On the design of education conditional cash transfer programs and non education outcomes: the case of teenage pregnancy

We investigate the effect of education Conditional Cash Transfer programs (CCTs) on teenage pregnancy. Our main concern is with how the size and sign of the effect may depend on the design of the program. Using a simple model we show that an education CCT that conditions renewal on school performance reduces teenage pregnancy; the program can increase teenage pregnancy if it does not condition on school performance. Then, using an original data base, we estimate the causal impact on teenage pregnancy of two education CCTs implemented in Bogot´a (Subsidio Educativo, SE, and Familias en Acci´on, FA); both programs differ particularly on whether school success is a condition for renewal or not. We show that SE has negative average effect on teenage pregnancy while FA has a null average effect. We also find that SE has either null or no effect for adolescents in all age and grade groups while FA has positive, null or negative effects for adolescents in different age and grade groups. Since SE conditions renewal on school success and FA does not, we can argue that the empirical results are consistent with the predictions of our model and that conditioning renewal of the subsidy on school success crucially determines the effect of the subsidy on teenage pregnancy

Dynamic conditional correlation in Latin-American asset markets

In this paper we reviewed the models of volatility for a group of five Latin American countries, mainly motivated by the recent periods of financial turbulence. Our results based on high frequency data suggest that Dynamic multivariate models are more powerful to study the volatilities of asset returns than Constant Conditional Correlation models. For the group of countries included, we identified that domestic volatilities of asset markets have been increasing; but the co-volatility of the region is still moderate.

Multiple perspectives on the concept of conditional probability. 'Perspectivas múltiples sobre el concepto del probabilidad condicional'

Resumen en portugués, español y francés. Resumen basado en el de la publicación

The influence of verbal mood in exceptive conditional reasoning : indicative versus subjunctive

Resumen tomado de la publicaci??n

Mesoclitic Romance futures and conditionals vs participle preposing

(INFINITIVE + CLITIC + AUX) is an evidential configuration in Old Spanish and Old Catalan, whereas (PARTICIPLE + CLITIC + AUX) is an instance of weak or unmarked focus fronting. The evidentiality of mesoclitic structures can be put forward on the bases of three main arguments: a) mesoclisis is not compulsory (i.e., whenever you have a clitic, you can either have mesoclisis or proclisis/enclisis); b) mesoclitic futures and conditionals are attested in interrogative sentences (with wh- elements); and c) they are not found in derived adverbial clauses (which is what you expect if they have an evidential value, since they bring about intervention effects corresponding to the derivational account of conditional and temporal sentences, for example - see Haegeman 2007 and ff.), and are related to high modal expressions (thus interfering with MoodPIrrealis)

The representation of conditional expectations of non-Gaussian noise

For Wiener spaces conditional expectations and $L^{2}$-martingales w.r.t. the natural filtration have a natural representation in terms of chaos expansion. In this note an extension to larger classes of processes is discussed. In particular, it is pointed out that orthogonality of the chaos expansion is not required.

Training conditional and cumulative risk judgements: the role of frequencies, problem-structure and Einstellung

Two experiments implement and evaluate a training scheme for learning to apply frequency formats to probability judgements couched in terms of percentages. Results indicate that both conditional and cumulative probability judgements can be improved in this manner, however the scheme is insufficient to promote any deeper understanding of the problem structure. In both experiments, training on one problem type only (either conditional or cumulative risk judgements) resulted in an inappropriate transfer of a learned method at test. The obstacles facing a frequency-based training programme for teaching appropriate use of probability data are discussed. Copyright (c) 2006 John Wiley & Sons, Ltd.

Autoregressive conditional kurtosis

This article proposes a new model for autoregressive conditional heteroscedasticity and kurtosis. Via a time-varying degrees of freedom parameter, the conditional variance and conditional kurtosis are permitted to evolve separately. The model uses only the standard Student’s t-density and consequently can be estimated simply using maximum likelihood. The method is applied to a set of four daily financial asset return series comprising U.S. and U.K. stocks and bonds, and significant evidence in favor of the presence of autoregressive conditional kurtosis is observed. Various extensions to the basic model are proposed, and we show that the response of kurtosis to good and bad news is not significantly asymmetric.

Conditional symmetric instability in sting-jet storms

Sting jets are transient mesoscale jets of air that descend from the tip of the cloud head towards the top of the boundary layer in severe extratropical cyclones and can lead to damaging surface wind gusts. This recently identified jet is distinct from the well-documented jets associated with the cold and warm conveyor belts. One mechanism proposed for their development is the release of conditional symmetric instability (CSI). Here the spatial distribution and temporal evolution of several CSI diagnostics in four severe storms are analysed. A sting jet has been identified in three of these storms; for comparison, we also analysed one storm that did not have a sting jet, even though it hadmany of the apparent features of sting-jet storms. The sting-jet storms are distinct from the non-sting-jet storms by having much greater andmore extensive conditional instability (CI) and CSI. CSI is released by ascending air parcels in the cloud head in two of the sting-jet storms and by descending air parcels in the other sting-jet storm. By contrast, only weak CI to ascending air parcels is present at the cloud-head tip in the non-sting-jet storm. CSI released by descending air parcels, as diagnosed by decaying downdraught slantwise convective available potential energy (DSCAPE), is collocated with the sting jets in all three sting-jet storms and has a localisedmaximum in two of them. Consistent evolutions of saturated moist potential vorticity are found.We conclude that CSI release has a role in the generation of the sting jet, that the sting jet may be driven by the release of instability to both ascending and descending parcels, and that DSCAPE could be used as a discriminating diagnostic for the sting jet based on these four case-studies.

Selecting from amongst non–nested conditional variance models: information criteria and portfolio determination

We consider the finite sample properties of model selection by information criteria in conditionally heteroscedastic models. Recent theoretical results show that certain popular criteria are consistent in that they will select the true model asymptotically with probability 1. To examine the empirical relevance of this property, Monte Carlo simulations are conducted for a set of non–nested data generating processes (DGPs) with the set of candidate models consisting of all types of model used as DGPs. In addition, not only is the best model considered but also those with similar values of the information criterion, called close competitors, thus forming a portfolio of eligible models. To supplement the simulations, the criteria are applied to a set of economic and financial series. In the simulations, the criteria are largely ineffective at identifying the correct model, either as best or a close competitor, the parsimonious GARCH(1, 1) model being preferred for most DGPs. In contrast, asymmetric models are generally selected to represent actual data. This leads to the conjecture that the properties of parameterizations of processes commonly used to model heteroscedastic data are more similar than may be imagined and that more attention needs to be paid to the behaviour of the standardized disturbances of such models, both in simulation exercises and in empirical modelling.