THE METHOD OF SIMULATED MAXIMUM LIKELIHOOD FOR THE ESTIMATON OF DYNAMIC ORDERED PROBIT: AN APPLICATION TO COUNTRY-RISK FOR NON-DEVELOPED COUNTRIES

This paper aims to give a detailed explanation of the econometric methodology necessary to estimate dynamic probit models with ordinal dependent variables. A typology of cases are established which appear when considering different choices of individual heterogeneity along with time correlation. To be able to estimate by maximum likelihood the models which come out of the different alternatives proposed, simulation techniques are used and put into practice by the GHK simulator and, in this way, estimators by simulated maximum likelihood are obtained. Finally, all the models described are used to measure and determine the macroeconomic factors which explain the ratings of country-risk in non-developed countries.Country risk, panel data, external debt, dynamic ordered probit

How cyclical do cyclically-adjusted balances remain? An EU study

Observed budget balances are an imperfect indicator of the fiscal policy stance, because fluctuations in economic activity induce automatic changes in the balance, hence the use of cyclically-adjusted balances (CAB). However, this paper shows that CABs (as measured through one of the two methods currently used by the Commission) tend to be systematically overestimated during downturns and underestimated during expansions. The dominant source of this distortion arises from the filtering of revenues deemed to be cyclical, possibly signalling a problem with the computation of elasticities. The effect of the items which are assumed not to move with the cycle is non significant, but this overall result conceals offseting effects: public investment turns to be significantly procyclical and interest payments and transfers to firms are countercyclical.Structural balances, output gap

Evaluating uncertainty in climate change impacts on crop productivity in the Iberian Peninsula

Using a multi-model ensemble of climate-change impacts over the Iberian Peninsula, we identified regions and cropping options for which the uncertainty levels of projected impacts on crop productivity were either high or low. The ensemble consisted of 10 members per combination of scenario, climate model, location and cropping option, and was used to quantify the uncertainty of impacts on crop yield. CERES wheat and maize simulation models were linked to the control run and 1 scenario provided by 10 regional climate models (RCMs): control (1969–1990) and A2 future (2070–2100) climate. The contribution of RCMs, locations and cropping options to uncertainty on yield projections was analysed. Differences between the sign of the response and 30 yr time series of projections generated by each member of the ensemble were compared. The largest response to A2 scenarios also resulted in the smallest uncertainty, and vice versa. Low uncertainty was found for the sign of the yield response, which was mainly positive for spring and winter cropping options and negative for the summer option. Uncertainty was lower for A2 than for control projections. Uncertainty was largest in northern, coastal and mountain regions, and smallest for inland southern regions, and depended on seasonal cropping options. Minimum and maximum uncertainty were found for maize and irrigated spring wheat, respectively. Water availability was the determinant for interannual variability and its uncertainty. Choice of RCM contributed less to uncertainty than choice of location, and choice of cropping option contributed more to uncertainty than both of these factors. Interannual variability showed larger uncertainty than mean impact magnitude, and this uncertainty was larger than that of the sign of the yield response. Regions with high uncertainty could benefit from higher-resolution simulations

Reply to: ''Network-based discovery of gene signature for vascular invasion prediction in HCC''

To the Editor:Liu and colleagues raise some issues regarding our recently pub-lished study [1] to which we would like to make the followingcomments. We acknowledge the limitations that a gene-expres-sion-based biomarker could have, and that our signature is notunique. Certainly, previous attempts to find such a signature havebeen published in the past [2]. We also know that, as in othergene expression studies, potential bias could occur. In fact,reported prognostic signatures are often not reproducible, inmost of the cases due to suboptimal study design, small samplesizes, and also because many of them have been based on retro-spectively collected tissue samples [3]. Even after taking intoaccount these sources of bias or inconsistencies, it so happensthat only a small minority of the reported signatures truly retainprognostic significance. In fact, our recent outcome analysisincluding 22 gene signatures with prognostic significance inHCC (18 from the tumor, and four from the non-tumoral adjacenttissue) showed that only two signatures retained independentprognostic value [4].In our work, we select a training cohort based upon a homo-geneous etiology to minimize the risk of molecular heterogene-ity and to identify a clean and distinct signature. Patients withHCV-related HCC were selected, since this is the most commonetiology in the Western countries. Then, we validate the signa-ture in an independent multi-etiologic cohort of patients andthe accuracy remained stable when an etiology-dependent sub-group analysis was performed [1]. The study was aimed at pro-viding a gene-set to ease the preoperative diagnosis of vascularinvasion, but was not designed for defining outcome prediction.Nonetheless, we have data indicating that the presence of a vas-cular invasion signature correlates with poor outcome, since thesignature was found to be associated with early recurrence(p = 0.057), and was enriched in patients sharing signatures ofpoor prognosis [4].Even considering that the question posed is simple (to identifya gene-signature capturing vascular invasion) the characteristicsof patients, sample collection, sampling issues, technical varia-tion, validation of results, and bioinformatics approaches are cer-tainly heterogeneous, and thus the results might vary. In mostinstances, however, the different signatures seem to be able tocapture common oncogenic mechanisms, as reflected by theircapacity to adequately allocate patients into a poor or good prog-nosis group [5]. By applying a different methodological approach(weighted gene co-expression network analysis) to our data, Liuet al. provide a 9-gene signature with similar accuracy and nooverlap with our 35-gene signature. The method applied is basedon systems biology to find clusters of highly correlated genesacross microarray samples, identify hubs of each module and cor-relate them with clinical traits [6]. This analysis is based on thehypothesis that information on signaling pathways is crucial tounderstand how genes are connected to each other and how theyinfluence cellular functions in both normal and cancer conditions.This result further underlines the need for integrating the vastamount of available data and the development of powerful bioin-formatics resources (annotation, methodologies, technical plat-forms, etc.).A more relevant question is when can our signature-alone orin combination with tumor size- be translated into clinical prac-tice. Strict rules have been proposed recently by Simon and col-leagues [7]. Following this proposal, the EASL-EORTC guidelineson management of HCC have outlined a list of requirements inorder to adopt molecular signatures in the clinical practice [8],which are as follows:1. First, the signature should be generated in the setting of ran-domized studies or in case of cohort studies, it should followthe training/validation approach.2. The signature should retain independent prognostic valuewhen tested along known clinico-pathological variables.3. The results should be confirmed by independent investigatorsin a separate set of samples.Thus, according to these rules, in order to implement our sig-nature in the decision-making process, for instance in the waitinglist of liver transplantation, it should be validated by independentinvestigators in a novel set of samples. Ideally, the signature hasto be reproduced in a device, which should give similar results.Only then, data is ready for acceptance in guidelines. It is a longpath, but the only one for translation of genomic results into ourpractice.Conflict of interestThe authors declared that they do not have anything to discloseregarding funding or conflict of interest with respect to thismanuscript.Reference

Switching of Magnetic Moments of Nanoparticles by Surface Acoustic Waves

We report evidence of the magnetization reversal in nanoparticles by surface acoustic waves (SAWs). The experimental system consists of isolated magnetite nanoparticles dispersed on a piezoelectric substrate. Magnetic relaxation from a saturated state becomes significantly enhanced in the presence of the SAW at a constant temperature of the substrate. The dependence of the relaxation on SAW power and frequency has been investigated. The effect is explained by the effective ac magnetic field generated by the SAW in the nanoparticles.Comment: Accepted in Europhysics Letter

Tuning Magnetic Avalanches in Mn12-ac

Using micron-sized Hall sensor arrays to obtain time-resolved measurements of the local magnetization, we report a systematic study in the molecular magnet Mn$_{12}$-acetate of magnetic avalanches controllably triggered in different fixed external magnetic fields and for different values of the initial magnetization. The speeds of propagation of the spin-reversal fronts are in good overall agreement with the theory of magnetic deflagration of Garanin and Chudnovsky \cite{Garanin}.Comment: 8 pages, 7 figures; discussion expanded and revise