On the optimal level of public inputs.

This paper studies the optimal level of public inputs under two different tax settings. With this aim, we adapt the approach by Gronberg and Liu (2001) to the case of productivity-enhancing public spending. We find that it is not analytically clear whether the first-best level of public spending exceeds the second-best level. After taking account the type of public input, a wide numerical simulation has been carried out. We obtain that the second-best level is always below the first-best level but the criterion by Gronberg and Liu has to be qualified.Second best, excess burden, public input.

Optimization in non-standard problems. An application to the provision of public inputs

This paper describes a new method for solving non-standard constrained optimization problems for which standard methodologies do not work properly. Our method (the Rational Iterative Multisection -RIM- algorithm) consists of different stages that can be interpreted as different requirements of precision by obtaining the optimal solution. We have performed an application of RIM method to the case of public inputs provision. We prove that the RIM approach and comparable standard methodologies achieve the same results with regular optimization problems while the RIM algorithm takes advantage over them when facing non-standard optimization problems.direct search, constrained optimization, multisection, optimal taxation, public input.

How sensitive is the provision of public inputs to specifications?

This paper studies the sensitivity of provision of public inputs to changes in the specification of technology and consumer preferences. We consider a simple model in which the government, with recourse to three different tax settings (a lump-sum tax, a tax on labour and a tax on economic profit), provides firms with certain productive services. We focus on the numerical results coming from the government optimization problem. We look at several specific cases in which the returns to scale in the production function emerges as a critical issue. Our …findings also address the impact of changes in output elasticity, in consumer preferences and in the number of households on the levels of public input and utility.firm-augmenting public input, factor-augmenting public input, optimal provision

Savings in Transnational Households: A Field Experiment Among Migrants from El Salvador

While remittance flows to developing countries are very large, it is unknown whether migrants desire more control over how remittances are used. This research uses a randomized field experiment to investigate the importance of migrant control over the use of remittances. In partnership with a Salvadoran bank, we offered US-based migrants from El Salvador bank accounts in their home country into which they could send remittances. We randomly varied migrant control over El Salvador-based savings by offering different types of accounts across treatment groups. Migrants offered the greatest degree of control over savings accumulated the most savings at the partner bank, compared to others offered less or no control over savings. Effects of this treatment on savings are concentrated among migrants who expressed demand for control over remittances in the baseline survey. We also find positive spillovers of our savings intervention in the form of increased savings at other banks (specifically, banks in the U.S.). We interpret the effects we find as arising from the joint effect of the bank account offers and the marketing pitch made to study participants by our project staff

A Bayesian Joinpoint regression model with an unknown number of break-points

Joinpoint regression is used to determine the number of segments needed to adequately explain the relationship between two variables. This methodology can be widely applied to real problems, but we focus on epidemiological data, the main goal being to uncover changes in the mortality time trend of a specific disease under study. Traditionally, Joinpoint regression problems have paid little or no attention to the quantification of uncertainty in the estimation of the number of change-points. In this context, we found a satisfactory way to handle the problem in the Bayesian methodology. Nevertheless, this novel approach involves significant difficulties (both theoretical and practical) since it implicitly entails a model selection (or testing) problem. In this study we face these challenges through (i) a novel reparameterization of the model, (ii) a conscientious definition of the prior distributions used and (iii) an encompassing approach which allows the use of MCMC simulation-based techniques to derive the results. The resulting methodology is flexible enough to make it possible to consider mortality counts (for epidemiological applications) as Poisson variables. The methodology is applied to the study of annual breast cancer mortality during the period 1980--2007 in Castell\'{o}n, a province in Spain.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS471 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Filtering techniques for the detection of Sunyaev-Zel'dovich clusters in multifrequency CMB maps

The problem of detecting Sunyaev-Zel'dovich (SZ) clusters in multifrequency CMB observations is investigated using a number of filtering techniques. A multifilter approach is introduced, which optimizes the detection of SZ clusters on microwave maps. An alternative method is also investigated, in which maps at different frequencies are combined in an optimal manner so that existing filtering techniques can be applied to the single combined map. The SZ profiles are approximated by the circularly-symmetric template $\tau (x) = [1 +(x/r_c)^2]^{-\lambda}$, with $\lambda \simeq \tfrac{1}{2}$ and $x\equiv |\vec{x}|$, where the core radius $r_c$ and the overall amplitude of the effect are not fixed a priori, but are determined from the data. The background emission is modelled by a homogeneous and isotropic random field, characterized by a cross-power spectrum $P_{\nu_1 \nu_2}(q)$ with $q\equiv |\vec{q}|$. The filtering methods are illustrated by application to simulated Planck observations of a $12.8^\circ \times 12.8^\circ$ patch of sky in 10 frequency channels. Our simulations suggest that the Planck instrument should detect $\approx 10000$ SZ clusters in 2/3 of the sky. Moreover, we find the catalogue to be complete for fluxes $S > 170$ mJy at 300 GHz.Comment: 12 pages, 7 figures; Corrected figures. Submitted to MNRA

Parsimonious Argument Annotations for Hate Speech Counter-narratives

We present an enrichment of the Hateval corpus of hate speech tweets (Basile et. al 2019) aimed to facilitate automated counter-narrative generation. Comparably to previous work (Chung et. al. 2019), manually written counter-narratives are associated to tweets. However, this information alone seems insufficient to obtain satisfactory language models for counter-narrative generation. That is why we have also annotated tweets with argumentative information based on Wagemanns (2016), that we believe can help in building convincing and effective counter-narratives for hate speech against particular groups. We discuss adequacies and difficulties of this annotation process and present several baselines for automatic detection of the annotated elements. Preliminary results show that automatic annotators perform close to human annotators to detect some aspects of argumentation, while others only reach low or moderate level of inter-annotator agreement