Search results for "Econometria"

showing 10 items of 61 documents

Estimation of ordered response models with sample selection

2011

We introduce two new Stata commands for the estimation of an ordered response model with sample selection. The opsel command uses a standard maximum-likelihood approach to fit a parametric specification of the model where errors are assumed to follow a bivariate Gaussian distribution. The snpopsel command uses the semi-nonparametric approach of Gallant and Nychka (1987, Econometrica 55: 363–390) to fit a semiparametric specification of the model where the bivariate density function of the errors is approximated by a Hermite polynomial expansion. The snpopsel command extends the set of Stata routines for semi-nonparametric estimation of discrete response models. Compared to the other semi-n…

EstimationSample selectionHermite polynomialsResponse modelComputer scienceEstimatorSettore SECS-P/05 - EconometriaProbability density functionBivariate analysisst0226 opsel opsel postestimation sneop sneop postestimation snp2 snp2 postestimation snp2s snp2s postestimation snpopsel snpopsel postestimation snp snp postestimation ordered response models sample selection parametric maximum-likelihood estimation semi-nonparametric estimationSet (abstract data type)Mathematics (miscellaneous)StatisticsSettore SECS-P/01 - Economia PoliticaAlgorithmMathematicsParametric statistics
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Volatility risk premia and financial connectedness

2014

In this paper we use the Diebold Yilmaz (2009 and 2012) methodology to construct an index of connectedness among five European stock markets: France, Germany, UK, Switzerland and the Netherlands, by using volatility risk premia. The volatility risk premium, which is a proxy of risk aversion, is measured by the difference between the implied volatility and expected realized volatility of the stock market for next month. While Diebold and Yilmaz focus is on the forecast error variance decomposition of stock returns or range based volatilities employing a stationary VAR in levels, we account for the (locally) long memory stationary properties of the levels of volatility risk premia series. The…

FIVARvolatility risk premium long memory FIVAR financial connectednessvolatility risk premiumfinancial connectednessSettore SECS-P/05 - Econometrialong memory
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Financial connectedness among European volatility risk premia

2015

In this paper we use the Diebold Yilmaz (2009 and 2012) methodology to estimate the contribution and the vulnerability to systemic risk of volatility risk premia for five European stock markets: France, Germany, UK, Switzerland and the Netherlands. The volatility risk premium, which is a proxy of risk aversion, is measured by the difference between the implied volatility and expected realized volatility of the stock market for next month. While Diebold and Yilmaz focus is on the forecast error variance decomposition of stock returns or range based volatilities employing a stationary VAR in levels, we account for the (locally) long memory stationary properties of the levels of volatility ris…

FIVARvolatility risk premium long memory FIVAR financial connectednessvolatility risk premiumfinancial connectednesslong memorySettore SECS-P/05 - Econometria
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An index of financial connectedness applied to variance risk premia

2014

The purpose is to construct an index of financial connectedness among France, Germany, UK, Switzerland and the Netherlands variance risk premia. The variance risk premium of each country stock market is measured by the difference between the (square) of implied volatility and expected realized variance of the stock market for next month. The total and directional indices of financial connectedness are obtained from the forecast error variance decomposition of a Vector Autoregressive Model, VAR, as recently suggested by Diebold and Yilmaz. While the authors main focus is on connectedness among financial returns, they base their analysis on a short memory stationary VAR. Given the long memory…

FIVARvolatility risk premiumfinancial connectednesslong memorySettore SECS-P/05 - Econometria
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Adaptive independent sticky MCMC algorithms

2018

In this work, we introduce a novel class of adaptive Monte Carlo methods, called adaptive independent sticky MCMC algorithms, for efficient sampling from a generic target probability density function (pdf). The new class of algorithms employs adaptive non-parametric proposal densities which become closer and closer to the target as the number of iterations increases. The proposal pdf is built using interpolation procedures based on a set of support points which is constructed iteratively based on previously drawn samples. The algorithm's efficiency is ensured by a test that controls the evolution of the set of support points. This extra stage controls the computational cost and the converge…

FOS: Computer and information sciencesMathematical optimizationAdaptive Markov chain Monte Carlo (MCMC)Monte Carlo methodBayesian inferenceHASettore SECS-P/05 - Econometrialcsh:TK7800-8360Machine Learning (stat.ML)02 engineering and technologyBayesian inference01 natural sciencesStatistics - Computationlcsh:Telecommunication010104 statistics & probabilitysymbols.namesakeAdaptive Markov chain Monte Carlo (MCMC); Adaptive rejection Metropolis sampling (ARMS); Bayesian inference; Gibbs sampling; Hit and run algorithm; Metropolis-within-Gibbs; Monte Carlo methods; Signal Processing; Hardware and Architecture; Electrical and Electronic EngineeringGibbs samplingStatistics - Machine Learninglcsh:TK5101-67200202 electrical engineering electronic engineering information engineeringComputational statisticsMetropolis-within-GibbsHit and run algorithm0101 mathematicsElectrical and Electronic EngineeringGaussian processComputation (stat.CO)MathematicsSignal processinglcsh:Electronics020206 networking & telecommunicationsMarkov chain Monte CarloMonte Carlo methodsHardware and ArchitectureSignal ProcessingSettore SECS-S/03 - Statistica EconomicasymbolsSettore SECS-S/01 - StatisticaStatistical signal processingGibbs samplingAdaptive rejection Metropolis sampling (ARMS)EURASIP Journal on Advances in Signal Processing
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Model averaging estimation of generalized linear models with imputed covariates

2015

a b s t r a c t We address the problem of estimating generalized linear models when some covariate values are missing but imputations are available to fill-in the missing values. This situation generates a bias-precision trade- off in the estimation of the model parameters. Extending the generalized missing-indicator method proposed by Dardanoni et al. (2011) for linear regression, we handle this trade-off as a problem of model uncertainty using Bayesian averaging of classical maximum likelihood estimators (BAML). We also propose a block model averaging strategy that incorporates information on the missing-data patterns and is computationally simple. An empirical application illustrates our…

Generalized linear modelEconomics and EconometricsApplied MathematicsSettore SECS-P/05 - EconometriaEstimatorMissing dataGeneralized linear mixed modelModel averaging Bayesian averaging of maximum likelihood destimators Generalized linear models Missing covariates Generalized missing-indicator method shareHierarchical generalized linear modelStatisticsLinear regressionCovariateApplied mathematicsGeneralized estimating equationMathematics
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Weighted-average least squares estimation of generalized linear models

2018

The weighted-average least squares (WALS) approach, introduced by Magnus et al. (2010) in the context of Gaussian linear models, has been shown to enjoy important advantages over other strictly Bayesian and strictly frequentist model averaging estimators when accounting for problems of uncertainty in the choice of the regressors. In this paper we extend the WALS approach to deal with uncertainty about the specification of the linear predictor in the wider class of generalized linear models (GLMs). We study the large-sample properties of the WALS estimator for GLMs under a local misspecification framework that allows the development of asymptotic model averaging theory. We also investigate t…

Generalized linear modelEconomics and EconometricsGeneralized linear modelsBayesian probabilityGeneralized linear modelSettore SECS-P/05 - EconometriaLinear predictionContext (language use)01 natural sciencesLeast squares010104 statistics & probabilityWALS; Model averaging; Generalized linear models; Monte Carlo; AttritionFrequentist inference0502 economics and businessAttritionEconometricsApplied mathematicsStatistics::Methodology0101 mathematicsMonte Carlo050205 econometrics MathematicsWALSApplied Mathematics05 social sciencesLinear modelEstimatorModel averaging
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Testing for Contagion: a Time-Scale Decomposition

2010

The aim of the paper is to test for financial contagion by estimating a simultaneous equation model subject to structural breaks. For this purpose, we use the Maximum Overlapping Discrete Wavelet Transform, MODWT, to decompose four asset returns into different scale components (each associated with a given frequency range). The decomposition will enable us to obtain the moment conditions necessary to (over)identify a structural form model with a single dummy and the one with multiple dummies capturing shifts in the co-movement of asset returns occurring during periods of financial turmoil. A Montecarlo simulation exercise shows that test based on a single dummy structural form model has goo…

Identification Wavelets Financial Contagion .Settore SECS-P/05 - Econometria
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A wavelet analysis of US fiscal sustainability

2015

Abstract In this paper, we reassess the relationship between primary deficit and lagged debt to GDP ratio (Bohn, 1998), to test for US debt sustainability over the period 1795–2012. Our analysis is rooted in the wavelet domain enabling the detection of interesting patterns and otherwise hidden information. We find evidence of long term fiscal sustainability but only up until 1995 and also we show that governments tend to respond more vigorously to budget deficits when the level of debt is high rather than low.

MacroeconomicsEconomics and EconometricsWavelet coherencemedia_common.quotation_subjecteducationDebt-to-GDP ratioPrimary deficitSettore SECS-P/05 - EconometriahumanitiesTerm (time)WaveletDebtSustainabilityEconomicsWavelet coherence Public debt sustainability Time–frequency decompositionFiscal sustainabilityhealth care economics and organizationsmedia_common
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Can an unglamorous non-event affect prices? The role of newspapers

2016

AbstractOur paper offers evidence that the print media can affect stock prices by covering public information. After price-to-book value figures of Italian listed shares were first published on the major national financial newspaper, the prices of value stocks did, on average, show a positive reaction. The price reaction was limited to small caps stocks and disappeared within three weeks. Over the period of analysis, we could not find any abnormal behaviour of the returns of small and value stocks on other European markets. These findings support the view that newspapers play a role in disseminating information to small investors and grabbing their attention, even if news are continuously r…

Macroeconomicsevent studieEconomics and EconometricsMarket efficiencyPositive reactionSettore SECS-P/05 - EconometriainattentionMonetary economicsmedi and and financial marketNewspaperlcsh:Financelcsh:HG1-99990502 economics and businessddc:330EconomicsC58050207 economicsmedia and financial marketsStock (geology)Public informationMedia and financial market050208 financeG14Print medialcsh:Economic theory. Demographymarket efficiency05 social sciencesMarket efficiencyEvent studymarket efficiency; inattention; media and financial markets; event studies; wild boostraplcsh:HB1-3840Price reactionInattentionwild boostrapevent studiesFinanceCogent Economics & Finance
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