the Lagrangian relaxation methods). In this paperwe show that these two seemingly distinct approaches coincide for the network RMdynamic program, i.e., the piecewise-linear approximation method and the Lagrangianrelaxation method are one and the same.

Current approaches and challenges for the metabolite profiling of complex natural extracts.

Metabolite profiling is critical in many aspects of the life sciences, particularly natural product research. Obtaining precise information on the chemical composition of complex natural extracts (metabolomes) that are primarily obtained from plants or microorganisms is a challenging task that requires sophisticated, advanced analytical methods. In this respect, significant advances in hyphenated chromatographic techniques (LC-MS, GC-MS and LC-NMR in particular), as well as data mining and processing methods, have occurred over the last decade. Together, these tools, in combination with bioassay profiling methods, serve an important role in metabolomics for the purposes of both peak annotation and dereplication in natural product research. In this review, a survey of the techniques that are used for generic and comprehensive profiling of secondary metabolites in natural extracts is provided. The various approaches (chromatographic methods: LC-MS, GC-MS, and LC-NMR and direct spectroscopic methods: NMR and DIMS) are discussed with respect to their resolution and sensitivity for extract profiling. In addition the structural information that can be generated through these techniques or in combination, is compared in relation to the identification of metabolites in complex mixtures. Analytical strategies with applications to natural extracts and novel methods that have strong potential, regardless of how often they are used, are discussed with respect to their potential applications and future trends.

Sex differences in the neurobiology of fear conditioning and extinction: a preliminary fMRI study of shared sex differences with stress-arousal circuitry.

BACKGROUND: The amygdala, hippocampus, medial prefrontal cortex (mPFC) and brain-stem subregions are implicated in fear conditioning and extinction, and are brain regions known to be sexually dimorphic. We used functional magnetic resonance imaging (fMRI) to investigate sex differences in brain activity in these regions during fear conditioning and extinction. METHODS: Subjects were 12 healthy men comparable to 12 healthy women who underwent a 2-day experiment in a 3 T MR scanner. Fear conditioning and extinction learning occurred on day 1 and extinction recall occurred on day 2. The conditioned stimuli were visual cues and the unconditioned stimulus was a mild electric shock. Skin conductance responses (SCR) were recorded throughout the experiment as an index of the conditioned response. fMRI data (blood-oxygen-level-dependent [BOLD] signal changes) were analyzed using SPM8. RESULTS: Findings showed no significant sex differences in SCR during any experimental phases. However, during fear conditioning, there were significantly greater BOLD-signal changes in the right amygdala, right rostral anterior cingulate (rACC) and dorsal anterior cingulate cortex (dACC) in women compared with men. In contrast, men showed significantly greater signal changes in bilateral rACC during extinction recall. CONCLUSIONS: These results indicate sex differences in brain activation within the fear circuitry of healthy subjects despite similar peripheral autonomic responses. Furthermore, we found that regions where sex differences were previously reported in response to stress, also exhibited sex differences during fear conditioning and extinction.

Asymptotic robust inferences in the analysis of mean and covariance structures

Structural equation models are widely used in economic, socialand behavioral studies to analyze linear interrelationships amongvariables, some of which may be unobservable or subject to measurementerror. Alternative estimation methods that exploit different distributionalassumptions are now available. The present paper deals with issues ofasymptotic statistical inferences, such as the evaluation of standarderrors of estimates and chi--square goodness--of--fit statistics,in the general context of mean and covariance structures. The emphasisis on drawing correct statistical inferences regardless of thedistribution of the data and the method of estimation employed. A(distribution--free) consistent estimate of $\Gamma$, the matrix ofasymptotic variances of the vector of sample second--order moments,will be used to compute robust standard errors and a robust chi--squaregoodness--of--fit squares. Simple modifications of the usual estimateof $\Gamma$ will also permit correct inferences in the case of multi--stage complex samples. We will also discuss the conditions under which,regardless of the distribution of the data, one can rely on the usual(non--robust) inferential statistics. Finally, a multivariate regressionmodel with errors--in--variables will be used to illustrate, by meansof simulated data, various theoretical aspects of the paper.

Recessions and babie's health

We study the effect of the business cycle on the health of newborn babies using 30 years of birth certificate data for Spain. Exploiting regional variation over time, we find that babies are born healthier when the local unemployment rate is high. Although fertility is lower during recessions, the effect on health is not the result of selection (healthier mothers being more likely to conceive when unemployment is high). We match multiple births to the same parents and find that the main result survives the inclusion of parents fixed-effects. We then explore a range of maternal behaviors as potential channels. Fertility-age women do not appear to engage in significantly healthier behaviors during recessions (in terms of exercise, nutrition, smoking and drinking). However, they are more likely to be out of work. Maternal employment during pregnancy is in turn negatively correlated with babies' health. We conclude that maternal employment is a plausible mediating channel.

Geometric and long run aspects of Granger causality

This paper extends multivariate Granger causality to take into account the subspacesalong which Granger causality occurs as well as long run Granger causality. The propertiesof these new notions of Granger causality, along with the requisite restrictions, are derivedand extensively studied for a wide variety of time series processes including linear invertibleprocess and VARMA. Using the proposed extensions, the paper demonstrates that: (i) meanreversion in L2 is an instance of long run Granger non-causality, (ii) cointegration is a specialcase of long run Granger non-causality along a subspace, (iii) controllability is a special caseof Granger causality, and finally (iv) linear rational expectations entail (possibly testable)Granger causality restriction along subspaces.

Scaled and adjusted restricted tests in multi-sample analysis of moment structures

We extend to score, Wald and difference test statistics the scaled and adjusted corrections to goodness-of-fit test statistics developed in Satorra and Bentler (1988a,b). The theory is framed in the general context of multisample analysis of moment structures, under general conditions on the distribution of observable variables. Computational issues, as well as the relation of the scaled and corrected statistics to the asymptotic robust ones, is discussed. A Monte Carlo study illustrates thecomparative performance in finite samples of corrected score test statistics.

The optimum quantity of money: Theory and evidence

In this paper we propose a simple and general model for computing the Ramsey optimal inflation tax, which includes several models from the previous literature as special cases. We show that it cannot be claimed that the Friedman rule is always optimal (or always non--optimal) on theoretical grounds. The Friedman rule is optimal or not, depending on conditions related to the shape of various relevant functions. One contribution of this paper is to relate these conditions to {\it measurable} variables such as the interest rate or the consumption elasticity of money demand. We find that it tends to be optimal to tax money when there are economies of scale in the demand for money (the scale elasticity is smaller than one) and/or when money is required for the payment of consumption or wage taxes. We find that it tends to be optimal to tax money more heavily when the interest elasticity of money demand is small. We present empirical evidence on the parameters that determine the optimal inflation tax. Calibrating the model to a variety of empirical studies yields a optimal nominal interest rate of less than 1\%/year, although that finding is sensitive to the calibration.

The persistence of abnormal returns at industry and firm levels

The present paper proposes a model for the persistence of abnormal returnsboth at firm and industry levels, when longitudinal data for the profitsof firms classiffied as industries are available. The model produces a two-way variance decomposition of abnormal returns: (a) at firm versus industrylevels, and (b) for permanent versus transitory components. This variancedecomposition supplies information on the relative importance of thefundamental components of abnormal returns that have been discussed in theliterature. The model is applied to a Spanish sample of firms, obtainingresults such as: (a) there are significant and permanent differences betweenprofit rates both at industry and firm levels; (b) variation of abnormal returnsat firm level is greater than at industry level; and (c) firm and industry levelsdo not differ significantly regarding rates of convergence of abnormal returns.

Price increase and stability with new entries in Cournot markets

It is widely accepted in the literature about the classicalCournot oligopoly model that the loss of quasi competitiveness is linked,in the long run as new firms enter the market, to instability of the equilibrium. In this paper, though, we present a model in which a stableunique symmetric equilibrium is reached for any number of oligopolistsas industry price increases with each new entry. Consequently, the suspicion that non quasi competitiveness implies, in the long run, instabilityis proved false.

On the impact of fundamentals, liquidity and coordination on market stability

We develop a coordination game to model interactions betweenfundamentals and liquidity during unstable periods in financial markets.We then propose a flexible econometric framework for estimationof the model and analysis of its quantitative implications. The specificempirical application is carry trades in the yen dollar market, includingthe turmoil of 1998. We find a generally very deep market, withlow information disparities amongst agents. We observe occasionallyepisodes of market fragility, or turmoil with up by the escalator, downby the elevator patterns in prices. The key role of strategic behaviorin the econometric model is also confirmed.

Performance assessment and league tables. Comparing like with like

We formulate performance assessment as a problem of causal analysis and outline an approach based on the missing data principle for its solution. It is particularly relevant in the context of so-called league tables for educational, health-care and other public-service institutions. The proposed solution avoids comparisons of institutions that have substantially different clientele (intake).

Value of sTREM-1, procalcitonin and CRP as laboratory parameters for postmortem diagnosis of sepsis.

OBJECTIVES: Triggering receptor expressed on myeloid cells-1 (TREM-1) was reported to be up-regulated in various inflammatory diseases as well as in bacterial sepsis. Increased cell-surface TREM-1 expression was also shown to result in marked plasma elevation of the soluble form of this molecule (sTREM-1) in patients with bacterial infections. In this study, we investigated sTREM-1, procalcitonin and C-reactive protein in postmortem serum in a series of sepsis-related fatalities and control individuals who underwent medico-legal investigations. sTREM-1 was also measured in pericardial fluid and urine. METHODS: Two study groups were prospectively formed, a sepsis-related fatalities group and a control group. The sepsis-related fatalities group consisted of sixteen forensic autopsy cases. Eight of these had a documented clinical diagnosis of sepsis in vivo. The control group consisted of sixteen forensic autopsy cases with various causes of death. RESULTS: Postmortem serum sTREM-1 concentrations were higher in the sepsis group with a mean value of 173.6 pg/ml in septic cases and 79.2 pg/ml in control individuals. The cutoff value of 90 pg/ml provided the best sensitivity and specificity. Pericardial fluid sTREM-1 values were higher in the septic group, with a mean value of 296.7 pg/ml in septic cases and 100.9 pg/ml in control individuals. The cutoff value of 135 pg/ml provided the best sensitivity and specificity. Mean urine sTREM-1 concentration was 102.9 pg/ml in septic cases and 89.3 pg/ml in control individuals. CONCLUSIONS: Postmortem serum sTREM-1, individually considered, did not provide better sensitivity and specificity than procalcitonin in detecting sepsis. However, simultaneous assessment of procalcitonin and sTREM-1 in postmortem serum can be of help in clarifying contradictory postmortem findings. sTREM-1 determination in pericardial fluid can be an alternative to postmortem serum in those situations in which biochemical analyses are required and blood collected during autopsy proves insufficient.