Dynamic Panel Probit Models for Current Account Reversals and their Efficient Estimation

We use panel probit models with unobserved heterogeneity and serially correlated errors in order to analyze the determinants and the dynamics of current-account reversals for a panel of developing and emerging countries. The likelihood evaluation of these models requires high-dimensional integration for which we use a generic procedure known as Efficient Importance Sampling (EIS). Our empirical results suggest that current account balance, terms of trades, foreign reserves and concessional debt are important determinants of the probability of current-account reversal. Furthermore we find under all specifications evidence for serially correlated error components and weak evidence for state dependence. --Panel data,Dynamic discrete choice,Current account reversals,Importance Sampling,Monte Carlo integration,State dependence

Determinants and dynamics of current account reversals: an empirical analysis

We use panel probit models with unobserved heterogeneity, state-dependence and serially correlated errors in order to analyze the determinants and the dynamics of current-account reversals for a panel of developing and emerging countries. The likelihood-based inference of these models requires high-dimensional integration for which we use Efficient Importance Sampling (EIS). Our results suggest that current account balance, terms of trades, foreign reserves and concessional debt are important determinants of current-account reversal. Furthermore, we find strong evidence for serial dependence in the occurrence of reversals. While the likelihood criterion suggest that state-dependence and serially correlated errors are essentially observationally equivalent, measures of predictive performance provide support for the hypothesis that the serial dependence is mainly due to serially correlated country-specific shocks related to local political or macroeconomic events. --Panel data,dynamic discrete choice,importance sampling,Monte Carlo integration,state dependence,spillover effects

Efficient Yield Curve Estimation and Forecasting in Brazil

Term Structure of the Interest Rate, Yield Curve, State-Space Model, Kalman Filter.

The Phillips curve and information rigidity in Brazil

This work aims at testing the null hypothesis of no sticky information against the alternative of sticky information using Brazilian data. The rejection of the null hypothesis allows us to derive the expected time between information updates. The median of market participants' predictions collected by Gerin/Bacen is used as a proxy to firms' expectation contained in the sticky information version of the Phillips curve. Our estimates imply that inflation expectations in Brazil are updated about once each five quarters, which in part can be attributed to reduced uncertainty about Brazilian inflation in the period of analysis.O objetivo deste trabalho é testar a hipótese de ausência de rigidez de informação no Brasil. A metodologia permite também derivar a frequência de reajuste informacional via Curva de Phillips sob Rigidez de Informação. Para tanto, a mediana das projeções de mercado divulgadas pela Gerin/Bacen são utilizadas como proxy para as expectativas contidas na curva de Phillips. As estimativas obtidas são consistentes com o modelo e implicam em atualização de informação a cada cinco trimestres. Portanto, o período de atualização de informações estimado para o Brasil é próximo de alguns estimados para países europeus e norte americanos, o que em parte pode ser atribuído à redução nas incertezas inflacionárias brasileiras no período de análise

Efficient likelihood evaluation of state-space representations

We develop a numerical procedure that facilitates efficient likelihood evaluation in applications involving non-linear and non-Gaussian state-space models. The procedure approximates necessary integrals using continuous approximations of target densities. Construction is achieved via efficient importance sampling, and approximating densities are adapted to fully incorporate current information. We illustrate our procedure in applications to dynamic stochastic general equilibrium models. --particle filter,adaption,efficient importance sampling,kernel density approximation,dynamic stochastic general equilibrium model

Comparing Forecasts of Extremely Large Conditional Covariance Matrices

Modelling and forecasting high dimensional covariance matrices is a key challenge in data-richenvironments involving even thousands of time series since most of the available models sufferfrom the curse of dimensionality. In this paper, we challenge some popular multivariate GARCH(MGARCH) and Stochastic Volatility (MSV) models by fitting them to forecast the conditionalcovariance matrices of financial portfolios with dimension up to 1000 assets observed daily over a30-year time span. The time evolution of the conditional variances and covariances estimated bythe different models is compared and evaluated in the context of a portfolio selection exercise. Weconclude that, in a realistic context in which transaction costs are taken into account, modelling thecovariance matrices as latent Wishart processes delivers more stable optimal portfolio compositionsand, consequently, higher Sharpe ratios.Guilherme V. Moura is supported by the Brazilian Government through grants number 424942- 2016-0 (CNPQ) and 302865-2016-0 (CNPQ). André A.P. Santos is supported by the Brazilian Government through grants number 303688-2016-5 (CNPQ) and 420038-2018-3 (CNPQ). Esther Ruiz is supported by the Spanish Government through grant number ECO2015-70331-C2-2-R (MINECO/FEDER)

Topological speckles

The time evolution of a topological Su-Schrieffer-Heeger chain is analyzed through the statistics of speckle patterns. The emergence of topological edge states dramatically affects the dynamical fluctuations of the wavefunction. The intensity statistics is found to be described by a family of noncentral chi-squared distributions, with the noncentrality parameter reflecting on the degree of edge-state localization. The response of the speckle contrast with respect to the dimerization of the chain is explored in detail as well as the role of chiral symmetry-breaking disorder, number of edge states, their energy gap, and the locations between which the transport occurs. In addition to providing a venue for speckle customization, our results appeal to the use of speckle patterns for characterization of nontrivial topological properties.Comment: 6 pages, 4 figure

Long-term effects of competition and environmental drivers on the growth of the endangered coral Mussismilia braziliensis (Verril, 1867)

Most coral reefs have recently experienced acute changes in benthic community structure, generally involving dominance shifts from slow-growing hard corals to fast-growing benthic invertebrates and fleshy photosynthesizers. Besides overfishing, increased nutrification and sedimentation are important drivers of this process, which is well documented at landscape scales in the Caribbean and in the Indo-Pacific. However, small-scale processes that occur at the level of individual organisms remain poorly explored. In addition, the generality of coral reef decline models still needs to be verified on the vast realm of turbid-zone reefs. Here, we documented the outcome of interactions between an endangered Brazilian-endemic coral (Mussismilia braziliensis) and its most abundant contacting organisms (turf, cyanobacteria, corals, crustose coralline algae and foliose macroalgae). Our study was based on a long (2006–2016) series of high resolution data (fixed photoquadrats) acquired along a cross-shelf gradient that includes coastal unprotected reefs and offshore protected sites. The study region (Abrolhos Bank) comprises the largest and richest coralline complex in the South Atlantic, and a foremost example of a turbid-zone reef system with low diversity and expressive coral cover. Coral growth was significantly different between reefs. Coral-algae contacts predominated inshore, while cyanobacteria and turf contacts dominated offshore. An overall trend in positive coral growth was detected from 2009 onward in the inshore reef, whereas retraction in live coral tissue was observed offshore during this period. Turbidity (+) and cyanobacteria (−) were the best predictors of coral growth. Complimentary incubation experiments, in which treatments of Symbiodinium spp. from M. braziliensis colonies were subjected to cyanobacterial exudates, showed a negative effect of the exudate on the symbionts, demonstrating that cyanobacteria play an important role in coral tissue necrosis. Negative effects of cyanobacteria on living coral tissue may remain undetected from percent cover estimates gathered at larger spatial scales, as these ephemeral organisms tend to be rapidly replaced by longer-living macroalgae, or complex turf-like consortia. The cross-shelf trend of decreasing turbidity and macroalgae abundance suggests either a direct positive effect of turbidity on coral growth, or an indirect effect related to the higher inshore cover of foliose macroalgae, constraining cyanobacterial abundance. It is unclear whether the higher inshore macroalgal abundance (10–20% of reef cover) is a stable phase related to a long-standing high turbidity background, or a contemporary response to anthropogenic stress. Our results challenge the idea that high macroalgal cover is always associated with compromised coral health, as the baselines for turbid zone reefs may derive sharply from those of coral-dominated reefs that dwell under oligotrophic conditions